Patent Application
20120015841
The invention relates to novel cells and cell lines, and methods for making and using them. In particular embodiments, the invention relates to cells and cell lines stably expressing complex targets. The invention further provides methods of making such cells and cell lines. The cells and cell lines provided herein are useful in identifying modulators of such complex targets.
Currently, the industry average failure rate for drug discovery programs in pharmaceutical companies is reported to be approximately 98%. Although this includes failures at all stages of the process, the high failure rate points to a dire need for any improvements in the efficiency of the process.
One factor contributing to the high failure rate is the lack of cell lines expressing therapeutic targets for used in cell-based functional assays during drug discovery. Indisputably, research using cell-based assays, especially drug discovery research, would benefit from cells and cell lines for use in cell-based assays.
Consequently, there is a great need for rapid and effective establishment of cell based assays for more rapid discovery of new and improved drugs. Preferably, for more effective drug discovery, the assay system should provide a more physiologically relevant predictor of the effect of a modulator in vivo.
Beyond the need for cell-based assays is a need for improved cells for protein production, cell-based therapy and a variety of other uses.
Accordingly, there is an urgent need for cells and cell lines that express a function protein or RNA of interest.
In the mouth, taste receptor cells (TRCs) can be found in several specialized zones that include the tongue, part of the palate, epiglottis, larynx and pharynx. On the tongue, TRCs are organized into groups of cells called taste buds. Taste buds consist of a single apical pore where microvilli of TRCs come into contact with tastants present within the oral cavity. On the tongue, taste buds are embedded in three types of specialized epidermal structures. The fungiform papillae are distributed over the anterior two-thirds of the tongue. The foliate papillae, which are well developed at birth but regress with age, are found on the sides of the posterior one-third of the tongue. Seven to nine circumvallate papillae are located far back on the posterior tongue close to the terminal sulcus. In addition to the ‘classical’ TRCs organized in taste buds, chemosensory cell clusters or solitary chemosensory cells are found in non-lingual epithelia in the lung and the intestine.
Sweet perception is mediated by a heteromeric G-protein coupled receptor (GPCR) composed of two subunits TASR2 (T1R2) and TASR3 (T1R3). The receptor is named the sweet taste receptor. Both subunits of the receptor are members of the class C GPCR subfamily and possess a large N-terminal extracellular domain, often referred to as the Venus flytrap domain. The T1R subunits can couple to the G proteins alpha transducin or alpha gustducin, through which they can activate a phospholipase C (PLC) β2-dependent pathway to increase intracellular Ca2+ concentration. They may also activate a cAMP-dependent pathway.
Sweet taste receptors detect a wide variety of sweet chemicals including simple carbohydrates (such as sugars), amino acids, peptides, proteins, and synthetic sweeteners. Sweet taste receptors are sensitive to both natural and artificial sweeteners. Given the wide diversity of chemical structures known to activate the receptors, multiple binding sites in the receptors have been proposed, including a site in the transmembrane region and a site on T1R3, which serves as a shared subunit with umami taste receptors.
Sweet taste receptors have also been implicated in conditions such as obesity and diabetes, as these receptors appear to play an important role in nutrient detection and sensing. Taste receptors are expressed in nutrient detection regions of the proximal small intestine in humans, where evidence suggests that they play a role in the detection of nutrients in the intestinal lumen. There is a highly coordinated expression of sweet taste receptors and gustducin, a G-protein implicated in intracellular taste signal transduction, in this region and, more specifically, in the endocrine cells of the gut. The function of these sweet taste receptors thus may show similar ligand-mediated control as other G-protein coupled receptors, that is, they will lose their activity and or expression in the presence of high concentrations of their ligands. This would make intestinal ‘taste’ signaling responsive to the dynamic metabolic changes in glucose concentrations in the blood and lumen. Accordingly, sweet taste receptors and their modulation in the gut may have important roles in diet, appetite and in the treatment of various diseases, such as obesity and diabetes.
Activation of intestinal sweet taste receptors by natural sugars and artificial sweeteners also leads to increased expression of the apical glucose transporter, GLUT2, and other glucose transporters. For example, artificial sweeteners are nutritionally active, because they can signal a functional taste reception system to increase sugar absorption during a meal, a finding that may have important implications in nutrition and appetite, and thus in the potential treatment of malnutrition and eating disorders. Consistently elevated apical GLUT2 levels result in increased sugar absorption and are a characteristic of experimental diabetes and of insulin-resistant states induced by fructose and fat. Additionally, sweet taste receptor activation in neuroendocrine cells leads to the release of glucagon like peptide (GLP-1) and perhaps other modulators of digestion. Overall, sweet taste receptors in the intestine play an important role in sensing the nutritional value of luminal content and help coordinate the body's response via regulated absorption and digestion. These findings suggest that sweet taste receptors could serve as possible targets for modulators useful in treating obesity and diabetes.
Savory (umami) perception is mediated by a heteromeric GPCR composed of two subunits TASR1 (T1R1) and TASR3 (T1R3). The receptor is named the umami taste receptor. Both subunits of the receptor are members of the class C GPCR subfamily and possess a large N-terminal extracellular domain, often referred to as the Venus flytrap domain. The T1R subunits can be coupled to the G proteins alpha transducin or alpha gustducin, through which they can activate a phospholipase C (PLC) 2-dependent pathway to increase intracellular Ca2+ concentration. They may also activate a cAMP-dependent pathway. These receptors can detect a wide variety of savory chemicals including L-amino acids and monosodium glutamate (MSG). T1R1 has also been shown to bind disodium 5′-inosinate (IMP) and other nucleotides, known potentiators of umami taste.
Umami taste receptors are also expressed in nutrient detection regions of the proximal small intestine in humans, where they are thought to play a role in the detection of nutrients in the intestinal lumen. There is a highly coordinated expression of umami taste receptors and gustducin, a G-protein implicated in intracellular taste signal transduction in this region and in specific, in neuroendocrine cells. Activation of intestinal umami taste receptors by amino acids leads to modulation of the apical oligopeptide transporter PepT1. Overall, umami taste receptors in the intestine play an important role in sensing the nutritional value of luminal content and help coordinate the body's response via regulated absorption and digestion. These findings suggest that umami taste receptors could serve as possible targets for modulators useful in treating obesity and diabetes.
Bitter receptors are G protein coupled receptors (GPCRs) expressed at the surface of taste receptor cells and are coupled to secondary messenger pathways. TAS2R receptors can be coupled to transducin (e.g., GNAT1, GNAT2, and guanine nucleotide-binding protein G(t)) or gustducin (e.g., GNAT3 guanine nucleotide binding protein and a transducin 3), for example, through which they can activate both phosphodiesterases and a phospholipase C (PLC) β2-dependent pathway to increase intracellular Ca2+ concentration. TAS2R receptors can also be coupled to human GNA15 (guanine nucleotide binding protein (G protein) α15 (Gq class; synonym GNA16) and mouse Gα15, and their chimera proteins Gα15-GNA15 (also known as Gα15-Gα16).
Human bitter taste is mediated by about 25 members of the human TAS2 receptor (hTAS2R) gene family. In addition to their role in taste, bitter receptors are also important in a series of physiological contexts. For example, taste receptor agonists elicit a secretory response in enteroendocrine cells in vitro and in animals in vivo, and induce neuronal activation. Therefore, all of the bitter receptor family members are important clinical targets for managing a variety of conditions associated with detection of bitter tastants.
The discovery of new and improved compounds that specifically target taste receptors (e.g., sweet taste receptors, umami taste receptors, and bitter taste receptors) and thus modulate their activity has been hampered by the lack of robust, physiologically relevant, cell-based systems and more especially such systems that are amenable to high through-put formats for identifying and testing taste receptor modulators (e.g., sweet taste receptor modulators, umami taste receptor modulators, and bitter taste receptor modulators). Such cell-based systems are preferred for drug discovery and validation because they provide a functional assay for a compound as opposed to cell-free systems, which only provide a binding assay. Moreover, cell-based systems have the advantage of simultaneously testing cytotoxicity. Ideally, cell-based systems should also stably and constitutively express the target protein. It is also desirable for a cell-based system to be reproducible. The present invention addresses these problems in various embodiments in the context of providing cells and cell lines that stably express taste receptors, e.g., sweet taste receptors, bitter taste receptors, or umami taste receptors, in a physiologically relevant form and in methods of using those cells and cell lines to identify modulators of taste receptors, e.g., sweet taste receptors, bitter taste receptors, or umami taste receptors.
In some embodiments, the invention provides a cell that expresses a heterodimeric protein of interest from an introduced nucleic acid encoding at least one of the subunits of the heterodimeric protein of interest, said cell being characterized in that it produces the heterodimeric protein of interest in a form suitable for use in a functional assay, wherein said protein of interest does not comprise a protein tag, or said protein is produced in that form consistently and reproducibly such that the cell has a Z′ factor of at least 0.4 in the functional assay, or said cell is cultured in the absence of selective pressure, or any combinations thereof.
In some embodiments, the invention provides a cell that expresses a heterodimeric protein of interest, wherein the cell is engineered to activate transcription of an endogenous nucleic acid encoding at least one of the subunits of the heterodimeric protein of interest, said cell being characterized in that it produces the heterodimeric protein of interest in a form suitable for use in a functional assay, wherein said protein of interest does not comprise a protein tag, or said protein is produced in that form consistently and reproducibly such that the cell has a Z′ factor of at least 0.4 in the functional assay, or said cell is cultured in the absence of selective pressure, or any combinations thereof.
In some embodiments, the invention provides a cell that expresses a heterodimeric protein of interest from an introduced nucleic acid encoding at least one of the subunits of the heterodimeric protein of interest, said cell being characterized in that it produces the protein of interest in a form that is or is capable of becoming biologically active, wherein the cell is cultured in the absence of selective pressure.
In some embodiments, the invention provides a cell that expresses a heterodimeric protein of interest wherein the cell is engineered to activate transcription of an endogenous nucleic acid encoding at least one of the subunits of the heterodimeric protein of interest, said cell being characterized in that it produces the protein of interest in a form that is or is capable of becoming biologically active, wherein the cell is cultured in the absence of selective pressure.
In some embodiments, the nucleic acid encoding the second subunit of the heterodimeric protein of interest is endogenous. In other embodiments, the nucleic acid encoding the second subunit of the heterodimeric protein of interest is introduced. In yet other embodiments, the protein of interest does not comprise a protein tag.
In some embodiments, the heterodimeric protein of interest is selected from the group consisting of: an ion channel, a G protein coupled receptor (GPCR), tyrosine receptor kinase, cytokine receptor, nuclear steroid hormone receptor, antibody, biologic, and immunological receptor. In some embodiments, the heterodimeric protein is an antibody or a biologic. In some embodiments, the heterodimeric protein of interest is selected from the group consisting of: a sweet taste receptor and an umami taste receptor. In some embodiments, the heterodimeric protein of interest has no known ligand. In other embodiments, there is no known assay to detect functional expression of the heterodimeric protein of interest.
In some embodiments, the heterodimeric protein of interest is not expressed in a cell of the same type. In some embodiments the cell is a mammalian cell.
In some embodiments, the cell is further characterized in that it has an additional desired property selected from the group consisting of: a signal to noise ratio greater than 1, being stable over time, growth without selective pressure without losing expression, physiological EC50 values, and physiological IC50 values. In some embodiments, the heterodimeric protein of interest is produced in a form consistently and reproducibly for a period of time selected from: at least one week, at least two weeks, at least three weeks, at least one month, at least two months, at least three months at least four months, at least five months, at least six months, at least seven months, at least eight months, and at least nine months. In some embodiments, the functional assay is selected from the group consisting of: a cell-based assay, a fluorescent cell-based assay, a high throughput screening assay, a reporter cell-based assay, a G protein mediated cell-based assay, and a calcium flux cell-based assay. In some embodiments, the functional assay is a membrane potential assay, ELISA, mass spectrometry, biochemical characterization of the protein of interest, a cell growth assay, a viability assay, a cell specification assay, or capacity for protein production. In other embodiments, the cell is suitable for utilization in a cell based high throughput screening.
In some embodiments, the selective pressure is an antibiotic. In other embodiments, the cell expresses the heterodimeric protein in the absence of selective pressure for at least 15 days, 30 days, 45 days, 60 days, 75 days, 100 days, 120 days, or 150 days.
In some embodiments, the invention provides a cell that expresses a heteromultimeric protein of interest wherein said heteromultimeric protein comprises at least 3 subunits, wherein at least one subunit of the heteromultimeric protein interest is encoded by an introduced nucleic acid, said cell being characterized in that it produces the heteromultimeric protein of interest in a form suitable for use in a functional assay, wherein said protein of interest does not comprise a protein tag, or said protein produced in that form consistently and reproducibly such that the cell has a Z′ factor of at least 0.4 in the functional assay, or said cell is cultured in the absence of selective pressure, or any combinations thereof.
In some embodiments, the invention provides a cell that expresses a heteromultimeric protein of interest wherein said heteromultimeric protein comprises at least 3 subunits, wherein the cell is engineered to activate transcription of an endogenous nucleic acid encoding at least one of the subunits of the heteromultimeric protein of interest, said cell being characterized in that it produces the heteromultimeric protein of interest in a form suitable for use in a functional assay, wherein said protein of interest does not comprise a protein tag, or said protein produced in that form consistently and reproducibly such that the cell has a Z′ factor of at least 0.4 in the functional assay, or said cell is cultured in the absence of selective pressure, or any combinations thereof.
In some embodiments, the invention provides a cell that expresses a heteromultimeric protein of interest wherein said heteromultimeric protein comprises at least 3 subunits, wherein at least one subunit of the heteromultimeric protein interest is encoded by an introduced nucleic acid, said cell being characterized in that it produces the protein of interest in a form that is or is capable of becoming biologically active.
In some embodiments, the invention provides a cell that expresses a heteromultimeric protein of interest wherein said heteromultimeric protein comprises at least 3 subunits, wherein the cell is engineered to activate transcription of an endogenous nucleic acid encoding at least one of the subunits of the heteromultimeric protein of interest, said cell being characterized in that it produces the protein of interest in a form that is or is capable of becoming biologically active.
In some embodiments, the nucleic acid encoding at least one of the subunits of the heteromultimeric protein of interest is endogenous.
In some embodiments, the nucleic acid encoding at least one of the subunits of the heteromultimeric protein of interest is introduced.
In some embodiments, the protein of interest does not comprise a protein tag.
In some embodiments, the heteromultimeric protein of interest is selected from the group consisting of: an ion channel, a G protein coupled receptor (GPCR), tyrosine receptor kinase, cytokine receptor, nuclear steroid hormone receptor and immunological receptor. In some embodiments, the heteromultimeric protein of interest is an antibody or a biologic. In other embodiments, the heteromultimeric protein of interest is selected from the group consisting of: GABA, ENaC and NaV. In some embodiments, the heteromultimeric protein of interest has no known ligand. In other embodiments, there is no known assay to detect functional expression of said heteromultimeric protein of interest.
In some embodiments, the heteromultimeric protein of interest is not expressed in a cell of the same type. In other embodiments, the cell is a mammalian cell.
In some embodiments, the cell is further characterized in that it has an additional desired property selected from the group consisting of: a signal to noise ratio greater than 1, being stable over time, growth without selective pressure without losing expression, physiological EC50 values, and physiological IC50 values. In other embodiments, the heteromultimeric protein of interest is produced in a form consistently and reproducibly for a period of time selected from: at least one week, at least two weeks, at least three weeks, at least one month, at least two months, at least three months at least four months, at least five months, at least six months, at least seven months, at least eight months, and at least nine months.
In some embodiments, the functional assay is selected from the group consisting of: a cell-based assay, a fluorescent cell-based assay, a high throughput screening assay, a reporter cell-based assay, a G protein mediated cell-based assay, and a calcium flux cell-based assay. In some embodiments, the functional assay is a membrane potential assay, ELISA, mass spectrometry, biochemical characterization of the protein of interest, a cell growth assay, a viability assay, a cell specification assay, or capacity for protein production. In other embodiments, the cell expressing the heteromultimeric protein is suitable for utilization in a cell based high throughput screening.
In some embodiments, the cells expressing the heteromultimeric protein are cultured in the absence of selective pressure. In some embodiments, the selective pressure is an antibiotic. In other embodiments, The cell according to claim 35 or 36, wherein the cell expresses the heteromultimeric protein in the absence of selective pressure for at least 15 days, 30 days, 45 days, 60 days, 75 days, 100 days, 120 days, or 150 days.
In some embodiments, the invention provides a cell that expresses two or more proteins of interest from an introduced nucleic acid encoding at least one of the proteins of interest, said cell being characterized in that it produces the proteins of interest in a form suitable for use in a functional assay, wherein said proteins of interest do not comprise a protein tag, or said proteins are produced in that form consistently and reproducibly such that the cell has a Z′ factor of at least 0.4 in the functional assay, or said cell is cultured in the absence of selective pressure, or any combinations thereof.
In some embodiments, the invention provides a cell that expresses two or more proteins of interest, wherein the cell is engineered to activate transcription of an endogenous nucleic acid encoding at least one of the proteins of interest, said cell being characterized in that it produces the proteins of interest in a form suitable for use in a functional assay, wherein said proteins of interest do not comprise a protein tag, or said proteins are produced in that form consistently and reproducibly such that the cell has a Z′ factor of at least 0.4 in the functional assay, or said cell is cultured in the absence of selective pressure, or any combinations thereof.
In some embodiments, the invention provides a cell that expresses two or more proteins of interest from an introduced nucleic acid encoding at least one of the proteins of interest, said cell being characterized in that it produces the proteins of interest in a form that is or is capable of becoming biologically active.
In some embodiments, the invention provides a cell that expresses two or more proteins of interest, wherein the cell is engineered to activate transcription of an endogenous nucleic acid encoding at least one of the proteins of interest, said cell being characterized in that it produces the proteins of interest in a form that is or is capable of becoming biologically active.
In some embodiments, at least one of the two or more proteins of interest is a dimeric protein. In other embodiments, the dimeric protein of interest is a homodimeric protein. In other embodiments, the dimeric protein of interest is a heterodimeric protein. In some embodiments, at least one of the two or more proteins of interest is a multimeric protein. In other embodiments, the multimeric protein of interest is a homomultimeric protein. In other embodiments, the multimeric protein of interest is a heteromultimeric protein.
In some of the embodiments, one of the two or more proteins of interest is encoded by an endogenous nucleic acid. In other embodiments, one of the two or more proteins of interest is encoded by an introduced nucleic acid. In other embodiments, the proteins of interest do not comprise a protein tag.
In some embodiments, one of the two or more proteins of interest is selected from the group consisting of: an ion channel, a G protein coupled receptor (GPCR), tyrosine receptor kinase, cytokine receptor, nuclear steroid hormone receptor and immunological receptor. In some embodiments, the two or more proteins of interest are independently antibodies or biologics. In other embodiments one of the proteins of interest has no known ligand. In other embodiments, there is no known assay to detect functional expression of the two or more protein of interest.
In some embodiments, one of the two or more proteins of interest is not expressed in a cell of the same type. In some embodiments, the cell expressing the two or more proteins is a mammalian cell.
In some embodiments, the cell expressing the two or more proteins is further characterized in that it has an additional desired property selected from the group consisting of: a signal to noise ratio greater than 1, being stable over time, growth without selective pressure without losing expression, physiological EC50 values, and physiological IC50 values.
In some embodiments, the two or more proteins of interest are produced in a form consistently and reproducibly for a period of time selected from: at least one week, at least two weeks, at least three weeks, at least one month, at least two months, at least three months at least four months, at least five months, at least six months, at least seven months, at least eight months, and at least nine months.
In some embodiments, the functional assay is selected from the group consisting of: a cell-based assay, a fluorescent cell-based assay, a high throughput screening assay, a reporter cell-based assay, a G protein mediated cell-based assay, and a calcium flux cell-based assay. In some embodiments, the functional assay is a membrane potential assay, ELISA, mass spectrometry, biochemical characterization of the protein of interest, a cell growth assay, a viability assay, a cell specification assay, or capacity for protein production. In some embodiments, the cell expressing the two or more proteins is suitable for utilization in a cell based high throughput screening.
In some embodiments, the cell expressing the two or more proteins is cultured in the absence of selective pressure. In some embodiments, the selective pressure is an antibiotic. In some embodiments, the cell expresses the two or more proteins in the absence of selective pressure for at least 15 days, 30 days, 45 days, 60 days, 75 days, 100 days, 120 days, or 150 days.
In some embodiments, the invention provides a cell that expresses at least one RNA of interest, wherein said RNA of interest is encoded by an introduced nucleic acid, said cell being characterized in that it produces the at least one RNA of interest in a form suitable for use in a functional assay, wherein said RNA of interest do not comprise a tag, or said RNA is produced in that form consistently and reproducibly such that the cell has a Z′ factor of at least 0.4 in the functional assay, or said cell is cultured in the absence of selective pressure, or any combinations thereof.
In some embodiments, the invention provides a cell that expresses at least one RNA of interest, wherein the cell is engineered to activate transcription of an endogenous nucleic acid encoding the at least one RNA of interest, said cell being characterized in that it produces the at least one RNA of interest in a form suitable for use in a functional assay, wherein said RNA of interest do not comprise a tag, or said RNA is produced in that form consistently and reproducibly such that the cell has a Z′ factor of at least 0.4 in the functional assay or said cell is cultured in the absence of selective pressure, or any combinations thereof.
In some embodiments, the cell expresses at least two RNAs of interest. In other embodiments, the cell expresses at least three RNAs of interest. In some embodiments, the cell further expresses a RNA encoded by an introduced nucleic acid. In some embodiments, the RNA of interest is selected from the group consisting of: a RNA encoding an ion channel, a RNA encoding a G protein coupled receptor (GPCR), a RNA encoding a tyrosine receptor kinase, a RNA encoding a cytokine receptor, a RNA encoding a nuclear steroid hormone receptor and a RNA encoding an immunological receptor. In other embodiments, the RNA of interest is a RNA encoding an antibody or a RNA encoding a biologic.
In some embodiments, the RNA of interest is not expressed in a cell of the same type. In some embodiments, the cell expressing the RNA of interest is a mammalian cell.
In some embodiments, the cell expressing the RNA of interest is further characterized in that it has an additional desired property selected from the group consisting of: a signal to noise ratio greater than 1, being stable over time, growth without selective pressure without losing expression, physiological EC50 values, and physiological IC50 values. In some embodiments, the RNA of interest is produced in a form consistently and reproducibly for a period of time selected from: at least one week, at least two weeks, at least three weeks, at least one month, at least two months, at least three months at least four months, at least five months, at least six months, at least seven months, at least eight months, and at least nine months.
In some embodiments, the functional assay is selected from the group consisting of: a cell-based assay, a fluorescent cell-based assay, a high throughput screening assay, a reporter cell-based assay, a G protein mediated cell-based assay, and a calcium flux cell-based assay. In other embodiments, the functional assay is a membrane potential assay, ELISA, mass spectrometry, biochemical characterization of the protein of interest, a cell growth assay, a viability assay, a cell specification assay, or capacity for protein production.
In some embodiments, the cell expressing the RNA of interest is suitable for utilization in a cell based high throughput screening.
In some embodiments, the invention provides a cell line produced from a cell described herein.
In some embodiments, the invention provides a method for producing a cell that expresses a protein of interest, wherein the cell has at least one desired property that is consistent over time, comprising the steps of:
In some embodiments, the invention provides a method for producing a cell that expresses a protein of interest, wherein the cell has at least one desired property that is consistent over time, comprising the steps of:
In some embodiments, the plurality of cells in step a) of the methods described herein are cultured for some period of time prior to the dispersing in step b).
In some embodiments, the individual culture vessels used in the methods of this invention are selected from the group consisting of: individual wells of a multiwell plate and vials.
In some embodiments, the method further comprises the step of determining the growth rate of a plurality of the separate cell cultures and grouping the separate cell cultures by their growth rates into groups such that the difference between the fastest and slowest growth rates in any group is no more than 1, 2, 3, 4 or 5 hours between steps b) and c).
In some embodiments, the method further comprises the step of preparing a stored stock of one or more of the separate cultures. In some embodiments, the method further comprises the step of one or more replicate sets of the separate cell cultures and culturing the one or more replicate sets separately from the source separate cell cultures.
In some embodiments, the assaying in step d) of the method of this invention is a functional assay for the protein.
In some embodiments, the at least one characteristic that has remained constant in step e) is protein function.
In some embodiments, the culturing in step c) of the methods of this invention is in a robotic cell culture apparatus. In some embodiments, the robotic cell culture apparatus comprises a multi-channel robotic pipettor. In some embodiments, the multi-channel robotic pipettor comprises at least 96 channels. In some embodiments, the robotic cell culture apparatus further comprises a cherry-picking arm.
In some embodiments, the automated methods include one or more of: media removal, media replacement, cell washing, reagent addition, removal of cells, cell dispersal, and cell passaging.
In some embodiments, the plurality of separate cell cultures used in the methods of this invention is at least 50 cultures. In other embodiments, the plurality of separate cell cultures is at least 100 cultures. In other embodiments, the plurality of separate cell cultures is at least 500 cultures. In yet other embodiments, the plurality of separate cell cultures is at least 1000 cultures.
In some embodiments, the growth rate is determined by a method selected from the group consisting of: measuring ATP, measuring cell confluency, light scattering, optical density measurement. In some embodiments, the difference between the fastest and slowest growth rates in a group is no more than 1, 2, 3, 4, or 5 hours.
In some embodiments, the culturing in step c) of the methods of this invention is for at least 2 days.
In some embodiments, the growth rates of the plurality of separate cell cultures are determined by dispersing the cells and measuring cell confluency. In some embodiments, the cells in each separate cell culture of the methods of this invention are dispersed prior to measuring cell confluency. In some embodiments, the dispersing step comprises adding trypsin to the well and to eliminate clumps. In some embodiments, the dispersing step comprises adding a cell dissociation reagent to the well and to eliminate clumps In some embodiments, the cell confluency of the plurality of separate cell cultures is measured using an automated microplate reader.
In some embodiments, at least two confluency measurements are made before growth rate is calculated. In some embodiments, the cell confluency is measured by an automated plate reader and the confluency values are used with a software program that calculates growth rate.
In some embodiments, the separate cell cultures in step d) are characterization for a desired trait selected from one or more of: fragility, morphology, adherence to a solid surface; lack of adherence to a solid surface and protein function. In other embodiments, the desired trait is UPR, cell viability, capacity for improved protein production, yield, folding, assembly, secretion, integration into a cell membrane, post-translational modification, or glycosylation or any combination thereof.
In some embodiments, the cells used in the methods of this invention are eukaryotic cells. In some embodiments, the eukaryotic cells used in the methods of this invention are mammalian cells. In some embodiments, the mammalian cell line is selected from the group consisting of: NS0 cells, CHO cells, COS cells, HEK-293 cells, HUVECs, 3T3 cells and HeLa cells. In another embodiment, the mammalian cell line is Perc6.
In some embodiments, the protein of interest expressed in the methods of this invention is a human protein. In some embodiments, the protein of interest is a heteromultimer. In some embodiments, the protein of interest is a G protein coupled receptor. In other embodiments, the protein has no known ligand. In other embodiments, there is no known assay to detect functional expression of said protein.
In some embodiments, the method of this invention, further comprises after the identifying step, the steps of:
In some embodiments, the invention provides a matched panel of clonal cell lines, wherein the clonal cell lines are of the same cell type, and wherein each cell line in the panel expresses a protein of interest, and wherein the clonal cell lines in the panel are matched to share the same physiological property to allow parallel processing.
In some embodiments, the invention provides a matched panel of clonal cell lines, wherein the clonal cell lines are of the same cell type, and wherein at least two cell lines in the panel express a protein of interest, and wherein the clonal cell lines in the panel are matched to share the same physiological property to allow parallel processing.
In some embodiments, the invention provides a combinatorial matched panel of clonal cell lines wherein the clonal cell lines are the of the same type and wherein at least two of the cell lines in the express a multi-subunit protein of interest and wherein each of said clonal cell lines comprises a different combination of subunits of the multi-subunit protein of interest; and wherein the clonal cell lines of the panel are matched such that they are grown under the same cell culture conditions in parallel.
In some embodiments, the physiological property is growth rate. In other embodiments, the physiological property is adherence to a tissue culture surface. In other embodiments, the physiological property is Z′ factor. In other embodiments, the physiological property is expression level of RNA encoding the protein of interest. In yet other embodiments, the physiological property is expression level of the protein of interest. In still other embodiments, the physiological property is activity level of RNA encoding the protein of interest. In some embodiments, the growth rates of the clonal cell lines in the panel are within 1, 2, 3, 4, or 5 hours of each other. In other embodiments, the culture conditions used for the matched panel are the same for all clonal cell lines in the panel.
In some embodiments, the clonal cell line used in the matched panels is a eukaryotic cell line. In some embodiments, the eukaryotic cell line is a mammalian cell line. In some embodiments, the cell line cells used in the matched panels are selected from the group consisting of: primary cells and immortalized cells.
In some embodiments, the cell line cells used in the matched panels are prokaryotic or eukaryotic. In some embodiments, the cell line cells used in the matched panels are eukaryotic and are selected from the group consisting of: fungal cells, insect cells, mammalian cells, yeast cells, algae, crustacean cells, arthropod cells, avian cells, reptilian cells, amphibian cells and plant cells. In some embodiments, the cell line cells used in the matched panels are mammalian and are selected from the group consisting of: human, non-human primate, bovine, porcine, feline, rat, marsupial, murine, canine, ovine, caprine, rabbit, guinea pig hamster.
In some embodiments, the cells in the cell line of the matched panels are engineered to express the protein of interest. In some embodiments, the cells in the cell line of the matched panels express the protein of interest from an introduced nucleic acid encoding the protein or, in the case of a multimeric protein, encoding a subunit of the protein. In some embodiments, the cells express the protein of interest from an endogenous nucleic acid and wherein the cell is engineered to activate transcription of the endogenous protein or, in the case of a multimeric protein, activates transcription of a subunit of the protein.
In some embodiments, the panel comprises at least four clonal cell lines. In other embodiments, the panel comprises at least six clonal cell lines. In yet other embodiments, the panel comprises at least twenty five clonal cell lines.
In some embodiments, two or more of the clonal cell lines in the panel express the same protein of interest. In other embodiments, two or more of the clonal cell lines in the panel express a different protein of interest.
In some embodiments, the cell lines in the panel express different forms of a protein of interest, wherein the forms are selected from the group consisting of: isoforms, amino acid sequence variants, splice variants, truncated forms, fusion proteins, chimeras, or combinations thereof. In other embodiments, the forms are active forms, modified forms, glycosylated forms, proteolyzed forms, or functional forms, or combinations thereof. In still other embodiments, the forms are selected from the group consisting of: isoforms, amino acid sequence variants, splice variants, truncated forms, fusion proteins, chimeras, active forms, modified forms, glycosylated forms, proteolyzed forms, functional forms or combinations thereof.
In some embodiments, the cell lines in the panel express different proteins in a group of proteins of interest, wherein the groups of proteins of interest are selected from the group consisting of: proteins in the same signaling pathway, expression library of similar proteins, monoclonal antibody heavy chain library, monoclonal antibody light chain library and SNPs.
In some embodiments, the protein of interest expressed in the panel is a single chain protein. In some embodiments, the single chain protein is a G protein coupled receptor. In some embodiments, the G protein coupled receptor is a taste receptor. In some embodiments, the taste receptor is selected from the group consisting of: a bitter taste receptor, a sweet taste receptor, a salt taste receptor and an umami taste receptor.
In other embodiments, the protein of interest expressed in the panel is a multimeric protein. In some embodiments, the protein is a heterodimer or a heteromultimer.
In some embodiments, the protein of interest expressed in the panel is selected from the group consisting of: an ion channel, an ion channel, a G protein coupled receptor (GPCR), tyrosine receptor kinase, cytokine receptor, nuclear steroid hormone receptor and immunological receptor. In other embodiments, the protein of interest expressed in the panel is an antibody or a biologic. In some embodiments, the protein expressed in the matched panel is Epithelial sodium Channel (ENaC). In some embodiments, the ENaC comprises an alpha subunit, a beta subunit and a gamma subunit. In other embodiments, the cell lines in the panel express different ENaC isoforms. In other embodiments, the cell lines in the panel comprise different proteolyzed isoforms of ENaC. In some embodiments, the ENaC is human ENaC. In some embodiments the protein expressed in the matched panel is voltage gated sodium channel (NaV). In some embodiments, the NaV comprises an alpha subunit and two beta subunits. In some embodiments, the NaV is human NaV.
In some embodiments, the protein expressed in the matched panel is selected from the group consisting of: gamma-aminobutyric acid A receptor (GABAA receptor), gamma-aminobutyric acid B receptor (GABAB receptor) and gamma-aminobutyric acid C receptor (GABAC receptor). In some embodiments, the protein is GABAA receptor. In some embodiments, the GABAA receptor comprises two alpha subunits, two beta subunits and a gamma or delta subunit.
In some embodiments, the clonal cell lines in the panel are produced simultaneously, or within no more than 4 weeks of each other. In other embodiments, the clonal cell lines in the panel were produced using substantially identical methods for isolation, maintenance or testing of the clonal cell lines of the panel.
In some embodiments, the invention provides a cell that expresses a monomeric protein of interest from an introduced nucleic acid encoding said monomeric protein of interest, characterized in that it produces the protein of interest in a form that is or is capable of becoming biologically active, wherein the cell is cultured in the absence of selective pressure and wherein the expression of the protein does not vary by more than 5% over 3 months. In some embodiments the expression of the protein does not vary by more than 5% over 6 months. In some embodiments, the monomeric protein of interest has no known ligand.
In some embodiments, the invention provides a cell that expresses a monomeric protein of interest from an introduced nucleic acid encoding said monomeric protein of interest, characterized in that it produces the protein of interest in a form that is or is capable of becoming biologically active, wherein the cell is cultured in the absence of selective pressure and wherein the expression of the protein does not vary by more than 30% over 3 months. In some embodiments the expression of the protein does not vary by more than 30% over 6 months.
In some embodiments, the invention provides a cell that expresses at least one RNA of interest, wherein said RNA of interest is encoded by an introduced nucleic acid, characterized in that it produces the RNA of interest in a form that is or is capable of becoming biologically active, wherein the cell is cultured in the absence of selective pressure and wherein the expression of the RNA does not vary by more than 30% over 3 months. In some embodiments the expression of the RNA does not vary by more than 30% over 6 months.
In some embodiments, the invention provides a cell that expresses a protein of interest, wherein said protein of interest is encoded by an introduced nucleic acid, characterized in that it produces the protein of interest in a form that is or is capable of becoming biologically active, wherein the cell is cultured in the absence of selective pressure and wherein the expression of the protein does not vary by more than 30% over 3 months. In some embodiments the expression of the protein does not vary by more than 30% over 6 months.
In some embodiments, the invention provides a cell that expresses at least one protein of interest, wherein the protein of interest has no known ligand or wherein there is no known assay to detect functional expression of said protein of interest; and wherein said protein of interest does not comprise a protein tag.
In some embodiments, the invention provides a method for identifying a modulator of a protein of interest comprising the steps of:
In another embodiment, the invention provides a modulator identified by the method of the preceding paragraph.
In some embodiments, the invention provides a cell that expresses at least one protein of interest from an introduced nucleic acid encoding the at least one protein of interest, wherein the at least one protein of interest alters a physiological property of the cell, and wherein the physiological property of the cell does not vary by more than 25% over 3 months under constant cell culture conditions.
In some embodiments, the invention provides a cell that expresses a protein of interest, wherein the cell is engineered to activate transcription of an endogenous nucleic acid encoding the protein of interest, wherein the protein of interest alters a physiological property of the cell, and wherein the physiological property of the cell does not vary by more than 25% over 3 months under constant cell culture conditions.
In some embodiments, the invention provides a cell that expresses an RNA of interest, wherein the RNA of interest is encoded by an introduced nucleic acid, wherein the at least one RNA of interest alters a physiological property of the cell, and wherein the physiological property of the cell does not vary by more than 25% over 3 months under constant cell culture conditions.
A cell that expresses at least one protein of interest from an introduced nucleic acid encoding the at least one protein of interest, said cell being characterized in that it produces the protein of interest in a form that is or is capable of becoming biologically active, and wherein the cell consistently and reproducibly expresses at least 500, 2,500, 5,000, or 100,000 picograms of protein per cell per day.
A cell that expresses a protein of interest, wherein the cell is engineered to activate transcription of an endogenous nucleic acid encoding the protein of interest, said cell being characterized in that it produces the protein of interest in a form that is or is capable of becoming biologically active, and wherein the cell consistently and reproducibly expresses at least 500, 2,500, 5,000, or 100,000 picograms of protein per cell per day.
In some embodiments, the cell is produced in a period of time selected from less than 1 week, less than 2 weeks, less than 3 weeks, less than 4 weeks, less than 1 month, less than 2 months, less than 3 months, less than 4 months, less than 5 months, less than 6 months, less than 7 months, less than 8 months or less than 9 months.
In some embodiments, the invention provides a cell that expresses at least one protein of interest from an introduced nucleic acid encoding the at least one protein of interest, said cell being characterized in that it produces the protein of interest in a form that is or is capable of becoming biologically active, wherein the cell is produced in a period of time selected from less than 7 months, less than 8 months or less than 9 months, and wherein the cell consistently and reproducibly expresses at least 0.5, 1.0, 5.0 or 10 g/L or protein.
In some embodiments, the invention provides a cell that expresses a protein of interest, wherein the cell is engineered to activate transcription of an endogenous nucleic acid encoding the protein of interest, said cell being characterized in that it produces the protein of interest in a form that is or is capable of becoming biologically active, wherein the cell is produced in a period of time selected from less than 7 months, less than 8 months or less than 9 months, and wherein the cell consistently and reproducibly expresses at least 0.5, 1.0, 5.0 or 10 g/L of protein.
In some embodiments, the cell is produced in a period of time selected from less than 3 months, less than 4 months or less than 6 months. In some embodiments, the protein is a monomeric protein. In other embodiments, the protein is a multimeric protein. In some embodiments, the protein of interest does not comprise a protein tag or said cell is cultured in the absence of selective pressure or a combination thereof. In some embodiments, the multimeric protein of interest comprises at least 2, 3, 4, 5, or at least 6 subunits. In some embodiments, the multimeric protein of interest is selected from the group consisting of: an ion channel, a G protein coupled receptor (GPCR), tyrosine receptor kinase, cytokine receptor, nuclear steroid hormone receptor, antibody, biologic and immunological receptor. In some embodiments, the multimeric protein of interest is an ion channel and the cell physiological property is selected from a membrane potential, UPR, cell viability, a capacity for improved protein production, yield, folding assembly, secretion, integration into a cell membrane, post-translational modification, glycosylation, or any combination thereof.
In another embodiment, the invention provides a cell line produced from a cell described herein.
In some embodiments, the invention provides a method for identifying a modulator of a protein of interest comprising the steps of:
In some embodiments, the invention provides a matched panel of cells or clonal cell lines comprising at least two cells described herein (e.g., a cell that expresses at least one protein or RNA of interest) or two clonal cell lines described herein (e.g., a cell line produced from a cell described herein), wherein the at least two cells or the at least two clonal cell lines are matched such that they are grown under the same cell culture conditions in parallel.
In some embodiments, the matched panel comprises at least 10 cells 10 clonal cell lines and the at least 10 cells or the 10 clonal cell lines are matched such that they are grown under identical cell culture conditions in parallel. In other embodiments, the panel comprises at least 100 cells or at least 100 clonal cell lines and the at least 100 cells or the at least 100 clonal cell lines are grown under identical cell culture conditions in parallel.
In some embodiments, the invention provides a matched panel of clonal cell lines wherein the clonal cell lines are of the same type and comprises a first and a second protein of interest; wherein the first protein of interest is the same in each clonal cell line; wherein the second protein of interest is a component of a functional biological pathway; and wherein:
In some embodiments, the first protein of interest is an antibody and the functional biological pathway is a glycosylation pathway.
In some embodiments, the invention provides a method for generating an in vitro correlate for an in vivo physiological property, wherein the method comprises:
In some embodiments, the first and second proteins of interest are independently selected from a monomeric protein or a multimeric protein. In some embodiments, the multimeric protein comprises at least 2, 3, 4, 5, or 6 subunits. In some embodiments, the multimeric protein is a heteromultimeric protein. In some embodiments, the first and second proteins of interest are independently selected from the group consisting of: ENaC, NaV, GABAA, sweet taste receptor, umami taste receptor, bitter taste receptor, CFTR and GCC.
In some embodiments, the first cell and the second cell are cells within a panel of cells further comprising at least one other cell; each cell in the panel of cells is engineered to express a different protein, and is contacted by the compound or plurality of compounds; the effect of the compound or plurality of compounds on each protein expressed in each cell in the panel of cells is assayed in a functional assay; and the activity profile of the compound or plurality of compounds in each cell is used to generate the in vitro correlate for the physiological property.
In some embodiments, each protein is independently selected from a monomeric protein or a multimeric protein. In some embodiments, the multimeric protein comprises at least 2, 3, 4, 5, or 6 subunits. In some embodiments, the multimeric protein is a heteromultimeric protein. In some embodiments, each protein is independently selected from the group consisting of: ENaC, NaV, GABAA, sweet taste receptor, umami taste receptor, bitter taste receptor, CFTR and GCC.
In some embodiments, the invention provides a method for predicting a physiological property of a test compound, wherein the method comprises:
wherein the first and second proteins independently i) do not comprise a protein tag, ii) are produced consistently and reproducibly in a form suitable for use in a functional assay such that the cells have a Z′ factor of at least 0.4 in the functional assay, iii) are expressed in cells cultured in the absence of selective pressure, iv) alter a physiological property of the cell and wherein the physiological property of the cell does not vary by more than 25% over 3 months under constant cell culture conditions; v) are stably expressed in cells cultured in the absence of selective pressure and wherein the expression of the protein does not vary by more than 30% over 3 months, vi) are expressed in a cell further expressing another protein and said cell is cultured in the absence of selective pressure or vii) any combination thereof; and wherein the test compound or plurality of test compounds are predicted to have the physiological property of the in vitro correlate if the activity profile of the test compound or compounds and the activity profile of the in vitro correlate are at least 90% identical.
In some embodiments, the invention provides a method for confirming a physiological property of a test compound or plurality of test compounds, wherein the method comprises:
In some embodiments, the first and second proteins are independently selected from a monomeric protein or a multimeric protein. In some embodiments, the multimeric protein comprises at least 2, 3, 4, 5, or at least 6 subunits. In some embodiments, the multimeric protein is a heteromultimeric protein.
In some embodiments, the first cell and the second cell are cells within a panel of cells further comprising at least one other cell; each cell in the panel of cells is engineered to express a different protein, and is contacted by the test compound or plurality of test compounds; the effect of the test compound or plurality of test compounds on each protein of interest expressed in each cell in the panel of cells is assayed in a functional assay; and the activity profile of the test compound or plurality of test compounds in each cell is used to compare with the profile of the in vitro correlate.
In some embodiments, at least one of the first multimeric protein of interest and the second multimeric protein of interest is a heteromeric protein. In some embodiments, at least one of the first protein of interest and the second protein of interest is a dimeric protein. In other embodiments, at least one of the first protein of interest and the second protein of interest is a trimeric protein. In some embodiments, the first protein of interest and the second protein of interest are different forms of a multimeric protein. In some embodiments, the multimeric protein is GABA A receptor.
In some embodiments, at least one of the first or second protein of interest is part of a functional biological pathway. In some embodiments, the functional biological pathway is selected from the group consisting of: glycosylation, protein synthesis, UPR, ER, ribosomal, mitochondrial activity, RNA synthesis, post-translational modification, cell signaling, cell growth and cell death.
In some embodiments, the physiological property is a therapeutic effect. In some embodiments, the physiological property is an adverse effect. In some embodiments, the effect of the compound or plurality of compounds on the physiological property is assayed by high throughput screening. In some embodiments, the step comparing described hereinabove is implemented in a computer system.
In some embodiments, the invention provides a computer-implemented method for determining a physiological property of a test compound or plurality of test compounds, wherein the method comprises:
In some embodiments, the one or more landmark activity profiles are most similar to said first activity profile if said measures of similarity are above a predetermined threshold.
In some embodiments, the invention provides a computer-implemented method for characterizing a test compound or plurality of test compounds as being associated with a particular physiological property, wherein the method comprises:
In some embodiments, the invention provides a computer-implemented method of classifying a test compound or a plurality of test compounds as to a physiological property using a classifier, wherein the method comprises:
In some embodiments, the invention provides a computer-implemented method of classifying a test compound or a plurality of test compounds as to a physiological property using a classifier, wherein the method comprises:
In some embodiments, the invention provides a method for characterizing an active subunit combination of a multimeric protein of interest in a cell, wherein the method comprises:
In some embodiments, the multimeric protein of interest is a heterodimer. In other embodiments, the multimeric protein of interest is a heterotrimer.
In some embodiments, the invention provides a method for characterizing an active subunit combination of a multimeric protein of interest in a cell, wherein the method comprises:
In some embodiments, the multimeric protein is a heterotrimer. In some embodiments, the multimeric protein is a GABA A receptor.
In some embodiments, the invention provides a panel of cells, wherein the panel comprises a first cell and a second cell, wherein the first cell and the second cell have been engineered to express the same subunit of a multimeric protein of interest, wherein the physiological profile of the multimeric protein of interest in the first cell differs from the physiological profile of the multimeric protein in the second cell, and wherein the first cell and the second cell originate from the same host cell line; wherein the subunits of the multimeric protein of interest do not comprise a protein tag, are expressed in cells cultured in the absence of selective pressure or any combination thereof.
In some embodiments, the invention provides a panel of clonal cell lines, wherein each cell line has been engineered to express the same subunit of a multimeric protein of interest, and wherein the physiological profiles of the multimeric protein in each cell line is different from the physiological profile of the multimeric protein of interest in the other cell lines of the panel, and wherein the cell lines in the panel of cell lines originate from the same host cell line; wherein the subunits of the multimeric protein of interest do not comprise a protein tag, are expressed in cells cultured in the absence of selective pressure or any combination thereof.
In some embodiments, the panel comprises 2 cell lines. In some embodiments, the panel comprises 5 cell lines. In some embodiments, the panel comprises 10 cell lines.
In some embodiments, the multimeric protein of interest is NaV.
In some embodiments, the invention provides a cell that has been engineered to express all component proteins of a functional biological pathway.
In some embodiments, the pathway has at least five protein components. In some embodiments, the cell is cultured in the absence of selective pressure. In some embodiments, the component proteins of the biological pathway do not comprise a protein tag.
In some embodiments, the invention provides a panel of clonal cell lines comprising a plurality of clonal cell lines, wherein each clonal cell line of the plurality of clonal cell lines has been engineered to express a different odorant receptor; wherein the odorant receptor does not comprise a protein tag, or the odorant receptor is produced consistently and reproducibly in a form suitable for use in a functional assay such that the cells have a Z′ factor of at least 0.4 in the functional assay, or the clonal cell lines are cultured in the absence of selective pressure, or any combination thereof.
In some embodiments, the plurality of clonal cell lines comprises at least 10 cell lines. In some embodiments, the different odorant receptors are human odorant receptors or insect odorant receptors.
In some embodiments, the different human odorant receptors are selected from the group consisting of OR10A1, OR10A3, OR10A4, OR10A5, OR10A6, OR10A7, OR10C1, OR10C2, OR10D4, OR10G2, OR10G3, OR10G4, OR10G7, OR10G8, OR10G9, OR10H1, OR10H2, OR10H3, OR10H4, OR10H5, OR10J1, OR10J3, OR10J5, OR10J6, OR10K1, OR10K2, OR10Q1, OR10R2, OR10S1, OR10T2, OR10V1, OR10Z1, OR11A1, OR11G2, OR11H1, OR11H4, OR11H6, OR11H7P, OR11L1, OR12D3, OR13A1, OR13C2, OR13C3, OR13C4, OR13C5, OR13C7, OR13C8, OR13C9, OR13D1, OR13E2, OR13F1, OR13G1, OR13H1, OR13J1, OR14A16, OR14A2, OR14C36, OR14J1, OR1A1, OR1A2, OR1A2, OR1B1, OR1C1, OR1D2, OR1D4, OR1D5, OR1E1, OR1E2, OR1E2, OR1E5, OR1E5, OR1E6, OR1E7, OR1F1, OR1F10, OR1F11, OR1F12, OR1F2, OR1G1, OR1I1, OR1J1, OR1J2, OR1J2, OR1J4, OR1J5, OR1K1, OR1L1, OR1L3, OR1L4, OR1L6, OR1L8, OR1M1, OR1M1, OR1N1, OR1N2, OR1N3, OR1Q1, OR1S1, OR1S2, OR2A1, OR2A10, OR2A19, OR2A20, OR2A21, OR2A4, OR2A42, OR2A5, OR2A6, OR2A7, OR2AE1, OR2AJ1, OR2AK2, OR2B1, OR2B2, OR2B3, OR2B6, OR2B9, OR2C1, OR2D1, OR2D2, OR2D3, OR2F1, OR2F2, OR2F3, OR2G2, OR2G3, OR2H1, OR2H2, OR2H3, OR2J2, OR2J3, OR2K1, OR2K2, OR2L1, OR2L2, OR2L3, OR2L5, OR2L8, OR2M1, OR2M2, OR2M4, OR2S2, OR2T1, OR2T3, OR2T4, OR2T5, OR2T6, OR2T7, OR2T8, OR2V1, OR2V2, OR2V3, OR2W1, OR2W3, OR2Y1, OR2Z1, OR3A1, OR3A2, OR3A3, OR3A4, OR4A15, OR4A16, OR4A4, OR4A5, OR4B1, OR4C12, OR4C13, OR4C15, OR4C16, OR4C3, OR4C6, OR4D1, OR4D2, OR4D5, OR4D6, OR4D9, OR4E2, OR4F10, OR4F15, OR4F16, OR4F16, OR4F17, OR4F18, OR4F19, OR4F3, OR4F6, OR4K1, OR4K13, OR4K14, OR4K15, OR4K17, OR4K2, OR4K3, OR4K5, OR4L1, OR4M1, OR4M2, OR4N2, OR4N4, OR4N5, OR4P4, OR4Q3, OR4S1, OR4X1, OR4X2, OR51A2, OR51A4, OR51A7, OR51B2, OR51B4, OR51D1, OR51E1, OR51E2, OR51F2, OR51G1, OR51G2, OR51H1, OR51I1, OR51I2, OR51L1, OR51M1, OR51Q1, OR51S1, OR51T1, OR52A1, OR52A2, OR52B2, OR52B4, OR52B4, OR52B4, OR52B6, OR52D1, OR52E2, OR52E4, OR52E5, OR52E6, OR52E8, OR52H1, OR52I1, OR52I2, OR52J3, OR52K1, OR52K2, OR52L1, OR52L2, OR52N1, OR52N2, OR52N4, OR52N5, OR52P1, OR52R1, OR56A4, OR56A6, OR56B2, OR56B4, OR5A1, OR5A2, OR5AC2, OR5AK2, OR5AK3, OR5AN1, OR5AP2, OR5AR1, OR5AS1, OR5AU1, OR5AU1, OR5B13, OR5B16, OR5B17, OR5B2, OR5B3, OR5C1, OR5D13, OR5D14, OR5D16, OR5D18, OR5F1, OR5G3, OR5H1, OR5H2, OR5H6, OR5I1, OR5K1, OR5K2, OR5L1, OR5L2, OR5M1, OR5M10, OR5M11, OR5M11, OR5M3, OR5M3, OR5M8, OR5M9, OR5P2, OR5P3, OR5T2, OR5T3, OR5V1, OR6A1, OR6B1, OR6B2, OR6C1, OR6C2, OR6C3, OR6F1, OR6J2, OR6K3, OR6K6, OR6M1, OR6N1, OR6N2, OR6P1, OR6Q1, OR6S1, OR6T1, OR6V1, OR6X1, OR6Y1, OR7A10, OR7A17, OR7A2, OR7A5, OR7C1, OR7C2, OR7D2, OR7D2, OR7D4P, OR7E102, OR7E120, OR7G1, OR7G2, OR7G3, OR8A1, OR8B12, OR8B2, OR8B3, OR8B4, OR8B8, OR8D1, OR8D2, OR8D4, OR8G1, OR8G2, OR8H1, OR8H2, OR8H3, OR8I2, OR8J1, OR8J3, OR8K1, OR8K3, OR8K5, OR9A2, OR9A4, OR9G1, OR9G4, OR9G5, OR9I1, OR9K2, and OR9Q1.
In some embodiments, the different insect odorant receptors are mosquito odorant receptors selected from the group consisting of IOR100, IOR101, IOR102, IOR103, IOR104, IOR105, IOR106, IOR107, IOR108, IOR109, IOR110, IOR111, IOR112, IOR113, IOR114, IOR115, IOR116, IOR117, IOR118, IOR119, IOR120, IOR121, IOR122, IOR123, IOR124, IOR125, IOR126, IOR127, IOR49, IOR50, IOR51, IOR52, IOR53, IOR54, IOR55, IOR56, IOR57, IOR58, IOR59, IOR60, IOR61, IOR62, IOR63, IOR64, IOR65, IOR66, IOR67, IOR68, IOR69, IOR70, IOR71, IOR72, IOR73, IOR74, IOR75, IOR76, IOR77, IOR78, IOR79, IOR80, IOR81, IOR82, IOR83, IOR84, IOR85, IOR86, IOR87, IOR88, IOR89, IOR90, IOR91, IOR92, IOR93, IOR94, IOR95, IOR96, IOR97, IOR98, IOR99, ORL7077, ORL7078, ORL7079, ORL7080, ORL7081, ORL7082, ORL7083, ORL7084, ORL7085, ORL7086, ORL7087, ORL7088, ORL7089, ORL7090, ORL7091, ORL7092, ORL7093, ORL7094, ORL7095, ORL7096, ORL7097, ORL7098, ORL7099, ORL7100, ORL7101, ORL7102, ORL7103, ORL7104, ORL7105, ORL7106, ORL7107, ORL7108, ORL7109, ORL7110, ORL7111, ORL7112, ORL7113, ORL7114, ORL7115, ORL7116, ORL7117, ORL7118, ORL7119, ORL7120, ORL7121, ORL7122, ORL7123, ORL7124, ORL7125, TPR2307, TPR2308, TPR2309, TPR2310, TPR2312, TPR2314, TPR2315, TPR2316, TPR2317, TPR2318, TPR2319, TPR2320, TPR2321, TPR2321, TPR698, TPR699, TPR700, TPR701, TPR702, TPR703, TPR704, TPR705, TPR706, TPR707, TPR708, TPR709, TPR710, TPR711, TPR712, TPR713, TPR714, TPR715, TPR716, TPR717, TPR718, TPR719, TPR720, TPR721, TPR722, TPR723, TPR724, TPR725, TPR725, TPR726, TPR727, TPR728, TPR729, TPR730, TPR731, TPR732, TPR733, TPR734, TPR735, TPR736, TPR737, TPR738, TPR739, TPR740, TPR741, TPR742, TPR743, TPR744, TPR745, TPR746, TPR747, TPR748, TPR749, TPR750, TPR751, TPR752, TPR753, TPR754, TPR755, TPR756, TPR757, TPR758, TPR759, TPR760, TPR761, TPR762, TPR763, TPR764, TPR765, TPR766, TPR767, TPR768, TPR769, TPR770, TPR771, and TPR772.
In some embodiments, the invention provides a method for generating an odorant activity profile of a test compound or composition, wherein the method comprises:
In some embodiments, the invention provides a method for identifying a second test compound that mimics the odor of a first test compound or composition, wherein the method comprises:
In some embodiments, the invention provides a method to identify a second test compound that modifies the odorant activity profile of a first test compound or composition, wherein the method comprises:
In some embodiments, the invention provides a computer-implemented method for identifying an odor associated with a test compound, wherein the method comprises:
In some embodiments, the one or more landmark odorant activity profiles are most similar to said first odorant activity profile if said measures of similarity are above a predetermined threshold.
In some embodiments, the invention provides a computer-implemented method for characterizing a compound as being associated with a particular odor, wherein the method comprises:
wherein steps (a), (b), (c), and (d) are implemented on a suitably programmed computer.
In some embodiments, the invention provides a computer-implemented method of classifying a test compound as having an odor using a classifier, wherein the method comprises:
(a) training a classifier for classifying a test compound as to an odor using a plurality of landmark odorant activity profiles stored in a database, wherein each said landmark odorant activity profile corresponds to a respective known compound having a known odor, and wherein each said landmark odorant activity profile is generated by the method described herein (e.g., a method for generating an odorant activity profile of a test compound or composition); and
(b) processing, using said classifier, a first odorant activity profile of said compound generated by the method described herein (e.g., a method for generating an odorant activity profile of a test compound or composition), to classify said compound as to a known odor;
wherein steps (a) and (b) are implemented on a suitably programmed computer.
In some embodiments, the invention provides a computer-implemented method of classifying a test compound as having an odor using a classifier, wherein the method comprises:
processing, using said classifier, a first odorant activity profile of said compound generated by the method described herein (e.g., a method for generating an odorant activity profile of a test compound or composition), to classify said test compound as to a known odor, wherein said classifier is trained according to a method comprising:
training said classifier for classifying a test compound as to an odor using a plurality of landmark odorant activity profiles stored in a database, wherein each said landmark odorant activity profile corresponds to a respective known compound having a known odor, and wherein each said landmark odorant activity profile is generated by the method described herein (e.g., a method for generating an odorant activity profile of a test compound or composition);
wherein the processing is implemented on a suitably programmed computer.
In some embodiments, the invention provides a computer-implemented method for associating one or more test compounds with an odor, wherein the method comprises:
(a) receiving a first odorant activity profile of a first test compound, wherein said first odorant activity profile is generated by the method described herein (e.g., a method for generating an odorant activity profile of a test compound or composition), and wherein said first test compound has a known odor;
(b) comparing said first odorant activity profile to a plurality of landmark odorant activity profiles stored in a database to determine a measure of similarity between said first odorant activity profile and each of said landmark odorant activity profile in said plurality of landmark odorant activity profiles, wherein each said landmark odorant activity profile corresponds to a respective known compound, and wherein each said landmark odorant activity profile is generated by the method described herein (e.g., a method for generating an odorant activity profile of a test compound or composition);
(c) determining one or more landmark odorant activity profiles most similar to said first odorant activity profile based on the measures of similarity determined in step (b); and
(d) characterizing the respective test compound corresponding to the one or more landmark odorant activity profiles determined to be most similar to said first odorant activity profile in step (c) as being associated with said known odor;
wherein steps (a), (b), (c), and (d) are implemented on a suitably programmed computer.
In some embodiments, the one or more landmark odorant activity profiles are most similar to said first odorant activity profile if said measures of similarity are above a predetermined threshold.
In some embodiments, the invention provides a computer-implemented method for characterizing one or more test compounds as being associated with a particular odor, wherein the method comprises:
In some embodiments, the invention provides a computer-implemented method of classifying one or more test compounds as having an odor using a classifier, wherein the method comprises:
processing, using said classifier, a first odorant activity profile generated by the method described herein (e.g., a method for generating an odorant activity profile of a test compound or composition), wherein said first odorant activity profile corresponds to a first test compound having a known odor, to classify one or more landmark odorant activity profiles of a plurality of landmark odorant activity profiles stored in a database as having said known odor, wherein said classifier is trained according to a method comprising:
training said classifier using said plurality of landmark odorant activity profiles for classifying said one or more landmark odorant activity profiles as having an odor, wherein each said landmark odorant activity profile corresponds to a respective known compound, and wherein each said landmark odorant activity profile is generated by the method described herein (e.g., a method for generating an odorant activity profile of a test compound or composition);
wherein the processing is implemented on a suitably programmed computer.
In some embodiments, the RNA of interest is siRNA or an antisense RNA. In some embodiments, the protein of interest comprises at least 2, 3, 4, 5, or 6 subunits.
In some embodiments, the protein of interest is an orphan receptor identified by a Human Gene Symbol as shown in Table 8 selected from the group consisting of BRS3, GPR42P, FPRL2, GPR81, OPN3, GPR52, GPR21, GPR78, GPR26, GPR37, GPR37L1, GPR63, GPR45, GPR83, GRCAe, GPR153, P2RY5, P2RY10, GPR174, GPR142, GPR139, ADMR, CMKOR1, LGR4, LGR5, LGR6, GPR85, GPR27, GPR173, CCRL2, MAS1, MAS1L, MRGPRE, MRGPRF, MRGPRG, MRGX3e, MRGX4e, GPR50, GPR87, TRAR3f, TRAR4, TRAR5, PNRe, GPR57g, GPR58, EBI2, GPR160, GPRe, GPR1, GPR101, GPR135, OPN5, GPR141, GPR146, GPR148, GPR149, GPR15, GPR150, GPR152, GPR161, GPR17, GPR171, GPR18, GPR19, GPR20, GPR22, GPR25, GPR31, GPR32, GPR33, GPR34, GPR55, GPR61, GPR62, GPR79h, GPR82, GPR84, GPR88, GPR92, P2RY8, GPR15, GPR64, GPR56, GPR115, GPR114, BAI1, BAI2, BAI3, CELSR1, CELSR2, CELSR3, EMR1, EMR2, GPR97, GPR110, GPR111, GPR112, GPR113, GPR116, MASS1, ELTD1, GPR123, GPR124, GPR125, GPR126, GPR128, GPR144, EMR3, EMR4b, CD97, LPHN2, LPHN3, LPHN1, GPR157, GPR51, GPR156, GPRC6A, GPRC5A, GPRC5B, GPRC5C, GPRC5D, GPR158 and GPR158L1.
In some embodiments, at least one subunit of the protein of interest is expressed by gene activation. In other embodiments, at least one subunit of the protein of interest is expressed from an introduced nucleic acid.
In some embodiments, the invention provides a method for generating a cell line, wherein the method comprises culturing a plurality of cell lines in a plurality of parallel cultures under the same culture conditions, and identifying a cell line that has at least one property that remains consistent over time.
In some embodiments, the plurality of parallel cultures comprises at least 50 cell cultures. In other embodiments, the plurality of parallel cultures comprises at least 100 cell cultures. In yet other embodiments, the plurality of parallel cultures comprises at least 200 cell cultures.
In some embodiments, the invention provides a protein or plurality of proteins that is/are an in vitro correlate for an in vivo protein of interest or a plurality of proteins of interest, wherein the in vitro correlate is predictive of the function or activity of the corresponding protein or plurality of proteins of interest expressed in vivo; wherein the in vitro correlate is a biologically active protein or plurality of proteins expressed under non-physiological conditions in vitro; wherein the in vitro correlate comprises at least one functional or pharmacological or physiological profile that corresponds to the in vivo protein or plurality of proteins of interest; and wherein at least 10% of compounds identified in a high throughput screening using said in vitro correlate are capable of having a therapeutic effect in vivo.
In some embodiments, the in vitro correlate comprises at least 2, 3, 4, 5, or 6 subunits. In some embodiments, at least one protein of the in vitro correlate comprises at least 2, 3, 4, 5, or 6 subunits. In some embodiments, the in vitro correlate comprises at a heteromultimer. In some embodiments, at least one protein of the in vitro correlate comprises a heteromultimer. In some embodiments, the protein or plurality of proteins of the in vitro correlate does not comprise a protein tag.
In some embodiments, the in vitro correlate is stably expressed in cells cultured in the absence of selective pressure. In some embodiments, the in vitro correlate is expressed in a cell line without causing cytotoxicity. In some embodiments, the in vitro correlate is expressed in a cell that does not endogenously express the protein or plurality of proteins.
In some embodiments, the protein or plurality of proteins may be produced by a cell of the present invention.
In some embodiments, the invention provides a cell expressing the protein or plurality of proteins as described hereinabove.
In some embodiments, the invention provides a cell line produced from the cell expressing the protein or plurality of proteins as described hereinabove.
In some embodiments, the invention provides a method for identifying a modulator of an in vivo protein of interest comprising the steps of
In some embodiments, the invention provides a modulator identified by the method described in the preceding paragraph.
In some embodiments, the cell described in any one of the preceding paragraphs is a differentiated cell. In some embodiments, the cell described in any one of the preceding paragraphs is a dedifferentiated cell. In further embodiments, the dedifferentiated cell is a stem cell selected from the group consisting of a multipotent stem cell, a pluripotent stem cell, an omnipotent stem cell, an induced pluripotent stem cell, an embryonic stem cell, a cancer stem cell, an organ-specific stem cell and a tissue-specific stem cell.
In specific embodiments, the invention provides a method for generating a stem cell comprising the step of: dedifferentiating a differentiated cell into a stem cell, wherein the differentiated cell is a cell described herein or a cell produced by a method described herein. In particular embodiments, the stem cell is selected from the group consisting of a multipotent stem cell, a pluripotent stem cell, an omnipotent stem cell, an induced pluripotent stem cell, an embryonic stem cell, a cancer stem cell, an organ-specific stem cell and a tissue-specific stem cell.
In certain embodiment, the invention provides for a method for generating a redifferentiated cell, comprising the steps of:
In certain embodiment, the invention provides for a method for generating a non-human organism comprising the steps of:
In other aspects, the invention provides for a redifferentiated cell produced by a method described herein.
In certain aspects, the invention provides for a non-human organism produced by a method described herein. In certain embodiments of such method, the organism is a mammal. In particular embodiments of such method, the mammal is a mouse.
In certain embodiments, cells that endogenously express the protein of interest can be isolated from a population of cells as described herein. Such isolated cells can be used with the methods and compositions described herein, such as the screening methods and panels
In certain aspects, provided herein are cells or cell lines stably expressing a sweet taste receptor comprising a sweet taste receptor T1R2 subunit and a sweet taste receptor T1R3 subunit, the expression of at least one of the subunits resulting from introduction of a nucleic acid encoding the subunit into a host cell or gene activation of a nucleic acid encoding the subunit already present in a host cell, the cell or cell line being derived from the host cell. Optionally, the cell or cell line may also be engineered to produce a G protein.
In specific embodiments, at least one sweet taste receptor subunit is expressed from a nucleic acid encoding that subunit that is introduced into the host cell. In other specific embodiments, at least one sweet taste receptor subunit is expressed from a nucleic acid present in the host cell by gene activation. In other specific embodiments, the host cell: a) is a eukaryotic cell; b) is a mammalian cell; c) does not express at least one subunit of a sweet taste receptor or a G protein endogenously; or d) any combination of (a), (b) and (c). In other specific embodiments, the host cell is an HEK-293 cell. In other specific embodiments, the sweet taste receptor a) is mammalian; b) is human; c) comprises subunits from different species; d) comprises one or more subunits that are chimeric; or e) any combination of (a)-(d). In other specific embodiments, the sweet taste receptor is functional. In other specific embodiments, the cell or cell line described herein, has a Z′ value of at least 0.3 in an assay. In other specific embodiments, the cell or cell line described herein has a Z′ value of at least 0.7 in an assay. In other specific embodiments, the cell or cell line described herein stably expresses the sweet taste receptor in culture media in the absence of selective pressure. In other specific embodiments, the sweet taste T1R2 receptor subunit is selected from the group consisting of:
In particular embodiments, the sweet taste receptor subunit T1R2 of the cell of cell line described herein is encoded by a nucleic acid selected from the group consisting of:
In other particular embodiments, the sweet taste receptor T1R3 subunit is encoded by a nucleic acid selected from the group consisting of:
In other particular embodiments, the G protein is selected from the group consisting of:
In other particular embodiments, the G protein is encoded by a nucleic acid selected from the group consisting of:
In certain aspects, provided herein are cells or cell lines stably expressing an umami taste receptor comprising an umami taste receptor T1R1 subunit and an umami taste receptor T1R3 subunit, the expression of at least one of the subunits resulting from introduction of a nucleic acid encoding the subunit into a host cell or gene activation of a nucleic acid encoding the subunit already present in a host cell, the cell or cell line being derived from the host cell. Optionally, the cell or cell line may also be engineered to produce a G protein.
In specific embodiments, at least one umami taste receptor subunit is expressed from a nucleic acid encoding that subunit that is introduced into the host cell. In other specific embodiments, at least one umami taste receptor subunit is expressed from a nucleic acid present in the host cell by gene activation. In other specific embodiments, the host cell: a) is a eukaryotic cell; b) is a mammalian cell; c) does not express at least one subunit of a umami taste receptor or a G protein endogenously; or d) any combination of (a), (b) and (c). In other specific embodiments, the host cell is an HEK-293 cell. In other specific embodiments, the umami taste receptor a) is mammalian; b) is human; c) comprises subunits from different species; d) comprises one or more subunits that are chimeric; or e) any combination of (a)-(d). In other specific embodiments, the umami taste receptor is functional. In other specific embodiments, the cell or cell line described herein, has a Z′ value of at least 0.3 in an assay. In other specific embodiments, the cell or cell line described herein has a Z′ value of at least 0.7 in an assay. In other specific embodiments, the cell or cell line described herein stably expresses the umami taste receptor in culture media in the absence of selective pressure. In other specific embodiments, the umami taste T1R1 receptor subunit is selected from the group consisting of:
In particular embodiments, the umami taste receptor subunit T1R1 of the cell of cell line described herein is encoded by a nucleic acid selected from the group consisting of:
In other particular embodiments, the umami taste receptor T1R3 subunit is encoded by a nucleic acid selected from the group consisting of:
In other particular embodiments, the G protein is selected from the group consisting of:
In other particular embodiments, the G protein is encoded by a nucleic acid selected from the group consisting of:
In one embodiment the cells and cell lines of this invention produce umami taste receptors or sweet taste receptors that are functional and physiologically relevant. They are, thus, useful to identify and selector modulators of the umami taste receptor or sweet taste receptor.
In another embodiment, the cells and cell lines of this invention stably express an umami taste receptor or a sweet taste receptor over 1 to 4 weeks, 1 to 9 months or any time in between.
In another embodiment, the cells and cell lines of the invention express an umami taste receptor or a sweet taste receptor at substantially the same level over a period of 1 to 4 weeks, 1 to 9 months or any time in between.
In particular embodiments, the expression levels are measured using a functional assay.
In other embodiments, this invention relates to modulators of umami taste receptors or sweet taste receptors identified using the cells and cell lines of this invention and the use of those modulators in modifying the tastes of products, including foods and pharmaceuticals, or in treating diseases, including diabetes and obesity, where umami taste receptors or sweet taste receptors are implicated.
In certain embodiments, provided herein is a method for producing the cell or cell line described herein (e.g., cell or cell line stably expressing a sweet taste receptor) comprising the steps of:
In certain embodiments, provided herein is a method for producing the cell or cell line described herein (e.g., a cell or cell line stably expressing an umami taste receptor) comprising the steps of:
In specific embodiments, the method described herein (e.g., method for producing a cell or cell line stably expressing a sweet taste receptor or an umami taste receptor) further comprises the step of generating a cell line from the cell isolated in step c). In other specific embodiments, the host cell:
In other embodiments, the method described herein (e.g., method for producing a cell or cell line stably expressing a sweet taste receptor or an umami taste receptor) further comprises the steps of:
In other embodiments, the method described herein (e.g., method for producing a cell or cell line stably expressing a sweet taste receptor or an umami taste receptor) further comprises the steps of:
In certain embodiments, measuring of the protein expression levels of the sweet taste receptor is carried out using a functional assay. In certain embodiments, the isolating step utilizes a fluorescence activated cell sorter (Beckman Coulter, Miami, Fla.).
In particular embodiments, provided herein is a method for identifying a modulator of a sweet taste receptor function comprising the step of exposing at least one cell or cell line described herein stably expressing a sweet taste receptor to at least one test compound and detecting a change in sweet taste receptor function. In particular embodiments, the modulator is selected from the group consisting of a sweet taste receptor inhibitor, a sweet taste receptor antagonist, a sweet taste receptor blocker, a sweet taste receptor activator, a sweet taste receptor agonist or a sweet taste receptor potentiator. In other particular embodiments, the sweet taste receptor is human sweet taste receptor. In other particular embodiments, the test compound is a small molecule, a chemical moiety, a polypeptide, or an antibody. In other particular compounds, the test compound is a library of compounds. In other particular embodiments, the library is a small molecule library, a combinatorial library, a peptide library or an antibody library. In specific embodiments, the modulator is selective for an enzymatically modified form of a sweet taste receptor.
In particular embodiments, provided herein is a method for identifying a modulator of an umami taste receptor function comprising the step of exposing at least one cell or cell line described herein stably expressing an umami taste receptor to at least one test compound and detecting a change in umami taste receptor function. In particular embodiments, the modulator is selected from the group consisting of an umami taste receptor inhibitor, an umami taste receptor antagonist, an umami taste receptor blocker, an umami taste receptor activator, an umami taste receptor agonist or an umami receptor potentiator. In other particular embodiments, the umami taste receptor is human umami taste receptor. In other particular embodiments, the test compound is a small molecule, a chemical moiety, a polypeptide, or an antibody. In other particular compounds, the test compound is a library of compounds. In other particular embodiments, the library is a small molecule library, a combinatorial library, a peptide library or an antibody library. In specific embodiments, the modulator is selective for an enzymatically modified form of an umami taste receptor.
In particular embodiments, provided herein is a modulator identified by the method described herein (e.g., a method for identifying a modulator of a sweet taste receptor function or an umami taste receptor function).
In particular embodiments, provided herein is a cell or cell line described herein (e.g., cell or cell line stably expressing a sweet taste receptor or an umami taste receptor) which is produced by the method described herein for producing such cell or cell line. In specific embodiments of such method, the cell (e.g., cell stably expressing a sweet taste receptor or an umami taste receptor) of such method has at least one desired property that is consistent over time, and such method comprises the steps of:
In certain embodiments, cells that endogenously express the sweet receptor, umami receptor, and/or G protein can be isolated from a population of cells as described herein. Such isolated cells can be used with the methods and compositions described herein, such as the screening methods and panels
According to one aspect of the present invention, a cell or cell line is engineered to stably express a bitter receptor. In some embodiments, the bitter receptor is expressed from a nucleic acid introduced into the cell or cell line. In some other embodiments, the bitter receptor is expressed from an endogenous nucleic acid by engineered gene activation. In some embodiments, the cell or cell line stably expresses at least one other bitter receptor. In some embodiments, the at least one other bitter receptor is endogenously expressed. In some other embodiments, the at least one other bitter receptor is expressed from a nucleic acid introduced into the cell or cell line. In still some other embodiments, the bitter receptor and the at least one other bitter receptor are expressed from separate nucleic acids introduced into the cell or cell line. In yet some other embodiments, the bitter receptor and the at least one other bitter receptor are both expressed form a single nucleic acid introduced into the cell or cell line.
In some embodiments, the cell or cell line stably expresses an endogenous G protein. In some other embodiments, the cell or cell line stably expresses a heterologous G protein. In still some other embodiments, the cell or cell line stably expresses both an endogenous G protein and a heterologous G protein. In some embodiments, the G protein is a heteromultimeric G protein comprising three different subunits. In some embodiments, at least one subunit of a heteromultimeric G protein is expressed from a nucleic acid introduced into the cell or cell line. In some other embodiments, at least two different subunits are expressed from different nucleic acids introduced into the cell or cell line. In still some other embodiments, at least two different subunits are expressed from the same nucleic acid introduced into the cell or cell line. In yet some other embodiments, the three different subunits are each expressed from the same nucleic acid introduced into the cell or cell line.
In some embodiments, the cell or the cells in the cell line are eukaryotic cells. In some other embodiments, the cell or the cells in the cell line are mammalian cells. In still some other embodiments, the cell or the cells in the cell line do not express an endogenous bitter receptor. In yet some other embodiments, the cell or the cells in the cell line are eukaryotic cells of a cell type that does not express an endogenous bitter receptor. In yet some other embodiments, the cell or the cells in the cell line are mammalian cells of a cell type that does not express an endogenous bitter receptor. In some embodiments, the cell or the cells in the cell line are human embryonic kidney 293T cells.
In some embodiments, the bitter receptor is mammalian. In some other embodiments, the bitter receptor is human. In still some other embodiments, the bitter receptor does not have a polypeptide tag at its amino terminus or carboxyl terminus. In yet some other embodiments, the bitter receptor is a mammalian bitter receptor that does not have a polypeptide tag at its amino terminus or carboxyl terminus. In yet some other embodiments, the bitter receptor is a human bitter receptor that does not have a polypeptide tag at its amino terminus or carboxyl terminus.
In some embodiments, the cell or cell line produces a Z′ value of at least 0.45 in an assay selected from the group consisting of: a cell-based assay, a fluorescent cell-based assay, a high throughput screening assay, a reporter cell-based assay, a G protein mediated cell-based assay, and a calcium flux cell-based assay. In some other embodiments, the cell or cell line produces a Z′ value of at least 0.5 in an assay selected from the group consisting of: a cell-based assay, a fluorescent cell-based assay, a high throughput screening assay, a reporter cell-based assay, a G protein mediated cell-based assay, and a calcium flux cell-based assay. In still some other embodiments, the cell or cell line produces a Z′ value of at least 0.6 in an assay selected from the group consisting of: a cell-based assay, a fluorescent cell-based assay, a high throughput screening assay, a reporter cell-based assay, a G protein mediated cell-based assay, and a calcium flux cell-based assay.
In some embodiments, the cell or cell line stably expresses the bitter receptor in culture media without antibiotics for at least 2 weeks. In some other embodiments, the cell or cell line stably expresses the bitter receptor in culture media without antibiotics for at least 4 weeks. In still some other embodiments, the cell or cell line stably expresses the bitter receptor in culture media without antibiotics for at least 6 weeks. In still some other embodiments, the cell or cell line stably expresses the bitter receptor in culture media without antibiotics for at least 3 months. In yet some other embodiments, the cell or cell line stably expresses the bitter receptor in culture media without antibiotics for at least 6 months. In yet some other embodiments, the cell or cell line stably expresses the bitter receptor in culture media without antibiotics for and at least 9 months.
In some embodiments, the bitter receptor comprises the amino acid sequence of any one of SEQ ID NOS: 77-101. In some other embodiments, the bitter receptor comprises an amino acid sequence that is at least 95% identical to the amino acid sequence of any one of SEQ ID NOS: 77-101. In still some other embodiments, the bitter receptor comprises an amino acid sequence encoded by a nucleic acid that hybridizes to a nucleic acid comprising the reverse-complement sequence of any one of SEQ ID NOS: 51-75 under stringent conditions. In yet some other embodiments, the bitter receptor comprises an amino acid sequence encoded by a nucleic acid that is an allelic variant of any one of SEQ ID NOS: 51-75.
In some embodiments, the bitter receptor comprises an amino acid sequence encoded by the nucleotide sequence of any one of SEQ ID NOS: 51-75. In some other embodiments, the bitter receptor comprises an amino acid sequence encoded by a nucleotide sequence that is at least 95% identical to any one of SEQ ID NOS: 51-75. In still some other embodiments, the bitter receptor comprises an amino acid sequence encoded by the sequence of a nucleic acid that hybridizes to a nucleic acid comprising the reverse-complement sequence of any one of SEQ ID NOS: 51-75 under stringent conditions. In yet some other embodiments, the bitter receptor comprises an amino acid sequence encoded by the sequence of a nucleic acid that is an allelic variant of any one of SEQ ID NOS: 51-75.
In some embodiments, the bitter receptor is a functional bitter receptor. In some embodiments, the cell or cell line has a change in the concentration of intracellular free calcium when contacted with isoproterenol. In some embodiments, the isoproterenol has an EC50 value of between about 1 nM and about 20 nM in a dose response curve conducted with the cell or cell line. In some embodiments, the cell or cell line has a signal to noise ratio of greater than 1.
According to another aspect of the present invention, there is provided a collection of cell or cell line that is engineered to stably express a bitter receptor. In some embodiments, the collection comprises two or more cell or cell lines, each cell or cell line stably expresses a different bitter receptor or an allelic variant thereof. In some embodiments, the collection additionally comprises a cell or cell line engineered to stably express a bitter receptor with a known ligand. In some embodiments, the allelic variant is a single-nucleotide polymorphism (SNP). In still some other embodiments, each of the cells or cell lines has a change in the concentration of intracellular free calcium when contacted with isoproterenol. In some embodiments, the isoproterenol has an EC50 value of between about 1 nM and about 20 nM in a dose response curve conducted with each cell or cell line.
In some embodiments, the cells or cell lines are matched to share the same physiological property to allow parallel processing. In some embodiments, the physiological property is growth rate. In some other embodiments, the physiological property is adherence to a tissue culture surface. In still some other embodiments, the physiological property is Z′ factor. In yet some other embodiments, the physiological property is expression level of the bitter receptor.
In some other embodiments of the present invention, the collection comprises two or more cell or cell lines, each cell or cell line stably expresses a same bitter receptor or an allelic variant thereof. In some embodiments, the collection additionally comprises a cell or cell line engineered to stably express a bitter receptor with a known ligand. In some embodiments, the allelic variant is a SNP. In still some other embodiments, each of the cells or cell lines has a change in the concentration of intracellular free calcium when contacted with isoproterenol. In some embodiments, the isoproterenol has an EC50 value of between about 1 nM and about 20 nM in a dose response curve conducted with each cell or cell line.
In some embodiments, the cells or cell lines are matched to share the same physiological property to allow parallel processing. In some embodiments, the physiological property is growth rate. In some other embodiments, the physiological property is adherence to a tissue culture surface. In still some other embodiments, the physiological property is Z′ factor. In yet some other embodiments, the physiological property is expression level of the bitter receptor.
According to still another aspect of the present invention, there is provided a method of producing a cell stably expressing a bitter receptor. The method comprises: a) introducing a nucleic acid encoding the bitter receptor into a plurality of cells; b) introducing a molecular beacon that detects expression of the bitter receptor into the plurality of cells provided in step (a); and c) isolating a cell that expresses the bitter receptor. In some embodiments, the method further comprises the step of generating a cell line from the cell isolated in step (c). In some embodiments, the generated cell line stably expresses the bitter receptor in culture media without any antibiotic selection for at least 2 weeks. In some other embodiments, the generated cell line stably expresses the bitter receptor in culture media without any antibiotic selection for at least 4 weeks. In still some other embodiments, the generated cell line stably expresses the bitter receptor in culture media without any antibiotic selection for at least 6 weeks. In still some other embodiments, the generated cell line stably expresses the bitter receptor in culture media without any antibiotic selection for at least 3 months. In yet some other embodiments, the generated cell line stably expresses the bitter receptor in culture media without any antibiotic selection for at least 6 months. In yet some other embodiments, the generated cell line stably expresses the bitter receptor in culture media without any antibiotic selection for at least 9 months.
In some embodiments, the cells that are used to produce a cell stably expressing a bitter receptor are eukaryotic cells. In some other embodiments, the cells that are used to produce a cell stably expressing a bitter receptor are mammalian cells. In still some other embodiments, the cells that are used to produce a cell stably expressing a bitter receptor do not express an endogenous bitter receptor. In yet some other embodiments, the cells that are used to produce a cell stably expressing a bitter receptor are eukaryotic cells of a cell type that does not express an endogenous bitter receptor. In yet some other embodiments, the cells that are used to produce a cell stably expressing a bitter receptor are mammalian cells of a cell type that does not express an endogenous bitter receptor. In some embodiments, the cells that are used to produce a cell stably expressing a bitter receptor are human embryonic kidney 293T cells.
In some embodiments, the bitter receptor is mammalian. In some other embodiments, the bitter receptor is human. In still some other embodiments, the bitter receptor does not have a polypeptide tag at its amino terminus or carboxyl terminus. In yet some other embodiments, the bitter receptor is a mammalian bitter receptor that does not have a polypeptide tag at its amino terminus or carboxyl terminus. In yet some other embodiments, the bitter receptor is a human bitter receptor that does not have a polypeptide tag at its amino terminus or carboxyl terminus.
In some embodiments, the bitter receptor comprises the amino acid sequence of any one of SEQ ID NOS: 77-101. In some other embodiments, the bitter receptor comprises an amino acid sequence that is at least 95% identical to the amino acid sequence of any one of SEQ ID NOS: 77-101. In still some other embodiments, the bitter receptor comprises an amino acid sequence encoded by a nucleic acid that hybridizes to a nucleic acid comprising the reverse-complement sequence of any one of SEQ ID NOS: 51-75 under stringent conditions. In yet some other embodiments, the bitter receptor comprises an amino acid sequence encoded by a nucleic acid that is an allelic variant of any one of SEQ ID NOS: 51-75.
In some embodiments, the bitter receptor comprises an amino acid sequence encoded by the nucleotide sequence of any one of SEQ ID NOS: 51-75. In some other embodiments, the bitter receptor comprises an amino acid sequence encoded by a nucleotide sequence that is at least 95% identical to any one of SEQ ID NOS: 51-75. In still some other embodiments, the bitter receptor comprises an amino acid sequence encoded by the sequence of a nucleic acid that hybridizes to a nucleic acid comprising the reverse-complement sequence of any one of SEQ ID NOS: 51-75 under stringent conditions. In yet some other embodiments, the bitter receptor comprises an amino acid sequence encoded by the sequence of a nucleic acid that is an allelic variant of any one of SEQ ID NOS: 51-75.
In some embodiments, the bitter receptor is a functional bitter receptor. In some embodiments, the cell isolated in step (c) has a change in the concentration of intracellular free calcium when contacted with isoproterenol. In some embodiments, the isoproterenol has an EC50 value of between about 1 nM and about 20 nM in a dose response curve conducted with the cell.
In some embodiments, the isolating utilizes a fluorescence activated cell sorter.
In some embodiments, the cells that are used to produce a cell stably expressing a bitter receptor stably express an endogenous G protein. In some other embodiments, the cells that are used to produce a cell stably expressing a bitter receptor stably express a heterologous G protein. In still some other embodiments of the present invention, the cells that are used to produce a cell stably expressing a bitter receptor stably express an endogenous G protein and a heterologous G protein.
In some embodiments, the method of producing a cell line expressing a bitter receptor further comprises introducing into the cells a nucleic acid encoding a G protein. In some embodiments, the nucleic acid encoding the G protein is introduced into the cells before introducing the nucleic acid encoding the bitter receptor. In some other embodiments, the nucleic acid encoding the G protein is introduced into the cells after introducing the nucleic acid encoding the bitter receptor. In still some other embodiments, the nucleic acid encoding the G protein is introduced simultaneously with introducing the nucleic acid encoding the bitter receptor. In some embodiments, the nucleic acid encoding the bitter receptor and the nucleic acid encoding the G protein are on a single vector. In some embodiment, the method further comprises introducing into the cells a molecular beacon that detects expression of the G protein before introducing the molecular beacon that detects expression of the bitter receptor. In some other embodiment, the method further comprises introducing into the cells a molecular beacon that detects expression of the G protein after introducing the molecular beacon that detects expression of the bitter receptor. In still some other embodiment, the method further comprises introducing into the cells a molecular beacon that detects expression of the G protein simultaneously with introducing the molecular beacon that detects expression of the bitter receptor. In some embodiments, the molecular beacon that detects expression of the bitter receptor and the molecular beacon that detects expression of the G protein are different molecular beacons. In some other embodiments, the molecular beacon that detects expression of the bitter receptor and the molecular beacon that detects expression of the G protein are a same molecular beacon. In some embodiments, the method further comprises isolating a cell that expresses the G protein before isolating the cell that expresses the bitter receptor, thereby isolating a cell that expresses both the bitter receptor and the G protein. In some other embodiments, the method further comprises isolating a cell that expresses the G protein after isolating the cell that expresses the bitter receptor, thereby isolating a cell that expresses both the bitter receptor and the G protein. In still some other embodiments, the method further comprises isolating a cell that expresses the G protein simultaneously with isolating the cell that expresses the bitter receptor, thereby isolating a cell that expresses both the bitter receptor and the G protein.
According to yet another aspect of the present invention, a method of identifying a modulator of a bitter receptor function comprises: a) exposing a cell or cell line that stably expresses a bitter receptor to a test compound; and b) detecting a change in a function of the bitter receptor. In some embodiments, the detecting utilizes an assay that measures intracellular free calcium. In some embodiments, the intracellular free calcium is measured using one or more calcium-sensitive fluorescent dyes, a fluorescence microscope, and optionally a fluorescent plate reader, wherein at least one fluorescent dye binds free calcium. In some other embodiments, the intracellular free calcium is monitored by real-time imaging using one or more calcium-sensitive fluorescent dyes, wherein at least one fluorescent dye binds free calcium.
In some embodiments, the cells or the cells in the cell line are eukaryotic cells. In some other embodiments, the cells or the cells in the cell line are mammalian cells. In still some other embodiments, the cells or the cells in the cell line do not express an endogenous bitter receptor. In yet some other embodiments, the cells or the cells in the cell line are eukaryotic cells of a cell type that does not express an endogenous bitter receptor. In yet some other embodiments, the cells or the cells in the cell line are mammalian cells of a cell type that does not express an endogenous bitter receptor. In some embodiments, the cells or the cells in the cell line are human embryonic kidney 293T cells.
In some embodiments, the bitter receptor comprises the amino acid sequence of any one of SEQ ID NOS: 77-101. In some other embodiments, the bitter receptor comprises an amino acid sequence that is at least 95% identical to the amino acid sequence of any one of SEQ ID NOS: 77-101. In still some other embodiments, the bitter receptor comprises an amino acid sequence encoded by a nucleic acid that hybridizes to a nucleic acid comprising the reverse-complement sequence of any one of SEQ ID NOS: 51-75 under stringent conditions. In yet some other embodiments, the bitter receptor comprises an amino acid sequence encoded by a nucleic acid that is an allelic variant of any one of SEQ ID NOS: 51-75.
In some embodiments, the bitter receptor comprises an amino acid sequence encoded by the nucleotide sequence of any one of SEQ ID NOS: 51-75. In some other embodiments, the bitter receptor comprises an amino acid sequence encoded by a nucleotide sequence that is at least 95% identical to any one of SEQ ID NOS: 51-75. In still some other embodiments, the bitter receptor comprises an amino acid sequence encoded by the sequence of a nucleic acid that hybridizes to a nucleic acid comprising the reverse-complement sequence of any one of SEQ ID NOS: 51-75 under stringent conditions. In yet some other embodiments, the bitter receptor comprises an amino acid sequence encoded by the sequence of a nucleic acid that is an allelic variant of any one of SEQ ID NOS: 51-75.
In some embodiments, the cell or cell line has a change in the concentration of intracellular free calcium. In some embodiments, the isoproterenol has an EC50 value of between 1 nM and 20 nM in a dose response curve conducted with the cell or cell line.
In some embodiments, the test compound is a bitter receptor inhibitor. In some embodiments, the method further comprises exposing the cell or cell line to a known agonist of the bitter receptor prior to the step of exposing the cell or cell line to the test compound. In some other embodiments, the method further comprises exposing the cell or cell line to a known agonist of the bitter receptor simultaneously with the step of exposing the cell or cell line to the test compound.
In some embodiments, the test compound is a bitter receptor agonist. In some embodiments, the method further comprises exposing the cell or cell line to a known inhibitor of the bitter receptor prior to the step of exposing the cell or cell line to the test compound. In some other embodiments, the method further comprises exposing the cell or cell line to a known inhibitor of the bitter receptor simultaneously with the step of exposing the cell or cell line to the test compound.
In some embodiments, the test compound is a small molecule. In some embodiments, the test compound is a chemical moiety. In some embodiments, the test compound is a polypeptide. In some embodiments, the test compound is an antibody. In some embodiments, the test compound is a food extract.
In a further aspect of the present invention, a method of identifying a modulator of bitter receptor function comprises a) exposing a collection of cell lines to a library of different test compounds, wherein the collection of cell lines comprises two or more cell lines, each cell line stably expressing a same bitter receptor or an allelic variant thereof, and wherein each cell line is exposed to one or more test compounds in the library; and b) detecting a change in a function of the bitter receptor or allelic variant thereof stably expressed by each cell line. In some embodiments, the detecting utilizes an assay that measures intracellular free calcium. In some embodiments, the intracellular free calcium is measured using one or more calcium-sensitive fluorescent dyes, a fluorescence microscope, and optionally a fluorescent plate reader, wherein at least one fluorescent dye binds free calcium. In some other embodiments, the intracellular free calcium is monitored by real-time imaging using one or more calcium-sensitive fluorescent dyes, wherein at least one fluorescent dye binds free calcium.
In some embodiments, the library is a small molecule library. In some embodiments, the library is a combinatorial library. In some embodiments, the library is a peptide library. In some embodiments, the library is an antibody library.
In some embodiments, the test compounds are small molecules. In some embodiments, the test compounds are chemical moieties. In some embodiments, the test compounds are polypeptides. In some embodiments, the test compounds are antibodies. In some embodiments, the test compounds are food extracts.
In some embodiments, the method further comprises exposing the collection of cell lines to a known bitter receptor agonist prior to or concurrently with step (a). In some other embodiments, the method further comprises exposing the collection of cell lines to a known bitter receptor inhibitor prior to or concurrently with step (a).
According to yet another aspect of the invention, a method of identifying a modulator of bitter receptor function comprises: a) exposing a collection of cell lines to a test compound, wherein the collection of cell lines comprises two or more cell lines, each cell line stably expressing a different bitter receptor or an allelic variant thereof; and b) detecting a change in a function of the bitter receptor stably expressed by each cell line. In some embodiments, the detecting utilizes an assay that measures intracellular free calcium. In some embodiments, the intracellular free calcium is measured using one or more calcium-sensitive fluorescent dyes, a fluorescence microscope, and optionally a fluorescent plate reader, wherein at least one fluorescent dye binds free calcium. In some other embodiments, the intracellular free calcium is monitored by real-time imaging using one or more calcium-sensitive fluorescent dyes, wherein at least one fluorescent dye binds free calcium.
In some embodiments, the test compound is a small molecule. In some embodiments, the test compound is a chemical moiety. In some embodiments, the test compound is a polypeptide. In some embodiments, the test compound is an antibody. In some embodiments, the test compound is a food extract.
In some embodiments, the method further comprises exposing the collection of cell lines to a known bitter receptor agonist prior to or concurrently with step (a). In some other embodiments, the method further comprises exposing the collection of cell lines to a known bitter receptor inhibitor prior to or concurrently with step (a).
According to yet another aspect of the invention, a cell engineered to stably express a bitter receptor at a consistent level over time is made by a method comprising the steps of: a) providing a plurality of cells that express mRNAs encoding the bitter receptor; b) dispersing the cells individually into individual culture vessels, thereby providing a plurality of separate cell cultures; c) culturing the cells under a set of desired culture conditions using automated cell culture methods characterized in that the conditions are substantially identical for each of the separate cell cultures, during which culturing the number of cells per separate cell culture is normalized, and wherein the separate cultures are passaged on the same schedule; d) assaying the separate cell cultures to measure expression of the bitter receptor at least twice; and e) identifying a separate cell culture that expresses the bitter receptor at a consistent level in both assays, thereby obtaining said cell.
In certain embodiments, cells that endogenously express a bitter receptor can be isolated from a population of cells as described herein. Such isolated cells can be used with the methods and compositions described herein, such as the screening methods and panels
In certain embodiments, the invention provides a method for defining the chemical space of compounds that modulate a protein complex, wherein the method comprises:
In certain embodiments, the invention provides a method for identifying a structural commonality among compounds that modulate a protein complex, wherein the method comprises:
In certain embodiments, the invention provides a method for identifying a structural commonality among compounds that modulates a protein complex, wherein the method comprises:
In more specific embodiments, said molecular representation of each said compounds further comprises physicochemical data of the respective compound, spatial data of the respective compound, topological data of the respective compound, or a combination thereof.
In more specific embodiments, the protein complex is a bitter receptor.
In more specific embodiments, said constructing said SAR model for each said compounds comprises applying a regression method to determine a relationship between said molecular representation of the respective compound and said activity profile of the respective compound.
In more specific embodiments, said SAR model for each said compounds is independently a receptor-dependent free energy force field QSAR (FEFF-QSAR) model, a receptor-independent three-dimensional QSAR (3D-QSAR), or a receptor-dependent or receptor-independent four-dimensional QSAR (4D-QSAR).
In certain aspects, provided herein are kits that can be used in the methods described herein. In particular, provided herein are kits comprising one or more cells or cell lines stably expressing one or more complex targets. In certain embodiments, kits provided herein comprise one or more signaling probes described herein. In particular embodiments, a kit may comprise one or more vectors encoding one or more complex targets. In specific embodiments, a kit comprises one or more dyes for use in functional cell-based assays (e.g., calcium flux assay, membrane potential assay) to screen and select cells stably expressing one or more complex targets.
In certain aspects, provided herein are kits comprising one or more containers filled with one or more of the reagents and/or cells described herein, such as one or more cells, vectors, and/or signaling probes provided herein. Optionally associated with such container(s) can be a notice containing instructions for using the components in the kit.
Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. Exemplary methods and materials are described below, although methods and materials similar or equivalent to those described herein can also be used in the practice or testing of the present invention. In case of conflict, the present specification, including definitions, will control.
All publications and other references mentioned herein are incorporated by reference in their entirety. Although a number of documents are cited herein, this citation does not constitute an admission that any of these documents forms part of the common general knowledge in the art.
Throughout this specification and claims, the word “comprise,” or variations such as “comprises” or “comprising” will be understood to imply the inclusion of a stated integer or group of integers but not the exclusion of any other integer or group of integers. Unless otherwise required by context, singular terms shall include pluralities and plural terms shall include the singular. The materials, methods, and examples are illustrative only and not intended to be limiting.
In order that the present invention may be more readily understood, certain terms are first defined. Additional definitions are set forth throughout the detailed description.
The term “stable” or “stably expressing” is meant to distinguish the cells and cell lines of the invention from cells that transiently express proteins as the terms “stable expression” and “transient expression” would be understood by a person of skill in the art. As used herein, “not expressed in a cell of the same type” includes not expressed in any other cell of the same type, or in at least 99% of the cells of the same type, or in at least 99% of the cells of the same type, or in at least 98% of the cells of the same type, or in at least 97% of the cells of the same type, or in at least 96% of the cells of the same type, or in at least 95% of the cells of the same type, or in at least 94% of the cells of the same type, or in at least 93% of the cells of the same type, or in at least 92% of the cells of the same type, or in at least 91% of the cells of the same type, or in at least 90% of the cells of the same type, or in at least 85% of the cells of the same type, or in at least 80% of the cells of the same type, or in at least 75% of the cells of the same type, or in at least 70% of the cells of the same type, or in at least 60% of the cells of the same type, or in at least 50% of the cells of the same type.
As used herein, a “functional” RNA or protein of interest is one that has a signal to noise ratio greater than 1:1 in a cell based assay. In some embodiments, a “functional” RNA or protein of interest has a signal to noise ratio is greater than 2. In some embodiments, a “functional” RNA or protein of interest has a signal to noise ratio is greater than 3. In some embodiments, a “functional” RNA or protein of interest has a signal to noise ratio is greater than 4. In some embodiments, a “functional” RNA or protein of interest has a signal to noise ratio is greater than 5. In some embodiments, a “functional” RNA or protein of interest has a signal to noise ratio is greater than 10. In some embodiments, a “functional” RNA or protein of interest has a signal to noise ratio is greater than 15. In some embodiments, a “functional” RNA or protein of interest has a signal to noise ratio is greater than 20. In some embodiments, a “functional” RNA or protein of interest has a signal to noise ratio is greater than 30. In some embodiments, a “functional” RNA or protein of interest has a signal to noise ratio is greater than 40. In some embodiments, a signal to noise ratio does not vary by more than 10%, 20%, 30%, 40%, 50%, 60% or 70%. In some embodiments, a signal to noise ratios does not vary by more than 10%, 20%, 30%, 40%, 50%, 60% or 70% from experiment to experiment. In some embodiments, a signal to noise ratio does not vary by more than 1%, 2%, 3%, 4%, 5%, 6%, 7%, 8%, 9% or 10% from experiment to experiment. In some embodiments, a signal to noise ratios does not vary by more than 10%, 20%, 30%, 40%, 50%, 60% or 70% between 2 to 20 different replicates of an experiment. In some embodiments, a signal to noise ratio does not vary by more than 1%, 2%, 3%, 4%, 5%, 6%, 7%, 8%, 9% or 10% between 2 to 20 different replicates of an experiment. In some embodiments, a signal to noise ratios does not vary by more than 10%, 20%, 30%, 40%, 50%, 60% or 70% for cells that are tested from 1 to 5, 5 to 10, 10 to 15, 15 to 20, 20 to 25, 25 to 30, 30 to 40, 40 to 50, 50 to 60, 60 to 70 or more than 70 days wherein the cells are in continuous culture. In some embodiments, a signal to noise ratio does not vary by more than 1%, 2%, 3%, 4%, 5%, 6%, 7%, 8%, 9% or 10% for cells that are tested from 1 to 5, 5 to 10, 10 to 15, 15 to 20, 20 to 25, 25 to 30, 30 to 40, 40 to 50, 50 to 60, 60 to 70 or more than 70 days wherein the cells are in continuous culture. In some embodiments, a functional protein or RNA of interest has one or more of the biological activities of the naturally occurring or endogenously expressed protein or RNA.
The term “cell line” or “clonal cell line” refers to a population of cells that is the progeny of a single original cell. As used herein, cell lines are maintained in vitro in cell culture and may be frozen in aliquots to establish banks of clonal cells.
The term “stringent conditions” or “stringent hybridization conditions” describe temperature and salt conditions for hybridizing one or more nucleic acid probes to a nucleic acid sample and washing off probes that have not bound specifically to target nucleic acids in the sample. Stringent conditions are known to those skilled in the art and can be found in, for example, Current Protocols in Molecular Biology, John Wiley & Sons, N.Y. (1989), 6.3.1-6.3.6. Aqueous and nonaqueous methods are described in the Protocols and either can be used. One example of stringent hybridization conditions is hybridization in 6×SSC at about 45° C., followed by at least one wash in 0.2×SSC, 0.1% SDS at 60° C. Another example of stringent hybridization conditions is hybridization in 6×SSC at about 45° C., followed by at least one wash in 0.2×SSC, 0.1% SDS at 65° C. Stringent hybridization conditions also include hybridization in 0.5M sodium phosphate, 7% SDS at 65° C., followed by at least one wash at 0.2×SSC, 1% SDS at 65° C.
The phrase “percent identical” or “percent identity” in connection with amino acid and/or nucleic acid sequences refers to the similarity between at least two different sequences. The percent identity can be determined by standard alignment algorithms, for example, the Basic Local Alignment Tool (BLAST) described by Altshul et al. ((1990) J. Mol. Biol., 215: 403-410); the algorithm of Needleman et al. ((1970) J. Mol. Biol., 48: 444-453); or the algorithm of Meyers et al. ((1988) Comput. Appl. Biosci., 4: 11-17). A set of parameters may be the Blosum 62 scoring matrix with a gap penalty of 12, a gap extend penalty of 4, and a frameshift gap penalty of 5. The percent identity between two amino acid or nucleotide sequences can also be determined using the algorithm of E. Meyers and W. Miller ((1989) CABIOS, 4:11-17) that has been incorporated into the ALIGN program (version 2.0), using a PAM120 weight residue table, a gap length penalty of 12 and a gap penalty of 4. The percent identity is usually calculated by comparing sequences of similar length.
Protein analysis software matches similar amino acid sequences using measures of similarity assigned to various substitutions, deletions and other modifications, including conservative amino acid substitutions. For instance, the GCG Wisconsin Package (Accelrys, Inc.) contains programs such as “Gap” and “Bestfit” that can be used with default parameters to determine sequence identity between closely related polypeptides, such as homologous polypeptides from different species or between a wild type protein and a mutein thereof. See, e.g., GCG Version 6.1. Polypeptide sequences also can be compared using FASTA using default or recommended parameters. A program in GCG Version 6.1. FASTA (e.g., FASTA2 and FASTA3) provides alignments and percent sequence identity of the regions of the best overlap between the query and search sequences (Pearson, Methods Enzymol. 183:63-98 (1990); Pearson, Methods Mol. Biol. 132:185-219 (2000)).
The length of polypeptide sequences compared for identity will generally be at least about 16 amino acid residues, usually at least about 20 residues, more usually at least about 24 residues, typically at least about 28 residues, and preferably more than about 35 residues. The length of a DNA sequence compared for identity will generally be at least about 48 nucleic acid residues, usually at least about 60 nucleic acid residues, more usually at least about 72 nucleic acid residues, typically at least about 84 nucleic acid residues, and preferably more than about 105 nucleic acid residues.
The phrase “substantially as set out,” “substantially identical” or “substantially homologous” in connection with an amino acid or nucleotide sequence means that the relevant amino acid or nucleotide sequence will be identical to or have insubstantial differences (e.g., conserved amino acid substitutions or nucleic acids encoding such substitutions) in comparison to the comparator sequences. Insubstantial differences include minor amino acid changes, such as 1 or 2 substitutions in a 50 amino acid sequence of a specified region and the nucleic acids that encode those sequences.
Modulators include any substance or compound that alters an activity of a protein of interest, for example, a taste receptor (e.g., bitter taste receptor, umami taste receptor, or sweet taste receptor). The modulator can be an agonist (potentiator or activator) or antagonist (inhibitor or blocker), including partial agonists or antagonists, selective agonists or antagonists and inverse agonists, and can also be an allosteric modulator. A substance or compound is a modulator even if its modulating activity changes under different conditions or concentrations or with respect to different forms of a protein of interest, for example, a taste receptor (e.g., bitter taste receptor, umami taste receptor, or sweet taste receptor). In other aspects, a modulator may change the ability of another modulator to affect the function of a protein of interest, for example, a taste receptor (e.g., bitter taste receptor, umami taste receptor, or sweet taste receptor). In specific embodiments, a modulator can alter the structure, conformation, biochemical or biophysical properties or functionality of a taste receptor (e.g., bitter taste receptor, umami taste receptor, or sweet taste receptor), either positively or negatively.
The terms “potentiator”, “agonist” or “activator” refer to a compound or substance that increases one or more activities of a protein of interest, for example, a taste receptor (e.g., bitter taste receptor, umami taste receptor, or sweet taste receptor). In specific embodiments, terms “potentiator”, “agonist” or “activator” in the context of taste receptors, refer to a compound or substance that increases the downstream signaling response associated with the taste receptor (e.g., bitter taste receptor, umami taste receptor, or sweet taste receptor). In particular embodiments, increasing taste receptor activity can result in change in the amount or distribution of an intracellular molecule or the activity of an enzyme which is part of the intracellular signaling pathway for the bitter receptor. Examples of the intracellular molecule include, but are not limited to, free calcium, cyclic adenosine monophosphate (cAMP), inositol mono-, di- or tri-phosphate. Examples of the enzyme include, but are not limited to, adenylate cyclase, phospholipase-C, G-protein coupled receptor kinase.
The terms “inhibitor”, “antagonist” or “blocker” refer to a compound or substance that decreases or blocks one or more activities of a protein of interest, for example, a taste receptor (e.g., bitter taste receptor, umami taste receptor, or sweet taste receptor). In specific embodiments, terms “inhibitor”, “antagonist” or “blocker” in the context of taste receptors, refer to a compound or substance that decreases the downstream signaling response associated with the taste receptor (e.g., bitter taste receptor, umami taste receptor, or sweet taste receptor). In particular embodiments, decreasing taste receptor activity can result in change in the amount or distribution of an intracellular molecule or the activity of an enzyme which is part of the intracellular signaling pathway for the bitter receptor. Examples of the intracellular molecule include, but are not limited to, free calcium, cyclic adenosine monophosphate (cAMP), inositol mono-, di- or tri-phosphate. Examples of the enzyme include, but are not limited to, adenylate cyclase, phospholipase-C, G-protein coupled receptor kinase.
A sweet taste receptor is a protein that is present in many mammalian tissues, including epithelial cells of the mouth, the lung and the intestine. Without being bound by theory, we believe that sweet taste receptor dysregulation or dysfunction may be linked to many disease states including diabetes and obesity.
The phrase “functional sweet taste receptor” refers to a sweet taste receptor that comprises at least a T1R2 and a T1R3 subunit and that responds to a known activator, such as fructose, glucose, sucrose, monellin/miraculin, mogroside, steviva, rebaudioside A, saccharin, asparatame, sodium cyclamate, sucralose, sorbital, acesulfame K or Gymnema Sylvestre, or a known inhibitor, such as methyl 4,6-dichloro-4,6-dideoxy-α-D-galactopyranoside (MAD-diCl-Gal), PNP/lactisole (may act differently at different concentrations), Gymnemic acid 1, hoduloside, Ziziphin, and gurmarin in a similar way (i.e. at least 50%, 60%, 70%, 80% 90% and 95% the same) as a sweet taste receptor produced in a cell that normally expresses that receptor without genetic engineering of the cell to produce it. Sweet taste receptor behavior can be determined by, for example, physiological activities or pharmacological responses. Physiological activities include, but are not limited to activation of a G protein and associated downstream signaling. Pharmacological responses include, but are not limited to, inhibition, activation, and modulation of the receptor. Such responses can, for example, be assayed in an assay that monitors intracellular calcium release from the endoplasmic reticulum upon Gαq protein activation by an activated sweet taste receptor.
An umami taste receptor is a protein that is present in many mammalian tissues, including epithelial cells of the mouth, the lung and the intestine. Without being bound by theory, we believe that umami taste receptor dysregulation or dysfunction may be linked to many disease states including diabetes and obesity.
The phrase “functional umami taste receptor” refers to an umami taste receptor that comprises at least a T1R1 and a T1R3 subunit and that responds to a known activator, such as monosodium glutamate (MSG), or a known inhibitor, such as lactisole, which is known to act as an umami taste receptor inhibitor at specific concentrations, or PMP (2-(4-methoxyphenoxy)-propionic acid) in a similar way (i.e. at least 50%, 60%, 70%, 80% 90% and 95% the same) as an umami taste receptor produced in a cell that normally expresses that receptor without genetic engineering of the cell to produce it. Umami taste receptor behavior can be determined by, for example, physiological activities or pharmacological responses. Physiological activities include, but are not limited to activation of a G protein and associated downstream signaling. Pharmacological responses include, but are not limited to, inhibition, activation, and modulation of the receptor. Such responses can, for example, be assayed in an assay that monitors intracellular calcium release from the endoplasmic reticulum upon Gαq protein activation by an activated umami taste receptor.
The phrase “functional bitter receptor” refers to a bitter receptor that responds to a known activator or a known inhibitor in substantially the same way as the bitter receptor in a cell that normally expresses the bitter receptor without engineering. Bitter receptor behavior can be determined by, for example, physiological activities and pharmacological responses. Physiological activities include, but are not limited to, the sense of bitter taste. Pharmacological responses include, but are not limited to, a change in the amount or distribution of an intracellular molecule or the activity of an enzyme which is part of the intracellular signaling pathway for the bitter receptor when a bitter receptor is contacted with a modulator. For example, a pharmacological response may include an increase in intracellular free calcium when the bitter receptor is activated, or a decrease in intracellular free calcium when the bitter receptor is blocked.
The term “bitter receptor”, as used herein, refers to any one of the G protein coupled receptors that is expressed at the surface of a taste receptor cell and that mediates bitter taste perception via secondary messenger pathways.
A “heterologous” or “introduced” protein of interest, for example, a taste receptor subunit (e.g., bitter taste receptor subunit, umami taste receptor subunit, or sweet taste receptor subunit) or G protein, means that the protein of interest, for example, a taste receptor subunit (e.g., bitter taste receptor subunit, umami taste receptor subunit, or sweet taste receptor subunit) or G protein is encoded by a nucleic acid introduced into a host cell.
A “gene activated” protein of interest, for example, a taste receptor subunit (e.g., bitter taste receptor subunit, umami taste receptor subunit, or sweet taste receptor subunit) or G protein, means that an endogenous nucleic acid encoding the subunit or protein has been activated for expression by the introduction and operative linking of an expression control sequence to that nucleic acid.
The invention provides for the first time novel cells and cell lines produced from the cells that meet the urgent need for cells that stably express a functional RNA of interest or a functional protein of interest, including complex proteins such as heteromultimeric proteins and proteins for which no ligand is known. The cells and cell lines of the invention are suitable for any use in which consistent, functional expression of an RNA or protein of interest are desirable. Applicants have produced cell lines meeting this description for a variety of proteins, both single subunit and heteromultimeric (including heterodimeric and proteins with more than two different subunits), including membrane proteins, cytosolic proteins and secreted proteins, as well as various combinations of these.
Examples of a protein of interest include, but are not limited to: receptor (e.g., cytokine receptor, immunoglobulin receptor family member, ligand-gated ion channel, protein kinase receptor, G-protein coupled receptor (GPCR), nuclear hormone receptor and other receptors), signaling molecule (e.g., cytokine, growth factor, peptide hormone, chemokine, membrane-bound signaling molecule and other signaling molecules), kinase (e.g., amino acid kinase, carbohydrate kinase, nucleotide kinase, protein kinase and other kinases), phosphatase (e.g., carbohydrate phosphatase, nucleotide phosphatase, protein phosphatase and other phosphatases), protease (e.g., aspartic protease, cysteine protease, metalloprotease, serine protease and other proteases), regulatory molecule (e.g., G-protein modulator, large G-protein, small GTPase, kinase modulator, phosphatase modulator, protease inhibitor and other enzyme regulator), calcium binding protein (e.g., annexin, calmodulin related protein and other select calcium binding proteins), transcription factor (e.g., nuclear hormone receptor, basal transcription factor, basic helix-loop-helix transcription factor, creb transcription factor, hmg box transcription factor, homeobox transcription factor, other transcription factor, transcription cofactor and zinc finger transcription factor), nucleic acid binding protein (e.g., helicase, DNA ligase, DNA methyltransferase, RNA methyltransferase, double-stranded DNA binding protein, endodeoxyribonuclease, replication origin binding protein, reverse transcriptase, ribonucleoprotein, ribosomal protein, single-stranded DNA-binding protein, centromere DNA-binding protein, chromatin/chromatin-binding protein, DNA glycosylase, DNA photolyase, DNA polymerase processivity factor, DNA strand-pairing protein, DNA topoisomerase, DNA-directed DNA polymerase, DNA-directed RNA polymerase, damaged DNA-binding protein, histone, primase, endoribonuclease, exodeoxyribonuclease, exoribonuclease, translation elongation factor, translation initiation factor, translation release factor, mRNA polyadenylation factor, mRNA splicing factor, other DNA-binding proteins, other RNA-binding proteins and other nucleic acid binding proteins), ion channel (e.g., anion channel, ligand-gated ion channel, voltage-gated ion channel and other ion channels), transporter (e.g., cation transporter, ATP-binding cassette (ABC) transporter, amino acid transporter, carbohydrate transporter and other transporters), transfer/carrier protein (e.g., apolipoprotein, mitochondrial carrier protein and other transfer/carrier proteins), cell adhesion molecule (e.g., cam family adhesion molecule, cadherin and other cell adhesion molecule), cytoskeletal protein (e.g., actin and actin related protein, actin binding motor protein, non-motor actin binding protein, other actin family cytoskeletal protein, intermediate filament, microtubule family cytoskeletal protein and other cytoskeletal proteins), extracellular matrix (e.g., extracellular matrix glycoprotein, extracellular matrix linker protein, extracellular matrix structural protein and other extracellular matrix), cell junction protein (e.g., gap junction protein, tight junction protein and other cell junction proteins), synthase, synthetase, oxidoreductase (e.g., dehydrogenase, hydroxylase, oxidase, oxygenase, peroxidase, reductase and other oxidoreductase), transferase (e.g., methyltransferase, acetyltransferase, acyltransferase, glycosyltransferase, nucleotidyltransferase, phosphorylase, transaldolase, transaminase, transketolase and other transferase), hydrolyase (e.g., deacetylase, deaminase, esterase, galactosidase, glucosidase, glycosidase, lipase, phosphodiesterase, pyrophosphatase, amylase and other hydrolase), lysase (e.g., adenylate cyclase, guanylate cyclase, aldolase, decarboxylase, dehydratase, hydratase and other lyases), isomerase (e.g., epimerase/racemase, mutase and other isomerases), ligase (e.g., DNA ligase, ubiquitin-protein ligase and other ligases), defense/immunity protein (e.g., antibacterial response protein, complement component, immunoglobulin, immunoglobulin receptor family member, major histocompatibility complex antigen and other defense and immunity proteins), membrane traffic protein (e.g., membrane traffic regulatory protein, SNARE protein, vesicle coat protein and other membrane traffic proteins), chaperone (e.g., chaperonin, hsp 70 family chaperone, hsp 90 family chaperone and other chaperones), viral protein (e.g., viral coat protein and other viral proteins), myelin protein, other miscellaneous function protein, storage protein, structural protein, surfactant, and transmembrane receptor regulatory/adaptor protein. Other examples of proteins and their functions include those identified in Paul D. Thomas, Michael J. Campbell, Anish Kejariwal, Huaiyu Mi, Brian Karlak, Robin Daverman, Karen Diemer, Anushya Muruganujan, Apurva Narechania. 2003. PANTHER: a library of protein families and subfamilies indexed by function. Genome Res., 13: 2129-2141, which is incorporated herein by reference in its entirety.
Examples of GPCRs include, but are not limited to:
Class A GPCRs, including, but not limited to:
5-Hydroxytryptamine receptors (e.g., HTR1A, HTR1B, HTR1D, HTR1E, HTR1F, HTR2A, HTR2B, HTR2C, HTR4, HTR5A, HTR6, and HTR7), Muscarinic acetylcholine receptors (e.g., CHRM1, CHRM2, CHRM3, CHRM4, and CHRM5), Adenosine receptors (e.g., ADORA1, ADORA2A, ADORA2B, and ADORA3), Alpha-Adrenoceptors (e.g., ADRA1A, ADRA1B, ADRA1D, ADRA2A, ADRA2B, and ADRA2C), Beta-Adrenoceptors (e.g., ADRB1, ADRB2, and ADRB3), Anaphylatoxin receptors (e.g., GPR77, C5R1, and C3AR1), Angiotensin receptors (e.g., AGTR1 and AGTR2), Apelin receptor (e.g., AGTRL1), Bile acid receptor (e.g., GPBAR1), Bombesin receptors (e.g., NMBR, GRPR, and BRS3), Bradykinin receptors (e.g., BDKRB1 and BDKRB2), Cannabinoid receptors (e.g., CNR1 and CNR2), Chemokine receptors-Interleukin (e.g., 8IL8RA and IL8RB), Chemokine receptors (e.g., CXCR3, CXCR4, CXCR5, CCR1, CCR2, CCR3, CCR4, CCR5, CCR6, CCR7, CCR8, CCR9, CCR10, CX3CR1, XCR1, and CXCR6), Cholecystokinin receptors (e.g., CCKAR and CCKBR), Dopamine receptors (e.g., DRD1, DRD2, DRD3, DRD4, and DRD5), Endothelin receptors (e.g., EDNRA and EDNRB), Estrogen receptor (e.g., GPER), Formylpeptide receptors (e.g., FPR2, FPR3, and FPR1), Free fatty acid receptors (e.g., FFAR1, FFAR3, FFAR2, and GPR42), Galanin receptors (e.g., GALR1, GALR2, and GALR3), Ghrelin receptor (e.g., GHSR), Glycoprotein hormone receptors (e.g., FSHR, LHCGR, and TSHR), Gonadotrophin-releasing hormone receptors (e.g., GNRHR and GNRHR2), Histamine receptors (e.g., HRH1, HRH2, HRH3, and HRH4), KiSS1-derived peptide receptor (e.g., KISS1R), Leukotriene receptors (e.g., LTB4R2, FPRL1, OXER1, LTB4R, CYSLTR1, and CYSLTR2), Lysophospholipid receptors (e.g., LPAR1, LPAR2, LPAR3, S1PR1, S1PR2, S1PR3, S1PR4, and S1PR5), Melanin-concentrating hormone receptors (e.g., MCHR1 and MCHR2), Melanocortin receptors (e.g., MC1R, MC2R, MC3R, MC4R, and MC5R), Melatonin receptors (e.g., MTNR1A and MTNR1B), Motilin receptor (e.g., MLNR), Neuromedin U receptors (e.g., NMUR1 and NMUR2), Neuropeptide FF/neuropeptide AF receptors (e.g., NPFFR1 and NPFFR2), Neuropeptide S receptor (e.g., NPSR1), Neuropeptide W/neuropeptide B receptors (e.g., NPBWR1 and NPBWR2), Neuropeptide Y receptors (e.g., NPY1R, NPY2R, PPYR1, and NPY5R), Neurotensin receptors (e.g., NTSR1 and NTSR2), Nicotinic acid receptor family (e.g., GPR109B, GPR109A, and GPR81), Non-signalling 7TM chemokine-binding proteins (e.g., DARC, CCBP2, and CCRL1), Opioid receptors (e.g., OPRM1, OPRD1, OPRK1, and OPRL1), Orexin receptors (e.g., HCRTR1 and HCRTR2), P2Y receptors (e.g., P2RY1, P2RY2, P2RY4, P2RY6, P2RY11, P2RY12, P2RY14, and P2RY13), Peptide P518 receptor (e.g., QRFPR), Platelet-activating factor receptor (e.g., PTAFR), Prokineticin receptors (e.g., PROKR1 and PROKR2), Prolactin-releasing peptide receptor (e.g., PRLHR), Prostanoid receptors (e.g., PTGDR, PTGER1, PTGER2, PTGER3, PTGER4, PTGFR, PTGIR, TBXA2R, and GPR44), Protease-activated receptors (e.g., Thrombin (F2R)), Protease-activated receptors (e.g., F2RL1, F2RL2, and F2RL3), Relaxin family peptide receptors (e.g., RXFP1, RXFP2, RXFP3, and RXFP4), Somatostatin receptors (e.g., SSTR2, SSTR5, SSTR3, SSTR1, and SSTR4), Tachykinin receptors (e.g., TACR1, TACR2, and TACR3), Thyrotropin-releasing hormone receptor (e.g., TRHR), Trace amine receptor (e.g., TAAR1), Urotensin receptor (e.g., UTS2R), Vasopressin and oxytocin receptors (e.g., AVPR1A, AVPR2, AVPR1B, and OXTR), Class A Orphans (e.g., GPR82, GPR182, CCRL2, CMKLR1, CMKOR1, GPR183, GPR1, GPR3, GPR4, GPR6, GPR12, GPR15, GPR17, GPR18, GPR19, GPR20, GPR21, GPR22, GPR23, GPR25, GPR26, GPR27, GPR31, GPR32, GPR33, GPR34, GPR35, GPR37, GPR37L1, GPR39, GPR45, GPR50, GPR52, GPR55, GPR61, GPR62, GPR63, GPR65, GPR68, GPR75, GPR78, GPR79, GPR83, GPR84, GPR85, GPR87, GPR88, GPR92, GPR101, GPR119, GPR120, GPR132, GPR135, GPR139, GPR141, GPR142, GPR146, GPR148, GPR149, GPR150, GPR151, GPR152, GPR153, GPR160, GPR161, GPR171, GPR173, GPR174, GPR162, LGR4, LGR5, LGR6, MAS1, MAS1L, MRGPRD, MRGPRE, MRGPRF, MRGPRG, MRGPRX1, MRGPRX2, MRGPRX3, MRGPRX4, OPN3, OPN5, OXGR1, P2RY10, P2RY5, P2RY8, SUCNR1, TAAR2, TAAR3, TAAR5, TAAR6, TAAR8, TAAR9, and GPR42);
Class B GPCRs, including, but not limited to:
Calcium-sensing receptors (e.g., CASR and GPRC6A), GABA-B receptors (e.g., GABBR1 and GABBR2), GPRC5 receptors (e.g., GPRC5A, GPRC5B, GPRC5C, and GPRC5D), Metabotropic glutamate receptors (e.g., GRM1, GRM2, GRM3, GRM4, GRM5, GRM6, GRM7, and GRM8), Class C Orphans (e.g., GPR156, GPR158, GPR179, GPRC5A, GPRC5B, GPRC5C, and GPRC5D);
Class C GPCRs, including, but not limited to:
Calcitonin receptors (e.g., CALCR/CT, AMY1, AMY2, AMY3, CALCRL, CGRP, AM1, and AM2), Corticotropin-releasing factor receptors (e.g., CRHR1 and CRHR2), Glucagon receptor family (e.g., GCGR, GLP1R, GLP2R, GIPR, SCTR, and GHRHR), Parathyroid hormone receptors (e.g., PTH1R and PTHR2), VIP and PACAP receptors (e.g., ADCYAP1R1, VIPR1, and VIPR2), Class B Orphans (e.g., BAI1, BAI2, BAI3, CD97, CELSR1, CELSR2, CELSR3, ELTD1, EMR1, EMR2, EMR3, EMR4, GPR56, GPR64, GPR97, GPR110, GPR111, GPR112, GPR113, GPR114, GPR115, GPR116, GPR123, GPR124, GPR125, GPR126, GPR128, GPR133, GPR143, GPR144, GPR157, LPHN1, LPHN2, LPHN3, and GPR98);
Class D GPCRs, including, but not limited to, fungal mating pheromone receptors (e.g., STE2 and STE3);
Class E GPCRs, including, but not limited to, cAMP receptors (e.g., Dictyostelium);
Class F GPCRs, including, but not limited to, frizzled receptors (e.g., FZD1, FZD2, FZD3, FZD4, FZD5, FZD6, FZD7, FZD8, FZD9, FZD10, and SMO); and
Unclassified GPCRs (e.g., OPCML, OGFR, OGFRL1, and OPRS1).
Examples of voltage-gated ion channels include, but are not limited to:
Calcium-activated potassium channels, including, but not limited to, KCNMA1, KCNN1, KCNN2, KCNN3, KCNN4, KCNT1, KCNT2, and KCNU1;
CatSper and two-pore channels, including, but not limited to, CATSPER1, CATSPER2, CATSPER3, CATSPER4, TPCN1, and TPCN2;
Cyclic nucleotide-regulated channels, including, but not limited to, CNGA1, CNGA2, CNGA3, CNGA4, CNGB1, CNGB3, HCN1, HCN2, HCN3, and HCN4;
Inwardly rectifying potassium channels, including, but not limited to, KCNJ1, KCNJ2, KCNJ12, KCNJ4, KCNJ14, KCNJ3, KCNJ6, KCNJ9, KCNJ5, KCNJ10, KCNJ15, KCNJ16, KCNJ8, KCNJ11, and KCNJ13;
Transient receptor potential channels, including, but not limited to, TRPA1, TRPC1, TRPC2, TRPC3, TRPC4, TRPC5, TRPC6, TRPC7, TRPM1, TRPM2, TRPM3, TRPM4, TRPM5, TRPM6, TRPM7, TRPM8, MCOLN1, MCOLN2, MCOLN3, PKD2, PKD2L1, PKD2L2, TRPV1, TRPV2, TRVP3, TRPV4, TRPV5, and TRPV6;
Two-P potassium channels, including, but not limited to, KCNK1, KCNK2, KCNK3, KCNK4, KCNK5, KCNK6, KCNK7, KCNK9, KCNK10, KCNK12, KCNK13, KCNK15, KCNK16, KCNK17, and KCNK18;
Voltage-gated calcium channels, including, but not limited to, CACNA1S, CACNA1C, CACNA1D, CACNA1F, CACNA1A, CACNA1B, CACNA1E, CACNA1G, CACNA1H, and CACNA1I;
Voltage-gated potassium channels, including, but not limited to, KCNA1, KCNA2, KCNA3, KCNA4, KCNA5, KCNA6, KCNA7, KCNA10, KCNB1, KCNB2, KCNC1, KCNC2, KCNC3, KCNC4, KCND1, KCND2, KCND3, KCNF1, KCNG1, KCNG2, KCNG3, KCNG4, KCNQ1, KCNA2, KCNA3, KCNA4, KCNA5, KCNV1, KCNV2, KCNS1, KCNS2, KCNS3, KCNH1, KCNH5, KCNH2, KCNH6, KCNH7, KCNH8, KCNH3, and KCNH4;
Voltage-gated sodium channels, including, but not limited to, SCN1A, SCN2A, SCN3A, SCN4A, SCN5A, SCN8A, SCN9A, SCN10A, and SCN11A; and
Other voltage-gated ion channels, including, but not limited to, KCNE1, KCNE1L, KCNE2, KCNE3, KCNIP1, KCNIP2, KCNIP3, KCNIP4, KCNMB1, KCNMB2, KCNMB3, CNMB3L, and KCNMB4.
Examples of ligand gated ion channels include, but are not limited to:
Serotonin receptor subunits, including, but not limited to, 5HT3Acapo, 5HT3Ahosa, 5HT3Amumu, 5HT3Amupu, 5HT3Aorcu, 5HT3Apatr, 5HT3Arano, 5HT3Bhosa, 5HT3Bmumu, 5HT3Borcu, 5HT3 Bpatr, 5HT3Brano, 5HT3Chosa, 5HT3 Cpatr, 5HT3Dhosa, 5HT3Dpatr, 5HT3Ehosa, 5HT3gaga, and 5HTmod1cael; 5-HT receptors including: 5-HT1A; 5-HT1B; 5-HT1D; 5-HT1E; 5-HT1F; 5-HT2A; 5-HT2B; 5-HT2C; 5HT4 splice isoforms a, b, c, d, e, f, g, n; 5-HT5A; 5-HT6; 5-HT7 splice forms a, b, c.
Acetylcholine receptor subunits, including, but not limited to, ACHa10gaga, ACHa10hosa, ACHa10mumu, ACHa10patr, ACHa10rano, ACHa1anga, ACHa1apca, ACHa1ataru, ACHa1axela, ACHa1bota, ACHa1btaru, ACHa1bxela, ACHa1cafa, ACHa1dare, ACHa1gaga, ACHa1hevi, ACHa1hosa, ACHa1lomi, ACHa1mumu, ACHa1mype, ACHa1naha, ACHa1nana, ACHa1nate, ACHa1patr, ACHa1rano, ACHa1toca, ACHa1toma, ACHa2anga, ACHa2apca, ACHa2apgo, ACHa2dare, ACHa2gaga, ACHa2hevi, ACHa2hosa, ACHa2lomi, ACHa2mamu, ACHa2mumu, ACHa2mype, ACHa2patr, ACHa2rano, ACHa2taru, ACHa3anga, ACHa3apme, ACHa3bota, ACHa3caau, ACHa3drme, ACHa3gaga, ACHa3hevi, ACHa3hosa, ACHa3lomi, ACHa3mamu, ACHa3mumu, ACHa3mype, ACHa3patr, ACHa3rano, ACHa3taru, ACHa4anga, ACHa4drme, ACHa4gaga, ACHa4hosa, ACHa4mamu, ACHa4mumu, ACHa4mype, ACHa4patr, ACHa4rano, ACHa4taru, ACHa5anga, ACHa5drme, ACHa5gaga, ACHa5hosa, ACHa5mamu, ACHa5mumu, ACHa5mype, ACHa5patr, ACHa5rano, ACHa6ataru, ACHa6btaru, ACHa6drme, ACHa6gaga, ACHa6hosa, ACHa6mamu, ACHa6mumu, ACHa6patr, ACHa6rano, ACHa7—1hevi, ACHa7—2hevi, ACHa7anga, ACHa7ataru, ACHa7bota, ACHa7btaru, ACHa7ctaru, ACHa7dare, ACHa7drme, ACHa7gaga, ACHa7hosa, ACHa7mamu, ACHa7mumu, ACHa7patr, ACHa7rano, ACHa7rasp, ACHa8ataru, ACHa8btaru, ACHa8gaga, ACHa9ataru, ACHa9btaru, ACHa9ctaru, ACHa9dare, ACHa9dtaru, ACHa9gaga, ACHa9hosa, ACHa9mumu, ACHa9patr, ACHa9rano, ACHaassu, ACHacr10cael, ACHacr11cael, ACHacr12cael, ACHacr13cael, ACHacr14cael, ACHacr15cael, ACHacr16cael, ACHacr17cael, ACHacr18cael, ACHacr19cael, ACHacr20cael, ACHacr21cael, ACHacr22cael, ACHacr23cael, ACHacr2cael, ACHacr3cael, ACHacr4cael, ACHacr5cael, ACHacr6cael, ACHacr7cael, ACHacr8cael, ACHacr9cael, ACHahaco, ACHal1acdo, ACHal1scgr, ACHalsdrme, ACHalsmase, ACHalyst, ACHarddrme, ACHb1ataru, ACHb1bota, ACHb1btaru, ACHb1hevi, ACHb1hosa, ACHb1mase, ACHb1mumu, ACHb1patr, ACHb1rano, ACHb1toca, ACHb1xela, ACHb2caau, ACHb2gaga, ACHb2hosa, ACHb2mamu, ACHb2mumu, ACHb2patr, ACHb2rano, ACHb3acaau, ACHb3adare, ACHb3bcaau, ACHb3gaga, ACHb3hosa, ACHb3mamu, ACHb3mumu, ACHb3patr, ACHb3rano, ACHb4bota, ACHb4gaga, ACHb4hosa, ACHb4mamu, ACHb4mumu, ACHb4patr, ACHb4rano, ACHb4taru, ACHb5taru, ACHb6taru, ACHb7taru, ACHblomi, ACHblyst, ACHc04c3—2cael, ACHc15a7—1cael, ACHcg7589drme, ACHclyst, ACHcup4cael, ACHdbota, ACHddare, ACHdeg3cael, ACHdgaga, ACHdhosa, ACHdlyst, ACHdmumu, ACHdpatr, ACHdrara, ACHdtaru, ACHdtoca, ACHdxela, ACHeat2cael, ACHebota, ACHehosa, ACHelyst, ACHemumu, ACHepatr, ACHerara, ACHetaru, ACHexyla, ACHf11c7—1cael, ACHf17e9—7cael, ACHf17e9—8cael, ACHf18g5—4cael, ACHf21a3—7cael, ACHf58h7—3cael, ACHflyst, ACHgbota, ACHggaga, ACHghosa, ACHglyst, ACHgmumu, ACHgpatr, ACHgrara, ACHgtaru, ACHgtoca, ACHgxela, ACHhlyst, ACHilyst, ACHjlyst, ACHklyst, ACHlev1cael, ACHllyst, ACHnaapca, ACHr03e1—3cael, ACHr13a5—4cael, ACHronvo, ACHsaddrme, ACHsbddrme, ACHssu1osci, ACHssu2osci, ACHt01h10—1cael, ACHt01h10—2cael, ACHt01h10—3cael, ACHt01h10—5cael, ACHt01h10—6cael, ACHt01h10—7cael, ACHt05b4—1cael, ACHtar1 trco, ACHunc29cael, ACHunc38cael, ACHunc63cael, ACHy44a6e—1cael, ACHy57g11c—2cael, ACHy57g11c—49cael, ACHy58g8a—1cael, ACHy73b6bl—26cael, and ACHy73f8a—30cael;
GABAA receptor subunits, including, but not limited to, GABa1bota, GABa1gaga, GABa1hosa, GABa1mumu, GABa1rara, GABa2bota, GABa2hosa, GABa2mumu, GABa2rara, GABa3bota, GABa3hevi, GABa3hosa, GABa3mumu, GABa3rara, GABa4bota, GABa4hosa, GABa4mumu, GABa4rara, GABa5hosa, GABa5rara, GABa6caau, GABa6hosa, GABa6mumu, GABa6rara, GABb1bota, GABb1hosa, GABb1mumu, GABb1rasp, GABb2dare, GABb2hosa, GABb2mumu, GABb2rasp, GABb3gaga, GABb3hosa, GABb3mumu, GABb3rasp, GABb4gaga, GABbdrme, GABblyst, GABbseof, GABc09g5—1cael, GABc27h5—4cael, GABc39b10—2cael, GABc53d6—3cael, GABdhosa, GABdmumu, GABdrara, GABehosa, GABemumu, GABerano, GABf09c12—1cael, GABf11h8—2cael, GABf47a4—1cael, GABf55d10—5cael, GABf58g6—4cael, GABg1gaga, GABg1hosa, GABg1 mumu, GABg1rano, GABg2bota, GABg2gaga, GABg2hosa, GABg2mumu, GABg2rara, GABg3hosa, GABg3mumu, GABg3rano, GABg4gaga, GABg4hosa, GABg4mumu, GABgbr2cael, GABgrddrme, GABhg1haco, GABk10d6—1cael, GABphosa, GABpmumu, GABr1amoam, GABr1bmoam, GABr1hosa, GABr1mumu, GABr1rano, GABr2amoam, GABr2bmoam, GABr2hosa, GABr2mumu, GABr2rara, GABr3hosa, GABr3moam, GABr3mumu, GABr3rano, GABrdlaeae, GABrdlceca, GABrdldrme, GABt20b12—9cael, GABt21f2—1cael, GABt24d8—1cael, GABthosa, GABtmumu, GABtrano, GABunc49bcael, GABunc49cael, and GABzlyst;
Glycine/Histamine receptor subunits, including, but not limited to, GLYa1dare, GLYa1hosa, GLYa1mumu, GLYa1rano, GLYa2dare, GLYa2hosa, GLYa2mumu, GLYa2rano, GLYa3dare, GLYa3hosa, GLYa3moam, GLYa3mumu, GLYa3rano, GLYa4adare, GLYa4bdare, GLYa4hosa, GLYa4mumu, GLYbdare, GLYbhosa, GLYbmumu, GLYbrano, and HIScl1drme;
ATP receptor subunits, including, but not limited to, ATPp2x1hosa, ATPp2x1rano, ATPp2x2capo, ATPp2x2hosa, ATPp2x2mumu, ATPp2x2rano, ATPp2x3hosa, ATPp2x3mumu, ATPp2x3rano, ATPp2x4bota, ATPp2x4gaga, ATPp2x4hosa, ATPp2x4mumu, ATPp2x4orcu, ATPp2x4rano, ATPp2x5bota, ATPp2x5hosa, ATPp2x5mumu, ATPp2x5rano, ATPp2x6hosa, ATPp2x6mumu, ATPp2x6rano, ATPp2x7bota, ATPp2x7hosa, ATPp2x7mumu, ATPp2x7rano, and ATPp2xscma;
Glutamate receptor subunits, including, but not limited to, GLU1—1arth, GLU1—2arth, GLU1—3arth, GLU1—4arth, GLU2—1arth, GLU2—2arth, GLU2—3arth, GLU2—4arth, GLU2—5arth, GLU2—6arth, GLU2—7arth, GLU2—8arth, GLU2—9arth, GLU3—1 arth, GLU3—2arth, GLU3—3arth, GLU3—4arth, GLU3—5arth, GLU3—6arth, GLU3—7arth, GLUd1hosa, GLUd1mumu, GLUd1rano, GLUd2hosa, GLUd2mumu, GLUd2rano, GLUglr10cael, GLUglr1cael, GLUglr2cael, GLUglr4cael, GLUglr5cael, GLUglr6cael, GLUglr7cael, GLUglr8cael, GLUglr9cael, GLUk10d3—1cael, GLUka1hosa, GLUka1mumu, GLUka1rano, GLUka2hosa, GLUka2mumu, GLUka2rano, GLUka4mumu, GLUkbpacaau, GLUkbpansp, GLUkbpbcaau, GLUkbpgaga, GLUkbprapi, GLUkbpxela, GLUnr1anpl, GLUnr1aple, GLUnr1caau, GLUnr1drme, GLUnr1hosa, GLUnr1mumu, GLUnr1rano, GLUnr1susc, GLUnr1xela, GLUnr2ahosa, GLUnr2amumu, GLUnr2arano, GLUnr2bhosa, GLUnr2bmumu, GLUnr2brano, GLUnr2chosa, GLUnr2 cmumu, GLUnr2crano, GLUnr2dhosa, GLUnr2dmumu, GLUnr2drano, GLUnr3ahosa, GLUnr3amumu, GLUnr3arano, GLUnr3bhosa, GLUnr3bmumu, GLUnr3brano, GLUr0, GLUr1gaga, GLUr1hosa, GLUr1moch, GLUr1mumu, GLUr1rano, GLUr2acorni, GLUr2borni, GLUr2coli, GLUr2gaga, GLUr2hosa, GLUr2mumu, GLUr2rano, GLUr3aormo, GLUr3caau, GLUr3coli, GLUr3gaga, GLUr3hosa, GLUr3mumu, GLUr3rano, GLUr4caau, GLUr4coli, GLUr4gaga, GLUr4hosa, GLUr4mumu, GLUr4rano, GLUr5daae, GLUr5hosa, GLUr5mumu, GLUr5rano, GLUr6hosa, GLUr6mumu, GLUr6rano, GLUr6xela, GLUr7hosa, GLUr7mumu, GLUr7rano, GLUrldrme, GLUrllAdrme, GLUrllBdrme, GLUrlllyst, GLUrllyst, GLUrk1lyst, GLUcl3cael, GLUclacael, GLUclbcael, GLUclbhaco, GLUcldrme, GLUclhaco, GLUclxcael, and GLUclxonvo.
Examples of other channel proteins include, but are not limited to:
ENaC/DEG family proteins, including, but not limited to, SCNN1A, SCNN1B, SCNN1G, SCNN1D, ACCN2, ACCN1, ACCN3, ACCN4, and ACCN5;
Aquaporins, including, but not limited to, AQP1, AQP2, AQP3, AQP4, AQP5, AQP6, AQP7, AQP7P1, AQP7P2, AQP7P3, AQP7P4, AQP8, AQP9, AQP10, AQP11, AQP12A, and AQP12B; and
Chloride channels, including, but not limited to, CLCA1, CLCA2, CLCA3P, CLCA4, CLCC1, CLCF1, CLCN1, CLCN2, CLCN3, CLCN4, CLCN5, CLCN6, CLCN7, CLCNKA, and CLCNKB.
Examples of membrane carrier/transporter proteins include, but are not limited to:
ABCC family of proteins, including, but not limited to, ABCA1, ABCA2, ABCA3, ABCA4, ABCA5, ABCA6, ABCA7, ABCA8, ABCA9, ABCA10, ABCA11P, ABCA12, ABCA13, ABCA17P, ABCB1, ABCB4, ABCB5, ABCB6, ABCB7, ABCB8, ABCB9, ABCB10, ABCB10P1, ABCB11, ABCC1, ABCC2, ABCC3, ABCC4, ABCC5, ABCC6, ABCC6P1, ABCC6P2, ABCC8, ABCC9, ABCC10, ABCC11, ABCC12, ABCC13, ABCD1, ABCD1P1, ABCD1P2, ABCD1P3, ABCD1P4, ABCD2, ABCD3, ABCD4, ABCE1, ABCF1, ABCF2, ABCF3, ABCG1, ABCG2, ABCG4, ABCG5, ABCG8, TAP1, TAP2, CFTR TAPBP, and TAPBPL;
Soluble carrier family of proteins, including, but not limited to, SLC1A1, SLC1A2, SLC1A3, SLC1A4, SLC1A5, SLC1A6, SLC1A7, SLC2A1, SLC2A2, SLC2A3, SLC2A3P1, SLC2A3P2, SLC2A3P4, SLC2A4, SLC2A4RG, SLC2A5, SLC2A6, SLC2A7, SLC2A8, SLC2A9, SLC2A10, SLC2A11, SLC2A12, SLC2A13, SLC2A14, SLC2AXP1, SLC3A1, SLC3A2, SLC4A1, SLC4A1AP, SLC4A2, SLC4A3, SLC4A4, SLC4A5, SLC4A7, SLC4A8, SLC4A9, SLC4A10, SLC4A11, SLC5A1, SLC5A2, SLC5A3, SLC5A4, SLC5A5, SLC5A6, SLC5A7, SLC5A8, SLC5A9, SLC5A10, SLC5A11, SLC5A12, SLC6A1, SLC6A2, SLC6A3, SLC6A4, SLC6A5, SLC6A6, SLC6A6P, SLC6A7, SLC6A8, SLC6A9, SLC6A10P, SLC6A11, SLC6A12, SLC6A13, SLC6A14, SLC6A15, SLC6A16, SLC6A17, SLC6A18, SLC6A19, SLC6A20, SLC6A21P, SLC7A1, SLC7A2, SLC7A3, SLC7A4, SLC7A5, SLC7A5P1, SLC7A6, SLC7A60S, SLC7A7, SLC7A8, SLC7A9, SLC7A10, SLC7A11, SLC7A13, SLC7A14, SLC8A1, SLC8A2, SLC8A3, SLC9A1, SLC9A2, SLC9A3, SLC9A3P, SLC9A3P2, SLC9A3P3, SLC9A3P4, SLC9A3R1, SLC9A3R2, SLC9A4, SLC9A5, SLC9A6, SLC9A7, SLC9A8, SLC9A9, SLC9A10, SLC9A11, SLC10A1, SLC10A2, SLC10A3, SLC10A4, SLC10A5, SLC10A6, SLC10A7, SLC11A1, SLC11A2, SLC12A1, SLC12A2, SLC12A3, SLC12A4, SLC12A5, SLC12A6, SLC12A7, SLC12A8, SLC12A9, SLC13A1, SLC13A2, SLC13A3, SLC13A4, SLC13A5, SLC14A1, SLC14A2, SLC15A1, SLC15A2, SLC15A3, SLC15A4, SLC15A5, SLC16A1, SLC16A2, SLC16A3, SLC16A4, SLC16A5, SLC16A6, SLC16A7, SLC16A8, SLC16A9, SLC16A10, SLC16A11, SLC16A12, SLC16A13, SLC16A14, SLC17A1, SLC17A2, SLC17A3, SLC17A4, SLC17A5, SLC17A6, SLC17A7, SLC17A8, SLC17A9, SLC18A1, SLC18A2, SLC18A3, SLC19A1, SLC19A2, SLC19A3, SLC20A1, SLC20A1P1, SLC20A2, SLC22A1, SLC22A2, SLC22A3, SLC22A4, SLC22A5, SLC22A6, SLC22A7, SLC22A8, SLC22A9, SLC22A10, SLC22A11, SLC22A12, SLC22A13, SLC22A14, SLC22A15, SLC22A16, SLC22A17, SLC22A18, SLC22A18AS, SLC22A20, SLC22A23, SLC22A24, SLC22A25, SLC23A1, SLC23A2, SLC23A3, SLC23A4, SLC24A1, SLC24A2, SLC24A3, SLC24A4, SLC24A5, SLC24A6, SLC25A1, SLC25A2, SLC25A3, SLC25A4, SLC25A5, SLC25A5P1, SLC25A5P2, SLC25A5P3, SLC25A5P4, SLC25A5P5, SLC25A5P6, SLC25A5P7, SLC25A5P8, SLC25A5P9, SLC25A6, SLC25A6P1, SLC25A10, SLC25A11, SLC25A12, SLC25A13, SLC25A14, SLC25A15, SLC25A15P, SLC25A16, SLC25A17, SLC25A18, SLC25A19, SLC25A20, SLC25A20P, SLC25A21, SLC25A22, SLC25A23, SLC25A24, SLC25A25, SLC25A26, SLC25A27, SLC25A28, SLC25A29, SLC25A30, SLC25A31, SLC25A32, SLC25A33, SLC25A34, SLC25A35, SLC25A36, SLC25A37, SLC25A38, SLC25A39, SLC25A40, SLC25A41, SLC25A42, SLC25A43, SLC25A44, SLC25A45, SLC25A46, SLC26A1, SLC26A2, SLC26A3, SLC26A4, SLC26A5, SLC26A6, SLC26A7, SLC26A8, SLC26A9, SLC26A10, SLC26A11, SLC27A1, SLC27A2, SLC27A3, SLC27A4, SLC27A5, SLC27A6, SLC28A1, SLC28A2, SLC28A3, SLC29A1, SLC29A2, SLC29A3, SLC29A4, SLC30A1, SLC30A2, SLC30A3, SLC30A4, SLC30A5, SLC30A6, SLC30A7, SLC30A8, SLC30A9, SLC30A10, SLC31A1, SLC31A1P, SLC31A2, SLC32A1, SLC33A1, SLC34A1, SLC34A2, SLC34A3, SLC35A1, SLC35A2, SLC35A3, SLC35A4, SLC35A5, SLC35B1, SLC35B2, SLC35B3, SLC35B4, SLC35C1, SLC35C2, SLC35D1, SLC35D2, SLC35D3, SLC35E1, SLC35E2, SLC35E3, SLC35E4, SLC35F1, SLC35F2, SLC35F3, SLC35F4, SLC35F5, SLC36A1, SLC36A2, SLC36A3, SLC36A4, SLC37A1, SLC37A2, SLC37A3, SLC37A4, SLC38A1, SLC38A2, SLC38A3, SLC38A4, SLC38A5, SLC38A6, SLC38A7, SLC38A8, SLC38A9, SLC38A10, SLC38A11, SLC39A1, SLC39A2, SLC39A3, SLC39A4, SLC39A5, SLC39A6, SLC39A7, SLC39A8, SLC39A9, SLC39A10, SLC39A11, SLC39A12, SLC39A13, SLC39A14, SLC40A1, SLC41A1, SLC41A2, SLC41A3, SLC43A1, SLC43A2, SLC43A3, LC44A1, SLC44A2, SLC44A3, SLC44A4, SLC44A5, SLC45A1, SLC45A2, SLC45A3, SLC45A4, SLC46A1, SLC46A2, SLC46A3, SLC47A1, SLC47A2, SLC48A1, SLCO1A2, SLCO1B1, SLCO1B3, SLCO1C1, SLCO2A1, SLCO2B1, SLCO3A1, SLCO4A1, SLCO4C1, SLCO5A1, and SLCO6A1;
ATP transporters, including, but not limited to, ATP1A1, ATP1A2, ATP1A3, ATP1A4, ATP1B1, ATP1B2, ATP1B3, ATP1B3P1, ATP1B4, ATP1L1, ATP2A1, ATP2A2, ATP2A3, ATP2B1, ATP2B2, ATP2B3, ATP2B4, ATP2C1, ATP2C2, ATP3, ATP4A, ATP4B, ATP5A1, ATP5AL1, ATP5AP1, ATP5AP2, ATP5AP3, ATP5AP4, ATP5B, ATP5BL1, ATP5BL2, ATP5C1, ATP5C2, ATP5D, ATP5E, ATP5EP1, ATP5EP2, ATP5F1, ATP5G1, ATP5G2, ATP5G3, ATP5GP1, ATP5GP2, ATP5GP3, ATP5GP4, ATP5H, ATP5HP1, ATP5I, ATP5J, ATP5J2, ATP5J2LP, ATP5J2P2, ATP5J2P3, ATP5J2P4, ATP5J2P5, ATP5J2P6, ATP5L, ATP5LP1, ATP5LP2, ATP5LP3, ATP50, ATP5S, ATP5SL, ATP6AP1, ATP6AP1L, ATP6AP2, ATP6V1A, ATP6V1B1, ATP6V1B2, ATP6V1C1, ATP6V1C2, ATP6V1D, ATP6V1E1, ATP6V1E2, ATP6V1 EL1, ATP6V1 EP1, ATP6V1EP2, ATP6V1F, ATP6V1G1, ATP6V1G2, ATP6V1G3, ATP6V1GP1, ATP6V1GP2, ATP6V1H, ATP6V0A1, ATP6V0A2, ATP6V0A4, ATP6V0B, ATP6V0C, ATP6V0D1, ATP6V0D2, ATP6V0E1, ATP6V0E2, ATP7A, ATP7B, and ATP8A1; and
Fatty acid binding proteins, including, but not limited to, FABP1, FABP2, FABP3, FABP3P2, FABP4, FABP5, FABP5L1, FABP5L2, FABP5L3, FABP5L4, FABP5L5, FABP5L6, FABP5L7, FABP5L8, FABP5L9, FABP5L10, FABP5L11, FABP5L12, FABP6, FABP7, FABP9, and FABP12;
Insulin-like growth factors, including, but not limited to, IGF1, IGF1R, IGF2, IGF2AS, IGF2BP1, IGF2BP2, IGF2BP3, IGF2R, IGFALS, IGFBP1, IGFBP2, IGFBP3, IGFBP4, IGFBP5, IGFBP6, IGFBP7, IGFBPL1, IGFL1, IGFL1P1, IGFL1P2, IGFL2, IGFL3, IGFL4, and IGFN1;
Transforming growth factors, including, but not limited to, TGFA, TGFB1, TGFB1I1, TGFB2, TGFB3, TGFBI, TGFBR1, TGFBR2, TGFBR3, TGFBRAP1, TGFBRE, LEFTY1, LEFTY2, BMPR1A, BMPR1APS1, BMPR1APS2, BMPR1B, BMPR2, ACVR1, ACVR1B, ACVR1C, ACVR2A, ACVR2B, and ACVRL1;
Nuclear receptors, including, but not limited to, NR1D1, NR1D2, NR1H2, NR1H3, NR1H4, NR1H5P, NR1I1, NR1I2, NR1I3, NR1I4, NR2A1, NR2A2, NR2B1, NR2B2, NR2B3, NR2C1, NR2C2, NR2C2AP, NR2E1, NR2E3, NR2F1, NR2F2, NR2F6, NR3C1, NR3C1P, NR3C2, NR3C3, NR3C4, NR4A1, NR4A2, NR4A3, NR5A1, NR5A2, NR6A1, NRAP, NRARP, NR0B1, NR0B2, NRBF2, NRBP1, NRBP2, NRCAM, NRIP1, NRIP2, and NRIP3;
Retinoic acid receptors, including, but not limited to, RARA, RARB, RARG, RARRES1, RARRES2, and RARRES3;
Receptor tyrosine kinase orphan and RAR related proteins, including, but not limited to, ROR1, ROR2, RORA, RORB, and RORC;
Peroxisome proliferator activated receptors, including, but not limited to, PPARA, PPARD, PPARG, PPARGC1A, and PPARGC1B;
Thyroid hormone receptors, including, but not limited to, THRA, THRAP3, THRAP3L, THRB, and THRSP;
Estrogen receptors, epithelial splicing regulatory proteins, and estrogen related receptors, including, but not limited to, ESR1, ESR2, ESRP1, ESRP2, ESRRA, ESRRAP1, ESRRAP2, ESRRB, and ESRRG;
Etrythroblastic leukemia viral oncogenes, including, but not limited to, ERBB2, ERBB2IP, ERBB3, ERBB4, and EGFR;
Platelet derived growth factors, including, but not limited to, PDGFA, PDGFB, PDGFC, PDGFD, PDGFRA, PDGFRB, and PDGFRL;
Fibroblast derived growth factors, including, but not limited to, FGFR1, FGFR1OP, FGFR1OP2, FGFR2, FGFR3, FGFR3P, FGFR4, FGFR6, and FGFRL1;
Latent transforming growth factor β binding proteins, including, but not limited to, LTBP1, LTBP2, LTBP3, and LTBP4;
Vitamin carrier proteins, including, but not limited to, RBP1, RBP2, RBP3, RBP4, RBP5, RBP7, RBPJ, RBPJL, RBPJP1, RBPJP2, RBPJP3, RBPJP4, RBPMS, RBPMS2, and RBPMSLP;
Steroidogenic acute regulatory proteins, including, but not limited to, STAR, STARD3, STARD3NL, STARD4, STARD5, STARD6, STARD7, STARD8, STARD9, STARD10, STARD13, and STARP1;
Sterol carrier proteins, including, but not limited to, SCP2 and SCPEP1;
Glycolipid transfer proteins, including, but not limited to, GLTP, GLTPD1, GLTPD2, and GLTPP1; and
Other transport proteins, e.g., CETP.
Other examples of proteins of interest include, but are not limited to:
T cell receptor β constant 1, including, but not limited to, TRBC1, TRBC2, TRBD1, TRBD2, TRBJ1-1, TRBJ1-2, TRBJ1-3, TRBJ1-4, TRBJ1-5, TRBJ1-6, TRBJ2-1, TRBJ2-2, TRBJ2-2P, TRBJ2-3, TRBJ2-4, TRBJ2-5, TRBJ2-6, TRBJ2-7, TRBV1, TRBV2, TRBV3-1, TRBV3-2, TRBV4-1, TRBV4-2, TRBV4-3, TRBV5-1, TRBV5-2, TRBV5-3, TRBV5-4, TRBV5-5, TRBV5-6, TRBV5-7, TRBV5-8, TRBV6-1, TRBV6-2, TRBV6-3, TRBV6-4, TRBV6-5, TRBV6-6, TRBV6-7, TRBV6-8, TRBV6-9, TRBV7-1, TRBV7-2, TRBV7-3, TRBV7-4, TRBV7-5, TRBV7-6, TRBV7-7, TRBV7-8, TRBV7-9, TRBV8-1, TRBV8-2, TRBV9, TRBV10-1, TRBV10-2, TRBV10-3, TRBV11-1, TRBV11-2, TRBV11-3, TRBV12-1, TRBV12-2, TRBV12-3, TRBV12-4, TRBV12-5, TRBV13, TRBV14, TRBV15, TRBV16, TRBV17, TRBV18, TRBV19, TRBV20-1, TRBV20OR9-2, TRBV21-1, TRBV21OR9-2, TRBV22-1, TRBV22OR9-2, TRBV23-1, TRBV23OR9-2, TRBV24-1, TRBV24OR9-2, TRBV25-1, TRBV25OR9-2, TRBV26, TRBV26OR9-2, TRBV27, TRBV28, TRBV29-1, TRBV29OR9-2, TRBV30, TRBVA, TRBVAOR9-2, TRBVB, and TRBVOR9;
Disintegrins, including, but not limited to, ADAM1, ADAM2, ADAM3A, ADAM3B, ADAM5P, ADAM6, ADAM7, ADAM8, ADAM9, ADAM10, ADAM11, ADAM12, ADAM15, ADAM17, ADAM18, ADAM19, ADAM20, ADAM21, ADAM21P, ADAM22, ADAM23, ADAM28, ADAM29, ADAM30, ADAM32, ADAM33, ADAMDEC1, ADAMTS1, ADAMTS2, ADAMTS3, ADAMTS4, ADAMTS5, ADAMTS6, ADAMTS7, ADAMTS8, ADAMTS9, ADAMTS10, ADAMTS12, ADAMTS13, ADAMTS14, ADAMTS15, ADAMTS16, ADAMTS17, ADAMTS18, ADAMTS19, ADAMTS20, ADAMTSL1, ADAMTSL2, ADAMTSL3, ADAMTSL4, and ADAMTSL5;
Integrins, including, but not limited to, ITGA1, ITGA2, ITGA2B, ITGA3, ITGA4, ITGA5, ITGA6, ITGA7, ITGA8, ITGA9, ITGA10, ITGA11, ITGAD, ITGAE, ITGAL, ITGAM, ITGAV, ITGAW, ITGAX, ITGB1, ITGB1BP1, ITGB1BP2, ITGB1BP3, ITGB2, ITGB3, ITGB3BP, ITGB4, ITGB5, ITGB6, ITGB7, ITGB8, and ITGBL1;
Cell adhesion molecules, including, but not limited to, NCAM1, NCAM2, VCAM1, ICAM1, ICAM2, ICAM3, ICAM4, ICAM5, PECAM1, L1CAM, CHL1, MAG, CADM1, CADM2, CADM3, and CADM4;
Human odorant receptors, including, but not limited to, OR10A1, OR10A3, OR10A4, OR10A5, OR10A6, OR10A7, OR10C1, OR10C2, OR10D4, OR10G2, OR10G3, OR10G4, OR10G7, OR10G8, OR10G9, OR10H1, OR10H2, OR10H3, OR10H4, OR10H5, OR10J1, OR10J3, OR10J5, OR10J6, OR10K1, OR10K2, OR10Q1, OR10R2, OR10S1, OR10T2, OR10V1, OR10Z1, OR11A1, OR11G2, OR11H1, OR11H4, OR11H6, OR11H7P, OR11L1, OR12D3, OR13A1, OR13C2, OR13C3, OR13C4, OR13C5, OR13C7, OR13C8, OR13C9, OR13D1, OR13E2, OR13F1, OR13G1, OR13H1, OR13J1, OR14A16, OR14A2, OR14C36, OR14J1, OR1A1, OR1A2, OR1A2, OR1B1, OR1C1, OR1D2, OR1D4, OR1D5, OR1E1, OR1E2, OR1E2, OR1E5, OR1E5, OR1E6, OR1E7, OR1F1, OR1F10, OR1F11, OR1F12, OR1F2, OR1G1, OR111, OR1J1, OR1J2, OR1J2, OR1J4, OR1J5, OR1K1, OR1L1, OR1L3, OR1L4, OR1L6, OR1L8, OR1M1, OR1M1, OR1N1, OR1N2, OR1N3, OR1Q1, OR1S1, OR1S2, OR2A1, OR2A10, OR2A19, OR2A20, OR2A21, OR2A4, OR2A42, OR2A5, OR2A6, OR2A7, OR2AE1, OR2AJ1, OR2AK2, OR2B1, OR2B2, OR2B3, OR2B6, OR2B9, OR2C1, OR2D1, OR2D2, OR2D3, OR2F1, OR2F2, OR2F3, OR2G2, OR2G3, OR2H1, OR2H2, OR2H3, OR2J2, OR2J3, OR2K1, OR2K2, OR2L1, OR2L2, OR2L3, OR2L5, OR2L8, OR2M1, OR2M2, OR2M4, OR2S2, OR2T1, OR2T3, OR2T4, OR2T5, OR2T6, OR2T7, OR2T8, OR2V1, OR2V2, OR2V3, OR2W1, OR2W3, OR2Y1, OR2Z1, OR3A1, OR3A2, OR3A3, OR3A4, OR4A15, OR4A16, OR4A4, OR4A5, OR4B1, OR4C12, OR4C13, OR4C15, OR4C16, OR4C3, OR4C6, OR4D1, OR4D2, OR4D5, OR4D6, OR4D9, OR4E2, OR4F10, OR4F15, OR4F16, OR4F16, OR4F17, OR4F18, OR4F19, OR4F3, OR4F6, OR4K1, OR4K13, OR4K14, OR4K15, OR4K17, OR4K2, OR4K3, OR4K5, OR4L1, OR4M1, OR4M2, OR4N2, OR4N4, OR4N5, OR4P4, OR4Q3, OR4S1, OR4X1, OR4X2, OR51A2, OR51A4, OR51A7, OR51B2, OR51B4, OR51D1, OR51E1, OR51E2, OR51F2, OR51G1, OR51G2, OR51H1, OR51I1, OR51I2, OR51L1, OR51M1, OR51Q1, OR51S1, OR51T1, OR52A1, OR52A2, OR52B2, OR52B4, OR52B4, OR52B4, OR52B6, OR52D1, OR52E2, OR52E4, OR52E5, OR52E6, OR52E8, OR52H1, OR52I1, OR52I2, OR52J3, OR52K1, OR52K2, OR52L1, OR52L2, OR52N1, OR52N2, OR52N4, OR52N5, OR52P1, OR52R1, OR56A4, OR56A6, OR56B2, OR56B4, OR5A1, OR5A2, OR5AC2, OR5AK2, OR5AK3, OR5AN1, OR5AP2, OR5AR1, OR5AS1, OR5AU1, OR5AU1, OR5B13, OR5B16, OR5B17, OR5B2, OR5B3, OR5C1, OR5D13, OR5D14, OR5D16, OR5D18, OR5F1, OR5G3, OR5H1, OR5H2, OR5H6, OR51I, OR5K1, OR5K2, OR5L1, OR5L2, OR5M1, OR5M10, OR5M11, OR5M11, OR5M3, OR5M3, OR5M8, OR5M9, OR5P2, OR5P3, OR5T2, OR5T3, OR5V1, OR6A1, OR6B1, OR6B2, OR6C1, OR6C2, OR6C3, OR6F1, OR6J2, OR6K3, OR6K6, OR6M1, OR6N1, OR6N2, OR6P1, OR6Q1, OR6S1, OR6T1, OR6V1, OR6X1, OR6Y1, OR7A10, OR7A17, OR7A2, OR7A5, OR7C1, OR7C2, OR7D2, OR7D2, OR7D4P, OR7E102, OR7E120, OR7G1, OR7G2, OR7G3, OR8A1, OR8B12, OR8B2, OR8B3, OR8B4, OR8B8, OR8D1, OR8D2, OR8D4, OR8G1, OR8G2, OR8H1, OR8H2, OR8H3, OR812, OR8J1, OR8J3, OR8K1, OR8K3, OR8K5, OR9A2, OR9A4, OR9G1, OR9G4, OR9G5, OR911, OR9K2, and OR9Q1; and
Mosquito (anopheles gambiae) odorant receptors, including, but not limited to, IOR100, IOR101, IOR102, IOR103, IOR104, IOR105, IOR106, IOR107, IOR108, IOR109, IOR110, IOR111, IOR112, IOR113, IOR114, IOR115, IOR116, IOR117, IOR118, IOR119, IOR120, IOR121, IOR122, IOR123, IOR124, IOR125, IOR126, IOR127, IOR49, IOR50, IOR51, IOR52, IOR53, IOR54, IOR55, IOR56, IOR57, IOR58, IOR59, IOR60, IOR61, IOR62, IOR63, IOR64, IOR65, IOR66, IOR67, IOR68, IOR69, IOR70, IOR71, IOR72, IOR73, IOR74, IOR75, IOR76, IOR77, IOR78, IOR79, IOR80, IOR81, IOR82, IOR83, IOR84, IOR85, IOR86, IOR87, IOR88, IOR89, IOR90, IOR91, IOR92, IOR93, IOR94, IOR95, IOR96, IOR97, IOR98, IOR99, ORL7077, ORL7078, ORL7079, ORL7080, ORL7081, ORL7082, ORL7083, ORL7084, ORL7085, ORL7086, ORL7087, ORL7088, ORL7089, ORL7090, ORL7091, ORL7092, ORL7093, ORL7094, ORL7095, ORL7096, ORL7097, ORL7098, ORL7099, ORL7100, ORL7101, ORL7102, ORL7103, ORL7104, ORL7105, ORL7106, ORL7107, ORL7108, ORL7109, ORL7110, ORL7111, ORL7112, ORL7113, ORL7114, ORL7115, ORL7116, ORL7117, ORL7118, ORL7119, ORL7120, ORL7121, ORL7122, ORL7123, ORL7124, ORL7125, TPR2307, TPR2308, TPR2309, TPR2310, TPR2312, TPR2314, TPR2315, TPR2316, TPR2317, TPR2318, TPR2319, TPR2320, TPR2321, TPR2321, TPR698, TPR699, TPR700, TPR701, TPR702, TPR703, TPR704, TPR705, TPR706, TPR707, TPR708, TPR709, TPR710, TPR711, TPR712, TPR713, TPR714, TPR715, TPR716, TPR717, TPR718, TPR719, TPR720, TPR721, TPR722, TPR723, TPR724, TPR725, TPR725, TPR726, TPR727, TPR728, TPR729, TPR730, TPR731, TPR732, TPR733, TPR734, TPR735, TPR736, TPR737, TPR738, TPR739, TPR740, TPR741, TPR742, TPR743, TPR744, TPR745, TPR746, TPR747, TPR748, TPR749, TPR750, TPR751, TPR752, TPR753, TPR754, TPR755, TPR756, TPR757, TPR758, TPR759, TPR760, TPR761, TPR762, TPR763, TPR764, TPR765, TPR766, TPR767, TPR768, TPR769, TPR770, TPR771, and TPR772.
Further examples of proteins of interest can be found in Tables 7-22 hereinbelow. In specific embodiments, spliced forms and/or SNPs of the proteins listed in Tables 7-22 may be expressed. In particular embodiments, any combination of any of the proteins listed in Tables 7-22 may be co-expressed in cells.
In one aspect, the cells and cell lines of the invention are suitable for use in a cell-based assay. Such cells and cell lines provide consistent and reproducible expression of the protein of interest over time and, thus, are particularly advantageous in such assays.
In another aspect, the invention provides cells and cell lines that are suitable for the production of biological molecules. The cells and cell lines for such use are characterized, for example, by consistent expression of a protein or polypeptide that is functional or that is capable of becoming functional.
The invention further provides a method for producing cells and cell lines that stably express an RNA or a protein of interest. Using the method of the invention, one can produce cells and cell lines that express any desired protein in functional form, including complex proteins such as multimeric proteins, (e.g., heteromultimeric proteins) and proteins that are cytotoxic. The method disclosed herein makes possible the production of engineered cells and cell lines stably expressing functional proteins that prior to this invention have not previously been produced. Without being bound by theory, it is believed that because the method permits investigation of very large numbers of cells or cell lines under any desired set of conditions, it makes possible the identification of rare cells that would not have been produced in smaller populations or could not otherwise be found and that are optimally suited to express a desired protein in a functional form under desired conditions. Without being limited by theory, many RNAs and proteins of interest are normally expressed in specialized cells (e.g. cells of specific tissues, cells of specialized tissues, cells of specialized functions, cells with specialized cellular domains or compartments, sensory cells, neurons, taste buds, epithelial cells, stem cells, cancer cells, muscle cells, cells of the eye, cells that produce antibodies, cells that produce high levels of proteins, as well as the various cell types disclosed herein). The specialized cells may provide a specific biological or cellular context, background or genetic make-up for non-cytotoxic or native functional or physiological expression of the RNAs or proteins of interest. For instance, the specialized cells may provide factors including accessory factors or chaperones or specialized cellular compartments for sufficient, proper or optimal expression, stoichiometry, production, folding, assembly, post-translational modification, targeting, membrane integration, secretion, function, pharmacology or physiology of the RNAs or proteins of interest. Engineering of cells or cell lines to express RNAs or proteins of interest that they do not normally express may result in the production of cells or cell lines where these conditions are not recapitulated nor approximated for optimal expression or function of RNAs or proteins of interest without associated cytotoxicity.
Many populations of cells that may be engineered to express an RNA or protein of interest are comprised of genetically diverse populations of individual cells where even the number of chromosomes may vary between cells. Rare cells included in these populations (compared to the average cell of such populations) may provide a biological or cellular context or background or genetic make-up that is sufficient, preferred, above average, improved, or optimal for native or non-cytotoxic expression, function, pharmacology or physiology of RNAs or proteins of interest that are not normally expressed in the average cell of the population of cells.
In some embodiments, the invention allows the analysis of millions of individual cells of populations of cells engineered to comprise an RNA or protein of interest such that individual cells that are compatible for the expression of the RNAs or proteins of interest can be rapidly or individually detected or isolated, even if this represents only rare cells in the population of cells. In some embodiments, rare cells that are compatible with viable, non-cytotoxic, functional or native expression of an RNA or protein of interest that normally results in cytotoxicity or cell death in the average cell of a the population of cells that is engineered to express the RNA or protein of interest may be detected and isolated. In some embodiments, according to the invention, each positive cell that is detected or isolated from a population of cells engineered to express an RNA or protein of interest may comprise different absolute or relative levels of each RNA or protein of interest. In some embodiments, each positive cell may further provide or comprise a different cellular or genetic context (e.g. different number of chromosomes or fragments of chromosomes, genes, gene sequences, expression profiles, or endogenously expressed proteins or RNAs including mRNAs or siRNAs, or accessory factors for the RNAs or proteins of interest) as the cellular background for the expression or function of the RNA or protein of interest. In some embodiments, the invention provides for the isolation of numerous engineered cells positive for the expression of an RNA or protein of interest coupled with novel methods that enable the maintenance of the isolated cells in culture. In some embodiments, the maintenance of the isolated cells in culture may be performed using conditions that are substantially identical for all of the cells that are maintained. In some embodiments, this in turn enables testing including functional testing of the isolated cells over time in culture to identify and produce functional stable cells or cell lines comprising desired or improved expression, function, physiology or pharmacology of the expressed RNA or protein of interest. In some embodiments, by isolating, maintaining and functionally testing numerous cells positive for the expression of an RNA or protein of interest, the methods allow identification or production of cells functionally, viably and stably expressing the RNAs or proteins of interest even for RNAs or proteins of interest that are not normally expressed in the average cell of the populations of cells engineered to express the RNAs or proteins of interest.
In fact, in some embodiments the methods were found to result in functional and stable expression of RNAs or proteins that had previously been considered to be cytotoxic when expressed in engineered cells, demonstrating the effectiveness with which the methods may be used to produce cells comprising the conditions that are required and compatible with non-cytotoxic expression of and function of such proteins which could not previously be modeled in engineered cells.
In a further aspect, the invention provides a matched panel of cell lines, i.e., a collection of clonal cell lines that are matched for one or more physiological properties. Because the method of the invention permits maintenance and characterization of large numbers of cell lines under identical conditions, it is possible to identify any number of cell lines with similar physiological properties. Using the method of the invention, it is possible to make matched panels comprising any desired number of cell lines or make up Such matched panels may be maintained under identical conditions, including cell density and, thus, are useful for high throughput screening and other uses where it is desired to compare and identify differences between cell lines. Also within the invention are matched panels of cell lines that are matched for growth rate.
In another aspect, the invention provides a method for producing cells or cell lines that express a protein of previously unknown function and/or for which no ligand had previously been identified. Such a protein may be a known naturally occurring protein, a previously unknown naturally occurring protein, a previously unknown form of a known naturally occurring protein or a modified form of any of the fore
Any desired cell type may be used for the cells of the invention. The cells may be prokaryotic or eukaryotic. The cells may express the protein of interest in their native state or not. Eukaryotic cells that may be used include but are not limited to fungi cells such as yeast cells, plant cells, insect cells and animal cells. Animal cells that can be used include but are not limited to mammalian cells. Primary or immortalized cells may be derived from mesoderm, ectoderm or endoderm layers of eukaryotic organisms. The cells may be endothelial, epidermal, mesenchymal, neural, renal, hepatic, hematopoietic, or immune cells. For example, the cells may be intestinal crypt or villi cells, clara cells, colon cells, intestinal cells, goblet cells, enterochromafin cells, enteroendocrine cells. Mammalian cells that are useful in the method include but are not limited to human, non-human primate, cow, horse, goat, sheep, pig, rodent (including rat, mouse, hamster, guinea pig), marsupial, rabbit, dog and cat. The cells can be differentiated cells or stem cells, including embryonic stem cells.
Cells of the invention can be primary, transformed, oncogenically transformed, virally transformed, immortalized, conditionally transformed, explants, cells of tissue sections, animals, plants, fungi, protists, archaebacteria and eubacteria, mammals, birds, fish, reptiles, amphibians, and arthropods, avian, chicken, reptile, amphibian, frog, lizard, snake, fish, worms, squid, lobster, sea urchin, sea slug, sea squirt, fly, squid, hydra, arthropods, beetles, chicken, lamprey, ricefish, zebra finch, pufferfish, and Zebrafish,
Additionally, cells such as blood/immune cells, endocrine (thyroid, parathyroid, adrenal), GI (mouth, stomach, intestine), liver, pancreas, gallbladder, respiratory (lung, trachea, pharynx), Cartilage, bone, muscle, skin, hair, urinary (kidney, bladder), reproductive (sperm, ovum, testis, uterus, ovary, penis, vagina), sensory (eye, ear, nose, mouth, tongue, sensory neurons), Blood/immune cells such as_B cell, T cell (Cytotoxic T cell, Natural Killer T cell, Regulatory T cell, T helper cell, γδ Tcell, Natural killer cell; granulocytes (basophil granulocyte, eosinophil granulocyte, neutrophil granulocyte/hypersegmented neutrophil), monocyte/macrophage, red blood cell (reticulocyte), mast cell, thrombocyte/Megakaryocyte, dendritic cell; endocrine cells such as: thyroid (thyroid epithelial cell, parafollicular cell), parathyroid (parathyroid chief cell, oxyphil cell), adrenal (chromaffin cell), nervous system cells such as: glial cells (astrocyte, microglia), magnocellular neurosecretory cell, stellate cell, nuclear chain cell, boettcher cell, pituitary, (gonadotrope, corticotrope, thyrotrope, somatotrope, lactotroph), respiratory system cells such as pneumocyte (type I pneumocyte, type II pneumocyte), clara cell, goblet cell; circulatory system cells such as myocardiocyte•pericyte; digestive system cells such as stomach (gastric chief cell, parietal cell), goblet cell, paneth cell, G cells, D cells, ECL cells, I cells, K cells, enteroendocrine cells, enterochromaffin cell, APUD cell, liver (hepatocyte, kupffer cell), pancreas (beta cells, alpha cells), gallbladder; cartilage/bone/muscle/integumentary system cells such as osteoblast, osteocyte, osteoclast, tooth cells (cementoblast, ameloblast), cartilage cells: chondroblast, chondrocyte, skin/hair cells: trichocyte, keratinocyte, melanocyte, muscle cells: myocyte, adipocyte, fibroblast, urinary system cells such as podocyte, juxtaglomerular cell, intraglomerular mesangial cell/extraglomerular mesangial cell, kidney proximal tubule brush border cell, macula densa cell; reproductive system cells such as spermatozoon, sertoli cell, leydig cell, ovum, ovarian follicle cell; sensory cells such as organ of corti cells, olfactory epithelium, temperature sensitive sensory neurons, merckel cells, olfactory receptor neuron, pain sensitive neurons, photoreceptor cells, taste bud cells, hair cells of the vestibular apparatus, carotid body cells are useful to make cells or cell lines of the invention.
Plant cells that are useful include roots, stems and leaves and plant tissues include meristematic tissues, parenchyma collenchyma, sclerenchyma, secretory tissues, xylem, phloem, epidermis, periderm (bark).
Cells that are useful for the cells and cell lines of the invention also include but are not limited to: Chinese hamster ovary (CHO) cells, established neuronal cell lines, pheochromocytomas, neuroblastomas fibroblasts, rhabdomyosarcomas, dorsal root ganglion cells, NS0 cells, CV-1 (ATCC CCL 70), COS-1 (ATCC CRL 1650), COS-7 (ATCC CRL 1651), CHO-K1 (ATCC CCL 61), 3T3 (ATCC CCL 92), NIH/3T3 (ATCC CRL 1658), HeLa (ATCC CCL 2), C127I (ATCC CRL 1616), BS-C-1 (ATCC CCL 26), MRC-5 (ATCC CCL 171), L-cells, HEK-293 (ATCC CRL1573) and PC12 (ATCC CRL-1721), HEK293T (ATCC CRL-11268), RBL (ATCC CRL-1378), SH-SY5Y (ATCC CRL-2266), MDCK (ATCC CCL-34), SJ-RH30 (ATCC CRL-2061), HepG2 (ATCC HB-8065), ND7/23 (ECACC 92090903), CHO (ECACC 85050302), Vero (ATCC CCL 81), Caco-2 (ATCC HTB 37), K562 (ATCC CCL 243), Jurkat (ATCC TIB-152), Per.C6 (Crucell, Leiden, The Netherlands), Huvec (ATCC Human Primary PCS 100-010, Mouse CRL 2514, CRL 2515, CRL 2516), HuH-7D12 (ECACC 01042712), 293 (ATCC CRL 10852), A549 (ATCC CCL 185), IMR-90 (ATCC CCL 186), MCF-7 (ATC HTB-22), U-20S (ATCC HTB-96), T84 (ATCC CCL 248), or any established cell line (polarized or nonpolarized) or any cell line available from repositories such as American Type Culture Collection (ATCC, 10801 University Blvd. Manassas, Va. 20110-2209 USA) or European Collection of Cell Cultures (ECACC, Salisbury Wiltshire SP4 0JG England).
Further, cells that are useful in the method of the invention are mammalian cells amenable to growth in serum containing media, serum free media, fully defined media without any animal-derived products, and cells that can be converted from one of these conditions to another.
Cells of the invention include cells into which a nucleic acid that encodes the protein of interest (or in the case of a heteromultimeric protein, a nucleic acid that encodes one or more of the subunits of the protein) has been introduced. Engineered cells also include cells into which nucleic acids for transcriptional activation of an endogenous sequence encoding a protein of interest (or for transcriptional activation of endogenous sequence encoding one or more subunits of a heteromultimeric protein) have been introduced. Engineered cells also include cells comprising a nucleic acid encoding a protein of interest that is activated by contact with an activating compound or following post-translational modification, treatment with or contact with an enzyme including but not limited to a protease. Engineered cells further include combinations of the foregoing, that is, cells that express one or more subunits of a heteromultimeric protein from an introduced nucleic acid encoding it and that express one or more subunits of the protein by gene activation.
Any of the nucleic acids may be introduced into the cells using known means. Techniques for introducing nucleic acids into cells are well-known and readily appreciated by the skilled worker. The methods include but are not limited to transfection, viral delivery, protein or peptide mediated insertion, coprecipitation methods, lipid based delivery reagents (lipofection), cytofection, lipopolyamine delivery, dendrimer delivery reagents, electroporation or mechanical delivery. Examples of transfection reagents are GENEPORTER, GENEPORTER2, LIPOFECTAMINE, LIPOFECTAMINE 2000, FUGENE 6, FUGENE HD, TFX-10, TFX-20, TFX-50, OLIGOFECTAMINE, TRANSFAST, TRANSFECTAM, GENESHUTTLE, TROJENE, GENESILENCER, X-TREMEGENE, PERFECTIN, CYTOFECTIN, SIPORT, UNIFECTOR, SIFECTOR, TRANSIT-LT1, TRANSIT-LT2, TRANSIT-EXPRESS, IFECT, RNAI SHUTTLE, METAFECTENE, LYOVEC, LIPOTAXI, GENEERASER, GENEJUICE, CYTOPURE, JETSI, JETPEI, MEGAFECTIN, POLYFECT, TRANSMESSANGER, RNAiFECT, SUPERFECT, EFFECTENE, TF-PEI-KIT, CLONFECTIN, and METAFECTINE.
Where two or more nucleotide sequences are introduced, such as sequences encoding two or more subunits of a heteromultimeric protein or sequences encoding two or more different proteins of interest, the sequences may be introduced on the same vector or, preferably, on separate vectors. The DNA can be genomic DNA, cDNA, synthetic DNA or mixtures of them. In some embodiments, nucleic acids encoding a protein of interest or a partial protein of interest do not include additional sequences such that the protein of interest is expressed with additional amino acids that may alter the function of the cells compared to the physiological function of the protein.
In some embodiments, the nucleic acid encoding the protein of interest comprises one or more substitutions, insertions, mutations or deletions, as compared to a nucleic acid sequence encoding the wild-type protein. In embodiments comprising a nucleic acid comprising a mutation, the mutation may be a random mutation or a site-specific mutation. These nucleic acid changes may or may not result in an amino acid substitution. In some embodiments, the nucleic acid is a fragment of the nucleic acid that encodes the protein of interest. Nucleic acids that are fragments or have such modifications encode polypeptides that retain at least one biological property of the protein of interest.
The invention also encompasses cells and cell lines stably expressing a nucleic acid, whose sequence is at least about 85% identical to the “wild type” sequence encoding the protein of interest, or a counterpart nucleic acid derived from a species other than human or a nucleic acid that encodes the same amino acid sequence as any of those nucleic acids. In some embodiments, the sequence identity is at least 85%, 90%, 95%, 96%, 97%, 98%, 99% or higher compared to those sequences. The invention also encompasses cells and cell lines wherein the nucleic acid encoding a protein of interest hybridizes under stringent conditions to the wild type sequence or a counterpart nucleic acid derived from a species other than human, or a nucleic acid that encodes the same amino acid sequence as any of those nucleic acids.
In some embodiments, the cell or cell line comprises a protein-encoding nucleic acid sequence comprising at least one substitution as compared to the wild-type sequence or a counterpart nucleic acid derived from a species other than human or a nucleic acid that encodes the same amino acid sequence as any of those nucleic acids. The substitution may comprise less than 10, 20, 30, or 40 nucleotides or, up to or equal to 1%, 5%, 10% or 20% of the nucleotide sequence. In some embodiments, the substituted sequence may be substantially identical to the wild-type sequence or a counterpart nucleic acid derived from a species other than human a nucleic acid that encodes the same amino acid sequence as any of those nucleic acids (e.g., a sequence at least 85%, 90%, 95%, 96%, 97%, 98%, 99% or higher identical thereto), or be a sequence that is capable of hybridizing under stringent conditions to the wild type sequence or a counterpart nucleic acid derived from a species other than human or a nucleic acid that encodes the same amino acid sequence as any one of those nucleic acids.
In some embodiments, the cell or cell line comprises protein-encoding nucleic acid sequence comprising an insertion into or deletion from the wild type sequence or a counterpart nucleic acid derived from a species other than human or a nucleic acid that encodes the same amino acid sequence as any of those nucleic acids. The insertion or deletion may be less than 10, 20, 30, or 40 nucleotides or up to or equal to 1%, 5%, 10% or 20% of the nucleotide sequence. In some embodiments, the sequences of the insertion or deletion may be substantially identical to the wild type sequence or a counterpart nucleic acid derived from a species other than human or a nucleic acid that encodes the same amino acid sequence as any of those nucleic acids (e.g., a sequence at least 85%, 90%, 95%, 96%, 97%, 98%, 99% or higher identical thereto), or be a sequence that is capable of hybridizing under stringent conditions to the wild-type sequence or a counterpart nucleic acid derived from a species other than human, or a nucleic acid that encodes the same amino acid sequence as any of those nucleic acids.
In some embodiments, the nucleic acid substitution or modification results in an amino acid change, such as an amino acid substitution. For example, an amino acid residue of the wild type protein of interest or a counterpart amino acid derived from a species other than human may be replaced by a conservative or a non-conservative substitution. In some embodiments, the sequence identity between the original and modified amino acid sequence can differ by about 1%, 5%, 10% or 20% or from a sequence substantially identical thereto (e.g., a sequence at least 85%, 90%, 95%, 96%, 97%, 98%, 99% or higher identical thereto).
A “conservative amino acid substitution” is one in which an amino acid residue is substituted by another amino acid residue having a side chain R group with similar chemical properties to the parent amino acid residue (e.g., charge or hydrophobicity). In cases where two or more amino acid sequences differ from each other by conservative substitutions, the percent sequence identity or degree of similarity may be adjusted upwards to correct for the conservative nature of the substitution. Means for making this adjustment are well-known to those of skill in the art. See, e.g., Pearson, Methods Mol. Biol. 243:307-31 (1994).
Examples of groups of amino acids that have side chains with similar chemical properties include 1) aliphatic side chains: glycine, alanine, valine, leucine, and isoleucine; 2) aliphatic-hydroxyl side chains: serine and threonine; 3) amide-containing side chains: asparagine and glutamine; 4) aromatic side chains: phenylalanine, tyrosine, and tryptophan; 5) basic side chains: lysine, arginine, and histidine; 6) acidic side chains: aspartic acid and glutamic acid; and 7) sulfur-containing side chains: cysteine and methionine. Preferred conservative amino acids substitution groups are: valine-leucine-isoleucine, phenylalanine-tyrosine, lysine-arginine, alanine-valine, glutamate-aspartate, and asparagine-glutamine. Alternatively, a conservative amino acid substitution is any change having a positive value in the PAM250 log-likelihood matrix disclosed in Gonnet et al., Science 256:1443-45 (1992). A “moderately conservative” replacement is any change having a nonnegative value in the PAM250 log-likelihood matrix.
Conservative modifications in the protein of interest will produce proteins having functional and chemical characteristics similar (i.e. at least 50%, 60%, 70%, 80%, 90% or 95% the same) to those of the unmodified protein.
In one embodiment, the host cell is an embryonic stem cell that is then used as the basis for the generation of transgenic animals that produce the protein of interest. Embryonic stem cells stably expressing a functional protein of interest, may be implanted into organisms directly, or their nuclei may be transferred into other recipient cells and these may then be implanted, or they may be used to create transgenic animals. In some embodiments the protein may be expressed in the animal with desired temporal and/or tissue specific expression.
As will be appreciated by those of skill in the art, any vector that is suitable for use with a chosen host cell may be used to introduce a nucleic acid encoding a protein of interest into a host cell. Where more than one vector is used, for example, to introduce two or more different subunits or two or more proteins of interest, the vectors may be the same type or may be of different types.
Examples of vectors that may be used to introduce the nucleic acids into host cells include but are not limited to plasmids, viruses, including retroviruses and lentiviruses, cosmids, artificial chromosomes and may include, for example, pCMVScript, pcDNA3.1 Hygro, pcDNA3.1neo, pcDNA3.1puro, pSV2neo, pIRES puro, pSV2 zeo. Exemplary mammalian expression vectors that are useful to make the cells and cell lines of the invention include: pFN11A (BIND) Flexi®, pGL4.31, pFC14A (HaloTag® 7) CMV Flexi®, pFC14K (HaloTag® 7) CMV Flexi®, pFN24A (HaloTag® 7) CMVd3 Flexi®, pFN24K (HaloTag® 7) CMVd3 Flexi®, HaloTag™ pHT2, pACT, pAdVAntage™, pALTER®-MAX, pBIND, pCAT®3-Basic, pCAT®3-Control, pCAT®3-Enhancer, pCAT®3-Promoter, pCI, pCMVTNT™, pG5luc, pSI, pTARGET™, pTNT™, pF12A RM Flexi®, pF12K RM Flexi®, pReg neo, pYES2/GS, pAd/CMV/V5-DEST Gateway® Vector, pAd/PL-DEST™ Gateway® Vector, Gateway® pDEST™27 Vector, Gateway® pEF-DEST51 Vector, Gateway® pcDNA™-DEST47 vector, pCMV/Bsd Vector, pEF6/His A, B, & c, pcDNA™6.2-DEST, pLenti6/TR, pLP-AcGFP1-C, pLPS-AcGFP1-N, pLP-IRESneo, pLP-TRE2, pLP-RevTRE, pLP-LNCX, pLP-CMV-HA, pLP-CMV-Myc, pLP-RetroQ and pLP-CMVneo.
In some embodiments, the vectors comprise expression control sequences such as constitutive or conditional promoters, preferably, constitutive promoters are used. One of ordinary skill in the art will be able to select such sequences. For example, suitable promoters include but are not limited to CMV, TK, SV40 and EF-1α. In some embodiments, the promoters are inducible, temperature regulated, tissue specific, repressible, heat-shock, developmental, cell lineage specific, eukaryotic, prokaryotic or temporal promoters or a combination or recombination of unmodified or mutagenized, randomized, shuffled sequences of any one or more of the above. In other embodiments, the protein of interest is expressed by gene activation or episomally.
In some embodiments, the vector lacks a selectable marker or drug resistance gene. In other embodiments, the vector optionally comprises a nucleic acid encoding a selectable marker, such as a protein that confers drug or antibiotic resistance or more generally any product that exerts selective pressure on the cell. Where more than one vector is used, each vector may have the same or a different drug resistance or other selective pressure marker. If more than one of the drug resistance or selective pressure markers are the same, simultaneous selection may be achieved by increasing the level of the drug. Suitable markers are well-known to those of skill in the art and include but are not limited to polypeptides products conferring resistance to any one of the following: Neomycin/G418, Puromycin, hygromycin, Zeocin, methotrexate and blasticidin. Although drug selection (or selection using any other suitable selection marker) is not a required step in producing the cells and cell lines of this invention, it may be used to enrich the transfected cell population for stably transfected cells, provided that the transfected constructs are designed to confer drug resistance. If subsequent selection of cells expressing the protein of interest is accomplished using signaling probes, selection too soon following transfection can result in some positive cells that may only be transiently and not stably transfected. However, this effect can be minimized by allowing sufficient cell passage to allow for dilution of transient expression in transfected cells.
Selective pressure can be applied to cells using a variety of compounds or treatments that would be known to one of skill in the art. Without being limited by theory, selective pressure can be applied by exposing cell to conditions that are suboptimal for or deleterious to cell growth, progression of the cell cycle or viability, such that cells that are tolerant or resistant to these conditions are selected for compared to cells that are not tolerant or resistant to these conditions. Conditions that can be used to exert or apply selective pressure include but are not limited to antibiotics, drugs, mutagens, compounds that slow or halt cell growth or the synthesis of biological building blocks, compounds that disrupt RNA, DNA or protein synthesis, deprivation or limitation of nutrients, amino acids, carbohydrates or compounds required for cell growth and viability from cell growth or culture media, treatments such as growth or maintenance of cells under conditions that are suboptimal for cell growth, for instance at suboptimal temperatures, atmospheric conditions (e.g., % carbon dioxide, oxygen or nitrogen or humidity) or in deprived media conditions. Without being limited by theory, selective pressure can be used to select a marker, factor or gene that confers or encodes resistance or tolerance to the selective pressure. For instance, (i) a population of cells can first be exposed to or introduced with such a marker, factor or gene that confers resistance or tolerance to a selective pressure such that each cell will uptake or be modified to comprise a different level or none of the marker, factor or gene, and (ii) the population can then be exposed to the selective pressure for which the marker, factor or gene confers resistance or tolerance such that cells that comprise the marker, factor or gene comprise a growth advantage compared to cells that do not. Without being limited by theory, cells comprising increased levels of the marker, factor or gene will exhibit a proportionally increased tolerance to the corresponding selective pressure. Selective pressure can be used to select for cells comprising a desired property, RNA or protein of interest by association of the property, RNA or protein with a marker, factor or gene that confers tolerance or resistance to the corresponding selective pressure. Without being limited by theory, cells with proportionally increased levels of the desired property, RNA or protein of interest may be selected by applying proportionally increased levels or amounts or selective pressure during the selection process. If cells comprising multiple properties, RNAs or proteins are desired, each of these can be associated a marker, factor or gene that confers resistance to the same or a different form of selective pressure and selection using all of these selective pressures may be used to select for cells comprising all of the desired properties, RNAs or proteins of interest. After selection of cells with desired properties, RNAs or proteins of interest, the selected cells may be maintained under the same, increased or decreased levels, concentrations, doses, or treatments of selective pressure that was used during selection. In some cases, periodic increases of the levels, concentrations, doses, or treatments of selective pressure can be used to select for amplification of cells comprising correspondingly increasing levels of the desired property, RNA or protein of interest. In some cases, following the selection of cells using selective pressure, the selected cells are maintained using reduced levels, concentrations, doses, or treatments of the selective pressure to help ensure that the desired property, RNA or protein that was selected for is maintained in the cells that are maintained.
The level of selective pressure that is used can be determined by one of skill in the art. This can be done for instance by performing a kill curve experiment, where control cells and cells that comprise resistance markers, factors or genes are tested with increasing levels, doses, concentrations or treatments of the selective pressure and the ranges that selected against the negative cells only or preferentially over a desired range of time (e.g., from 1 to 24 hours, 1 to 3 days, 3 to 5 days, 4 to 7 days, 5 to 14 days, 1 to 3 weeks, 2 to 6 weeks, 1 to 2 months, 1 to 3 months, 4, 5, 6, 7, 8, 9, or more than 10 months). The exact levels, concentrations, doses, or treatments of selective pressure that can be used depends on the cells that are used, the desired properties themselves, the markers, factors or genes that confer resistance or tolerance to the selective pressure as well as the levels of the desired properties that are desired in the cells that are selected and one of skill in the art would readily appreciate how to determine appropriate ranges based on these considerations. In some cases following selection, less than 1, 5, 10, 20, 30, 40, 50, 60, 70, 80, 90 or 100% of the levels, concentrations, doses, or treatments of selective pressure used during the selection process are used in the subsequent maintenance of the cells that are selected. In some cases where multiple different selective pressures are used, the levels, concentrations, doses, or treatments of each selective pressure used during the selection process can be reduced in the subsequent maintenance of the cells that are selected, e.g., to less than 1, 5, 10, 20, 30, 40, 50, 60, 70, 80, 90 or 100% of those used during the selection process itself. In some embodiments, these reduced levels, concentrations, doses, or treatments are selected such that the cells that are selected to comprise desired properties, RNAs or proteins continue to comprise the desired properties over time in culture. In some embodiments, no more than the levels, concentrations, doses, or treatments necessary to prevent a loss or diminishment of the desired properties in the selected cells is used during the maintenance of the cells over time in culture, for instance to minimize the exposure of the cells to any possible deleterious effects to the cells from the use of higher levels, concentrations, doses, or treatments than necessary for the cells to maintain the properties, RNAs or proteins for which they were selected.
In some embodiments, cells and cell lines of the present invention are capable of maintaining the properties, RNAs or proteins for which they are selected for (e.g., expression of the proteins or RNAs of interest) in the absence of selective pressure for at least 15 days, 30 days, 45 days, 60 days, 75 days, 100 days, 120 days, or 150 days. Such cells and cell lines may be cultured in the presence of the same, increased, or reduced levels, concentrations, doses, or treatments of selective pressure, as compared to the those used in the selection process. Such cells and cell lines can also be cultured in the absence of any selective pressure. In the case where the levels, concentrations, doses or treatments are reduced, they can be reduced to less than 1, 5, 10, 20, 30, 40, 50, 60, 70, 80, 90 or 100% of the respective levels, concentrations, doses or treatments used during the selection process. In the case where the cells and cell lines express more than one protein or RNA of interest, and expression of each protein or RNA of interest is selected for using a different selective pressure, the levels, concentrations, doses or treatments of each selective pressure may be independently chosen during culturing of the cells and cell lines following selection, e.g., each selective pressure may be independently chosen to be absent in the cell culture, or to be at the same, or an increased or reduced level, concentration, dose or treatment as compared to its respective level, concentration, dose or treatment used during the selection process. In the case where the levels, concentrations, doses or treatments are reduced, they can be reduced to less than 1, 5, 10, 20, 30, 40, 50, 60, 70, 80, 90 or 100% of the respective levels, concentrations, doses or treatments used during the selection process.
In some embodiments, the protein-encoding nucleic acid sequence further comprises a tag. Such tags may encode, for example, a HIS tag, a myc tag, a hemagglutinin (HA) tag, protein C, VSV-G, FLU, yellow fluorescent protein (YFP), green fluorescent protein, FLAG, BCCP, maltose binding protein tag, Nus-tag, Softag-1, Softag-2, Strep-tag, S-tag, thioredoxin, GST, V5, TAP or CBP. A tag may be used as a marker to determine protein expression levels, intracellular localization, protein-protein interactions, regulation of the protein of interest, or the protein's function. Tags may also be used to purify or fractionate proteins.
In the case of cells and cell lines expressing an RNA of interest, the RNA can be of any type including antisense RNA, short interfering RNA (siRNA), transfer RNA (tRNA), structural RNA, ribosomal RNA, heterogeneous nuclear RNA (hnRNA) and small nuclear RNA (snRNA), messenger RNA (mRNA), RNA that adopts a stem-loop structure, RNA that adopts a hairpin structure, RNA that comprises single stranded RNA, RNA that comprises double stranded RNA, RNA that binds protein, RNA that binds a fluorescent compound, RNA that has biological activity, RNA that encodes a biologically active product, catalytic RNA, RNA oligonucleotide, RNA that can mediate RNAi or RNA that can regulate the level or activity of at least a second RNA.
In embodiments in which the cells and cell lines of the invention express a functional protein of interest, the protein can be any protein including but not limited to single chain proteins, multi-chain proteins, hetero-multimeric proteins. In the case of multimeric proteins, in some embodiments the cells express all of the subunits that make up the native protein. The protein can have a “wild type” sequence or may be a variant. In some embodiments, the cells express a protein that comprises a variant of one or more of the subunits including allelic variants, splice variants, truncated forms, isoforms, different stoichiometries of subunits, different assemblies of subunits, differentially folded forms, differentially active forms, forms with different functionalities, forms with different binding properties, forms associated with different accessory factors, forms expressed in different cell backgrounds, forms expressed in different cellular genetic backgrounds, forms expressed in cells with different endogenous expression profiles, differentially localized forms, chimeric or chemically modified forms, enzymatically modified forms, post-translationally modified forms, glycosylated forms, proteolyzed forms, chimeric subunits and mutated forms that comprise amino acid substitutions (conservative or non-conservative), modified amino acids including chemically modified amino acids, and non-naturally occurring amino acids, and combinations thereof. A heteromultimeric protein expressed by cells or cell lines of the invention may comprise subunits from two or more species, such as from species homologs of the protein of interest.
In some embodiments, the cells of the invention express two or more functional proteins of interest. According to the invention, such expression can be from the introduction of a nucleic acid encoding all or part of a protein of interest, from the introduction of a nucleic acid that activates the transcription of all or part of a protein of interest from an endogenous sequence or from any combination thereof. The cells may express any desired number of proteins of interest. In various embodiments, the cells express three, four, five, six, or more proteins of interest. For example, the invention contemplates cells and cell lines that stably express functional proteins in a pathway of interest, proteins from intersecting pathways including enzymatic pathways, signaling pathways regulatory pathways and the like. In some embodiments, the cells or cell lines of the invention stably express one or more functional RNAs and/or proteins involved in a biological pathway of interest, e.g., protein and/or RNA components of the biological pathway and protein and/or RNA regulators of the biological pathway and/or one or more of its components. In some embodiments, the biological pathway consists of at least 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 25, 30, 35, 40, 45, or at least 50 protein components. In some embodiments, the biological pathway consists of at least 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 25, 30, 35, 40, 45, or at least 50 RNA components. Examples of biological pathways in which functional proteins can be stably expressed by the cells and cell lines of the present invention include, but are not limited to: 2-arachidonoylglycerol biosynthesis pathway, 5-hydroxytryptamine biosynthesis pathway, 5-hydroxytryptamine degredation pathway, 5ht1 type receptor mediated signaling pathway, 5ht2 type receptor mediated signaling pathway, 5ht3 type receptor mediated signaling pathway, 5ht4 type receptor mediated signaling pathway, acetate utilization pathway, adenine and hypoxanthine salvage pathway, adrenaline and noradrenaline biosynthesis pathway, alanine biosynthesis pathway, allantoin degradation pathway, alpha adrenergic receptor signaling pathway, alzheimer disease-amyloid secretase pathway, alzheimer disease-presenilin pathway, aminobutyrate degradation pathway, anandamide biosynthesis pathway, anandamide degradation pathway, androgen/estrogen/progesterone biosynthesis pathway, angiogenesis pathway, angiotensin ii-stimulated signaling pathway through G proteins and beta-arrestin, apoptosis signaling pathway, arginine biosynthesis pathway, ascorbate degradation pathway, asparagine and aspartate biosynthesis pathway, ATP synthesis pathway, axon guidance mediated by netrin, axon guidance mediated by semaphorins, axon guidance mediated by slit/robo, B cell activation pathway, beta1 adrenergic receptor signaling pathway, beta2 adrenergic receptor signaling pathway, beta3 adrenergic receptor signaling pathway, biotin biosynthesis pathway, blood coagulation pathway, bupropion degradation pathway, cadherin signaling pathway, carnitine metabolism pathway, cell cycle pathway, cholesterol biosynthesis pathway, chorismate biosynthesis pathway, circadian clock system pathway, cobalamin biosynthesis pathway, coenzyme A biosynthesis pathway, coenzyme A linked carnitine metabolism pathway, corticotropin releasing factor receptor signaling pathway, cysteine biosynthesis pathway, cytoskeletal regulation by rho gtpase, de novo purine biosynthesis pathway, de novo pyrimidine deoxyribonucleotide biosynthesis pathway, de novo pyrimidine ribonucleotides biosynthesis pathway, DNA replication, dopamine receptor mediated signaling pathway, egf receptor signaling pathway, endogenous cannabinoid signaling pathway, endothelin signaling pathway, enkephalin release pathway, fas signaling pathway, fgf signaling pathway, flavin biosynthesis pathway, formyltetrahydroformate biosynthesis pathway, fructose galactose metabolism pathway, GABA-b receptor ii signaling pathway, gamma-aminobutyric acid synthesis pathway, general transcription by RNA polymerase I, general transcription regulation, glutamine glutamate conversion pathway, glycolysis pathway, hedgehog signaling pathway, heme biosynthesis pathway, heterotrimeric G-protein signaling pathway-gi alpha and gs alpha mediated pathway, heterotrimeric G-protein signaling pathway-gq alpha and go alpha mediated pathway, heterotrimeric G-protein signaling pathway-rod outer segment phototransduction pathway, histamine h1 receptor mediated signaling pathway, histamine h2 receptor mediated signaling pathway, histamine synthesis pathway, histidine biosynthesis pathway, huntington disease, hypoxia response via hif activation, inflammation mediated by chemokine and cytokine signaling pathway, insulin/igf pathway-mitogen activated protein kinase kinase/map kinase cascade, insulin/igf pathway-protein kinase B signaling cascade, integrin signalling pathway, interferon-gamma signaling pathway, interleukin signaling pathway, ionotropic glutamate receptor pathway, isoleucine biosynthesis pathway, jak/stat signaling pathway, leucine biosynthesis pathway, lipoate biosynthesis pathway, lysine biosynthesis pathway, mannose metabolism pathway, metabotropic glutamate receptor group i pathway, metabotropic glutamate receptor group ii pathway, metabotropic glutamate receptor group iii pathway, methionine biosynthesis pathway, methylcitrate cycle, methylmalonyl pathway, mRNA splicing, muscarinic acetylcholine receptor 1 and 3 signaling pathway, muscarinic acetylcholine receptor 2 and 4 signaling pathway, n-acetylglucosamine metabolism, nicotine degradation pathway, nicotinic acetylcholine receptor signaling pathway, notch signaling pathway, o-antigen biosynthesis pathway, opioid prodynorphin pathway, opioid proenkephalin pathway, opioid proopiomelanocortin pathway, ornithine degradation pathway, oxidative stress response pathway, oxytocin receptor mediated signaling pathway, p38 mapk pathway, p53 pathway, p53 pathway by glucose deprivation, p53 pathway feedback loops 1, p53 pathway feedback loops 2, pantothenate biosynthesis pathway, parkinson disease, PDGF signaling pathway, pentose phosphate pathway, peptidoglycan biosynthesis pathway, phenylacetate degradation pathway, phenylalanine biosynthesis pathway, phenylethylamine degradation pathway, phenylpropionate degradation pathway, pi3 kinase pathway, plasminogen activating cascade, proline biosynthesis pathway, prpp biosynthesis pathway, purine metabolism, pyridoxal phosphate salvage pathway, pyridoxal-5-phosphate biosynthesis pathway, pyrimidine metabolism, pyruvate metabolism, ras pathway, s-adenosylmethionine biosynthesis pathway, salvage pyrimidine deoxyribonucleotides, salvage pyrimidine ribonucleotides, serine glycine biosynthesis pathway, succinate to proprionate conversion, sulfate assimilation pathway, synaptic vesicle trafficking, T cell activation pathway, TCA cycle, tetrahydrofolate biosynthesis pathway, TGF-beta signaling pathway, thiamin biosynthesis pathway, thiamin metabolism, threonine biosynthesis pathway, thyrotropin-releasing hormone receptor signaling pathway, toll receptor signaling pathway, transcription regulation by bzip transcription factor, triacylglycerol metabolism, tryptophan biosynthesis pathway, tyrosine biosynthesis pathway, ubiquitin proteasome pathway, valine biosynthesis pathway, vasopressin synthesis pathway, VEGF signaling pathway, vitamin B6 biosynthesis pathway, vitamin B6 metabolism, vitamin D metabolism and pathway, wnt signaling pathway, and xanthine and guanine salvage pathway.
Other examples of biological pathways in which functional proteins can be stably expressed by the cells and cell lines of the present invention include, but are not limited to, the following biological processes: amino acid metabolism (e.g., amino acid biosynthesis, amino acid catabolism, amino acid metabolism regulation, amino acid transport and other amino acid metabolism), transport (e.g., amino acid transport, carbohydrate transport, vitamin/cofactor transport, anion transport, cation transport, lipid and fatty acid transport, nucleoside, nucleotide and nucleic acid transport, phosphate transport, extracellular transport and import, small molecule transport and other transports), apoptosis (e.g., induction of apoptosis, inhibition of apoptosis other apoptosis, and other apoptotic processes), blood circulation and gas exchange, carbohydrate metabolism (e.g., carbohydrate transport, disaccharide metabolism, gluconeogenesis, glycogen metabolism, glycolysis, monosaccharide metabolism, other carbohydrate metabolism, other polysaccharide metabolism, pentose-phosphate shunt, regulation of carbohydrate metabolism and tricarboxylic acid pathway), cell adhesion, cell cycle (e.g., cell cycle control, DNA replication, mitosis and other cell cycle processes), cell proliferation and differentiation, cell structure and motility, coenzyme and prosthetic group metabolism (e.g., coenzyme metabolism, porphyrin metabolism, pterin metabolism, vitamin/cofactor transport, vitamin biosynthesis, vitamin catabolism and other coenzyme and prosthetic group metabolism), developmental processes (e.g., ectoderm development, anterior/posterior patterning, determination of dorsal/ventral axis, embryogenesis, endoderm development, fertilization, meiosis, mesoderm development, segment specification, sex determination, oogenesis, spermatogenesis and motility, and other developmental processes), electron transport (e.g., ferredoxin metabolism, oxidative phosphorylation and other pathways of electron transport), homeostasis (calcium ion homeostasis, glucose homeostasis, growth factor homeostasis and other homeostasis activities), immunity and defense (e.g., antioxidation and free radical removal, B-cell- and antibody-mediated immunity, blood clotting, complement-mediated immunity, cytokine/chemokine mediated immunity, detoxification, granulocyte-mediated immunity, interferon-mediated immunity, macrophage-mediated immunity, natural killer cell mediated immunity, stress response, T-cell mediated immunity and other immune and defense processes), intracellular protein traffic (e.g., exocytosis, endocytosis, general vesicle transport, lysosome transport, mitochondrial transport, nuclear transport, peroxisome transport and other intracellular protein traffic), lipid, fatty acid and steroid metabolism (e.g., acyl-coa metabolism, fatty acid beta-oxidation, fatty acid biosynthesis, fatty acid desaturation, lipid and fatty acid binding, lipid and fatty acid transport, lipid metabolism, and other lipid, fatty acid and steroid metabolism, phospholipid metabolism, regulation of lipid, fatty acid and steroid metabolism, bile acid metabolism, cholesterol metabolism, steroid hormone metabolism and other steroid metabolism), muscle contraction, neuronal activities (e.g., action potential propagation, nerve-nerve synaptic transmission, neuromuscular synaptic transmission, neurotransmitter release and other neuronal activities), nitrogen metabolism (e.g., nitric oxide biosynthesis, nitrogen utilization and other nitrogen metabolism), non-vertebrate process, nucleoside, nucleotide and nucleic acid metabolism (e.g., DNA replication, DNA degradation, DNA recombination, DNA repair, chromatin packaging and remodeling, metabolism of cyclic nucleotides, nucleoside, nucleotide and nucleic acid transport, other nucleoside, nucleotide and nucleic acid metabolism, purine metabolism, pyrimidine metabolism, RNA catabolism, RNA localization, regulation of nucleoside, nucleotide metabolism, reverse transcription, RNA metabolism, tRNA metabolism, mRNA capping, mRNA end-processing and stability, mRNA polyadenylation, mRNA splicing, general mRNA transcription activities, other mRNA transcription, mRNA transcription elongation, mRNA transcription initiation, mRNA transcription regulation and mRNA transcription termination), oncogenesis (e.g., oncogene, tumor suppressor and other oncogenesis-related processes), phosphate metabolism (e.g., phosphate transport, polyphosphate biosynthesis, polyphosphate catabolism, regulation of phosphate metabolism and other phosphate metabolism), protein metabolism and modification (e.g., proteolysis, amino acid activation and other protein metabolism, protein biosynthesis, protein complex assembly, protein folding, translational regulation, protein ADP-ribosylation, protein acetylation, protein disulfide-isomerase reaction, protein glycosylation, protein methylation, protein phosphorylation, protein-lipid modification), protein targeting and localization (e.g., asymmetric protein localization and other protein targeting and localization), sensory perception (e.g., olfaction, taste, hearing, pain sensation, pheromone response, vision and other sensory perception), sulfur metabolism (e.g., sulfur redox metabolism and other sulfur metabolism), cell communication (e.g., cell adhesion-mediated signaling, extracellular matrix protein-mediated signaling, ligand-mediated signaling and steroid hormone-mediated signaling), cell surface receptor mediated signal transduction (e.g., cytokine and chemokine mediated signaling pathway, G-protein mediated signaling, receptor protein serine/threonine kinase signaling pathway, receptor protein tyrosine kinase signaling pathway and other receptor mediated signaling pathway), intracellular signaling cascade (e.g., calcium mediated signaling, jak-stat cascade, JNK cascade, MAPKKK cascade, NF-kappaB cascade, NO mediated signal transduction and other intracellular signaling cascade), and other signal transduction processes.
Proteins and/or RNA components of the various biological pathways disclosed herein and their relationship to each other are known to those skilled in the art, and can be found, e.g., at the KEGG pathway database on the internet (http://www.genome.jp/kegg/pathway.html).
In some embodiments, the cells or cell lines of the invention express at least one functional RNA or protein involved in a biological pathway. In some embodiments, the cells or cell lines of the invention expressing an RNA or protein of interest also express at least one functional RNA or protein component of a biological pathway. In some embodiments, the cells or cell lines of the invention express at least one functional RNA or protein component of a biological pathway, which may or may not be expressed in the cells or cell lines of the same type that are not engineered. In some embodiments, the cells or cell lines of the invention express at least two functional RNA or protein components of a biological pathway that is sufficient to impart at least one activity of the pathway in the cells or cell lines, also referred to herein as “expression of a functional biological pathway”. In some embodiments, expression of a biological pathway can comprise expression of at least 1, 2, 3, 4, 5, 6, 7, 8, 9 or 10 components of the biological pathway. In some embodiments, expression of a biological pathway can comprise expression of at least 1%, 2%, 3%, 4%, 5%, 6%, 7%, 8%, 9%, 10%, 20%, 30%, 40%, 50%, 60%, 70%, 80% or 90% or all components of the biological pathway. Expression of at least one functional RNA or protein component of a biological pathway in a cell or cell line in which the biological pathway does not naturally exist may result in reconstitution of at least one activity of the functional biological pathway in the cell or cell line. Expression of at least one functional RNA or protein component of a biological pathway in a cell or cell line in which the biological pathway naturally exists may result in an increase in at least one activity of the functional biological pathway in the cell or cell line. Expression of at least one functional RNA or protein component of a biological pathway in a cell or cell line in which the biological pathway naturally exists may result in an alteration of the net or overall activity of the pathway in the cell. In some embodiments, a protein of interest expressed in cells or cell lines of the invention may be modified, post-translationally modified, glycosylated or altered by co-expression of at least one of the RNA or protein components of a biological pathway. In some embodiments the protein of interest is an IgG or antibody and the pathway is a glycosylation pathway. In some embodiments, cell lines in a panel of cell lines each expressing the same protein of interest (e.g. an antibody) also each express at least one of the RNA or protein components of a biological pathway (e.g., a glycosylation pathway). In some embodiments, at least one of the functional RNA or protein components of a biological pathway interacts with (e.g., modifies, alters, glycosylates or binds, either transiently or for an extended period of time) an expressed protein of interest in the cell. However, protein-protein interaction between the expressed functional proteins is not a requirement. For example, cells and cell lines of the invention can express two or more functional proteins related to each other by being components of a same biological pathway, although the two or more functional proteins may not directly interact with each other. A biological pathway may or may not naturally exist in cells or cell lines of the invention expressing two or more functional protein components of the biological pathway. In the first case, expression of the two or more functional protein components of the biological pathway may result in an increase in at least one activity of the biological pathway in the cells or cell lines. In the latter case, expression of the two or more functional protein components of the biological pathway may result in reconstitution of at least one activity of or the entire biological pathway in the cells or cell lines. In some embodiments, at least one or more components of the biological pathway are naturally expressed by the cells or cell lines.
In some embodiments, the invention provides a cell or cell line stably expressing at least one functional protein involved in a biological pathway of interest, wherein the cell or cell line is cultured in the absence of selective pressure and wherein the cell or cell line consistently expresses the at least one functional protein as described herein. Examples of biological pathways that may be used in accordance with the present invention include, but are not limited to, those biological pathways involved in unfolded protein response (“UPR”); cell growth, cell viability, cell death, cell health; protein expression, production, folding, secretion, membrane integration, modification or post-translational modification including glycosylation or enzymatic modification; pathways enriched or more highly expressed or active in antibody producing cells, mammary gland cells salivary cells, or cells that highly express engineered proteins, as compared to other cell types.
Any cell described herein may be used as the host cell to express functional RNAs or proteins involved in a biological pathway. Examples of cells that may be used to express at least one functional RNA or protein involved in a biological pathway include, but are not limited to: CHO, CHOK1, CHOKiSV, PerC6, NS0, 293, 293T and insect cells. In some embodiments, CHO cells may be used to express at least one component of the UPR pathway. In some embodiments, CHO cells may be used to express at least one component of the a glycosylation pathway. In some further embodiments, these cells may further express a protein of interest (e.g.; an antibody) that is glycosylated.
In some embodiments, prior to the introduction into a host cell of a nucleic acid that encodes or activates the transcription of a functional protein of interest involved in a biological pathway, the host cell expresses none of the components of the pathway. In other embodiments, prior to the introduction into a host cell of a nucleic acid that encodes or activates the transcription of a functional protein of interest involved in a biological pathway, the host cell expresses at least 1, 2, 5, 10, 15, 20, or at least 25 components of the pathway.
In some embodiments, in addition to expressing one or more functional protein components of a biological pathway, the cells and cell lines of the invention also express one or more functional proteins that regulate the biological pathway and/or at least one of its components, e.g., by affecting the expression or function of one or more of the functional protein components in the biological pathway. Such effect(s) may include, but are not limited to: the post-translational modification (e.g., glycosylation), yield, folding, assembly and/or secretion of the one or more functional proteins in the biological pathway. Examples of genes or RNAs (including mutated, spliced, and processed forms) and expression products encoded by these that may be involved in biological pathways (e.g., those involved in UPR, cell viability, protein production, folding, assembly, modification, glycosylation, proteolysis, secretion, integration into membrane of a cell, cell surface presentation or a combination of these) include, but are not limited to: ATF6a spliced, IRE1a, IRE1b, PERCDC, ATF4, YYI, NF-YA, NF-YB, NF-YC, XBP1 spliced, and EDEM1 (UPR genes); NRF2, HERP, XIAP, GADD34, PPI a, b and g, and DNAJC3 (switch-off genes); BLIMP-1 and XBP1 spliced (genes expressed in B cells); CRT (CaBP3), CNX, ERp57 (PDIA3), BiP, BAP, ERdj3, CaBP1, GRP94 (CaBP4), ERp72 (PDIA4), and cyclophilin B (folding/secretion genes−Class 1 Chaperones); BiP, BAP, ERdj3, CaBP1, GRP94 (CaBP4), ERp72 (PDIA4) and cyclophilin B (Class 2 Chaperones); SDF2-L (glycosylation gene); ERO1a and b, ERAD, mannosidase 1, HRD1 (oxidation genes); STC1 and 2, SERCA1 and 2, COD1 (calcium pumps); INO1, SREBP1DC, SREBP2DC, and PYC (lipogenesis/metabolism genes); Sec61 Pa, b and g (transport/membrane integration genes); and Bcl-2sp, Bcl-xL, Bim, Ku70, VDAC2, BAP31 and 14-3-3 (cell viability/anti-apoptosis genes).
In some embodiments, in addition to the expression of a first protein of interest, or a functional biological pathway or one or more components thereof, the cells and cell lines of the invention also express at least a second protein of interest, wherein the expression of the second protein of interest is affected or altered by the expression of the first protein of interest or a functional biological pathway or one or more components thereof. Examples of such effects include, but are not limited to, those at the level of mRNA transcription, splicing, transport, protein translation, post-translational modification (e.g., glycosylation), and protein transport, folding, assembly, membrane integration, secretion and overall production (yield). For example, expression of the first protein of interest or a functional biological pathway or one or more components thereof may result in increased or more efficient or correct mRNA transcription, splicing, transport, protein translation, post-translational modification (e.g., glycosylation), and protein transport, folding, assembly, membrane integration, secretion and/or overall production (yield) of the second protein of interest. In some embodiments, the second protein of interest is a biologic. Examples of biologics are further provided hereinbelow. In some embodiments, the cells or cell lines of the invention co-express an antibody and a glycosylation pathway.
In some embodiments, in particular, the protein expressed by the cells or cell lines used in the method are proteins for which functional cell lines have not previously been available in cells of a cell type that does not normally express the protein without cell or genetic engineering. Without being bound by theory, it is believed that some reasons why such cell lines have not heretofore been possible include that the protein is highly complex or only expressed in specialized or rare cells in the absence of cell or genetic engineering and without preparing a large number of cells expressing the protein, it has not been possible to identify one of the possible rare engineered cells in which the protein may be properly or expressed, assembled, modified, localized, functional, associated with accessory factors, or is not associated with cytotoxicity; or because no ligand or modulator of the protein is known for use in identifying a cell or cell line that expresses the protein in functional form; or because the protein is cytotoxic when expressed outside its natural context, such as in a content that does not naturally express it.
Cells and cell lines of the invention can be made that consistently express any protein of interest including but not limited to proteins that are localized in the cytoplasm, proteins that are integrated or associated with at least one membrane of the cell, proteins that are cell-surface localized or proteins that are secreted, or any combination of these. Such proteins include heteromultimeric ion channels, ligand gated (such as GABA A receptor), ion channels (such as CFTR), heteromultimeric ion channels, voltage gated (such as NaV), heteromultimeric ion channel, non-ligand gated (Epithelial sodium channel, ENaC), heterodimeric GPCRs (such as opioid receptors, taste receptors including sweet, umami and bitter), other GPCRs, Orphan GPCRs, GCC, opioid receptors, growth hormone receptors, estrogen/hgh, nuclear or membrane bound, TGF receptors, PPAR nuclear hormone receptor, nicotinics/Ach, immune receptors such as B-cell/T-cell receptors, chemosensory receptors such as receptors for sour, cool, cold, warm, hot, fat, fatty acid or lipid taste or feel, creamyness, touch, pain, mouthfeel and tingle.
Cells and cell lines of the invention can express functional proteins including any protein or combination of proteins listed in Tables 7-22 (Mammalian G proteins, Human orphan GPCRs, Human opioid receptors, Human olfactory receptors, Canine olfactory receptors, Mosquito olfactory receptors, Other heteromultimeric receptors and GABA receptors.
The cells and cell lines of the invention have a number of attributes that make them particularly advantageous for any use where it is desired that cells provide consistent expression of a functional protein of interest over time. The terms “stable” or “consistent” as applied to the expression of the protein and the function of the protein is meant to distinguish the cells and cell lines of the invention from cells with transient expression or variable function, as the terms “stable expression” and “transient expression” would be understood by a person of skill in the art. A cell or cell line of the invention may have stable or consistent expression of a functional protein that has less than 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15 or 20% variation for at least 2-4 days.
In some embodiments, stability of the cells or cell lines of the invention can be differentiated from transient expression.
In some embodiments, stability of cells or cell lines of the invention can be maintained in the absence of selective pressure for one or more of the RNAs or proteins of interest. In some embodiments, the stability of the cells or cell lines of the invention can be maintained in minimal or reduced levels or amounts of selective pressure or drug compared to the levels or amounts that are normally used or used immediately following introduction of nucleic acids encoding the RNAs or proteins of interest into the population of cells that are engineered or that are normally used during methods to select for cells or cell lines with amplified copy numbers of the nucleic acids.
In some embodiments, the level of stability that is observed in cells or cell lines of the invention is higher compared to normal levels that may be achieved in cells or cell lines produced in an average or in most cells of the same cell type.
In some embodiments, the level of stability that is observed in cells or cell lines of the invention is characterized by lower variability in the expression levels, activity or function of the RNA or protein of interest compared to normal values that could be achieved in cells or cell lines produced in an average or in most cells of the same cell type.
In some embodiments, the length of time for the duration of stability of expression of an RNA or protein of interest in cells or cell lines of the invention is longer compared to normal values that could be achieved in the average or in most cells of the same cell type.
In some embodiments, stability of cells or cell lines of the invention can be maintained with minimal or in the absence of observed cytotoxicity associated with expression of the RNA or protein of interest compared to values that could be achieved in normal or most cells of the same cell type.
In some embodiments, stability of cells or cell lines of the invention can be maintained with minimal or no alteration of the functional form, function, physiology, pharmacology, assembly, localization, post-translational modification, glycosylation, enzymatic modification, proteolytic modification or stoichiometry of the RNA or protein of interest over time in culture compared to values that could be achieved in normal or most cells of the same cell type. In some embodiments, these properties may be determined by characterizing the pharmacological profile or response of the cells or cell lines in a cell based assay using compounds that modulate the expression or function of the RNA or protein of interest.
In various embodiments, the cells or cell lines of the invention express the functional RNA or protein of interest, i.e., the cells are consistently functional after growth for at least 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, 100, 110, 120, 130, 140, 150, 160, 170, 180, 190, or 200 days, where consistent expression or consistently functional refers to a level of expression that does not vary by more than: 1%, 2%, 3%, 4%, 5%, 6%, 7%, 8% 9% or 10% over 2 to 4 days of continuous cell culture; 1%, 2%, 4%, 6%, 8%, 10% or 12% over 5 to 15 days of continuous cell culture; 1%, 2%, 4%, 6%, 8%, 10%, 12%, 14%, 16%, 18% or 20% over 16 to 20 days of continuous cell culture; 1%, 2%, 4%, 6%, 8%, 10%, 12%, 14%, 16%, 18%, 20%, 22%, 24% over 21 to 30 days of continuous cell culture; 1%, 2%, 4%, 6%, 8%, 10%, 12%, 14%, 16%, 18%, 20%, 22%, 24%, 26%, 28% or 30% over 30 to 40 days of continuous cell culture; 1%, 2%, 4%, 6%, 8%, 10%, 12%, 14%, 16%, 18%, 20%, 22%, 24%, 26%, 28% or 30% over 41 to 45 days of continuous cell culture; 1%, 2%, 4%, 6%, 8%, 10%, 12%, 14%, 16%, 18%, 20%, 22%, 24%, 26%, 28% or 30% over 45 to 50 days of continuous cell culture; 1%, 2%, 4%, 6%, 8%, 10%, 12%, 14%, 16%, 18%, 20%, 22%, 24%, 26%, 28%, 30% or 35% over 45 to 50 days of continuous cell culture; 1%, 2%, 4%, 6%, 8%, 10%, 12%, 14%, 16%, 18%, 20%, 22%, 24%, 26%, 28% or 30% or 35% over 50 to 55 days of continuous cell culture; 1%, 2%, 4%, 6%, 8%, 10%, 12%, 14%, 16%, 18%, 20%, 22%, 24%, 26%, 28%, 30% or 35% over 50 to 55 days of continuous cell culture; 1%, 2%, 3%, 4%, 5%, 10%, 15%, 20%, 25%, 30%, 35% or 40% over 55 to 75 days of continuous cell culture; 1%, 2%, 3%, 4%, 5%, 5%, 10%, 15%, 20%, 25%, 30%, 35%, 40% or 45% over 75 to 100 days of continuous cell culture; 1%, 2%, 3%, 4%, 5%, 5%, 10%, 15%, 20%, 25%, 30%, 35%, 40% or 45% over 101 to 125 days of continuous cell culture; 1%, 2%, 3%, 4%, 5%, 5%, 10%, 15%, 20%, 25%, 30%, 35%, 40% or 45% over 126 to 150 days of continuous cell culture; 1%, 2%, 3%, 4%, 5%, 5%, 10%, 15%, 20%, 25%, 30%, 35%, 40% or 45% over 151 to 175 days of continuous cell culture; 1%, 2%, 3%, 4%, 5%, 5%, 10%, 15%, 20%, 25%, 30%, 35%, 40% or 45% over 176 to 200 days of continuous cell culture; 1%, 2%, 3%, 4%, 5%, 5%, 10%, 15%, 20%, 25%, 30%, 35%, 40% or 45% over more than 200 days of continuous cell culture.
In various embodiments, the cells or cell lines of the invention are stable, i.e., the cells or cell lines maintain consistent expression, amount, yield, function or activity of an RNA or protein of interest for at least 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, 100, 110, 120, 130, 140, 150, 160, 170, 180, 190, or 200 days, where “consistent” refers to a level of expression, amount, yield, function or activity of the RNA or protein of interest that does not vary by more than: 1%, 2%, 3%, 4%, 5%, 6%, 7%, 8% 9% or 10% over 2 to 4 days of continuous cell culture; 1%, 2%, 4%, 6%, 8%, 10% or 12% over 5 to 15 days of continuous cell culture; 1%, 2%, 4%, 6%, 8%, 10%, 12%, 14%, 16%, 18% or 20% over 16 to 20 days of continuous cell culture; 1%, 2%, 4%, 6%, 8%, 10%, 12%, 14%, 16%, 18%, 20%, 22%, 24% over 21 to 30 days of continuous cell culture; 1%, 2%, 4%, 6%, 8%, 10%, 12%, 14%, 16%, 18%, 20%, 22%, 24%, 26%, 28% or 30% over 30 to 40 days of continuous cell culture; 1%, 2%, 4%, 6%, 8%, 10%, 12%, 14%, 16%, 18%, 20%, 22%, 24%, 26%, 28% or 30% over 41 to 45 days of continuous cell culture; 1%, 2%, 4%, 6%, 8%, 10%, 12%, 14%, 16%, 18%, 20%, 22%, 24%, 26%, 28% or 30% over 45 to 50 days of continuous cell culture; 1%, 2%, 4%, 6%, 8%, 10%, 12%, 14%, 16%, 18%, 20%, 22%, 24%, 26%, 28%, 30% or 35% over 45 to 50 days of continuous cell culture; 1%, 2%, 4%, 6%, 8%, 10%, 12%, 14%, 16%, 18%, 20%, 22%, 24%, 26%, 28% or 30% or 35% over 50 to 55 days of continuous cell culture; 1%, 2%, 4%, 6%, 8%, 10%, 12%, 14%, 16%, 18%, 20%, 22%, 24%, 26%, 28%, 30% or 35% over 50 to 55 days of continuous cell culture; 1%, 2%, 3%, 4%, 5%, 10%, 15%, 20%, 25%, 30%, 35% or 40% over 55 to 75 days of continuous cell culture; 1%, 2%, 3%, 4%, 5%, 5%, 10%, 15%, 20%, 25%, 30%, 35%, 40% or 45% over 75 to 100 days of continuous cell culture; 1%, 2%, 3%, 4%, 5%, 5%, 10%, 15%, 20%, 25%, 30%, 35%, 40% or 45% over 101 to 125 days of continuous cell culture; 1%, 2%, 3%, 4%, 5%, 5%, 10%, 15%, 20%, 25%, 30%, 35%, 40% or 45% over 126 to 150 days of continuous cell culture; 1%, 2%, 3%, 4%, 5%, 5%, 10%, 15%, 20%, 25%, 30%, 35%, 40% or 45% over 151 to 175 days of continuous cell culture; 1%, 2%, 3%, 4%, 5%, 5%, 10%, 15%, 20%, 25%, 30%, 35%, 40% or 45% over 176 to 200 days of continuous cell culture; 1%, 2%, 3%, 4%, 5%, 5%, 10%, 15%, 20%, 25%, 30%, 35%, 40% or 45% over more than 200 days of continuous cell culture.
In various embodiments, the cells or cell lines of the invention are stable, i.e., the cells or cell lines maintain consistent expression, amount, yield, function or activity of at least two RNAs or proteins of interest for at least 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, 100, 110, 120, 130, 140, 150, 160, 170, 180, 190, or 200 days, where “consistent” refers to a level of expression, stoichiometry, amount, yield, function or activity of the RNAs or proteins of interest that does not vary by more than: 1%, 2%, 3%, 4%, 5%, 6%, 7%, 8% 9% or 10% over 2 to 4 days of continuous cell culture; 1%, 2%, 4%, 6%, 8%, 10% or 12% over 5 to 15 days of continuous cell culture; 1%, 2%, 4%, 6%, 8%, 10%, 12%, 14%, 16%, 18% or 20% over 16 to 20 days of continuous cell culture; 1%, 2%, 4%, 6%, 8%, 10%, 12%, 14%, 16%, 18%, 20%, 22%, 24% over 21 to 30 days of continuous cell culture; 1%, 2%, 4%, 6%, 8%, 10%, 12%, 14%, 16%, 18%, 20%, 22%, 24%, 26%, 28% or 30% over 30 to 40 days of continuous cell culture; 1%, 2%, 4%, 6%, 8%, 10%, 12%, 14%, 16%, 18%, 20%, 22%, 24%, 26%, 28% or 30% over 41 to 45 days of continuous cell culture; 1%, 2%, 4%, 6%, 8%, 10%, 12%, 14%, 16%, 18%, 20%, 22%, 24%, 26%, 28% or 30% over 45 to 50 days of continuous cell culture; 1%, 2%, 4%, 6%, 8%, 10%, 12%, 14%, 16%, 18%, 20%, 22%, 24%, 26%, 28%, 30% or 35% over 45 to 50 days of continuous cell culture; 1%, 2%, 4%, 6%, 8%, 10%, 12%, 14%, 16%, 18%, 20%, 22%, 24%, 26%, 28% or 30% or 35% over 50 to 55 days of continuous cell culture; 1%, 2%, 4%, 6%, 8%, 10%, 12%, 14%, 16%, 18%, 20%, 22%, 24%, 26%, 28%, 30% or 35% over 50 to 55 days of continuous cell culture; 1%, 2%, 3%, 4%, 5%, 10%, 15%, 20%, 25%, 30%, 35% or 40% over 55 to 75 days of continuous cell culture; 1%, 2%, 3%, 4%, 5%, 5%, 10%, 15%, 20%, 25%, 30%, 35%, 40% or 45% over 75 to 100 days of continuous cell culture; 1%, 2%, 3%, 4%, 5%, 5%, 10%, 15%, 20%, 25%, 30%, 35%, 40% or 45% over 101 to 125 days of continuous cell culture; 1%, 2%, 3%, 4%, 5%, 5%, 10%, 15%, 20%, 25%, 30%, 35%, 40% or 45% over 126 to 150 days of continuous cell culture; 1%, 2%, 3%, 4%, 5%, 5%, 10%, 15%, 20%, 25%, 30%, 35%, 40% or 45% over 151 to 175 days of continuous cell culture; 1%, 2%, 3%, 4%, 5%, 5%, 10%, 15%, 20%, 25%, 30%, 35%, 40% or 45% over 176 to 200 days of continuous cell culture; 1%, 2%, 3%, 4%, 5%, 5%, 10%, 15%, 20%, 25%, 30%, 35%, 40% or 45% over more than 200 days of continuous cell culture.
Cells may be selected that have desirable properties in addition to the stable expression of functional protein. Any desired property that can be detected may be selected for. Those of skill in the art will aware of such characteristics. By way of non-limiting example, such properties include:
fragility, morphology and adherence to a solid surface, monodispersion by trypsin or cell dissociation reagent, adaptability to the automated culture conditions, performance under serum-containing conditions, performance in serum-free conditions, convertability to serum-free suspension conditions, propensity to form clumps, propensity to form monodisperse cell layers following passaging, resilience, propensity to remain attached to growth chamber surfaces under fluid addition steps of different force, non-fragmented nucleus, lack of intracellular vacuoles, lack of microbial contamination, lack of mycoplasma, lack of viral contamination, clonality, consistency of gross physical properties of cells within wells, propensity for growth below/at/above room temperature, propensity for tolerance of various temperatures for various time periods, propensity of cells to evenly uptake plasmid/oligonucleotides/fluorogenic probes/peptides/proteins/compounds, propensity of cells to withstand incubation with DMSO/EtOH/MeOH, organic solvent/detergent, propensity of cells to withstand maintained UPR induction, propensity of cells to withstand exposure to DTT, propensity of cells to be infected with viral/lentiviral/cosmid vectors, endogenous expression of desired RNA(s)/protein(s) or lack thereof, chromosomal number, chromosomal aberrations, amenable to growth at 5/6/7/8/9pH, tolerance to UV/mutagen/radiation, ability to maintain the above characteristics under altered/manual/scaled-up growth conditions (i.e., including reactors).
Cells and cell lines of the invention have enhanced properties as compared to cells and cell lines made by conventional methods. For example, the cells and cell lines of this invention have enhanced stability of expression and/or levels of expression (even when maintained in cultures without selective pressure, including, for example, antibiotics and other drugs). In other embodiments, the cells and cell lines of the invention have high Z′ values in various assays. In still other embodiments, the cells and cell lines of this invention are improved in context of their expression of a physiologically relevant protein activity as compared to more conventionally engineered cells. These properties enhance and improve the ability of the cells and cell lines of this invention to be used for any use, whether in assays to identify modulators, for cell therapy, for protein production or any other use and improve the functional attributes of the identified modulators.
In some embodiments, a further advantageous property of the cells and cell lines of the invention is that they stably express the protein of interest in the absence or with reduced drug or other selective pressure that is typically used or that may be used immediately following introduction of nucleic acids encoding the protein of interest into cells or that may be used during procedures to select for cells with amplified copy number of the nucleic acids. Without being bound by theory, cytotoxicity associated with expression or RNAs or proteins of interest in cells of a cell type that do not normally express the RNAs or proteins of interest may reflect that conditions that are sufficient for non-cytotoxic expression of the RNAs or proteins of interest have not been approximated or recapitulated in the engineered cells. In some embodiments engineered cells with diminished or that lack cytotoxicity associated with expression of such RNAs or proteins of interest are preferred as diminished or the lack of cytotoxicity could indicate that improved conditions for expression or function of the RNAs or proteins of interest have been achieved. In certain embodiments, engineered cells or cell lines may express an RNA or protein of interest that is not naturally expressed or that is not naturally expressed in the absence of associated cytotoxicity in the same type of cell in the absence of cell or genetic engineering. In certain embodiments, engineered cells or cell lines may express an RNA or protein of interest that is not naturally functionally or properly expressed, folded, assembled, modified, post-translationally modified, localized or active in the same type of cell in the absence of cell or genetic engineering. In some embodiments, the methods of the invention result in cells or cell lines comprising functional, stable, viable or non-cytotoxic expression of RNAs or proteins of interest that had previously been considered to be cytotoxic when expressed in average or most cells of the same cell types. Thus, in preferred embodiments, the cells and cell lines of the invention are maintained in culture without any selective pressure. In further embodiments, cells and cell lines are maintained without any drug or antibiotics. As used herein, cell maintenance refers to culturing cells after they have been selected as described for protein expression. Maintenance does not refer to the optional step of growing cells under selective pressure (e.g., an antibiotic) prior to cell sorting where marker(s) introduced into the cells allow enrichment of stable transfectants in a mixed population.
Drug-free and selective pressure-free cell maintenance of the cells and cell lines of this invention provides a number of advantages. For example, drug-resistant cells may not express the co-transfected transgene of interest at adequate levels, because the selection relies on survival of the cells that have taken up the drug resistant gene, with or without the transgene. Further, cytotoxicity or the requirement for drug selection or other selective pressure to maintain expression or function of a RNA or protein of interest could indicate that optimal conditions for expression or function of the RNA of protein of interest have not been achieved. Further, selective drugs and other selective pressure factors are often mutagenic or otherwise interfere with the physiology of the cells, leading to skewed results in cell-based assays. For example, selective drugs may decrease susceptibility to apoptosis (Robinson et al., Biochemistry, 36(37):11169-11178 (1997)), increase DNA repair and drug metabolism (Deffie et al., Cancer Res. 48(13):3595-3602 (1988)), increase cellular pH (Thiebaut et al., J Histochem Cytochem. 38(5):685-690 (1990); Roepe et al., Biochemistry. 32(41):11042-11056 (1993); Simon et al., Proc Natl Acad Sci USA. 91(3):1128-1132 (1994)), decrease lysosomal and endosomal pH (Schindler et al., Biochemistry. 35(9):2811-2817 (1996); Altan et al., J Exp Med. 187(10):1583-1598 (1998)), decrease plasma membrane potential (Roepe et al., Biochemistry. 32(41):11042-11056 (1993)), increase plasma membrane conductance to chloride (Gill et al., Cell. 71(1):23-32 (1992)) and ATP (Abraham et al., Proc Natl Acad Sci USA. 90(1):312-316 (1993)), and increase rates of vesicle transport (Altan et al., Proc Natl Acad Sci USA. 96(8):4432-4437 (1999)). Thus, the cells and cell lines of this invention allow screening assays that are free from the artifacts caused by selective pressure. In some preferred embodiments, the cells and cell lines of this invention are not cultured with selective pressure factors, such as antibiotics, before or after cell sorting, so that cells and cell lines with desired properties are isolated by sorting, even when not beginning with an enriched cell population.
The cells and cell lines of the invention have enhanced stability as compared to cells and cell lines produced by conventional methods in the context of expression and expression levels (RNA or protein). To identify cells and cell lines characterized by such stable expression, a cell or cell line's expression of a protein of interest is measured over a timecourse and the expression levels are compared. Stable cell lines will continue expressing (RNA or protein) throughout the timecourse. In some aspects of the invention, the timecourse may be for at least one week, two weeks, three weeks, etc., or at least one month, or at least two, three, four, five, six, seven, eight or nine months, or any length of time in between.
Isolated cells and cell lines may be further characterized, such as by PCR, RT-PCR, qRT-PCR and single end-point RT-PCR to determine the absolute amounts and relative amounts (in the case of multisubunit proteins or multiple proteins of interest) being expressed (RNA). Preferably, the expansion levels of the subunits of a multi-subunit protein are substantially the same in the cells and cell lines of this invention.
In other embodiments, the expression of a functional protein of interest is assayed over time. In these embodiments, stable expression is measured by comparing the results of functional assays over a timecourse. The assay of cell and cell line stability based on a functional assay provides the benefit of identifying cells and cell lines that not only stably express the protein (RNA or protein), but also stably produce and properly process (e.g., post-translational modification, subunit assembly, and localization within the cell) the protein to produce a functional protein.
Cells and cell lines of the invention have the further advantageous property of providing assays with high reproducibility as evidenced by their Z′ factor. See Zhang J H, Chung T D, Oldenburg K R, “A Simple Statistical Parameter for Use in Evaluation and Validation of High Throughput Screening Assays.” J. Biomol. Screen. 1999; 4(2):67-73, which is incorporated herein by reference in its entirety. Z′ values relate to the quality of a cell or cell line because it reflects the degree to which a cell or cell line will respond consistently to modulators. Z′ is a statistical calculation that takes into account the signal-to-noise range and signal variability (i.e., from well to well) of the functional response to a reference compound across a multiwell plate. is Z′ calculated using Z′ data obtained from multiple wells with a positive control and multiple wells with a negative control. The ratio of their combined standard deviations multiplied by three to the difference factor, in their mean values is subtracted from one to give the Z′ according the equation below:
Z′ factor=1−((3σpositive control+3σnegative control)/(μpositive control−μnegative control))
If the factor is 1.0, which would indicate an ideal assay with theoretical maximum Z′ no variability and limitless dynamic range. As used herein, a “high Z′” refers to a Z′ factor of Z′ of at least 0.6, at least 0.7, at least 0.75 or at least 0.8, or any decimal in between 0.6 and 1.0. In the case of a complex target, a high Z′ means a Z′ of at least 0.4 or greater. A score of close to 0 is undesirable because it indicates that there is overlap between positive and negative controls. In the industry, for simple cell-based assays, Z′ scores up to 0.3 are considered marginal scores, Z′ scores between 0.3 and 0.5 are considered acceptable, and Z′ scores above 0.5 are considered excellent. Cell-free or biochemical assays may approach scores for cell-based systems tend to be lower because higher Z′ scores, but Z′ cell-based systems are complex.
As those of ordinary skill in the art will recognize cell-based assays using conventional cells expressing even a single chain protein do not typically achieve a Z′ higher than 0.5 to 0.6. Cells with engineered expression (either from introduced coding sequences or gene activation) of multi-subunit proteins, if even reported in the art, would be lower due to their added complexity. Such cells would not be reliable for use in assays because the results would not be reproducible. Cells and cell lines of this invention, on the other hand, have higher Z′ values and advantageously produce consistent results in assays. Indeed, the cells and cell lines of the invention provide the basis for high throughput screening (HTS) compatible assays because they generally have values than conventionally produced cells. In some aspects of the invention, the cells and cell lines result in Z′ of at least 0.3, at least 0.4, at least 0.5, at least 0.6, at least 0.7, or at least 0.8. Even Z′ values of at least 0.3-0.4 for the cells and cell lines of the invention are advantageous because the proteins of interest are multigene targets. In other aspects of the invention, the cells and cell lines of the invention result in a Z′ of at least 0.7, at least 0.75 or at least 0.8 even after the cells are maintained for multiple passages, e.g., between 5-20 passages, including any integer in between 5 and 20. In some aspects of the invention, the cells and cell lines result in a Z′ of at least 0.7, at least 0.75 or at least 0.8 in cells and cell lines maintained for 1, 2, 3, 4 or 5 weeks or 2, 3, 4, 5, 6, 7, 8 or 9 months, including any period of time in between.
In some embodiments, the cells and cell lines of the invention express a protein of interest wherein one or more physiological properties remain(s) substantially constant over time.
A physiological property includes any observable, detectable or measurable property of cells or cell lines apart from the expression of the protein of interest.
In some embodiments, the expression of a protein of interest can alter one or more physiological properties. Alteration of a physiological property includes any change of the physiological property due to the expression of the protein of interest, e.g., a stimulation, activation, or increase of the physiological property, or an inhibition, blocking, or decrease of the physiological property. Without being bound by theory, in these embodiments, the one or more constant physiological properties indicate that the functional expression of the protein of interest also remains constant. In particular embodiments, one or more constant physical properties associated with a taste receptor (e.g., sweet taste receptor, umami taste receptor, or bitter taste receptor), which are discussed in more detail below, can be used to monitor the expression of functional taste receptors.
Without being bound by theory, the invention provides a method for culturing a plurality of cells or cell lines expressing a protein of interest under constant culture conditions, wherein cells or cell lines can be selected that have one or more desired properties, such as stable expression of the protein of interest and/or one or more substantially constant physiological properties.
In some embodiments where a physiological property can be measured, the physiological property is determined as an average of the physiological property measured in a plurality of cells or a plurality of cells of a cell line. In certain specific embodiments, a physiological property is measured over at least 10; 100; 1,000; 10,000; 100,000; 1,000,000; or at least 10,000,000 cells and the average remains substantially constant over time.
In some embodiments, the average of a physiological property is determined by measuring the physiological property in a plurality of cells or a plurality of cells of a cell line wherein the cells are at different stages of the cell cycle. In other embodiments, the cells are synchronized with respect to cell cycle.
In some embodiments, a physiological property is observed, detected, measured or monitored on a single cell level. In certain embodiments, the physiological property remains substantially constant over time on a single cell level.
In certain embodiments, a physiological property remains substantially constant over time if it does not vary more than 0.1%, 0.5%, 1%, 2.5%, 5%, 10%, 15%, 20%, 25%, 30%, 35%, 40%, 45%, or no more than 50% over 12 hours. In certain embodiments, a physiological property remains substantially constant over time if it does not vary more than 0.1%, 0.5%, 1%, 2.5%, 5%, 10%, 15%, 20%, 25%, 30%, 35%, 40%, 45%, or no more than 50% over 1 day. In certain embodiments, a physiological property remains substantially constant over time if it does not vary more than 0.1%, 0.5%, 1%, 2.5%, 5%, 10%, 15%, 20%, 25%, 30%, 35%, 40%, 45%, or no more than 50% over 2 days. In certain embodiments, a physiological property remains substantially constant over time if it does not vary more than 0.1%, 0.5%, 1%, 2.5%, 5%, 10%, 15%, 20%, 25%, 30%, 35%, 40%, 45%, or no more than 50% over 5 days. In certain embodiments, a physiological property remains substantially constant over time if it does not vary more than 0.1%, 0.5%, 1%, 2.5%, 5%, 10%, 15%, 20%, 25%, 30%, 35%, 40%, 45%, or no more than 50% over 10 days. In certain embodiments, a physiological property remains substantially constant over time if it does not vary more than 0.1%, 0.5%, 1%, 2.5%, 5%, 10%, 15%, 20%, 25%, 30%, 35%, 40%, 45%, or no more than 50% over 20 days. In certain embodiments, a physiological property remains substantially constant over time if it does not vary more than 0.1%, 0.5%, 1%, 2.5%, 5%, 10%, 15%, 20%, 25%, 30%, 35%, 40%, 45%, or no more than 50% over 30 days. In certain embodiments, a physiological property remains substantially constant over time if it does not vary more than 0.1%, 0.5%, 1%, 2.5%, 5%, 10%, 15%, 20%, 25%, 30%, 35%, 40%, 45%, or no more than 50% over 40 days. In certain embodiments, a physiological property remains substantially constant over time if it does not vary more than 0.1%, 0.5%, 1%, 2.5%, 5%, 10%, 15%, 20%, 25%, 30%, 35%, 40%, 45%, or no more than 50% over 50 days. In certain embodiments, a physiological property remains substantially constant over time if it does not vary more than 0.1%, 0.5%, 1%, 2.5%, 5%, 10%, 15%, 20%, 25%, 30%, 35%, 40%, 45%, or no more than 50% over 60 days. In certain embodiments, a physiological property remains substantially constant over time if it does not vary more than 0.1%, 0.5%, 1%, 2.5%, 5%, 10%, 15%, 20%, 25%, 30%, 35%, 40%, 45%, or no more than 50% over 70 days. In certain embodiments, a physiological property remains substantially constant over time if it does not vary more than 0.1%, 0.5%, 1%, 2.5%, 5%, 10%, 15%, 20%, 25%, 30%, 35%, 40%, 45%, or no more than 50% over 80 days. In certain embodiments, a physiological property remains substantially constant over time if it does not vary more than 0.1%, 0.5%, 1%, 2.5%, 5%, 10%, 15%, 20%, 25%, 30%, 35%, 40%, 45%, or no more than 50% over 90 days. In certain embodiments, a physiological property remains substantially constant over time if it does not vary more than 0.1%, 0.5%, 1%, 2.5%, 5%, 10%, 15%, 20%, 25%, 30%, 35%, 40%, 45%, or no more than 50% over the course of 1 passage, 2 passages, 3 passages, 5 passages, 10 passages, 25 passages, 50 passages, or 100 passages.
Examples of cell physiological properties include, but are not limited to: growth rate, size, shape, morphology, volume; profile or content of DNA, RNA, protein, lipid, ion, carbohydrate or water; endogenous, engineered, introduced, gene-activated or total gene, RNA or protein expression or content; propensity or adaptability to growth in adherent, suspension, serum-containing, serum-free, animal-component free, shaken, static or bioreactor growth conditions; propensity or adaptability to growth in or on chips, arrays, microarrays, slides, dishes, plates, multiwell plates, high density multiwell plates, flasks, roller bottles, bags or tanks; propensity or adaptability to growth using manual or automated or robotic cell culture methodologies; abundance, level, number, amount or composition of at least one cell organelle, compartment or membrane, including, but not limited to cytoplasm, nucleoli, nucleus, ribosomes, rough endoplasmic reticulum, Golgi apparatus, cytoskeleton, smooth endoplasmic reticulum, mitochondria, vacuole, cytosol, lysosome, centrioles, chloroplasts, cell membrane, plasma cell membrane, nuclear membrane, nuclear envelope, vesicles (e.g., secretory vesicles), or membrane of at least one organelle; having acquired or having the capacity or propensity to acquire at least one functional or gene expression profile (of one or more genes) shared by one or more specific cell types or differentiated, undifferentiated or dedifferentiated cell types, including, but not limited to: a stem cell, a pluripotent cell, an omnipotent cell or a specialized or tissue specific cell including one of the liver, lung, skin, muscle (including but not limited to: cardiac muscle, skeletal muscle, striatal muscle), pancreas, brain, testis, ovary, blood, immune system, nervous system, bone, cardiovascular system, central nervous system, gastro-intestinal tract, stomach, thyroid, tongue, gall bladder, kidney, nose, eye, nail, hair, taste bud cell or taste cell, neuron, skin, pancreas, blood, immune, red blood cell, white blood cell, killer T-cell, enteroendocrine cell, secretory cell, kidney, epithelial cell, endothelial cell, a human, animal or plant cell; ability to or capacity to uptake natural or synthetic chemicals or molecules including, but not limited to: nucleic acids, RNA, DNA, protein, small molecules, probes, dyes, oligonucleotides (including modified oligonucleotides) or fluorogenic oligonucleotides; resistance to or capacity to resist negative or deleterious effects of chemicals or substances that negatively affect cell growth, function or viability, including, but not limited to: resistance to infection, drugs, chemicals, pathogens, detergents, UV, adverse conditions, cold, hot, extreme temperatures, shaking, perturbation, vortexing, lack of or low levels of oxygen, lack of or low levels of nutrients, toxins, venoms, viruses or compound, treatment or agent that has an adverse effect on cells or cell growth; suitability for use in in vitro tests, cell based assays, biochemical or biological tests, implantation, cell therapy or secondary assays, including, but not limited to: large scale cell culture, miniaturized cell culture, automated cell culture, robotic cell culture, standardized cell culture, drug discovery, high throughput screening, cell based assay, functional cell based assay (including but not limited to membrane potential assays, calcium flux assays, reporter assays, G-protein reporter assays), ELISA, in vitro assays, in vivo applications, secondary testing, compound testing, binding assays, panning assays, antibody panning assays, phage display, imaging studies, microscopic imaging assays, immunofluorescence studies, RNA, DNA, protein or biologic production or purification, vaccine development, cell therapy, implantation into an organism, animal, human or plant, isolation of factors secreted by the cell, preparation of cDNA libraries, or infection by pathogens, viruses or other agent; and other observable, measurable, or detectable physiological properties such as: biosynthesis of at least one metabolite, lipid, DNA, RNA or protein; chromosomal silencing, activation, heterochromatization, euchromoatinization or recombination; gene expression, gene silencing, gene splicing, gene recombination or gene-activation; RNA production, expression, transcription, processing splicing, transport, localization or modification; protein production, expression, secretion, folding, assembly, transport, localization, cell surface presentation, secretion or integration into a cell or organelle membrane; protein modification including but not limited to post-translational modification, processing, enzymatic modification, proteolysis, glycosylation, phosphorylation, dephosphorylation; cell division including mitosis, meiosis or fission or cell fusion; high level RNA or protein production or yield.
Physiological properties may be observed, detected or measured using routine assays known in the art, including but not limited to tests and methods described in reference guides and manuals such as the Current Protocols series. This series includes common protocols in various fields and is available through the Wiley Publishing House. The protocols in these reference guides are illustrative of the methods that can be used to observe, detect or measure physiological properties of cells. The skilled worker would readily recognize any one or more of these methods may be used to observe, detect or measure the physiological properties disclosed herein.
Many markers, dyes or reporters, including proteins markers expressed as fusion proteins comprising an autofluorescent protein, that can be used to measure the level, activity or content of cellular compartments or organelles including but not limited to ribosomes, mitochondria, ER, rER, golgi, TGN, vesicles, endosomes and plasma membranes in cells are compatible with the testing of individual viable cells. In some embodiments fluorescence activated cell sorting or a cell sorter can be used. In some embodiments, cells or cell lines isolated or produced to comprise an RNA or protein of interest can be tested using these markers, dyes or reporters at the same time, subsequent, or prior to isolation, testing or production of the cells or cell lines comprising the RNA or protein of interest. In some embodiments, the level, activity or content of one or more of the cellular compartments or organelles can be correlated with improved, increased, native, non-cytotoxic, viable or optimal expression, function, activity, folding, assembly modification, post-translational modification, secretion, cell surface presentation, membrane integration, pharmacology, yield or physiology of the RNA or protein of interest. In some embodiments, cells or cell lines comprising the level, activity or content of at least one cellular compartment or organelle that is correlated with improved, increased, native, non-cytotoxic, viable or optimal expression, function, activity, folding, assembly modification, post-translational modification, secretion, cell surface presentation, membrane integration, pharmacology, yield or physiology of the RNA or protein of interest can be isolated. In some embodiments, cells or cell lines comprising the RNA or protein of interest and the level, activity or content of at least one cellular compartment or organelle that is correlated with improved, increased, native, non-cytotoxic, viable or optimal expression, function, activity, folding, assembly modification, post-translational modification, secretion, cell surface presentation, membrane integration, pharmacology, yield or physiology of the RNA or protein of interest can be isolated. In some embodiments the isolation of the cells is performed using cell sorting or fluorescence activated cell sorting.
In some embodiments, populations of diverse cells that can be engineered to comprise an RNA or protein of interest can be exposed to, introduced with or engineered to comprise at least 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, 100, 125, 150, 175 or 200 additional nucleic acid sequences at the same time, prior or subsequent to isolation, testing or production of cells or cell lines engineered to comprise the RNA or protein of interest. In some embodiments the additional nucleic acids can be selected from the group consisting of: RNAs, DNAs or genes encoding regulators of the unfolded protein response (UPR); RNAs, DNAs, or genes that are regulated in or in the state of UPR; RNAs, DNAs, or genes that regulate cell growth, cell viability, cell death, cell health; RNAs, DNAs, or genes that regulate RNA or protein expression, production, folding, secretion, yield, membrane integration, modification or post-translational modification including glycosylation or enzymatic modification; RNAs, DNAs or genes that are enriched in antibody producing cells compared to other cell types.
In some embodiments, the expression of at least one of the nucleic acids in cells can be correlated with improved, increased, native, non-cytotoxic, viable or optimal expression, function, activity, folding, assembly modification, post-translational modification, secretion, cell surface presentation, membrane integration, pharmacology, yield or physiology of the RNA or protein of interest. In some embodiments, cells or cell lines comprising at least one nucleic acid that is correlated with improved, increased, native, non-cytotoxic, viable or optimal expression, function, activity, folding, assembly modification, post-translational modification, secretion, cell surface presentation, membrane integration, pharmacology, yield or physiology of the RNA or protein of interest can be isolated. In some embodiments, populations of diverse cells that can be engineered to comprise an RNA or protein of interest can be exposed to, introduced with or engineered to comprise at least 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, 100, 125, 150, 175 or 200 additional nucleic acid sequences at the same time, prior or subsequent to isolation, testing or production of cells or cell lines engineered to comprise the RNA or protein of interest and cells or cell lines comprising the RNA or protein of interest and the level, activity or content of at least one cellular compartment or organelle that is correlated with improved, increased, native, non-cytotoxic, viable or optimal expression, function, activity, folding, assembly modification, post-translational modification, secretion, cell surface presentation, membrane integration, pharmacology, yield or physiology of the RNA or protein of interest can be isolated. In some embodiments the isolation of the cells is performed using cell sorting or fluorescence activated cell sorting.
Cells or preparations made from cells may be tested to analyze DNA, RNA, protein content, organization, expression or profiles using methods and tests including sequencing, PCR methods including PCR, RT-PCR, qRT-PCR, RACE, hybridization methods including northern and southern blots, FISH, in situ hybridization, microscopy including fluorescence, electron, confocal or immunofluorescence microscopy or array or microarray tests such as genechips or protein arrays, for instance to identify expression profiles or one or more genes whose expression impacts, benefits or is detrimental to the expression of a target, for instance by affecting its functional, viable or stable expression, or to a cell-physiological property. In certain embodiments such tests are conducted to identify one or more endogenous factors that influence, benefit or affect the functional, viable or stable expression of a protein of interest or physiological property of interest.
Cells or preparations of made from cells may be tested to analyze or characterize cellular content including metabolites, DNA, RNA, protein, membranes, lipids, carbohydrates or organelles using methods and tests including centrifugation, ultracentrifugation, floating, sucrose gradients, HPLC, FPLC, subcellular fractionation, metabolite analysis, chemical composition analysis, chromosomal spreads, DAPI labeling, NMR, enzyme assays, ELISAs;
Protein produced by cells may be tested to assess its sequence, function, form, folding, membrane integration, abundance, yield, post-translational modification, glycosylation, phosphorylation, cleavage, proteolysis or degradation using sequencing, antibody binding ELISA or activity assays.
Cells may be tested and characterized by tests for cell growth, mitosis, meiosis, gene integration, gene activation, gene introduction or gene expression or silencing. In certain embodiments, such tests are conducted to identify sites of integration of any transgenes in the genome of the cell.
In some embodiments, the expression profile (e.g., profile of gene expression or protein expression) of a cell or cell line in accordance with the invention can be compared to the expression profile of a reference cell or cell line. Any method known to the skilled artisan can be used to measure the expression profile of one or more nucleic acid or amino acid sequences. Exemplary methods are gene chip, protein chip etc. In some embodiments, the expression of at least 0.1%, 0.5%, 1%, 2.5%, 5%, 10%, 15%, 20%, 25%, 30%, 35%, 40%, 45%, 50%, 60%, 70%, 80%, 90%, 95%, 98%, 99%, or 100% of the genes in a genome are assayed. In some embodiments, at least 0.1%, 0.5%, 1%, 2.5%, 5%, 10%, 15%, 20%, 25%, 30%, 35%, 40%, 45%, 50%, 60%, 70%, 80%, 90%, 95%, 98%, 99%, or 100% of the nucleic acid or amino acid sequences in a cell are assayed. In some embodiments, the expression of at least 1, 2, 3, 4, 5, 10, 15, 20, 25, 30, 35, 40, 50, 60, 70, 80, 90 or 100 or more than 100 of the genes in a genome are assayed. In some embodiments, at least at least 1, 2, 3, 4, 5, 10, 15, 20, 25, 30, 35, 40, 50, 60, 70, 80, 90 or 100 or more than 100 of the nucleic acid or amino acid sequences in a cell are assayed.
In some embodiments, the reference cell or cell line is the host cell from which the cell or cell line in accordance with the invention was generated. In other embodiments, the cell or cell line and the reference cell or cell line are derived from the same parent clone. In some embodiments, the cell or cell line and the reference cell or cell line are derived from the same parent cell. In other embodiments, the reference cell or cell line is a cell or cell line of a cell type that the cell or cell line in accordance with the invention was designed to approximate. Such cell types include, but are not limited to: epidermal keratinocyte (differentiating epidermal cell), epidermal basal cell (stem cell), keratinocyte of fingernails and toenails, nail bed basal cell (stem cell), medullary hair shaft cell, cortical hair shaft cell, cuticular hair shaft cell, cuticular hair root sheath cell, hair root sheath cell of Huxley's layer, hair root sheath cell of Henle's layer, external hair root sheath cell, hair matrix cell (stem cell), surface epithelial cell of stratified squamous epithelium of cornea, tongue, oral cavity, esophagus, anal canal, distal urethra and vagina, basal cell (stem cell) of epithelia of cornea, tongue, oral cavity, esophagus, anal canal, distal urethra and vagina, urinary epithelium cell (lining urinary bladder and urinary ducts), salivary gland mucous cell (polysaccharide-rich secretion), salivary gland serous cell (glycoprotein enzyme-rich secretion), von Ebner's gland cell in tongue (washes taste buds), mammary gland cell (milk secretion), lacrimal gland cell (tear secretion), ceruminous gland cell in ear (wax secretion), eccrine sweat gland dark cell (glycoprotein secretion), eccrine sweat gland clear cell (small molecule secretion), apocrine sweat gland cell (odoriferous secretion, sex-hormone sensitive), gland of Moll cell in eyelid (specialized sweat gland), sebaceous gland cell (lipid-rich sebum secretion), bowman's gland cell in nose (washes olfactory epithelium), Brunner's gland cell in duodenum (enzymes and alkaline mucus), seminal vesicle cell (secretes seminal fluid components, including fructose for swimming sperm), prostate gland cell (secretes seminal fluid components), bulbourethral gland cell (mucus secretion), Bartholin's gland cell (vaginal lubricant secretion), gland of Littre cell (mucus secretion), uterus endometrium cell (carbohydrate secretion), isolated goblet cell of respiratory and digestive tracts (mucus secretion), stomach lining mucous cell (mucus secretion), gastric gland zymogenic cell (pepsinogen secretion), gastric gland oxyntic cell (hydrochloric acid secretion), pancreatic acinar cell (bicarbonate and digestive enzyme secretion), paneth cell of small intestine (lysozyme secretion), type II pneumocyte of lung (surfactant secretion), clara cell of lung, anterior pituitary cells, somatotropes, lactotropes, thyrotropes, gonadotropes, corticotropes, intermediate pituitary cell, secreting melanocyte-stimulating hormone, magnocellular neurosecretory cells (secreting oxytocin and/or secreting vasopressin), gut and respiratory tract cells (secreting serotonin, secreting endorphin, secreting somatostatin, secreting gastrin, secreting secretin, secreting cholecystokinin, secreting insulin, secreting glucagons, and/or secreting bombesin), thyroid gland cells, thyroid epithelial cell, parafollicular cell, parathyroid gland cells, parathyroid chief cell, oxyphil cell, adrenal gland cells, chromaffin cells, adrenal gland secreting steroid hormones (mineralocorticoids and glucocorticoids), Leydig cell of testes secreting testosterone, theca interna cell of ovarian follicle secreting estrogen, corpus luteum cell of ruptured ovarian follicle secreting progesterone (Granulosa lutein cells, and Theca lutein cells), juxtaglomerular cell (renin secretion), macula densa cell of kidney, peripolar cell of kidney, mesangial cell of kidney, hepatocyte (liver cell), white fat cell, brown fat cell, liver lipocyte, kidney glomerulus parietal cell, kidney glomerulus podocyte, kidney proximal tubule brush border cell, loop of Henle thin segment cell, kidney distal tubule cell, kidney collecting duct cell, type I pneumocyte (lining air space of lung), pancreatic duct cell (centroacinar cell), nonstriated duct cell (of sweat gland, salivary gland, mammary gland, etc.) such as principal cell and intercalated cell, duct cell (of seminal vesicle, prostate gland, etc.), intestinal brush border cell (with microvilli), exocrine gland striated duct cell, gall bladder epithelial cell, ductulus efferens nonciliated cell, epididymal principal cell, epididymal basal cell, blood vessel and lymphatic vascular endothelial fenestrated cell, blood vessel and lymphatic vascular endothelial continuous cell, blood vessel and lymphatic vascular endothelial splenic cell, synovial cell (lining joint cavities, hyaluronic acid secretion), serosal cell (lining peritoneal, pleural, and pericardial cavities), squamous cell (lining perilymphatic space of ear), squamous cell (lining endolymphatic space of ear), columnar cell of endolymphatic sac with microvilli (lining endolymphatic space of ear), columnar cell of endolymphatic sac without microvilli (lining endolymphatic space of ear), dark cell (lining endolymphatic space of ear), vestibular membrane cell (lining endolymphatic space of ear), stria vascularis basal cell (lining endolymphatic space of ear), stria vascularis marginal cell (lining endolymphatic space of ear), cell of Claudius (lining endolymphatic space of ear), cell of Boettcher (lining endolymphatic space of ear), choroid plexus cell (cerebrospinal fluid secretion), pia-arachnoid squamous cell, pigmented ciliary epithelium cell of eye, nonpigmented ciliary epithelium cell of eye, corneal endothelial cell, respiratory tract ciliated cell, oviduct ciliated cell (in female), uterine endometrial ciliated cell (in female), rete testis ciliated cell (in male), ductulus efferens ciliated cell (in male), ciliated ependymal cell of central nervous system (lining brain cavities), ameloblast epithelial cell (tooth enamel secretion), planum semilunatum epithelial cell of vestibular apparatus of ear (proteoglycan secretion), organ of Corti interdental epithelial cell (secreting tectorial membrane covering hair cells), loose connective tissue fibroblasts, corneal fibroblasts (corneal keratocytes), tendon fibroblasts, bone marrow reticular tissue fibroblasts, other nonepithelial fibroblasts, pericyte, nucleus pulposus cell of intervertebral disc, cementoblast/cementocyte (tooth root bonelike cementum secretion), ontoblast/odontocyte (tooth dentin secretion), hyaline cartilage chondrocyte, fibrocartilage chondrocyte, elastic cartilage chondrocyte, oteoblast/osteocyte, osteoprogenitor cell (stem cell of osteoblasts), hyalocyte of vitreous body of eye, stellate cell of perilymphatic space of ear, hepatic stellate cell (Ito cell), pancreatic stellate cell, skeletal muscle cells (such as Red skeletal muscle cell (slow), white skeletal muscle cell (fast), intermediate skeletal muscle cell, nuclear bag cell of muscle spindle, and nuclear chain cell of muscle spindle), satellite cell (stem cell), heart muscle cells (such as ordinary heart muscle cell, nodal heart muscle cell, and purkinje fiber cell), smooth muscle cell (various types), myoepithelial cell of iris, myoepithelial cell of exocrine glands, erythrocyte (red blood cell), megakaryocyte (platelet precursor), monocytes, connective tissue macrophage (various types), epidermal Langerhans cell, osteoclast (in bone), dendritic cell (in lymphoid tissues), microglial cell (in central nervous system), neutrophil granulocyte, eosinophil granulocyte, basophil granulocyte, mast cell, helper T cell, suppressor T cell, cytotoxic T cell, natural Killer T cell, B cell, natural killer cell, reticulocyte, stem cells and committed progenitors for the blood and immune system (various types), auditory outer hair cell of organ of Corti, basal cell of olfactory epithelium (stem cell for olfactory neurons), cold-sensitive primary sensory neurons, heat-sensitive primary sensory neurons, merkel cell of epidermis (touch sensor), olfactory receptor neuron, pain-sensitive primary sensory neurons (various types), photoreceptor cells of retina in eye (such as photoreceptor rod cells, photoreceptor blue-sensitive cone cell of eye, photoreceptor green-sensitive cone cell of eye, photoreceptor red-sensitive cone cell of eye), proprioceptive primary sensory neurons (various types), touch-sensitive primary sensory neurons (various types), type I carotid body cell (blood pH sensor), type II carotid body cell (blood pH sensor), type I hair cell of vestibular apparatus of ear (acceleration and gravity), type II hair cell of vestibular apparatus of ear (acceleration and gravity), type I taste bud cell, cholinergic neural cell (various types), adrenergic neural cell (various types), peptidergic neural cell (various types), inner pillar cell of organ of Corti, outer pillar cell of organ of Corti, inner phalangeal cell of organ of Corti, outer phalangeal cell of organ of Corti, border cell of organ of Corti, hensen cell of organ of Cortim vestibular apparatus supporting cell, type I taste bud supporting cell, olfactory epithelium supporting cell, schwann cell, satellite cell (encapsulating peripheral nerve cell bodies), enteric glial cell, astrocyte (various types), neuron cells (large variety of types, still poorly classified), oligodendrocyte, spindle neuron, anterior lens epithelial cell, crystallin-containing lens fiber cell, melanocyte, retinal pigmented epithelial cell, oogonium/oocyte, spermatid, spermatocyte, spermatogonium cell (stem cell for spermatocyte), spermatozoon, ovarian follicle cell, sertoli cell (in testis), thymus epithelial cell, and interstitial kidney cells. For example, if the protein of interest that is expressed in the cell or cell line is an ion channel that is normally expressed in a particular type of neurons, the reference cell could be a neuron of that particular type. Particular types of neurons include, but are not limited to: sensory neurons, neurons of the central nervous system, unipolar neurons, pseudounipolar neurons, bipolar neurons, multipolar neurons, Golgi I neurons, pyramidal cells, purkinje cells, anterior horn cells, Golgi II neurons, granule cells, basket cells, betz cells, large motor neurons, medium spiny neurons, Renshaw cells, alpha motor neurons, afferent neurons, efferent neurons, motor neurons and interneurons.
In some embodiments, the reference cell is a cell of a cell type that normally expresses or functionally expresses the RNA or protein of interest without genetic engineering. In some embodiments, the reference cell is a cell that has the capacity to stably express the RNA or protein of interest. In some embodiments the reference cell is a cell that has the capacity to express the RNA or protein of interest without associated cytotoxicity.
In a further aspect, the invention provides a method for producing the cells and cell lines of the invention. In one embodiment, the method comprises the steps of:
According to the method, the cells are cultured under a desired set of culture conditions. The conditions can be any desired conditions. Those of skill in the art will understand what parameters are comprised within a set of culture conditions. For example, culture conditions include but are not limited to: the media (Base media (DMEM, MEM, RPMI, serum-free, with serum, fully chemically defined, without animal-derived components), mono and divalent ion (sodium, potassium, calcium, magnesium) concentration, additional components added (amino acids, antibiotics, glutamine, glucose or other carbon source, HEPES, channel blockers, modulators of other targets, vitamins, trace elements, heavy metals, co-factors, growth factors, anti-apoptosis reagents), fresh or conditioned media, with HEPES, pH, depleted of certain nutrients or limiting (amino acid, carbon source)), level of confluency at which cells are allowed to attain before split/passage, feeder layers of cells, or gamma-irradiated cells, CO2, a three gas system (oxygen, nitrogen, carbon dioxide), humidity, temperature, still or on a shaker, and the like, which will be well known to those of skill in the art.
The cell culture conditions may be chosen for convenience or for a particular desired use of the cells. Advantageously, the invention provides cells and cell lines that are optimally suited for a particular desired use. That is, in embodiments of the invention in which cells are cultured under conditions for a particular desired use, cells are selected that have desired characteristics under the condition for the desired use.
By way of illustration, if cells will be used in assays in plates where it is desired that the cells are adherent, cells that display adherence under the conditions of the assay may be selected. Similarly, if the cells will be used for protein production, cells may be cultured under conditions appropriate for protein production and selected for advantageous properties for this use.
In some embodiments, the method comprises the additional step of measuring the growth rates of the separate cell cultures. Growth rates may be determined using any of a variety of techniques means that will be well known to the skilled worker. Such techniques include but are not limited to measuring ATP, cell confluency, light scattering, optical density (e.g., OD 260 for DNA). Preferably growth rates are determined using means that minimize the amount of time that the cultures spend outside the selected culture conditions.
In some embodiments, cell confluency is measured and growth rates are calculated from the confluency values. In some embodiments, cells are dispersed and clumps removed prior to measuring cell confluency for improved accuracy. Means for monodispersing cells are well-known and can be achieved, for example, by addition of a dispersing reagent to a culture to be measured. Dispersing agents are well-known and readily available, and include but are not limited to enzymatic dispersing agents, such as trypsin or other protease, and non-enzymatic cell dissociation reagents, including but not limited to EDTA-based dispersing agents. Growth rates can be calculated from confluency date using commercially available software for that purpose such as HAMILTON VECTOR. Automated confluency measurement, such as using an automated microscopic plate reader is particularly useful. Plate readers that measure confluency are commercially available and include but are not limited to the CLONE SELECT IMAGER (Genetix). Typically, at least 2 measurements of cell confluency are made before calculating a growth rate. The number of confluency values used to determine growth rate can be any number that is convenient or suitable for the culture. For example, confluency can be measured multiple times over e.g., a week, 2 weeks, 3 weeks or any length of time and at any frequency desired.
When the growth rates are known, according to the method, the plurality of separate cell cultures are divided into groups by similarity of growth rates. By grouping cultures into growth rate bins, one can manipulate the cultures in the group together, thereby providing another level of standardization that reduces variation between cultures. For example, the cultures in a bin can be passaged at the same time, treated with a desired reagent at the same time, etc. Further, functional assay results are typically dependent on cell density in an assay well. In some embodiments, a true comparison of individual clones is only accomplished by having them plated and assayed at the same density. Grouping into specific growth rate cohorts enables the plating of clones at a specific density that allows them to be functionally characterized in a high throughput format
The range of growth rates in each group can be any convenient range. It is particularly advantageous to select a range of growth rates that permits the cells to be passaged at the same time and avoid frequent renormalization of cell numbers. Growth rate groups can include a very narrow range for a tight grouping, for example, average doubling times within an hour of each other. But according to the method, the range can be up to 2 hours, up to 3 hours, up to 4 hours, up to 5 hours or up to 10 hours of each other or even broader ranges. The need for renormalization arises when the growth rates in a bin are not the same so that the number of cells in some cultures increases faster than others. To maintain substantially identical conditions for all cultures in a bin, it is necessary to periodically remove cells to renormalize the numbers across the bin. The more disparate the growth rates, the more frequently renormalization is needed.
In step d) the cells and cell lines may be tested for and selected for any physiological property including but not limited to: a change in a cellular process encoded by the genome; a change in a cellular process regulated by the genome; a change in a pattern of chromosomal activity; a change in a pattern of chromosomal silencing; a change in a pattern of gene silencing; a change in a pattern or in the efficiency of gene activation; a change in a pattern or in the efficiency of gene expression; a change in a pattern or in the efficiency of RNA expression; a change in a pattern or in the efficiency of RNAi expression; a change in a pattern or in the efficiency of RNA processing; a change in a pattern or in the efficiency of RNA transport; a change in a pattern or in the efficiency of protein translation; a change in a pattern or in the efficiency of protein folding; a change in a pattern or in the efficiency of protein assembly; a change in a pattern or in the efficiency of protein modification; a change in a pattern or in the efficiency of protein transport; a change in a pattern or in the efficiency of transporting a membrane protein to a cell surface change in growth rate; a change in cell size; a change in cell shape; a change in cell morphology; a change in % RNA content; a change in % protein content; a change in % water content; a change in % lipid content; a change in ribosome content; a change in mitochondrial content; a change in ER mass; a change in plasma membrane surface area; a change in cell volume; a change in lipid composition of plasma membrane; a change in lipid composition of nuclear envelope; a change in protein composition of plasma membrane; a change in protein; composition of nuclear envelope; a change in number of secretory vesicles; a change in number of lysosomes; a change in number of vacuoles; a change in the capacity or potential of a cell for: protein production, protein secretion, protein folding, protein assembly, protein modification, enzymatic modification of protein, protein glycosylation, protein phosphorylation, protein dephosphorylation, metabolite biosynthesis, lipid biosynthesis, DNA synthesis, RNA synthesis, protein synthesis, nutrient absorption, cell growth, mitosis, meiosis, cell division, to dedifferentiate, to transform into a stem cell, to transform into a pluripotent cell, to transform into a omnipotent cell, to transform into a stem cell type of any organ (i.e. liver, lung, skin, muscle, pancreas, brain, testis, ovary, blood, immune system, nervous system, bone, cardiovascular system, central nervous system, gastro-intestinal tract, stomach, thyroid, tongue, gall bladder, kidney, nose, eye, nail, hair, taste bud), to transform into a differentiated any cell type (i.e. muscle, heart muscle, neuron, skin, pancreatic, blood, immune, red blood cell, white blood cell, killer T-cell, enteroendocrine cell, taste, secretory cell, kidney, epithelial cell, endothelial cell, also including any of the animal or human cell types already listed that can be used for introduction of nucleic acid sequences), to uptake DNA, to uptake small molecules, to uptake fluorogenic probes, to uptake RNA, to adhere to solid surface, to adapt to serum-free conditions, to adapt to serum-free suspension conditions, to adapt to scaled-up cell culture, for use for large scale cell culture, for use in drug discovery, for use in high throughput screening, for use in a functional cell based assay, for use in membrane potential assays, for use in calcium flux assays, for use in G-protein reporter assays, for use in reporter cell based assays, for use in ELISA studies, for use in in vitro assays, for use in vivo applications, for use in secondary testing, for use in compound testing, for use in a binding assay, for use in panning assay, for use in an antibody panning assay, for use in imaging assays, for use in microscopic imaging assays, for use in multiwell plates, for adaptation to automated cell culture, for adaptation to miniaturized automated cell culture, for adaptation to large-scale automated cell culture, for adaptation to cell culture in multiwell plates (6, 12, 24, 48, 96, 384, 1536 or higher density), for use in cell chips, for use on slides, for use on glass slides, for microarray on slides or glass slides, for immunofluorescence studies, for use in protein purification, for use in biologics production, for use in the production of industrial enzymes, for use in the production of reagents for research, for use in vaccine development, for use in cell therapy, for use in implantation into animals or humans, for use in isolation of factors secreted by the cell, for preparation of cDNA libraries, for purification of RNA, for purification of DNA, for infection by pathogens, viruses or other agent, for resistance to infection by pathogens, viruses or other agents, for resistance to drugs, for suitability to be maintained under automated miniaturized cell culture conditions, for use in the production of protein for characterization, including: protein crystallography, vaccine development, stimulation of the immune system, antibody production or generation or testing of antibodies. Those of skill in the art will readily recognize suitable tests for any of the above-listed properties.
Tests that may be used to characterize cells and cell lines of the invention and/or matched panels of the invention include but are not limited to: Amino acid analysis, DNA sequencing, Protein sequencing, NMR, A test for protein transport, A test for nucelocytoplasmic transport, A test for subcellular localization of proteins, A test for subcellular localization of nucleic acids, Microscopic analysis, Submicroscopic analysis, Fluorescence microscopy, Electron microscopy, Confocal microscopy, Laser ablation technology, Cell counting and Dialysis. The skilled worker would understand how to use any of the above-listed tests.
When collections or panels of cells or cell lines are produced, e.g., for drug screening, the cells or cell lines in the collection or panel may be matched such that they are the same (including substantially the same) with regard to one or more selective physiological properties. The “same physiological property” in this context means that the selected physiological property is similar enough amongst the members in the collection or panel such that the cell collection or panel can produce reliable results in drug screening assays; for example, variations in readouts in a drug screening assay will be due to, e.g., the different biological activities of test compounds on cells expressing different forms of a protein, rather than due to inherent variations in the cells. For example, the cells or cell lines may be matched to have the same growth rate, i.e., growth rates with no more than one, two, three, four, or five hour difference amongst the members of the cell collection or panel. In some embodiments, this may be achieved by, for example, binning cells by their growth rate into five, six, seven, eight, nine, or ten groups, and creating a panel using cells from the same or different binned group. In some embodiments, cells can be binned by growth rate into 11, 12, 13, 14, 15, 16, 17, 18, 19 or 20 groups. In some embodiments, cells can be binned by growth rate into at least 20, 25, 30, 35, 40, 45, 50, 60, 70, 80, 90, 100 or more than 100 groups. In some embodiments, a panel of cell lines can comprise cell lines binned into the same group based on their growth rate. In some embodiments, a panel of cell lines can comprise cell lines binned into different groups based on their growth rate. Methods of determining cell growth rate are well known in the art. The cells or cell lines in a panel also can be matched to have the same Z′ factor (e.g., Z′ factors that do not differ by more than 0.1), protein expression level (e.g., CFTR expression levels that do not differ by more than 5%, 10%, 15%, 20%, 25%, or 30%), RNA expression level, adherence to tissue culture surfaces, and the like. Matched cells and cell lines can be grown under identical conditions, achieved by, e.g., automated parallel processing, to maintain the selected physiological property. In some embodiments, cells or cell lines of the invention can be binned into groups based on physiological properties of the cells or cell lines including but not limited to growth rates. In some embodiments, a matched panel of cells or cell lines can comprise cells or cell lines of one or more bins grouped by at least one physiological property of a cell including but not limited to growth rate.
In one embodiment, the panel is matched for growth rate under the same set of conditions. Such a panel, also referred to herein as a matched panel, are highly desirable for use in a wide range of cell-based studies in which it is desirable to compare the effect of an experimental variable across two or more cell lines. Cell lines that are matched for growth rate maintain roughly the same number of cells per well over time thereby reducing variation in growth conditions, such as nutrient content between cell lines in the panel
According to the invention, matched panels may have growth rates within any desired range, depending on a number of factors including the characteristics of the cells, the intended use of the panel, the size of the panel, the culture conditions, and the like. Such factors will be readily appreciated by the skilled worker.
Growth rates may be determined by any suitable and convenient means, the only requirement being that the growth rates for all of the cell lines for a matched panel are determined by the same means. Numerous means for determining growth rate are known as described herein.
A matched panel of the invention can comprise any number of clonal cell lines. The maximum number of clonal cell lines in the panel will differ for each use and user and can be as many as can be maintained. In various embodiments, the panel may comprise 2, 3, 4, 5, 6, 7, 8, 9, 10 or more clonal cell lines, for example, at least 12, at least 15, at least 20, at least 24, at least 25, at least 30, at least 35, at least 40, at least 45, at least 48, at least 50, at least 75, at least 96, at least 100, at least 200, at least 300, at least 384, at least 400 or more clonal cell lines. In some embodiments, the matched panel may comprise at least 100, 150, 200, 250, 300, 350, 400, 350, 500, 550, 600, 650, 700, 750, 800, 850, 900 or 1,000 clonal cell lines. In other embodiments, the matched panel may comprise at least 1,100, 1,250, 1,500, 2,000, 3,000, 4,000, 5,000, 6,000, 7,000, 8,000, 9,000 or 10,000 clonal cell lines. In other embodiments, the matched panel may comprise at least 11,000, 15,000, 20,000, 25,000, 30,000, 35,000, 40,000, 45,000, 50,000, 60,000, 70,000, 80,000, 90,000 or 100,000 clonal cell lines. In other embodiments, the matched panel may comprise at least 100,000, 150,000, 200,000, 300,000, 400,000, 500,000, 600,000, 700,000, 800,000, 900,000 or 1,000,000 clonal cell lines or more than 1,000,000 clonal cell lines. In yet other embodiments, the matched panel may comprise at least 1,000 clonal cell lines.
According to the invention, the panel comprises a plurality of clonal cell lines, that is, a plurality of cell lines generated from a different single parent cell. In some embodiments the plurality of cell lines in a panel of cell lines are of the same type. In some embodiments the plurality of cell lines in a panel of cell lines are of at least two different types. Any desired cell type may be used in the production of a matched panel. The panel can comprise cell lines of all the same cell type or cell lines of different cell types.
The clonal cell lines in the panel stably express one or more proteins of interest. The stable expression can be for any length of time that is suitable for the desired use of the panel but at a minimum, is sufficiently long to permit selection and use in a matched panel.
The clonal cell lines in the matched panel may all express the same one or more proteins of interest or some clonal cell lines in the panel may express different proteins of interest.
In some embodiments, the matched panel comprises one or more clonal cell lines that express different proteins of interest. That is, a first clonal cell line in the panel may express a first protein of interest, a second clonal cell line in the panel may express a second protein of interest, a third cell line may express a third protein of interest, etc. for as many different proteins of interest as are desired. The different proteins of interest may be different isoforms, allelic variants, splice variants, or mutated (including but not limited to sequence mutated or truncated), different subunit stoichiometries, different subunit assemblies, differentially folded forms, differentially active forms, forms with different functionalities, forms with different binding properties, forms associated with different accessory factors, forms expressed in different cell backgrounds, forms expressed in different cellular genetic backgrounds, forms expressed in cells with different endogenous expression profiles, differentially localized forms, chimeric or chemically including modified forms, enzymatically modified forms, post-translationally modified forms, glycosylated forms, proteolyzed forms, or combinations thereof of a protein of interest. In some embodiments the different proteins can be members of a functionally defined group of proteins, such as a panel of bitter taste receptors or a panel of kinases. In some embodiments the different proteins may be part of the same or interrelated signaling pathways. In still other panels involving heteromultimeric proteins (including heterodimers), the panel may comprise two or more different combinations of subunits up to all possible combinations of subunits. The combinations may comprise subunit sequence variants, subunit isoform combinations, interspecies combinations of subunits and combinations of subunit types.
By way of example, Gamma-aminobutyric acid (GABA)A receptors typically comprise two alpha subunits, two beta subunits and a gamma subunit. There are 6 alpha isoforms, 5 beta isoforms, 4 gamma isoforms, and a delta, a pi, a theta and an epsilon subunit. The present invention contemplates panels comprising two or more combinations of any of these subunits including panels comprising every possible combination of alpha, beta, gamma, delta, pi, epsilon and theta subunit. Further, the GABA receptor family also includes GABAB and GABAC receptors. The invention also contemplates panels that comprise any combination of GABAA, GABAB and GABAC subunits. In some embodiments, such panels comprise human GABA subunits. In other embodiments, mammalian GABA receptor panels may comprise non-human primate (e.g., cynomolgus) GABA receptors, mouse, rat or human GABA receptor panels or mixtures thereof.
In a further example, the invention contemplates one or more epithelial sodium channel (ENaC) panels, including any mammalian ENaC panel such as a non-human primate (e.g., cynomolgus) ENaC, mouse, rat or human ENaC panels or mixtures thereof. Like GABA receptors, intact ENaC comprise multiple subunits: alpha or delta, beta and gamma. The invention contemplates panels with at least two different combinations of ENaC subunits and also contemplates all possible combinations of ENaC subunits, including combinations of subunits from different species, combinations of isoforms, allelic variants, SNPs, chimeric subunits, forms comprising modified and/or non-natural amino acids and chemically modified such as enzymatically modified subunits. The present invention also contemplates panels comprising any ENaC form set forth in International Application PCT/US09/31936, the contents of which are incorporated by reference in its entirety.
In a further particular embodiment, a matched panel of 25 bitter taste receptors comprising cell lines that express native (no tag) functional bitter receptors listed in Table 10. In some embodiments, the panel is matched for growth rate. In some embodiments the panel is matched for growth rate and an additional physiological property of interest. In some embodiments the cell lines in the panel were generated in parallel and/or screened in parallel.
Further exemplary but non-limited examples of panels and their uses are the following: a panel of odorant receptors (insect, canine, human, bed bug), for example to profile of fragrances or to discovery of modulators; panels of cells expressing a gene fused to a test peptide, i.e., to find a peptide that works to internalize a cargo such as a protein, including an antibody, monoclonal antibody or a non-protein drug into cells (the cargo could be a reporter such as GFP or AP). Related to this embodiment, supernatants from cells of this panel could be added to other cells for assessment of internalization. In such an embodiment, the panel may comprise different cell types to assess cell-type specific delivery. A panel of cell lines expressing different antibody or monoclonal antibody heavy chain/light chain combinations to identify active antibodies or monoclonal antibodies. An antibody panel also could provide a series of derivatized versions of an antibody or monoclonal antibody to identify one with improved characteristics, such as stability in serum, binding affinity and the like. Yet another panel could be used to express a target protein in the presence of various signaling molecules, such as different G-proteins. Still another type of panel could be used to test variants of a target proteins for improved activity/stability. A panels could comprise single nucleotide polymorphs (SNPs) or other mutated forms of a target protein to select modulators that act on a subset, many or all forms. Other panels could be used to define the patterns of activity of test compounds on a family of proteins or isoforms of a protein (such as GABAA or other CNS ion channels). Differentially acting compounds could then be used in further study to determine the function/role/localization of corresponding subunit combinations in vivo. The test compounds could be known modulators that failed in the clinic or ones that have adverse off-target effects, to determine subunit combinations that may correlate with such effects. Still other panels could be used in HTS for parallel screening for reliable assessment of compounds' activity at multiple target subtypes to assist in finding compounds active at desired targets and that have minimal off target effects.
The panels can include cells that have been engineered to express any desired group of proteins and all such panels are contemplated by the invention.
The panels can include cells that have been engineered to express any desired group of RNAs and all such panels are contemplated by the invention.
In some embodiments, the invention provides a panel of cells or cell lines, wherein the panel comprises a plurality of cells or cell lines each expressing a different odorant receptor. These odorant receptor panels can be used to generate odorant activity profiles of compounds or compositions of interest. An odorant activity profile of a compound or composition refers to the effect of the compound or composition on the activity of a plurality of odorant receptors. To generate an odorant activity profile of a compound or composition of interest, the compound or composition is contacted with a plurality of cells or cell lines each expressing a different odorant receptor.
In some embodiments, the odorant receptor cell panels are used to identify compounds that modify, enhance, or reduce the odorant activity profile of a compound or composition. Compounds that are identified as modifying, enhancing, or reducing the odorant activity profile of another compound or composition are predicted to modify, enhance, or reduce the olfactory effect of the other compound or composition.
In some embodiments, the odorant receptor cell panels are used to identify compounds that have an odorant activity profile that is similar to a compound or composition of interest. Compounds that are identified as having an odorant activity profile that is similar to a compound or composition of interest are predicted to have an olfactory effect that is similar to the other compound or composition, i.e., smell similar or identical. Odorant activity profiles can be compared as described below.
Useful odorant receptors include, but are not limited to, the olfactory receptors set forth in Tables 10-12. In certain embodiments, the odorant receptors are of the class I human olfactory receptors or the class II human olfactory receptors or a combination thereof. An odorant receptor panel of the present invention can have at least 2, 5, 10, 25, 50, 75, 100, 250, 500, 750, 1000, 1500, 2000, or at least 2500 different cells or cell lines each expressing a different odorant receptor. The different odorant receptors may be of different species or of the same species. In certain embodiments, an odorant receptor for use with the cells, panels and methods of the invention may be encoded by a pseudogene.
The activity of a compound or composition of interest on an odorant receptor can be measured by any technique known to the skilled artisan. Assays to measure the effect of a compound or composition of interest on the activity of an odorant receptor include, but are not limited to: cell based assays, fluorescent cell based assays, imaging assays, calcium flux assays, membrane potential assays, high throughput screening assays, fluorogenic assays and combination of the above. Any assays to be used with the methods of the invention can be conducted in high throughput format.
Any of the cells or cell lines disclosed herein can be used to generate an odorant receptor panel in accordance with the present invention. In some embodiments, a host cell for generation of an odorant receptor panel may be a cell that has been tested and verified to endogenously express signaling or other protein factors that are desirable for functional expression of odorant receptors. RNA or protein characterization of cells by tests including RT-PCR and microarray methods including genechip analysis may be used to identify such cells.
In some embodiments, a cell panel of the invention comprises a plurality of cells or cell lines, wherein each cell or cell line has been engineered to express one or more insect odorant receptor. The resulting cell panel can be used in cell based assays to characterize odorants and for high throughput screening (“HTS”) to identify odorant receptor modulators.
In some embodiments, a panel of cells or cell lines may comprise all or a subset of the odorant receptors from one species (e.g., a species of mosquito). A panel of cells or cell lines may comprise at least one odorant receptor from at least two different insect species. Insect odorant receptors from any insect species may be used including insects that transmit human or animal disease, insects that afflict crop or cause agricultural damage or damage to plants, including but not limited to mosquitoes, cockroaches, beetles, bed bugs, moths, butterflies, flies, ants, crickets, bees, wasps, fruit flies, ticks, lice, genital lice, scorpions, millipedes, centipedes, grasshoppers, praying mantis, and spiders. A common method to identify a protein as an olfactory receptor is based on sequence comparisons to known olfactory receptors. In some embodiments, cell based assays may also be used to test for responsiveness of a transmembrane protein to known volatile or odorant compounds in order to determine its role as an odorant receptor.
Substances including compounds and extracts that attract or repel insects can be tested against a panel provided herein to identify responsive receptors or receptors whose activity is modulated by the test substance. The substances may be collected from, e.g., plants, flowers, foods (e.g., cheese), animals, smoke, waste products, secretions, sweat (including human sweat, e.g., male sweat or female sweat), industrial products, natural and synthetic chemicals and biological preparations. Substances may be tested against a subset or all odorant receptor cell lines to identify the profile of activity of a compound at against all tested receptors. The patterns of activity that result from testing of substances against the odorant receptor cell lines may be used to characterize, “fingerprint” or serve as a diagnostic.
HTS may be used to screen a cell line or panel comprising an insect odorant receptor identified to respond to a substance in order to identify other substances with similar, increased or decreased activity. HTS may be used to screen a cell line or panel comprising an insect odorant receptor that responds to a substance to identify compounds that modulate, block or potentiate the activity of the receptor in the presence of the substance. HTS may be used to screen a cell line or panel comprising an odorant receptor that does not respond to a substance to identify compounds that result in a response or activity of the receptor in the presence of the substance.
In some embodiments, the methods of the invention are used to identify a compound or a mixture of compounds that have an activity that is similar to a known substance (e.g., a known compound) on an insect odorant receptor. In a more specific embodiment, the methods of the invention are used to identify a compound that mimics the odorant receptor activity of DEET and/or other insect repellents and attractants. In certain embodiments, the methods of the invention are used to identify compounds that can be used as insect repellents. In certain embodiments, the compound that is identified as insect repellents is volatile and non-toxic to the environment, human, animals and/or crops. In certain embodiments, the methods of the invention are used to identify compounds that can be used as insects attractant. In certain embodiments, the compound that is identified as insect attractant is a volatile compound and non-toxic to the environment, human, animals and/or crops. Such insect attractants can be used in insect traps. In certain embodiments, the insect attractant or repellent can be specific for a particular insect species.
In specific embodiments, the methods of the invention are used to identify a compound or a mixture of compounds that block the activity of a particular substance on one or more odorant receptors. In a more specific embodiment, the methods are used to identify compounds that block receptor responses to sweat, human or animal secretions or their components or carbon dioxide.
In some embodiments, the methods of the invention are used to identify one or a mixture of compounds that potentiate the activity of a particular substance (e.g., a particular compound) on one or more odorant receptors, for instance, compounds that attract or repel insects.
In some embodiments, the methods of the invention are used to identify one or a mixture of compounds that alter the activity of a particular substance (e.g., a particular compound) on one or more odorant receptors. In other embodiments, the methods of the invention can be used to identify a combination of at least 2 compounds, wherein the at least 2 compounds activate an odorant receptor only if combined, and wherein each of the at least 2 compounds does not activate the odorant receptor individually. The receptor can be a receptor that detects an insect repellent or an insect attractant.
In some embodiments, the methods of the invention are used to generate odorant activity profiles of human sweat samples obtained from males and/or females and fractions of these or compounds isolated from these to identify responsive receptors and correlate this data with other data including for instance results for testing of the same substances against one or more insect species to identify activities or compounds that correlate with insect repulsion or attraction.
In some embodiments, the methods of the invention are used to test and compare the odorant activity profiles of at least two samples. In specific embodiments, samples can be volatiles obtained from different plants; different species of plants or animals, or from different flowers. The odorant activity profiles of the different samples are then compared to identify responsive receptors (e.g., those receptors the activities of which are affected by the different samples). The responsive receptors are an indicator for the chemical composition of the samples. The similarity of the odorant activity profiles of the samples that are being compared is a measure for the chemical similarity of the different samples.
In some embodiments, the methods of the invention are used to identify a number of chemically diverse compounds having similar activity, for combined or sequential use or introduction to address potential insect adaptation or evolution that may render at least one of the compounds ineffective.
A panel of cell lines each comprising one or more human odorant receptors can be produced for use in cell based assays to characterize odorants and for HTS to identify odorant receptor modulators.
Substances including compounds and extracts that have a scent, odor, aroma or fragrance can be tested against a panel of human odorant receptors to identify responsive receptors or receptors whose activity is modulated by the test substance. The compounds or mixtures can be collected from plants, flowers, foods, animals, cigarettes, tobacco, truffles, musk, vanilla, mint, waste products, secretions, sweat (including human sweat, e.g., male sweat or female sweat), industrial products, natural and synthetic chemicals and biological preparations including disease tissues and tumors. Compounds may be tested against a subset or all human odorant receptor cell lines to identify the profile of activity of a compound against all tested receptors. The patterns of activity that result from testing of substances against the human odorant receptor cell lines may be used to characterize, “fingerprint” or serve as a diagnostic.
HTS may be used to screen a cell line or panel comprising a human odorant receptor identified to respond to a substance to identify other substances with similar, increased or decreased activity. HTS may be used to screen a cell line comprising a human odorant receptor that responds to a substance to identify compounds that modulate, block or potentiate the activity of the receptor in the presence of the substance. HTS may be used to screen a cell line comprising a human odorant receptor that does not respond to a substance to identify compounds that result in a response or activity of the receptor in the presence of the substance.
Illustrative uses of the odorant receptor panels include:
Identify one or a mixture of compounds that have similar activity on one or more odorant receptors as a known substance, for instance a synthetic compound that can mimic the activity of musk.
Identify one or a mixture of compounds that block the activity of a known substance on one or more odorant receptors, for instance compounds that block substances that are malodorous (human or animal waste).
Identify one or a mixture of compounds that potentiate the activity of a known substance on one or more odorant receptors, for instance compounds that mimic the scent of a rose or the aroma of a steak.
Identify one or a mixture of compounds that alter the activity of a known substance on one or more odorant receptors, for instance compounds that result in the activation of receptors that detect malodors in the presence of substances such as tobacco smoke that may not normally produce this effect.
Identify one or a mixture of compounds that alter the activity of a known substance on one or more odorant receptors, for instance compounds that result in the activation of receptors that detect desirable scents in the presence of substances such as malodorous substances that may normally activate other receptors not receptors corresponding to desirable scents.
Profile human sweat samples obtained from males and females and fractions of these or compounds isolated from these to identify responsive receptors and correlate this data with other data including for instance human psychophysics studies to identify activities or compounds that correlate with perceived malodor or attraction.
Test a set of samples that can be compared (for instance fragrances obtained from roses of different species, or fragrances obtained from different flowers, or fractions of one substance) to identify common or specific receptors that are responsive to these fragrances.
The cells, panels and methods described herein may be applied to odorant receptors from other species including but not limited to: mammalian species selected from the group consisting of: human, non-human primate, bovine, porcine, feline, rat, marsupial, murine, canine, ovine, caprine, rabbit, guinea pig and hamster; or insect species selected from the group consisting of: Mosquitoes including Anopheles (Anopheles gamiae and all mosquito sub-species, Aedes (including Aedes aegypti and all sub-species), Culex and Aedes mosquitoes, Simulium, black flies, Phlebotomus, sand flies, Tabanus, horse flies, Chryops, deer flies, Glossina, tsetse flies, Order Siphonaptera, Fleas, Xenopsylla, Nosopsyllus, Order Hemiptera, Triatoma and Rhodnius (kissing bugs), Order Anoplura, Sucking Lice, Pediculus humanis, Lice, Black Flies, Chiggers, Eye Gnats, Stable fly, Deer and Horse Flies, Aphid, Migratory locust, Maize planthopper, Thrips, Flies, Lepidoptera, Nematodes, Homoptera, Coleoptera, Mites, Termite, cockroaches including German cockroach, Ants, Aphididae, Acrididae, Fulgoromorpha, Fulgoroidea, Thripidae, Phlaeothripidae, Tortricidae, Noctuidae, Crambidae, Noctuidae, Plutellidae, Pyralidae, Heteroderidae, Aleyrodidae, Chrysomelidae, Tenebrionidae, Curculionoidea, the grain weevil, Sitophilus granarius, rice weevil, Sitophilus oryzae, alfalfa weevil, Hypera postica. Seed weevil on peas, Bruchus pisorum, on bean seeds, Acanthoscelides obtectus, Tetranychidae, Rhinotermitidae, Kolotermitidae, Blattellidae, Formicidae, beetles and bed bugs, and moths.
The odorant activity profile of a compound of interest and a landmark odorant activity profile may be compared through computation of a correlation between the odorant activity profiles, such as but not limited to computing a measure of similarity between the odorant activity profiles. The landmark odorant activity profile may be one of a group of odorant activity profiles in a database. The landmark odorant activity profile may be a historical profile. The odorant activity profile of the compound of interest can comprise measured amounts representing an effect of the compound on the activity of two or more odorant receptors in a panel. Each landmark odorant activity profile comprises measured amounts representing the effect of a respective compound on the activity of two or more odorant receptors in the panel.
In some embodiments, each respective compound corresponding to a landmark odorant activity profile can be associated with a known odor. That is, measured amounts of the effect of a respective compound on the activity of two or more odorant receptors in the panel can be assembled to produce a landmark transcript profile that can be associated with a known odor. The database of landmark odorant activity profiles can be stored on a computer readable storage medium. In specific embodiments, the database contains at least 10 landmark odorant activity profiles, at least 50 landmark odorant activity profiles, at least 100 landmark odorant activity profiles, at least 500 landmark odorant activity profiles, at least 1,000 landmark odorant activity profiles, at least 10,000 landmark odorant activity profiles, or at least 50,000 landmark odorant activity profiles, each landmark odorant activity profile containing measured amounts of at least 2, at least 10, at least 100, at least 200, at least 500, at least 1,000, at least 2000, at least 2500, at least 7500, at least 10,000, at least 20,000, at least 25,000, or at least 35,000 components. In the foregoing embodiment, the odorant activity profile of the compound of interest can be compared to a plurality of landmark odorant activity profiles to determine the one or more landmark odorant activity profiles that correlate with (e.g., are most similar to) the odorant activity profile of the compound of interest, and the compound of interest can be characterized as having the known odor(s) associated with the respective compound corresponding to these one or more landmark odorant activity profiles.
In other embodiments, a compound of interest can be associated with a known odor. In the foregoing embodiment, the odorant activity profile of the compound of interest can be compared to a plurality of landmark odorant activity profiles to determine the one or more landmark odorant activity profiles that correlate with (e.g., are most similar to) the odorant activity profile of the compound of interest, and the respective compound corresponding to these one or more landmark odorant activity profiles can be characterized as having the known odor associated with the compound of interest.
In certain embodiments, a correlation can be computed between the odorant activity profile of a compound of interest and each landmark odorant activity profile of a plurality of landmark odorant activity profiles stored in a database. The correlation can be computed by comparing a measured amount in the odorant activity profile of the compound of interest representing an effect of the compound of interest on the activity of a selection of two or more odorant receptors in a panel to the corresponding measured amount in the landmark odorant activity profile representing an effect of a different compound on the activity of the same selection of two or more odorant receptors in the panel. The odorant activity profile of the compound of interest can be deemed to correlate with a landmark odorant activity profile if the measured amounts in the landmark odorant activity profile are within about 2%, about 5%, about 8%, about 10%, about 12%, about 15%, about 20%, about 25%, about 30%, or about 35% of the measured amounts in the odorant activity profile of the compound of interest.
The odorant activity profile of a compound of interest can be deemed to be most similar to a landmark odorant activity profile if a measure of similarity between the odorant activity profile of the compound of interest and the landmark odorant activity profile is above a predetermined threshold. In specific embodiments, the predetermined threshold can be determined as the value of the measure of similarity which indicates that the measured amounts in a landmark odorant activity profile are within about 2%, about 5%, about 8%, about 10%, about 12%, about 15%, about 20%, about 25%, about 30%, or about 35% of the measured amounts in the odorant activity profile of the compound of interest.
In some embodiments, the odorant activity profile of a compound of interest can be expressed as a vector p,
p=[p1, . . . pi, . . . pn]
where pi is the measured amount of the i'th component, for example, the effect of the compound of interest on the i'th biological activity of a given odorant receptor in the panel. In specific embodiments, n is more than 2, more than 10, more than 100, more than 200, more than 500, more than 1000, more than 2000, more than 2500, more than 7500, more than 10,000, more than 20,000, more than 25,000, or more than 35,000. Each landmark odorant activity profile also can be expressed as a vector p. In computing a correlation, the measured amount of the i'th component in the vector representing the odorant activity profile for the compound of interest can be compared to the corresponding measured amount of the i'th component of the vector representing a landmark odorant activity profile, for each component i=1 . . . n.
A correlation may be computed using any statistical method in the art for determining the probability that two datasets are related may be used in accordance with the methods of the present invention in order to identify whether there is a correlation between the odorant activity profile of a compound of interest and a landmark odorant activity profile. For example, the correlation between the odorant activity profile (pi1) of the compound of interest and each landmark odorant activity profile (pi2) can be computed using a similarity metric sim(pi1, pi2). One way to compute the similarity metric sim(pi1, pi2) is to compute the negative square of the Euclidean distance. In alternative embodiments, metrics other than Euclidean distance can be used to compute sim(pi1, pi2), such as a Manhattan distance, a Chebychev distance, an angle between vectors, a correlation distance, a standardized Euclidean distance, a Mahalanobis distance, a squared Pearson correlation coefficient, or a Minkowski distance. In some embodiments a Pearson correlation coefficient, a squared Euclidean distance, a Euclidean sum of squares, or squared Pearson correlation coefficients is used to determine similarity. Such metrics can be computed, for example, using SAS (Statistics Analysis Systems Institute, Cary, N.C.) or S-Plus (Statistical Sciences, Inc., Seattle, Wash.). Use of such metrics are described in Draghici, 2003, Data Analysis Tools for DNA Microarrays, Chapman & Hall, CRC Press London, chapter 11, which is hereby incorporated by reference herein in its entirety for such purpose.
The correlation can also be computed based on ranks, where xi and yi are the ranks of the values of the measured amounts in ascending or descending numerical order. See for example, Conover, Practical Nonparametric Statistics, 2nd ed., Wiley, (1971). Shannon mutual information also can be used as a measure of similarity. See for example, Pierce, An Introduction To Information Theory: Symbols, Signals, and Noise, Dover, (1980), which is incorporated by reference herein in its entirety.
Various classifiers known in the art can be trained according to the methods described in this application, and used to classify a compound of interest as having an odor. Algorithms can be used to produce classifiers capable of predicting an odor of a compound of interest using an odorant activity profile of the compound of interest.
In some embodiments, a classifier can be trained to classify a compound as to an odor using the measured amounts in the landmark odorant activity profile of a previously characterized compound and the known odor associated with that previously characterized compound. Each respective compound corresponding to a landmark odorant activity profile can be associated with a known odor. The classifier may be an algorithm used for classification by applying a non-supervised or supervised learning algorithm to evaluate the measured amounts in the landmark odorant activity profile of a previously characterized compound and the known odor associated with that previously characterized compound. The odorant activity profile of the compound of interest can be processed using the classifier to classify the compound of interest as to an odor. That is, the classifier can be used to classify the compound of interest as having one or more of the known odors associated with the plurality of landmark odorant activity profiles used to train the class
In some embodiments, a compound of interest can be associated with a known odor. In the foregoing embodiment, a classifier can be trained to identify one or more landmark odorant activity profiles that can be associated with the known odor of the compound of interest based on the odorant activity profile of the compound of interest. The classifier may be an algorithm used for classification by applying a non-supervised or supervised learning algorithm to evaluate the measured amounts in the landmark odorant activity profile of a respective compound, and to identify the one or more landmark odorant activity profiles that can be associated with the known odor of the compound of interest based on the odorant activity profile of the compound of interest.
Any standard non-supervised or supervised learning technique known in the art can be used to generate a classifier. Below are non-limiting examples of non-supervised and supervised algorithms known in the art. Given the disclosure in this application, one of skill in the art will appreciate that other pattern classification or regression techniques and algorithms may be used for the classifier and the present invention encompasses all such techniques.
Neural networks. In some embodiments, a classifier is learned using a neural network. A neural network is a two-stage regression or classification decision rule. A neural network has a layered structure that includes a layer of input units (and the bias) connected by a layer of weights to a layer of output units. For regression, the layer of output units typically includes just one output unit. However, neural networks can handle multiple quantitative responses in a seamless fashion.
In multilayer neural networks, there are input units (input layer), hidden units (hidden layer), and output units (output layer). There is, furthermore, a single bias unit that is connected to each unit other than the input units. Neural networks are described in Duda et al., 2001, Pattern Classification, Second Edition, John Wiley & Sons, Inc., New York; and Hastie et al., 2001, The Elements of Statistical Learning, Springer-Verlag, New York, each of which is hereby incorporated by reference herein in its entirety. Neural networks are also described in Draghici, 2003, Data Analysis Tools for DNA Microarrays, Chapman & Hall/CRC; and Mount, 2001, Bioinformatics: sequence and genome analysis, Cold Spring Harbor Laboratory Press, Cold Spring Harbor, N.Y., each of which is hereby incorporated by reference herein in its entirety. What are discussed below are some exemplary forms of neural networks.
The basic approach to the use of neural networks is to start with an untrained network, present a training pattern to the input layer, and to pass signals through the net and determine the output at the output layer. These outputs are then compared to the target values; any difference corresponds to an error. For classification, this error can be either squared error or cross-entropy (deviation). See, for example, Hastie et al., 2001, The Elements of Statistical Learning, Springer-Verlag, New York, which is hereby incorporated by reference herein in its entirety.
Three commonly used training protocols are stochastic, batch, and on-line. In stochastic training, patterns are chosen randomly from the training set and network weights are updated for each pattern presentation. Multilayer nonlinear networks trained by gradient descent methods such as stochastic back-propagation perform a maximum-likelihood estimation of weight values in the classifier defined by the network topology. In batch training, all patterns are presented to the network before learning takes place. Typically, in batch training, several passes are made through the training data. In online training, each pattern is presented once and only once to the net.
A recurrent problem in the use of three-layer networks is the optimal number of hidden units to use in the network. The number of inputs and outputs of a three-layer network are determined by the problem to be solved. In the present invention, the number of inputs for a given neural network will equal the number of biomarkers selected from Y. The number of output for the neural network will typically be just one. If too many hidden units are used in a neural network, the network will have too many degrees of freedom and if trained too long, there is a danger that the network will overfit the data. If there are too few hidden units, the training set cannot be learned. Generally speaking, however, it is better to have too many hidden units than too few. With too few hidden units, the classifier might not have enough flexibility to capture the nonlinearities in the date; with too many hidden units, the extra weight can be shrunk towards zero if appropriate regularization or pruning, as described below, is used. In typical embodiments, the number of hidden units is somewhere in the range of 5 to 100, with the number increasing with the number of inputs and number of training cases.
Clustering. In some embodiments, a classifier is learned using clustering. In some embodiments, select components i of the vectors representing the landmark odorant activity profiles are used to cluster the odorant activity profiles. In some embodiments, prior to clustering, the measured amounts are normalized to have a mean value of zero and unit variance.
Landmark odorant activity profiles that exhibit similar patterns of measured amounts across the training population will tend to cluster together. A particular combination of measured amounts of components i can be considered to be a good classifier in this aspect of the invention when the vectors form clusters for a particular known odor. See, e.g., pages 211-256 of Duda and Hart, Pattern Classification and Scene Analysis, 1973, John Wiley & Sons, Inc., New York (hereinafter “Duda 1973”), which is hereby incorporated by reference in its entirety. As described in Section 6.7 of Duda 1973, the clustering problem is described as one of finding natural groupings in a dataset. To identify natural groupings, two issues are addressed. First, a way to measure similarity (or dissimilarity) between two odorant activity profiles is determined. This metric (similarity measure) is used to ensure that the odorant activity profiles in one cluster are more like one another than they are to other odorant activity profiles. Second, a mechanism for partitioning the data into clusters using the similarity measure is determined.
Similarity measures are discussed in Section 6.7 of Duda 1973, where it is stated that one way to begin a clustering investigation is to define a distance function and to compute the matrix of distances between pairs of odorant activity profiles. If distance is a good measure of similarity, then the distance between odorant activity profiles in the same cluster will be significantly less than the distance between odorant activity profiles in different clusters. However, as stated on page 215 of Duda 1973, clustering does not require the use of a distance metric. For example, a nonmetric similarity function s(x, x′) can be used to compare two vectors x and x′. Conventionally, s(x, x′) is a symmetric function whose value is large when x and x′ are somehow “similar”. An example of a nonmetric similarity function s(x, x′) is provided on page 216 of Duda 1973.
Once a method for measuring “similarity” or “dissimilarity” between points in a dataset has been selected, clustering requires a criterion function that measures the clustering quality of any partition of the data. Partitions of the data set that extremize the criterion function are used to cluster the data. See, e.g., page 217 of Duda 1973. Criterion functions are discussed in Section 6.8 of Duda 1973. More recently, Duda et al., Pattern Classification, 2nd edition, John Wiley & Sons, Inc. New York, has been published. Pages 537-563 describe clustering in detail. Additional information on clustering techniques can be found in Kaufman and Rousseeuw, 1990, Finding Groups in Data: An Introduction to Cluster Analysis, Wiley, New York, N.Y.; Everitt, 1993, Cluster analysis (3d ed.), Wiley, New York, N.Y.; and Backer, 1995, Computer-Assisted Reasoning in Cluster Analysis, Prentice Hall, Upper Saddle River, N.J. Particular exemplary clustering techniques that can be used in the present invention include, but are not limited to, hierarchical clustering (agglomerative clustering using nearest-neighbor algorithm, farthest-neighbor algorithm, the average linkage algorithm, the centroid algorithm, or the sum-of-squares algorithm), k-means clustering, fuzzy k-means clustering algorithm, and Jarvis-Patrick clustering.
Principal component analysis. In some embodiments, a classifier is learned using principal component analysis. Principal component analysis is a classical technique to reduce the dimensionality of a data set by transforming the data to a new set of variable (principal components) that summarize the features of the data. See, e.g., Jolliffe, 1986, Principal Component Analysis, Springer, New York, which is hereby incorporated by reference herein in its entirety. Principal component analysis is also described in Draghici, 2003, Data Analysis Tools for DNA Microarrays, Chapman & Hall/CRC, which is hereby incorporated by reference herein in its entirety. What follows is non-limiting examples of principal components analysis.
Principal components (PCs) are uncorrelated and are ordered such that the kth PC has the kth largest variance among PCs. The kth PC can be interpreted as the direction that maximizes the variation of the projections of the data points such that it is orthogonal to the first k−1 PCs. The first few PCs capture most of the variation in the data set. In contrast, the last few PCs are often assumed to capture only the residual ‘noise’ in the data.
In one approach to using PCA to learn a classifier, vectors representing landmark odorant activity profiles can be constructed in the same manner described for clustering above. In fact, the set of vectors, where each vector represents a landmark odorant activity profile, can be viewed as a matrix. In some embodiments, this matrix is represented in a Free-Wilson method of qualitative binary description of monomers (Kubinyi, 1990, 3D QSAR in drug design theory methods and applications, Pergamon Press, Oxford, pp 589-638, hereby incorporated by reference herein), and distributed in a maximally compressed space using PCA so that the first principal component (PC) captures the largest amount of variance information possible, the second principal component (PC) captures the second largest amount of all variance information, and so forth until all variance information in the matrix has been considered.
Then, each of the vectors, where each vector represents a member of the training population (such as the landmark odorant activity profiles), is plotted. Many different types of plots are possible. In some embodiments, a one-dimensional plot is made. In this one-dimensional plot, the value for the first principal component from each of the members of the training population is plotted. In this form of plot, the expectation is that odorant activity profiles corresponding to an odor will cluster in one range of first principal component values and profiles corresponding to another odor will cluster in a second range of first principal component values.
In some embodiments, the members of the training population are plotted against more than one principal component. For example, in some embodiments, the members of the training population are plotted on a two-dimensional plot in which the first dimension is the first principal component and the second dimension is the second principal component.
Nearest neighbor analysis. In some embodiments, a classifier is learned using nearest neighbor analysis. Nearest neighbor classifiers are memory-based and require no classifier to be fit. Given a query point x0, the k training points x(r), r, . . . , k closest in distance to x0 are identified and then the point x0 is classified using the k nearest neighbors. Ties can be broken at random. In some embodiments, Euclidean distance in feature space is used to determine distance as:
d
(i)
=∥x
(i)
−x
0∥.
Typically, when the nearest neighbor algorithm is used, the abundance data from Y used to compute the linear discriminant is standardized to have mean zero and variance 1. In the present invention, the members of the training population are randomly divided into a training set and a test set. For example, in one embodiment, two thirds of the members of the training population are placed in the training set and one third of the members of the training population are placed in the test set. A select combination of vector components i represents the feature space into which members of the test set are plotted. Next, the ability of the training set to correctly characterize the members of the test set is computed. In some embodiments, nearest neighbor computation is performed several times for a given combination of vector components i. In each iteration of the computation, the members of the training population are randomly assigned to the training set and the test set.
The nearest neighbor rule can be refined to deal with issues of unequal class priors, differential misclassification costs, and feature selection. Many of these refinements involve some form of weighted voting for the neighbors. For more information on nearest neighbor analysis, see, e.g., Duda, Pattern Classification, Second Edition, 2001, John Wiley & Sons, Inc; and Hastie, 2001, The Elements of Statistical Learning, Springer, New York, each of which is hereby incorporated by reference herein in its entirety.
Linear discriminant analysis. In some embodiments, a classifier is learned using linear discriminant analysis. Linear discriminant analysis (LDA) attempts to classify a subject into one of two categories based on certain object properties. In other words, LDA tests whether object attributes measured in an experiment predict categorization of the objects. LDA typically requires continuous independent variables and a dichotomous categorical dependent variable. In the present invention, the abundance values for the select combinations of vector components i across a subset of the training population serve as the requisite continuous independent variables. The trait subgroup classification (e.g., an odor) of each of the members of the training population serves as the dichotomous categorical dependent variable.
LDA seeks the linear combination of variables that maximizes the ratio of between-group variance and within-group variance by using the grouping information. Implicitly, the linear weights used by LDA depend on how the measured amount of a vector component i across the training set separates in the groups of the odor. In some embodiments, LDA is applied to the data matrix of the members in the training population. Then, the linear discriminant of each member of the training population is plotted. Ideally, those members of the training population representing an odor will cluster into one range of linear discriminant values (for example, negative) and those members of the training population representing another odor will cluster into a second range of linear discriminant values (for example, positive). The LDA is considered more successful when the separation between the clusters of discriminant values is larger. For more information on linear discriminant analysis, see, e.g., Duda, Pattern Classification, Second Edition, 2001, John Wiley & Sons, Inc; and Hastie, 2001, The Elements of Statistical Learning, Springer, New York; and Venables & Ripley, 1997, Modern Applied Statistics with s-plus, Springer, New York, each of which is hereby incorporated by reference herein in its entirety.
Quadratic discriminant analysis. In some embodiments, a classifier is learned using quadratic discriminant analysis. Quadratic discriminant analysis (QDA) takes the same input parameters and returns the same results as LDA. QDA uses quadratic equations, rather than linear equations, to produce results. LDA and QDA are interchangeable, and which to use is a matter of preference and/or availability of software to support the analysis. Logistic regression takes the same input parameters and returns the same results as LDA and QDA.
Support vector machine. In some embodiments, a classifier is learned using a support vector machine. SVMs are described, for example, in Cristianini and Shawe-Taylor, 2000, An Introduction to Support Vector Machines, Cambridge University Press, Cambridge; Boser et al., 1992, “A training algorithm for optimal margin classifiers,” in Proceedings of the 5th Annual ACM Workshop on Computational Learning Theory, ACM Press, Pittsburgh, Pa., pp. 142-152; Vapnik, 1998, Statistical Learning Theory, Wiley, New York; Mount, 2001, Bioinformatics: sequence and genome analysis, Cold Spring Harbor Laboratory Press, Cold Spring Harbor, N.Y., Duda, Pattern Classification, Second Edition, 2001, John Wiley & Sons, Inc.; and Hastie, 2001, The Elements of Statistical Learning, Springer, New York; and Furey et al., 2000, Bioinformatics 16, 906-914, each of which is hereby incorporated by reference herein in its entirety. When used for classification, SVMs separate a given set of binary labeled data training data with a hyper-plane that is maximally distant from them. For cases in which no linear separation is possible, SVMs can work in combination with the technique of ‘kernels’, which automatically realizes a non-linear mapping to a feature space. The hyper-plane found by the SVM in feature space corresponds to a non-linear decision boundary in the input space. For more information on support vector machines see, for example, Furey et al., 2000, Bioinformatics 16, page 906-914, which is hereby incorporated by reference herein.
Decision tree. In one embodiment, a classifier is a decision tree. Decision trees are described generally in Duda, 2001, Pattern Classification, John Wiley & Sons, Inc., New York, pp. 395-396, which is hereby incorporated herein by reference. One specific algorithm that can be used is a classification and regression tree (CART). Other specific algorithms include, but are not limited to, ID3, C4.5, MART, and Random Forests. CART, ID3, and C4.5, each described in Duda, 2001, Pattern Classification, John Wiley & Sons, Inc., New York, pp. 396-408 and pp. 411-412, which is hereby incorporated by reference herein in its entirety. CART, MART, and C4.5 are also described in Hastie et al., 2001, The Elements of Statistical Learning, Springer-Verlag, New York, Chapter 9, which is hereby incorporated by reference herein in its entirety. The Random Forests technique is described in Breiman, 1999, “Random Forests—Random Features,” Technical Report 567, Statistics Department, University of California at Berkeley, September 1999, which is hereby incorporated by reference herein in its entirety.
In addition to univariate decision trees in which each split is based on measured amounts for a corresponding vector component i, or the relative measured amounts of vector components i, the classifier can be a multivariate decision tree. In such a multivariate decision tree, some or all of the decisions actually comprise a linear combination of measured amounts for a plurality of vector components i. Multivariate decision trees are described in Duda, 2001, Pattern Classification, John Wiley & Sons, Inc., New York, pp. 408-409, which is hereby incorporated by reference herein in its entirety.
Multivariate adaptive regression splines. Another approach that can be used to learn a pairwise probability function gpq(X, Wpq) uses multivariate adaptive regression splines (MARS). MARS is an adaptive procedure for regression, and is well suited for the high-dimensional problems addressed by the present invention. MARS can be viewed as a generalization of stepwise linear regression or a modification of the CART method to improve the performance of CART in the regression setting. MARS is described in Hastie et al., 2001, The Elements of Statistical Learning, Springer-Verlag, New York, pp. 283-295, which is hereby incorporated by reference herein in its entirety.
Centroid classifier techniques. In one embodiment a nearest centroid classifier technique is used. Such a technique computes, for the different odors, a centroid given by the average measured amounts of vector components i in the training population (landmark odorant activity profiles), and then assigns vector representing the compound of interest to the class whose centroid is nearest. This approach is similar to k-means clustering except clusters are replaced by known classes. An example implementation of this approach is the Prediction Analysis of Microarray, or PAM. See, for example, Tibshirani et al., 2002, Proceedings of the National Academy of Science USA 99; 6567-6572, which is hereby incorporated by reference herein in its entirety.
Regression. In some embodiments, the classifier is a regression classifier, such as a logistic regression classifier. Such a regression classifier includes a coefficient for each of the odorant activity profiles used to construct the classifier. In such embodiments, the coefficients for the regression classifier are computed using, for example, a maximum likelihood approach. In such a computation, the measured amounts of vector components i are used.
Other methods. In some embodiments, the classifier is learned using k-nearest neighbors (k-NN), an artificial neural network (ANN), a parametric linear equation, a parametric quadratic equation, a naive Bayes analysis, linear discriminant analysis, a decision tree, or a radial basis function.
Some embodiments of the present invention provide a computer program product that contains any or all of the program modules shown in
In some embodiments, the invention provides cells or cell lines, or panels of cells or cell lines that express a biologic, e.g., a secreted protein. Secreted proteins may include antibodies and active fragments thereof, e.g., antibodies comprising heavy and light chains, single chain antibodies, proteins having an activity in the immune system, IgA, IgD, IgE, IgG and IgM proteins or active fragments thereof, enzymes, coagulation factors or hormones or a protein corresponding to a fragment of any of these. Biologics may also include FDA-approved biologics drugs, known biologics, proteins that are therapeutically active or therapeutic biologics. Examples of biologics and their brand names, include, but are not limited to: Canakinumab (Ilaris), Abobotulinumtoxin A (Dysport), Golimumab (Simponi), Romiplostim (NPLATE), Certolizumab Pegol (Cimzia), Rilonacept (Arcalyst), methoxy polyethylene glycol-epoetin beta (Mircera), eculizumab (Soliris), panitumumab (Vectibix), idursulfase (Elaprase), ranibizumab (Lucentis), alglucosidase alfa (Myozyme), Abatacept (Orencia), Galsulfase (Naglazyme), Palifermin (Kepivance), Natalizumab (Tysabri), Bevacizumab (Avastin), Cetuximab (Erbitux), nofetumomab (Verluma), capromab pendetide (ProstaScint), epoietin alfa (Procrit, Epogen), technetium fanolesomab (NeutroSpec), arcitumomab (CEA-Scan), darbepoetin alfa (Aranesp), urokinase (Abbokinase), Ibritumomab tiuxetan (Zevalin), Rituximab (Rituxan), Aldesleukin (Proleukin), Denileukin diffitox (Ontak), Pegaspargase (Oncaspar), Filgrastim (Neupoen), Oprelvekin (Neumega), Pegfilgrastim (Nuelasta), Sargramostim, (Leukine), Palifermin (Kepivance), trastuzumab (Herceptin), Cetuximab (Eribitux), Asparginase (Elspar) Rasburicase (Elitek), Alemtuzumab (Campath), Tositumomab (Bexxar), Palivizumab (Synagis), Interferon alfa-2a (Roferon-A), Peginterferon alfa-2b (Peg-Intron), Peginterferon alfa-2a (Pegasys), interferon alfa-2b (Intron A), interferon alfacon-1 (Infergen), peginterferon alpha-2 (Copasys Copegus), Daclizumab (Zenapax), Basiliximab (Simulect), Moromonab-CD3 (Orthocolone, OKT3), interferon gamma-1b (Actimmune), Drotrecogin alfa-activated (Xigris), Collagenase (Santyl), Becaplermin (Regranex), Efalizumab (Raptiva), Alefacept (Amevive), Interferon alfa-n3 (Alferon N), Galsulfase (Naglazyme), Agalsidase beta (Fabrazyme), Laronidase (Aldurazyme), Infliximab (Remicade), Abatacept (Orencia), Anakinra (Kineret), Adalimumab (Humira), Enteracept (Enbrel), Omalzumab (Xolair), Dornase alpha (Pulmozyme), Natalizumab (Tysabri), Interferon beta-1-a (Rebif), Botulinum Toxin Type B (Myobloc), Botulinum Toxin Type A (Botox), interferon beta-1-b (Betaseron), interferon beta-1-a (Avonex), Tenecteplase (TNKase), Streptokinase (Streptase), Reeplase (Retavase), Abciximab (ReoPro), Alteplase (Cathflo Activase, Activase), epo alpha (Abseamed, Binocrit), indunorate-2-sulfatase (Elaprase), Insulin (Exubera), HPV vaccine (Gardasil), pegaptanib (Macugen), human acid-a-glucosidase (Myozyme), galsulfase (Naglazyme), human growth hormone (Omnitrope), Parathyroid hormone (Preotach), human growth hormone (Valtropin), antithrombin (Atryn), Major capsid L1 proteins from HPV (Cervarix), erythropoietin alfa (Epotein alfa hexyl), mecasermin human IGF-1 (Increlex), methoxy polyethylene glycol-epoitein beta (Mlrcera), follitropin alpha/lutrophin alpha Pergoveris, epoietin zeta (Retacrit, Silapo), Ribavirin and interferon alfa-2b (Rebetron Combination Therapy), alglucerase (Ceredase), imiglucerase (Cerezyme), human insulin (Humulin, Novolin), somatropin (Humatrope, Nutropin/Nutropin AQ), Sermorelin (Geref), somatrem (Protopin), human albumin (Albutein), and gemtuzumab (Mylotarg).
Cells and cell lines with properties optimal for expression of a secreted protein may be selected using known tests to characterize clones with respect to any of properties, including, but not limited to: post-translational processing or modification, yield, percent active product, stability of certain properties (e.g., by testing the properties as described herein but over time), and stoichiometry (e.g., by RT-PCR or protein analysis).
The post-translational processing or modification of a secreted protein may be characterized by tests known in the art including, but not limited to, protein sequencing, mass spectroscopy, methods to test for glycosylation or phosphorylation, or a covalent addition of a chemical group or residue to select cell lines and conditions that result in a specific or desired form of the secreted protein product. Cells and cell lines may be designed to or selected to express one or more factors that effect the post-translational processing or modification of the secreted product, for instance by introducing sequences corresponding to enzymes that catalyze the post-translational processing or modification or by testing cell lines to select for those endogenously expressing these or gene-activated to express these.
Cells and cell lines with maximal production or yield of the secreted product may be produced by testing isolated clones using methods to assess secreted protein product levels, for instance using ELISA methods (e.g., ELISA that detect FC fragment to assess antibody yield).
Cells and cell lines that result in maximal percent active secreted protein compared to total yield of secreted product may be produced by testing isolated clones using methods to assess the activity or binding of the protein, for instance by using activity assays, functional assays, or binding assays such as functional cell based assays, ELISAs utilizing capture reagents that comprise the binding epitope, secondary tests, animal studies or a test that is used to measure the binding or activity of the protein.
Cell lines that additionally are optimized for growth in animal component free media conditions and/or in suspension conditions as used in reactors for scaled-up production can be produced either by operating the methods used for cell line production under these and/or similar conditions or by testing clones under these desired conditions to identify those cell lines having the desired properties. In some embodiments, cell lines that are additionally optimized for growth in media supplemented with compounds that normally retard or impede cell growth can be produced by selecting for cells that exhibit normal or improved growth under these conditions compared to most cells of the same cell type.
In some embodiments, cells or cell lines that express a protein of interest according to the present invention may be used to produce the protein of interest. Encompassed herein are methods of protein production using cells that possess certain physiological properties favorable for protein production and/or have been engineered to express one or more protein expression accessory factors. In certain embodiments, cells that express a protein of interest consistently and reproducibly as described herein (e.g., for a period of time selected from: at least one week, at least two weeks, at least three weeks, at least one month, at least two months, at least three months at least four months, at least five months, at least six months, at least seven months, at least eight months, and at least nine months) are further modified and/or selected to provide an improved environment for protein production. In certain embodiments, a cell that is engineered to express a protein of interest and a protein expression accessory factor can be used for production of the protein of interest. In certain, more specific embodiments, the protein of interest and/or the protein expression accessory factor is expressed consistently and reproducibly.
In certain embodiments, the protein of interest is a biologic, e.g., an antibody for therapeutic use. Any protein of interest or fragment thereof can be produced in accordance with the methods described herein including, but not limited to, membrane proteins, transmembrane proteins, structural proteins, membrane-anchored proteins, cell surface receptors, secreted proteins, cytosolic proteins, heteromultimeric proteins, homomultimeric proteins, dimeric proteins, monomeric proteins, post-translationally modified proteins, glycosylated proteins, phosphorylated proteins, and proteolytically processed proteins. Specific examples of such proteins include, but are not limited to, antibodies (including antibody fragments such as Fab and Fab, Fab′, F(ab′)2, Fd, Fv, dAb and the like, single chain antibodies (scFv), single domain antibodies, heavy chain, light chain, and all antibody classes, i.e., IgA, IgD, IgE, IgG and IgM), enzymes, coagulation factors, hormones, cytokines, ion channels, G-protein coupled receptors (GPCRs), and transporters. Other exemplary biologics include those disclosed hereinabove.
In certain embodiments, cells that are favorable for protein production produce at least 1%, 2%, 5%, 10%, 15%, 20%, 25%, 30%, 40%, 50%, 60%, 70%, 80%, 90%, 100%, 250%, 500%, or at least 1000% more protein of interest than a reference cell. In certain embodiments, cells that are favorable for protein production produce a protein of interest that has at least 1%, 2%, 5%, 10%, 15%, 20%, 25%, 30%, 40%, 50%, 60%, 70%, 80%, 90%, 100%, 250%, 500%, or at least 1000% more activity than the same protein of interest expressed in a reference cell. Activity may refer, e.g., to enzymatic activity or binding activity or therapeutic activity to a binding partner of the protein of interest. In certain embodiments, cells that are favorable for protein production produce protein of interest wherein at least 1%, 2%, 5%, 10%, 15%, 20%, 25%, 30%, 40%, 50%, 60%, 70%, 80%, 90%, 100%, 250%, 500%, or at least 1000% more protein of interest is secreted relative to a reference cell. In certain embodiments, at least 50%, 60%, 70%, 80%, 90%, 95%, 98%, or at least 99% of the protein of interest are localized in the subcellular compartment in which the protein of interest is located in a cell that expresses the protein of interest without genetic engineering. Parameters to assess protein expression in a cell include quantification/analysis of protein yield, processing, modification, localization within cell or secretion, percent total protein that is optimally folded/processed. A reference cell may be the host cell from which the cell that expresses the protein of interest was generated. Any cell disclosed herein may be used as a reference cell.
Proteins produced in accordance with the methods provided herein may be characterized using methods known in the art, including protein sequencing, mass spectroscopy, immunocytochemistry, methods to analyze the extent or type of glycosylation and/or phosphorylation, as well as methods for determining the covalent addition of chemical groups and/or residues to the protein produced.
Cells that yield the greatest overall amount of protein can be identified using methods known in the art, such as ELISA. Moreover, cells that result in the maximal percentage of active protein compared to total yield of protein can be identified using assays that detect the activity of the protein or the binding of the protein, such as activity assays, functional assays, binding assays (e.g., ELISA), secondary tests, animal studies, or cell based assays.
In certain embodiments, protein expression in a cell that expresses a protein of interest is tested using a test protein, wherein if the test protein is expressed at levels higher than in a reference cell then the protein of interest in the same cell is predicted to be expressed at higher levels compared to the reference cell. Test proteins could include any protein, membrane proteins, transmembrane proteins, membrane anchored proteins, cell surface receptors, secreted proteins, cytosolic proteins, heteromultimeric proteins, homomultimeric proteins, dimeric proteins, monomeric proteins, proteins that are post translationally modified, proteins that are glycosylated/phosphorylated/proteolytically processed, and any possible combination of the above. In certain embodiments, specific test proteins could include antibodies, ion channels, GPCRs, transporters. Cells may be tested with just one or multiple test proteins. In the case of multiple test proteins, they may be of one or multiple types (e.g. multiple GPCRs only, or GPCRs, ion channels and antibodies).
Cells that possess physiological properties that are favorable for the production of proteins (e.g., cells with increased endoplasmic reticulum mass) as well as cells that have been engineered to be optimized for the production of proteins (e.g., by introduction of genes that encode proteins beneficial for protein production) can be identified using methods known in the art, the methods described herein, or a combination thereof. Once such cells are identified, the cells can be cultured and cell lines that stably express one or more genes that encode proteins beneficial for protein production can be generated in accordance with the methods described herein. Such cell lines can be engineered to express a protein of interest by introduction of a transgene or by gene activation either before or after selection of the cells that are favorable for protein production. Cells that produce the protein of interest then can be identified using methods known in the art and/or the methods described herein.
Cells that possess physiological properties that are favorable for the production of proteins include, but are not limited to, cells with improved viability; increased cell size; increased production of endogenously expressed proteins; increased mitochondrial activity; improved stability; the ability to maintain the properties for which they were selected; increased size of one or more organelles involved in protein processing (e.g., the endoplasmic reticulum and ribosomes); and increased content of one or more organelles involved in protein processing (e.g., lysosomes and endosomes). These physiological properties can be compared relative to a reference cell or historical values for a reference cell.
Cells that possess physiological properties that are favorable for the production of proteins can be identified using FACS analysis in combination with standard approaches for fluorescently labeled probes. In particular, markers for certain physiological properties are used to quantify physiological properties that relate to protein expression and compare them to a reference cell. Such markers include molecules that detect cellular structures that are related to protein expression such as ribosomes, mitochondria, ER, rER, golgi, TGN, vesicles, endosomes, and plasma membrane. Such markers can be fluorescent stains. For example, the activity of certain cellular organelles, e.g., mitochondrial activity, could be assessed by assaying for fluorescent metabolites. Fluorescent metabolites that report the activity of the organelles/compartments (e.g. mitochondrial activity, or incorporation of sugars onto proteins (which e.g. can be detected using fluorescent lectins) can be used. Proteins markers specific to one or more cellular organelles involved in protein processing could be expressed as fusion proteins with auto-fluorescing protein tags, e.g., green fluorescent protein (GFP); and membrane proteins and/or secreted proteins could be labeled with fluorescent probes. Probes (e.g. antibodies) to endogenously expressed proteins may be used as markers for the output of cellular organelles/compartments. Specifically, heteromultimeric membrane proteins could be used as read-out of protein expression activity in a cell.
Without being bound by theory, an increase in fluorescence as measured by FACS would suggest that the cell possesses qualities favorable for the production of proteins, and such cells could be isolated for future use. In addition to these standard techniques, the methods described herein could be used to identify cells that naturally possess physiological properties that are favorable for the production of proteins. For example, signaling probes complementary to target sequences of endoplasmic reticulum markers (e.g., ERp29, cytochrome P450, NADPH-cytochrome c reductase, Calreticulin) could be used in accordance with the methods described herein to identify cells with increased endoplasmic reticulum size. Cells that demonstrate a high degree of fluorescence, as measured by FACS, would likely have increased ER size and/or content, and thus would possess qualities favorable for the production of proteins.
In one embodiment, cells that possess physiological properties that are favorable for the production of proteins are identified and subsequently used to develop stable cell lines which are used to produce a protein(s) of interest. In another embodiment, cells are engineered to express a protein of interest followed by the identification of cells that express the protein of interest. Cells that express the protein of interest and additionally possess physiological properties that are favorable for the production of proteins then are identified. Such cells then are used to develop stable cell lines which produce the protein(s) of interest.
In an illustrative embodiment, a cell is transfected with a nucleic acid encoding the protein of interest; a fluorogenic oligonucleotide capable of detecting the transcript of the nucleic acid is introduced into the cell; a fluorogenic probe for a marker of a physiological property related to protein expression is introduced into the cell; selection of a cell that expresses the protein of interest and has increased levels of the physiological property related to protein expression. A cell line that expresses the protein of interest consistently and reproducibly can then be established.
The cells used in the methods of protein production provided herein may be engineered to express a protein expression accessory factor or a combination of two or more protein expression accessory factors. In certain embodiments, the cells are engineered to express a splice variant, mutant, or fragment of a protein expression accessory factor. In certain embodiments, a cell is engineered to express at least 2, 5, 10, 15, 20, 25, 30, 40, 50, 75, 100, or 150 protein expression accessory factors. Illustrative protein expression accessory factors include: proteins that regulate the unfolded protein response (UPR) and genes that encode proteins that are regulated in the UPR (e.g., ATF6a (spliced), IRE1α, IRE1β, PERCΔC, ATF4, YYI, NF-YA, NF-YB, NF-YC, XBP1 (spliced), EDEM1); genes that encode proteins that switch-off the apoptotic pathway induced by the UPR (e.g., NRF2, HERP XIAP, GADD34, PPIα, PPIβ, PPIγ, DNAJC3); genes that encode proteins that affect the growth of cells, the viability of cells, cell death, and cell size; B-cell genes (e.g., BLIMP-1, XBP1 (spliced)); genes that encode proteins involved in protein transport (e.g., Sec61Pα, Sec61Pβ, Sec61Pγ); genes that encode proteins involved in glycosylation (e.g., SDF2-L); genes that encode proteins involved in oxidation (e.g., ERO1α, ERO1β); genes that encode anti-apoptotic proteins (e.g., Bcl-2sp, Bcl-xL, Bim trunk. Mut., Ku70, 14-3-3q mut., VDAC2, BAP31 mut.); genes that encode proteins implicated in endoplasmic reticulum-associated degradation (e.g., mannosidase 1, HRD1); genes that encode proteins involved in calcium transport (e.g., STC1, STC2, SERCA1, SERCA2, COD1); genes that encode proteins implicated in lipogenesis/metabolism (e.g., INO1, PYC, SREBP1ΔC, SREBP2ΔC); and genes that encode proteins implicated in protein folding and secretion (e.g., CRT (CaBP3), CNX, ERp57 (PDIA3), BiP, BAP, ERdj3, CaBP1, GRP94 (CaBP4), ERp72 (PDIA4), cyclophilin B), protein assembly, the integration of proteins into membranes, cell surface presentation of proteins, and post-translational modification of proteins. In a specific embodiment, the cells are engineered to express any one or a combination of genes implicated in the UPR. In another specific embodiment, the cells are engineered to express any one or a combination of genes implicated in the UPR as well as at least one other gene that encodes a protein known to be beneficial for protein production. Genes that regulate UPR or are regulated in UPR; genes that alter cell growth, viability, apoptosis, cell death, cell size; genes encoding chaperones or factors implicated in protein folding, assembly, membrane integration, cell surface presentation or secretion, post-translational modification including glycosylation/phosphorylation/proteolysis can be used. In certain embodiments, a protein expression accessory factor alters a cell physiological property.
Identification of cells that express one or a combination of genes that encode proteins known to be beneficial for protein production can be accomplished using the methods described herein, e.g., signaling probes that bind to target sequences in the genes/mRNA of interest could be generated and the presence of the gene/mRNA of interest then could be verified by FACS analysis.
In an illustrative embodiment, a cell is transfected with a first nucleic acid encoding the protein of interest and a second nucleic acid encoding a protein expression accessory factor; a fluorogenic oligonucleotide capable of detecting the transcript of the first nucleic acid and a fluorogenic oligonucleotide capable of detecting the transcript of the second nucleic acid are introduced into the cell; selection of a cell that expresses the protein of interest and the protein expression accessory factor. A cell line that expresses the protein of interest consistently and reproducibly can then be established. The cell line can be further tested for physiological properties related to protein expression as discussed above.
In one embodiment, cells are first engineered to express a protein expression accessory factor; cell lines expressing the protein expression accessory factor are established, cells of the cell line are then engineered to express a protein of interest. In another embodiment, cells are first engineered to express a protein of interest; cell lines expressing the protein of interest are established, cells of the cell line are then engineered to express a protein expression accessory factor. In even another embodiment, cells are concurrently engineered to express a protein of interest and a protein expression accessory factor. Cell lines that express the protein of interest and/or the protein expression accessory factor consistently and reproducibly can then be established as described herein.
In certain embodiments, a plurality of cells that have been engineered to express a protein of interest are provided. These cells are then engineered to express a protein expression accessory factor and/or a cell most favorable to protein expression is selected from the plurality by using a marker for a physiological property related to protein expression as discussed above.
In certain embodiments, the cell lines can be optimized for growth in animal component-free media and/or in suspension conditions as used in reactors for scaled-up production in accordance with the methods provided herein. In certain more specific embodiments, the cell lines can be optimized for growth in media that comprises a component that slows growth.
In further illustrative embodiments, a method for protein production is provided that comprises (i) identifying cells that possess physiological properties that are favorable for the production of proteins; (ii) engineering the cells to express a protein of interest; (iii) generating a cell line that stably expresses the protein of interest; (iv) culturing the cells under conditions suitable for production of the protein of interest; and (v) isolation of the protein of interest.
In another embodiment, a method for protein production is provided that comprises (i) introducing to cells at least one gene that encodes a protein expression accessory factor; (ii) identifying cells that express the protein expression accessory factor; (iii) engineering the cells to express a protein of interest; (iv) generating a cell line that stably expresses the protein of interest; (v) culturing the cells under conditions suitable for production of the protein of interest; and (vi) isolation of the protein of interest.
In another embodiment, a method for protein production is provided that comprises (i) introducing to cells at least one gene that encodes a protein expression accessory factor; (ii) identifying cells that express the protein expression accessory factor; (iii) identifying cells that possess physiological properties that are favorable for the production of proteins; (iv) engineering the cells to express a protein of interest; (v) generating a cell line that stably expresses the protein of interest; (vi) culturing the cells under conditions suitable for production of the protein of interest; and (vii) isolation of the protein of interest. In one aspect of this embodiment, steps (ii) and (iii) are performed sequentially. In another aspect, steps (ii) and (iii) are performed concurrently.
In another embodiment, a method for protein production is provided that comprises (i) introducing to cells at least one gene that encodes a protein expression accessory factor and engineering the cells to express a protein of interest; (ii) identifying cells that express the protein expression accessory factor and the protein of interest; (iii) generating a cell line that stably expresses the protein expression accessory factor and the protein of interest; (iv) culturing the cells under conditions suitable for production of the protein of interest; and (v) isolation of the protein of interest.
In another embodiment, a method for protein production is provided that comprises (i) introducing to cells at least one gene that encodes a protein expression accessory factor and engineering the cells to express a protein of interest; (ii) identifying cells that express the protein expression accessory factor and the protein of interest; (iii) identifying cells that possess physiological properties that are favorable for the production of proteins; (iv) generating a cell line that expresses the protein expression accessory factor and the protein of interest consistently and reproducibly; (v) culturing the cells under conditions suitable for production of the protein of interest; and (vi) isolation of the protein of interest. In one aspect of this embodiment, steps (ii) and (iii) are performed sequentially. In another aspect, steps (ii) and (iii) are performed concurrently.
Host cells that can be used to generate cells suitable for protein production include primary cells and immortalized cells. In specific embodiments, a host cells can be, e.g., CHO cells, NS0 cells, PerC6 cells, yeast cells, insect cells, 293 cells, CACO cells, HUVEC, CHOK1, CHOKiSV, NS0, 293T cells, and insect cells.
In some embodiments, cells or cell lines that produce or are capable of producing 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1.0, 1 to 1.5, 1.5 to 2.0, 2.0 to 2.5, 2.5 to 3.0, 3.0 to 3.5, 3.5 to 4.0, 4.0 to 4.5, 4.5 to 5.0, 5.0 to 5.5, 5.5 to 6.0, 6.5 to 7.0, 7.0 to 7.5, 7.5 to 8.0, 8.0 to 8.5, 8.5 to 9.0, 9.0 to 9.5, 9.5 to 10.0, 10 to 11, 11 to 12, 12 to 13, 13 to 14, 14 to 15, 15 to 16, 16 to 17, 17 to 18, 18 to 19, 19 to 20, 20 to 25 or more than 25 grams per liter of a protein of interest are produced in less than 1, 2, 3, or 5 weeks. In some embodiments, cells or cell lines that produce or are capable of producing 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1.0, 1 to 1.5, 1.5 to 2.0, 2.0 to 2.5, 2.5 to 3.0, 3.0 to 3.5, 3.5 to 4.0, 4.0 to 4.5, 4.5 to 5.0, 5.0 to 5.5, 5.5 to 6.0, 6.5 to 7.0, 7.0 to 7.5, 7.5 to 8.0, 8.0 to 8.5, 8.5 to 9.0, 9.0 to 9.5, 9.5 to 10.0, 10 to 11, 11 to 12, 12 to 13, 13 to 14, 14 to 15, 15 to 16, 16 to 17, 17 to 18, 18 to 19, 19 to 20, 20 to 25 or more than 25 grams per liter of a protein of interest are produced in less than 1, 2, 3, 4, 5, 6, 7, 8 or 9 months. In some embodiments, the cells are stable over 1, 2, 3, 4, 5, 6, 7, 8, 9, 10 months wherein the level of protein produce does not vary by more than 30%. In some embodiments, the cells are stable over 1 year, 2 years or more in continuous culture wherein the level of protein produce does not vary by more than 30%. In some embodiments, the protein of interest is a biologic or a protein that can be used in clinical applications. In some embodiments, the protein of interest is an antibody. In some embodiments, the protein of interest is modified, post-translationally modified or glycosylated. In some embodiments, the protein produced by the cell is modified, post-translationally modified or glycosylated by a second protein that the cells are engineered to comprise.
In some embodiments, the invention provides methods to produce equivalent biologic products that match the properties of existing biologic products (e.g., bio-equivalent or biosimilar biologics) in a short period of time.
A matched panel of the invention may be produced by generating the different cell lines for the panel sequentially, in parallel or a combination of both. For example, one can make each cell line individually and then match them. More preferably, to minimize difference between the cell lines, sequentially generated cell lines can be frozen at the same stage or passage number and thawed in parallel. Even more preferably, the cell lines are made in parallel. In some embodiments, matched panels can be made by producing each cell line of the panel using conditions, protocols or cell culture steps that are substantially the same.
In preferred embodiments, the cell lines in a panel are screened or assayed in parallel.
According to the invention, the cell lines of the matched panel are maintained under the same cell culture conditions including but not limited to the same culture media, temperature, and the like. All of the cell lines in the panel are passaged at the same frequency which may be any desired frequency depending on a number of factors including cell type and growth rate. As will be appreciated, to maintain roughly equal numbers of cells from cell line to cell line of the panel, the number of cells should be normalized periodically.
According to the method, cells may be cultured in any cell culture format so long as the cells or cell lines are dispersed in individual cultures prior to the step of measuring growth rates. For example, for convenience, cells may be initially pooled for culture under the desired conditions and then individual cells separated one cell per well or vessel.
Cells may be cultured in multi-well tissue culture plates with any convenient number of wells. Such plates are readily commercially available and will be well known to a person of skill in the art. In some cases, cells may preferably be cultured in vials or in any other convenient format, the various formats will be known to the skilled worker and are readily commercially available.
In embodiments comprising the step of measuring growth rate, prior to measuring growth rates, the cells are cultured for a sufficient length of time for them to acclimate to the culture conditions. As will be appreciated by the skilled worker, the length of time will vary depending on a number of factors such as the cell type, the chosen conditions, the culture format and may be any amount of time from one day to a few days, a week or more.
Preferably, each individual culture in the plurality of separate cell cultures is maintained under substantially identical conditions a discussed below, including a standardized maintenance schedule. Another advantageous feature of the method is that large numbers of individual cultures can be maintained simultaneously, so that a cell with a desired set of traits may be identified even if extremely rare. For those and other reasons, according to the invention, the plurality of separate cell cultures are cultured using automated cell culture methods so that the conditions are substantially identical for each well. Automated cell culture prevents the unavoidable variability inherent to manual cell culture.
Any automated cell culture system may be used in the method of the invention. A number of automated systems are commercially available and will be well-known to the skilled worker. In some embodiments, these systems could be adapted for use to automate or standardize the culture of multiple separate cultures of cells or cell lines. In some embodiments, these systems could be adapted for use to automate or standardize the culture of multiple separate cultures of cells or cell lines under substantially identical conditions. In some embodiments, these systems could be adapted for use to automate or standardize the parallel culture of multiple separate cultures of cells or cell lines under substantially identical conditions. In some embodiments, these systems could be adapted for use to automate or standardize the culture of multiple separate cultures of cells or cell lines such that at least 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 35, 40, 45, 50 or more than 50 physiological properties of the cells are maintained during culture. In some embodiments, these systems could be adapted for use to automate or standardize the culture of multiple separate cultures of cells or cell lines such that the RNA or protein of interest is stably expressed by the cells or cell lines. In some embodiments, these systems could be adapted for use to automate or standardize the culture of multiple separate cultures of cells or cell lines such that at least 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 35, 40, 45, 50 or more than 50 physiological properties of the cells are maintained and such that the RNA or protein of interest is stably expressed by the cells or cell lines. In some embodiments, the automated system is a robotic system. Preferably, the system includes independently moving channels, a multichannel head (for instance a 96-tip head) and a gripper or cherry-picking arm and a HEPA filtration device to maintain sterility during the procedure. The number of channels in the pipettor should be suitable for the format of the culture. Convenient pipettors have, e.g., 96 or 384 channels. Such systems are known and are commercially available. For example, a MICROLAB STAR™ instrument (Hamilton) may be used in the method of the invention. The automated system should be able to perform a variety of desired cell culture tasks. Such tasks will be known by a person of skill in the art. They include but are not limited to: removing media, replacing media, adding reagents, cell washing, removing wash solution, adding a dispersing agent, removing cells from a culture vessel, adding cells to a culture vessel and the like.
The production of a cell or cell line of the invention may include any number of separate cell cultures. However, the advantages provided by the method increase as the number of cells increases. There is no theoretical upper limit to the number of cells or separate cell cultures that can be utilized in the method. According to the invention, the number of separate cell cultures can be two or more but more advantageously is at least 3, 4, 5, 6, 7, 8, 9, 10 or more separate cell cultures, for example, at least 12, at least 15, at least 20, at least 24, at least 25, at least 30, at least 35, at least 40, at least 45, at least 48, at least 50, at least 75, at least 96, at least 100, at least 200, at least 300, at least 384, at least 400, at least 500, at least 1000, at least 10,000, at least 100,000, at least 500,000 or more.
In some embodiments, the cells and cell lines of the invention that are cultured as described are cells at least two of which have previously been selected as positive for a nucleic acid of interest, which can be an introduced nucleic acid encoding all or part of a protein of interest or an introduced nucleic acid that activates transcription of a sequence encoding all or part of a protein of interest. In some embodiments, the cells that are cultured as described herein are cells at least two of which have been selected as positive for an RNA of interest or an RNA encoding the protein of interest.
To make cells and cell lines of the invention, one can use, for example, the technology described in U.S. Pat. No. 6,692,965 and WO/2005/079462. Both of these documents are incorporated herein by reference in their entirety. This technology provides real-time assessment of millions of cells such that any desired number of clones (from hundreds to thousands of clones). Using cell sorting techniques, such as flow cytometric cell sorting (e.g., with a FACS machine) or magnetic cell sorting (e.g., with a MACS machine), one cell per well is automatically deposited with high statistical confidence in a culture vessel (such as a 96 well culture plate). The speed and automation of the technology allows multigene recombinant cell lines to be readily isolated. In certain embodiments, cells positive for the desired signal (i.e., cells that express the desired RNA) are pooled. Such a pool can then be subjected to a second round of selection. In certain embodiments, the pool of cells is subjected to a total of at least 2, 3, 4, 5, 6, 7, 8, 9, 10, 15, 20, 25, or at least 50 rounds of selection.
Using the technology, the RNA sequence for a protein of interest may be detected using a signaling probe, also referred to as a molecular beacon or fluorogenic probe. In some embodiments, the vector containing the coding sequence has an additional sequence coding for an RNA tag sequence. “Tag sequence” refers to a nucleic acid sequence that is an expressed RNA or portion of an RNA that is to be detected by a signaling probe. Signaling probes may detect a variety of RNA sequences, any of which may be used as tags, including those encoding peptide and protein tags described above. Signaling probes may be directed against the tag by designing the probes to include a portion that is complementary to the sequence of the tag. The tag sequence may be a 3′ untranslated region of the plasmid that is cotranscribed with the transcript of the protein of interest and comprises a target sequence for signaling probe binding. The tag sequence can be in frame with the protein-coding portion of the message of the gene or out of frame with it, depending on whether one wishes to tag the protein produced. Thus, the tag sequence does not have to be translated for detection by the signaling probe. The tag sequences may comprise multiple target sequences that are the same or different, wherein one signaling probe hybridizes to each target sequence. The tag sequence may be located within the RNA encoding the gene of interest, or the tag sequence may be located within a 5′- or 3′-untranslated region. The tag sequences may be an RNA having secondary structure. The structure may be a three-arm junction structure. In some embodiments, the signaling probe detects a sequence within the coding sequence for the protein of interest. The tag sequence may contain chemically modified nucleotides. The tag sequences can be generated and used as described in International Patent Application Publication No. WO2005/079462 published on Sep. 1, 2005 (Application No. PCT/US05/005080).
Following transfection of the DNA constructs into cells and subsequent drug selection (if used), or following gene activation, molecular beacons (e.g., fluorogenic probes), each of which is targeted to a different tag sequence and differentially labeled, may be introduced into the cells, and a flow cytometric cell sorter is used to isolate cells positive for their signals (multiple rounds of sorting may be carried out). In one embodiment, the flow cytometric cell sorter is a FACS machine. MACS (magnetic cell sorting) or laser ablation of negative cells using laser-enabled analysis and processing can also be used. Other fluorescence plate readers, including those that are compatible with high-throughput screening can also be used. Signal-positive cells take up and may integrate into their genomes at least one copy of the introduced sequence(s). Cells introduced with message for the protein of interest are then identified. By way of example, the coding sequences may be integrated at different locations of the genome in the cell. The expression level of the introduced sequence may vary based upon copy number or integration site. Further, cells comprising a protein of interest may be obtained wherein one or more of the introduced nucleic acids is episomal or results from gene activation.
Signaling probes useful in this invention are known in the art and generally are oligonucleotides comprising a sequence complementary to a target sequence and a signal emitting system so arranged that no signal is emitted when the probe is not bound to the target sequence and a signal is emitted when the probe binds to the target sequence. By way of non-limiting illustration, the signaling probe may comprise a fluorophore and a quencher positioned in the probe so that the quencher and fluorophore are brought together in the unbound probe. Upon binding between the probe and the target sequence, the quencher and fluorophore separate, resulting in emission of signal. International publication WO/2005/079462, for example, describes a number of signaling probes that may be used in the production of the present cells and cell lines. The methods described above for introducing nucleic acids into cells may be used to introduce signaling probes.
Where tag sequences are used, each vector (where multiple vectors are used) can comprise the same or a different tag sequence. Whether the tag sequences are the same or different, the signaling probes may comprise different signal emitters, such as different colored fluorophores and the like so that expression of each subunit may be separately detected. By way of illustration, the signaling probe that specifically detects a first RNA (e.g., mRNA, siRNA or RNA oligonucleotide) of interest can comprise a red fluorophore, the probe that detects a second RNA (e.g., mRNA, siRNA or RNA oligonucleotide) of interest can comprise a green fluorophore, and the probe that detects a third RNA (e.g., mRNA, siRNA or RNA oligonucleotide) of interest can comprise a blue fluorophore. Those of skill in the art will be aware of other means for differentially detecting the expression of the three subunits with a signaling probe in a triply transfected cell.
In one embodiment, the signaling probes are designed to be complementary to either a portion of the RNA encoding the protein of interest or to portions of the 5′ or 3′ untranslated regions. Even if the signaling probe designed to recognize a messenger RNA of interest is able to detect spuriously endogenously expressed target sequences, the proportion of these in comparison to the proportion of the sequence of interest produced by transfected cells is such that the sorter is able to discriminate the two cell types.
The expression level of a protein of interest may vary from cell to cell or cell line to cell line. The expression level in a cell or cell line may also decrease over time due to epigenetic events such as DNA methylation and gene silencing and loss of transgene copies. These variations can be attributed to a variety of factors, for example, the copy number of the transgene taken up by the cell, the site of genomic integration of the transgene, and the integrity of the transgene following genomic integration. One may use FACS or other cell sorting methods (i.e., MACS) to evaluate expression levels. Additional rounds of introducing signaling probes may be used, for example, to determine if and to what extent the cells remain positive over time for any one or more of the RNAs for which they were originally isolated.
Optionally, one or more replicate sets of cultures for one or more of the growth rate groups may be prepared. In some cases, it may be advantageous to freeze a replicate set of one or more growth bins, for example, to serve as a frozen stock. However, according to the method, frozen cell stocks can be made as often as desired and at any point and at as many points during their production. Methods for freezing cell cultures are well-known to those of skill in the art. By way of example, the replicate set can be frozen at any temperature, for example, at −70° to −80° C. In one embodiment, cells were incubated until 70-100% confluency was reached. Next, media was aspirated and a solution of 90% FBS and 10% media was added to the plates, insulated and frozen.
The invention contemplates performing the method with any number of replicate sets using different culture conditions. That is, the method can be performed with a first plurality (set) of separate cell cultures under a first set of culture conditions and with a second set of separate cell cultures that are cultured under a second set of conditions that are different from the first conditions, and so on for any desired number of sets of conditions. The methods using different sets of conditions can be performed simultaneously or sequentially or a combination of both (such as two sets simultaneously followed by two more sets, and so on).
One advantage of the method described herein for selecting a cell with consistent functional expression of a protein of interest is that cells are selected by function, not by the presence of a particular nucleic acid in the cell. Cells that comprise a nucleic acid encoding a protein of interest may not express it, or even if the protein is produced, for many reasons the protein may not be functional or have altered function compared to “native” function, i.e., function in a cell in its normal context that naturally expresses the protein. By selecting cells based on function, the methods described herein make it possible to identify novel functional forms. For example, it is possible to identify multiple cells that have various degrees of function in the same assay, such as with the same test compound or with a series of compounds. The differential function provides a series of functional “profiles”. Such profiles are useful, for example, to identify compounds that differentially affect different functional forms of a protein. Such compounds are useful to identify the functional form of a protein in a particular tissue or disease state, and the like.
A further advantage of the method for making cells and cell lines of the invention including cells that express complex proteins or multiple proteins of interest is that the cells can be produced in significantly less time that by conventional methods. For example, depending on a number of factors including the number of cells required for the functional assay, whether growth rate binning is done and other factors, cells expressing a demonstrably functional protein may be produced in as little as 2 day, or a week but even production time of 2 weeks, 3 weeks, 1 month, 2 months, 3 months or even 6 months are significantly faster than was possible by conventional methods, even for complex or multiple proteins.
In another aspect, the invention provides methods of using the cells and cell lines of the invention. The cells and cell lines of the invention may be used in any application for which the functional protein of interest are needed. The cells and cell lines may be used, for example, in an in vitro cell-based assay or an in vivo assay where the cells are implanted in an animal (e.g., a non-human mammal) to, e.g., screen for modulators; produce protein for crystallography and binding studies; and investigate compound selectivity and dosing, receptor/compound binding kinetic and stability, and effects of receptor expression on cellular physiology (e.g., electrophysiology, protein trafficking, protein folding, and protein regulation). The cells and cell lines of the invention also can be used in knock down studies to examine the roles of the protein of interest.
Cells and cell lines of the invention also may be used to identify soluble biologic competitors, for functional assays, bio-panning (e.g., using phage display libraries), gene chip studies to assess resulting changes in gene expression, two-hybrid studies to identify protein-protein interactions, knock down of specific subunits in cell lines to assess its role, electrophysiology, study of protein trafficking, study of protein folding, study of protein regulation, production of antibodies to the protein, isolation of probes to the protein, isolation of fluorescent probes to the protein, study of the effect of the protein's expression on overall gene expression/processing, study of the effect of the protein's expression on overall protein expression and processing, and study of the effect of protein's expression on cellular structure, properties, characteristics.
The cells and cell lines of the invention further are useful to characterize the protein of interest (DNA, RNA or protein) including DNA, RNA or protein stoichiometry, protein folding, assembly, membrane integration or surface presentation, conformation, activity state, activation potential, response, function, and the cell based assay function, where the protein of interest comprises a multigene system, complex or pathway whether all components of these are provided by one or more target genes introduced into cells or by any combination of introduced and endogenously expressed sequences.
Cells and cell lines that have been engineered to express one or more subunits of a multimeric (dimeric, trimeric or higher orders of multimerization) protein can produce different forms of this multimeric protein. The present invention provides methods to distinguish cells with different forms of a multimeric protein. The functional form of a multimeric protein can vary depending on the physiological state of the cell, alternative splicing or post-translational modification of a target including proteolysis, its association with accessory or interacting factors or its folding, assembly or integration in cell membranes. Different subunit assemblies and stoichiometries further increase the number of possible functional forms for heteromultimeric targets. Functional forms can differ with respect to their responses to test compounds or the kinetics of their activity over time. Comparative analysis of cells expressing different functional forms of a multimeric protein allows cells comprising specific functional forms to be identified.
In some embodiments, a multimeric protein is a physical or biochemical association of at least two protein subunits. In some embodiments, a multimeric protein is a physical or biochemical association of one protein subunit and an accessory factor of the protein subunit. In some embodiments, a multimeric protein has at least 2, 3, 4, 5, 6, 7, 8, 9, or 10 subunits. The subunits can be the same polypeptide or different polypeptides or combinations thereof. The multimeric protein can be any multimeric protein disclosed herein.
Functional activities, or pharmacological profiles, as described herein, can be defined for cell lines expressing a target of interest by testing the effect of one or more compounds on the activity of the target in the cell line. Grouping or categorizing the clones according to these pharmacological profiles can be used to result in a panel of cell lines representing each possible form of the target. Representation of all possible functional forms may be pursued by saturating the screen, that is, by testing at least a number of cell lines such that each form as defined by its pharmacological profile is represented by at least 2, 3, 5, 10, 25, 50, or at least 100 cell lines.
In some embodiments, the effect of a compound on a target of interest is assayed at a particular point of the cell cycle (e.g., M, S, G1, or G2 phase). In other embodiments, the effect of a compound on a target of interest is monitored over time (e.g., over 1, 5, 10, 15, 20, 30, 40, 50 seconds; over 1, 5, 10, 15, 20, 30, 40, 50 minutes; over 1, 5, 10, 15, 20 hours, 1, 2, 5, 10, 20, 30 days, or over 1, 2, 5, 10 months).
In some embodiments, for a heteromultimeric protein, a plurality of cell lines each comprising all subunits can be used to generate a plurality of pharmacological profiles of the heteromeric protein of interest, i.e., one profile per cell line. Differences in the pharmacological profiles between the cell lines distinguish different forms of the heteromeric protein of interest, e.g., variable assemblies or stoichiometries of the subunits.
Comparisons to cells that express different or fewer than all subunits can be used to ascribe functionality to individual subunits.
Examples of heteromultimeric proteins wherein different subunit combinations may be obtained and functionally tested include, but are not limited to:
GABA(A) receptor heteromultimeric combinations (see, e.g., Olsen and Sieghart, “International Union of Pharmacology. LXX. Subtypes of γ-Aminobutyric AcidA Receptors: Classification of the Basis of Subunit Composition, Pharmacology, and Function. Update”, Pharmacological Reviews, 60:243-260, 2008, which is incorporated by reference herein in its entirety):
GABA(A) subunits include, but are not limited to, GABRA1 (α1), GABRA2 (α2), GABRA3 (α3), GABRA4 (α4), GABRA5 (α5), GABRA6 (α6), GABRB1 (β1), GABRB2 (β2), GABRB3(β3), GABRG1 (γ1), GABRG2 (γ2), GABRG3 (γ3), GABRD (δ), GABRE (ε), GABRP (π), and GABRQ (θ);
GABA(A) subunit combinations include, but are not limited to, α1β2γ2, α2βγ2, α3βγ2, α4βγ2, α4β2δ, α4β3δ, α5βγ2, α6βγ2, α6β2δ, α6β3δ, ρ, α1β3γ2, α1βδ, α5β3γ2, αβ1γ, αβ1δ, αβ, α1α6βγ, α1α6βδ, ρ1, ρ2, αβγ1, αβγ3, αβθ, αβε, and αβπ;
nAChR heteromultimeric receptor combinations (see, e.g., Gotti, Zoli and Clementi, “Brain nicotinic acetylcholine receptors: native subtypes and their relevance”, Trends in Pharmacological Sciences, 27:482-491, 2006, and N. Millar Neuropharmacology Volume 56, Issue 1, January 2009, Pages 237-246, the entire teachings of which are incorporated herein by reference):
nAChR subunits include, but are not limited to, CHRNA1 (α1), CHRNA2 (α2), CHRNA3 (α3), CHRNA4 (α4), CHRNA5 (α5), CHRNA6 (α6), CHRNA7 (α7), CHRNA8 (α8), CHRNA9 (α9), CHRNA10 (α10), CHRNB1 (β1), CHRNB2 (β2), CHRNB3 (β3), CHRNB4 (β4), CHRND (δ), and CHRNE (ε);
nAChR subunit combinations include, but are not limited to, α1β1γδ, α1β1δ, α1β1δε, α2α4β2, α2α5β2, α2β2, α2β4, α2α6β2, α3α4β2, α3α4α6β2, α3α5β2, α3α4β4, α3α5β2β4, α3α5β4, α3α6β2, α3β2, α3β3, α3β2β3, α3β2β4, α3β3β4, α3β4, α4α5β2, α4α6β2β3, α4β2, α4β4, α6β2, α6β2β3, α6α4β2, α6β2β3, α6β3β4, α6β4, α7, α7α8, α8, and α9α10;
5-HT3 heteromeric receptors (see, e.g., N. M. Barnes et al., Neuropharmacology 56 (2009) 273-284, which is incorporated by reference herein in its entirety):
5-HT3 subunits include, but are not limited to, HTR3A (A), HTR3B (B), HTR3C (C), HTR3D (D), and HTR3E (E);
5-HT3 subunit combinations include, but are not limited to, Aft AC, AD, and AE;
Glycine heteromeric receptors (see, e.g., J W Lynch Neuropharmacology 56 (2009) 303-309, which is incorporated by reference herein in its entirety):
Glycine receptor subunits include, but are not limited to, GLRA1 (α1), GLRA2 (α2), GLRA3 (α3), GLRA4 (α4), and GLRB (β);
Glycine receptor subunit combinations include, but are not limited to, α1α3, α1β, α2β, α3β, and α4β;
Glutamate heteromeric receptors (see, e.g., Perrais, Neuropharmacology 56 (2009) 131-140; Jane, Neuropharmacology 56 (2009) 90-113; and W. Lu, Neuron, 62, (2009) 2, 254-268, the entire teachings of which are incorporated by reference herein):
Glutamate receptor subunits include, but are not limited to, GRIK1 (K1), GRIK2 (K2), GRIK3 (K3), GRIK5 (K5), GRIA1 (A1) GRIA2 (A2), and GRIA3 (A3);
Glutamate receptor subunit combinations include, but are not limited to, K2K3, K1K2, K1K5, K2K5, A1A2, A1A3, and A2A3;
ATP-gated P2X heteromeric receptors (see, e.g., M. F. Jarvis, B. S. Khakh, Neuropharmacology 56 (2009) 208-215; and S Robertson, Current Opinion in Neurobiology 11, 2001, 378-386, the entire teachings of which are incorporated by reference herein):
ATP-gated P2X receptor subunits include, but are not limited to, P2RX1 (X1), P2RX2 (X2), P2RX3 (X3), P2RX4 (X4), P2RX5 (X5), P2RX6 (X6), and P2RX7 (X7);
ATP-gated P2X receptor subunit combinations include, but are not limited to, X1/X2, X1/X4, X1/X5, X2/X3, X2/X6, X4/X6, and X4/X7;
Taste receptor subunits include, but are not limited to, TAS1R1 (T1R1), TAS1R2 (T1R2), TAS1R3 (T1R3);
Taste receptor subunit combinations include, but are not limited to, T1R2/T1R3 (sweet receptor), T1R1/T1R3 (umami receptor);
GPCR heteromultimers, e.g., GPCR heterodimers (see, e.g., Prinster, Hague and Hall, “Heterodimerization of G Protein-Coupled Receptors: Specificity and Functional Significance”, Pharmacological Reviews, 57:289-298, 2005, which is incorporated by reference herein in its entirety), including, but not limited to: HTR1B (5-HT1B)/HTR1D (5HT1D), ADORA1 (Adenosine A1)/DRD1 (Dopamine D1), ADORA1 (Adenosine A1)/P2RY1 (P2Y1), ADORA1 (Adenosine A1)/GRM1(mGluR1{alpha}), ADORA2a (Adenosine A2A)/DRD2 (Dopamine D2), ADORA2a (Adenosine A2A)/GRM5 (mGluR5), AGTR1 (Angiotensin 1)/AGTR2 (Angiotensin 2), AGTR1 (Angiotensin 1)/ADRB2({beta}2AR), AGTR1 (Angiotensin 1)/BDKRB2 (Bradykinin B2), CASR (Calcium sensing receptor)/GRM1(mGluR1), CASR (Calcium sensing receptor)/GRM5(mGluR5), CCR2/CXCR4, CCR2/CCR5, CCR5/OPRD1 (opioid receptor delta), CCR5/OPRK1 (opioid receptor kappa), CCR5/OPRM1 (opioid receptor mu), CCKRA (Cholecystokinin A)/CCKRB (Cholecystokinin B), DRD1 (Dopamine D1)/DRD2 (Dopamine D2), DRD2 (Dopamine D2)/SSTR5, DRD2 (Dopamine D2)/DRD3 Dopamine D3, EDNRA (Endothelin A)/EDNRB (Endothelin B), GABABR1/GABABR2, MTNR1A (Melatonin MT1)/MTNR1B (Melatonin MT2), CHRM2 (Muscarinic M2)/CHRM3 (Muscarinic M3), OXTR(Oxytocin)/AVPR1A (Vasopressin V1a), OXTR(Oxytocin)/AVPR2 (Vasopressin V2), S1PR1 (S1P1)/S1PR2 (S1P2), S1PR1 (S1P1)/S1PR3 (S1P3), SSTR1/SSTR5, SSTR2A/SSTR3, SSTR2A/OPRM1 (μ-OPR), TACR1 (Substance P)/OPRM1 (μ-OPR), TRHR1/TRHR2, AVPR1A (Vasopressin V1a)/AVPR2(Vasopressin V2), ADRA1B (alpha1BAR)/ADRA1A (alpha1AAR), ADRA1B (alpha1BAR)/HRH1 (Histamine H1), ADRA1B (alpha1BAR)/ADRA1D (alpha1DAR), ADRA1D (alpha1DAR)/ADRB2D (beta2AR), ADRA2A (alpha2AAR)/ADRB1(beta1AR), ADRA2A (alpha2AAR)/OPRM1 (μ-OPR), ADRB1(beta1AR)/ADRB2(beta2AR), ADRB2(beta2AR)/OPRD1 (δ-OPR), ADRB2(beta2AR)/OPRK1(κ-OPR), ADRB2(beta2AR)/ADRB3(beta3AR), ADRB2(beta2AR)/M71-OR, OPRK1(κ-OPR)/OPRD1 (δ-OPR), and OPRM1 (μ-OPR)/OPRD1
(δ-OPR);
Voltage-gated calcium channel (CaV) multisubunit complexes (see, e.g., W A Catterall et al. Pharmacol Rev 2005 57 411-425, and J Arikkath and K Campbell, Current Opinion in Neurobiology 2003, 13:298-307, the entire teachings of which are incorporated by reference herein):
CaV subunits include, but are not limited to, CACNA1S (α1S), CACNA1C (α1C), CACNA1D (α1D), CACNA1F (α1F), CACNA1A (α1A), CACNA1B (α1B), CACNA1E (α1E), CACNB1 (β1), CACNB2 (β2), CACNB3 (β3), CACNB4 (β4), CACNA2D1 (α2δ), CACNG1 (γ1), and CACNG2 (γ2);
CaV subunit combinations include, but are not limited to, α1Sβ1aα2δγ1, α1Sβ1aα2δ, α1Cβ2α2δγ, α1Cβ3α2δγ, α1Dβα2δ, α1Fβ3α2δ, α1Fβ2α2δ, α1Aβ3α2δ, α1Aβ4α2δ, α1Aβ3α2δγ1, α1Aβ3α2δγ2, α1Aβ4α2δγ1, α1Aβ4α2δγ2, α1Bβ1α2δ, α1Bβ3α2δ, α1Bβ4α2δ, α1Bβ3α2δγ2, and α1Eβα2δ;
Voltage-gated sodium channel (NaV) multisubunit complexes (see, e.g., WA Catterall et al. Pharmacol. Rev., 2005 57 397-409, which is incorporated by reference herein in its entirety):
NaV subunits include, but are not limited to, SCN1A (α1), SCN2A (α2), SCN3A (α3), SCN4A (α4), SCN5A (α5), SCN8A (α6), SCN9A (α7), SCN1B (β1), SCN2B (β2), SCN3B (β3), and SCN4B (β4);
NaV subunit combinations include, but are not limited to, α1/β1, α1/β2, α1/β3, α1/β4, α1/β1/β2, α1/β1/β3, α1/β1/β4, α1/β2/β3, α1/β2/β4, α1/β3/β4, α2/β1, α2/β2, α2/β3, α2/β4, α2/β1/β2, α2/β1/β3, α2/β1/β4, α2/β2/β3, α2/β2/β4, α2/β3/β4, α3/β1, α3/β3, α4/β1, α5/β1, α5/β2, α5/β3, α5/β4, α5/β1/β2, α5/β1/β3, α5/β1/β4, α5/β2/β3, α5/β2/β4, α5/β3/β4, α6/β1, α6/β2, α6/β1/β2, α7/β1, α7/β2, and α7/β1/β2;
Inwardly Rectifying Potassium Channels—heteromeric/multisubunit complexes (see, e.g., Y Kubo et al. Pharmacol. Rev., 2005 57 509-526, which is incorporated by reference herein in its entirety):
Inwardly Rectifying Potassium Channel subunits include, but are not limited to, KCNJ2 (Kir2.1) KCNJ12 (Kir2.2), KCNJ4 (Kir2.3), KCNJ14 (Kir2.4), KCNJ3 (Kir3.1), KCNJ6 (Kir3.2), KCNJ9 (Kir3.3), KCNJ5 (Kir3.4), and KCNJ10 (Kir4.1);
Inwardly Rectifying Potassium Channel subunit combinations include, but are not limited to, those listed in the table (Table 1) below:
Voltage-Gated Potassium Channels—heteromeric/multisubunit complexes (see, e.g., G Gutman et al. Pharmacol. Rev., 2005 57 473-508, which is incorporated herein by reference in its entirety):
Voltage-Gated Potassium Channel subunits include, but are not limited to, KCNA1 (KV1.1), KCNA2 (KV1.2), KCNA3 (KV1.3), KCNA5 (KV1.5), KCNA6 (KV1.6), KCNA10 (KV1.8), KCNB1 (KV2.1) KCNB2 (KV2.2), KCNC4 (KV3.4), KCND1 (KV4.1), KCND2 (KV4.2), KCND3 (KV4.3), KCNF1 (KV5.1) KCNG1 (KV6.1), KCNG2 (KV6.2), KCNG3 (KV6.3), KCNG4 (KV6.4), KCNQ1 (KV7.1), KCNA2 (KV7.2), KCNQ3 (KV7.3), KCNQ4 (KV7.4), KCNA5 (KV7.5), KCNV1 (KV8.1), KCNV2 (KV8.2), KCNS1 (KV9.1), KCNS2 (KV9.2), KCNS3 (KV9.3), KCNH1 (KV10.1), KCNH5 (KV10.2), KCNH2 (KV11.1), KCNH6 (KV11.2), KCNH7 (KV11.3), KCNAB1 (KVβ1), KCNAB2 (KVβ2), KCNAB3 (KVβ3) KCNE1 (minK), KCNE2 (MiRP1), KCNE3 (MiRP2), KCNE4 (MiRP3), KCNE1L (KCNE1-like), KCNIP1, KCNIP2, KCNIP3, and KCNIP4;
Voltage-Gated Potassium Channel subunit combinations include, but are not limited to, those listed in the table (Table 2) below:
Calcium-Activated Potassium Channels—heteromeric and multisubunit complexes (see, e.g., A Wei et al. Pharmacol. Rev., 2005; 57: 463-472, which is incorporated herein by reference in its entirety):
Calcium-Activated Potassium Channel subunits include, but are not limited to, KCNMA1 (KCa1.1), KCNN1 (KCa2.1), KCNN2 (KCa2.2), KCNN3 (KCa2.3), KCNN4 (KCa3.1), KCNT1 (KCa4.1), KCNT2 (KCa4.2), and KCNU1 (KCa5.1);
Calcium-Activated Potassium Channel subunit combinations include, but are not limited to, those listed in the table (Table 3) below:
Transient Receptor Potential channels—heteromeric/multisubunit complexes (see, e.g., D E Clapham et al. Pharmacol. Rev., 2005; 57(4): 427-450, which is incorporated herein by reference in its entirety):
Transient Receptor Potential Channel subunits include, but are not limited to, TRPC1, TRPC3, TRPC4, TRPC5, TRPC6, TRPC7, TRPV-5, TRPM1, and TRPM1-S;
Transient Receptor Potential Channel subunit combinations include, but are not limited to, those listed in the table (Table 4) below:
Cyclic Nucleotide-Regulated Channels—heteromeric/multisubunit complexes (see, e.g., F Hofmann et al. Pharmacol. Rev., 2005; 57(4): 455-462, which is incorporated herein by reference in its entirety);
Cyclic Nucleotide-Regulated Channel subunits include, but are not limited to, CNGA, CNGB1a, CNGA2, CNGB1b, CNGA4, CNGA3, CNGB3, CNG4A, and CNGA1;
Cyclic Nucleotide-Regulated Channel subunit combinations include, but are not limited to, CNGA1/CNGB1a, CNGA2/CNGB1b/CNGA4, CNGA3/CNGB3, CNG4A/CNGA2/CNGB1b, CNGB1a/CNGA1, CNGB1b/CNGA2/CNGA4, and CNGB3/CNGA3;
Epithelial Sodium Channel/Degenerin—heteromeric/multisubunit complexes (see, e.g., A Staruschenko et al Biophys J, 2005; 88, 3966-3975, H Yamamura et al European J Pharm., 2008, 600, 32-36, and S Kellenberger and L Schild Physiol Rev, 2002, 82, 735-767, the entire teachings of which are incorporated herein by reference):
Epithelial Sodium Channel/Degenerin subunits include, but are not limited to, SCNN1A (ENaCα); SCNN1B (β), SCNN1G (γ), SCNN1D (ENaCδ), ACCN1 (ASIC2, two splice variants 2a and 2b), ACCN3 (ASIC3);
Epithelial Sodium Channel/Degenerin subunit combinations include, but are not limited to, ENaCαβγ, ENaCαδβγ, ENaCδβγ, ASIC2a/ASIC2b, ASIC2a/ASIC3, and ASIC2b/ASIC3.
For the heteromeric proteins listed above and those disclosed elsewhere herein, many more combinations of subunits yet to be defined may exist. Cell lines comprising the combinations listed above may be used as references against those cell lines that may express novel combinations, so that the novel combinations may be ascertained. For example, different subunit combinations may be characterized by different response profiles of different cell lines each expressing a same set of subunits to a same set of compounds. See, e.g., Example 23 hereinbelow.
Large scale application of the method applied to heteromultimeric targets defined by large gene families (e.g., GABA or the acetylcholine ion channels) allows cross comparative analysis of multiple cell lines for all or a subset of possible subunit combinations.
In certain embodiments, gene activation is used with the methods, cells, and cell lines of the invention. Gene activation is described, e.g., in International Application Publication WO 94/12650, which is incorporated herein by reference. In certain embodiments, homologous recombination can be used to genetically modify a regulatory region of one or more endogenous genes in the cell that encodes for a receptor or a receptor subunit of ENaC (epithelial sodium channel), GABAA (Gamma-aminobutyric acid type A), NaV (voltage-gated sodium ion channel), a sweet taste receptor, an umami taste receptor, a bitter taste receptor, CFTR (cystic fibrosis transmembrane-conductance regulator), or GCC (guanylyl cyclase C) such that the genetic modification results in increased expression of the receptor or receptor subunit of ENaC, GABAA, NaV, sweet taste receptor, umami taste receptor, bitter taste receptor, CFTR, or GCC relative to the expression levels of the receptor or receptor subunit in the cell before the genetic modification. In certain embodiments, the genetic modification results in an increase of expression by at least 10%, 50%, 100%, 500%, 1000%, 5000%, or at least 10,000%. In certain embodiments, the cell expresses the receptor or receptor subunit at background levels before gene activation.
In certain embodiments, a promoter is introduced via homologous recombination to be operatively linked with the coding sequence that is endogenous to the cell for a receptor or one or more receptor subunits of ENaC, GABAA, NaV, a sweet taste receptor, an umami taste receptor, a bitter taste receptor, CFTR, or GCC. The promoter can be a constitutively active promoter. In particular, the promoter can be a promoter that is constitutively active in the cell. In other embodiments, the promoter is a conditional promoter. Cells that can be used with these methods are described above. In certain embodiments, promotors can be randomly inserted into the genome of the cell. Fluorogenic oligonucleotides can then be used to select a cell in which the randomly inserted promoter activates the expression of an RNA of interest. In certain embodiments, the RNA of interest may be for a receptor or one or more subunits of a receptor of ENaC, GABAA, NaV, a sweet taste receptor, an umami taste receptor, a bitter taste receptor, CFTR, or GCC. In certain embodiments, regulatory DNA elements, such as enhancers or repressors, are inserted at random positions into the genome and a cell in which an RNA of interest is upregulated or downregulated is selected.
In certain embodiments, homologous recombination is used to introduce DNA into the genome of a cell such that the endogenous gene is expressed. In some embodiments, the endogenous gene may be a gene encoding a receptor or one or more receptor subunits of ENaC, GABAA, NaV, a sweet taste receptor, an umami taste receptor, a bitter taste receptor, CFTR, or GCC. In certain embodiments the introduced DNA includes a selectable marker, such as a gene encoding for antibiotic resistance (e.g., DHFR). In certain embodiments, the endogenous gene is amplified in the genome of the cell. In certain embodiments, the endogenous gene is amplified such that the genome of the cell comprises 2 copies, 3 copies, 4 copies, 5 copies, 6 copies, 7 copies, 8 copies, 9 copies, 10 copies, at least 2 copies, at least 5 copies, at least 10 copies, at least 15 copies, at least 20 copies, or at least 25 copies of the endogenous gene. In certain embodiments, a cell with stable functional expression of the amplified gene is selected.
Regulatory sequences can also be modified and expression achieved by the genetic variation methods described below. Genetic variability may be generated in a cell line and subsequently a cell that expresses a receptor or one or more subunits of a receptor of ENaC, GABAA, NaV, a sweet taste receptor, an umami taste receptor, a bitter taste receptor, CFTR, or GCC is selected using a fluorogenic oligonucleotide as described herein.
In certain embodiments, a cell expresses a receptor or one or more receptor subunits of ENaC, GABAA, NaV, a sweet taste receptor, an umami taste receptor, a bitter taste receptor, CFTR, or GCC before application of the gene activation or generation of genetic variability. Gene activation and/or generation of genetic variability and selection is then used to generate and select a cell that expresses another receptor or at least one additional subunit of the same receptor and/or that has a reduced level of expression of the receptor or of one or more receptor subunits that was expressed before application of the gene activation or generation of genetic variability.
In certain embodiments, an accessory factor is also expressed in the cell. The accessory factor can be expressed in the cell without genetic modification; the accessory factor can be expressed as a transgene; or the accessory factor can be expressed via gene activation and/or generation of genetic variability and selection as described above. The accessory factor can be a factor that facilitates the transcription and/or translation and/or folding and/or subcellular localization and/or function of a receptor or subunit of a receptor of interest. The accessory factor can facilitate the assembly of a multi-subunit receptor.
In certain embodiments, provided herein is a cell line that expresses a complete receptor, or that expresses one, two, three, four, or five subunits of a multisubunit receptor of interest. The multisubunit receptor of interest may be, e.g., ENaC, GABAA, NaV, a sweet taste receptor, an umami taste receptor, or a bitter taste receptor. In certain embodiments, neither the receptor nor any receptor subunits of a multisubunit receptor of interest is expressed from a transgene. In certain embodiments, one, two, three, four, or five subunits of the multisubunit receptor of interest is/are not expressed from a transgene. In certain embodiments, a complete receptor, or one, two, three, four, or five subunits of a multisubunit receptor of interest is/are expressed from amplified genomic region of the endogenous gene encoding the receptor or the receptor subunit(s).
In certain embodiments, genomic DNA is transfected or microinjected into a population of cells and a cell that expresses an RNA of interest is selected. In some embodiments, the RNA of interest may be for a receptor or one or more subunits of a receptor of ENaC, GABAA, NaV, a sweet taste receptor, an umami taste receptor, a bitter taste receptor, CFTR, or GCC. Genomic DNA may be obtained from a cell that expresses the RNA of interest. In certain embodiments, the donor cell of genomic DNA is of the same species as the acceptor cell. In certain embodiments, the donor cell is a different species than the acceptor cell.
In certain embodiments, the donor cell of genomic DNA can be a human, mouse, insect, dog, donkey, horse, rat, guinea pig, avian or monkey cell. In certain embodiments, genomic DNA from 2, 3, 4, 5, 6, 7, 8, 9, or 10 different species is introduced. In certain, more specific embodiments, the different donor species of genomic DNA have orthologs of the gene of interest. In other embodiments, the donor species do not have orthologs of the gene of interest.
In certain embodiments, the genomic DNA fragment is a defined region of the genome and includes the gene of interest. In certain embodiments, the genomic DNA fragment is at least 1 kb, 5 kb, 10 kb, 100 kb, 500 kb, or 1000 kb in size.
Any method known to the skilled artisan can be used to extract genomic DNA from a cell. An illustrative method for isolating genomic DNA is described in Unit 2.2. of Short Protocols in Molecular Biology, Ausubel et al. (editors), John Wiley & Sons, Inc., 1999. In certain embodiments, the genomic DNA is treated very gently to avoid shearing of the DNA. In other embodiments, the genomic DNA is sheared to obtain smaller DNA fragments. In certain embodiments, the DNA is treated with DNAse-free protease to remove any proteinaceous substances from the DNA. In other embodiments, the genomic DNA is not treated with protease, and instead care is taken to leave undisturbed the proteins associated with the genomic DNA. In certain embodiments, the DNA is treated with DNAse free RNAse.
The genomic DNA can be introduced into cells using any method known to the skilled artisan. In certain embodiments, the genomic DNA is transfected into a cell. In more specific embodiments, the genomic DNA is transfected into the cells using lipofection. Illustrative methods for introducing the genomic DNA into cells are described in Chapter 9 of Short Protocols in Molecular Biology, Ausubel et al. (editors), John Wiley & Sons, Inc., 1999.
The optimal amount of genomic DNA to be introduced into a cell can be determined by identifying the number of cells expressing the RNA of interest. In certain embodiments, the amount of genomic DNA introduced per cell corresponds to at least the equivalent of 1 genome, at least the equivalent of 10−1 genome, at least the equivalent of 10−2 genome, at least the equivalent of 10−3 genome, at least the equivalent of 10−4 genome, at least the equivalent of 10−5 genome, at least the equivalent of 10−6 genome, or at least the equivalent of 10−7 genome. In certain embodiments, the amount of genomic DNA introduced per cell corresponds to at most the equivalent of 1 genome, at most the equivalent of 10−1 genome, at most the equivalent of 10−2 genome, at most the equivalent of 10−3 genome, at most the equivalent of 10−4 genome, at most the equivalent of 10−5 genome, at most the equivalent of 10−6 genome, or at most the equivalent of 10−7 genome.
In certain embodiments, the genomic DNA can be amplified by any technique known to the skilled artisan. In a certain, more specific embodiment, the genomic DNA is amplified by Whole Genome Amplification.
Any method can be used to identify and isolate those cells in which genomic DNA has been introduced. In certain embodiments, DNA that encodes a marker gene is introduced concurrently with the genomic DNA into cells. Cells that are positive for the marker gene also harbor the genomic DNA. Any marker gene known to the skilled artisan can be used. Illustrative examples of marker genes include genes whose gene products confer resistance to a particular antibiotic to the cells (e.g., neomycin resistance), genes whose gene products enable a cell to grow on a medium that lacks a substance that is normally required by this cell for growth, or genes whose gene products encode a visual marker. A visual marker that can be used with the methods of the invention is, e.g., GFP. Cells in which the DNA encoding the visual marker and the genomic DNA have been introduced can be isolated using FACS.
In certain embodiments, the genomic DNA is introduced into cells using microinjection.
In certain embodiments, fragments of the genomic DNA are packaged into vectors for propagation of the genomic DNA. Such vectors include, but are not limited to, bacteriophages, cosmids or YACs. Any method known to the skilled artisan can be used to package and propagate the genomic DNA.
In certain embodiments, provided herein is a cell line that expresses a multisubunit receptor of interest with the same stoichiometry of subunits as the stoichiometry of subunits of the multisubunit receptor of interest in a non-recombinant organism, wherein the cell from which the cell line was derived does not express the multisubunit receptor of interest. In certain embodiments, provided herein is a cell line that expresses a receptor, including a cell line that expresses a multisubunit receptor, wherein the pharmacological profile of the receptor in the cell line matches the pharmacological profile of the receptor in a cell that normally expresses the target in an organism. The receptor or multisubunit receptor of interest can be, e.g., ENaC, GABAA, NaV, a sweet taste receptor, an umami taste receptor, a bitter taste receptor, CFTR, or GCC. In certain embodiments, the cell line expresses the receptor or multisubunit receptor stably in the absence of selective pressure as described hereinabove.
In certain aspects, the invention provides for methods for identifying, isolating, and enriching cells that are naturally occurring and express a receptor or one or more receptor subunits of ENaC, GABAA, NaV, a sweet taste receptor, an umami taste receptor, or a bitter taste receptor, CFTR, or GCC. In some embodiments, the naturally occurring cell expresses a receptor or one or more receptor subunits of ENaC, GABAA, NaV, a sweet taste receptor, an umami taste receptor, or a bitter taste receptor, CFTR, or GCC in nature.
In certain embodiments, the methods described herein rely on the genetic variability and diversity that exists in nature. In certain embodiments, the isolated cell is represented by not more than 1 in 10, 1 in 100, 1 in 1000, 1 in 10,000, 1 in 100,000, 1 in 1,000,000 or 1 in 10,000,000 cells in a population of cells. The population of cells can be primary cells harvested from organisms. In certain embodiments, genetic variability and diversity may also be increased using natural processes known to a person skilled in the art. Any suitable methods for creating or increasing genetic variability and/or diversity may be performed on host cells. Without being limited by theory, such generation of genetic variability generates modifications in regulatory regions of a gene encoding, for example, a receptor or a receptor subunit of ENaC, GABAA, NaV, a sweet taste receptor, an umami taste receptor, or a bitter taste receptor, CFTR, or GCC. Cells expressing such a subunit can then be selected as described herein. In certain embodiments, a cell that endogenously expresses the protein of interest is isolated from a clonal cell line that has been subjected to at least 50, 100, 500, 750, or at least 1000 passages; or that has been subjected to at least 1, 2, 5, or 10 months, or at least 1, 2, 5, 10 years of continuous growth.
In other embodiments, genetic variability may be achieved by exposing a cell to UV light and/or x-rays (e.g., gamma-rays). Genetic variability can also be achieved in a population of cells by introducing genomic DNA, cDNA, and/or mRNA into the cells of the population of cells. In particular embodiments, fragments of genomic DNA is introduced as discussed above. In particular embodiments, a library of genomic DNA is introduced. In particular embodiments, a cDNA library is introduced. In particular embodiments, an expression DNA library is introduced. In certain embodiments, the genomic DNA, cDNA, and/or mRNA is derived from a cell type different from the cell type of the recipient cells. In a particular embodiment, the genomic DNA, cDNA, and/or mRNA is derived from a taste cell.
In other embodiments, genetic variability may be achieved by exposing cells to EMS (ethyl methane sulftonate). In some embodiments, genetic variability may be achieved by exposing cells to mutagens, carcinogens, or chemical agents. Non-limiting examples of such agents include deaminating agents such as nitrous acid, intercalating agents, and alkylating agents. Other non-limiting examples of such agents include bromine, sodium azide, and benzene.
In specific embodiments, genetic variability may be achieved by exposing cells to growth conditions that are sub-optimal, e.g., low oxygen, low nutrients, oxidative stress or low nitrogen.
In certain embodiments, enzymes that result in DNA damage or that decrease the fidelity of DNA replication or repair (e.g. mismatch repair) can be used to increase genetic variability. In certain embodiments, an inhibitor of an enzyme involved in DNA repair is used. In certain embodiments, a compound that reduces the fidelity of an enzyme involved in DNA replication is used. In certain embodiments, proteins that result in DNA damage and/or decrease the fidelity of DNA replication or repair are introduced into cells (co-expressed, injected, transfected, electroporated).
The duration of exposure to certain conditions or agents depend on the conditions or agents used. In some embodiments, seconds or minutes of exposure is sufficient. In other embodiments, exposure for a period of hours, days or months are necessary. The skilled artisan will be aware what duration and intensity of the condition can be used.
Without being bound by theory, a method that increases genetic variability produces a mutation or alteration in a promoter region of a gene that leads to a change in the transcriptional regulation of the gene, e.g., gene activation, wherein the gene is more highly expressed than a gene with an unaltered promoter region. In certain embodiments, the gene encodes a receptor or a receptor subunit of ENaC, GABAA, NaV, a sweet taste receptor, an umami taste receptor, or a bitter taste receptor, CFTR, or GCC. Generally, a promoter region includes a genomic DNA sequence upstream of a transcription start site that regulates gene transcription, and may include the minimal promoters and/or enhancers and/or repressor regions. A promoter region may range from about 20 basepairs (bps) to about 10,000 bps or more. In specific embodiments, a method that increases gene variability produces a mutation or alteration in an intron of a gene of interest that leads to a change in the transcriptional regulation of the gene, e.g., gene activation wherein the gene is more highly expressed than gene with an unaltered intron. In certain embodiments, untranscribed genomic DNA is modified. For example, promoter, enhancer, modifier, or repressor regions can be added, deleted, or modified. In these cases, transcription of a transcript that is under control of the modified regulatory region can be used as a read-out. For example, if a repressor is deleted, the transcript of the gene that is repressed by the repressor is tested for increased transcription levels.
In certain embodiments, the genome of a cell or an organism can be mutated by site-specific mutagenesis or homologous recombination. In certain embodiments, oligonucleotide- or triplex-mediated recombination can be employed. See, e.g., Faruqi et al., 2000, Molecular and Cellular Biology 20:990-1000 and Schleifman et al., 2008, Methods Molecular Biology 435:175-90.
In certain embodiments, fluorogenic oligonucleotide probes or molecular beacons can be used to select cells in which the genetic modification was successful, i.e., cells in which the transgene or the gene of interest is expressed. To identify cells in which a mutagenic or homologous recombination event was successful, a fluorogenic oligonucleotide that specifically hybridizes to the mutagenized or recombined transcript can be used. In certain embodiments, where a cell is selected that endogenously expresses a protein of interest and the cell is of a cell type that does not express the protein of interest, a fluorogenic oligonucleotide can be used that specifically hybridizes to the RNA encoding the protein of interest to isolate cells that express the desired protein. The isolation of cells can be performed as described in U.S. Pat. No. 6,692,965 by Shekdar et al. issued Feb. 17, 2004 and International Application No. PCT/US2005/005080 published as WO/2005/079462). In certain embodiments, cells positive for the desired signal (i.e., cells that express the desired RNA) are pooled. Such a pool can then be subjected to a second round of selection. In certain embodiments, the pool of cells is subjected to a total of at least 2, 3, 4, 5, 6, 7, 8, 9, 10, 15, 20, 25, or at least 50 rounds of selection.
Cells and cell lines engineered to express a multimeric protein may comprise multiple different functional forms of the multimeric protein. The same cell or cell line engineered to comprise a multimeric protein complex could comprise different functional forms or different proportions of the same or different functional forms when it is cultured under different cell culture conditions. Culture conditions may vary with respect to temperature, nutrient concentration, serum addition, ion concentration, cell density, synchronization of cell cycle, pH, acidity, carbonation, atmospheric conditions, percent carbon dioxide, shaking, stirring, UV exposure, activity or concentration of metabolites, serum, amino acids, sugars, carbohydrates, proteins, lipids, detergents, growth factors, co-factors, vitamins, mutagens, chemicals, compounds or trace metals. Different cells or cell lines engineered to comprise the same target may comprise different functional forms or different proportions of the same or different functional forms. The methods described may be used for comparative analysis of cells or cell lines engineered to comprise the same or different multimeric protein cultured in the same or different cell culture conditions.
In some embodiments, the cells or cell lines to be used with the methods for characterizing a multimeric protein and for making panels of cells or cell lines expressing different forms of a multimeric protein of interest are cells or cell lines as described herein, e.g., cells or cell lines with a substantially constant physiological property, cells or cell lines that express a protein of interest which does not comprise a protein tag, or cells or cell lines having a Z′ factor of at least 0.4 in a functional assay, or cells or cell lines cultured in the absence of selective pressure, or any combinations thereof. In some embodiments, the different cell lines to be used are maintained in parallel under substantially identical culture conditions. Robotic methods described herein may be used to maintain and manipulate the cells or cell lines expressing different forms of a multimeric protein of interest. In some embodiments, the invention provides a cell or cell line that expresses a multimeric (dimeric, trimeric or higher order of multimerization) protein of interest from an introduced nucleic acid encoding said multimeric protein of interest or one or more subunits thereof, wherein the cell is cultured in the absence of selective pressure and/or wherein the protein is expressed consistently as described herein.
In some embodiments, the invention provides methods for generating a panel of cell lines comprising a plurality of cell lines wherein each of the plurality of cell lines synthesizes a different form of a multimeric protein of interest. Examples of multimeric proteins of interest are further disclosed hereinabove. Without being bound by theory, the different forms of the multimeric protein differ, e.g., in their subunit combination, post-translational modification of individual subunits, and/or subcellular localization (e.g., with respect to the cytoskeleton; for transmembrane proteins: membrane integration/localization, exit out of the endoplasmic reticulum, exit out of the Golgi apparatus; and for secreted proteins: exit out of the endoplasmic reticulum, exit out of the Golgi apparatus). In some embodiments, such panels can be generated by starting with a specific clone or line of a host cell and engineering that host cell to express one or more subunits of a multimeric protein of interest. In some embodiments, transgenes encoding the one or more subunits are introduced. In other embodiments, gene activation is employed. Cells that have been successfully engineered to express the one or more subunit can be selected by any method known to the skilled artisan. In some embodiments, the positive cells are selected using fluorogenic oligonucleotides or molecular beacons (see, e.g., International Application No. PCT/US2005/005080 published as WO/2005/079462). Cell lines are established from the identified cells. In some embodiments, the resulting cell lines are generated from the same materials (e.g., the same host parental clone, the same nucleic acids for engineering the expression of the one or more subunits) and the same protocols (e.g., the same cell culturing methods, the same genetic engineering methods). Without being bound by theory, the resulting cell lines may vary with regard to the insertion sites of any transgenes in the genome of the host cell and/or with regard to the copy number of any transgenes in the genome. Surprisingly, it was found that the resulting cell lines may synthesize different forms of a multimeric protein. Cell lines that synthesize different forms of a multimeric protein may be identified by establishing a pharmacological profile of each cell line. Certain compounds are tested for their effects on the multimeric protein in the various cell lines. Activities may be monitored over time. Dose-response curves can be established. In certain embodiments, at least 2, 5, 10, 25, 50, 100, 250, 500, 750, 1000, 1500, 2000, 2500, 3000, 4000, 5000, 7500, or at least 10000 different compounds are tested per cell line to generate a pharmacological fingerprint for the multimeric protein synthesized by a particular cell line. The resulting pharmacological fingerprints for each cell line are then compared with each other. If the pharmacological fingerprints are substantially the same, the form of the multimeric protein in the cell lines are the same. If the pharmacological fingerprints are not substantially the same, the forms of the multimeric protein in these cell lines are different.
In certain embodiments, the forms are the same if the quality of the response of the multimeric protein is the same for each compound (e.g., activated, inhibited, or neutral).
In other embodiments, the forms are the same if the quantity of the response is the same for each compound within a margin of 50%, 25%, 10%, 5%, 1%, or 0.5%.
In certain embodiments, the forms are different if the quality of the response of the multimeric protein is different for at least 1 compound (e.g., activated, inhibited, or neutral). In certain embodiments, the forms are different if the quality of the response of the multimeric protein is different for at least 50%, 25%, 10%, 5%, 1%, or 0.5% of the compounds tested (e.g., activated, inhibited, or neutral). In other embodiments, the forms are different if the quantity of the response for at least 1 compound is not within a margin of at least 50%, 25%, 10%, 5%, 1%, or 0.5%. In other embodiments, the forms are different if the quantity of the response for at least 50%, 25%, 10%, 5%, 1%, or 0.5% of the tested compounds is not within a margin of at least 50%, 25%, 10%, 5%, 1%, or 0.5%. Any algorithm known to the skilled artisan can be used to quantify and compare the pharmacological fingerprints of the multimeric proteins in the different cell lines.
In some embodiments, the composition of a biologically active multimeric protein of interest in a cell that co-expresses a first subunit and a second subunit can be classified by comparing a first subunit pharmacological profile, a second subunit pharmacological profile, and a mixed subunit pharmacological profile. The first subunit pharmacological profile can comprise measured amounts representing an effect of a compound on the biological activity of the multimeric protein as it would be expressed in a cell that expresses the first subunit of the multimeric protein and not the second subunit. The second subunit pharmacological profile can comprise measured amounts representing an effect of the compound on the biological activity of the multimeric protein as it would be expressed in a cell that expresses the second subunit of the multimeric protein and not the first subunit. The mixed subunit pharmacological profile can comprise measured amounts representing an effect of the compound on the biological activity of the multimeric protein is it would be expressed in a cell that expresses both the first subunit and the second subunit of the multimeric protein. In some embodiments, the biologically active multimeric protein of interest can be classified as (i) a homodimer of the first subunit, if the first subunit pharmacological profile has a high similarity to the mixed subunit pharmacological profile, and the second subunit pharmacological profile has a low similarity to the mixed subunit pharmacological profile; (ii) a homodimer of the second subunit, if the second subunit pharmacological profile has a high similarity to the mixed subunit pharmacological profile, and the first subunit pharmacological profile has a low similarity to the mixed subunit pharmacological profile; (iii) a heterodimer of the first subunit and the second subunit, if the first subunit pharmacological profile has a low similarity to the mixed subunit pharmacological profile, and the second subunit pharmacological profile has a low similarity to the mixed subunit pharmacological profile; or (iv) a combination of homodimers of the first subunit and homodimers of the second subunit, if the mixed subunit pharmacological profile is a combination of the first subunit pharmacological profile and the second subunit pharmacological profile.
In another embodiment, the composition of a biologically active multimeric protein of interest in a cell that co-expresses a first subunit and a second subunit can be classified by comparing a pharmacological profile of the cell of interest with the first subunit pharmacological profile, the second subunit pharmacological profile, and the mixed subunit pharmacological profile. In some embodiments, the biologically active multimeric protein of interest can be classified as (i) a homodimer of the first subunit, if said first pharmacological profile has a low similarity to said second subunit pharmacological profile and a high similarity to both said first subunit pharmacological profile and said mixed subunit pharmacological profile; (ii) a homodimer of the second subunit, if said first pharmacological profile has a low similarity to said first subunit pharmacological profile and a high similarity to both said second subunit pharmacological profile and said mixed subunit pharmacological profile; (iii) a heterodimer of the first subunit and the second subunit, if said first pharmacological profile has a low similarity to said first subunit pharmacological profile, a low similarity to said second subunit pharmacological profile, and a low similarity to said mixed subunit pharmacological profile; or (iv) a combination of homodimers of the first subunit and homodimers of the second subunit, if said first pharmacological profile has a high similarity to said mixed subunit pharmacological profile, and said first pharmacological profile is a combination of said first subunit pharmacological profile and said second subunit pharmacological profile.
In certain embodiments, an effect of a subunit on the biological activity of a multimeric protein in a cell can be characterized by comparing a pharmacological profile from a cell that expresses the subunit of interest to a pharmacological profile from a cell that does not express the subunit of interest. In some embodiments, a test pharmacological profile can be compared to a base pharmacological profile to characterize that effect. In the foregoing embodiment, the test pharmacological profile can comprise measured amounts representing an effect of a compound on the biologically active multimeric protein in a cell that expresses a pre-selected combination of subunits and, in addition, the subunit of interest; the base pharmacological profile can comprise measured amounts representing an effect of that compound on the biologically active multimeric protein in a cell that expresses the pre-selected combination of subunits but not the subunit of interest. The subunit of interest is not one of the subunits of the pre-selected combination of subunits. The subunit of interest can be characterized as having an effect on the biological activity of the multimeric protein if the test pharmacological profile has a low similarity to the base pharmacological profile, or as having no effect on the biological activity of the multimeric protein if the test pharmacological profile has a high similarity to the base pharmacological profile.
The pharmacological profiles can be compared by computing a correlation between the pharmacological profiles, such as but not limited to, computing a measure of similarity between the pharmacological profiles.
In certain embodiments, two pharmacological profiles can be deemed to be correlated if the measured amounts in one of the pharmacological profiles are within about 2%, about 5%, about 8%, about 10%, about 12%, about 15%, about 20%, about 25%, about 30%, or about 35% of the measured amounts in the other pharmacological profiles.
In certain embodiments, two pharmacological profiles can be deemed to have a high similarity to each other if a measure of similarity computed between them is above a predetermined threshold, or can be deemed to have a low similarity to each other if a measure of similarity computed between them is below a predetermined threshold. In some embodiments, the predetermined threshold can be determined as the value of the measure of similarity which indicates that the measured amounts in one of the pharmacological profiles are within about 2%, about 5%, about 8%, about 10%, about 12%, about 15%, about 20%, about 25%, about 30%, or about 35% of the measured amounts in the other pharmacological profile.
In some embodiments, the pharmacological profile of the compound of interest can be expressed as a vector p,
p=[p1, . . . pi, . . . pn]
where pi is the measured amount of the i'th component, for example, the effect of a compound on the i'th biological activity of a cell that expresses the subunits of interest of a multimeric protein. In some embodiments, n is more than 2, more than 10, more than 100, more than 200, more than 500, more than 1000, more than 2000, more than 2500, more than 7500, more than 10,000, more than 20,000, more than 25,000, or more than 35,000. Each pharmacological profile also can be expressed as a vector p. In computing a correlation, the measured amount of the i'th component in the vector representing the pharmacological profile for the compound of interest can be compared to the corresponding measured amount of the i'th component of the vector representing a pharmacological profile, for each component i=1 . . . n. However, there are many ways in which a correlation can be computed. Indeed, any statistical method in the art for determining the probability that two datasets are related may be used in accordance with the methods of the present invention in order to identify whether there is a correlation between the pharmacological profile of a compound of interest and a pharmacological profile. For example, the correlation between the pharmacological profile (pi
The correlation can also be computed based on ranks, where xi and yi are the ranks of the values of the measured amounts in ascending or descending numerical order. See for example, Conover, Practical Nonparametric Statistics, 2nd ed., Wiley, (1971). Shannon mutual information also can be used as a measure of similarity. See for example, Pierce, An Introduction To Information Theory: Symbols, Signals, and Noise, Dover, (1980), which is incorporated by reference herein in its entirety.
Some embodiments of the present invention provide a computer program product that contains any or all of the program modules shown in
Any assay known to the skilled artisan can be used to assay the activity of a multimeric protein of interest and thereby establish a pharmacological fingerprint. Examples of such assays are further described hereinbelow. Any assays to be used with the methods of the invention can be conducted in high throughput format.
In some embodiments, the panels of the invention may be used in HTS or in combination with medicinal chemistry to test and identify compounds that are selective for one or a set of targets; in particular, to identify compounds whose activity is specific to particular forms of a multimeric protein of interest or having certain patterns or profiles of activity. Secondary testing including in vivo tests using the compounds could be used to determine the presence, role and function of the corresponding target or targets in vivo, or its relevance as a biomarker. (Testing methods are diverse and include brain imaging studies, animal studies, binding studies, behavioral models, PET scans, NMRIs, etc.)
The present invention provides for characterizing the composition of a multimeric protein. Without being bound by theory, multimeric proteins characterized by functional criteria could reflect specific stoichiometries of the multimeric proteins or combinations or levels of different specific stoichiometries. In certain embodiments, a multimeric protein is expressed in a cell that has been engineered to express the multimeric protein.
In some embodiments, the composition of a dimer is determined using the methods of the invention.
In some embodiments, the methods of the invention allow the determination whether the dimer in a particular cell is a) a homodimer of a first subunit; b) a homodimer of a second subunit; or c) a heterodimer of the first and the second subunit. For example, such a method may comprise the following steps:
Step A) The activity of the first subunit in a cell that does not express the second subunit is tested.
Step B) The activity of the second subunit in a cell that does not express the first subunit is tested.
Step C) The activity of the first subunit and the second subunit is tested in a cell that expresses both the first and the second subunits.
The activities obtained in Steps A, B, and C are compared and the composition of the dimeric protein in a cell that expresses both the first and the second subunits is deduced. If the activity determined in Step A equals the activity determined in Step C, then the dimer that is formed in a cell that co-expresses the first and the second subunits is a homodimer of the first subunit. If the activity determined in Step B equals the activity determined in Step C, then the dimer that is formed in a cell that co-expresses the first and the second subunit is a homodimer of the second subunit. If the activity determined in Step A and the activity determined in Step B are both different from the activity determined in Step C, then the dimer that is formed in a cell that co-expresses the first and the second subunits is a heterodimer of the first and the second subunits. If the activity determined in Step C is a combination of activities observed in Step A and Step B, then the cell that co-expresses the first and the second subunits produces homodimers of the first subunit and homodimers of the second subunit.
In some embodiments, the activity profile of a compound over time is measured.
Similar steps can be taken to determine the subunit combination of trimers and other multimeric proteins with higher orders of multimerization. In some embodiments, the invention provides a panel of cell lines comprising a plurality of cell lines wherein each cell line of the plurality of cell lines has been engineered to express the same subunit or subunits of a multimeric protein using the same protocol and the same host cells, wherein the resulting multimeric proteins differ among the cell lines. The differences between the multimeric proteins can be: different subunit combinations, different subunit stoichiometries, different post-translational modifications including proteolysis, and/or different splicing of one or more subunits. Without being bound by theory, the differences in the multimeric proteins between cell lines may result, e.g., from different insertion sites of the subunit(s) or copy number of introduced sequences that are being introduced into the cells. In some embodiments, a multimeric protein is characterized by generating a pharmacological profile by measuring the activity of at least 2, 5, 10, 50, 100, 250, 500, 1000, 2000, 5000, or at least 10,000 compounds against the multimeric protein. These pharmacological profiles of each cell line are compared with each other. If the pharmacological profiles are identical, the composition of the multimeric proteins are predicted to be the same. If the pharmacological profiles differ, the composition of the multimeric proteins are predicted to be different.
In some embodiments, the invention provides panels of cell lines, wherein each panel comprises a plurality of cell lines each of which expresses a different multimeric protein as defined by different pharmacological profiles as discussed above, wherein the different cell lines were generated using the same protocol and the same host cell line. In some embodiments, substantially same protocols for cell culture could be used. In some embodiments, the cell lines of the panel could be processed in parallel or at different times but using consistent or similar cells, conditions or protocols.
In some embodiments, the methods can be applied to clones produced from different host cell lines. In certain specific embodiments, the host cell lines differ in their gene expression profile. In these embodiments, the different cell lines can be used to characterize the effect of specific co-factors or endogenously provided factors on the formation of certain forms of a multimeric protein of interest.
In particular embodiments, the activity of a multimeric protein can be tested by contacting the cell that expresses the multimeric protein with a compound that activates or inhibits the multimeric protein.
In some embodiments, the activity profile of a multimeric protein under certain conditions is determined. Without being bound by theory, it is believed that a same condition can have different effects on different forms of a multimeric protein. For example, a plurality of different conditions are tested for their effect on the multimeric protein. Exemplary conditions include: temperature, ion concentration in the cell media, CO2 concentration, cell density, synchronization of cell cycle, pH, acidity, carbonation, atmospheric conditions, percent carbon dioxide, shaking, stirring, UV exposure, activity or concentration of metabolites, nutrients, serum, amino acids, sugars, carbohydrates, proteins, lipids, detergents, growth factors, co-factors, vitamins, mutagens, chemicals, compounds or trace metals. The activity profiles can then be used to deduce the composition of the multimeric protein.
In some embodiments, the pharmacological profile of a multimeric protein is determined. For example, a plurality of different compounds is tested for their effect on a multimeric protein. Exemplary compounds include compounds that are known to modulate the protein or a protein of the same class or family, compounds known to have side-effects in clinical studies, compounds with clinical efficacy, compounds that may be pharmacologically active, compounds of combinatorial compound libraries, chemical compounds, synthetic compounds, natural compounds, peptides, lipids, detergents, mutagens, fluorescent compounds or polymers. The pharmacological profiles can then be used to deduce the composition of the multimeric protein.
The invention makes possible the production of multiple cell lines expressing a protein of interest. Clonal cell lines of the invention will have different absolute and relative levels of such expression. A large panel of such clones can be screened for activity with a number of known reference compounds. In this way, each isolated cell line will have a “fingerprint” of responses to test compounds which represent the activities of differential functional expression of the protein. The cell lines can then be grouped based on the similarity of such responses to the compounds. At least one cell line representing each functionally distinct expression profile can be chosen for further study. A collection of these cell lines can then be used to screen a large number of compounds. In this way, compounds which selectively modulate one or more of the corresponding distinct functional forms of the protein may be identified. These modulators can then be tested in secondary assays or in vivo models to determine which demonstrate activity in these assays or models. In this connection, the modulators would be used as reference compounds to identify which corresponding functional forms of the protein may be present or play a role in the secondary assay or model system employed. Such testing may be used to determine the functional forms of a protein that may exist in vivo as well as those that may be physiologically relevant. These modulators could be used to discern which of the functionally distinct forms are involved in a particular phenotype or physiological function such as disease.
In some embodiments, the present invention provides a method for generating an in-vitro-correlate (“IVC”) for an in vivo physiological property of interest. An IVC is generated by establishing the activity profile of a compound with an in vivo physiological property on different proteins, e.g., a profile of the effect of a compound on the physiological property of different proteins. This activity profile is representative of the in vivo physiological property and thus is an IVC of a fingerprint for the physiological property.
In some embodiments, the in-vitro-correlate is an in-vitro-correlate for a negative side effect of a drug. In other embodiments, the in-vitro-correlate is an in-vitro-correlate for a beneficial effect of a drug.
In some embodiments, the IVC can be used to predict or confirm one or more physiological properties of a compound of interest. The compound may be tested for its activity against different proteins and the resulting activity profile is compared to the activity profile of IVCs that were generated as described herein. The physiological property of the IVC with the activity profile most similar to the activity profile of a compound of interest is predicted to be and/or confirmed to be a physiological property of the compound of interest.
In some embodiments, an IVC is established by assaying the activities of a compound against different proteins or biological pathways, or combinations thereof. Similarly, to predict or confirm the physiological activity of a compound, the activities of the compound can be tested against different proteins or biological pathways, or combinations thereof.
In some embodiments, the methods of the invention can be used to determine and/or predict and/or confirm to what degree a particular physiological effect is caused by a compound of interest. In certain embodiments, the methods of the invention can be used to determine and/or predict and/or confirm the tissue specificity of a physiological effect of a compound of interest.
The cell lines for use with the present methods can be engineered using gene activation (see, e.g., PCT Application Publication WO/1994/012650) or introduction of a transgene. Cells expressing a protein of interest can be identified using molecular beacons or fluorogenic oligonucleotides (see, e.g., U.S. Pat. No. 6,692,965 by Shekdar et al. issued Feb. 17, 2004 and International Application No. PCT/US2005/005080 published as WO/2005/079462). In some embodiments, cells or cell lines are engineered to express a protein subunit that is part of a multimeric protein. In certain, more specific, embodiments, cells or cell lines are engineered to express at least 2, at least 3, at least 4, at least 5, at least 6, at least 7, at least 8, at least 9, at least 10, at least 11, or at least 12 subunits of a multimeric protein. In particular embodiments, an activity profile is generated against a plurality of cell lines wherein each has been engineered to express a different combination of subunits of a multimeric protein.
In some embodiments, cells or cell lines to be used with the methods for generating an IVC are cells or cell lines as described herein, e.g., cells or cell lines with a substantially constant physiological property, cells or cell lines that express a protein of interest which does not comprise a protein tag, or cells or cell lines having a Z′ factor of at least 0.4 in a functional assay, or cells or cell lines cultured in the absence of selective pressure, or any combinations thereof. In some embodiments, different cells or cell lines to be used are maintained in parallel under substantially identical culture conditions. Robotic methods described herein can be used to maintain and manipulate the cells or cell lines for generating an IVC. In some embodiments, the invention provides a cell or cell line for generating an IVC, wherein the cell or cell line is cultured in the absence of selective pressure and wherein the expression of at least one protein of the cell does not vary by more than 1%, 5%, 10%, 15%, 20%, 25% 30% 35% or 40% over 3 months. In some embodiments the expression of the at least one protein does not vary by more than 1%, 5%, 10%, 15%, 20%, 25% 30% 35% or 40% over 4, 5, 6 or more months.
In more specific embodiments, the activity profile of a compound of interest is established by testing the activity of the compound in a plurality of in vitro assays using cell lines that are engineered to express a multimeric protein, wherein at least two cell lines express different multimeric proteins. In particular embodiments, the different multimeric proteins are different combinations of subunits of a multimeric protein. In certain more specific embodiments, an IVC is generated by testing a compound of interest against at least 0.01%, 0.05%, 0.1%, 0.5%, 1%, 5%, 10%, 20%, 25%, 50%, 75%, 80%, 90%, 95%, 98%, or at least 99% of possible subunit combinations of a multimeric protein. In even more specific embodiments, all possible subunit combinations are tested. In certain embodiments, at least 5, 10, 25, 50, 100, 150, 200, 250, 500, 1000, 2500, 5000, 7500, or at least 10000 subunit combinations are tested.
In some embodiments, different multimeric proteins of different cell lines are different forms of a multimeric protein, wherein different forms differ in the combination, stoichiometry, splicing, and/or post-translation modification of their subunits, including proteolysis.
In some embodiments, testing of failed and successful candidate drugs against a panel representing multiple functional forms of a target or related target can be used to correlate specific targets to adverse or undesired side-effects or therapeutic efficacy observed in the clinic. This information may be used to select well defined targets in HTS or during compound development towards drugs with maximal desired and minimal off-target activity.
In certain, more specific, embodiments, an IVC of a compound is generated by testing the compound against different cell lines that express different subunit combinations of multimeric proteins. In more, specific embodiments such multimeric proteins include, but are not limited to receptor protein complexes such as GABAA; NaV; GABAB; ENaC; sweet receptor; umami receptor and other multimeric proteins described herein.
In certain embodiments, an IVC is generated using ENaC, GABAA, NaV, a sweet taste receptor, an umami taste receptor, a bitter taste receptor, CFTR, or GCC. As described below the IVC of a compound may represent the effect of the compound on a particular physiological parameter. In certain embodiments, the physiological parameter is measured using functional magnetic resonance imaging (“fMRI”). Other imaging methods can also be used. Such other imaging methods include Computed tomography (CT); Computed Axial Tomography (CAT) scanning; diffuse optical imaging (DOI); diffuse optical tomography (DOT); event-related optical signal (EROS); near infrared spectroscopy (NIRS); magnetic resonance imaging (MRI); magnetoencephalography (MEG); positron emission tomography (PET) and single photon emission computed tomography (SPECT). In certain embodiments, if the IVC represents an effect of the compound on the central nervous system (“CNS”), an IVC may be established that correlates with an fMRI pattern in the CNS. IVCs may be generated that correlate with activity of compounds in various tests and models, including human and animal (such as livestock and pets) testing models. Human diseases and disorders are listed, e.g., in The Merck Manual 18th Edition (Hardcover) Mark H. Beers (Author) Robert S. Porter (Editor), Thomas V. Jones (Editor). Mental diseases and disorders are listed, e.g., in Diagnostic and Statistical Manual of Mental Disorders DSM-IV-TR Fourth Edition (Text Revision) by American Psychiatric Association (Corporate Author).
IVCs generated using GABA may be for a physiological effect of a compound on CNS disorder, anxiety, sedation, post-traumatic stress disorder (PTSD), memory, learning, autism, epilepsy, alcoholism, mood disorders, CNS function, CNS physiology, CNS development, and/or aging of the CNS. The physiological effect can be an increase of decrease of at least one symptom of the disease.
IVCs for GABA may also be generated for an emotion, mood, state of mind, feeling, sensation of, or perception, including: happiness, satisfaction, euphoria, mania, excitement, anticipation, complacency, anxiety, depression, anger, fear, terror, doubt, love, hate, ambivalence, apathy, lethargy, guilt, devotion, sadness, unhappiness, grumpiness, irritability, drive, motivation, aggressiveness, hostility, rage, arrogance, self-assuredness or a lack of it, confidence, lack of confidence, uneasiness, hesitation; a positive, negative, cooperative, uncooperative, helpful or unhelpul attitude; a sense of freedom, well being, accomplishment, adequacy, inadequacy, or limitation; feelings of being attractive, unattractive, sexy, not sexy, likeable, dislikable, lovable, unlovable, desirable, or undesirable; feelings of loneliness or of being included/inclusiveness; of belonging or not belonging to a social group; feelings of being trapped, tricked, manipulated, misguided, helped, encouraged or discouraged; feelings of considering committing suicide; feelings of taking a risk, committing a crime, breaking the law, avoiding responsibility; or feelings of committing murder.
IVCs for GABA may also be generated for sensory stimulations that stimulate a positive or negative mood. Positive sensory stimulations may include odor sensations, such as sea breeze, forest, food, etc. In some embodiments, IVCs for GABA may be generated for sedation or sleep, including restful, uninterrupted, deep, light or REM sleep, restfulness, lack of sleep, insomnia, sleep disruption, sleep disturbances, or walking, talking or eating in one's sleep; memory, learning, interpretation, analysis, thinking, remembering, placing, making associations, recalling past events, short term memory, long term memory or cognition; alcohol dependence or addiction or alcoholism; CNS indications, chronic pain, epilepsy, convulsants, addiction, dependence; endocrine/hormonal indications, eye blink conditioning paradigms, lung cancer, prostate cancer, breast cancer and other cancers and carcinomas; glucose metabolic response, anoxia, prostaglandin induced thermogenesis, cardiac baro-receptor reflex and other reflex abnormalities; and mental disorders including autism.
An IVC generated using a bitter taste receptor may be for a physiological effect on obesity, sugar absorption, glucagon-like peptide (GLP) secretion, or blood glucose regulation. The physiological effect may be upregulation or downregulation of appetite, overall nutrition, degree or rate of nutrient absorption, obesity (gain or loss), degree or rate of sugar absorption, GLP secretion, or blood glucose regulation. Alternatively, the IVC may also be correlated to bitter taste in food and/or drug.
In some embodiments, IVCs using bitter taste receptors may be generated for activity in the gut (e.g., GLP secretion or the secretion of other gut hormones), blood-glucose control or balance, diabetes, feeding, starvation, appetite, nutrient absorption, weight loss, energy. In other embodiments, IVCs using bitter taste receptors may be generated for desired or undesired bitter taste/off-taste of beverage or food ingredients or drugs, including over the counter drugs and different stereoisoforms of drugs; for food preferences; for eating disorders (e.g. bulimia, anorexia or dieting); for the sensory or taste perception of compounds; or for quality control of the taste or bitter taste receptor or GPCR activity of beverage or food ingredients or drugs. In other embodiments, IVCs using bitter taste receptors may be generated for: neuronal firing or CNS activity in response to active compounds; nausea, vomiting (including nausea caused by drugs or other compounds, e.g., chemotherapy-induced nausea and vomiting (CINV)); activity of compounds at non-bitter GPCRs; bitter or bitter modulating compounds that are active in the oral cavity but not elsewhere (e.g., not active in the gut), and vice versa. In certain embodiments, compounds that activate, inhibit, or modulate bitter taste receptors in a tissue-specific manner can be used to modulate blood glucose levels, glucose absorption, and/or to prevent vomiting or CINV, where modulating activity is desirable in the gut but not in the oral cavity. In certain embodiments, bitter modulating compounds that are only active in the oral cavity can be used in flavor applications where physiological activity in the gut is not desired.
IVCs generated using a sweet taste receptor may be for a physiological effect on appetite, nutrition, nutrient absorption, obesity, sugar absorption, GLP secretion, or blood glucose regulation. The physiological effect may be upregulation or downregulation of appetite, overall nutrition, degree or rate of nutrient absorption, obesity (gain or loss), degree or rate of sugar absorption, or GLP secretion, or blood glucose regulation.
IVCs using a sweet taste receptor may be generated for the following: lingering/long lasting/extended duration/off- or after-taste of sweet compounds including natural and artificial high intensity sweeteners (e.g. saccharin, aspartame, cyclamate, mogroside, stevia and its components, acesulfame K, neotame, sucralose and mixtures thereof); for food preferences; for eating disorders (e.g. bulimia, anorexia or dieting); activity in the gut (e.g. GLP secretion or the secretion of other gut hormones), blood-glucose control or balance, diabetes, feeding, starvation, appetite, nutrient absorption, weight loss or energy; desired, undesired or off-taste of beverage, food or drug ingredients, including over the counter drugs and different stereoisoforms of drugs; sensory or taste perception of compounds; neuronal firing or CNS activity in response to active compounds; nausea/vomiting, including nausea caused by drugs or other compounds (e.g. CINV); quality control of the taste or GPCR triggering activity of beverage, food or drug ingredients; sweet or sweet modulating compounds that are active in the oral cavity but not elsewhere (e.g., not active in the gut), and vice versa. In certain embodiments, compounds that activate, inhibit, or modulate sweet taste receptors in a tissue-specific manner can be used to modulate blood glucose levels, glucose absorption, and/or to prevent vomiting or CINV, where modulating activity is desirable in the gut but not in the oral cavity. In certain embodiments, bitter modulating compounds that are only active in the oral cavity can be used in flavor applications where physiological activity in the gut is not desired.
If an umami taste receptor is used to generate an IVC, the IVC may be for a physiological effect on appetite, nutrition, nutrient absorption, obesity, sugar absorption, GLP secretion, blood glucose regulation or amino acid absorption. The physiological effect may be upregulation or downregulation of appetite, overall nutrition, degree or rate of nutrient absorption, obesity (gain or loss), degree or rate of sugar absorption, or GLP secretion, or blood glucose regulation.
IVCs using an umami taste receptor can be generated for the following: food preferences; eating disorders (e.g. bulimia, anorexia or dieting); activity in the gut (e.g. GLP secretion or the secretion of other gut hormones), blood-glucose control or balance, diabetes, feeding, starvation, appetite, nutrient absorption, weight loss or energy; desired, undesired or off-taste of beverage, food or drug ingredients, including over the counter drugs and different stereoisoforms of drugs; sensory or taste perception of compounds; neuronal firing or CNS activity in response to active compounds; nausea/vomiting, including nausea caused by drugs or other compounds (e.g. CINV); quality control of the taste or GPCR triggering activity of beverage, food or drug ingredients; umami or umami modulating compounds that are active in the oral cavity but not elsewhere (e.g., not active in the gut), and vice versa. In certain embodiments, compounds that activate, inhibit, or modulate umami taste receptors in a tissue-specific manner can be used to modulate blood glucose levels, glucose absorption, and/or to prevent vomiting or CINV, where modulating activity is desirable in the gut but not in the oral cavity. In certain embodiments, umami modulating compounds that are only active in the oral cavity can be used flavor applications where physiological activity in the gut is not desired.
An IVC generated using ENaC may be for a physiological effect of a compound on COPD (chronic obstructive pulmonary disease), CF (cystic fibrosis), fertility, IBS (irritable bowel syndrome), Crohn's disease, pulmonary edema or hypertension. The physiological effect can be worsening of the disease or reduction or amelioration of at least one symptom of the disease. The IVC may also represent different salt tastes of a compound.
IVCs using ENaC can also be generated for the following: food preferences; eating disorders (e.g. bulimia, anorexia or dieting); regulation, secretion, quality, clearance, production, viscosity, or thickness of mucous; water absorption, retention, balance, passing, or transport across epithelial tissues (especially lung, kidney, vascular tissues, eye, gut, small intestine and large intestine); neuronal firing or CNS activity in response to active compounds; pulmonary indications; gastrointestinal indications such as bowel cleansing, Irritable Bowel Syndrome (IBS), drug-induced (i.e. opioid) constipation, constipation/CIC of bedridden patients, acute infectious diarrhea, E. coli, cholera, viral gastroenteritis, rotavirus, modulation of malabsorption syndromes, pediatric diarrhea (viral, bacterial, protozoan), HIV, or short bowel syndrome; fertility indications such as sperm motility or sperm capacitation; female reproductive indications, cervical mucus/vaginal secretion viscosity (i.e. hostile cervical mucus); contraception, such as compounds that negatively affect sperm motility or cervical mucous quality relevant for sperm motility; or dry mouth, dry eye, glaucoma or runny nose.
IVCs using ENaC can also be generated for sensory or taste perception of compounds. In particular, the IVC can be for salt taste, such as taste of magnesium, sodium, potassium, and/or calcium salts. The salts may have different counter ions, such as sulfate, chloride or other halides, bromide, phosphate, lactate and others. In a particular embodiment, the salt is potassium chloride or potassium lactate. In certain embodiments, the IVC represents the taste perception of a combination of different salts.
An IVC generated using CFTR may be for a physiological effect of a compound on COPD (chronic obstructive pulmonary disease), CF (cystic fibrosis), fertility, IBS (irritable bowel syndrome), Crohn's disease, pulmonary edema or hypertension. The physiological effect can be an increase or decrease of at least one symptom of the disease.
IVCs using CFTR can also be generated for the following: regulation, secretion, quality, clearance, production, viscosity, or thickness of mucous; water absorption, retention, balance, passing, or transport across epithelial tissues (especially of lung, kidney, vascular tissues, eye, gut, small intestine, large intestine); sensory or taste perception of compounds; neuronal firing or CNS activity in response to active compounds; pulmonary indications; gastrointestinal indications such as bowel cleansing, Irritable Bowel Syndrome (IBS), drug-induced (i.e. opioid) constipation, constipation/CIC of bedridden patients, acute infectious diarrhea, E. coli, cholera, viral gastroenteritis, rotavirus, modulation of malabsorption syndromes, pediatric diarrhea (viral, bacterial, protozoan), HIV, or short bowel syndrome; fertility indications such as sperm motility or sperm capacitation; female reproductive indications, cervical mucus/vaginal secretion viscosity (i.e. hostile cervical mucus); contraception, such as compounds that negatively affect sperm motility or cervical mucous quality relevant for sperm motility; dry mouth, dry eye, glaucoma, runny nose; or endocrine indications, i.e. pancreatic function in CF patients.
An IVC generated using NaV may be for a physiological effect on pain. The physiological effect can be increase or decrease of the pain.
IVCs using NaV can also be generated for the following: pain (including chronic pain, acute pain, cardiac pain, muscle pain, bone pain, organ pain, fatigue, pain caused by overstimulation, abrasion, bodily harm or internal damage, pain from cancer, pain from physical injury, perceived pain, phantom pain, and debilitating pain); generation or propagation of action potentials, neuronal signaling, or transmission of neuronal information; or muscle or cardiac indications or for the activity of compounds on muscle or cardiac muscle in vivo.
An IVC generated using GCC can be for the following: gastrointestinal indications including: constipation, IBS (irritable bowel syndrome), including IBS-C (constipation), IBS-D (diarrhea) or IBS-M (mixed), chronic idiopathic constipation, opioid or drug induced constipation, constipation in bedridden or geriatric patients, acute infectious diarrhea (e.g. mediated by bacteria, E. coli, salmonella, cholera, especially traveler's diarrhea), viral gastroenteritis, clinical indications of rotavirus, malabsorption syndromes, pediatric diarrhea (viral, bacterial, protozoan), short bowel syndrome, colitis (collagenous, lymphocytic), Crohn's disease, UC, diverticulitis, cystic fibrosis or ulcers including peptic ulcers; regulation/modulation of mucosal and/or epithelial fluid absorption and secretion; pulmonary indications such as cystic fibrosis, kidney function, cardiac fibrosis, cardiac hypertrophy, hypertension, eye disorders (i.e. autosomal dominant retinitis pigmentosa and Leber congenital amaurosis), growth disorders, short stature, stroke and other vascular injury; CNS indications such as memory or depression; or inflammatory disorders (i.e. rheumatoid arthritis).
Odorant receptors may be used to generate IVCs for sensory stimulations that stimulate a positive or negative mood. Sensory stimulations that stimulate a positive mood may include pleasant odors such as sea breeze, forest scents or food scents. Sensory stimulations that stimulate a positive mood may include unpleasant odors. IVCs may be generated for sensory stimulations that stimulate the following positive or negative emotions: happiness, satisfaction, euphoria, mania, excitement, anticipation, complacency, anxiety, depression, anger, fear, terror, doubt, love, hate, ambivalence, apathy, lethargy, guilt, devotion, sadness, unhappiness, grumpiness, irritability, drive, motivation, aggressiveness, hostility, rage, arrogance, self-assuredness or a lack of it, confidence, lack of confidence, uneasiness, hesitation; a positive, negative, cooperative, uncooperative, helpful or unhelpul attitude; a sense of freedom, well being, accomplishment, adequacy, inadequacy, or limitation; feeling of being attractive, unattractive, sexy, not sexy, likeable, dislikable, lovable, unlovable, desirable or undesirable; feelings of loneliness or of being included/inclusiveness, belonging or not belonging to a social group; feelings of being trapped, tricked, manipulated, misguided, helped, encouraged or discouraged; feelings of considering committing suicide; feelings of taking a risk, committing a crime, breaking the law, avoiding responsibility; or feelings of committing murder.
Acetylcholine receptors may also be used to generate IVCs for sensory stimulations that stimulate a positive or negative mood. Sensory stimulations include, but are not limited to, scents. IVCs may be generated for sensory stimulations that stimulate the following positive or negative emotions, moods, states of mind, feelings, sensations or perceptions, including: happiness, satisfaction, euphoria, mania, excitement, anticipation, complacency, anxiety, depression, anger, fear, terror, doubt, love, hate, ambivalence, apathy, lethargy, guilt, devotion, sadness, unhappiness, grumpiness, irritability, drive, motivation, aggressiveness, hostility, rage, arrogance, self-assuredness or a lack of it, confidence, lack of confidence, uneasiness, hesitation; a positive, negative, cooperative, uncooperative, helpful or unhelpul attitude; a sense of freedom, well being, accomplishment, adequacy, inadequacy, or limitation; feeling of being attractive, unattractive, sexy, not sexy, likeable, dislikable, lovable, unlovable, desirable or undesirable; feelings of loneliness or of being included/inclusiveness, belonging or not belonging to a social group; feelings of being trapped, tricked, manipulated, misguided, helped, encouraged or discouraged; feelings of considering committing suicide; feelings of taking a risk, committing a crime, breaking the law, avoiding responsibility; or feelings of committing murder.
IVCs for acetylcholine receptors may also be generated for physiological effects of a compound on a CNS disorder, anxiety, sedation, PTSD, memory, learning, autism, epilepsy, alcoholism, mood disorders, and/or CNS function, CNS physiology, CNS development, and/or aging of the CNS. The physiological effect can be increase or decrease of at least one symptom of the disease. IVCs generated using acetylcholine can also be generated for the following: sedation or sleep, including restful, uninterrupted, deep, light or REM sleep, restfulness, lack of sleep, insomnia, sleep disruption, sleep disturbances, or walking, talking or eating in one's sleep; memory, learning, interpretation, analysis, thinking, remembering, placing, making associations, recalling past events, short term memory, long term memory or cognition; alcohol dependence or addiction or alcoholism; CNS indications, chronic pain, epilepsy, convulsants, addiction, dependence; endocrine/hormonal indications, eye blink conditioning paradigms, lung cancer, prostate cancer, breast cancer and other cancers and carcinomas; glucose metabolic response, anoxia, prostaglandin induced thermogenesis, cardiac baro-receptor reflex and other reflex abnormalities; and mental disorders including autism.
In some embodiments, cells or cell lines for use with the methods are engineered to express one or more proteins as set forth in Tables 6 and 7-22 herein.
In some embodiments, an IVC represents a physiological property of a compound in a tissue of an organism, an organ of an organism, an extracellular matrix of an organism, a system of an organism (e.g., the immune system of an organism), or a whole organism. The organism may be a vertebrate. The organism may be a mammal. In more specific embodiments, the organism is a mouse, rat, dog, cat, cattle, horse, donkey, goat, monkey, or human. The physiological property can be an effect on a particular cell type, tissue, organ, or organ system. For example, the physiological property can be an effect on mammalian tissue, healthy tissue, tissue, diseased tissue, cancer tissue, embryonic tissue, adult tissue, transplanted tissue, organ tissue, liver tissue, neuronal tissue, gastrointestinal tissue, muscle tissue, fat tissue, skin, urogenital tissue, neuronal tissue, the central nervous system, cardiovascular tissue, the endocrine system, skeletal tissue, bone tissue, bone, the immune system, an organ, a cell or a specialized cell, as well as any other cells disclosed herein. In some embodiments, the physiological property is tissue protective activity, anti-inflammatory activity, neuro-stimulatory or has an activity similar to the activity of substances or compounds including but not limited to: adamantane antivirals, adrenergic bronchodilators, agents for hypertensive emergencies, agents for pulmonary hypertension, amebicides, analgesic combinations, analgesics, androgens and anabolic steroids, angiotensin II inhibitors, anorexiants, antacids, antihelmintics, anti-angiogenic ophthalmic agents, anti-infectives, antianginal agents, antiarrhythmic agents, antiasthmatic combinations, antibiotics/antineoplastics, anticholinergic antiemetics, anticholinergic antiparkinson agents, anticholinergic bronchodilators, anticholinergics/antispasmodics, anticoagulants, anticonvulsants, antidepressants, antidiabetic agents, antidiabetic combinations, antidiarrheals, antidotes, antiemetic/antivertigo agents, antifungals, antigout agents, antihistamines, antihyperlipidemic agents, antihyperlipidemic combinations, antihypertensive combinations, antihyperuricemic agents, antimalarial agents, antimalarial combinations, antimalarial quinolines, antimetabolites, antimigraine agents, antineoplastic detoxifying agents, antineoplastic interferons, antineoplastic monoclonal antibodies, antineoplastics, antiparkinson agents, antiplatelet agents, antipseudomonal penicillins, antipsoriatics, antipsychotics, antirheumatics, antiseptic and germicides, antitoxins and antivenins, antituberculosis agents, antituberculosis combinations, antitussives, antiviral agents, antiviral combinations, antiviral interferons, anxiolytics, sedatives, and hypnotics, bile acid sequestrants, bronchodilators, cardiac stressing agents, chelating agents, cholinergic muscle stimulants, CNS stimulants, coagulation modifiers, contraceptives, decongestants, digestive enzymes, diuretics, dopaminergic antiparkinsonism agents, drugs used in alcohol dependence, expectorants, factor Xa inhibitors, fatty acid derivative anticonvulsants, functional bowel disorder agents, gallstone solubilizing agents, general anesthetics, genitourinary tract agents, GI stimulants, glucose elevating agents, glycoprotein platelet inhibitors, growth hormone receptor blockers, hematopoietic stem cell mobilizer, heparin antagonists, hormone replacement therapy, hormones/antineoplastics, immunosuppressive agents, impotence agents, in vivo diagnostic biologicals, incretin mimetics, inotropic agents, laxatives, leprostatics, local injectable anesthetics, lung surfactants, lymphatic staining agents, lysosomal enzymes, mucolytics, muscle relaxants, mydriatics, ophthalmic glaucoma agents, ophthalmic lubricants and irrigations, spermicides, vasodilators, or vasopressors.
In some embodiments, an IVC represents the physiological effect of a compound of interest on a virus, bacterium, fungus, or yeast. Such compounds are useful, e.g., as antibiotics against viruses, bacteria, fungi, and/or yeasts.
The assay to test and/or confirm the activity of a compound of interest against a particular multimeric protein of interest depends on the biological activity of the multimeric protein. Any assay to be used with the methods of the invention can be conducted in high throughput format.
Exemplary proteins, their references, and possible assays are set forth in the following Table (Table 5). These examples are non-limiting, in that the assays listed may be used for targets in addition to those listed, and the targets listed can be tested by other assays than those listed.
The activity profile of a compound of interest and a landmark activity profile may be compared through computation of a correlation between the activity profiles, such as but not limited to computing a measure of similarity between the activity profiles. The landmark activity profile may be one of a group of activity profiles in a database. The landmark activity profile may be a historical profile. The database of landmark activity profiles can be stored on a computer readable storage medium. In specific embodiments, the database contains at least 10 landmark activity profiles, at least 50 landmark activity profiles, at least 100 landmark activity profiles, at least 500 landmark activity profiles, at least 1,000 landmark activity profiles, at least 10,000 landmark activity profiles, or at least 50,000 landmark activity profiles, each landmark activity profile containing measured amounts of at least 2, at least 10, at least 100, at least 200, at least 500, at least 1,000, at least 2000, at least 2500, at least 7500, at least 10,000, at least 20,000, at least 25,000, or at least 35,000 components. The activity profile of the compound of interest can comprise measured amounts representing an effect of the compound of interest on the biological activity of different multimeric proteins, such as a first protein subunit and a second protein subunit. A landmark activity profile provides an in vitro correlate for a known physiological property of a previously characterized compound. The physiological property can be a pharmacological property such as, but not limited to, a negative side effect of a drug or a beneficial effect of a drug. Each landmark activity profile can comprise measured amounts representing the effect of a respective previously characterized compound on the biological activity of different multimeric proteins, such as the first protein subunit and the second protein subunit of a multimeric protein. In some embodiments, a correlation can be computed between the activity profile of a compound of interest and each landmark activity profile of a plurality of landmark activity profiles stored in a database. The correlation can be computed by comparing a measured amount in the activity profile of a compound of interest representing an effect of the compound of interest on the biological activity of a given multimeric protein to the corresponding measured amount in the landmark activity profile representing an effect of the previously characterized compound on the biological activity of the same multimeric protein. The activity profile of a compound of interest can be deemed to correlate with a landmark activity profile if the measured amounts in the landmark activity profile are within about 2%, about 5%, about 8%, about 10%, about 12%, about 15%, about 20%, about 25%, about 30%, or about 35% of the measured amounts in the activity profile of the compound of interest.
The activity profile of a compound of interest can be deemed to be most similar to a landmark activity profile if a measure of similarity between the activity profile of the compound of interest and the landmark activity profile is above a predetermined threshold. In specific embodiments, the predetermined threshold can be determined as the value of the measure of similarity which indicates that the measured amounts in a landmark activity profile are within about 2%, about 5%, about 8%, about 10%, about 12%, about 15%, about 20%, about 25%, about 30%, or about 35% of the measured amounts in the activity profile of the compound of interest.
In some embodiments, the activity profile of a compound of interest can be expressed as a vector p,
p=[p1, . . . pi, . . . pn]
where pi is the measured amount of the i'th component, for example, the effect of the compound of interest on the i'th biological activity of a given multimeric protein. In specific embodiments, n is more than 2, more than 10, more than 100, more than 200, more than 500, more than 1000, more than 2000, more than 2500, more than 7500, more than 10,000, more than 20,000, more than 25,000, or more than 35,000. Each landmark activity profile also can be expressed as a vector p. In computing a correlation, the measured amount of the i'th component in the vector representing the activity profile for the compound of interest can be compared to the corresponding measured amount of the i'th component of the vector representing a landmark activity profile, for each component i=1 . . . n. However, there are many ways in which a correlation can be computed. Indeed, any statistical method in the art for determining the probability that two datasets are related may be used in accordance with the methods of the present invention in order to identify whether there is a correlation between the activity profile of a compound of interest and a landmark activity profile. For example, the correlation between the activity profile (pi
The correlation can also be computed based on ranks, where xi and yi are the ranks of the values of the measured amounts in ascending or descending numerical order. See for example, Conover, Practical Nonparametric Statistics, 2nd ed., Wiley, (1971). Shannon mutual information also can be used as a measure of similarity. See for example, Pierce, An Introduction To Information Theory: Symbols, Signals, and Noise, Dover, (1980), which is incorporated by reference herein in its entirety.
Various classifiers known in the art can be trained according to the methods described in this application, and used to classify a compound of interest as to a physiological property, such as but not limited to a pharmacological property. Algorithms can be used to produce classifiers capable of predicting a physiological property of a compound of interest using an activity profile of the compound of interest. Exemplary classifiers are described above. In some embodiments, the classifier can be trained using the measured amounts in the landmark activity profile of a previously characterized compound and the known physiological property associated with that previously characterized compound.
The classifier may be an algorithm used for classification by applying a non-supervised or supervised learning algorithm to evaluate the measured amounts in the landmark activity profile of a previously characterized compound and the known physiological property associated with that previously characterized compound. Any standard non-supervised or supervised learning technique known in the art can be used to generate a classifier. Below are non-limiting examples of non-supervised and supervised algorithms known in the art. Given the disclosure in this application, one of skill in the art will appreciate that other pattern classification or regression techniques and algorithms may be used for the classifier and the present invention encompasses all such techniques.
Neural networks. Neural networks (e.g., a two-stage regression or classification decision rule) are described hereinabove.
Clustering. In some embodiments, the classifier is learned using clustering. In some embodiments, select components i of the vectors representing the landmark activity profiles are used to cluster the activity profiles. In some embodiments, prior to clustering, the measured amounts are normalized to have a mean value of zero and unit variance.
Landmark activity profiles that exhibit similar patterns of measured amounts across the training population will tend to cluster together. A particular combination of measured amounts of components i can be considered to be a good classifier in this aspect of the invention when the vectors cluster into the physiological property. Clustering is described on pages 211-256 of Duda 1973. As described in Section 6.7 of Duda 1973, the clustering problem is described as one of finding natural groupings in a dataset. To identify natural groupings, two issues are addressed. First, a way to measure similarity (or dissimilarity) between two activity profile is determined. This metric (similarity measure) is used to ensure that the activity profiles in one cluster are more like one another than they are to other activity profiles. Second, a mechanism for partitioning the data into clusters using the similarity measure is determined.
Similarity measures are discussed in Section 6.7 of Duda 1973, where it is stated that one way to begin a clustering investigation is to define a distance function and to compute the matrix of distances between pairs of activity profiles. If distance is a good measure of similarity, then the distance between activity profiles in the same cluster will be significantly less than the distance between activity profiles in different clusters. However, as stated on page 215 of Duda 1973, clustering does not require the use of a distance metric. For example, a nonmetric similarity function s(x, x′) can be used to compare two vectors x and x′. Conventionally, s(x, x′) is a symmetric function whose value is large when x and x′ are somehow “similar”. An example of a nonmetric similarity function s(x, x′) is provided on page 216 of Duda 1973
Other aspects of clustering are further discussed hereinabove.
Principal component analysis (“PCA”). In some embodiments, the classifier is learned using principal component analysis. PCA is discussed hereinabove.
In one approach to using PCA to learn a classifier, vectors representing landmark activity profiles can be constructed in the same manner described for clustering above. In fact, the set of vectors, where each vector represents a landmark activity profile, can be viewed as a matrix. In some embodiments, this matrix is represented in a Free-Wilson method of qualitative binary description of monomers (Kubinyi, 1990, 3D QSAR in drug design theory methods and applications, Pergamon Press, Oxford, pp 589-638, hereby incorporated by reference herein), and distributed in a maximally compressed space using PCA so that the first principal component (PC) captures the largest amount of variance information possible, the second principal component (PC) captures the second largest amount of all variance information, and so forth until all variance information in the matrix has been considered.
Then, each of the vectors, where each vector represents a member of the training population (such as the landmark activity profiles), is plotted. Many different types of plots are possible. In some embodiments, a one-dimensional plot is made. In this one-dimensional plot, the value for the first principal component from each of the members of the training population is plotted. In this form of plot, the expectation is that activity profiles corresponding to a physiological property will cluster in one range of first principal component values and profiles corresponding to another physiological property will cluster in a second range of first principal component values.
In some embodiments, the members of the training population are plotted against more than one principal component. For example, in some embodiments, the members of the training population are plotted on a two-dimensional plot in which the first dimension is the first principal component and the second dimension is the second principal component.
Nearest neighbor analysis. Nearest neighbor analysis is described hereinabove.
Linear discriminant analysis. In some embodiments, the classifier is learned using linear discriminant analysis. Linear discriminant analysis (LDA) attempts to classify a subject into one of two categories based on certain object properties. In other words, LDA tests whether object attributes measured in an experiment predict categorization of the objects. LDA typically requires continuous independent variables and a dichotomous categorical dependent variable. In the present invention, the abundance values for the select combinations of vector components i across a subset of the training population serve as the requisite continuous independent variables. The trait subgroup classification (e.g., a physiological property) of each of the members of the training population serves as the dichotomous categorical dependent variable.
LDA seeks the linear combination of variables that maximizes the ratio of between-group variance and within-group variance by using the grouping information. Implicitly, the linear weights used by LDA depend on how the measured amount of a vector component i across the training set separates in the groups of the physiological property. In some embodiments, LDA is applied to the data matrix of the members in the training population. Then, the linear discriminant of each member of the training population is plotted. Ideally, those members of the training population representing a physiological property will cluster into one range of linear discriminant values (for example, negative) and those members of the training population representing another physiological property will cluster into a second range of linear discriminant values (for example, positive). The LDA is considered more successful when the separation between the clusters of discriminant values is larger. For more information on linear discriminant analysis, see Duda, Pattern Classification, Second Edition, 2001, John Wiley & Sons, Inc; and Hastie, 2001, The Elements of Statistical Learning, Springer, New York; and Venables & Ripley, 1997, Modern Applied Statistics with s-plus, Springer, New York, each of which is hereby incorporated by reference herein in its entirety.
Quadratic discriminant analysis. Quadratic discriminant analysis is described hereinabove.
Support vector machine. Support vector machine is described hereinabove.
Decision tree. Decision tree is described hereinabove.
Multivariate adaptive regression splines. Multivariate adaptive regression splines are described hereinabove.
Centroid classifier techniques. In one embodiment a nearest centroid classifier technique is used. Such a technique computes, for different physiological properties, a centroid given by the average measured amounts of vector components i in the training population (landmark activity profiles), and then assigns vector representing the compound of interest to the class whose centroid is nearest. This approach is similar to k-means clustering except clusters are replaced by known classes. An example implementation of this approach is the Prediction Analysis of Microarray, or PAM. See, for example, Tibshirani et al., 2002, Proceedings of the National Academy of Science USA 99; 6567-6572, which is hereby incorporated by reference herein in its entirety.
Regression. In some embodiments, the classifier is a regression classifier, such as a logistic regression classifier. Such a regression classifier includes a coefficient for each of the activity profiles used to construct the classifier. In such embodiments, the coefficients for the regression classifier are computed using, for example, a maximum likelihood approach. In such a computation, the measured amounts of vector components i are used.
Other methods to learn a classifier are further described hereinabove.
The present invention can be implemented as a computer program product that comprises a computer program mechanism embedded in a computer-readable storage medium. Further, any of the methods of the present invention can be implemented in one or more computers or other forms of apparatus. Examples of apparatus include but are not limited to, a computer, and a measuring device (for example, an assay reader or scanner). Further still, any of the methods of the present invention can be implemented in one or more computer program products. Some embodiments of the present invention provide a computer program product that encodes any or all of the methods disclosed in this application. Such methods can be stored on a CD-ROM, DVD, magnetic disk storage product, or any other computer-readable data or program storage product. Such computer readable storage media are intended to be tangible, physical objects (as opposed to carrier waves). Such methods can also be embedded in permanent storage, such as ROM, one or more programmable chips, or one or more application specific integrated circuits (ASICs). Such permanent storage can be localized in a server, 802.11 access point, 802.11 wireless bridge/station, repeater, router, mobile phone, or other electronic devices. Such methods encoded in the computer program product can also be distributed electronically, via the Internet or otherwise, by transmission of a computer data signal (in which the software modules are embedded) either digitally or on a carrier wave (it will be clear that such use of carrier wave is for distribution, not storage).
Some embodiments of the present invention provide a computer program product that contains any or all of the program modules shown in
In a specific embodiment, the computer program provides for outputting a result of the claimed method to a user, a user interface device, a computer readable storage medium, a monitor, a local computer, or a computer that is part of a network. Such computer readable storage media are intended to be tangible, physical objects (as opposed to carrier waves).
The present invention also provides methods for creating cell lines for proteins that have not been well characterized. For such proteins, there is often little information regarding the nature of their functional response to known compounds. Such a lack of established functional benchmarks to assess the activity of clones may be one challenge in producing physiologically relevant cell lines. The method described above provides a way to obtain physiologically relevant cell lines even for proteins that are not well characterized where there is a lack of such information. Cell lines comprising the physiologically relevant form of a protein may be obtained by pursuing clones representing a number or all of the functional forms that may result from the expression of genes comprising a protein.
The cells and cell lines of the invention may be used to identify the roles of different forms of the protein of interest in different pathologies by correlating the identity of in vivo forms of the protein with the identity of known forms of the protein based on their response to various modulators. This allows selection of disease- or tissue-specific modulators for highly targeted treatment of pathologies associated with the protein.
To identify a modulator, one exposes a cell or cell line of the invention to a test compound under conditions in which the protein would be expected to be functional and then detects a statistically significant change (e.g., p<0.05) in protein activity compared to a suitable control, e.g., cells that are not exposed to the test compound. Positive and/or negative controls using known agonists or antagonists and/or cells expressing the protein of interest may also be used. One of ordinary skill in the art would understand that various assay parameters may be optimized, e.g., signal to noise ratio.
In some embodiments, one or more cells or cell lines of the invention are exposed to a plurality of test compounds, for example, a library of test compounds. Such libraries of test compounds can be screened using the cell lines of the invention to identify one or more modulators of the protein of interest. The test compounds can be chemical moieties including small molecules, polypeptides, peptides, peptide mimetics, antibodies or antigen-binding portions thereof, natural compounds, synthetic compounds, extracts, lipids, detergents, and the like. In the case of antibodies, they may be non-human antibodies, chimeric antibodies, humanized antibodies, or fully human antibodies. The antibodies may be intact antibodies comprising a full complement of heavy and light chains or antigen-binding portions of any antibody, including antibody fragments (such as Fab and Fab, Fab′, F(ab′)2, Fd, Fv, dAb and the like), single chain antibodies (scFv), single domain antibodies, all or an antigen-binding portion of a heavy chain or light chain variable region.
In some embodiments, prior to exposure to a test compound, the cells or cell lines of the invention may be modified by pretreatment with, for example, enzymes, including mammalian or other animal enzymes, plant enzymes, bacterial enzymes, protein modifying enzymes and lipid modifying enzymes. Such enzymes can include, for example, kinases, proteases, phosphatases, glycosidases, oxidoreductases, transferases, hydrolases, lyases, isomerases, ligases bacterial proteases, proteases from the gut, proteases from the GI tract, proteases in saliva, in the oral cavity, proteases from lysol cells/bacteria, and the like. Alternatively, the cells and cell lines may be exposed to the test compound first followed by enzyme treatment to identify compounds that alter the modification of the protein by the treatment.
In some embodiments, large compound collections are tested for protein modulating activity in a cell-based, functional, high-throughput screen (HTS), e.g., using 96-well, 384-well, 1536-well or higher density formats. In some embodiments, a test compound or multiple test compounds, including a library of test compounds, may be screened using more than one cell or cell line of the invention.
In some embodiments, the cells and cell lines of the invention have increased sensitivity to modulators of the protein of interest. Cells and cell lines of the invention also respond to modulators with a physiological range EC50 or IC50 values for the protein. As used herein, EC50 refers to the concentration of a compound or substance required to induce a half-maximal activating response in the cell or cell line. As used herein, IC50 refers to the concentration of a compound or substance required to induce a half-maximal inhibitory response in the cell or cell line. EC50 and IC50 values may be determined using techniques that are well-known in the art, for example, a dose-response curve that correlates the concentration of a compound or substance to the response of the protein-expressing cell line.
A further advantageous property of the cells and cell lines of the invention is that modulators identified in initial screening using those cells and cell lines are functional in secondary functional assays. As those of ordinary skill in the art will recognize, compounds identified in initial screening assays typically must be modified, such as by combinatorial chemistry, medicinal chemistry or synthetic chemistry, for their derivatives or analogs to be functional in secondary functional assays. However, due to the high physiological relevance of the cells and cell lines of this invention, many compounds identified using those cells and cell lines are functional without further modification. In some embodiments, at least 25%, 30%, 40%, 50% or more of the modulators identified in an initial assay are functional in a secondary assay. Further, cell lines of the invention perform in functional assays on a par with the “gold standard” assays. For example, cell lines of the invention expressing GABA A receptors perform substantially the same in membrane potential assays and in electrophysiology.
In a further aspect of the present invention, differentiated, adult or specialized cells generated according to the present invention may be used to generate stem cells. In some embodiments, cells of the invention or cells identified by the methods of the invention wherein the cell type or specification is a differentiated, adult or specialized cell may be dedifferentiated into stems cells including but not limited to multipotent stem cells, pluripotent stem cells, omnipotent stem cells, induced pluripotent stem (“iPS”) cells, embryonic stem cells, cancer stem cells, and organ or tissue specific stem cells. Methods of dedifferentiation are known to those skilled in the art. See, e.g., Panagiotis A. Tsonis; Stem Cells from Differentiated Cells; Molecular Interventions 4:81-83, (2004). Stem cells generated from the cells of the present invention or cells identified by the methods of the invention may be differentiated into one or more cells of a differentiated, adult, or specialized cell type or specification. Embryonic stem cells and iPS cells generated from the cells of the present invention or cell identified by the methods of the present invention may be used to produce a whole non-human organism, e.g., a mouse. Method of producing mice using mouse embryonic stem cells are known to those skilled in the art. See, e.g., Smith, “EMBRYO-DERIVED STEM CELLS: Of Mice and Men”, Annu. Rev. Cell Dev. Biol. 2001, 17:435-62, which is incorporated herein by reference in its entirety. Methods of producing mice using iPS cells are known to those skilled in the art. See, e.g., Kang et al., “iPS Cells Can Support Full-Term Development of Tetraploid Blastocyst-Complemented Embryos”, Cell Stem Cell, Jul. 22, 2009 [Epub ahead of print], and Zhao et al., “iPS cells produce viable mice through tetraploid complementation”, Nature, Jul. 23, 2009 [Epub ahead of print].
In some embodiments, cells of the invention or cells identified by the methods of the present invention wherein the cell type or specification is a differentiated, adult or specialized cell may be dedifferentiated into stems cells including but not limited to multipotent stem cells, pluripotent stem cells, omnipotent stem cells, induced pluripotent stem cells (“iPS”), embryonic stem cells, cancer stem cells, and organ or tissue specific stem cells, and the stem cells thus produced may be differentiated into one or more cells of a differentiated, adult, or specialized cell type or specification.
In some embodiments, cells of the invention or cells identified by the methods of the invention wherein the cell type or specification is a differentiated, adult or specialized cell may be dedifferentiated into embryonic stem cells or iPS cells, and the stem cells thus produced may be used to produce a whole organism, e.g., a mouse.
In some embodiments, cells of the invention or cells identified by the methods of the invention wherein the cell type or specification is a differentiated, adult or specialized cell may be dedifferentiated into embryonic stem cells or iPS cells, and the stem cells thus produced may be used to produce a whole organism, e.g., a mouse, wherein the cells in the organism of the same cell type or specification comprise the same properties for which the cells of the invention were selected, e.g., expression of a protein or RNA of interest.
In some embodiments, cells of a specialized cell or tissue type comprising an RNA or protein or a functional or physiological form of an RNA or protein may be used to produce an embryonic stem cell or iPS cell that may be used to produce an organism, e.g., a mouse, wherein the cells or tissues of the organism of the same type comprise the RNA or protein or the functional or physiological form of the RNA or protein. In some embodiments, the organism thus produced comprises RNA or protein of the same species. In other embodiments, the organism thus produced comprises the RNA or protein of a different species. In some embodiments, the organism is mouse and the RNA or protein is of a human origin. In some embodiments, the organism thus produced comprises an in vitro correlate of the invention. In some embodiments, the organism thus produced may be used in testing, including preclinical testing. In some embodiments, the testing or preclinical testing is used to predict the activity of test compounds in humans.
In a further aspect, the present invention provides a method for generating an in vitro correlate for an in vivo physiological property. An in vitro correlate for an in vivo physiological property includes the effect(s) of one or more compounds on one or more proteins or RNAs expressed in the cells or cell lines of the present invention (i.e., expressed in vitro) that correlate(s) to the effect(s) of the one or more compounds on one or more pharmacological properties in vivo. Without being bound by theory, a test compound may be considered to have similar or substantially same effect(s) on one or more in vivo physiological properties, as compared to a reference compound, if it is found to have similar or substantially same effect(s) on one or more proteins or RNAs expressed in vitro, as compared to the reference compound, i.e., the test compound is considered to have similar or substantially same in vitro correlate as compared to the reference compound (e.g., at least 90% identical). In some embodiments, the test compound is considered to have similar or substantially the same in vitro correlate as compared to the reference compound (e.g., at least 10%, 20%, 30%, 40%, 50% 60%, 70%, 80% or 90% identical). An in vitro correlate may comprise one or more activity profiles of a compound.
In a further aspect, a protein or a plurality of proteins expressed by the cells or cell lines of the present invention provides an in vitro correlate for an in vivo protein of interest or a plurality of in vivo proteins of interest. Cells and cell lines of the present invention may not exactly recapitulate those cells in vivo in providing exactly the same conditions for expressing one or more proteins, e.g., there may be difference(s) in post-translational modification, folding, assembly, subunit combinations, transport and/or membrane integration between a protein expressed in the cells or cell lines of the present invention, as compared to the protein expressed in vivo. In addition, the parameters used in testing the function of a protein expressed in vitro may not exactly recapitulate those parameters in vivo, e.g., certain protein functional assays performed in vitro may be performed under certain pH or salt concentration that is considered non-physiological. Nonetheless, proteins expressed by the cells or cell lines of the present invention may be biologically active in these non-physiological conditions and may provide at least one functional or pharmacological or physiological profile when assayed in vitro. Such a functional or pharmacological or physiological profile may correspond to the in vivo protein. For example, a compound that regulates or alters the physiological property associated with a protein in vivo may be able to alter a biological activity of the corresponding protein expressed by the cells or cell lines of the present invention when assayed in vitro, thereby establishing an correlation between the protein expressed by the cells or cell lines of the present invention and the protein expressed in vivo, with the protein expressed by the cells or cell lines of the present invention considered as the “in vitro correlate” of the protein expressed in vivo. For example, we have found that different cell lines each expressing the same set of Nav subunits (α, β1 and β2) can respond differently to the same set of compounds. See, e.g., Example 23 hereinbelow. These distinct functional profiles are indications of different subunit combinations in these cell lines, and each of the different subunit combinations may be considered as an in vitro correlate of a corresponding subunit combination in vivo. In addition, we have also obtained profiles of compound activities against panels of cell lines expressing bitter taste receptors. Sensory human taste testing was used to compare with the compound activity profiles to see which patterns of compound activity against the panel correlated with a desired or off-taste in vivo.
Aside from response to compounds, in vitro correlates of the present invention may also be generated and/or categorized by applying other treatments and/or conditions to the proteins expressed by the cells of the present invention. For example, we have generated in vitro correlates of ENaC by proteolysis (e.g., generation of different proteolyzed forms of ENac), and have generated in vitro correlates of sweet/umami receptors by applying different media conditions.
An in vitro correlate may comprise one protein or a plurality of proteins. Such an in vitro correlate may be predictive of the function or activity of its corresponding protein(s) in vivo. Such an in vitro correlate may be used in a high throughput screening to identity modulators of one or more biological activities of the protein expressed by the cells or cell lines of the present invention (i.e., the in vitro correlate), and some or all of the compounds thus identified as modulators of the in vitro correlate may also modulate the protein expressed in vivo (e.g., have a therapeutic effect in vivo). In various embodiments, at least 10%, 20%, 30%, 40%, 50%, 60%, 70%, 80%, 90%, 95%, or 99% of all of the compounds identified in a high throughput screening are capable of having a therapeutic effect. In some embodiments, an in vitro correlate may comprise at least 2, 3, 4, 5, or 6 subunits. In some embodiments, an in vitro correlate may be a heteromultimer. In some embodiments, the in vitro correlate is stably expressed in cells cultured in the absence of selective pressure. In some embodiments, the in vitro correlate is expressed in a cell line without causing cytotoxicity. In some embodiments, the in vitro correlate is expressed in a cell that does not endogenously express the protein or plurality of proteins.
In some embodiments, cells or cell lines expressing the in vitro correlate in accordance with the present invention may be used to identify a modulator of an in vivo protein of interest, e.g., by contacting the cells or cell lines with a test compound; and detecting a change in the activity of the protein or plurality of proteins of the in vitro correlate in the cells or cell lines contacted with the test compound compared to the activity of the protein or plurality of proteins of the in vitro correlate in a cell not contacted by the test compound, wherein a compound that produces a difference in the activity in the presence compared to in the absence is a modulator of the in vivo protein of interest.
In certain aspects, the present invention provides kits that can be used in the methods described herein. In one embodiment, a kit comprises one or more containers comprising one or more reagents for use in the methods described herein.
In certain aspects, provided herein are kits that can be used in the methods described herein. In particular, provided herein are kits comprising one or more cells or cell lines stably expressing one or more complex targets. In certain embodiments, kits provided herein comprise one or more signaling probes described herein. In particular embodiments, a kit may comprise one or more vectors encoding one or more complex targets. In specific embodiments, a kit comprises one or more dyes for use in functional cell-based assays (e.g., calcium flux assay, membrane potential assay) to screen and select cells stably expressing one or more complex targets.
In certain aspects, provided herein are kits comprising one or more containers filled with one or more of the reagents and/or cells described herein, such as one or more cells, vectors, and/or signaling probes provided herein. In certain embodiments, the kits of the present invention further comprise a control reagent (e.g., control signaling probe, dye, cell, and/or vector), wherein such control reagent may be a positive control or a negative control reagent. Optionally associated with such container(s) can be a notice containing instructions for using the components in the kit.
This invention relates to novel cells and cell lines that have been engineered to stably express a T1R2 and a T1R3 subunit of a sweet taste receptor, as well as optionally a G protein. This invention also relates to novel cells and cell lines that have been engineered to stably express a T1R1 and a T1R3 subunit of an umami taste receptor, as well as optionally a G protein. In some embodiments, the taste receptor (e.g., sweet taste receptor or umami taste receptor) produced in those cells and cell lines is functional and physiologically relevant. In other aspects, the invention provides methods of making and using these cells and cell lines. The cells and cell lines of the invention comprising a taste receptor, e.g., umami taste receptor or a sweet taste receptor can be used to identify modulators of the taste receptor, e.g., umami taste receptor or sweet taste receptor. These modulators are useful in modifying the taste of, e.g., food stuffs and pharmaceuticals, and in the therapeutic treatment of diseases where the taste receptor, e.g., umami taste receptor or sweet taste receptor, is implicated, e.g., obesity and diabetes.
According to some embodiments of the invention, the novel cells and cell lines are singly or doubly transfected with a nucleic acid encoding a sweet taste receptor T1R2 subunit and/or a nucleic acid encoding a sweet taste receptor T1R3 subunit. In some specific embodiments, the novel cells and cell lines are singly or doubly transfected with a nucleic acid encoding an umami taste receptor T1R1 subunit and/or a nucleic acid encoding an umami taste receptor T1R3 subunit. The other subunit may be expressed in the cell from endogenous nucleic acids. The two nucleic acids, if present, may be in the same or in separate vectors. In another embodiment, the novel cells and cell lines of this invention are singly, doubly or triply transfected with nucleic acids encoding a sweet taste receptor T1R2 subunit, a sweet taste receptor T1R3 subunit and a G protein. In another embodiment, the novel cells and cell lines of this invention are singly, doubly or triply transfected with nucleic acids encoding an umami taste receptor T1R1 subunit, an umami taste receptor T1R3 subunit and a G protein. As before, the nucleic acids may be in the same or in separate vectors. For example, three vectors can be used; one vector can be used; or two vectors can be used. The other subunits, and optional G protein, may be expressed in the cell from endogenous nucleic acids. In another embodiment, the novel cells and cells lines have at least one taste receptor subunit, e.g., umami taste receptor subunit or sweet taste receptor subunit, activated for expression by gene activation. The other taste receptor subunit, e.g., umami taste receptor subunit or sweet taste receptor subunit, and/or optionally a G protein, as necessary, may be expressed from introduced nucleic acid sequences encoding those proteins or may be already expressed from endogenously active nucleic acids. The novel cell lines of the invention stably express the introduced and/or gene activated taste receptor subunits, e.g., umami taste receptor subunits or sweet taste receptor subunits, and optionally the G protein.
As described above, in some embodiments of this invention, the cells and cell lines of the invention are engineered to produce a G protein, in addition to producing the two subunits of a taste receptor, e.g., umami taste receptor or sweet taste receptor. The cells and cell lines are engineered to produce a G protein because they do not, in their pre-engineered state, produce a G protein, which is necessary to trigger downstream signaling from an activated taste receptor, e.g., umami taste receptor or sweet taste receptor, or the cells do not produce that G protein in a sufficient amount for taste receptor induced signaling, e.g., umami taste receptor induced signaling or sweet taste receptor induced signalling.
In a first aspect, the invention provides cells and cell lines that express taste receptors, e.g., umami taste receptors or sweet taste receptors, which cells and cell lines have enhanced properties as compared to cells and cell lines made by conventional methods. For example, the taste receptor cells and cell lines, e.g., umami taste receptor cells and cell lines or sweet taste receptor cells and cell lines, of this invention have enhanced stability of expression and/or levels of expression (even when maintained in cultures without selective pressure, including, for example, antibiotics and other drugs). In other embodiments, the cells and cell lines of the invention have high Z′ values in various assays. In still other embodiments, the cells and cell lines of this invention are improved in the context of their expression of physiologically relevant taste receptor activity, e.g., umami taste receptor activity or sweet taste receptor activity, as compared to more conventionally engineered cells. These properties enhance and improve the ability of the cells and cell lines of this invention to be used in assays to identify modulators of taste receptors, e.g., umami taste receptors and/or sweet taste receptors, and improve the functional attributes of the identified modulators.
In various embodiments, the cells or cell lines of the invention express umami taste receptor T1R1 and T1R3 subunits or sweet taste receptor T1R2 and T1R3 subunits at a consistent level of expression for at least 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, 100, 110, 120, 130, 140, 150, 160, 170, 180, 190, 200 days or over 200 days, where consistent expression refers to a level of expression that does not vary by more than: 1%, 2%, 3%, 4%, 5%, 6%, 7%, 8% 9% or 10% over 2 to 4 days of continuous cell culture; 1%, 2%, 4%, 6%, 8%, 10% or 12% over 5 to 15 days of continuous cell culture; 1%, 2%, 4%, 6%, 8%, 10%, 12%, 14%, 16%, 18% or 20% over 16 to 20 days of continuous cell culture; 1%, 2%, 4%, 6%, 8%, 10%, 12%, 14%, 16%, 18%, 20%, 22%, 24% over 21 to 30 days of continuous cell culture; 1%, 2%, 4%, 6%, 8%, 10%, 12%, 14%, 16%, 18%, 20%, 22%, 24%, 26%, 28% or 30% over 30 to 40 days of continuous cell culture; 1%, 2%, 4%, 6%, 8%, 10%, 12%, 14%, 16%, 18%, 20%, 22%, 24%, 26%, 28% or 30% over 41 to 45 days of continuous cell culture; 1%, 2%, 4%, 6%, 8%, 10%, 12%, 14%, 16%, 18%, 20%, 22%, 24%, 26%, 28% or 30% over 45 to 50 days of continuous cell culture; 1%, 2%, 4%, 6%, 8%, 10%, 12%, 14%, 16%, 18%, 20%, 22%, 24%, 26%, 28%, 30% or 35% over 45 to 50 days of continuous cell culture; 1%, 2%, 4%, 6%, 8%, 10%, 12%, 14%, 16%, 18%, 20%, 22%, 24%, 26%, 28% or 30% or 35% over 50 to 55 days of continuous cell culture; 1%, 2%, 4%, 6%, 8%, 10%, 12%, 14%, 16%, 18%, 20%, 22%, 24%, 26%, 28%, 30% or 35% over 50 to 55 days of continuous cell culture; 1%, 2%, 3%, 4%, 5%, 10%, 15%, 20%, 25%, 30%, 35% or 40% over 55 to 75 days of continuous cell culture; 1%, 2%, 3%, 4%, 5%, 5%, 10%, 15%, 20%, 25%, 30%, 35%, 40% or 45% over 75 to 100 days of continuous cell culture; 1%, 2%, 3%, 4%, 5%, 5%, 10%, 15%, 20%, 25%, 30%, 35%, 40% or 45% over 101 to 125 days of continuous cell culture; 1%, 2%, 3%, 4%, 5%, 5%, 10%, 15%, 20%, 25%, 30%, 35%, 40% or 45% over 126 to 150 days of continuous cell culture; 1%, 2%, 3%, 4%, 5%, 5%, 10%, 15%, 20%, 25%, 30%, 35%, 40% or 45% over 151 to 175 days of continuous cell culture; 1%, 2%, 3%, 4%, 5%, 5%, 10%, 15%, 20%, 25%, 30%, 35%, 40% or 45% over 176 to 200 days of continuous cell culture; 1%, 2%, 3%, 4%, 5%, 5%, 10%, 15%, 20%, 25%, 30%, 35%, 40% or 45% over more than 200 days of continuous cell culture.
According to the invention, the taste receptor, e.g., umami taste receptor or sweet taste receptor, expressed by a cell or cell line of the invention can be from any mammal, including rat, mouse, rabbit, goat, dog, cow, pig or primate. The T1R2 and T1R3 subunits that together form the expressed sweet taste receptor can be from the same or different species. For example, sweet taste receptor T1R2 subunit from any species may be co-expressed with a sweet taste receptor T1R3 subunit from the same species or from any other species in a cell or cell line of the invention. Also, the T1R1 and T1R3 subunits that together form the expressed umami taste receptor can be from the same or different species. For example, umami taste receptor T1R1 subunit from any species may be co-expressed with an umami taste receptor T1R3 subunit from the same species or from any other species in a cell or cell line of the invention. Similarly, in the embodiments where a G protein is also expressed in the cells and cell lines of this invention, the G protein may be from any species. Among these G proteins are those referred to in Table 7. Chimera G proteins (Gα15-Gα16; GNA15-GNA16) can also be expressed in the cells and cell lines of this invention. G proteins from any species may be co-expressed with a sweet taste receptor T1R2 subunit from any species, and a sweet taste receptor T1R3 subunit from any species or any combination of the three may be used. In a specific embodiment, the sweet taste receptor is a human sweet taste receptor and is characterized, preferably, by human T1R2 and T1R3 subunits. In another specific embodiment, the umami taste receptor is a human umami taste receptor and is characterized, preferably, by human T1R1 and T1R3 subunits. One aspect of the invention provides a collection of clonal cells and cell lines, each expressing the same taste receptor, e.g., umami taste receptor or sweet taste receptor, or different taste receptors, e.g., umami taste receptors or sweet taste receptors. The collection may include, for example, cells or cell lines expressing combinations of different subunits, or of full length or fragments of those subunits.
The nucleic acid encoding taste receptor subunits, e.g., umami taste receptor subunits T1R1 and T1R2 or sweet taste receptor subunits T1R2 and T1R3, and the nucleic acid encoding the optional G protein can be genomic DNA, cDNA, synthetic DNA or mixtures of them. In some embodiments, the taste receptor (e.g., umami taste receptor or sweet taste receptor) subunit-encoding nucleic acid sequence and optionally the nucleic acid sequence encoding the G protein further comprise a tag. Such tags may encode, for example, a HIS tag, a myc tag, a hemagglutinin (HA) tag, protein C, VSV-G, FLU, yellow fluorescent protein (YFP), green fluorescent protein, FLAG, BCCP, maltose binding protein tag, Nus-tag, Softag-1, Softag-2, Strep-tag, S-tag, thioredoxin, GST, V5, TAP or CBP. A tag may be used as a marker to determine taste receptor (e.g., umami taste receptor or sweet taste receptor) subunit and G protein expression levels, intracellular localization, protein-protein interactions, taste receptor (e.g., umami taste receptor or sweet taste receptor) regulation, or taste receptor (e.g., umami taste receptor or sweet taste receptor) function. Tags may also be used to purify or fractionate taste receptors (e.g., umami taste receptors or sweet taste receptors) or G proteins.
In some embodiments, a cell or cell line of the invention may comprise nucleic acid (SEQ ID NO: 31), which encodes a human sweet taste receptor T1R2 subunit. In some embodiments, a cell or cell line of the invention may comprise nucleic acid (SEQ ID NO: 41), which encodes a human umami taste receptor T1R1 subunit. A cell or cell line of the invention may also comprise nucleic acid (SEQ ID NO: 32), which encodes a human sweet taste receptor or umami taste receptor T1R3 subunit. In a specific embodiment, the cells or cell lines of the invention comprise both nucleic acids encoding T1R3 and T1R1 or T1R2. In other embodiments, a cell or cell line of the invention may comprise nucleic acid sequence (SEQ ID NO: 33) in addition to the nucleic acids encoding the T1R1 and T1R3 subunits or T1R2 and T1R3 subunits. SEQ ID NO: 33 encodes a mouse Gα15 protein. In other embodiments, this G protein is human Gα15. See SEQ ID NO: 37.
In some embodiments, the nucleic acid encoding a taste receptor subunit (e.g., umami taste receptor subunit or sweet taste receptor subunit) and optional G protein comprises one or more substitutions, insertions, mutations or deletions, as compared to a nucleic acid sequence encoding the wild-type taste receptor subunit (e.g., umami taste receptor subunit or sweet taste receptor subunit) or G protein. In embodiments comprising a nucleic acid comprising a mutation, the mutation may be a random mutation or a site-specific mutation. These nucleic acid changes may or may not result in an amino acid substitution. In some embodiments, the nucleic acid is a fragment of the nucleic acid that encodes a taste receptor subunit (e.g., umami taste receptor subunit or sweet taste receptor subunit) or G protein. Nucleic acids that are fragments or have such modifications encode polypeptides that retain at least one biological property of a taste receptor subunit (e.g., umami taste receptor subunit or sweet taste receptor subunit) or a G protein, e.g., its ability with its other subunit to activate a G protein or its ability to be activated by a taste receptor subunit (e.g., umami taste receptor subunit or sweet taste receptor), respectively.
The invention also encompasses cells and cell lines stably expressing a subunit-encoding nucleic acid, whose sequence is at least about 85% identical to subunit sequences selected from the group of SEQ ID NO: 31, SEQ ID NO: 41, SEQ ID NO: 32 or a counterpart nucleic acid derived from a species other than human or a nucleic acid that encodes the same amino acid sequence as any of those nucleic acids. In some embodiments, the subunit-encoding sequence identity is at least 85%, 90%, 95%, 96%, 97%, 98%, 99% or higher compared to those subunit sequences. The invention also encompasses cells and cell lines wherein the nucleic acid encoding a taste receptor subunit (e.g., umami taste receptor subunit or sweet taste receptor subunit) that hybridizes under stringent conditions to subunit sequences selected from the group of SEQ ID NO: 31, SEQ ID NO: 41, SEQ ID NO: 32 or a counterpart nucleic acid derived from a species other than human, or a nucleic acid that encodes the same amino acid sequence as any of those nucleic acids.
In some embodiments, the cell or cell line comprises a taste receptor subunit-encoding nucleic acid sequence (e.g., umami taste receptor subunit-encoding nucleic acid sequence or sweet taste receptor subunit-encoding nucleic acid sequence) comprising at least one substitution as compared to SEQ ID NO: 31, SEQ ID NO: 41, SEQ ID NO: 32 or a counterpart nucleic acid derived from a species other than human or a nucleic acid that encodes the same amino acid sequence as any of those nucleic acids. The substitution may comprise less than 10, 20, 30, or 40 nucleotides or, up to or equal to 1%, 5%, 10% or 20% of the nucleotide sequence. In some embodiments, the substituted sequence may be substantially identical to SEQ ID NO: 31, SEQ ID NO: 41, SEQ ID NO: 32 or a counterpart nucleic acid derived from a species other than human a nucleic acid that encodes the same amino acid sequence as any of those nucleic acids (e.g., a sequence at least 85%, 90%, 95%, 96%, 97%, 98%, 99% or higher identical thereto), or be a sequence that is capable of hybridizing under stringent conditions to SEQ ID NO: 31, SEQ ID NO: 41, SEQ ID NO: 32 or a counterpart nucleic acid derived from a species other than human or a nucleic acid that encodes the same amino acid sequence as any one of those nucleic acids.
In some embodiments, the cell or cell line comprises a taste receptor subunit-encoding nucleic acid sequence (e.g., umami taste receptor subunit-encoding nucleic acid sequence or sweet taste receptor subunit-encoding nucleic acid sequence) comprising an insertion into or deletion from SEQ ID NO: 31, SEQ ID NO: 41, SEQ ID NO: 32 or a counterpart nucleic acid derived from a species other than human or a nucleic acid that encodes the same amino acid sequence as any of those nucleic acids. The insertion or deletion may be less than 10, 20, 30, or 40 nucleotides or up to or equal to 1%, 5%, 10% or 20% of the nucleotide sequence. In some embodiments, the sequences of the insertion or deletion may be substantially identical to SEQ ID NO: 31, SEQ ID NO: 41, SEQ ID NO: 32 or a counterpart nucleic acid derived from a species other than human or a nucleic acid that encodes the same amino acid sequence as any of those nucleic acids (e.g., a sequence at least 85%, 90%, 95%, 96%, 97%, 98%, 99% or higher identical thereto), or be a sequence that is capable of hybridizing under stringent conditions to SEQ ID NO: 31, SEQ ID NO: 41, SEQ ID NO: 32 or a counterpart nucleic acid derived from a species other than human, or a nucleic acid that encodes the same amino acid sequence as any of those nucleic acids.
As described above, in some embodiments the cells and cell lines of this invention optionally express a G protein, for example, the mouse Gα15 protein (SEQ ID NO: 36) or human Gα15 protein (SEQ ID NO: 37). As with the nucleic acid sequence encoding the T1R2 and T1R3 subunits of a sweet taste receptor or the T1R1 and T1R3 subunits of an umami taste receptor, the nucleic acid sequence encoding the G protein (and the amino sequence of the G protein) may include substitutions, deletions and insertions as described above for the sweet taste receptor subunits.
In some embodiments, the nucleic acid substitution or modification results in an amino acid change, such as an amino acid substitution. For example, an amino acid residue of SEQ ID NO: 34 (human T1R2), SEQ ID NO: 35 (human T1R3), SEQ ID NO: 42 (umami human T1R1 isoform 1 aa), SEQ ID NO: 43 (umami human T1R1 isoform 2 aa), SEQ ID NO: 44 (umami human T1R1 isoform 3 aa), SEQ ID NO: 45 (umami human T1R1 isoform 4 aa), or a counterpart amino acid derived from a species other than human or an amino acid residue of SEQ ID NOS: 36 (mouse Gα15) and 37 (human Gα15) or a G protein from any species may be replaced by a conservative or a non-conservative substitution. In some embodiments, the sequence identity between the original and modified amino acid sequence can differ by about 1%, 5%, 10% or 20% or from a sequence substantially identical thereto (e.g., a sequence at least 85%, 90%, 95%, 96%, 97%, 98%, 99% or higher identical thereto).
A “conservative amino acid substitution” is one in which an amino acid residue is substituted by another amino acid residue having a side chain R group with similar chemical properties to the parent amino acid residue (e.g., charge or hydrophobicity). In cases where two or more amino acid sequences differ from each other by conservative substitutions, the percent sequence identity or degree of similarity may be adjusted upwards to correct for the conservative nature of the substitution. Means for making this adjustment are well-known to those of skill in the art. See, e.g., Pearson, Methods Mol. Biol. 243:307-31 (1994).
Examples of groups of amino acids that have side chains with similar chemical properties include 1) aliphatic side chains: glycine, alanine, valine, leucine, and isoleucine; 2) aliphatic-hydroxyl side chains: serine and threonine; 3) amide-containing side chains: asparagine and glutamine; 4) aromatic side chains: phenylalanine, tyrosine, and tryptophan; 5) basic side chains: lysine, arginine, and histidine; 6) acidic side chains: aspartic acid and glutamic acid; and 7) sulfur-containing side chains: cysteine and methionine. Preferred conservative amino acids substitution groups are: valine-leucine-isoleucine, phenylalanine-tyrosine, lysine-arginine, alanine-valine, glutamate-aspartate, and asparagine-glutamine. Alternatively, a conservative amino acid substitution is any change having a positive value in the PAM250 log-likelihood matrix disclosed in Gonnet et al., Science 256:1443-45 (1992). A “moderately conservative” replacement is any change having a nonnegative value in the PAM250 log-likelihood matrix.
Conservative modifications in subunits T1R2 and T1R3 will produce sweet taste receptors having functional and chemical characteristics similar (i.e. at least 50%, 60%, 70%, 80%, 90% or 95% the same) to those of the unmodified sweet taste receptor. Conservative modifications in subunits T1R1 and T1R3 will produce umami taste receptors having functional and chemical characteristics similar (i.e. at least 50%, 60%, 70%, 80%, 90% or 95% the same) to those of the unmodified umami taste receptor. The same is true for conservative modifications in a G protein.
Host cells used to produce a cell or cell line of the invention may express in their native state one or more endogenous taste receptor subunits (e.g., umami taste receptor subunits or sweet taste receptor subunits) or lack expression of any taste receptor subunits (e.g., umami taste receptor subunits or sweet taste receptor subunit). The same is true for a G protein. The host cell may be a primary, germ, or stem cell, including an embryonic stem cell. The host cell may also be an immortalized cell. Primary or immortalized host cells may be derived from mesoderm, ectoderm or endoderm layers of eukaryotic organisms. The host cell may be endothelial, epidermal, mesenchymal, neural, renal, hepatic, hematopoietic, or immune cells. For example, the host cells may be blood/immune cells such as B cell, T cell (Cytotoxic T cell, Natural Killer T cell, Regulatory T cell, T helper cell, gd T cell, Natural killer cell); granulocytes (Basophil granulocyte, Eosinophil granulocyte, Neutrophil granulocyte/Hypersegmented neutrophil), Monocyte/Macrophage, Red blood cell (Reticulocyte), Mast cell, Thrombocyte/Megakaryocyte, Dendritic cell; Endocrine cells such as thyroid (Thyroid epithelial cell, Parafollicular cell), parathyroid (Parathyroid chief cell, Oxyphil cell), adrenal (Chromaffin cell); Nervous system cells such as glial cells (Astrocyte, Microglia), Magnocellular neurosecretory cell, Stellate cell, Nuclear chain cell, Boettcher cell, pituitary, (Gonadotrope, Corticotrope, Thyrotrope, Somatotrope, Lactotroph), Respiratory system cells such as Pneumocyte (Type I pneumocyte, Type II pneumocyte), Clara cell, Goblet cell; Circulatory system cells (Myocardiocyte, Pericyte); Digestive system cells (stomach (Gastric chief cell, Parietal cell), Goblet cell, Paneth cell, G cells, D cells, ECL cells, I cells, K cells, Enteroendocrine cells, Enterochromaffin cell, APUD cell, liver (Hepatocyte, Kupffer cell), pancreas (beta cells, alpha cells), gallbladder); Cartilage/bone/muscle/integumentary system cells such as osteoblast, osteocyte, osteoclast, tooth cells (Cementoblast, Ameloblast); cartilage cells such as Chondroblast, Chondrocyte, skin/hair cells such as Trichocyte, Keratinocyte; Melanocyte muscle cells such as Myocyte, Adipocyte, Fibroblast; Urinary system cells such as Podocyte, Juxtaglomerular cell, Intraglomerular mesangial cell/Extraglomerular mesangial cell, Kidney proximal tubule brush border cell, Macula densa cell; Reproductive system cells such as Spermatozoon, Sertoli cell, Leydig cell, Ovum, Ovarian follicle cell; Sensory cells such as organ of Corti cells, olfactory epithelium, temperature sensitive sensory neurons, Merckel cells, olfactory receptor neuron, pain sensitive neurons, photoreceptor cells, taste bud cells, hair cells of the vestibular apparatus, carotid body cells. The host cells may be eukaryotic, prokaryotic, mammalian, avian, chicken, reptile, amphibian, frog, lizard, snake, fish, worms, squid, lobster, sea urchin, sea slug, sea squirt, fly, hydra, arthropods, beetles, chicken, lamprey, ricefish, zebra finch, pufferfish, and Zebrafish. Mammalian examples include human, non-human primate, bovine, porcine, feline, rat, marsupial, murine, canine, ovine, caprine, rabbit, guinea pig and hamster. The host cells may also be nonmammalian, such as yeast, insect, fungus, plant, lower eukaryotes and prokaryotes. Such host cells may provide backgrounds that are more divergent for testing taste receptor modulators, e.g., umami taste receptor modulators or sweet taste receptor modulators, with a greater likelihood for the absence of expression products provided by the cell that may interact with the target. In preferred embodiments, the host cell is a mammalian cell.
Examples of host cells that may be used to produce a cell or cell line of the invention include but are not limited to: Human Embryonic Kidney-293T cells, established neuronal cell lines, pheochromocytomas, neuroblastomas fibroblasts, rhabdomyosarcomas, dorsal root ganglion cells, NS0 cells, CV-1 (ATCC CCL 70), COS-1 (ATCC CRL 1650), COS-7 (ATCC CRL 1651), CHO-K1 (ATCC CCL 61), 3T3 (ATCC CCL 92), NIH/3T3 (ATCC CRL 1658), HeLa (ATCC CCL 2), C127I (ATCC CRL 1616), BS-C-1 (ATCC CCL 26), MRC-5 (ATCC CCL 171), L-cells, HEK-293 (ATCC CRL1573) and PC12 (ATCC CRL-1721), HEK293T (ATCC CRL-11268), RBL (ATCC CRL-1378), SH-SY5Y (ATCC CRL-2266), MDCK (ATCC CCL-34), SJ-RH30 (ATCC CRL-2061), HepG2 (ATCC HB-8065), ND7/23 (ECACC 92090903), CHO (ECACC 85050302), Vero (ATCC CCL 81), Caco-2 (ATCC HTB 37), K562 (ATCC CCL 243), Jurkat (ATCC TIB-152), Per.C6 (Crucell, Leiden, The Netherlands), Huvec (ATCC Human Primary PCS 100-010, Mouse CRL 2514, CRL 2515, CRL 2516), HuH-7D12 (ECACC 01042712), 293 (ATCC CRL 10852), A549 (ATCC CCL 185), IMR-90 (ATCC CCL 186), MCF-7 (ATC HTB-22), U-20S (ATCC HTB-96), T84 (ATCC CCL 248), or any established cell line (polarized or nonpolarized) or any cell line available from repositories such as American Type Culture Collection (ATCC, University Blvd. Manassas, Va. 20110-2209 USA) or European Collection of Cell Cultures (ECACC, Salisbury Wiltshire SP4 0JG England).
In one embodiment, the host cell is an embryonic stem cell that is then used as the basis for the generation of transgenic animals that produce a taste receptor, e.g., umami taste receptor or sweet taste receptor. Embryonic stem cells stably expressing at least one taste receptor subunit (e.g., umami taste receptor subunits or sweet taste receptor subunit), or both taste receptor subunits (e.g., both umami taste receptor subunits or both sweet taste receptor subunits), and preferably a functional taste receptor (e.g., umami taste receptor or sweet taste receptor), may be implanted into organisms directly, or their nuclei may be transferred into other recipient cells and these may then be implanted, or they may be used to create transgenic animals. In some embodiments one or more subunits may be expressed in the animal with desired temporal and/or tissue specific expression.
As will be appreciated by those of skill in the art, any vector that is suitable for use with a chosen host cell may be used to introduce a nucleic acid encoding a taste receptor subunit (e.g., umami taste receptor subunits or sweet taste receptor subunit) or G protein into a host cell. The vectors comprising the nucleic acids encoding the various taste receptor subunits (e.g., umami taste receptor subunits or sweet taste receptor subunits) or G protein may be the same type or may be of different types. Examples of vectors that may be used to introduce a taste receptor subunit (e.g., umami taste receptor subunit or sweet taste receptor subunit) or G protein encoding nucleic acids into host cells include but are not limited to plasmids, viruses, including retroviruses and lentiviruses, cosmids, artificial chromosomes and may include, for example, pFN11A (BIND) Flexi®, pGL4.31, pFC14A (HaloTag® 7) CMV Flexi®, pFC14K (HaloTag® 7) CMV Flexi®, pFN24A (HaloTag® 7) CMVd3 Flexi®, pFN24K (HaloTag® 7) CMVd3 Flexi®, HaloTag™ pHT2, pACT, pAdVAntage™, pALTER®-MAX, pBIND, pCAT®3-Basic, pCAT®3-Control, pCAT®3-Enhancer, pCAT®3-Promoter, pCI, pCMVTNT™, pG5luc, pSI, pTARGET™, pTNT™, pF12A RM Flexi®, pF12K RM Flexi®, pReg neo, pYES2/GS, pAd/CMV/V5-DEST Gateway® Vector, pAd/PL-DEST™ Gateway® Vector, Gateway® pDEST™27 Vector, Gateway® pEF-DEST51 Vector, Gateway® pcDNA™-DEST47 vector, pCMV/Bsd Vector, pEF6/His A, B, & c, pcDNA™6.2-DEST, pLenti6/TR, pLP-AcGFP1-C, pLPS-AcGFP1-N, pLP-IRESneo, pLP-TRE2, pLP-RevTRE, pLP-LNCX, pLP-CMV-HA, pLP-CMV-Myc, pLP-RetroQ, pLP-CMVneo, pCMVScript, pcDNA3.1 Hygro, pcDNA3.1neo, pcDNA3.1puro, PSV2neo, pIRESpuro, pSV2zeo. In some embodiments, the vectors comprise expression control sequences such as constitutive or conditional promoters, preferably, constitutive promoters are used. One of ordinary skill in the art will be able to select such sequences. For example, suitable promoters include but are not limited to CMV, TK, SV40 and EF-1α. In some embodiments, the promoters are inducible, temperature regulated, tissue specific, repressible, heat-shock, developmental, cell lineage specific, eukaryotic, prokaryotic or temporal promoters or a combination or recombination of unmodified or mutagenized, randomized, shuffled sequences of any one or more of the above. In other embodiments, a taste receptor subunit (e.g., umami taste receptor subunit or sweet taste receptor subunit) or more than one of them (and optionally the G protein) is expressed by gene activation or episomally.
In some embodiments, the vector lacks a selectable marker or drug resistance gene. In other embodiments, the vector optionally comprises a nucleic acid encoding a selectable marker, such as a protein that confers drug or antibiotic resistance or more generally any product that exerts selective pressure on the cell. Each vector for introducing a sequence encoding a different taste receptor subunit (e.g., umami taste receptor subunit or sweet taste receptor subunit) or G protein may have the same or a different drug resistance or other selective pressure marker. If more than one of the drug resistance or selective pressure markers are the same, simultaneous selection may be achieved by increasing the level of the drug. Suitable markers are well-known to those of skill in the art and include but are not limited to polypeptides products conferring resistance to any one of the following: Neomycin/G418, Puromycin, hygromycin, Zeocin, methotrexate and blasticidin. Although drug selection (or selection using any other suitable selection marker) is not a required step in producing the cells and cell lines of this invention, it may be used to enrich the transfected cell population for stably transfected cells, provided that the transfected constructs are designed to confer drug resistance. If subsequent selection of cells expressing both umami taste receptor subunits, and optionally a G protein, or both sweet taste receptor subunits and optionally a G protein is accomplished using signaling probes, selection too soon following transfection can result in some positive cells that may only be transiently and not stably transfected. However, this effect can be minimized by allowing sufficient cell passage to allow for dilution of transient expression in transfected cells.
In some embodiments, the vector used to introduce a nucleic acid encoding a taste receptor subunit (e.g., umami taste receptor subunit or sweet taste receptor subunit) or optionally a G protein comprises a nucleic acid sequence encoding an RNA tag sequence. An “RNA Tag sequence” refers to a nucleic acid sequence that is an expressed RNA or portion of an RNA that is to be detected by a signaling probe. Signaling probes may detect a variety of RNA sequences. Any of these RNAs may be used as tags. Signaling probes may be directed against the RNA tag by designing the probes to include a portion that is complementary to the RNA sequence of the tag. The tag sequence may be a 3′ untranslated region of the vector that is cotranscribed and comprises a target sequence for signaling probe binding. The RNA produced from the nucleic acid of interest may include the tag sequence or the tag sequence may be located within a 5′-untranslated region or 3′-untranslated region. In some embodiments, the tag is not part of the RNA produced from the nucleic acid of interest. The tag sequence can be in frame with the protein-coding portion of the message of the nucleic acid of interest or out of frame with it, depending on whether one wishes to tag the protein produced. Thus, the tag sequence does not have to be translated for detection by the signaling probe. The tag sequences may comprise multiple target sequences that are the same or different, wherein one signaling probe hybridizes to each target sequence. The tag sequences may encode an RNA having secondary structure. The structure may be a three-arm junction structure. Examples of tag sequences that may be used in this invention, and to which signaling probes may be prepared, include but are not limited to the RNA transcript of epitope tags such as, for example, a HIS tag, a myc tag, a hemagglutinin (HA) tag, protein C, VSV-G, FLU, yellow fluorescent protein (YFP), green fluorescent protein, various known magnetic tags, FLAG, BCCP, maltose binding protein tag, Nus-tag, Softag-1, Softag-2, Strep-tag, S-tag, thioredoxin, GST, V5, TAP or CBP. As described herein, one of ordinary skill in the art can readily prepare and use RNA tag sequences.
To make the cells and cell lines of the invention, one can use, for example, the methods described in U.S. Pat. No. 6,692,965 and International Patent Publication WO/2005/079462. Both of these documents are incorporated herein by reference in their entirety for all purposes. These methods, which are preferred for making the cells and cell lines of this invention, provide real-time assessment of millions of cells such that any desired number of clones (from tens to hundreds to thousands of clones) expressing (i.e., producing RNA) the nucleic acid sequences of interest may be selected. Using cell sorting techniques, such as flow cytometric cell sorting (e.g., with a FACS machine) or magnetic cell sorting (e.g., with a MACS machine), one selected cell per well may be automatically deposited with high statistical confidence in a culture vessel (such as a 96 well culture plate). The speed and automation of the technology allows multigene cell lines (i.e., those expressing the T1R2 and T1R3 subunits of a taste receptor (e.g., umami taste receptor or sweet taste receptor) and optionally a G protein) to be readily isolated.
Using this technology, the RNA sequence for each taste receptor subunit (e.g., umami taste receptor subunit or sweet taste receptor subunit) (and optionally the G protein) expressed in the cell or cell line may be detected using a signaling probe, also referred to as a molecular beacon or fluorogenic probe. In some embodiments, the molecular beacon recognizes a target sequence as described above. In another embodiment, the molecular beacon recognizes a sequence within the taste receptor subunit (e.g., umami taste receptor subunit or sweet taste receptor subunit) (or G protein) itself. Signaling probes may be directed against the RNA tag or a taste receptor subunit sequence (e.g., umami taste receptor subunit sequence or sweet taste receptor subunit sequence) (or G protein sequence) by designing the probes to include a portion that is complementary to the RNA sequence of the tag or the taste receptor subunit (e.g., umami taste receptor subunit or sweet taste receptor subunit) (or G protein), respectively.
Nucleic acids encoding a taste receptor subunit (e.g., umami taste receptor subunit or sweet taste receptor subunit) (and optionally a nucleic acid encoding a G protein), or the sequence encoding a taste receptor subunit (e.g., umami taste receptor subunit or sweet taste receptor subunit) (or G protein) and a tag sequence, and optionally a nucleic acid encoding a selectable marker may be introduced into selected host cells by well known methods. Gene activation sequences may be introduced into the cells in the a similar way using conventional methods well known in the art. The methods include but are not limited to transfection, viral delivery, protein or peptide mediated insertion, coprecipitation methods, lipid based delivery reagents (lipofection), cytofection, lipopolyamine delivery, dendrimer delivery reagents, electroporation or mechanical delivery. Examples of transfection reagents are GENEPORTER, GENEPORTER2, LIPOFECTAMINE, LIPOFECTAMINE 2000, FUGENE 6, FUGENE HD, TFX-10, TFX-20, TFX-50, OLIGOFECTAMINE, TRANSFAST, TRANSFECTAM, GENESHUTTLE, TROJENE, GENESILENCER, X-TREMEGENE, PERFECTIN, CYTOFECTIN, SIPORT, UNIFECTOR, SIFECTOR, TRANSIT-LT1, TRANSIT-LT2, TRANSIT-EXPRESS, IFECT, RNAI SHUTTLE, METAFECTENE, LYOVEC, LIPOTAXI, GENEERASER, GENEJUICE, CYTOPURE, JETSI, JETPEI, MEGAFECTIN, POLYFECT, TRANSMESSANGER, RNAiFECT, SUPERFECT, EFFECTENE, TF-PEI-KIT, CLONFECTIN, AND METAFECTINE. The taste receptor subunit (e.g., umami taste receptor subunit or sweet taste receptor subunit) nucleic acid sequences (and potentially G protein encoding nucleic acids) may be integrated at different locations of the genome in the cell. The expression level of the introduced nucleic acids encoding the taste receptor subunits (e.g., umami taste receptor subunits or sweet taste receptor subunits) and G proteins may vary based upon integration site.
Following introduction of the taste receptor subunit (e.g., umami taste receptor subunit or sweet taste receptor subunit) coding sequences or the taste receptor (e.g., umami taste receptor or sweet taste receptor) gene activation sequences into host cells (and optionally introducing or activating a G protein encoding sequence in those cells) and optional subsequent drug selection, molecular beacons (e.g., fluorogenic probes) are introduced into the cells and cell sorting is used to isolate cells positive for their signals and thus the expression (RNA) of the desired nucleic acid sequences. The skilled worker will recognize that this sorting can be gated for any desired expression level. Multiple rounds of sorting may be carried out, if desired. In one embodiment, the flow cytometric cell sorter is a FACS machine. MACS (magnetic cell sorting) or laser ablation of negative cells using laser-enabled analysis and processing can also be used. According to this method, cells expressing sweet taste receptor subunits T1R2 and T1R3 (and optimally a G protein) or umami taste receptor subunits T1R1 and T1R3 (and optionally a G protein) are detected and recovered.
Signaling probes useful in this embodiment of the invention are known in the art. They are generally oligonucleotides comprising a sequence complementary to a target sequence and a signal emitting system so arranged that no signal is emitted when the probe is not bound to the target sequence and a signal is emitted when the probe binds to the target sequence. By way of a non-limiting illustration, the signaling probe may comprise a fluorophore and a quencher positioned in the probe so that the quencher and fluorophore are brought together in the unbound probe. Upon binding between the probe and the target sequence, the quencher and fluorophore separate, resulting in emission of signal. International publication WO/2005/079462, for example, describes a number of signaling probes that may be, and are preferably, used in the production of the cells and cell lines of this invention. Where tag sequences are used, the vector for each of the taste receptor subunit (e.g., umami taste receptor subunit or sweet taste receptor subunit) (or optionally a G protein) can comprise the same or a different tag sequence. Whether the tag sequences are the same or different, the signaling probes may comprise different signal emitters, such as different colored fluorophores and the like so that (RNA) expression of each subunit (and G protein) may be separately detected. By way of illustration, the signaling probe that specifically detects sweet taste receptor T1R2 mRNA or umami taste receptor T1R1 mRNA can comprise a red fluorophore, the probe that detects the sweet/umami taste receptor T1R3 subunit (RNA) can comprise a green fluorophore and, optionally, the probe that detects a G protein (RNA) can comprise a yellow fluorophore. Those of skill in the art will be aware of other means for differentially detecting the expression of the two (or optionally three) expressed RNAs with signaling probes in a transfected cell.
Nucleic acids encoding signaling probes may be introduced into the selected host cell by any of numerous means that will be well-known to those of skill in the art, including but not limited to transfection, coprecipitation methods, lipid based delivery reagents (lipofection), cytofection, lipopolyamine delivery, dendrimer delivery reagents, electroporation or mechanical delivery. Examples of transfection reagents are GENEPORTER, GENEPORTER2, LIPOFECTAMINE, LIPOFECTAMINE 2000, FUGENE 6, FUGENE HD, TFX-10, TFX-20, TFX-50, OLIGOFECTAMINE, TRANSFAST, TRANSFECTAM, GENESHUTTLE, TROJENE, GENESILENCER, X-TREMEGENE, PERFECTIN, CYTOFECTIN, SIPORT, UNIFECTOR, SIFECTOR, TRANSIT-LT1, TRANSIT-LT2, TRANSIT-EXPRESS, IFECT, RNAI SHUTTLE, METAFECTENE, LYOVEC, LIPOTAXI, GENEERASER, GENEJUICE, CYTOPURE, JETSI, JETPEI, MEGAFECTIN, POLYFECT, TRANSMESSANGER, RNAiFECT, SUPERFECT, EFFECTENE, TF-PEI-KIT, CLONFECTIN, AND METAFECTINE.
In one embodiment, the signaling probes are designed to be complementary to either a portion of the RNA encoding a taste receptor subunit (e.g., umami taste receptor subunit or sweet taste receptor subunit) or to a portion of its 5′ or 3′ untranslated regions (or similar portions of the RNA encoding a G protein). Even if the signaling probe, designed to recognize a messenger RNA of interest, is able to detect endogenously expressed target sequences, the proportion of these sequences in comparison to the proportion of the sequence of interest produced by transfected or gene activated cells is such that the sorter is able to discriminate the two cell types.
In specific embodiments, signaling probes directed (e.g., complementary) to other sequences within the same or other coding exons, non-coding introns or non-coding untranslated sequences can also be designed and used. In particular embodiments, signaling probes to components of signaling pathways including the signaling pathway of the sweet taste receptor (e.g., T1R2 and T1R3) or the umami taste receptor (e.g., T1R1 and T1R3) can also be used.
The expression level of a taste receptor subunit (e.g., umami taste receptor subunit or sweet taste receptor subunit) (and optionally the G protein) may vary from cell to cell or cell line to cell line. The expression level in a cell or cell line may also decrease over time due to epigenetic events such as DNA methylation and gene silencing and loss of transgene copies. These variations can be attributed to a variety of factors, for example, the copy number of the transgene taken up by the cell, the site of genomic integration of the transgene, and the integrity of the transgene following genomic integration. One may use FACS or other cell sorting methods (i.e., MACS) to evaluate expression levels. Additional rounds of introducing signaling probes may be used, for example, to determine if and to what extent the cells remain positive over time for any one or more of the RNAs for which they were originally isolated.
In specific embodiments, cells with different absolute or relative fluorescence levels for at least one signaling probe can be isolated, for example by FACS, by gating subsets of cells with the suitable fluorescent levels relative to the entire cell population. For example, the top 5%, the top 10%, the top 15%, the top 20%, the top 25%, the top 30%, the top 35%, the top 40%, the top 45%, the top 50%, the top 55%, the top 60%, or the top 65%, of cells with the highest fluorescent signal for a particular signaling probe (or combination of signaling probes) can be gated and isolated by, e.g., FACS. In other embodiments, the top 2% to 3%, the top 5% to 10%, the top 5% to 15%, the top 5% to 20%, the top 5% to 30%, the top 40% to 50%, the top 10% to 30%, the top 10% to 25%, or the top 10% to 50%, of cells with the highest fluorescent signal for a particular signaling probe (or combination of signaling probes) can be gated and isolated by, e.g., FACS.
Once cells expressing the RNA for T1R1 and T1R3, or T1R2 and T1R3, (and optionally a G protein) are isolated, they may be cultured in media under any conditions for a length of time sufficient to produce and identify those cells stably expressing the subunits (and optionally G protein) (RNA or protein) and more preferably expressing a functional taste receptor (e.g., umami taste receptor or sweet taste receptor) (and optionally G protein). In another embodiment of the invention, adherent cells can be adapted to suspension before or after cell sorting and isolating single cells. In one embodiment, isolated cells may be grown individually or pooled to give rise to populations of cells. Individual or multiple cells or cell lines may also be grown separately or pooled. If a pool of cells or cell lines is stably expressing the subunits and more preferably a functional taste receptor (e.g., umami taste receptor or sweet taste receptor), it can be further fractionated until the cell or cell line or set of cells or cell lines having this characteristic is identified. This may make it easier to maintain large numbers of cells and cell lines without the requirements for maintaining each separately. Thus, a pool of cells or cell lines may be enriched for positive cells. An enriched pool is at least 50%, at least 60%, at least 70%, at least 80% or at least 90%, or 100% positive for the desired property or activity.
In a further aspect, the invention provides a method for producing the cells and cell lines of the invention. In one embodiment, the method comprises the steps of:
According to the method, the cells are cultured under a desired set of culture conditions. The conditions can be any desired conditions. Those of skill in the art will understand what parameters are comprised within a set of culture conditions. For example, culture conditions include but are not limited to: the media (Base media (DMEM, MEM, RPMI, serum-free, with serum, fully chemically defined, without animal-derived components), mono and divalent ion (sodium, potassium, calcium, magnesium) concentration, additional components added (amino acids, antibiotics, glutamine, glucose or other carbon source, HEPES, channel blockers, modulators of other targets, vitamins, trace elements, heavy metals, co-factors, growth factors, anti-apoptosis reagents), fresh or conditioned media, with HEPES, pH, depleted of certain nutrients or limiting (amino acid, carbon source)), level of confluency at which cells are allowed to attain before split/passage, feeder layers of cells, or gamma-irradiated cells, CO2, a three gas system (oxygen, nitrogen, carbon dioxide), humidity, temperature, still or on a shaker, and the like, which will be well known to those of skill in the art.
The cell culture conditions may be chosen for convenience or for a particular desired use of the cells. Advantageously, the invention provides cells and cell lines that are optimally suited for a particular desired use. That is, in embodiments of the invention in which cells are cultured under conditions for a particular desired use, cells are selected that have desired characteristics under the condition for the desired use.
By way of illustration, if cells will be used in assays in plates where it is desired that the cells are adherent, cells that display adherence under the conditions of the assay may be selected. Similarly, if the cells will be used for protein production, cells may be cultured under conditions appropriate for protein production and selected for advantageous properties for this use.
In some embodiments, the method comprises the additional step of measuring the growth rates of the separate cell cultures. Growth rates may be determined using any of a variety of techniques means that will be well known to the skilled worker. Such techniques include but are not limited to measuring ATP, cell confluency, light scattering, optical density (e.g., OD 260 for DNA). Preferably growth rates are determined using means that minimize the amount of time that the cultures spend outside the selected culture conditions.
In some embodiments, cell confluency is measured and growth rates are calculated from the confluency values. In some embodiments, cells are dispersed and clumps removed prior to measuring cell confluency for improved accuracy. Means for monodispersing cells are well-known and can be achieved, for example, by addition of a dispersing reagent to a culture to be measured. Dispersing agents are well-known and readily available, and include but are not limited to enzymatic dispersing agents, such as trypsin, and EDTA-based dispersing agents. Growth rates can be calculated from confluency date using commercially available software for that purpose such as HAMILTON VECTOR. Automated confluency measurement, such as using an automated microscopic plate reader is particularly useful. Plate readers that measure confluency are commercially available and include but are not limited to the CLONE SELECT IMAGER (Genetix). Typically, at least 2 measurements of cell confluency are made before calculating a growth rate. The number of confluency values used to determine growth rate can be any number that is convenient or suitable for the culture. For example, confluency can be measured multiple times over e.g., a week, 2 weeks, 3 weeks or any length of time and at any frequency desired.
When the growth rates are known, according to the method, the plurality of separate cell cultures are divided into groups by similarity of growth rates. By grouping cultures into growth rate bins, one can manipulate the cultures in the group together, thereby providing another level of standardization that reduces variation between cultures. For example, the cultures in a bin can be passaged at the same time, treated with a desired reagent at the same time, etc. Further, functional assay results are typically dependent on cell density in an assay well. A true comparison of individual clones is only accomplished by having them plated and assayed at the same density. Grouping into specific growth rate cohorts enables the plating of clones at a specific density that allows them to be functionally characterized in a high throughput format
The range of growth rates in each group can be any convenient range. It is particularly advantageous to select a range of growth rates that permits the cells to be passaged at the same time and avoid frequent renormalization of cell numbers. Growth rate groups can include a very narrow range for a tight grouping, for example, average doubling times within an hour of each other. But according to the method, the range can be up to 2 hours, up to 3 hours, up to 4 hours, up to 5 hours or up to 10 hours of each other or even broader ranges. The need for renormalization arises when the growth rates in a bin are not the same so that the number of cells in some cultures increases faster than others. To maintain substantially identical conditions for all cultures in a bin, it is necessary to periodically remove cells to renormalize the numbers across the bin. The more disparate the growth rates, the more frequently renormalization is needed.
In step d) the cells and cell lines may be tested for and selected for any physiological property including but not limited to: a change in a cellular process encoded by the genome; a change in a cellular process regulated by the genome; a change in a pattern of chromosomal activity; a change in a pattern of chromosomal silencing; a change in a pattern of gene silencing; a change in a pattern or in the efficiency of gene activation; a change in a pattern or in the efficiency of gene expression; a change in a pattern or in the efficiency of RNA expression; a change in a pattern or in the efficiency of RNAi expression; a change in a pattern or in the efficiency of RNA processing; a change in a pattern or in the efficiency of RNA transport; a change in a pattern or in the efficiency of protein translation; a change in a pattern or in the efficiency of protein folding; a change in a pattern or in the efficiency of protein assembly; a change in a pattern or in the efficiency of protein modification; a change in a pattern or in the efficiency of protein transport; a change in a pattern or in the efficiency of transporting a membrane protein to a cell surface change in growth rate; a change in cell size; a change in cell shape; a change in cell morphology; a change in % RNA content; a change in % protein content; a change in % water content; a change in % lipid content; a change in ribosome content; a change in mitochondrial content; a change in ER mass; a change in plasma membrane surface area; a change in cell volume; a change in lipid composition of plasma membrane; a change in lipid composition of nuclear envelope; a change in protein composition of plasma membrane; a change in protein; composition of nuclear envelope; a change in number of secretory vesicles; a change in number of lysosomes; a change in number of vacuoles; a change in the capacity or potential of a cell for: protein production, protein secretion, protein folding, protein assembly, protein modification, enzymatic modification of protein, protein glycosylation, protein phosphorylation, protein dephosphorylation, metabolite biosynthesis, lipid biosynthesis, DNA synthesis, RNA synthesis, protein synthesis, nutrient absorption, cell growth, mitosis, meiosis, cell division, to dedifferentiate, to transform into a stem cell, to transform into a pluripotent cell, to transform into a omnipotent cell, to transform into a stem cell type of any organ (i.e. liver, lung, skin, muscle, pancreas, brain, testis, ovary, blood, immune system, nervous system, bone, cardiovascular system, central nervous system, gastro-intestinal tract, stomach, thyroid, tongue, gall bladder, kidney, nose, eye, nail, hair, taste bud), to transform into a differentiated any cell type (i.e. muscle, heart muscle, neuron, skin, pancreatic, blood, immune, red blood cell, white blood cell, killer T-cell, enteroendocrine cell, taste, secretory cell, kidney, epithelial cell, endothelial cell, also including any of the animal or human cell types already listed that can be used for introduction of nucleic acid sequences), to uptake DNA, to uptake small molecules, to uptake fluorogenic probes, to uptake RNA, to adhere to solid surface, to adapt to serum-free conditions, to adapt to serum-free suspension conditions, to adapt to scaled-up cell culture, for use for large scale cell culture, for use in drug discovery, for use in high throughput screening, for use in a functional cell based assay, for use in calcium flux assays, for use in G protein reporter assays, for use in reporter cell based assays, for use in ELISA studies, for use in in vitro assays, for use in vivo applications, for use in secondary testing, for use in compound testing, for use in a binding assay, for use in panning assay, for use in an antibody panning assay, for use in imaging assays, for use in microscopic imaging assays, for use in multiwell plates, for adaptation to automated cell culture, for adaptation to miniaturized automated cell culture, for adaptation to large-scale automated cell culture, for adaptation to cell culture in multiwell plates (6, 12, 24, 48, 96, 384, 1536 or higher density), for use in cell chips, for use on slides, for use on glass slides, for microarray on slides or glass slides, for immunofluorescence studies, for use in protein purification, for use in biologics production, for use in the production of industrial enzymes, for use in the production of reagents for research, for use in cell therapy, for use in implantation into animals or humans, for use in isolation of factors secreted by the cell, for preparation of cDNA libraries, for purification of RNA, for purification of DNA, for infection by pathogens, viruses or other agent, for resistance to infection by pathogens, viruses or other agents, for resistance to drugs, for suitability to be maintained under automated miniaturized cell culture conditions, for use in the production of protein for characterization, including: protein crystallography, stimulation of the immune system, antibody production or generation or testing of antibodies. Those of skill in the art will readily recognize suitable tests for any of the above-listed properties. In particular embodiments, one or more of these physical properties may be a constant physical property associated with a taste receptor (e.g., sweet taste receptor or umami taste receptor) and can be used to monitor the expression of functional taste receptors (e.g., sweet taste receptors or umami taste receptors).
Tests that may be used to characterize cells and cell lines of the invention and/or matched panels of the invention include but are not limited to: Amino acid analysis, DNA sequencing, Protein sequencing, NMR, A test for protein transport, A test for nucleocytoplasmic transport, A test for subcellular localization of proteins, A test for subcellular localization of nucleic acids, Microscopic analysis, Submicroscopic analysis, Fluorescence microscopy, Electron microscopy, Confocal microscopy, Laser ablation technology, Cell counting and Dialysis. The skilled worker would understand how to use any of the above-listed tests.
According to the method, cells may be cultured in any cell culture format so long as the cells or cell lines are dispersed in individual cultures prior to the step of measuring growth rates. For example, for convenience, cells may be initially pooled for culture under the desired conditions and then individual cells separated one cell per well or vessel.
Cells may be cultured in multi-well tissue culture plates with any convenient number of wells. Such plates are readily commercially available and will be well knows to a person of skill in the art. In some cases, cells may preferably be cultured in vials or in any other convenient format, the various formats will be known to the skilled worker and are readily commercially available.
In embodiments comprising the step of measuring growth rate, prior to measuring growth rates, the cells are cultured for a sufficient length of time for them to acclimate to the culture conditions. As will be appreciated by the skilled worker, the length of time will vary depending on a number of factors such as the cell type, the chosen conditions, the culture format and may be any amount of time from one day to a few days, a week or more.
Preferably, each individual culture in the plurality of separate cell cultures is maintained under substantially identical conditions a discussed below, including a standardized maintenance schedule. Another advantageous feature of the method is that large numbers of individual cultures can be maintained simultaneously, so that a cell with a desired set of traits may be identified even if extremely rare. For those and other reasons, according to the invention, the plurality of separate cell cultures are cultured using automated cell culture methods so that the conditions are substantially identical for each well. Automated cell culture prevents the unavoidable variability inherent to manual cell culture.
Any automated cell culture system may be used in the method of the invention. A number of automated cell culture systems are commercially available and will be well-known to the skilled worker. In some embodiments, the automated system is a robotic system. Preferably, the system includes independently moving channels, a multichannel head (for instance a 96-tip head) and a gripper or cherry-picking arm and a HEPA filtration device to maintain sterility during the procedure. The number of channels in the pipettor should be suitable for the format of the culture. Convenient pipettors have, e.g., 96 or 384 channels. Such systems are known and are commercially available. For example, a MICROLAB STAR™ instrument (Hamilton) may be used in the method of the invention. The automated system should be able to perform a variety of desired cell culture tasks. Such tasks will be known by a person of skill in the art. They include but are not limited to: removing media, replacing media, adding reagents, cell washing, removing wash solution, adding a dispersing agent, removing cells from a culture vessel, adding cells to a culture vessel an the like.
The production of a cell or cell line of the invention may include any number of separate cell cultures. However, the advantages provided by the method increase as the number of cells increases. There is no theoretical upper limit to the number of cells or separate cell cultures that can be utilized in the method. According to the invention, the number of separate cell cultures can be two or more but more advantageously is at least 3, 4, 5, 6, 7, 8, 9, 10 or more separate cell cultures, for example, at least 12, at least 15, at least 20, at least 24, at least 25, at least 30, at least 35, at least 40, at least 45, at least 48, at least 50, at least 75, at least 96, at least 100, at least 200, at least 300, at least 384, at least 400, at least 500, at least 1000, at least 10,000, at least 100,000, at least 500,000 or more.
The cells and cell lines of the invention have enhanced stability as compared to cells and cell lines produced by conventional methods in the context of expression and expression levels (RNA or protein). To identify cells and cell lines characterized by such stable expression, a cell or cell line's expression of each taste receptor, e.g., umami taste receptor or sweet taste receptor subunit, (and optionally G protein), is measured over a timecourse and the expression levels are compared. Stable cell lines will continue expressing (RNA or protein) sweet taste receptor T1R2 and T1R3 subunits, or umami taste receptor T1R1 and T1R3 subunits, (and optionally G protein) throughout the timecourse. In some aspects of the invention, the timecourse may be for at least one week, two weeks, three weeks, etc., or at least one month, or at least two, three, four, five, six, seven, eight or nine months, or any length of time in between.
Isolated cells and cell lines may be further characterized, such as by qRT-PCR and single end-point RT-PCR to determine the absolute amounts and relative amounts of each taste receptor subunit, e.g., umami taste receptor subunit or sweet taste receptor subunit, (or G protein) being expressed (RNA). Preferably, the expansion levels of the two subunits are substantially the same in the cells and cell lines of this invention.
In other embodiments, the expression of a functional taste receptor, e.g., umami taste receptor or sweet taste receptor, (and G protein) is assayed over time. In these embodiments, stable expression is measured by comparing the results of functional assays over a timecourse. The assay of cell and cell line stability based on a functional assay provides the benefit of identifying cells and cell lines that not only stably express the T1R1 and T1R3 subunits of the umami taste receptor, or the T1R2 and T1R3 subunits of the sweet taste receptor, (and optionally the G protein) (RNA or protein), but also stably produce and properly process (e.g., post-translational modification, subunit assembly, and localization within the cell) the subunits (and G protein) to produce a functional umami taste receptor or sweet taste receptor.
Cells and cell lines of the invention have the further advantageous property of providing assays with high reproducibility as evidenced by their Z′ factor. See Zhang J H, Chung T D, Oldenburg K R, “A Simple Statistical Parameter for Use in Evaluation and Validation of High Throughput Screening Assays.” J. Biomol. Screen. 1999; 4(2):67-73. Z′ values relate to the quality of a cell or cell line because it reflects the degree to which a cell or cell line will respond consistently to modulators. Z′ is a statistical calculation that takes into account the signal-to-noise range and signal variability (i.e., from well to well) of the functional response to a reference compound across a multiwell plate. Z′ is calculated using data obtained from multiple wells with a positive control and multiple wells with a negative control. The ratio of their combined standard deviations multiplied by three to the difference in their mean values is subtracted from one to give the Z′ factor, according the equation below:
Z′ factor=1−((3σpositive control+3σnegative control)/(μpositive control−μnegative control))
The theoretical maximum Z′ factor is 1.0, which would indicate an ideal assay with no variability and limitless dynamic range. As used herein, a “high Z′” refers to a Z′ factor of Z′ of at least 0.6, at least 0.7, at least 0.75 or at least 0.8, or any decimal in between 0.6 and 1.0. In the case of a complex target such as taste receptor, e.g., umami taste receptor or sweet taste receptor, a high Z′ means a Z′ of at least 0.4 or greater. A score of close to 0 is undesirable because it indicates that there is overlap between positive and negative controls. In the industry, for simple cell-based assays, Z′ scores up to 0.3 are considered marginal scores, Z′ scores between 0.3 and 0.5 are considered acceptable, and Z′ scores above 0.5 are considered excellent. Cell-free or biochemical assays may approach higher Z′ scores, but Z′ scores for cell-based systems tend to be lower because cell-based systems are complex.
As those of ordinary skill in the art will recognize cell-based assays using conventional cells expressing even a single chain protein do not typically achieve a Z′ higher than 0.5 to 0.6. Cells with engineered expression (either from introduced coding sequences or gene activation) of multi-subunit proteins, if even reported in the art, would be lower due to their added complexity. Such cells would not be reliable for use in assays because the results would not be reproducible. Cells and cell lines of this invention, on the other hand, have higher Z′ values and advantageously produce consistent results in assays. Indeed, the taste receptor (e.g., umami taste receptor or sweet taste receptor) expressing cells and cell lines of the invention provide the basis for high throughput screening (HTS) compatible assays because they generally have higher Z′ values than conventionally produced cells. In some aspects of the invention, the cells and cell lines result in Z′ of at least 0.3, at least 0.4, at least 0.5, at least 0.6, at least 0.7, or at least 0.8. Even Z′ values of at least 0.3-0.4 for taste receptor (e.g., umami taste receptor or sweet taste receptor)-expressing cell are advantageous because the taste receptor (e.g., umami taste receptor or sweet taste receptor) is a multigene target. In other aspects of the invention, the cells and cell lines of the invention result in a Z′ of at least 0.7, at least 0.75 or at least 0.8 even after the cells are maintained for multiple passages, e.g., between 5-20 passages, including any integer in between 5 and 20. In some aspects of the invention, a Z′ of at least 0.7, at least 0.75 or at least 0.8 is observed in cells and cell lines maintained for 1, 2, 3, 4 or 5 weeks or 2, 3, 4, 5, 6, 7, 8 or 9 months, including any period of time in between.
A further advantageous property of the taste receptor (e.g., umami taste receptor or sweet taste receptor) cells and cell lines of the invention is that they stably express T1R2 and T1R3 subunits of the sweet taste receptor, or T1R1 and T1R3 subunits of the umami taste receptor, and optionally a G protein, in the absence of drug or other selective pressure. Thus, in preferred embodiments, the cells and cell lines of the invention are maintained in culture without any selective pressure. In further embodiments, cells and cell lines are maintained without any drug or antibiotics. As used herein, cell maintenance refers to culturing cells after they have been selected as described above for their sweet taste receptor subunit or umami taste receptor subunit (and optionally a G protein) expression. Maintenance does not refer to the optional step of growing cells under selective pressure (e.g., an antibiotic) prior to cell sorting where marker(s) introduced into the cells allow enrichment of stable transfectants in a mixed population.
Drug-free and selective pressure-free cell maintenance of the cells and cell lines of this invention provides a number of advantages. For example, drug-resistant cells may not express the co-transfected transgene of interest at adequate levels, because the selection relies on survival of the cells that have taken up the drug resistant gene, with or without the transgene. Further, selective drugs and other selective pressure factors are often mutagenic or otherwise interfere with the physiology of the cells, leading to skewed results in cell-based assays. For example, selective drugs may decrease susceptibility to apoptosis (Robinson et al., Biochemistry, 36(37):11169-11178 (1997)), increase DNA repair and drug metabolism (Deffie et al., Cancer Res. 48(13):3595-3602 (1988)), increase cellular pH (Thiebaut et al., J Histochem Cytochem. 38(5):685-690 (1990); Roepe et al., Biochemistry. 32(41):11042-11056 (1993); Simon et al., Proc Natl Acad Sci USA. 91(3):1128-1132 (1994)), decrease lysosomal and endosomal pH (Schindler et al., Biochemistry. 35(9):2811-2817 (1996); Altan et al., J Exp Med. 187(10):1583-1598 (1998)), decrease plasma membrane potential (Roepe et al., Biochemistry. 32(41):11042-11056 (1993)), increase plasma membrane conductance to chloride (Gill et al., Cell. 71(1):23-32 (1992)) and ATP (Abraham et al., Proc Natl Acad Sci U S A. 90(1):312-316 (1993)), and increase rates of vesicle transport (Altan et al., Proc Natl Acad Sci USA. 96(8):4432-4437 (1999)). Thus, the cells and cell lines of this invention allow screening assays that are free from the artifacts caused by selective pressure. In some preferred embodiments, the cells and cell lines of this invention are not cultured with selective pressure factors, such as antibiotics, before or after cell sorting, so that cells and cell lines with desired properties are isolated by sorting, even when not beginning with an enriched cell population.
In another aspect, the invention provides methods of using the cells and cell lines of the invention. The cells and cell lines of the invention may be used in any application for which functional taste receptor subunits (e.g., umami taste receptor subunits or sweet taste receptor subunits) are needed. The cells and cell lines may be used, for example, in an in vitro cell-based assay or an in vivo assay where the cells are implanted in an animal (e.g., a non-human mammal) to, e.g., screen for taste receptor modulators (e.g., umami taste receptor modulators or sweet taste receptor modulators); produce protein for crystallography and binding studies; and investigate compound selectivity and dosing, receptor/compound binding kinetic and stability, and effects of receptor expression on cellular physiology (e.g., electrophysiology, protein trafficking, protein folding, and protein regulation). The cells and cell lines of the invention also can be used in knock down studies to examine the roles of specific taste receptor subunits (e.g., umami taste receptor subunits or sweet taste receptor subunits).
Cells and cell lines expressing various combinations of subunits can be used separately or together to identify taste receptor modulators (e.g., umami taste receptor modulators or sweet taste receptor modulators). The cells and cell lines may be used to identify the roles of different forms of a taste receptor (e.g., umami taste receptor or sweet taste receptor) in different taste receptor pathologies by correlating the identity of in vivo forms of a taste receptor with the identity of known forms of taste receptors based on their response to various modulators. This allows selection of disease- or tissue-specific taste receptor modulators (e.g., umami taste receptor modulators or sweet taste receptor modulators) for highly targeted treatment of such taste receptor-related pathologies.
To identify a taste receptor modulator (e.g., umami taste receptor modulator or sweet taste receptor modulator), one exposes a cell or cell line of the invention to a test compound under conditions in which the taste receptor (e.g., umami taste receptor or sweet taste receptor) would be expected to be functional and then detects a statistically significant change (e.g., p<0.05) in taste receptor activity (e.g., umami taste receptor activity or sweet taste receptor activity) compared to a suitable control, e.g., cells that are not exposed to the test compound. Positive and/or negative controls using known agonists or antagonists and/or cells expressing different combinations of taste receptor subunits (e.g., umami taste receptor subunits or sweet taste receptor subunits) (and optionally a G protein) may also be used. In some embodiments, the taste receptor activity (e.g., umami taste receptor activity or sweet taste receptor activity) to be detected and/or measured is calcium release from the endoplasmic reticulum as a result of the down stream signaling events following taste receptor activation (e.g., umami taste receptor activation or sweet taste receptor activation). One of ordinary skill in the art would understand that various assay parameters may be optimized, e.g., signal to noise ratio.
In some embodiments, one or more cells or cell lines of the invention are exposed to a plurality of test compounds, for example, a library of test compounds. Such libraries of test compounds can be screened using the cell lines of the invention to identify one or more modulators of a taste receptor (e.g., umami taste receptor or sweet taste receptor). The test compounds can be chemical moieties including small molecules, polypeptides, peptides, peptide mimetics, antibodies or antigen-binding portions thereof. In the case of antibodies, they may be non-human antibodies, chimeric antibodies, humanized antibodies, or fully human antibodies. The antibodies may be intact antibodies comprising a full complement of heavy and light chains or antigen-binding portions of any antibody, including antibody fragments (such as Fab and Fab, Fab′, F(ab′)2, Fd, Fv, dAb and the like), single chain antibodies (scFv), single domain antibodies, all or an antigen-binding portion of a heavy chain or light chain variable region.
In some embodiments, prior to exposure to a test compound, the cells or cell lines of the invention may be modified by pretreatment with, for example, enzymes, including mammalian or other animal enzymes, plant enzymes, bacterial enzymes, protein modifying enzymes and lipid modifying enzymes. Such enzymes can include, for example, kinases, proteases, phosphatases, glycosidases, oxidoreductases, transferases, hydrolases, lyases, isomerases, ligases bacterial proteases, proteases from the gut, proteases from the GI tract, proteases in saliva, in the oral cavity, proteases from lysol cells/bacteria, and the like. Alternatively, the cells and cell lines may be exposed to the test compound first followed by enzyme treatment to identify compounds that alter the modification of the umami taste receptor or sweet taste receptor by the treatment.
In some embodiments, large compound collections are tested for taste receptor modulating activity (e.g., umami taste receptor modulating activity or sweet taste receptor modulating activity) in a cell-based, functional, high-throughput screen (HTS), e.g., using 96-well, 384-well, 1536-well or higher density formats. In some embodiments, a test compound or multiple test compounds, including a library of test compounds, may be screened using more than one cell or cell line of the invention. In the case of a cell or cell line of the invention that expresses a human sweet taste receptor, one can expose the cells or cell lines to a test compound to identify a compound that modulates sweet taste receptor activity (either increasing or decreasing) for use in the treatment of disease or condition characterized by undesired sweet taste receptor activity, or the decrease or absence of desired sweet taste receptor activity. Further, according to the methods of the invention, cells or cell lines of the invention can be used to identify compounds or substances that potentiate or inhibit sweet taste for use in ingestible substances.
In the case of a cell or cell line of the invention that expresses a human umami taste receptor, one can expose the cells or cell lines to a test compound to identify a compound that modulates umami taste receptor activity (either increasing or decreasing) for use in the treatment of disease or condition characterized by undesired umami taste receptor activity, or the decrease or absence of desired umami taste receptor activity. Further, according to the methods of the invention, cells or cell lines of the invention can be used to identify compounds or substances that potentiate or inhibit umami taste for use in ingestible substances.
In some embodiments, the cells and cell lines of the invention have increased sensitivity to modulators of a sweet taste receptor. For example, the cells and cell lines of this invention respond to all of the known classes of sweet compounds, e.g., natural sweeteners (e.g., glucose, fructose and sucrose); high intensity sweeteners (e.g., steviva, rebaudioside A, mogroside); and artificial sweeteners (e.g., asparatame, saccharin; and acesulfamek). See, e.g.,
In some embodiments, the cells and cell lines of the invention have increased sensitivity to modulators of an umami taste receptor. For example, the cells and cell lines of this invention respond to all of the known classes of umami compounds, e.g. MSG and sodium cyclamate. See, e.g.,
As used herein, EC50 refers to the concentration of a compound or substance required to induce a half-maximal activating response in the cell or cell line. As used herein, IC50 refers to the concentration of a compound or substance required to induce a half-maximal inhibitory response in the cell or cell line. EC50 and IC50 values may be determined using techniques that are well-known in the art, for example, a dose-response curve that correlates the concentration of a compound or substance to the response of the umami taste receptor-expressing cell line or sweet taste receptor-expressing cell line.
A further advantageous property of the taste receptor (e.g., umami taste receptor or sweet taste receptor) cells and cell lines of the invention is that modulators identified in initial screening using those cells and cell lines are functional in secondary functional assays, e.g., sip and spit, taste testing and sensory evaluation. As those of ordinary skill in the art will recognize, compounds identified in initial screening assays typically must be modified, such as by combinatorial chemistry, medicinal chemistry or synthetic chemistry, for their derivatives or analogs to be functional in secondary functional assays. However, due to the high physiological relevance of the taste receptor (e.g., umami taste receptor or sweet taste receptor) expressing cells and cell lines of this invention, many compounds identified using those cells and cell lines are functional without further modification.
In certain aspects, provided herein are methods that take advantage of the naturally occurring high degree of genetic diversity that exists in cells, and efficiently identify, select, and enrich for cells possessing desired gene expression profiles conferring desired properties (e.g., stable and/or high expression of functional taste receptors, for example, sweet taste receptors, umami taste receptors, or bitter taste receptors). The present methods can identify, select, and enrich for cells with improved properties from a pool of genetically diverse cells faster and more efficiently than conventional methods. In particular embodiments, the cells have not been genetically modified. In other particular embodiments, the present methods allow for the generation of novel homogeneous populations of cells possessing improved properties (e.g., more stable and/or higher expression of functional taste receptors, for example, sweet taste receptors, umami taste receptors, or bitter taste receptors).
In certain embodiments, the methods described herein comprise selecting naturally occurring cells with one or more desired properties (e.g., stable and/or high expression of functional taste receptors, for example, sweet taste receptors, umami taste receptors, or bitter taste receptors). In specific embodiments, the methods described herein comprise selecting cells with naturally occurring variants or mutations in one or more taste receptor genes (e.g., sweet taste receptor gene or umami taste receptor genes).
In specific embodiments, the methods described herein comprise selecting cells with naturally occurring variants or mutations in a promoter region of a gene or in a non-coding region of a gene (e.g., intron, 5′ untranslated region, and/or 3′ untranslated region). Variants or mutations in a promoter region of a gene or in a non-coding region of a gene may result in higher and/or more stable expression of the gene product. In specific embodiments, a promoter region of a gene or in a non-coding region of a gene has been modified, for example by methylation or acetylation of DNA. In particular embodiments, a cell comprises epigenetic modification affecting chromatin remodeling with respect to one or more of the gene of interest. Non-limiting examples of epigenetic modifications include, but are not limited to, acetylation, methylation, ubiquitylation, phosphorylation and sumoylation.
In certain other embodiments, the present methods comprise selecting cells that underwent prior treatments. Such prior treatments may be exposure to sunlight or ultraviolet (UV) light, mutagens such as ethyl methane sulfonate (EMS), and chemical agents. In specific embodiments, such prior treatments may include exposure to undesirable growth conditions, e.g., low oxygen or low nutrients conditions, or toxic conditions.
The methods described herein provide for identifying and/or selection of isolated cells (e.g., eukaryotic cells) that express one or more genes of interest (e.g., a taste receptor subunit gene, for example, sweet taste receptor subunit gene, umami taste receptor subunit gene, or bitter taste receptor subunit gene). In certain embodiments, the gene of interest is expressed at higher levels than other cells as a result of genetic variability. In particular embodiments, the methods described here comprise (a) introducing into a cell (e.g., eukaryotic cell) one or more signaling probes that is capable of detecting an RNA of interest (e.g., capable of hybridizing to a target sequence of an RNA of interest); and (b) determining whether the cell (e.g., eukaryotic cells) comprises the RNA of interest. Such methods may further comprise quantifying the level of the RNA of interest. In specific embodiments, the methods described herein for identifying a cell with a desired RNA expression profile, wherein the method comprises: (a) introducing into a eukaryotic cell (e.g., eukaryotic cell) a plurality of signaling probes each capable of detecting an RNA of interest; and (b) quantifying the RNA levels detected by the plurality of signaling probes. The desired gene expression profile may be determined by comparison to a reference population.
In particular embodiments, the methods described here comprise (a) introducing into a cell (e.g., eukaryotic cell) one or more signaling probes that is capable of detecting an RNA of a taste receptor (e.g., sweet taste receptor or umami taste receptor); and (b) determining whether the cell (e.g., eukaryotic cells) comprises the RNA of a taste receptor (e.g., sweet taste receptor or umami taste receptor). Such methods may further comprise quantifying the level of the RNA of a taste receptor (e.g., sweet taste receptor or umami taste receptor). In specific embodiments, the methods described herein for identifying a cell with a desired RNA expression profile, wherein the method comprises: (a) introducing into a eukaryotic cell (e.g., eukaryotic cell) a plurality of signaling probes each capable of detecting a plurality of RNAs of interest; and (b) quantifying the RNA levels detected by the plurality of signaling probes. The desired gene expression profile may be determined by comparison to a reference population. In particular embodiments, the plurality of RNAs of interest may comprise any combination of the following RNAs: RNA of T1R1, RNA of T1R2, RNA of T1R3, RNA of a G protein, and RNA of a gene associated with a taste receptor. In certain embodiments, the plurality of RNAs of interest comprise the RNA of T1R1 and the RNA of T1R3 (and optionally RNA of a G protein). In some embodiments, the plurality of RNAs of interest comprise the RNA of T1R2 and the RNA of T1R3 (and optionally RNA of a G protein).
In specific embodiments, such method further comprises the step of comparing the quantified RNA levels of the cell with the RNA levels in a reference cell, respectively. In particular embodiments, the plurality of signaling probes comprises at least 2, 3, 4, 5, 6, 7, 8, 9, 10, 15, 20, 25, 30, 35, 40, 45, 50, 60, 70, 80, 90, 100, 125, 150, 175, 200, 250, 300, 350, 500, 600, 700, 800, 900, or at least 1000 signaling probes. In some embodiments, the RNA of interest is translated. In other embodiments, the RNA of interest is not translated. In specific embodiments, the RNA of interest is encoded by a taste receptor subunit gene (e.g., sweet taste receptor subunit gene, umami taste receptor subunit gene, or bitter receptor subunit gene). In specific embodiments, the isolated cell (e.g., eukaryotic cell) expresses one or more recombinant RNA of interest.
In specific embodiments, eukaryotic cells identified and/or selected by the methods described herein have not been genetically engineered (e.g., do not recombinantly express one or more transgenes). In other embodiments, eukaryotic cells identified and/or selected by the methods described herein have been genetically engineered (e.g., do recombinantly express one or more transgenes). In specific embodiments, such cells are somatic cells or differentiated cells.
In other embodiments, the cell comprises a desired gene expression profile. In certain embodiments, the desired gene expression profile is achieved by genetic engineering or by increasing genetic variability. In specific embodiments, a desired gene expression profile may be determined based on comparison with that of a reference population.
In some embodiments, the methods described herein are for identifying and/or selecting cells that express an RNA of interest at a level higher than the average heterologous cell population. In some embodiments, the methods described herein are for identifying and/or selecting cells that express an RNA of interest (e.g., RNA of a sweet taste receptor or an umami taste receptor) at a level higher than the average heterologous cell population (e.g., unsorted cell line population, for example unsorted 293T cell line population). In some embodiments, the methods described herein are for identifying and/or selecting cells that express an RNA of interest (e.g., RNA of a sweet taste receptor or an umami taste receptor) at a level that is at least 20%, 30%, 40%, 50%, 60%, 70%, 80%, 90%, 95%, or 100% higher than the average heterologous cell population (e.g., unsorted cell line population, for example unsorted 293T cell line population). In some embodiments, the methods described herein are for identifying and/or selecting cells that express an RNA of interest (e.g., RNA of a sweet taste receptor or an umami taste receptor) at a level that is at least 1 fold, 1.5 fold, 2 fold, 3 fold, 4 fold, 5 fold, 6 fold, 7 fold, 8 fold, 9 fold, or 10 fold higher than the average heterologous cell population (e.g., unsorted cell line population, for example unsorted 293T cell line population).
In specific embodiments, the methods described herein are for identifying and/or selecting cells that express an RNA of interest at a level lower than the average heterologous cell population. An exemplary heterologous cell population may be a cell population of mixed cell types of different origin, a cell population of cells of one cell type that are genetically heterologous, or a cell population of one particular cell line from which the isolated cell is obtained using the methods described herein.
In particular embodiments, a cell isolated using the methods described herein is a cell clone from a cell line. In certain embodiments, a cell isolated using the methods described herein is a primary cell. In some embodiments, a cell isolated using the methods described herein is a transformed cell.
In certain embodiments, a cell is not a human cell. In particular embodiments, a cell is a cell derived from a mouse, rat, monkey, dog, cat, pig, sheep, goat, horse, chicken, frog, worm, insect (e.g., fly), fish, shellfish, or cow. In some embodiments, a cell is a mammalian cell or a eukaryotic cell. In other embodiments, a cell is a human cell. In some embodiments, a cell is a primary cell. In other embodiments, a cell is a transformed cell or a cell clone of a cell line.
In a specific aspect, provided herein is a method for isolating a cell that endogenously expresses a sweet taste receptor T1R2 subunit and/or sweet taste receptor T1R3 subunit, wherein the method comprises the steps of:
In another specific aspect, provided herein is a method for isolating a cell that endogenously expresses a sweet taste receptor T1R2 subunit and sweet taste receptor T1R3 subunit, wherein the method comprises the steps of:
In particular embodiments of such method, the population of cells is not known to express T1R2 or T1R3. In other specific embodiments of such method, any expression level of T1R2 or T1R3 in the isolated cell is at least 10 times, 50 times, 100 times, 250 times, 500 times, 750 times, 1000 times, 2500 times, 5000 times, 7500 times, 10000 times, 50000 times, or at least 100000 times higher than in the average cell of the population of cells. The expression level of a taste receptor subunit, for example T1R2 or T1R3, can be readily determined using methods known to one of skill in the art.
In a specific aspect, provided herein is a method for isolating a cell that endogenously expresses a umami taste receptor T1R1 subunit and/or umami taste receptor T1R3 subunit, wherein the method comprises the steps of:
In another specific aspect, provided herein is a method for isolating a cell that endogenously expresses an umami taste receptor T1R1 subunit and umami taste receptor T1R3 subunit, wherein the method comprises the steps of:
In particular embodiments of such method, the population of cells is not known to express T1R1 or T1R3. In other specific embodiments of such method, any expression level of T1R1 or T1R3 in the isolated cell is at least 10 times, 50 times, 100 times, 250 times, 500 times, 750 times, 1000 times, 2500 times, 5000 times, 7500 times, 10000 times, 50000 times, or at least 100000 times higher than in the average cell of the population of cells. The expression level of a taste receptor subunit, for example T1R1 or T1R3, can be readily determined using methods known to one of skill in the art.
Non-limiting examples of methods for determining protein expression level include immunoblotting (Western blotting), flow cytometry, or ELISA. Non-limiting examples of methods for determining RNA expression level include Northern blotting, RT-PCR, and real-time quantitative PCR. Such protein or RNA expression levels may be determined for a population of cells generally to determine the average expression level in the population.
In other particular embodiments of such method, genetic variability in the population of cells had been increased prior to said isolating step. In particular embodiments, provided herein is an isolated cell generated according to such method.
This application relates to novel cells and cell lines that have been engineered to express one or more bitter receptors. In some embodiments, the novel cells or cell lines of the invention express one or more functional bitter receptors. In other aspects, the invention provides methods of making and using the novel cells and cell lines.
According to one embodiment of the invention, the novel cells and cell lines are transfected with a nucleic acid encoding a native bitter receptor. In other embodiments the novel cells and cell lines are transfected with a nucleic acid encoding an allelic variant (i.e., a polymorphism) of a native bitter receptor, or a mutant bitter receptor. The novel cell lines of the invention stably express the introduced bitter receptor. In another embodiment, the novel cells and cell lines have a bitter receptor activated for expression by gene activation.
In a particular embodiment, the novel cells and cell lines express an endogenous bitter receptor as a result of engineered gene activation, i.e., activation of the expression of an endogenous gene, wherein the activation does not naturally occur in a cell without proper treatment. Engineered gene activation may turn on the expression of an endogenous bitter receptor, for example, where the endogenous bitter receptor is not expressed in the cell line without the proper treatment. Alternatively, engineered gene activation may result in increased expression level of the endogenous bitter receptor, for example, where the expression level of the endogenous gene in the cell line is undesirably low without the proper treatment, for example, not sufficient for functional assay of the bitter receptor in the cell line. Alternatively, engineered gene activation may be used to over-express an endogenous bitter receptor, for example, for isolating the endogenous bitter receptor from the cell line. Engineered gene activation can be achieved by a number of means known to those skilled in the art. For example, one or more transcription factors or transactivators of transcription of a gene can be over-expressed or induced to express by, e.g., introducing nucleic acids expressing the transcription factors or transactivators into a cell under the control of a constitutive or inducible promoter. If the endogenous gene is known to be under the control of an inducible promoter, expression can be induced by exposing the cell to a known inducer of the gene. In addition, a nucleic acid encoding the endogenous gene itself can be introduced into a cell to obtain an increased level of expression of the gene due to increased copy number in the genome. Furthermore, certain known inhibitors of the expression of an endogenous gene that are expressed by the cell can be knocked down or even knocked out in the cell using techniques well known in the art, e.g., RNAi, thereby increasing the expression of the endogenous gene.
The cells and cell lines of the invention comprising a bitter receptor, a mutant form thereof, or a naturally-occurring allelic variant thereof, can be used to identify modulators of bitter receptor function, including modulators that are specific for a particular bitter receptor mutant form or naturally-occurring allelic variant. The cells and cell lines can thus be used to obtain information about the properties, activities and roles of individual native or mutant forms or naturally-occurring allelic variants of bitter receptors and to identify bitter receptor modulators with activity for a particular native or mutant form or naturally-occurring allelic variant or for a subset of native or mutant forms or naturally-occurring allelic variants. These modulators are useful as therapeutics that target differentially modified bitter receptor forms in disease states or tissues. Because the polymorphism of bitter receptors in vivo, for example, may contribute to an undesired activity or disease state, cells and cell lines of this invention also can be used to screen for modulators for therapeutic use where alteration of the response of a mutant form or naturally-occurring allelic variant may be desired. The cells and cell lines are also useful to identify modulators that have activity with only subset of native or mutant forms or naturally-occurring allelic variants of a bitter receptor.
This invention also identifies and solves a difficulty in generating stable bitter receptor expressing cells and cell lines. As disclosed herein, we have discovered that expression of tagged bitter receptors led to incorrect assignment of bitter receptor agonists. It has been thought that specific tags, signal sequences, and/or chaperones were essential for the expression and/or transportation of the bitter receptors to the cell surface (Reichling, Meyerhof and Behrens, J. Neurochem. 106:1138-1148, 2008). This creates a dilemma and may lead to the identification of physiologically irrelevant modulators of tagged receptors. Accordingly, the physiologically relevant cell lines of the present invention can also facilitate identification of the ligands for orphan bitter receptors and dissection of the specificity of the various receptor-ligand interactions.
In a first aspect, the invention provides cells and cell lines that stably express one or more bitter receptors. In some embodiments, the expressed bitter receptors increase intracellular free calcium upon activation by an agonist. In some embodiments, a potentiator, agonist or activator can be a small molecule, a chemical moiety, a polypeptide, an antibody, or a food extract. In other embodiments, the expressed bitter receptors decrease intracellular free calcium upon inhibition by an antagonist. In some embodiments, an inhibitor, antagonist or blocker can be a small molecule, a chemical moiety, a polypeptide, an antibody, or a food extract. A potentiator, agonist, activator, inhibitor, antagonist or blocker may act upon all or upon a specific subset of bitter receptors. In further embodiments, the bitter receptor expressing cells and cell lines of the invention have enhanced properties compared to cells and cell lines made by conventional methods. For example, the bitter receptor expressing cells and cell lines have enhanced stability of expression (even when maintained in culture without selective antibiotics) and result in high Z′ values. In other aspects, the invention provides methods of making and using the bitter receptor expressing cells and cell lines.
In various embodiments, the cell or cell line of the invention expresses a bitter receptor at a consistent level of expression for at least 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, 100, 110, 120, 130, 140, 150, 160, 170, 180, 190, 200 days or over 200 days, where consistent expression refers to a level of expression that does not vary by more than:
1%, 2%, 3%, 4%, 5%, 6%, 7%, 8% 9% or 10% over 2 to 4 days of continuous cell culture; 2%, 4%, 6%, 8%, 10% or 12% over 5 to 15 days of continuous cell culture; 2%, 4%, 6%, 8%, 10%, 12%, 14%, 16%, 18% or 20% over 16 to 20 days of continuous cell culture; 2%, 4%, 6%, 8%, 10%, 12%, 14%, 16%, 18%, 20%, 22%, 24% over 21 to 30 days of continuous cell culture; 2%, 4%, 6%, 8%, 10%, 12%, 14%, 16%, 18%, 20%, 22%, 24%, 26%, 28% or 30% over 30 to 40 days of continuous cell culture; 2%, 4%, 6%, 8%, 10%, 12%, 14%, 16%, 18%, 20%, 22%, 24%, 26%, 28% or 30% over 41 to 45 days of continuous cell culture; 2%, 4%, 6%, 8%, 10%, 12%, 14%, 16%, 18%, 20%, 22%, 24%, 26%, 28% or 30% over 45 to 50 days of continuous cell culture; 2%, 4%, 6%, 8%, 10%, 12%, 14%, 16%, 18%, 20%, 22%, 24%, 26%, 28%, 30% or 35% over 45 to 50 days of continuous cell culture; 2%, 4%, 6%, 8%, 10%, 12%, 14%, 16%, 18%, 20%, 22%, 24%, 26%, 28% or 30% over 50 to 55 days of continuous cell culture; 2%, 4%, 6%, 8%, 10%, 12%, 14%, 16%, 18%, 20%, 22%, 24%, 26%, 28%, 30% or 35% over 50 to 55 days of continuous cell culture; 1%, 2%, 3%, 4%, 5%, 10%, 15%, 20%, 25%, 30%, 35% or 40% over 55 to 75 days of continuous cell culture; 1%, 2%, 3%, 4%, 5%, 6%, 10%, 15%, 20%, 25%, 30%, 35%, 40% or 45% over 75 to 100 days of continuous cell culture; 1%, 2%, 3%, 4%, 5%, 6%, 10%, 15%, 20%, 25%, 30%, 35%, 40% or 45% over 101 to 125 days of continuous cell culture; 1%, 2%, 3%, 4%, 5%, 6%, 10%, 15%, 20%, 25%, 30%, 35%, 40% or 45% over 126 to 150 days of continuous cell culture; 1%, 2%, 3%, 4%, 5%, 6%, 10%, 15%, 20%, 25%, 30%, 35%, 40% or 45% over 151 to 175 days of continuous cell culture; 1%, 2%, 3%, 4%, 5%, 6%, 10%, 15%, 20%, 25%, 30%, 35%, 40% or 45% over 176 to 200 days of continuous cell culture; 1%, 2%, 3%, 4%, 5%, 6%, 10%, 15%, 20%, 25%, 30%, 35%, 40% or 45% over more than 200 days of continuous cell culture.
According to the invention, the bitter receptor expressed by a cell or cell line can be from any mammal, including rat, mouse, rabbit, goat, dog, cow, pig or primate. In a preferred embodiment, the bitter receptor is human bitter receptor.
In some embodiments, a cell or cell line of the invention may comprise: a nucleotide sequence (SEQ ID NO: 51) that encodes a human TAS2R1; a nucleotide sequence (SEQ ID NO: 52) that encodes a human TAS2R3; a nucleotide sequence (SEQ ID NO: 53) that encodes a human TAS2R4; a nucleotide sequence (SEQ ID NO: 54) that encodes a human TAS2R5; a nucleotide sequence (SEQ ID NO: 55) that encodes a human TAS2R7; a nucleotide sequence (SEQ ID NO: 56) that encodes a human TAS2R8; a nucleotide sequence (SEQ ID NO: 57) that encodes a human TAS2R9; a nucleotide sequence (SEQ ID NO: 58) that encodes a human TAS2R10; a nucleotide sequence (SEQ ID NO: 59) that encodes a human TAS2R13; a nucleotide sequence (SEQ ID NO: 60) that encodes a human TAS2R14; a nucleotide sequence (SEQ ID NO: 61) that encodes a human TAS2R16; a nucleotide sequence (SEQ ID NO: 62) that encodes a human TAS2R38; a nucleotide sequence (SEQ ID NO: 63) that encodes a human TAS2R39; a nucleotide sequence (SEQ ID NO: 64) that encodes a human TAS2R40; a nucleotide sequence (SEQ ID NO: 65) that encodes a human TAS2R41; a nucleotide sequence (SEQ ID NO: 66) that encodes a human TAS2R43; a nucleotide sequence (SEQ ID NO: 67) that encodes a human TAS2R44; a nucleotide sequence (SEQ ID NO: 68) that encodes a human TAS2R45; a nucleotide sequence (SEQ ID NO: 69) that encodes a human TAS2R46; a nucleotide sequence (SEQ ID NO: 70) that encodes a human TAS2R47; a nucleotide sequence (SEQ ID NO: 71) that encodes a human TAS2R48; a nucleotide sequence (SEQ ID NO: 72) that encodes a human TAS2R49; a nucleotide sequence (SEQ ID NO: 73) that encodes a human TAS2R50; a nucleotide sequence (SEQ ID NO: 74) that encodes a human TAS2R55; a nucleotide sequence (SEQ ID NO: 75) that encodes a human TAS2R60; or any combination thereof.
In some embodiments, a cell or cell line of the invention may comprise: a polynucleotide sequence for: human TAS2R1 (SEQ ID NO: 77); human TAS2R3 (SEQ ID NO: 78); human TAS2R4 (SEQ ID NO: 79); human TAS2R5 (SEQ ID NO: 80); human TAS2R7 (SEQ ID NO: 81); human TAS2R8 (SEQ ID NO: 82); human TAS2R9 (SEQ ID NO: 83); human TAS2R10 (SEQ ID NO: 84); human TAS2R13 (SEQ ID NO: 85); human TAS2R14 (SEQ ID NO: 86); human TAS2R16 (SEQ ID NO: 87); human TAS2R38 (SEQ ID NO: 88); human TAS2R39 (SEQ ID NO: 89); human TAS2R40 (SEQ ID NO: 90); human TAS2R41 (SEQ ID NO: 91); human TAS2R43 (SEQ ID NO: 92); human TAS2R44 (SEQ ID NO: 93); human TAS2R45 (SEQ ID NO: 94); human TAS2R46 (SEQ ID NO: 95); human TAS2R47 (SEQ ID NO: 96); human TAS2R48 (SEQ ID NO: 97); human TAS2R49 (SEQ ID NO: 98); human TAS2R50 (SEQ ID NO: 99); human TAS2R55 (SEQ ID NO: 100); human TAS2R60 (SEQ ID NO: 101); or any combination thereof.
Nucleic acids encoding bitter receptors can be genomic DNA or cDNA. In some embodiments, the nucleic acids comprise one or more mutations, as compared to the nucleic acid sequences encoding wild type bitter receptors, that may or may not result in an amino acid substitution. In some other embodiments, the nucleic acids comprise one or more naturally-occurring allelic variants, as compared to the most frequently occurring nucleic acid sequences encoding a certain bitter receptor in a given population. Naturally-occurring allelic variants” include different amino acid sequences of a same bitter receptor that are naturally-occurring, e.g., those observed in a given population due to allelic variation or polymorphism.
Polymorphism is a common phenomenon in the human genome. Polymorphisms occurring within or near the bitter receptor genes may affect their expression or change their function by, e.g., up-regulating or down-regulating their expression levels or by changing their amino acid sequences. Table 20 shows reference numbers for unique polymorphisms, including single nucleotide polymorphisms (“SNPs”) related to human TAS2R genes, position of the SNPs in each reference sequence, and description of the SNPs. The reference numbers are searchable in the Single Nucleotide Polymorphism database (“dbSNP”) of the National Center for Biotechnology Information (“NCBI”; Bethesda, Md.).
Allelic variations of human bitter receptor genes resulting in coding sequence diversity have been studied and documented. See, e.g., Ueda et al., “Identification of coding single-nucleotide polymorphisms in human taste receptor genes involving bitter tasting”, Biochem Biophys Res Commun 285:147-151, 2001; Wooding et al., “Natural selection and molecular evolution in PTC, a bitter-taste receptor gene,” Am. J. Hum, Genet. 74:637-646, 2004; and Kim et al., “Worldwide haplotype diversity and coding sequence variation at human bitter taste receptor loci”, Human Mutation 26:199-204, 2005. Table 21 is a list of natural variations in the coding sequences of different human bitter receptors. The human bitter receptors, SEQ ID NOS of their coding sequences, and the protein sequences are listed in the first three columns. The nucleotide changes and their positions within each coding sequence as identified by their SEQ ID NOS are indicated in the columns under “Nucleotide change” and “Position of nucleotide change,” respectively. The amino acid changes within each bitter receptor as identified by their SEQ ID NOS are indicated in the column under “Description” using single-letter abbreviations. Their positions with reference to each corresponding SEQ ID NO are indicated in the column under “Position of amino acid change.” In addition, the “Description” column also contains identifiers of those variations that are searchable in dbSNP of NCBI. “Feature identifiers” are unique and stable feature identifiers assigned to some of the variations by the UniProt Protein Knowledgebase hosted by the European Bioinformatics Institute (Cambridge, United Kingdom). They are searchable within UniProt. “NA” denotes no feature identifiers assigned by UniProt yet.
Variation in human taste is a well-known phenomenon. Without wishing to be bound by theory, the variation of bitter taste may be related to polymorphisms of the bitter receptors. For example, polymorphisms in the hTAS2R38, a receptor for phenylthiocarbamide (PTC), has been linked to the ability to detect propylthiouracil (PROP) (Kim et al., “Positional cloning of the human quantitative trait locus underlying taste sensitivity to phenylthiocarbamide”, Science 299:1221-1225, 2003; Wooding et al., 2004). Certain polymorphisms in the hT2R43 gene allele make people very sensitive to the bitterness of the natural plant compounds aloin and aristolochic acid. People who do not possess this allele do not taste these compounds at low concentrations. Certain variations of the same hTAS2R43 gene allele make people more sensitive to the bitterness of saccharin. In addition, certain variations of a closely related gene's (hTAS2R44's) allele also make people more sensitive to the bitterness of saccharin. Furthermore, some people do not possess certain hTAS2R genes, which contribute to taste variation between individuals. Polymorphisms in bitter genes have also been linked to increased risk of certain diseases. Cell lines stably expressing a heterologous naturally-occurring bitter receptor, or an alleleic variant or polymorph thereof, or a mutant form thereof having one or more mutations (e.g., random mutations or site-specific mutations) that are not naturally-occurring, are all within the scope of the present invention.
In some embodiments, the nucleic acid is a fragment of the nucleic acid sequences provided hereinabove. Such bitter receptors that are fragments or have such modifications retain at least one biological property of a bitter receptor, e.g., its ability to increase intracellular free calcium. The invention encompasses cells and cell lines stably expressing a bitter receptor-encoding nucleotide sequence that is at least about 85% identical to a sequence disclosed herein. In some embodiments, the subunit-encoding sequence identity is at least 85%, 90%, 95%, 96%, 97%, 98%, 99% or higher compared to a subunit sequence provided herein. The invention also encompasses cells and cell lines wherein a nucleic acid encoding a bitter receptor hybridizes under stringent conditions to a nucleic acid provided herein encoding the corresponding bitter receptor.
In some embodiments, the cell or cell line comprises a bitter receptor-encoding nucleic acid sequence comprising a substitution compared to a sequence provided herein by at least one but less than 10, 20, 30, or 40 nucleotides, up to or equal to 1%, 5%, 10% or 20% of the nucleotide sequence or from a sequence substantially identical thereto (e.g., a sequence at least 85%, 90%, 95%, 96%, 97%, 98%, 99% or higher identical thereto, or that is capable of hybridizing under stringent conditions to the sequences disclosed). In some embodiments, the cell or cell line comprises a bitter receptor-encoding nucleic acid sequence comprising an insertion into or deletion from the sequences provided herein by less than 10, 20, 30, or 40 nucleotides up to or equal to 1%, 5%, 10% or 20% of the nucleotide sequence or from a sequence substantially identical thereto (e.g., a sequence at least 85%, 90%, 95%, 96%, 97%, 98%, 99% or higher identical thereto, or that is capable of hybridizing under stringent conditions to the sequences disclosed). The substitutions, insertions and deletions described herein may occur in any of the polynucleotides encoding bitter receptors in the cells or cell lines of the invention.
In some embodiments, where the nucleic acid substitution or modification results in an amino acid change, such as an amino acid substitution, the native amino acid may be replaced by a conservative or non-conservative substitution. In some embodiments, the sequence identity between the original and modified polypeptide sequence can differ by about 1%, 5%, 10% or 20% of the polypeptide sequence or from a sequence substantially identical thereto (e.g., a sequence at least 85%, 90%, 95%, 96%, 97%, 98%, 99% or higher identical thereto). Those of skill in the art will understand that a conservative amino acid substitution is one in which the amino acid side chains are similar in structure and/or chemical properties and the substitution should not substantially change the structural characteristics of the parent sequence. In embodiments comprising a nucleic acid comprising a mutation, the mutation may be a random mutation or a site-specific mutation.
Conservative modifications will produce bitter receptors having functional and chemical characteristics similar to those of the unmodified bitter receptor. A “conservative amino acid substitution” is one in which an amino acid residue is substituted by another amino acid residue having a side chain R group with similar chemical properties to the parent amino acid residue (e.g., charge or hydrophobicity). In general, a conservative amino acid substitution will not substantially change the functional properties of a protein. In cases where two or more amino acid sequences differ from each other by conservative substitutions, the percent sequence identity or degree of similarity may be adjusted upwards to correct for the conservative nature of the substitution. Means for making this adjustment are well-known to those of skill in the art. See, e.g., Pearson, Methods Mol. Biol. 243:307-31 (1994).
Examples of groups of amino acids that have side chains with similar chemical properties include 1) aliphatic side chains: glycine, alanine, valine, leucine, and isoleucine; 2) aliphatic-hydroxyl side chains: serine and threonine; 3) amide-containing side chains: asparagine and glutamine; 4) aromatic side chains: phenylalanine, tyrosine, and tryptophan; 5) basic side chains: lysine, arginine, and histidine; 6) acidic side chains: aspartic acid and glutamic acid; and 7) sulfur-containing side chains: cysteine and methionine. Preferred conservative amino acids substitution groups are: valine-leucine-isoleucine, phenylalanine-tyrosine, lysine-arginine, alanine-valine, glutamate-aspartate, and asparagine-glutamine. Alternatively, a conservative amino acid substitution is any change having a positive value in the PAM250 log-likelihood matrix disclosed in Gonnet et al., Science 256:1443-45 (1992). A “moderately conservative” replacement is any change having a nonnegative value in the PAM250 log-likelihood matrix.
In some embodiments, the bitter receptor-encoding nucleic acid sequence further comprises a tag. Such tags may encode, for example, a HIS tag, a myc tag, a hemagglutinin (HA) tag, protein C, VSV-G, FLU, yellow fluorescent protein (YFP), green fluorescent protein (GFP), FLAG, BCCP, maltose binding protein tag, Nus-tag, Softag-1, Softag-2, Strep-tag, S-tag, thioredoxin, GST, V5, TAP or CBP. A tag may be used as a marker to determine bitter receptor expression levels, intracellular localization, protein-protein interactions, bitter receptor regulation, or bitter receptor function. Tags may also be used to purify or fractionate bitter receptor. In some embodiments, a tag is cleavable from the bitter receptor to which it tags. This can be achieved by, e.g., introducing a specific protease cleavage site between the tag and the bitter receptor in the nucleic acid encoding the bitter receptor, and subjecting the tagged bitter receptor expressed by the nucleic acid to the treatment of the specific protease.
Host cells used to produce a cell or cell line of the invention may express in their native state one or more endogenous bitter receptor or lack expression of any bitter receptor. In the case where the cell or cell line expresses one or more of its own bitter receptors, also referred to as “endogenous” bitter receptors, the heterologous bitter receptor can be the same as one of the cell or cell line's endogenous bitter receptor(s). For example, a nucleic acid encoding an bitter receptor endogenous to a cell or cell line may be introduced into the cell or the cell line to increase the copy number of the gene encoding the bitter receptor in the cell or the cell line so that the bitter receptor is expressed at a higher level in the cell or cell line than without the introduced nucleic acid. The host cell may be a primary, germ, or stem cell, including an embryonic stem cell. The host cell may also be an immortalized cell. Primary or immortalized host cells may be derived from mesoderm, ectoderm or endoderm layers of eukaryotic organisms. The host cell may be endothelial, epidermal, mesenchymal, neural, renal, hepatic, hematopoietic, or immune cells. For example, the host cells may be intestinal crypt or villi cells, clara cells, colon cells, intestinal cells, goblet cells, enterochromafin cells, enteroendocrine cells. The host cells may be eukaryotic, prokaryotic, mammalian, human, primate, bovine, porcine, feline, rodent, marsupial, murine or other cells. The host cells may also be nonmammalian, such as yeast, insect, fungus, plant, lower eukaryotes and prokaryotes. Such host cells may provide backgrounds that are more divergent for testing bitter receptor modulators with a greater likelihood for the absence of expression products provided by the cell that may interact with the target. In preferred embodiments, the host cell is a mammalian cell. Examples of host cells that may be used to produce a cell or cell line of the invention include but are not limited to: human embryonic kidney 293T cells, established neuronal cell lines, pheochromocytomas, neuroblastomas fibroblasts, rhabdomyosarcomas, dorsal root ganglion cells, NS0 cells, CV-1 (ATCC CCL 70), COS-1 (ATCC CRL 1650), COS-7 (ATCC CRL 1651), CHO-K1 (ATCC CCL 61), 3T3 (ATCC CCL 92), NIH/3T3 (ATCC CRL 1658), HeLa (ATCC CCL 2), C127I (ATCC CRL 1616), BS-C-1 (ATCC CCL 26), MRC-5 (ATCC CCL 171), L-cells, HEK-293 (ATCC CRL1573) and PC12 (ATCC CRL-1721), HEK293T (ATCC CRL-11268), RBL (ATCC CRL-1378), SH-SY5Y (ATCC CRL-2266), MDCK (ATCC CCL-34), SJ-RH30 (ATCC CRL-2061), HepG2 (ATCC HB-8065), ND7/23 (ECACC 92090903), CHO (ECACC 85050302), Vero (ATCC CCL 81), Caco-2 (ATCC HTB 37), K562 (ATCC CCL 243), Jurkat (ATCC TIB-152), Per.C6 (Crucell, Leiden, The Netherlands), Huvec (ATCC Human Primary PCS 100-010, Mouse CRL 2514, CRL 2515, CRL 2516), HuH-7D12 (ECACC 01042712), 293 (ATCC CRL 10852), A549 (ATCC CCL 185), IMR-90 (ATCC CCL 186), MCF-7 (ATC HTB-22), U-20S (ATCC HTB-96), T84 (ATCC CCL 248), or any established cell line (polarized or nonpolarized) or any cell line available from repositories such as American Type Culture Collection (ATCC, 10801 University Blvd. Manassas, Va. 20110-2209 USA) or European Collection of Cell Cultures (ECACC, Salisbury Wiltshire SP4 0JG England).
In one embodiment, the host cell is an embryonic stem cell that is then used as the basis for the generation of transgenic animals. In some embodiments one or more bitter receptors may be expressed with desired temporal and/or tissue specific expression. Embryonic stem cells stably expressing at least one bitter receptor, and preferably a functional heterologous bitter receptor, may be implanted into organisms directly, or their nuclei may be transferred into other recipient cells and these may then be implanted, or they may be used to create transgenic animals.
As will be appreciated by those of skill in the art, any vector that is suitable for use with the host cell may be used to introduce a nucleic acid encoding a bitter receptor into the host cell. Examples of vectors that may be used to introduce the bitter receptor encoding nucleic acids into the host cell include but are not limited to plasmids, viruses, including retroviruses and lentiviruses, cosmids, artificial chromosomes and may include, for example, pCMVScript, pcDNA3.1 Hygro, pcDNA3.1neo, pcDNA3.1puro, pSV2neo, pIRES puro, pSV2 zeo, pFN11A (BIND) Flexi®, pGL4.31, pFC14A (HaloTag® 7) CMV Flexi®, pFC14K (HaloTag® 7) CMV Flexi®, pFN24A (HaloTag® 7) CMVd3 Flexi®, pFN24K (HaloTag® 7) CMVd3 Flexi®, HaloTag™ pHT2, pACT, pAdVAntage™, pALTER®-MAX, pBIND, pCAT®3-Basic, pCAT®3-Control, pCAT®3-Enhancer, pCAT®3-Promoter, pCI, pCMVTNT™, pG5luc, pSI, pTARGET™, pTNT™, pF12A RM Flexi®, pF12K RM Flexi®, pReg neo, pYES2/GS, pAd/CMV/V5-DEST Gateway® Vector, pAd/PL-DEST™ Gateway® Vector, Gateway® pDEST™27 Vector, Gateway® pEF-DEST51 Vector, Gateway® pcDNA™-DEST47 vector, pCMV/Bsd Vector, pEF6/His A, B, & c, pcDNA™6.2-DEST, pLenti6/TR, pLP-AcGFP1-C, pLPS-AcGFP1-N, pLP-IRESneo, pLP-TRE2, pLP-RevTRE, pLP-LNCX, pLP-CMV-HA, pLP-CMV-Myc, pLP-RetroQ, pLP-CMVneo. In some embodiments, the vectors comprise expression control sequences such as constitutive or conditional promoters. One of ordinary skill in the art will be able to select such sequences. For example, suitable promoters include but are not limited to CMV, TK, SV40 and EF-1α. In some embodiments, the promoters are inducible, temperature regulated, tissue specific, repressible, heat-shock, developmental, cell lineage specific, or temporal promoters or a combination or recombination of unmodified or mutagenized, randomized, shuffled sequences of any one or more of the above. In other embodiments, bitter receptors are expressed by gene activation or when a gene encoding a bitter receptor is episomal. RNAs encoding bitter receptors or mutant forms or naturally-occurring allelic variants thereof are preferably constitutively expressed.
In some embodiments, the vector lacks a selectable marker or drug resistance gene. In other embodiments, the vector optionally comprises a nucleic acid encoding a selectable marker such as a protein that confers drug or antibiotic resistance. Selection pressure may be applied in cell culture to select cells with desired sequences or traits, and is usually achieved by linking the expression of a polypeptide of interest with the expression of a selection marker that imparts to the cells resistance to a corresponding selective agent or pressure. Antibiotic selection includes, without limitation, the use of antibiotics (e.g., puromycin, neomycin, G418, hygromycin, bleomycin and the like). Non-antibiotic selection includes, without limitation, the use of nutrient deprivation, exposure to selective temperatures, and exposure to mutagenic conditions where selection marker may be e.g., glutamine synthetase, dihydrofolate reductase (DHFR), oabain, thymidine kinase (TK), hypoxanthine guanine phosphororibosyltransferase (HGPRT). Each vector for a sequence encoding a different bitter receptor may have the same or a different drug resistance or other selectable marker. If more than one of the drug resistance markers are the same, simultaneous selection may be achieved by increasing the level of the drug. Suitable markers will be well-known to those of skill in the art and include but are not limited to genes conferring resistance to any one of the following: Neomycin/G418, Puromycin, hygromycin, Zeocin, methotrexate and blasticidin. Although drug selection (or selection using any other suitable selection marker) is not a required step, it may be used to enrich the transfected cell population for stably transfected cells, provided that the transfected constructs are designed to confer drug resistance. If subsequent selection of cells expressing a bitter receptor is accomplished using signaling probes, selection too soon following transfection can result in some positive cells that may only be transiently and not stably transfected. However, this can be minimized by allowing sufficient cell passage allowing for dilution of transient expression in transfected cells.
In some embodiments, the vector comprises a nucleic acid sequence encoding an RNA tag sequence. “Tag sequence” refers to a nucleic acid sequence that is an expressed RNA or portion of an RNA that is to be detected by a signaling probe. Signaling probes may detect a variety of RNA sequences. Any of these RNAs may be used as tags. Signaling probes may be directed against the RNA tag by designing the probes to include a portion that is complementary to the sequence of the tag. In specific embodiments, signaling probes are directed (e.g., complementary) to sequences within the same or different coding exons, non-coding introns or non-coding untranslated sequences of an RNA. In particular embodiments, signaling probes can be directed to RNA of components of signaling pathways including the signaling pathway of the bitter taste receptor. The tag sequence may be a 3′ untranslated region of the plasmid that is cotranscribed and comprises a target sequence for signaling probe binding. The RNA encoding the gene of interest may include the tag sequence or the tag sequence may be located within a 5′-untranslated region or 3′-untranslated region. In some embodiments, the tag is not with the RNA encoding the gene of interest. The tag sequence can be in frame with the protein-coding portion of the message of the gene or out of frame with it, depending on whether one wishes to tag the protein produced. Thus, the tag sequence does not have to be translated for detection by the signaling probe. The tag sequences may comprise multiple target sequences that are the same or different, wherein one signaling probe hybridizes to each target sequence. The tag sequences may encode an RNA having secondary structure. The structure may be a three-arm junction structure. Examples of tag sequences that may be used in the invention, and to which signaling probes may be prepared, include but are not limited to the RNA transcript of epitope tags such as, for example, a HIS tag, a myc tag, a hemagglutinin (HA) tag, protein C, VSV-G, FLU, yellow fluorescent protein (YFP), green fluorescent protein (GFP), FLAG, BCCP, maltose binding protein tag, Nus-tag, Softag-1, Softag-2, Strep-tag, S-tag, thioredoxin, GST, V5, TAP or CBP. As described herein, one of ordinary skill in the art could create his or her own RNA tag sequences.
In another aspect, cells and cell lines of the invention stably expresses a G protein. There are two families of G proteins, heterotrimeric G proteins and monomeric G proteins. Heterotrimeric G proteins are activated by G protein coupled receptors (“GPCRs”), and include three subunits: Gα, Gβ and Gγ. As used herein, the term G protein includes any one of these subunits, for example a Gα, or any combination thereof, as well as a heterotrimeric G protein with all three subunits. In the inactive state, Gα, Gβ and Gγ form a trimer. The β and γ subunits are closely bound to one another and are referred to as the beta-gamma complex. Gα separates from Gβγ after ligand binding to the GPCR. The Gβγ complex is released from the Gα subunit after its GDP-GTP exchange. The Gβγ complex can activate other second messengers or gate ion channels. The four families of G alpha include: Gs (stimulatory) which increase cAMP synthesis by activating adenylate cyclase; Gi (inhibitory) that inhibits adenylate cyclase; the G12/13 family regulates various cell movement processes (i.e. cytoskeleton, cell junctions); and Gq, which stimulates calcium signaling and phospholipase C. The monomeric G proteins are homologous to the α subunit of the heterotrimeric G proteins. Any G protein may be expressed in the cells or cell lines of the invention, including, but not limited to, transducin (e.g., GNAT1, GNAT2, and guanine nucleotide-binding protein G(t)), gustducin (e.g., GNAT3 guanine nucleotide binding protein and α transducin 3), human GNA15 (guanine nucleotide binding protein (G protein) α15 (Gq class; synonym GNA16) and mouse Gα15, and their chimera proteins, e.g. Gα15-GNA15 (also known as Gα15-Gα16). In a preferred embodiment, the G protein is mouse Gα15 (SEQ ID NO: 102). In another preferred embodiment, the G protein is human GNA15 (SEQ ID NO: 50) or is a human G protein encoded by a nucleic acid comprising SEQ ID NO: 76. The G protein may also be any mammalian G protein, such as, but not limited to, any mammalian G protein listed in Table 7. The G protein stably expressed by the cell can be endogenous to the cell. Alternatively, the stable expression of the G protein may be a result of stable transfection of a nucleic acid encoding the G protein into the cell. Cells stably expressing a heterologous G protein are known in the art, e.g., HEK293/Gα15 cells (Chandrashekar et al., “T2Rs function as bitter taste receptors”, Cell 100:703-711, 2000; Bufe et al., “The human TAS2R16 receptor mediates bitter taste in response to β-glucopyranosides”, Na Genet 32:397-401). In other embodiments, a nucleic acid encoding a G protein and a nucleic acid encoding a bitter receptor can be transfected consecutively into a host cell, with either the nucleic acid encoding the G protein transfected first or the nucleic acid encoding the bitter receptor transfected first. In other embodiments, a nucleic acid encoding a G protein and a nucleic acid encoding a bitter receptor can be co-transfected into a host cell on the same or different vectors. Accordingly, selection of cells stably expressing both the G protein and the bitter receptor, can likewise be carried out consecutively or simultaneously. The cells or cell lines that may be used to stably express a G protein are the same as those that may be used to stably express a bitter receptor, as explained above. Vectors for transfecting G proteins optionally comprise a nucleic acid encoding a selectable marker for antibiotic or non-antibiotic selection, as explained above.
In some embodiments of the invention, cells or cell lines of the invention co-express other proteins with the bitter receptor(s). In a preferred embodiment, the other protein is at least one other taste receptor, such as a sweet (TAS1R2/TAS1R3) receptor or an umami (TAS1R1/TAS1R3) receptor. Proteins that are co-expressed with bitter receptors may be expressed by any mechanism, such as, but not limited to, endogenously in the host cell or heterologously from a vector. Also, in other embodiments of the invention, more than one type of bitter receptor may be stably expressed in a cell or cell line.
In another aspect, cells and cell lines of the invention have enhanced stability as compared to cells and cell lines produced by conventional methods. To identify stable expression, a cell or cell line's expression of a bitter receptor is measured over a time course and the expression levels are compared. Stable cell lines will continue expressing the bitter receptor throughout the time course. In some aspects of the invention, the time course may be for at least one week, two weeks, three weeks, four weeks, five weeks, six weeks, etc., or at least one month, or at least two, three, four, five, six, seven, eight or nine months, or any length of time in between. Isolated cells and cell lines can be further characterized, such as by qRT-PCR and single end-point RT-PCR to determine the absolute amounts and relative amounts of a bitter receptor being expressed. In some embodiments, stable expression is measured by comparing the results of functional assays over a time course. The measurement of stability based on functional assay provides the benefit of identifying clones that not only stably express the mRNA of the gene of interest, but also stably produce and properly process (e.g., post-translational modification, subunit assembly, and localization within the cell) the protein encoded by the gene of interest that functions appropriately.
Cells and cell lines of the invention have the further advantageous property of providing assays with high reproducibility as evidenced by their Z′ factor. See Zhang J H, Chung T D, Oldenburg K R, “A Simple Statistical Parameter for Use in Evaluation and Validation of High Throughput Screening Assays.” J. Biomol. Screen. 1999; 4(2):67-73. Z′ values pertain to the quality of a cell or cell line because it reflects the degree to which a cell or cell line will respond consistently to modulators. Z′ is a statistical calculation that takes into account the signal-to-noise range and signal variability (i.e., from well to well) of the functional response to a reference compound across a multiwell plate. Z′ is calculated using data obtained from multiple wells with a positive control and multiple wells with a negative control. The ratio of their combined standard deviations multiplied by three to the difference in their mean values is subtracted from one to give the Z′ factor, according the equation below:
Z′ factor=1−((3σpositive control+3σnegative control)/(μpositive control−μnegative control))
The theoretical maximum Z′ factor is 1.0, which would indicate an ideal assay with no variability and limitless dynamic range. Lower scores (i.e., scores close to 0) are undesirable because it indicates that there is overlap between positive and negative controls. In the industry, for simple cell-based assays, Z′ scores up to 0.3 are considered marginal scores, Z′ scores between 0.3 and 0.5 are considered acceptable, and Z′ scores above 0.5 are considered excellent. Cell-free or biochemical assays may approach higher Z′ scores, but Z′ scores for cell-based systems tend to be lower because cell-based systems are complex.
Cells and cell lines of the invention have Z′ values reflecting their ability to advantageously produce consistent results in assays. Bitter receptor expressing cells and cell lines of the invention provided the basis for high throughput screening (HTS) compatible assays because they generally have Z′ factors of at least 0.45. In some aspects of the invention, the cells and cell lines result in Z′ of at least 0.3, at least 0.4, at least 0.5, at least 0.6, at least 0.7, or at least 0.8. In other aspects of the invention, the cells and cell lines of the invention result in a Z′ of at least 0.3, at least 0.4, at least 0.5, at least 0.6, at least 0.7, or at least 0.8 maintained for multiple passages, e.g., between 5-20 passages, including any integer in between 5 and 20. In some aspects of the invention, the cells and cell lines result in a Z′ of at least 0.4, at least 0.5, at least 0.6, at least 0.7, or at least 0.8 maintained for 1, 2, 3, 4 or 5 weeks or 2, 3, 4, 5, 6, 7, 8 or 9 months, including any period of time in between.
Also according to the invention, cells and cell lines that express a form of a naturally occurring bitter receptor or a naturally-occurring allelic variant thereof, as well as cells and cell lines that express a mutant form of bitter receptor, can be characterized for intracellular free calcium levels. In some embodiments, the cells and cell lines of the invention express bitter receptor with “physiologically relevant” activity. As used herein, physiological relevance refers to a property of a cell or cell line expressing a bitter receptor whereby the bitter receptor causes an increase in intracellular free calcium as a naturally occurring bitter receptor of the same type would when activated, and responds to modulators in the same ways that naturally occurring bitter receptors of the same type would respond when modulated by the same compounds. Bitter receptor-expressing cells and cell lines of this invention, including some mutant forms of bitter receptor and some naturally-occurring allelic variants of bitter receptors, preferably demonstrate comparable function to cells that normally express native bitter receptor in a suitable assay, such as an assay measuring intracellular free calcium. Such assays are known to those skilled in the art (Nahorski, “Pharmacology of intracellular signaling pathways,” Brit. J. Pharm. 147:S38-S45, 2000)). Such comparisons are used to determine a cell or cell line's physiological relevance. “Sip and spit” taste tests using a panel of trained taste testers also may be used to further validate bitter receptor physiological relevance in cells and cell lines of the invention. The results of sip and spit taste tests using modulators identified via screening of native or mutant forms of a bitter receptor or a naturally-occurring allelic variant thereof can be used to validate the physiological relevance of these different forms.
In some embodiments, the cells and cell lines of the invention have increased sensitivity to modulators of bitter receptors. Cells and cell lines of the invention respond to modulators and increase intracellular free calcium with physiological range EC50 or IC50 values for bitter receptors. As used herein, EC50 refers to the concentration of a compound or substance required to induce a half-maximal activating response in the cell or cell line. As used herein, IC50 refers to the concentration of a compound or substance required to induce a half-maximal inhibitory response in the cell or cell line. EC50 and IC50 values may be determined using techniques that are well-known in the art, for example, a dose-response curve that correlates the concentration of a compound or substance to the response of the bitter receptor-expressing cell line.
A further advantageous property of the bitter receptor expressing cells and cell lines of the inventions, flowing from the physiologically relevant function of the bitter receptors is that modulators identified in initial screening are functional in secondary functional assays, e.g., sip and spit or other taste tests, or functional magnetic resonance imaging (MRI) to scan brain activity in response to taste modulating compounds. As those of ordinary skill in the art will recognize, compounds identified in initial screening assays typically must be modified, such as by combinatorial chemistry, medicinal chemistry or synthetic chemistry, for their derivatives or analogs to be functional in secondary functional assays. However, due to the high physiological relevance of the present bitter receptor expressing cells and cell lines, many compounds identified therewith are functional without modification.
In some embodiments, properties of the cells and cell lines of the invention, such as stability, physiological relevance, reproducibility in an assay (Z′), or physiological EC50 or IC50 values, are achievable under specific culture conditions. In some embodiments, the culture conditions are standardized and rigorously maintained without variation, for example, by automation. Culture conditions may include any suitable conditions under which the cells or cell lines are grown and may include those known in the art. A variety of culture conditions may result in advantageous biological properties for any of the bitter receptors, or their mutants or allelic variants.
In other embodiments, the cells and cell lines of the invention with desired properties, such as stability, physiological relevance, reproducibility in an assay (Z′), or physiological EC50 or IC50 values, can be obtained within one month or less. For example, the cells or cell lines may be obtained within 2, 3, 4, 5, or 6 days, or within 1, 2, 3 or 4 weeks, or any length of time in between.
One aspect of the invention provides a collection of clonal cells and cell lines, each expressing the same bitter receptor, or different bitter receptors, including different mutant forms and naturally-occurring allelic variants of one or more bitter receptors. The collection may include, for example, cells or cell lines expressing combinations of different bitter receptors, or mutant forms of bitter receptors, naturally-occurring allelic variants of bitter receptors, or any combination thereof. The collection may also include cells or cell lines expressing the same bitter receptor and different G proteins, or any possible dimers or other multimers, including heteromultimers or chimeric dimers or multimers, of bitter receptors.
When collections or panels of cells or cell lines are produced, e.g., for drug screening, the cells or cell lines in the collection or panel may be matched such that they are the same (including substantially the same) with regard to one or more selective physiological properties. The “same physiological property” in this context means that the selected physiological property is similar enough amongst the members in the collection or panel such that the cell collection or panel can produce reliable results in drug screening assays; for example, variations in readouts in a drug screening assay will be due to, e.g., the different biological activities of test compounds on cells expressing different native or mutant forms of bitter receptors, or allelic variants thereof, rather than due to inherent variations in the cells. For example, the cells or cell lines may be matched to have the same growth rate, i.e., growth rates with no more than one, two, three, four, or five hour difference amongst the members of the cell collection or panel. This may be achieved by, for example, binning cells by their growth rate into five, six, seven, eight, nine, or ten groups, and creating a panel using cells from the same binned group. Methods of determining cell growth rate are well known in the art. The cells or cell lines in a panel also can be matched to have the same Z′ factor (e.g., Z′ factors that do not differ by more than 0.1), bitter receptor expression level (e.g., bitter receptor expression levels that do not differ by more than 5%, 10%, 15%, 20%, 25%, or 30%), adherence to tissue culture surfaces, and the like. Matched cells and cell lines can be grown under identical conditions, achieved by, e.g., automated parallel processing, to maintain the selected physiological property.
Matched cell panels of the invention can be used to, for example, identify modulators with defined activity (e.g., agonist or antagonist) on bitter receptors; to profile compound activity across different bitter receptors, or their allelic variants or mutant forms; to identify modulators active on just one type of bitter receptor, or its allelic variant or mutant form; and to identify modulators active on just a subset of bitter receptors. The matched cell panels of the invention allow high throughput screening. Screenings that used to take months to accomplish can now be accomplished within weeks.
To make cells and cell lines of the invention, one can use, for example, the technology described in U.S. Pat. No. 6,692,965 and International Patent Publication WO/2005/079462. Both of these documents are incorporated herein by reference in their entirety for all purposes. This technology provides real-time assessment of millions of cells such that any desired number of clones (from hundreds to thousands of clones) may be selected. Using cell sorting techniques, such as flow cytometric cell sorting (e.g., with a FACS machine) or magnetic cell sorting (e.g., with a MACS machine), one cell per well may be automatically deposited with high statistical confidence in a culture vessel (such as a 96 well culture plate). The speed and automation of the technology allows multigene cell lines to be readily isolated.
Using the technology, the RNA sequence for each bitter receptor may be detected using a signaling probe, also referred to as a molecular beacon or fluorogenic probe. In some embodiments, the molecular beacon recognizes a target tag sequence as described above. In another embodiment, the molecular beacon recognizes a sequence within the bitter receptor coding sequence itself. Signaling probes may be directed against the RNA tag or bitter receptor coding sequence by designing the probes to include a portion that is complementary to the RNA sequence of the tag or the bitter receptor coding sequence, respectively. These same techniques may be used to detect the RNA sequence for a G protein, if used.
Nucleic acids comprising a sequence encoding a bitter receptor, a sequence encoding a G protein, a tag sequence, or any combination thereof, and optionally further comprising a nucleic acid encoding a selectable marker may be introduced into selected host cells by well known methods. The methods include but not limited to transfection, viral delivery, protein or peptide mediated insertion, coprecipitation methods, lipid based delivery reagents (lipofection), cytofection, lipopolyamine delivery, dendrimer delivery reagents, electroporation or mechanical delivery. Examples of transfection reagents are GENEPORTER, GENEPORTER2, LIPOFECTAMINE, LIPOFECTAMINE 2000, FUGENE 6, FUGENE HD, TFX-10, TFX-20, TFX-50, OLIGOFECTAMINE, TRANSFAST, TRANSFECTAM, GENESHUTTLE, TROJENE, GENESILENCER, X-TREMEGENE, PERFECTIN, CYTOFECTIN, SIPORT, UNIFECTOR, SIFECTOR, TRANSIT-LT1, TRANSIT-LT2, TRANSIT-EXPRESS, IFECT, RNAI SHUTTLE, METAFECTENE, LYOVEC, LIPOTAXI, GENEERASER, GENEJUICE, CYTOPURE, JETSI, JETPEI, MEGAFECTIN, POLYFECT, TRANSMESSANGER, RNAiFECT, SUPERFECT, EFFECTENE, TF-PEI-KIT, CLONFECTIN, and METAFECTINE.
Following introduction of the bitter receptor coding sequences, and optionally also the G protein coding sequences, into host cells and optional subsequent drug selection, molecular beacons (e.g., fluorogenic probes) are introduced into the cells and cell sorting is used to isolate cells positive for their signals. Molecular beacons may also be used to identify expression of bitter receptors, G proteins, or both. If expression of both are identified, their identification may be carried out simultaneously or sequentially. Multiple rounds of sorting may be carried out, if desired. In one embodiment, the flow cytometric cell sorter is a FACS machine. MACS (magnetic cell sorting) or laser ablation of negative cells using laser-enabled analysis and processing can also be used. According to this method, cells expressing at least one bitter receptor are detected and recovered. The bitter receptor (and, optionally, G protein) sequences may be integrated at different locations of the genome in the cell. The expression level of the introduced genes encoding the bitter receptors (and, if introduced, the G proteins) may vary based upon integration site. The skilled worker will recognize that sorting can be gated for any desired expression level (i.e., above background or at a specific level above background). Further, stable cell lines may be obtained wherein one or more of the introduced genes encoding a bitter receptor or G protein is episomal.
Signaling probes useful in this invention are known in the art and generally are oligonucleotides comprising a sequence complementary to a target sequence and a signal emitting system so arranged that no signal is emitted when the probe is not bound to the target sequence and a signal is emitted when the probe binds to the target sequence. By way of non-limiting illustration, the signaling probe may comprise a fluorophore and a quencher positioned in the probe so that the quencher and fluorophore are brought together in the unbound probe. Upon binding between the probe and the target sequence, the quencher and fluorophore separate, resulting in emission of signal. International publication WO/2005/079462, for example, describes a number of signaling probes that may be used in the production of the cells and cell lines of this invention. Where tag sequences are used, the vector for each of the bitter receptors, if multiple bitter receptors are expressed in one cell, or the vectors for bitter receptors and G proteins, can comprise the same or a different tag sequence. Whether the tag sequences are the same or different, the signaling probes may comprise different signal emitters, such as different colored fluorophores and the like so that (RNA) expression of each different bitter receptor and, optionally, G protein, may be separately detected. By way of illustration, the signaling probe that specifically detects one bitter receptor mRNA can comprise a red fluorophore and the probe that detects an introduced G protein (RNA) can comprise a green fluorophore. Also by way of illustration, the signaling probe that specifically detects one bitter receptor mRNA can comprise a red fluorophore, the signaling probe that specifically detects another bitter receptor mRNA can comprise a green fluorophore, and the signaling probe that specifically detects a third bitter receptor mRNA can comprise a yellow fluorophore. Those of skill in the art will be aware of other means for differentially detecting the expression of multiple bitter receptors or bitter receptors and G proteins with a signaling probe in a cell transfected with multiple bitter receptors.
Nucleic acids encoding signaling probes may be introduced into the selected host cell by any of numerous means that will be well-known to those of skill in the art, including but not limited to transfection, coprecipitation methods, lipid based delivery reagents (lipofection), cytofection, lipopolyamine delivery, dendrimer delivery reagents, electroporation or mechanical delivery. Examples of transfection reagents are GENEPORTER, GENEPORTER2, LIPOFECTAMINE, LIPOFECTAMINE 2000, FUGENE 6, FUGENE HD, TFX-10, TFX-20, TFX-50, OLIGOFECTAMINE, TRANSFAST, TRANSFECTAM, GENESHUTTLE, TROJENE, GENESILENCER, X-TREMEGENE, PERFECTIN, CYTOFECTIN, SIPORT, UNIFECTOR, SIFECTOR, TRANSIT-LT1, TRANSIT-LT2, TRANSIT-EXPRESS, IFECT, RNAI SHUTTLE, METAFECTENE, LYOVEC, LIPOTAXI, GENEERASER, GENEJUICE, CYTOPURE, JETSI, JETPEI, MEGAFECTIN, POLYFECT, TRANSMESSANGER, RNAiFECT, SUPERFECT, EFFECTENE, TF-PEI-KIT, CLONFECTIN, and METAFECTINE.
In one embodiment, the signaling probes are designed to be complementary to either a portion of the RNA encoding a bitter receptor or to portions of their 5′ or 3′ untranslated regions. If the signaling probe designed to recognize a messenger RNA of interest is able to detect spurious endogenously existing target sequences, the proportion of these in comparison to the proportion of the sequence of interest produced by transfected cells is such that the sorter is able to discriminate the two cell types. Accordingly, the constructs comprising the nucleic acids encoding the bitter receptors do not require and do not include sequences encoding a fluorescent protein. Accordingly, heterologous fluorescent proteins are not expressed in the cells of the invention. The cells or cell lines of the invention stably express heterologous native bitter receptors. Although such protein tags/chaperones have been in use for expression of a number of bitter receptors to facilitate trafficking of a bitter receptor to the cell surface, the cells and cell lines of the invention advantageously functionally express novel bitter receptors at the cell surface without them.
In another embodiment of the invention, adherent cells can be adapted to suspension before or after cell sorting and isolating single cells. In other embodiments, isolated cells may be grown individually or pooled to give rise to populations of cells. Individual or multiple cell lines may also be grown separately or pooled. If a pool of cell lines is producing a desired activity or has a desired property, it can be further fractionated until the cell line or set of cell lines having this effect is identified. Pooling cells or cell lines may make it easier to maintain large numbers of cell lines without the requirements for maintaining each separately. Thus, a pool of cells or cell lines may be enriched for positive cells. An enriched pool may have at least 50%, at least 60%, at least 70%, at least 80%, at least 90% or 100% are positive for the desired property or activity.
In a further aspect, the invention provides a method for producing the cells and cell lines of the invention. In one embodiment, the method comprises the steps of:
According to the method, the cells are cultured under a desired set of culture conditions. The conditions can be any desired conditions. Those of skill in the art will understand what parameters are comprised within a set of culture conditions. For example, culture conditions include but are not limited to: the media (Base media (DMEM, MEM, RPMI, serum-free, with serum, fully chemically defined, without animal-derived components), mono and divalent ion (sodium, potassium, calcium, magnesium) concentration, additional components added (amino acids, antibiotics, glutamine, glucose or other carbon source, HEPES, channel blockers, modulators of other targets, vitamins, trace elements, heavy metals, co-factors, growth factors, anti-apoptosis reagents), fresh or conditioned media, with HEPES, pH, depleted of certain nutrients or limiting (amino acid, carbon source)), level of confluency at which cells are allowed to attain before split/passage, feeder layers of cells, or gamma-irradiated cells, CO2, a three gas system (oxygen, nitrogen, carbon dioxide), humidity, temperature, still or on a shaker, and the like, which will be well known to those of skill in the art.
The cell culture conditions may be chosen for convenience or for a particular desired use of the cells. Advantageously, the invention provides cells and cell lines that are optimally suited for a particular desired use. That is, in embodiments of the invention in which cells are cultured under conditions for a particular desired use, cells are selected that have desired characteristics under the condition for the desired use.
By way of illustration, if cells will be used in assays in plates where it is desired that the cells are adherent, cells that display adherence under the conditions of the assay may be selected. Similarly, if the cells will be used for protein production, cells may be cultured under conditions appropriate for protein production and selected for advantageous properties for this use.
In some embodiments, the method comprises the additional step of measuring the growth rates of the separate cell cultures. Growth rates may be determined using any of a variety of techniques means that will be well known to the skilled worker. Such techniques include but are not limited to measuring ATP, cell confluency, light scattering, optical density (e.g., OD 260 for DNA). Preferably growth rates are determined using means that minimize the amount of time that the cultures spend outside the selected culture conditions.
In some embodiments, cell confluency is measured and growth rates are calculated from the confluency values. In some embodiments, cells are dispersed and clumps removed prior to measuring cell confluency for improved accuracy. Means for monodispersing cells are well-known and can be achieved, for example, by addition of a dispersing reagent to a culture to be measured. Dispersing agents are well-known and readily available, and include but are not limited to enzymatic dispersing agents, such as trypsin, and EDTA-based dispersing agents. Growth rates can be calculated from confluency date using commercially available software for that purpose such as HAMILTON VECTOR. Automated confluency measurement, such as using an automated microscopic plate reader is particularly useful. Plate readers that measure confluency are commercially available and include but are not limited to the CLONE SELECT IMAGER (Genetix). Typically, at least 2 measurements of cell confluency are made before calculating a growth rate. The number of confluency values used to determine growth rate can be any number that is convenient or suitable for the culture. For example, confluency can be measured multiple times over e.g., a week, 2 weeks, 3 weeks or any length of time and at any frequency desired.
When the growth rates are known, according to the method, the plurality of separate cell cultures are divided into groups by similarity of growth rates. By grouping cultures into growth rate bins, one can manipulate the cultures in the group together, thereby providing another level of standardization that reduces variation between cultures. For example, the cultures in a bin can be passaged at the same time, treated with a desired reagent at the same time, etc. Further, functional assay results are typically dependent on cell density in an assay well. A true comparison of individual clones is only accomplished by having them plated and assayed at the same density. Grouping into specific growth rate cohorts enables the plating of clones at a specific density that allows them to be functionally characterized in a high throughput format
The range of growth rates in each group can be any convenient range. It is particularly advantageous to select a range of growth rates that permits the cells to be passaged at the same time and avoid frequent renormalization of cell numbers. Growth rate groups can include a very narrow range for a tight grouping, for example, average doubling times within an hour of each other. But according to the method, the range can be up to 2 hours, up to 3 hours, up to 4 hours, up to 5 hours or up to 10 hours of each other or even broader ranges. The need for renormalization arises when the growth rates in a bin are not the same so that the number of cells in some cultures increases faster than others. To maintain substantially identical conditions for all cultures in a bin, it is necessary to periodically remove cells to renormalize the numbers across the bin. The more disparate the growth rates, the more frequently renormalization is needed.
In step d) the cells and cell lines may be tested for and selected for any physiological property including but not limited to: a change in a cellular process encoded by the genome; a change in a cellular process regulated by the genome; a change in a pattern of chromosomal activity; a change in a pattern of chromosomal silencing; a change in a pattern of gene silencing; a change in a pattern or in the efficiency of gene activation; a change in a pattern or in the efficiency of gene expression; a change in a pattern or in the efficiency of RNA expression; a change in a pattern or in the efficiency of RNAi expression; a change in a pattern or in the efficiency of RNA processing; a change in a pattern or in the efficiency of RNA transport; a change in a pattern or in the efficiency of protein translation; a change in a pattern or in the efficiency of protein folding; a change in a pattern or in the efficiency of protein assembly; a change in a pattern or in the efficiency of protein modification; a change in a pattern or in the efficiency of protein transport; a change in a pattern or in the efficiency of transporting a membrane protein to a cell surface change in growth rate; a change in cell size; a change in cell shape; a change in cell morphology; a change in % RNA content; a change in % protein content; a change in % water content; a change in % lipid content; a change in ribosome content; a change in mitochondrial content; a change in ER mass; a change in plasma membrane surface area; a change in cell volume; a change in lipid composition of plasma membrane; a change in lipid composition of nuclear envelope; a change in protein composition of plasma membrane; a change in protein composition of nuclear envelope; a change in number of secretory vesicles; a change in number of lysosomes; a change in number of vacuoles; a change in the capacity or potential of a cell for: protein production, protein secretion, protein folding, protein assembly, protein modification, enzymatic modification of protein, protein glycosylation, protein phosphorylation, protein dephosphorylation, metabolite biosynthesis, lipid biosynthesis, DNA synthesis, RNA synthesis, protein synthesis, nutrient absorption, cell growth, mitosis, meiosis, cell division, to dedifferentiate, to transform into a stem cell, to transform into a pluripotent cell, to transform into a omnipotent cell, to transform into a stem cell type of any organ (i.e. liver, lung, skin, muscle, pancreas, brain, testis, ovary, blood, immune system, nervous system, bone, cardiovascular system, central nervous system, gastro-intestinal tract, stomach, thyroid, tongue, gall bladder, kidney, nose, eye, nail, hair, taste bud), to transform into a differentiated any cell type (i.e. muscle, heart muscle, neuron, skin, pancreatic, blood, immune, red blood cell, white blood cell, killer T-cell, enteroendocrine cell, taste, secretory cell, kidney, epithelial cell, endothelial cell, also including any of the animal or human cell types already listed that can be used for introduction of nucleic acid sequences), to uptake DNA, to uptake small molecules, to uptake fluorogenic probes, to uptake RNA, to adhere to solid surface, to adapt to serum-free conditions, to adapt to serum-free suspension conditions, to adapt to scaled-up cell culture, for use for large scale cell culture, for use in drug discovery, for use in high throughput screening, for use in a functional cell based assay, for use in calcium flux assays, for use in G-protein reporter assays, for use in reporter cell based assays, for use in ELISA studies, for use in in vitro assays, for use in vivo applications, for use in secondary testing, for use in compound testing, for use in a binding assay, for use in panning assay, for use in an antibody panning assay, for use in imaging assays, for use in microscopic imaging assays, for use in multiwell plates, for adaptation to automated cell culture, for adaptation to miniaturized automated cell culture, for adaptation to large-scale automated cell culture, for adaptation to cell culture in multiwell plates (6, 12, 24, 48, 96, 384, 1536 or higher density), for use in cell chips, for use on slides, for use on glass slides, for microarray on slides or glass slides, for immunofluorescence studies, for use in protein purification, for use in biologics production, for use in the production of industrial enzymes, for use in the production of reagents for research, for use in cell therapy, for use in implantation into animals or humans, for use in isolation of factors secreted by the cell, for preparation of cDNA libraries, for purification of RNA, for purification of DNA, for infection by pathogens, viruses or other agent, for resistance to infection by pathogens, viruses or other agents, for resistance to drugs, for suitability to be maintained under automated miniaturized cell culture conditions, for use in the production of protein for characterization, including: protein crystallography, stimulation of the immune system, antibody production or generation or testing of antibodies. Those of skill in the art will readily recognize suitable tests for any of the above-listed properties. In particular embodiments, one or more of these physical properties may be a constant physical property associated with a bitter taste receptor and can be used to monitor the expression of functional bitter taste receptors.
Tests that may be used to characterize cells and cell lines of the invention and/or matched panels of the invention include but are not limited to: Amino acid analysis, DNA sequencing, Protein sequencing, NMR, A test for protein transport, A test for nucleocytoplasmic transport, A test for subcellular localization of proteins, A test for subcellular localization of nucleic acids, Microscopic analysis, Submicroscopic analysis, Fluorescence microscopy, Electron microscopy, Confocal microscopy, Laser ablation technology, Cell counting and Dialysis. The skilled worker would understand how to use any of the above-listed tests.
According to the method, cells may be cultured in any cell culture format so long as the cells or cell lines are dispersed in individual cultures prior to the step of measuring growth rates. For example, for convenience, cells may be initially pooled for culture under the desired conditions and then individual cells separated one cell per well or vessel.
Cells may be cultured in multi-well tissue culture plates with any convenient number of wells. Such plates are readily commercially available and will be well knows to a person of skill in the art. In some cases, cells may preferably be cultured in vials or in any other convenient format, the various formats will be known to the skilled worker and are readily commercially available.
In embodiments comprising the step of measuring growth rate, prior to measuring growth rates, the cells are cultured for a sufficient length of time for them to acclimate to the culture conditions. As will be appreciated by the skilled worker, the length of time will vary depending on a number of factors such as the cell type, the chosen conditions, the culture format and may be any amount of time from one day to a few days, a week or more.
Preferably, each individual culture in the plurality of separate cell cultures is maintained under substantially identical conditions a discussed below, including a standardized maintenance schedule. Another advantageous feature of the method is that large numbers of individual cultures can be maintained simultaneously, so that a cell with a desired set of traits may be identified even if extremely rare. For those and other reasons, according to the invention, the plurality of separate cell cultures are cultured using automated cell culture methods so that the conditions are substantially identical for each well. Automated cell culture prevents the unavoidable variability inherent to manual cell culture.
Any automated cell culture system may be used in the method of the invention. A number of automated cell culture systems are commercially available and will be well-known to the skilled worker. In some embodiments, the automated system is a robotic system. Preferably, the system includes independently moving channels, a multichannel head (for instance a 96-tip head) and a gripper or cherry-picking arm and a HEPA filtration device to maintain sterility during the procedure. The number of channels in the pipettor should be suitable for the format of the culture. Convenient pipettors have, e.g., 96 or 384 channels. Such systems are known and are commercially available. For example, a MICROLAB STAR™ instrument (Hamilton) may be used in the method of the invention. The automated system should be able to perform a variety of desired cell culture tasks. Such tasks will be known by a person of skill in the art. They include but are not limited to: removing media, replacing media, adding reagents, cell washing, removing wash solution, adding a dispersing agent, removing cells from a culture vessel, adding cells to a culture vessel an the like.
The production of a cell or cell line of the invention may include any number of separate cell cultures. However, the advantages provided by the method increase as the number of cells increases. There is no theoretical upper limit to the number of cells or separate cell cultures that can be utilized in the method. According to the invention, the number of separate cell cultures can be two or more but more advantageously is at least 3, 4, 5, 6, 7, 8, 9, 10 or more separate cell cultures, for example, at least 12, at least 15, at least 20, at least 24, at least 25, at least 30, at least 35, at least 40, at least 45, at least 48, at least 50, at least 75, at least 96, at least 100, at least 200, at least 300, at least 384, at least 400, at least 500, at least 1000, at least 10,000, at least 100,000, at least 500,000 or more.
A further advantageous property of the bitter receptor expressing cells and cell lines of the invention is that they stably express one or more bitter receptors in the absence of drug selection pressure. Thus, in preferred embodiments, cells and cell lines of the invention are maintained in culture without any selective drug. In further embodiments, cells and cell lines are maintained without any antibiotics. As used herein, cell maintenance refers to culturing cells after they have been selected as described above for their bitter receptor expression. Maintenance does not refer to the optional step of growing cells in a selective drug (e.g., an antibiotic) prior to cell sorting where drug resistance marker(s) introduced into the cells allow enrichment of stable transfectants in a mixed population.
Drug-free cell maintenance provides a number of advantages. For example, drug-resistant cells do not always express the co-transfected transgene of interest at adequate levels, because the selection relies on survival of the cells that have taken up the drug resistant gene, with or without the transgene. Further, selective drugs are often mutagenic or otherwise interfere with the physiology of the cells, leading to skewed results in cell-based assays. For example, selective drugs may decrease susceptibility to apoptosis (Robinson et al., Biochemistry, 36(37):11169-11178 (1997)), increase DNA repair and drug metabolism (Deffie et al., Cancer Res. 48(13):3595-3602 (1988)), increase cellular pH (Thiebaut et al., J Histochem Cytochem. 38(5):685-690 (1990); Roepe et al., Biochemistry. 32(41):11042-11056 (1993); Simon et al., Proc Natl Acad Sci USA. 91(3):1128-1132 (1994)), decrease lysosomal and endosomal pH (Schindler et al., Biochemistry. 35(9):2811-2817 (1996); Altan et al., J Exp Med. 187(10):1583-1598 (1998)), decrease plasma membrane potential (Roepe et al., Biochemistry. 32(41):11042-11056 (1993)), increase plasma membrane conductance to chloride (Gill et al., Cell. 71(1):23-32 (1992)) and ATP (Abraham et al., Proc Natl Acad Sci USA. 90(1):312-316 (1993)), and increase rates of vesicle transport (Altan et al., Proc Natl Acad Sci USA. 96(8):4432-4437 (1999)). Thus, the cells and cell lines of this invention allow screening assays that are free from any artifact caused by selective drugs. In some preferred embodiments, the cells and cell lines of this invention are not cultured with selective drugs such as antibiotics before or after cell sorting, so that cells and cell lines with desired properties are isolated by sorting, even when not beginning with an enriched cell population.
The expression level of a bitter receptor may vary from cell or cell line to cell or cell line. The expression level in a cell or cell line also may decrease over time due to epigenetic events such as DNA methylation and gene silencing and loss of transgene copies. These variations can be attributed to a variety of factors, for example, the copy number of the transgene taken up by the cell, the site of genomic integration of the transgene, and the integrity of the transgene following genomic integration. One may use FACS or other cell sorting methods (i.e., MACS) to evaluate expression levels. Additional rounds of introducing signaling probes may be used, for example, to determine if and to what extent the cells remain positive over time for any one or more of the RNAs for which they were originally isolated.
In specific embodiments, cells with different absolute or relative fluorescence levels for at least one signaling probe can be isolated, for example by FACS, by gating subsets of cells with the suitable fluorescent levels relative to the entire cell population. For example, the top 5%, the top 10%, the top 15%, the top 20%, the top 25%, the top 30%, the top 35%, the top 40%, the top 45%, the top 50%, the top 55%, the top 60%, or the top 65%, of cells with the highest fluorescent signal for a particular signaling probe (or combination of signaling probes) can be gated and isolated by, e.g., FACS. In other embodiments, the top 2% to 3%, the top 5% to 10%, the top 5% to 15%, the top 5% to 20%, the top 5% to 30%, the top 40% to 50%, the top 10% to 30%, the top 10% to 25%, or the top 10% to 50%, of cells with the highest fluorescent signal for a particular signaling probe (or combination of signaling probes) can be gated and isolated by, e.g., FACS.
The ease with which it is possible to re-isolate cells expressing all of the desired RNAs from cells which may no longer express all of the RNAs of interest makes it possible to maintain cell lines in the presence of no drug or minimal concentrations of drug. Signaling probes may also be re-applied to cells or cell lines generated previously, for example, to determine if and to what extent the cells are still positive for any one or more of the RNAs for which they were originally isolated.
In another aspect, the invention provides methods of using the cells and cell lines of the invention. The cells and cell lines of the invention may be used in any application for which functional bitter receptors are needed. The cells and cell lines may be used, for example, but not limited to, in an in vitro cell-based assay or an in vivo assay where the cells are implanted in an animal (e.g., a non-human mammal) to, e.g., screen for bitter receptor modulators; assess bitterness of substances; produce protein for crystallography and binding studies; and investigate compound selectivity and dosing, receptor/compound binding kinetic and stability, and effects of receptor expression on cellular physiology (e.g., electrophysiology, protein trafficking, protein folding, and protein regulation). The cells and cell lines of the invention also can be used in knock down studies to study the roles of specific bitter receptors or groups of bitter receptors.
Cells and cell lines expressing various combinations of bitter receptors can be used separately or together to identify bitter receptor modulators, including those specific for a particular bitter receptor or a mutant form or a naturally-occurring allelic variant of bitter receptor and to obtain information about the activities of individual forms.
Modulators include any substance or compound that alters an activity of a bitter receptor or a mutant form or a naturally-occurring allelic variant thereof. The modulator can be a bitter receptor agonist (potentiator or activator) or antagonist (inhibitor or blocker), including partial agonists or antagonists, selective agonists or antagonists and inverse agonists, and can be an allosteric modulator. A substance or compound is a modulator even if its modulating activity changes under different conditions or concentrations or with respect to different forms (e.g., mutant forms and naturally-occurring allelic variants) of bitter receptor. In other aspects, a modulator may change the ability of another modulator to affect the function of a bitter receptor. For example, a modulator of a form of bitter receptor that is not inhibited by an antagonist may render that form of bitter receptor susceptible to inhibition by the antagonist.
The present cells and cell lines may be used to identify the roles of different forms of bitter receptors in different bitter receptors pathologies by correlating the identity of in vivo forms of bitter receptor with the identify of known forms of bitter receptors based on their response to various modulators. This allows selection of disease- or tissue-specific bitter receptor modulators for highly targeted treatment of such bitter receptor-related pathologies or other physiological conditions. For example, because many naturally occurring bitter compounds are toxic, bitter receptors may serve as warning sensors against the ingestion of toxic food compounds. Bitter receptors expressed in the gastrointestinal mucosa might participate in the functional detection of nutrients and harmful substances in the lumen and prepare the gut to absorb them or initiate a protective response. They might also participate in the control of food intake through the activation of gut-brain neural pathways. Accordingly, bitter receptor modulators identified using the cell lines and methods of the present invention may be used to regulate nutrient uptake in a number of contexts, e.g., to control the appetite and/or reduce nutrient uptake in the gut of the obese, or to control the hunger feeling and/or to increase the uptake of nutrients and/or energy from food in the malnourished. Bitter receptor modulators may also be useful in identifying bitter compounds, further characterizing the specific chemical or structural motifs or key residues of bitter receptors that influence their binding properties, identifying bitter receptors that are broadly, moderately or selectively tuned for ligand binding, defining groups and subgroups of bitter receptors based on their binding profiles, deorphaning orphan bitter receptors, using such data for molecular modeling or drug design for bitter receptors, and determining in which tissues various bitter receptors are active.
To identify a bitter receptor modulator, one can expose a novel cell or cell line of the invention to a test compound under conditions in which the bitter receptor would be expected to be functional and then detect a statistically significant change (e.g., p<0.05) in bitter receptor activity compared to a suitable control, e.g., cells that are not exposed to the test compound. Positive and/or negative controls using known agonists or antagonists and/or cells expressing different bitter receptor or mutant forms or naturally-occurring allelic variants thereof may also be used. In some embodiments, the bitter receptor activity to be detected and/or measured is change in intracellular free calcium levels. One of ordinary skill in the art would understand that various assay parameters may be optimized, e.g., signal to noise ratio.
In a further related aspect, the invention provides a method of identifying ligands of other GPCRs. Any GPCR may be used in this method, including, but not limited to, mammalian or human GPCRs and orphaned or deorphaned GPCRs. A non-limiting example of deorphaned GPCRs are opioids (listed in Table 9). A cell or cell line expressing a GPCR may be screened using a compound or extract library to generate an expression profile for the receptor. Receptors with similar profiles may be grouped together and screened with compounds to identify a ligand(s) that binds a receptor(s).
In a further aspect, the invention provides a method of identifying ligands for orphan bitter receptors, i.e. the invention provides a method of deorphaning bitter receptors. A cell or cell line expressing a bitter receptor with no known modulator may be screened using a compound or extract library to generate an expression profile for the receptor. Optionally, receptors with similar profiles (if any) are grouped together and screened with known bitter compounds to a ligand(s) that binds a receptor(s). Once a ligand is identified, the results may be further verified with taste tests. Advantageously, the cells and cell lines of the invention stably express native (i.e. untagged) bitter receptors so the ligands identified using this method are accurate and relevant. In a related embodiment, the method of deorphaning bitter receptors may be used to deorphan any orphan GPCR, including any orphan mammalian GPCR or any orphan human GPCR, such as those listed in Table 8.
In some embodiments, one or more cells or cell lines, including collections of cell lines, of the invention are exposed to a plurality of test compounds, for example, a library of test compounds. A library of test compounds can be screened using the cell lines of the invention to identify one or more modulators. The test compounds can be chemical moieties including small molecules, polypeptides, peptides, peptide mimetics, antibodies or antigen-binding portions thereof. In the case of antibodies, they may be non-human antibodies, chimeric antibodies, humanized antibodies, or fully human antibodies. The antibodies may be intact antibodies comprising a full complement of heavy and light chains or antigen-binding portions of any antibody, including antibody fragments (such as Fab, Fab′, F(ab′)2, Fd, Fv, dAb and the like), single chain antibodies (scFv), single domain antibodies, all or an antigen-binding portion of a heavy chain or light chain variable region.
Cells or cell lines of the invention may also be used to create collections with specific variables. For example, a collection may include: cells or cell lines that all express the same bitter receptor and different G proteins to study receptor-G protein interactions; or cells or cell lines that express multiple endogenous and/or heterologous bitter receptors to study possible dimerization or formation of heteromultimers. Collections of cells or cell lines of the invention may also, in a preferred embodiment, include all 25 bitter receptors. Such a panel may be used to determine on-target versus off-target activity for a compound, or the role of the receptors in pure bitter versus related (i.e., astringent or metallic) tastes.
The cells and cell lines of the present invention may be used to identify players of the GPCR pathway other than the bitter receptors that they stably express. For example, nucleic acids expressing different G proteins can be introduced (either transiently or stably) into each cell line in a collection of cell lines expressing a same heterologous bitter receptor and, preferably, no endogenous bitter receptor. Any interactions between these G proteins and the bitter receptor expressed by the cell lines may be assayed by, e.g., detecting a change in intracellular free calcium after the cells are exposed to a known agonist of the bitter receptor.
In some embodiments, large compound collections are tested for bitter receptor modulating activity in a cell-based, functional, high-throughput screen (HTS), e.g., using a 96 well, 384 well, 1536 well or higher plate format. In some embodiments, a test compound or multiple test compounds including a library of test compounds may be screened using more than one cell or cell line, including collections of cell lines, of the invention. If multiple cells or cell lines, each expressing a different naturally occurring or mutant bitter receptor molecule, are used, one can identify modulators that are effective on multiple bitter receptors or mutant forms or naturally-occurring allelic variants thereof or alternatively, modulators that are specific for a particular bitter receptor or a mutant form or naturally-occurring allelic variant thereof and that do not modulate other bitter receptors or other forms of the bitter receptor. In the case of a cell or cell line of the invention that expresses a human bitter receptor, one can expose the cells to a test compound to identify a compound that modulates bitter receptor activity (either increasing or decreasing) for use in the treatment of disease or condition characterized by undesired bitter receptor activity, or the decrease or absence of desired bitter receptor activity.
In some embodiments, prior to exposure to a test compound, the cells or cell lines of the invention may be modified by pretreatment with, for example, enzymes, including mammalian or other animal enzymes, plant enzymes, bacterial enzymes, enzymes from lysed cells, protein modifying enzymes, lipid modifying enzymes, and enzymes in the oral cavity, gastrointestinal tract, stomach or saliva. Such enzymes can include, for example, kinases, proteases, phosphatases, glycosidases, oxidoreductases, transferases, hydrolases, lyases, isomerases, ligases and the like. Alternatively, the cells and cell lines may be exposed to the test compound first followed by treatment to identify compounds that alter the modification of the bitter receptor by the treatment.
In certain aspects, provided herein are methods that take advantage of the naturally occurring high degree of genetic diversity that exists in cells, and efficiently identify, select, and enrich for cells possessing desired gene expression profiles conferring desired properties (e.g., stable and/or high expression of functional bitter taste receptors). The present methods can identify, select, and enrich for cells with improved properties from a pool of genetically diverse cells faster and more efficiently than conventional methods. In particular embodiments, the cells have not been genetically modified. In other particular embodiments, the present methods allow for the generation of novel homogeneous populations of cells possessing improved properties (e.g., more stable and/or higher expression of functional bitter taste receptors).
In certain embodiments, the methods described herein comprise selecting naturally occurring cells with one or more desired properties (e.g., stable and/or high expression of functional bitter taste receptors). In specific embodiments, the methods described herein comprise selecting cells with naturally occurring variants or mutations in one or more bitter taste receptor subunit genes.
In specific embodiments, the methods described herein comprise selecting isolated cells with naturally occurring variants or mutations in a promoter region of a bitter taste receptor gene or in a non-coding region of a bitter taste receptor gene (e.g., intron, 5′ untranslated region, and/or 3′ untranslated region). Variants or mutations in a promoter region of a bitter taste receptor gene or in a non-coding region of a bitter taste receptor gene may result in higher and/or more stable expression of the gene product. In specific embodiments, a promoter region of a bitter taste receptor gene or in a non-coding region of a bitter taste receptor gene has been modified, for example by methylation or acetylation of DNA. In particular embodiments, a cell comprises epigenetic modification affecting chromatin remodeling with respect to a bitter taste receptor gene. Non-limiting examples of epigenetic modifications include, but are not limited to, acetylation, methylation, ubiquitylation, phosphorylation and sumoylation.
In certain other embodiments, the present methods comprise selecting cells that underwent prior treatments. Such prior treatments may be exposure to sunlight or ultraviolet (UV) light, mutagens such as ethyl methane sulfonate (EMS), and chemical agents. In specific embodiments, such prior treatments may include exposure to undesirable growth conditions, e.g., low oxygen or low nutrients conditions, or toxic conditions.
The methods described herein provide for identifying and/or selection of cells (e.g., eukaryotic cells) that express one or more genes of interest (e.g., a bitter taste receptor subunit gene). In certain embodiments, the gene of interest is expressed at higher levels than other cells as a result of genetic variability.
In particular embodiments, the methods described here comprise (a) introducing into a cell (e.g., eukaryotic cell) one or more signaling probes that is capable of detecting an RNA of a bitter taste receptor; and (b) determining whether the cell (e.g., eukaryotic cells) comprises the RNA of a bitter taste receptor. Such methods may further comprise quantifying the level of the RNA of a bitter taste receptor. In specific embodiments, the methods described herein for identifying a cell with a desired RNA expression profile, wherein the method comprises: (a) introducing into a eukaryotic cell (e.g., eukaryotic cell) a plurality of signaling probes each capable of detecting a plurality of RNA of interest; and (b) quantifying the RNA levels detected by the plurality of signaling probes. The desired gene expression profile may be determined by comparison to a reference population. In particular embodiments, the plurality of RNA of interest may comprise any combination of the following RNA: an RNA encoded by any one of SEQ ID NO: 50-102.
In specific embodiments, such method further comprises the step of comparing the quantified RNA levels of the cell with the RNA levels in a reference cell, respectively. In particular embodiments, the plurality of signaling probes comprises at least 2, 3, 4, 5, 6, 7, 8, 9, 10, 15, 20, 25, 30, 35, 40, 45, 50, 60, 70, 80, 90, 100, 125, 150, 175, 200, 250, 300, 350, 500, 600, 700, 800, 900, or at least 1000 signaling probes. In some embodiments, the RNA of interest is translated. In other embodiments, the RNA of interest is not translated. In specific embodiments, the RNA of interest is encoded by a bitter taste receptor subunit gene. In specific embodiments, the isolated cell expresses one or more recombinant RNA of interest.
In specific embodiments, isolated cells identified and/or selected by the methods described herein have not been genetically engineered (e.g., do not recombinantly express one or more transgenes). In other embodiments, isolated cells identified and/or selected by the methods described herein have been genetically engineered (e.g., do recombinantly express one or more transgenes). In specific embodiments, such cells are somatic cells or differentiated cells.
In other embodiments, the cell comprises a desired gene expression profile. In certain embodiments, the desired gene expression profile is achieved by genetic engineering or by increasing genetic variability. In specific embodiments, a desired gene expression profile may be determined based on comparison with that of a reference population.
In some embodiments, the methods described herein are for identifying and/or selecting cells that express an RNA of interest (e.g., RNA of a bitter taste receptor) at a level higher than the average heterologous cell population (e.g., unsorted cell line population, for example unsorted 293T cell line population). In some embodiments, the methods described herein are for identifying and/or selecting cells that express an RNA of interest (e.g., RNA of a bitter taste receptor) at a level that is at least 20%, 30%, 40%, 50%, 60%, 70%, 80%, 90%, 95%, or 100% higher than the average heterologous cell population (e.g., unsorted cell line population, for example unsorted 293T cell line population). In some embodiments, the methods described herein are for identifying and/or selecting cells that express an RNA of interest (e.g., RNA of a bitter taste receptor) at a level that is at least 1 fold, 1.5 fold, 2 fold, 3 fold, 4 fold, 5 fold, 6 fold, 7 fold, 8 fold, 9 fold, or 10 fold higher than the average heterologous cell population (e.g., unsorted cell line population, for example unsorted 293T cell line population).
In specific embodiments, the methods described herein are for identifying and/or selecting cells that express an RNA of interest (e.g., RNA of a bitter taste receptor) at a level lower than the average heterologous cell population. An exemplary heterologous cell population may be a cell population of mixed cell types of different origin, a cell population of cells of one cell type that are genetically heterologous, or a cell population of one particular cell line from which the isolated cell is obtained using the methods described herein.
In particular embodiments, a cell isolated using the methods described herein is a cell clone from a cell line. In certain embodiments, a cell isolated using the methods described herein is a primary cell. In some embodiments, a cell isolated using the methods described herein is a transformed cell.
In certain embodiments, a cell is not a human cell. In particular embodiments, a cell is a cell derived from a mouse, rat, monkey, dog, cat, pig, sheep, goat, horse, chicken, frog, worm, insect (e.g., fly), fish, shellfish, or cow. In some embodiments, a cell is a mammalian cell or a eukaryotic cell. In other embodiments, a cell is a human cell. In some embodiments, a cell is a primary cell. In other embodiments, a cell is a transformed cell or a cell clone of a cell line.
Without being bound by theory, in their role as bitter taste, the bitter receptors presumably have evolved to detect a broad diversity of potentially physiologically active compounds as bitter tasting. Some of these receptors may be more broadly tuned than other GPCRs in their binding or interaction with a greater diversity of chemical structures. Therefore, testing of the bitter GPCRs with a library of structurally diverse compounds can be used to identify the compounds that interact with or modulate bitter receptors. Thereby identified compounds are predicted to also modulate the activity of other GPCRs.
In certain more specific embodiments, different bitter receptors, such as a panel of cell lines expressing at least 2, 5, 10, 50, or at least 100 different bitter receptors, may be used to identify the chemical space relevant for other GPCRs most closely related to these bitter receptors. Conversely, chemical space not found to interact with the bitter receptors could be enriched for compounds that have a lower likelihood of interacting with GPCRs.
In certain embodiments, definition of GPCR and non-GPCR chemical space according to these methods can be used to enrich chemical libraries for likely hits during HTS depending on whether GPCR or non-GPCR targets are used. Similarly, the same information may be used to guide medicinal chemistry efforts, for instance where a compound in development for a non-GPCR target can be optimized to exclude functionalities that may underlie undesired interactions with GPCRs.
Any assays to be used with the methods of the invention can be conducted in high throughput format.
In certain embodiments, if the protein complexes are bitter receptors, the activity of the bitter receptors can be measured using a calcium mobilization test.
Identification of Structural Commonalities Among Compounds
Systems and methods are provided for identifying a structural commonality among compounds that modulate a protein complex. In certain embodiments, the protein complex can be a cell surface receptor is a G protein-coupled receptor. In a specific embodiment, the protein complex can be a bitter receptor. The compounds that modulate the protein complex can be identified using any of the systems and methods disclosed herein. These compounds can be identified, for example by contacting, separately, a number of candidate compounds with a cell that has been engineered to express the protein complex, and assaying the effects of each of the candidate compounds on the activity of the protein complex, where the effect can be ascertained using various quantitative measures of the effect of the respective candidate compound on the biological activity of the protein complex. In a specific embodiment, a library of candidate compound can be screened against the protein complex to identify the compounds that can modulate the protein complex. The effect of the compound of interest on the protein complex can be represented by an activity profile. Non-limiting examples of such quantitative measures include those derived from the assays discussed herein. Each compound of interest can be represented by molecular representations that describe the structure and other properties of the compound. In a specific embodiment, the molecular representation of the compound of interest can include structural descriptors that mathematically describe the structural features of the compound. Structural and other types of descriptors are discussed below. A structure-activity relationship (SAR) model can be used to correlate mathematically the one or more descriptors of a compound of interest with the biological activity of the compound, as observed from the activity profile of the compound.
The systems and methods are provided for identifying a structural commonality among compounds that modulate a protein complex can comprise constructing one or more SAR models of the compounds of interest using the molecular representations of a compound and its activity profile, identifying the one or more structural features of each of the compounds that correlates with the activity profile of the respective compound based on that SAR model, and identifying at least one structural feature common to the compounds from among the one or more structural features identified for each of the compounds. In a specific embodiment, a SAR model can be constructed for each of the compounds of interest, using the molecular representation and of the respective compound and the activity profile of the respective compound. Structure-activity relationship (SAR) models are discussed below.
From the SAR models, one or more structural features of each of the compounds of interest that correlates with the activity profile of the respective compound can be identified. From among these features, one or more structural features that are common to all of the compounds of interest (structural commonalities) can be identified. In certain embodiments, computer modeling technology can be used to visualize the three-dimensional atomic structure of the compounds of interest. In a specific embodiment, the structural commonalities of the compounds of interest can be visualized using the computer modeling technology. A three-dimensional construct of a molecule can depend on data from x-ray crystallographic analyses or NMR imaging of the selected molecule. Force field data can be used to generate a model of the molecular dynamics of the compounds of interest, and/or the structural commonality. Examples of molecular modeling programs are the CHARMm and QUANTA programs (Accelrys, Inc., San Diego, Calif.).
Molecular Representation of a Compound
The molecular representation of a compound of interest can comprise various descriptors that describe features and properties of the compound. The descriptors can be topological, structural, physicochemical and/or spatial types of descriptors. A given compound can be represented by various descriptors, including sub-structural components or moieties, distance of chemical functional groups, or spatial, 2D or 3D topological, electrochemical, electro-physical, and or quantum mechanical properties of the compound. In specific embodiments, the compound of interest can be represented by structural descriptors. Examples of structural descriptors of a compound can include, but are not limited to, atom type, molecular weight (MW), numbers of rotatable bonds (Rotlbonds), number of hydrogen bond donors (Hbond donor), number of hydrogen bond acceptors (Hbond acceptor), number of chiral centers (R or S) in a compound, 3D molecular moment, sub-structural properties, molecular properties, and quantum mechanical properties. Non-limiting examples of topological descriptors include Balaban index (Jx), kappa shape indices, flexibility, subgraph count, connectivity, Wiener index, Zagreb index, connectivity indices, Hosoya index and E-sate keys. Non-limiting examples of physicochemical (or thermodynamic) descriptors include the log of the partition coefficient (AlogP), log of the partition coefficient, atom-type value (AlogP98), the octanol/water partition coefficient (LogP), molar refractivity (MR) and molar refractivity (MolRef). Non-limiting examples of spatial descriptors include radius of gyration (RadOfGyration), Jurs charged partial surface area descriptors (Jurs), surface area projections (shadow indices), molecular surface area (Area), Density, molecular volume (Vm), and principal moments of inertia (PMI). Non-limiting examples of electronic descriptors include charge, sum of atomic polarizabilities (Apol), highest occupied molecular orbital energy (HOMO), lowest unoccupied molecular orbital energy (LUMO) and superdelocalizability (Sr). Descriptions of the various descriptors can be found at the website titled QSAR Descriptors, available from The Scripps Research Institute (La Jolla Calif.). Definitions can also be found, for example, at the website tutorial for the Cerius2 software (Accelrys, Inc., San Diego, Calif.) or Accelrys QSAR software product (Accelrys, Inc., San Diego, Calif.).
Values for the various descriptors for a compound of interest can be derived using a computational program for determining molecular structure. For example, the GRID program (Molecular Discovery Ltd., Middlesex, UK) can be used to determine energetically favorable binding sites on compounds of known structure, which can be used as descriptors input in QSAR analyses. Also, various programs that perform a QSAR analysis can also be used to derive values for the descriptors for a compound of interest, such as the Accelrys QSAR software product (Accelrys, Inc., San Diego, Calif.). In another example, information that can serve as descriptors of a compound of interest can be obtained from a database of compound structures, such as the Accelrys Chemicals Available for Purchase (CAP) database (Accelrys Inc., San Diego, Calif.).
A SAR model can be used to correlate mathematically the descriptors of a compound of interest with the biological activity of the compound. The biological activity of the compound of interest can be provided by an activity profile of the compound. A SAR model can be constructed using different combination of descriptors and algorithms to establish models that can be used to classify other compounds. For example, a SAR that predicts the structural features of a class of compounds that modulate a protein complex, that was constructed using a set of training compounds that were highly similar to one another, can be used to classify other compounds believed to be similar to the training set.
A SAR algorithm can be used to describe mathematic relationships between relevant chemical descriptors and the potencies of the observed biological activity, i.e. activity Y is a function of descriptors X, [Y=f(X)]. Any algorithm in the art that is useful for data interrogations can be used to construct a SAR model. As non-limiting examples, programs that can be used to construct a SAR model includes programs that can perform an ordinary multiple regression (OMR), a stepwise regression (SWR), an all possible subsets regression (PSR), and a partial least squares (PLS) regressions and genetic algorithms (GA). In a specific embodiment, a SAR model for a compound can take the form of a linear equation:
A0+(A1M1)+(A2M2)+(A3M3)+ . . . (AnMn)
where the parameters M1 through Mn are the different descriptors in a molecular representation of the compound, A0 is a constant, and the coefficients A1 through An are calculated by fitting variations in the parameters M1 through Mn and the biological activity of the compound, such as provided by the activity profile. This SAR model can be fit using any regression technique in the art. For example, an ordinary multiple regression can be used to compute the least squares fit of the independent variables (for example, taken to be the descriptors) to the dependent variables (for example, taken to be the activity profile). Examples of software that can be used to provide a SAR model, such as by performing a quantitative structure-activity relationship analysis (QSAR), include but are not limited to, the Accelrys QSAR software (Accelrys Inc., San Diego, Calif.), and the Quasar 5, a 6D-QSAR software product (Biographics Laboratory 3R, Basel, Switzerland). Other SAR models are discussed in Selassie, C. D., “History of Quantitative Structure-Activity Relationships,” Burger's Medicinal Chemistry and Drug Discovery, 6th Edition, vol. 1: Drug Discovery, which is incorporated herein by reference.
Examples of SAR models that can be constructed for a compound of interest include, but are not limited to, receptor-dependent free energy force field QSAR (FEFF-QSAR), receptor-independent three-dimensional QSAR (3D-QSAR), and receptor-dependent or receptor-independent four-dimensional QSAR (4D-QSAR).
Receptor-independent 3D-QSAR. An approach that can be used to provide a tool to relate the magnitude of a particular property exhibited by a compound to one or more structural characteristics and/or physical properties of the compound is a receptor-independent 3D-QSAR analysis. The receptor geometry can be unknown in the performance of a receptor-independent 3D-QSAR analysis. A receptor-independent QSAR can be applicable to a series of chemical analogs for which the dependent (i.e., biological activity) property is derived from a set of intramolecular descriptors based upon the assumption that the chemical compounds share a common mechanism of action. A regression analysis can be used to fit the descriptors of a compound to the different measures of the activity profile for a receptor-independent 3D-QSAR analysis.
Receptor-dependent 3D-QSAR. Another approach can be to use a receptor-dependent 3D-QSAR, also referred to as a free energy force field QSAR (FEFF-QSAR). For a receptor-dependent 3D-QSAR analysis, the receptor geometry is known. The free energy force field ligand-receptor binding energy terms can be calculated and used as the independent variables of the QSAR scoring function. See, for example, Tokarski and Hopfinger (1997), J. Chem. Inf. Computer Sci. 37:792-811, which is incorporated herein by reference.
Receptor-dependent or receptor-independent 4D-QSAR. A 4D-QSAR model can incorporate conformational and alignment freedom with a 3D-QSAR analysis by performing molecular state ensemble averaging (the fourth dimension) on a set of training compounds. In 4D-QSAR analysis, it is considered that differences in the activity of compounds can be related to differences in the Boltzmann average spatial distribution of molecular shape with respect to the interaction pharmacophore element (IPE). A single “active” conformation can be assumed for each compound in a set of training compounds. The 4D-QSAR analysis can be used with additional molecular design applications including receptor independent 3D-QSAR and FEFF-QSAR models. The 4D-QSAR models are described in Duca and Hopfinger (2001), J Chem Inf Comput Sci 41(5): 1367-87, which is incorporated herein by reference.
The present invention can be implemented as a computer program product that comprises a computer program mechanism embedded in a computer-readable storage medium. Further, any of the methods of the present invention can be implemented in one or more computers or other forms of apparatus. Examples of apparatus include but are not limited to, a computer, and a measuring device (for example, an assay reader or scanner). Further still, any of the methods of the present invention can be implemented in one or more computer program products. Some embodiments of the present invention provide a computer program product that encodes any or all of the methods disclosed in this application. Such methods can be stored on a CD-ROM, DVD, magnetic disk storage product, or any other computer-readable data or program storage product. Such computer readable storage media are intended to be tangible, physical objects (as opposed to carrier waves). Such methods can also be embedded in permanent storage, such as ROM, one or more programmable chips, or one or more application specific integrated circuits (ASICs). Such permanent storage can be localized in a server, 802.11 access point, 802.11 wireless bridge/station, repeater, router, mobile phone, or other electronic devices. Such methods encoded in the computer program product can also be distributed electronically, via the Internet or otherwise, by transmission of a computer data signal (in which the software modules are embedded) either digitally or on a carrier wave (it will be clear that such use of carrier wave is for distribution, not storage).
Some embodiments of the present invention provide a computer program product. These program modules can be stored on a CD-ROM, DVD, magnetic disk storage product, or any other computer-readable data or program storage product. The program modules can also be embedded in permanent storage, such as ROM, one or more programmable chips, or one or more application specific integrated circuits (ASICs). Such permanent storage can be localized in a server, 802.11 access point, 802.11 wireless bridge/station, repeater, router, mobile phone, or other electronic devices. The software modules in the computer program product can also be distributed electronically, via the Internet or otherwise, by transmission of a computer data signal (in which the software modules are embedded) either digitally or on a carrier wave.
In a specific embodiment, the computer program provides for outputting a result of the claimed method to a user, a user interface device, a computer readable storage medium, a monitor, a local computer, or a computer that is part of a network. Such computer readable storage media are intended to be tangible, physical objects (as opposed to carrier waves).
These and other embodiments of the invention may be further illustrated in the following non-limiting Examples.
Generating Expression Vectors
Plasmid expression vectors that allowed streamlined cloning were generated based on pCMV-SCRIPT (Stratagene) and contained various necessary components for transcription and translation of a gene of interest, including: CMV and SV40 eukaryotic promoters; SV40 and HSV-TK polyadenylation sequences; multiple cloning sites; Kozak sequences; and neomycin/kanamycin resistance cassettes.
We transfected both 293T and CHO cells. The example focuses on CHO cells, where the CHO cells were cotransfected with three separate plasmids, one encoding a human GABA alpha subunit (SEQ ID NO: 1-4), one encoding the human GABA beta 3 subunit (SEQ ID NO:5) and the other encoding the human GABA gamma 2 subunit (SEQ ID NO: 6) in the following combinations: α1β3γ2s (α1), α2β3γ2s (α2), α3β3γ2s (α3) and α5β3γ2s (α5). As will be appreciated by those of skill in the art, any reagent that is suitable for use with a chosen host cell may be used to introduce a nucleic acid, e.g. plasmid, oligonucleotide, labeled oligonucleotide, into a host cell with proper optimization. Examples of reagents that may be used to introduce nucleic acids into host cells include but are not limited to Lipofectamine, Lipofectamine 2000, Oligofectamine, TFX reagents, Fugene 6, DOTAP/DOPE, Metafectine, or Fecturin.
Although drug selection is optional in the methods of this invention, we included one drug resistance marker per plasmid. The sequences were under the control of the CMV promoter. An untranslated sequence encoding a tag for detection by a signaling probe was also present along with a sequence encoding a drug resistance marker. The target sequences utilized were GABA Target Sequence 1 (SEQ ID NO: 7), GABA Target Sequence 2 (SEQ ID NO: 8) and GABA Target Sequence 3 (SEQ ID NO: 9). In these examples, the GABA alpha subunit gene-containing vector contained GABA Target Sequence 1, the GABA beta subunit gene-containing vector contained GABA Target Sequence 2 and the GABA gamma subunit gene-containing vector contained the GABA Target Sequence 3.
Transfected cells were grown for 2 days in HAMF12-FBS, followed by 14 days in antibiotic-containing HAMF12-FBS. The antibiotic containing period had antibiotics added to the media as follows: Puromycin (3.5 ug/ml), Hygromycin (150 ug/ml), and G418/Neomycin (300 ug/ml)
Following antibiotic selection, and prior to introduction of fluorogenic probes, cells were passaged 6 to 18 times in the absence of antibiotics to allow time for expression that is not stable over the selected period of time to subside.
Cells were harvested and transfected with GABA signaling probes (SEQ ID NO: 10-12). As will be appreciated by those of skill in the art, any reagent that is suitable for use with a chosen host cell may be used to introduce a nucleic acid, e.g. plasmid, oligonucleotide, labeled oligonucleotide, into a host cell with proper optimization. Examples of reagents that may be used to introduce nucleic acids into host cells include but are not limited to Lipofectamine, Lipofectamine 2000, Oligofectamine, TFX reagents, Fugene 6, DOTAP/DOPE, Metafectine, or Fecturin.
GABA Signaling Probe 1 binds GABA Target Sequence 1, GABA Signaling Probe 2 binds GABA Target Sequence 2 and GABA Signaling Probe 3 binds GABA Target Sequence 3. The cells were then collected for analysis and sorted using a fluorescence activated cell sorter (Beckman Coulter, Miami, Fla.) (below).
Target Sequences detected by signaling probes
Signaling Probes
Supplied as 100 μM stocks
A similar probe using a Quasar Dye (BioSearch) with spectral properties similar to Cy5 was used in certain experiments. Note also that 5-MedC and 2-aminodA mixmer probes rather than DNA probes were used in some instances. Note that BHQ3 could be substituted with BHQ2 or a gold particle in Probe 1 or Probe 2.
The cells were dissociated and collected for analysis and sorting using a fluorescence activated cell sorter (Beckman Coulter, Miami, Fla.). Standard analytical methods were used to gate cells fluorescing above background and to isolate individual cells falling within the gate into barcoded 96-well plates. The gating hierarchy was as follows: Gating hierarchy: coincidence gate>singlets gate>live gate>Sort gate. With this gating strategy, the top 0.04-0.4% of triple positive cells were marked for sorting into barcoded 96-well plates.
Step 6: Additional Cycles of Steps 1-5 and/or 3-5
Steps 1 to 5 and/or 3-5 were repeated to obtain a greater number of cells. Two independent rounds of steps 1-5 were completed, and for each of these cycles, at least three internal cycles of steps 3-5 were performed for the sum of independent rounds.
The plates were transferred to a Hamilton Microlabstar automated liquid handler. Cells were incubated for 5-7 days in a 1:1 mix of 2-3 day conditioned growth medium:fresh growth medium (growth medium is Ham's F12/10% FBS) supplemented with 100 units penicillin/ml plus 0.1 mg/ml streptomycin and then dispersed by trypsinization with 0.25% trypsin to minimize clumps and transferred to new 96-well plates. After the clones were dispersed, plates were imaged to determine confluency of wells (Genetix). Each plate was focused for reliable image acquisition across the plate. Reported confluencies of greater than 70% were not relied upon. Confluency measurements were obtained at days every 3 times over 9 days (between days 1 and 10 post-dispersal) and used to calculate growth rates.
Cells were binned (independently grouped and plated as a cohort) according to growth rate between 10-11 days following the dispersal step in step 7. Bins were independently collected and plated on individual 96 well plates for downstream handling, and there could be more than one target plate per specific bin. Bins were calculated by considering the spread of growth rates and bracketing a range covering a high percentage of the total number of populations of cells. Depending on the sort iteration (see Step 5), between 5 and 6 growth bins were used with a partition of 1-4 days. Therefore each bin corresponded to a growth rate or population doubling time difference between 12 and 14.4 hours depending on the iteration.
The plates were incubated under standard and fixed conditions (humidified 37° C., 5% CO2/95% air) in Ham's F12 media/10% FBS without antibiotics. The plates of cells were split to produce 4 sets (the set consists of all plates with all growth bins—these steps ensure there are 4 replicates of the initial set) of target plates. Up to 2 target plate sets were committed for cryopreservation (see below), and the remaining set was scaled and further replica plated for passage and for functional assay experiments. Distinct and independent tissue culture reagents, incubators, personnel and carbon dioxide sources were used for each independently carried set of plates. Quality control steps were taken to ensure the proper production and quality of all tissue culture reagents: each component added to each bottle of media prepared for use was added by one designated person in one designated hood with only that reagent in the hood while a second designated person monitored to avoid mistakes. Conditions for liquid handling were set to eliminate cross contamination across wells. Fresh tips were used for all steps or stringent tip washing protocols were used. Liquid handling conditions were set for accurate volume transfer, efficient cell manipulation, washing cycles, pipetting speeds and locations, number of pipetting cycles for cell dispersal, and relative position of tip to plate.
At least two sets of plates were frozen at −70 to −80 C. Plates in each set were first allowed to attain confluencies of 70 to 100%. Media was aspirated and 90% FBS and 10% DMSO was added. The plates were sealed with Parafilm and then individually surrounded by 1 to 5 cm of foam and placed into a −80 C freezer.
The remaining set of plates were maintained as described in step 9 (above). All cell splitting was performed using automated liquid handling steps, including media removal, cell washing, trypsin addition and incubation, quenching and cell dispersal steps.
The consistency and standardization of cell and culture conditions for all populations of cells was controlled. Any differences across plates due to slight differences in growth rates could be controlled by periodic normalization of cell numbers across plates.
The cells were maintained for 6 to 8 weeks of cell culture to allow for their in vitro evolution under these conditions. During this time, we observed size, morphology, fragility, response to trypsinization or dissociation, roundness/average circularity post-dissociation, percentage viability, tendency towards microconfluency, or other aspects of cell maintenance such as adherence to culture plate surfaces.
Populations of cells were tested using functional criteria. Membrane potential assay kits (Molecular Devices/MDS) were used according to manufacturer's instructions. Cells were tested at multiple different densities in 96 or 384-well plates and responses were analyzed. A variety of time points post plating were used, for instance 12-48 hours post plating. Different densities of plating were also tested for assay response differences.
The functional responses from experiments performed at low and higher passage numbers were compared to identify cells with the most consistent responses over defined periods of time, ranging from 3 to 9 weeks. Other characteristics of the cells that changed over time are also noted, including morphology, tendency toward microconfluency, and time to attach to culture matrices post-plating.
Populations of cells meeting functional and other criteria were further evaluated to determine those most amenable to production of viable, stable and functional cell lines. Selected populations of cells were expanded in larger tissue culture vessels and the characterization steps described above were continued or repeated under these conditions. At this point, additional standardization steps were introduced for consistent and reliable passages. These included different plating cell densities, time of passage, culture dish size/format and coating, fluidics optimization, cell dissociation optimization (type, volume used, and length of time), as well as washing steps. Assay Z′ scores were stable when tested every few days over the course of four weeks in culture.
Also, viability of cells at each passage were determined. Manual intervention was increased and cells were more closely observed and monitored. This information was used to help identify and select final cell lines that retained the desired properties Final cell lines and back-up cell lines were selected that showed consistent growth, appropriate adherence, as well as functional response.
The low passage frozen plates (see above) corresponding to the final cell line and back-up cell lines were thawed at 37° C., washed two times with Ham's F12/10% FBS and incubated in humidified 37° C./5% CO2 conditions. The cells were then expanded for a period of 2-3 weeks. Cell banks for each final and back-up cell line consisting of 25 vials each with 10 million cells were established.
At least one vial from the cell bank was thawed and expanded in culture. The resulting cells were tested to confirm that they met the same characteristics for which they were originally selected.
The response of CHO cell lines expressing GABAA (subunit combinations of α1β3γ2s (α1), α2β3γ2s (α2), α3β3γ2s (α3) and α5β3γ2s (α5)) GABA, the endogenous GABAA ligand, was evaluated. Interaction of cell lines with GABA was evaluated by measuring the membrane potential of GABAA, in response to GABA using the following protocol.
Cells were plated 24 hours prior to assay at 10-25,000 cells per well in 384 well plates in growth media (Ham's F-12 media plus FBS and glutamine). Media removal was followed by the addition of membrane potential dye diluted in load buffer (137 mM NaCl, 5 mMKCl, 1.25 mM CaCl, 25 mM HEPES, 10 mM Glucose). Incubation was for 1 hour, followed by plate loading onto the high throughput fluorescent plate reader (Hamamastu FDSS). GABA ligand was diluted in MP assay buffer (137 mM NaCl, 5 mM KGluconate, 1.25 mM CaCl, 25 mM HEPES, 10 mM Glucose) to the desired concentration (when needed, serial dilutions of GABA were generated, concentrations used: 3 nM, 10 nM, 30 nM, 100 nM, 300 nM, 1 uM, 3 uM, 10 uM) and added to each well. The plates were read for 90 seconds.
Table 6 (below) demonstrates that each of the cell lines generated responds to GABA ligand. These results indicate that the GABAA cell lines produced, which respond as expected to the endogenous ligand, are physiologically relevant for use in high-throughput screening assays. Further, the replicate wells produced precise EC50 values from well to well indicating high reproducibility of the GABAA cell lines. Z′ values generated using the membrane potential assay were α1β3γ2s 0.58, α2β3γ2s 0.67, α3β3γ2s 0.69 and α5β3γ2s 0.62.
The GABAA cell lines and membrane potential assay were verified by the methods described in Example 2 using serial dilutions in assay buffer of bicuculline (a known antagonist) at 30 uM, 10 uM, 3 uM, 1 uM, 300 nM, 100 nM and 30 nM.
Bicuculline was found to interact with all four GABAA cell lines in the presence of EC50 concentrations of GABA. These results indicate that the GABAA cell lines produced, which respond as expected to this known modulator of GABAA, are physiologically and pharmacologically relevant for use in high-throughput screening assays.
The interaction of CHO cell lines expressing GABAA (subunit combinations of α1β3γ2s (α1), α2β3γ2s (α2), α3β3γ2s (α3) and α5β3γ2s (α5)) with 1280 compounds from the LOPAC 1280 (Library of Pharmacologically Active Compounds) was evaluated (Sigma-RBI Prod. No. L01280). The LOPAC 1280 library contains high purity, small organic ligands with well documented pharmacological activities. Interaction of cell lines with test compounds was evaluated by measuring the membrane potential of GABAA, in response to test compounds using the following protocol.
Cells were plated 24 hours prior to assay at 10-25,000 cells per well in 384 well plates in growth media (Ham's F-12 media plus FBS and glutamine). Media removal was followed by the addition of membrane potential dye diluted in load buffer (137 mM NaCl, 5 mMKCl, 1.25 mM CaCl, 25 mM HEPES, 10 mM Glucose). Incubation was for 1 hour, followed by plate loading onto the high throughput fluorescent plate reader (Hamamastu FDSS). Test compounds were diluted in MP assay buffer (137 mM NaCl, 5 mM KGluconate, 1.25 mM CaCl, 25 mM HEPES, 10 mM Glucose) to the desired concentration (when needed, serial dilutions of each test compound were generated, concentrations used: 3 nM, 10 nM, 30 nM, 100 nM, 300 nM, 1 uM, 3 uM, 10 uM) and added to each well. The plates were read for 90 seconds.
The activity of each compound towards the GABAA cell lines produced was measured and compounds which exhibited similar or greater activity as GABA (the endogenous ligand) were scored as positive hits. Of the 1280 compounds screened, 34 activated at least one cell line (i.e., either a1, a2, a3 and a5) as well as, if not better, than GABA. The interaction of 17 of these compounds with the produced GABAA cell lines was confirmed in the following dose response studies. Modulators which require GABA to be present, partial agonists and low potency compounds were not included in the list.
The screening assay identified each of the GABAA agonists in the LOPAC library: GABA (endogenous ligand), propofol, isoguvacine hydrochloride, muscimol hydrobromide, piperidine-4-sulphonic acid, 3-alpha,21-dihydroxy-5-alpha-pregnan-20-one (a neurosteroid), 5-alpha-pregnan-3alpha-ol-11,20-dione (a neurosteroid), 5-alpha-pegnan-3alpha-ol-20-one (a neurosteroid), and tracazolate. The results indicate that the produced GABAA cell lines respond in a physiologically relevant manner (e.g., they respond to agonists of the endogenous receptor). EC50 values for these eight agonists were determined and are included in Table 6 (below).
The screening assay also identified four compounds in the LOPAC library not described as GABA agonist but known to have other activities associated with GABAA which we noted: etazolate (a phosphodiesterase inhibitor), androsterone (a steroid hormone), chlormezanone (a muscle relaxant), and ivermectin (an anti-parasitic known to effect chlorine channels). EC50 values for these four compounds were determined and are summarized in Table 6 (below).
The screening assay further identified four compounds in the LOPAC library which, until now, were not known to interact with GABAA. These novel compounds include: dipyrimidole (an adenosine deaminase inhibitor), niclosamide (an anti-parasitic), tyrphosin A9 (a PDGFR inhibitor), and I-Ome-Tyrphosin AG 538 (an IGF RTK inhibitor). EC50 values for these four compounds were determined and are summarized in Table 6 (below).
The results of the screening assays summarized in Table 6:
The following voltage-clamp protocol was used: the membrane potential was clamped to a holding potential of −60 mV. Currents were evoked by 2-sec applications of increasing concentrations of GABA (0.10-100 μM) with intermediate wash with buffer.
Whole cell receptor current traces for the α2, α3, and α5 GABAA cell lines in response to 100 uM GABA, and the al GABAA cell line in response to increasing concentrations of GABA (0.10-100 μM in log increments), confirm that the GABAA cell lines can be used in traditional electrophysiology assays in addition to the High-Throughput Screening assays described above. These electrophysiology assay results, along with the membrane potential assay of Example 2, confirm the physiological and pharmacological relevance of the GABAA cell lines produced herein. Electrophysiology is accepted as a reliable method of detecting modulators of GABAA receptors. Our data indicate that the cell lines of the invention can produce similarly reliable results using a membrane potential assay. Cell lines of the prior art are not reliable or sensitive enough to effectively utilize this membrane potential assay, which is cheaper and faster than electrophysiology. Thus, the cell lines of the invention allow screening on a much larger scale than is available using electrophysiology (10,000's of assays per day using the membrane potential assay compared to less than 100 per day using electrophysiology).
The response of GABAA (subunit combinations of α1β3γ2s (A1), α2β3γ2s (A2), α3β3γ2s (A3) and α5β3γ2s (A5)) expressing CHO cells of the invention to test compounds was evaluated using the following protocol for an in-cell readout assay.
Cells were plated 24 hours prior to assay at 10-25,000 cells per well in 384 well plates in growth media (Ham's F-12 media plus FBS and glutamine). Media removal was followed by the addition of loading buffer (135 mM NaCl, 5 mM KCl, 2 mM CaCl2, 1 mM MgCl2, 10 mM HEPES, 10 mM glucose) and incubation for 1 hour. The assay plates were then loaded on the FDSS (Hamamatsu Corporation). Test compounds (e.g. GABA ligand) were diluted in assay buffer (150 mM NaI, 5 mMKCl, 1.25 mM CaCl2, 1 mM MgCl2, 25 mM HEPES, 10 mM glucose) to the desired concentration (when needed, serial dilutions of each test compound were generated, effective concentrations used: 3 nM, 10 nM, 30 nM, 100 nM, 300 nM, 1 uM, 3 uM, 10 uM) and added to each well. The plates were read for 90 seconds.
In response to increasing concentrations of GABA ligand, GABAA-meYFP-CHO cells show increasing quench of meYFP signal. This quench can be used to calculate dose response curves for GABA activation. The GABA dose response curves generated by the in-cell readout assay are similar to the curves generated by the Membrane Potential Blue assay described in Example 3. These data demonstrate that the cells of the invention can be used in an in-cell readout assay to determine modulators of GABAA.
293T cells were transfected with a plasmid encoding the human GC-C gene (SEQ ID NO: 15) using standard techniques. (Examples of reagents that may be used to introduce nucleic acids into host cells include, but are not limited to, LIPOFECTAMINE™, LIPOFECTAMINE™ 2000, OLIGOFECTAMINE™, TFX™ reagents, FUGENE® 6, DOTAP/DOPE, Metafectine or FECTURIN™.)
Although drug selection is optional in the methods of this invention, we included one drug resistance marker in the plasmid encoding the human GC-C gene. The GC-C sequence was under the control of the CMV promoter. An untranslated sequence encoding a tag for detection by a signaling probe was also present along with a sequence encoding a drug resistance marker. The target sequence utilized was GC-C Target Sequence 1 (SEQ ID NO: 13). In this example, the GC-C gene-containing vector contained GC-C Target Sequence 1.
Transfected cells were grown for 2 days in DMEM-FBS, followed by 10 days in 500 μg/ml hygromycin-containing DMEM-FBS, then in DMEM-FBS for the remainder of the time, totaling between 4 and 5 weeks (depending on which independent isolation) in DMEM/10% FBS, prior to the addition of the signaling probe.
Following enrichment on antibiotic, cells were passaged 8-10 times in the absence of antibiotic selection to allow time for expression that is not stable over the selected period of time to subside.
Cells were harvested and transfected with GC-C Signaling Probe 1 (SEQ ID NO: 14) using standard techniques. (Examples of reagents that may be used to introduce nucleic acids into host cells include, but are not limited to, LIPOFECTAMINE™, LIPOFECTAMINE™ 2000, OLIGOFECTAMINE™, TFX™ reagents, FUGENE® 6, DOTAP/DOPE, Metafectine or FECTURIN™.) The cells were then dissociated and collected for analysis and sorted using a fluorescence activated cell sorter (Beckman Coulter, Miami, Fla.).
(Supplied as 1000 stock)
In addition, a similar probe using a QUASAR® Dye (BioSearch) with spectral properties similar to Cy5 was used in certain experiments. In some experiments, 5-MedC and 2-amino dA mixmers were used rather than DNA probes.
The cells were dissociated and collected for analysis and sorting using a fluorescence activated cell sorter (Beckman Coulter, Miami, Fla.). Standard analytical methods were used to gate cells fluorescing above background and to isolate individual cells falling within the gate into bar-coded 96-well plates. The following gating hierarchy was used:
coincidence gate→singlets gate→live gate→Sort gate in plot FAM vs. Cy5: 0.3% of live cells
The above steps were repeated to obtain a greater number of cells. Two rounds of all the above steps were performed. In addition, the cell passaging, exposure to the signaling probe and isolation of positive cells by the fluorescence activated cell sorter sequence of steps was performed a total of two times for one of the independent transfection rounds.
The plates were transferred to a MICROLAB STAR™ (Hamilton Robotics). Cells were incubated for 9 days in 100 μl of 1:1 mix of fresh complete growth medium and 2-day-conditioned growth medium, supplemented with 100 U penicillin and 0.1 mg/ml streptomycin, dispersed by trypsinization twice to minimize clumps and transferred to new 96-well plates. Plates were imaged to determine confluency of wells (Genetix). Each plate was focused for reliable image acquisition across the plate. Reported confluencies of greater than 70% were not relied upon. Confluency measurements were obtained on 3 consecutive days and used to calculate growth rates.
Cells were binned (independently grouped and plated as a cohort) according to growth rate 3 days following the dispersal step. Each of the 4 growth bins was separated into individual 96-well plates; some growth bins resulted in more than one 96-well plate. Bins were calculated by considering the spread of growth rates and bracketing a range covering a high percentage of the total number of populations of cells. Bins were calculated to capture 12-hour differences in growth rate.
Cells can have doubling times from less than 1 day to more than 2 weeks. In order to process the most diverse clones that at the same time can be reasonably binned according to growth rate, it is preferable to use 3-9 bins with a 0.25 to 0.7 day doubling time per bin. One skilled in the art will appreciate that the tightness of the bins and number of bins can be adjusted for the particular situation and that the tightness and number of bins can be further adjusted if cells were synchronized for their cell cycle.
The plates were incubated under standardized and fixed conditions (DMEM/FBS, 37° C., 5% CO2) without antibiotics. The plates of cells were split to produce 5 sets of 96-well plates (3 sets for freezing, 1 for assay and 1 for passage). Distinct and independent tissue culture reagents, incubators, personnel and carbon dioxide sources were used downstream in the workflow for each of the sets of plates. Quality control steps were taken to ensure the proper production and quality of all tissue culture reagents: each component added to each bottle of media prepared for use was added by one designated person in one designated hood with only that reagent in the hood while a second designated person monitors to avoid mistakes. Conditions for liquid handling were set to eliminate cross contamination across wells. Fresh tips were used for all steps, or stringent tip washing protocols were used. Liquid handling conditions were set for accurate volume transfer, efficient cell manipulation, washing cycles, pipetting speeds and locations, number of pipetting cycles for cell dispersal, and relative position of tip to plate.
One set of plates was frozen at −70 to −80° C. Plates in the set were first allowed to attain confluencies of 70 to 100%. Medium was aspirated and 90% FBS and 10% DMSO was added. The plates were individually sealed with Parafilm, surrounded by 1 to 5 cm of foam and placed into a freezer.
The remaining two sets of plates were maintained under standardized and fixed conditions as described above. All cell splitting was performed using automated liquid handling steps, including media removal, cell washing, trypsin addition and incubation, quenching and cell dispersal steps.
The consistency and standardization of cell and culture conditions for all populations of cells was controlled. Differences across plates due to slight differences in growth rates were controlled by normalization of cell numbers across plates and occurred 3 passages after the rearray. Populations of cells that are outliers were detected and eliminated.
The cells were maintained for 3 to 6 weeks to allow for their in vitro evolution under these conditions. During this time, we observed size, morphology, tendency towards microconfluency, fragility, response to trypsinization and average circularity post-trypsinization, or other aspects of cell maintenance such as adherence to culture plate surfaces and resistance to blow-off upon fluid addition.
Populations of cells were tested using functional criteria. The Direct Cyclic GMP Enzyme Immunoassay Kit (Cat. 900-014; AssayDesigns, Inc.) was used according to manufacturer's instructions: (http://www.assaydesigns.com/objects/catalog//product/extras/900-014.pdf). Cells were tested at 4 different densities in 96- or 384-well plates and responses were analyzed. The following conditions were used for the GC-C-expressing cell lines of the invention:
The functional responses from experiments performed at low and higher passage numbers were compared to identify cells with the most consistent responses over defined periods of time, ranging from 4 to 10 weeks. Other characteristics of the cells that changed over time were also noted.
Populations of cells meeting functional and other criteria were further evaluated to determine those most amenable to production of viable, stable and functional cell lines. Selected populations of cells were expanded in larger tissue culture vessels, and the characterization steps described above were continued or repeated under these conditions. At this point, additional standardization steps, such as different cell densities; time of plating, length of cell culture passage; cell culture dishes format and coating; fluidics optimization, including speed and shear force; time of passage; and washing steps, were introduced for consistent and reliable passages. Also, viability of cells at each passage was determined. Manual intervention was increased, and cells were more closely observed and monitored. This information was used to help identify and select final cell lines that retain the desired properties. Final cell lines and back-up cell lines (20 clones total) were selected that showed appropriate adherence/stickiness and growth rate and even plating (lack of microconfluency) when produced following this process and under these conditions.
The initial frozen stock of 3 vials per each of the selected 20 clones was generated by expanding the non-frozen populations from the re-arrayed 96-well plates via 24-well, 6-well and 10 cm dishes in DMEM/10% FBS/HEPES/L-Glu. The low passage frozen stocks corresponding to the final cell line and back-up cell lines were thawed at 37° C., washed two times with DMEM containing FBS and incubated in the same manner. The cells were then expanded for a period of 2 to 4 weeks. Two final clones were selected.
One vial from one clone of the initial freeze was thawed and expanded in culture. The resulting cells were tested to confirm that they met the same characteristics for which they were originally selected. Cell banks for each cell line consisting of 20 to over 100 vials may be established.
The following step can also be conducted to confirm that the cell lines are viable, stable and functional: At least one vial from the cell bank is thawed and expanded in culture; the resulting cells are tested to determine if they meet the same characteristics for which they were originally selected.
A competitive ELISA for detection of cGMP was used to characterize native GC-C function in the produced GC-C-expressing cell line. Cells expressing GC-C were maintained under standard cell culture conditions in Dulbecco's Modified Eagles medium (DMEM) supplemented with 10% fetal bovine serum, glutamine and HEPES and grown in T175 cm flasks. For the ELISA, the cells were plated into coated 96-well plates (poly-D-lysine).
Cell Treatment and Cell Lysis Protocol
Cells were washed twice with serum-free medium and incubated with 1 mM IBMX for 30 minutes. Desired activators (i.e., guanylin, 0.001-40 μM) were then added to the cells and incubated for 30-40 minutes. Supernatant was removed, and the cells were washed with TBS buffer. The cells were lysed with 0.1 N HCl. This was followed by lysis with 0.1N HCl and a freeze/thaw cycle at −20° C./room temperature. Defrosted lysates (samples were spun in Eppendorf tubes at 10,000 rpm) were centrifuged to pellet cell debris. The cleared supernatant lysate was then transferred to ELISA plates.
ELISA Protocol
All of the following steps were performed at room temperature, unless otherwise indicated. ELISA plates were coated with anti-IgG antibodies in coating buffer (Na-carbonate/bi-carbonate buffer, 0.1M final, pH 9.6) overnight at 4° C. Plates were then washed with wash buffer (TBS-Tween 20, 0.05%), followed by blocking reagent addition. Incubation for 1 hour with blocking reagent at 37° C. was followed by a wash of the plates with wash buffer. A rabbit anti-cGMP polyclonal antibody (Chemicon) was then added, followed by incubation for 1 hour and a subsequent wash with wash buffer. Cell lysate was then added, and incubated for 1 hour before the subsequent addition of a cGMP-biotin conjugate (1 and 10 nM of 8-Biotin-AET-cGMP (Biolog)). Plates were incubated for 2 hours and then washed with wash buffer. Streptavidin-alkaline phosphate was then added and incubated for 1 hour, then washed with wash buffer. Plates were incubated for at least 1 hour (preferably 2-5 hours) with PNPP substrate (Sigma). The absorbance was then read at 405 nm on a SAFIRE2™ plate reader (Tecan).
Maximum absorbance was seen when no cell lysate was used in the ELISA (Control). Reduction in absorbance (corresponding to increased cGMP levels) was observed with cell lysate from the produced GC-C-expressing cell line treated with 100 nM guanylin (Clone).
The cGMP level in the produced GC-C-expressing cell line treated with 100 nM guanylin was also compared to that of parental cell line control samples not expressing GC-C (not shown) using the Direct Cyclic GMP Enzyme Immunoassay Kit (Cat. 900-014; AssayDesigns, Inc.). The GC-C-expressing cell line showed a greater reduction in absorbance (corresponding to increased cGMP levels) than parental cells treated and untreated with guanylin.
For guanylin dose-response experiments, cells of the produced GC-C-expressing cell line, plated at densities of 20,000, 40,000, 60,000, 80,000, 120,000 and 160,000 cells/well in a 96-well plate, were challenged with increasing concentration of guanylin for 30 minutes. The cellular response (i.e., absorbance) as a function of changes in cGMP levels (as measured using the Direct Cyclic GMP Enzyme Immunoassay Kit (Cat. 900-014; AssayDesigns, Inc.) was detected using a SAFIRE2™ plate reader (Tecan). Data were then plotted as a function of guanylin concentration and analyzed using non-linear regression analysis using Graph Pad Prism 5.0 software, resulting in an EC50 value of 1.1 nM. The produced GC-C-expressing cell line shows a higher level of cGMP (6 pmol/ml) when treated with low concentrations of guanylin in comparison to that previously reported in other cell lines (3.5 pmol/ml) (Forte et al., Endocr. 140(4):1800-1806 (1999)), indicating the potency of the clone.
Z′ for the produced GC-C-expressing cell line was calculated using a direct competitive ELISA assay. The ELISA was performed using the Direct Cyclic GMP Enzyme Immunoassay Kit (Cat. 900-014; AssayDesigns, Inc.). Specifically, for the Z′ assay, 24 positive control wells in a 96-well assay plate (plated at a density of 160,000 or 200,000 cells/well) were challenged with a GC-C activating cocktail of 400 guanylin and IBMX in DMEM media for 30 minutes. Considering the volume and surface area of the 96-well assay plate, this amount of guanylin created a concentration comparable to the 100 used by Forte et al. (1999) Endocr. 140(4), 1800-1806. An equal number of wells containing clonal cells in DMEM/IMBX were challenged with vehicle alone (in the absence of activator). Absorbance (corresponding to cGMP levels) in the two conditions was monitored using a SAFIRE2™ plate reader (Tecan). Mean and standard deviations in the two conditions were calculated and Z′ was computed using the method of Zhang et al., J Biomol Screen, 4(2):67-73 (1999)). The Z′ value of the produced GC-C-expressing cell line was determined to be 0.72.
Using chamber experiments are performed 7-14 days after plating GC-C-expressing cells (primary or immortalized epithelial cells, for example, lung, intestinal, mammary, uterine, or renal) on culture inserts (Snapwell, Corning Life Sciences). Cells on culture inserts are rinsed, mounted in an Using type apparatus (EasyMount Chamber System, Physiologic Instruments) and bathed with continuously gassed Ringer solution (5% CO2 in O2, pH 7.4) maintained at 37° C. containing (in mM) 120 NaCl, 25 NaHCO3, 3.3 KH2PO4, 0.8 K2HPO4, 1.2 CaCl2, 1.2 MgCl2, and 10 glucose. The hemichambers are connected to a multichannel voltage and current clamp (VCC-MC8, Physiologic Instruments). Electrodes [agar bridged (4% in 1 M KCl) Ag—AgCl] are used, and the inserts are voltage clamped to 0 mV. Transepithelial current, voltage and resistance are measured every 10 seconds for the duration of the experiment. Membranes with a resistance of <200 mOhms are discarded. This secondary assay can provide confirmation that in the appropriate cell type (i.e., cell that form tight junctions) the introduced GC-C is altering CFTR activity and modulating a transepithelial current.
Plasmid expression vectors that allowed streamlined cloning were generated based on pCMV-SCRIPT (Stratagene) and contained various necessary components for transcription and translation of a gene of interest, including: CMV and SV40 eukaryotic promoters; SV40 and HSV-TK polyadenylation sequences; multiple cloning sites; Kozak sequences; and drug resistance cassettes (i.e., puromycin). Ampicillin or neomycin resistance cassettes can also be used to substitute puromycin. A tag sequence containing Target Sequence 2 (SEQ ID NO: 138) was then inserted into the multiple cloning site of the plasmid. A cDNA cassette encoding a human CFTR was then subcloned into the multiple cloning site upstream of the tag sequence, using Asc1 and Pac1 restriction endonucleases.
CHO cells were transfected with a plasmid encoding a human CFTR (SEQ ID NO: 16) using standard techniques. (Examples of reagents that may be used to introduce nucleic acids into host cells include, but are not limited to, LIPOFECTAMINE™, LIPOFECTAMINE™ 2000, OLIGOFECTAMINE™, TFX™ reagents, FUGENE® 6, DOTAP/DOPE, Metafectine or FECTURIN™.)
Although drug selection is optional to produce the cells or cell lines of this invention, we included one drug resistance marker in the plasmid (i.e., puromycin). The CFTR sequence was under the control of the CMV promoter. An untranslated sequence encoding a Target Sequence for detection by a signaling probe was also present along with the sequence encoding the drug resistance marker. The target sequence utilized was Target Sequence 2 (SEQ ID NO: 138), and in this example, the CFTR gene-containing vector comprised Target Sequence 2 (SEQ ID NO: 138).
Transfected cells were grown for 2 days in Ham's F12-FBS media (Sigma Aldrich, St. Louis, Mo.) without antibiotics, followed by 10 days in 12.5 μg/ml puromycin-containing Ham's F12-FBS media. The cells were then transferred to Ham's F12-FBS media without antibiotics for the remainder of the time, prior to the addition of the signaling probe.
Following enrichment on antibiotic, cells were passaged 5-14 times in the absence of antibiotic selection to allow time for expression that was not stable over the selected period of time to subside.
Cells were harvested and transfected with Signaling Probe 2 (SEQ ID NO: 139) using standard techniques. (Examples of reagents that may be used to introduce nucleic acids into host cells include, but are not limited to, LIPOFECTAMINE™, LIPOFECTAMINE™ 2000, OLIGOFECTAMINE™, TFX™ reagents, FUGENE® 6, DOTAP/DOPE, Metafectine or FECTURIN™.) CFTR Signaling Probe 2 (SEQ ID NO: 139) bound Target Sequence 2 (SEQ ID NO: 138). The cells were then collected for analysis and sorted using a fluorescence activated cell sorter.
BHQ2 in Signaling Probe 2 can be substituted with BHQ3 or a gold particle. Target Sequence 2 and Signaling Probe 2 can be replaced by Target Sequence 1 (SEQ ID NO: 17) and Signaling Probe 1 (SEQ ID NO: 18), respectively. BHQ2 in Signaling Probe 1 can be substituted with BHQ3 or a gold particle.
In addition, a similar probe using a Quasar® Dye (BioSearch) with spectral properties similar to Cy5 is used in certain experiments against Target Sequence 1 (SEQ ID NO: 17). In some experiments, 5-MedC and 2-amino dA mixmers were used rather than DNA probes. A non-targeting FAM labeled probe is also used as a loading control.
The cells were dissociated and collected for analysis and sorting using a fluorescence activated cell sorter (Beckman Coulter, Miami, Fla.). Standard analytical methods were used to gate cells fluorescing above background and to isolate individual cells falling within the gate into bar-coded 96-well plates. The following gating hierarchy was used:
coincidence gate→singlets gate→live gate→Sort gate in plot FAM vs. Cy5.5: 0.1-0.4% of cells according to standard procedures in the field.
Step 6: Additional Cycles of Steps 1-5 and/or 3-5
Steps 1-5 and/or 3-5 were repeated to obtain a greater number of cells. Two rounds of steps 1-5 were performed, and for each of these rounds, two internal cycles of steps 3-5 were performed.
The plates were transferred to a Microlab Star (Hamilton Robotics). Cells were incubated for 9 days in 100 μl of 1:1 mix of fresh complete growth media and 2 to 3 day-conditioned growth media, supplemented with 100 units/ml penicillin and 0.1 mg/ml streptomycin. Then the cells were dispersed by trypsinization once or twice to minimize clumps and later transferred to new 96-well plates. Plates were imaged to determine confluency of wells (Genetix). Each plate was focused for reliable image acquisition across the plate. Reported confluencies of greater than 70% were not relied upon. Confluency measurements were obtained on consecutive days between days 1 and 10 post-dispersal and used to calculate growth rates.
Cells were binned (independently grouped and plated as a cohort) according to growth rate less than two weeks following the dispersal step in step 7. Each of the three growth bins was separated into individual 96 well plates; some growth bins resulted in more than one 96 well plate. Bins were calculated by considering the spread of growth rates and bracketing a high percentage of the total number of populations of cells. Bins were calculated to capture 12-16 hour differences in growth rate.
Cells can have doubling times from less than 1 day to more than 2 week. In order to process the most diverse clones that at the same time can be reasonably binned according to growth rate, it may be preferable to use 3-9 bins with a 0.25 to 0.7 day doubling time per bin. One skilled in the art will appreciate that the tightness of the bins and number of bins can be adjusted for the particular situation and that the tightness and number of bins can be further adjusted if cells are synchronized for their cell cycle.
The plates were incubated under standardized and fixed conditions (i.e., Ham's F12-FBS media, 37° C./5% CO2) without antibiotics. The plates of cells were split to produce 4 sets of 96 well plates (3 sets for freezing, 1 set for assay and passage). Distinct and independent tissue culture reagents, incubators, personnel, and carbon dioxide sources were used for each of the sets of the plates. Quality control steps were taken to ensure the proper production and quality of all tissue culture reagents: each component added to each bottle of media prepared for use was added by one designated person in one designated hood with only that reagent in the hood while a second designated person monitored to avoid mistakes. Conditions for liquid handling were set to eliminate cross contamination across wells. Fresh tips were used for all steps or stringent tip washing protocols were used. Liquid handling conditions were set for accurate volume transfer, efficient cell manipulation, washing cycles, pipetting speeds and locations, number of pipetting cycles for cell dispersal, and relative position of tip to plate.
Three sets of plates were frozen at −70 to −80° C. Plates in the set were first allowed to attain confluencies of 70 to 100%. Medium was aspirated and 90% FBS and 10% DMSO was added. The plates were individually sealed with Parafilm, individually surrounded by 1 to 5 cm of foam, and then placed into a −80° C. freezer.
The remaining set of plates was maintained as described in step 9. All cell splitting was performed using automated liquid handling steps, including media removal, cell washing, trypsin addition and incubation, quenching and cell dispersal steps.
The consistency and standardization of cell and culture conditions for all populations of cells was controlled. Differences across plates due to slight differences in growth rates were controlled by normalization of cell numbers across plates and occurred every 8 passages after the rearray. Populations of cells that were outliers were detected and eliminated.
The cells were maintained for 6 to 10 weeks post rearray in culture. During this time, we observed size, morphology, tendency towards microconfluency, fragility, response to trypsinization and average circularity post-trypsinization, or other aspects of cell maintenance such as adherence to culture plate surfaces and resistance to blow-off upon fluid addition as part of routine internal quality control to identify robust cells. Such benchmarked cells were then admitted for functional assessment.
Populations of cells were tested using functional criteria. Membrane potential dye kits (Molecular Devices, MDS) were used according to manufacturer's instructions.
Cells were tested at varying densities in 384-well plates (i.e., 12.5×103 to 20×103 cells/per well) and responses were analyzed. Time between cell plating and assay read was tested. Dye concentration was also tested. Dose response curves and Z′ scores were both calculated as part of the assessment of potential functionality.
The following steps (i.e., steps 15-18) can also be conducted to select final and back-up viable, stable and functional cell lines.
The functional responses from experiments performed at low and higher passage numbers are compared to identify cells with the most consistent responses over defined periods of time (e.g., 3-9 weeks). Other characteristics of the cells that change over time are also noted.
Populations of cells meeting functional and other criteria are further evaluated to determine those most amenable to production of viable, stable and functional cell lines. Selected populations of cells are expanded in larger tissue culture vessels and the characterization steps described above are continued or repeated under these conditions. At this point, additional standardization steps, such as different cell densities; time of plating, length of cell culture passage; cell culture dishes format and coating; fluidics optimization, including speed and shear force; time of passage; and washing steps, are introduced for consistent and reliable passages.
In addition, viability of cells at each passage is determined. Manual intervention is increased and cells are more closely observed and monitored. This information is used to help identify and select final cell lines that retain the desired properties. Final cell lines and back-up cell lines are selected that show appropriate adherence/stickiness, growth rate, and even plating (lack of microconfluency) when produced following this process and under these conditions.
The low passage frozen stocks corresponding to the final cell line and back-up cell lines are thawed at 37° C., washed two times with Ham's F12-FBS and then incubated in Ham's F12-FBS. The cells are then expanded for a period of 2 to 4 weeks. Cell banks of clones for each final and back-up cell line are established, with 25 vials for each clonal cells being cryopreserved.
At least one vial from the cell bank is thawed and expanded in culture. The resulting cells are tested to determine if they meet the same characteristics for which they are originally selected.
We used a high-throughput compatible fluorescence membrane potential assay to characterize native CFTR function in the produced stable CFTR-expressing cell lines.
CHO cell lines stably expressing CFTR were maintained under standard cell culture conditions in Ham's F12 medium supplemented with 10% fetal bovine serum and glutamine. On the day before assay, the cells were harvested from stock plates and plated into black clear-bottom 384 well assay plates. The assay plates were maintained in a 37° C. cell culture incubator under 5% CO2 for 22-24 hours. The media was then removed from the assay plates and blue membrane potential dye (Molecular Devices Inc.) diluted in loading buffer (137 mM NaCl, 5 mM KCl, 1.25 mM CaCl2, 25 mM HEPES, 10 mM glucose) was added and allowed to incubate for 1 hour at 37° C. The assay plates were then loaded on a fluorescent plate reader (Hamamatsu FDSS) and a cocktail of forskolin and IBMX dissolved in compound buffer (137 mM sodium gluconate, 5 mM potassium gluconate, 1.25 mM CaCl2, 25 mM HEPES, 10 mM glucose) was added.
Representative data from the fluorescence membrane potential assay showed that the ion flux attributable to functional CFTR in stable CFTR-expressing CHO cell lines (cell line 1, M11, J5, E15, and O15) were all higher than control cells lacking CFTR as indicated by the assay response.
The ion flux attributable to functional CFTR in stable CFTR-expressing CHO cell lines (cell line 1, M11, J5, E15, and O15) were also all higher than transiently CFTR-transfected CHO cells. The transiently CFTR-transfected cells were generated by plating CHO cells at 5-16 million per 10 cm tissue culture dish and incubating them for 18-20 hours before transfection. A transfection complex consisting of lipid transfection reagent and plasmids encoding CFTR was directly added to each dish. The cells were then incubated at 37° C. in a CO2 incubator for 6-12 hours. After incubation, the cells were lifted, plated into black clear-bottom 384 well assay plates, and assayed for function using the above-described fluorescence membrane potential assay.
For forskolin dose-response experiments, cells of the produced stable CFTR-expressing cell lines, plated at a density of 15,000 cells/well in a 384-well plate were challenged with increasing concentration of forskolin, a known CFTR agonist. The cellular response as a function of changes in cell fluorescence was monitored over time by a fluorescent plate reader (Hamamatsu FDSS). Data were then plotted as a function of forskolin concentration and analyzed using non-linear regression analysis using GraphPad Prism 5.0 software, resulting in an EC50 of 256 nM. The produced CFTR-expressing cell line shows a EC50 value of forskolin within the ranges of EC50 if forskolin previously reported in other cell lines (between 250 and 500 nM) (Galietta et al., Am J Physiol Cell Physiol. 281(5): C1734-1742 (2001)), indicating the potency of the clone.
Z′ value for the produced stable CFTR-expressing cell line was calculated using a high-throughput compatible fluorescence membrane potential assay. The fluorescence membrane potential assay protocol was performed substantially according to the protocol in Example 12. Specifically for the Z′ assay, 24 positive control wells in a 384-well assay plate (plated at a density of 15,000 cells/well) were challenged with a CFTR activating cocktail of forskolin and IBMX. An equal number of wells were challenged with vehicle alone and containing DMSO (in the absence of activators). Cell responses in the two conditions were monitored using a fluorescent plate reader (Hamamatsu FDSS). Mean and standard deviations in the two conditions were calculated and Z′ was computed using the method disclosed in Zhang et al., J Biomol Screen, 4(2): 67-73, (1999). The Z′ value of the produced stable CFTR-expressing cell line was determined to be higher than or equal to 0.82.
A high-throughput compatible fluorescence membrane potential assay is used to screen and identify CFTR modulator. On the day before assay, the cells are harvested from stock plates into growth media without antibiotics and plated into black clear-bottom 384 well assay plates. The assay plates are maintained in a 37° C. cell culture incubator under 5% CO2 for 19-24 hours. The media is then removed from the assay plates and blue membrane potential dye (Molecular Devices Inc.) diluted in load buffer (137 mM NaCl, 5 mM KCl, 1.25 mM CaCl2, 25 mM HEPES, 10 mM glucose) is added and the cells are incubated for 1 hr at 37° C. Test compounds are solubilized in dimethylsulfoxide, diluted in assay buffer (137 mM sodium gluconate, 5 mM potassium gluconate, 1.25 mM CaCl2, 25 mM HEPES, 10 mM glucose) and then loaded into 384 well polypropylene micro-titer plates. The cell and compound plates are loaded into a fluorescent plate reader (Hamamatsu FDSS) and run for 3 minutes to identify test compound activity. The instrument will then add a forskolin solution at a concentration of 300 nM-1 μM to the cells to allow either modulator or blocker activity of the previously added compounds to be observed. The activity of the compound is determined by measuring the change in fluorescence produced following the addition of the test compounds to the cells and/or following the subsequent agonist addition.
Using chamber experiments are performed 7-14 days after plating CFTR-expressing cells (primary or immortalized epithelial cells including but not limited to lung and intestinal) on culture inserts (Snapwell, Corning Life Sciences). Cells on culture inserts are rinsed, mounted in an Using type apparatus (EasyMount Chamber System, Physiologic Instruments) and bathed with continuously gassed Ringer solution (5% CO2 in O2, pH 7.4) maintained at 37° C. containing 120 mM NaCl, 25 mM NaHCO3, 3.3 mM KH2PO4, 0.8 mM K2HPO4, 1.2 mM CaCl2, 1.2 mM MgCl2, and 10 mM glucose. The hemichambers are connected to a multichannel voltage and current clamp (VCC-MC8 Physiologic Instruments). Electrodes [agar bridged (4% in 1 M KCl) Ag—AgCl] are used and the inserts are voltage clamped to 0 mV. Transepithelial current, voltage and resistance are measured every 10 seconds for the duration of the experiment. Membranes with a resistance of <200 mΩs are discarded.
While both manual and automated electrophysiology assays have been developed and both can be applied to assay this system, described below is the protocol for manual patch clamp experiments.
Cells are seeded at low densities and are used 2-4 days after plating. Borosilicate glass pipettes are fire-polished to obtain tip resistances of 2-4 mega Ω. Currents are sampled and low pass filtered. The extracellular (bath) solution contains: 150 mM NaCl, 1 mM CaCl2, 1 mM MgCl2, 10 mM glucose, 10 mM mannitol, and 10 mM TES, pH 7.4. The pipette solution contains: 120 mM CsCl, 1 mM MgCl2, 10 mM TEA-Cl, 0.5 mM EGTA, 1 mM Mg-ATP, and 10 mM HEPES (pH 7.3). Membrane conductances are monitored by alternating the membrane potential between −80 mV and −100 mV. Current-voltage relationships are generated by applying voltage pulses between −100 mV and +100 mV in 20-mV steps.
Plasmid expression vectors that allowed streamlined cloning were generated based on pCMV-SCRIPT (Stratagene) and contained various necessary components for transcription and translation of a gene of interest, including: CMV and SV40 eukaryotic promoters; SV40 and HSV-TK polyadenylation sequences; multiple cloning sites; Kozak sequences; and Neomycin/Kanamycin resistance cassettes (or Ampicillin, Hygromycin, Puromycin, Zeocin resistance cassettes).
293T cells were cotransfected with three separate plasmids, one encoding a human NaV 1.7 α subunit (SEQ ID NO: 19), one encoding a human NaV 1.7 β1 subunit (SEQ ID NO: 20) and one encoding a human NaV 1.7 β2 subunit (SEQ ID NO: 21), using standard techniques. (Examples of reagents that may be used to introduce nucleic acids into host cells include, but are not limited to, LIPOFECTAMINE™, LIPOFECTAMINE™ 2000, OLIGOFECTAMINE™, TFX™ reagents, FUGENE® 6, DOTAP/DOPE, Metafectine or FECTURIN™.)
Although drug selection is optional to produce the cells or cell lines of this invention, we included one drug resistance marker per plasmid. The sequences were under the control of the CMV promoter. An untranslated sequence encoding a NaV Target Sequence for detection by a signaling probe was also present along with the sequence encoding the drug resistance marker. The NaV Target Sequences utilized were NaV Target Sequence 1 (SEQ ID NO: 22), NaV Target Sequence 2 (SEQ ID NO: 23) and NaV Target Sequence 3 (SEQ ID NO: 24). In this example, the NaV 1.7 α subunit gene-containing vector comprised NaV Target Sequence 1 (SEQ ID NO: 22); the NaV 1.7 β1 subunit gene-containing vector comprised NaV Target Sequence 2 (SEQ ID NO: 23); and the NaV 1.7 β2 subunit gene-containing vector comprised NaV Target Sequence 3 (SEQ ID NO: 24).
Transfected cells were grown for 2 days in DMEM-FBS media, followed by 10 days in antibiotic-containing DMEM-FBS media. During the antibiotic containing period, antibiotics were added to the media as follows: puromycin (0.1 μg/ml), hygromycin (100 μg/ml), and zeocin (200 μg/ml).
Following enrichment on antibiotic, cells were passaged 6-18 times in the absence of antibiotic selection to allow time for expression that was not stable over the selected period of time to subside.
Cells were harvested and transfected with signaling probes (SEQ ID NOS: 25, 26, 27) using standard techniques. (Examples of reagents that may be used to introduce nucleic acids into host cells include, but are not limited to, LIPOFECTAMINE™, LIPOFECTAMINE™ 2000, OLIGOFECTAMINE™, TFX™ reagents, FUGENE® 6, DOTAP/DOPE, Metafectine or FECTURIN™.)
NaV Signaling Probe 1 (SEQ ID NO: 25) bound NaV Target Sequence 1 (SEQ ID NO: 22); NaV Signaling Probe 2 (SEQ ID NO: 26) bound NaV Target Sequence 2 (SEQ ID NO:23); and NaV Signaling Probe 3 (SEQ ID NO: 27) bound NaV Target Sequence 3 (SEQ ID NO: 24). The cells were then dissociated and collected for analysis and sorted using a fluorescence activated cell sorter (Beckman Coulter, Miami, Fla.).
The following target sequences were used for the NaV 1.7 subunit transgenes.
Supplied as 100 μM stocks.
BHQ3 in NaV Signaling probes 1 and 2 can be replaced by BHQ2 or gold particle. BHQ1 in NaV Signaling probe 3 can be replaced by BHQ2, gold particle, or DABCYL.
In addition, a similar probe using a Quasar® Dye (BioSearch) with spectral properties similar to Cy5 was used in certain experiments. In some experiments, 5-MedC and 2-amino dA mixmer probes were used rather than DNA probes.
Standard analytical methods were used to gate cells fluorescing above background and to isolate cells falling within the defined gate directly into 96-well plates. Flow cytometric cell sorting was operated such that a single cell was deposited per well. After selection, the cells were expanded in media lacking drug.
The following gating hierarchy was used:
coincidence gate→singlets gate→live gate→Sort gate in plot FAM vs. Cy5: 0.1-1.0% of live cells.
Step 6: Additional Cycles of Steps 1-5 and/or 3-5
Steps 1-5 and/or 3-5 were repeated to obtain a greater number of cells. At least four independent rounds of steps 1-5 were completed, and for each of these cycles, at least two internal cycles of steps 3-5 were performed for each independent round.
The plates were transferred to a Microlabstar automated liquid handler (Hamilton Robotics). Cells were incubated for 5-7 days in a 1:1 mix of fresh complete growth medium (DMEM/10% FBS) and 2-3 day conditioned growth medium, supplemented with 100 units/ml penicillin and 0.1 mg/ml streptomycin. Then the cells were dispersed by trypsinization to minimize clumps and transferred to new 96-well plates. After the clones were dispersed, plates were imaged to determine confluency of wells (Genetix). Each plate was focused for reliable image acquisition across the plate. Reported confluencies of greater than 70% were not relied upon. Confluency measurements were obtained at days every 3 times over 9 days (i.e., between days 1 and 10 post-dispersal) and used to calculate growth rates.
Cells were binned (independently grouped and plated as a cohort) according to growth rate between 10-11 days following the dispersal step in step 7. Bins were independently collected and plated on individual 96 well plates for downstream handling; some growth bins resulted in more than one 96-well plate. Bins were calculated by considering the spread of growth rates and bracketing a high percentage of the total number of populations of cells. Depending on the sort iteration described in Step 5, between 5 and 9 growth bins were used with a partition of 1-4 days. Therefore, each bin corresponded to a growth rate or population doubling time difference between 8 and 14.4 hours depending on the iteration.
Cells can have doubling times from less 1 day to more than 2 weeks. In order to process the most diverse clones that at the same time can be reasonably binned according to growth rate, it is preferable to use 3-9 bins with a 0.25 to 0.7 day doubling time per bin. One skilled in the art will appreciate that the tightness of the bins and number of bins can be adjusted for the particular situation and that the tightness and number of bins can be further adjusted if cells are synchronized for their cell cycle.
The plates were incubated under standard and fixed conditions (humidified 37° C., 5% CO2) in antibiotics-free DMEM-10% FBS media. The plates of cells were split to produce 4 sets of target plates. These 4 sets of plates comprised all plates with all growth bins to ensure there were 4 replicates of the initial set. Up to 3 target plate sets were committed for cryopreservation (described in step 10), and the remaining set was scaled and further replica plated for passage and functional assay experiments. Distinct and independent tissue culture reagents, incubators, personnel, and carbon dioxide sources were used for downstream replica plates. Quality control steps were taken to ensure the proper production and quality of all tissue culture reagents: each component added to each bottle of media prepared for use was added by one designated person in one designated hood with only that reagent in the hood while a second designated person monitored to avoid mistakes. Conditions for liquid handling were set to eliminate cross contamination across wells. Fresh tips were used for all steps, or stringent tip washing protocols were used. Liquid handling conditions were set for accurate volume transfer, efficient cell manipulation, washing cycles, pipetting speeds and locations, number of pipetting cycles for cell dispersal, and relative position of tip to plate.
Three sets of plates were frozen at −70 to −80° C. Plates in each set were first allowed to attain confluencies of 70 to 80%. Medium was aspirated and 90% FBS and 5%-10% DMSO was added. The plates were sealed with Parafilm, individually surrounded by 1 to 5 cm of foam, and then placed into a −80° C. freezer.
The remaining set of plates was maintained as described in step 9. All cell splitting was performed using automated liquid handling steps, including media removal, cell washing, trypsin addition and incubation, quenching and cell dispersal steps. For some assay plating steps, cells were dissociated with cell dissociation buffer (e.g., CDB, Invitrogen or CellStripper, CellGro) rather than trypsin.
The consistency and standardization of cell and culture conditions for all populations of cells was controlled. Differences across plates due to slight differences in growth rates were controlled by periodic normalization of cell numbers across plates every 2 to 8 passages. Populations of cells that were outliers were detected and eliminated.
The cells were maintained for 3 to 8 weeks to allow for their in vitro evolution under these conditions. During this time, we observed size, morphology, fragility, response to trypsinization or dissociation, roundness/average circularity post-dissociation, percentage viability, tendency towards microconfluency, or other aspects of cell maintenance such as adherence to culture plate surfaces.
Populations of cells were tested using functional criteria. Membrane potential assay kits (Molecular Devices/MDS) were used according to manufacturer's instructions. Cells were tested at multiple different densities in 96- or 384-well plates and responses were analyzed. A variety of post-plating time points were used, e.g., 12-48 hours post plating. Different densities of plating were also tested for assay response differences.
The functional responses from experiments performed at low and higher passage numbers were compared to identify cells with the most consistent responses over defined periods of time, ranging from 3 to 9 weeks. Other characteristics of the cells that changed over time were also noted.
Populations of cells meeting functional and other criteria were further evaluated to determine those most amenable to production of viable, stable and functional cell lines. Selected populations of cells were expanded in larger tissue culture vessels and the characterization steps described above were continued or repeated under these conditions. At this point, additional standardization steps, such as different plating cell densities; time of passage; culture dish size/format and coating); fluidics optimization; cell dissociation optimization (e.g., type, volume used, and length of time); and washing steps, were introduced for consistent and reliable passages. Temperature differences were also used for standardization (i.e., 30° C. vs 37° C.).
In addition, viability of cells at each passage was determined. Manual intervention was increased and cells were more closely observed and monitored. This information was used to help identify and select final cell lines that retained the desired properties. Final cell lines and back-up cell lines were selected that showed consistent growth, appropriate adherence, and functional response.
The low passage frozen plates described above corresponding to the final cell line and back-up cell lines were thawed at 37° C., washed two times with DMEM-10% FBS and incubated in humidified 37° C./5% CO2 conditions. The cells were then expanded for a period of 2-3 weeks. Cell banks for each final and back-up cell line consisting of 15-20 vials were established.
The following step can also be conducted to confirm that the cell lines are viable, stable, and functional. At least one vial from the cell bank is thawed and expanded in culture. The resulting cells are tested to determine if they meet the same characteristics for which they were originally selected.
Quantitative RT-PCR (qRT-PCR) was used to determine the relative expression of the heterologous human NaV 1.7 α, β1, and β2 subunits in the produced stable NaV 1.7-expressing cell lines. Total RNA was purified from 1-3×106 mammalian cells using an RNA extraction kit (RNeasy Mini Kit, Qiagen). DNase treatment was done according to rigorous DNase treatment protocol (TURBO DNA-free Kit, Ambion). First strand cDNA synthesis was performed using a reverse transcriptase kit (SuperScript III, Invitrogen) in 20 μL reaction volume with 1 μg DNA-free total RNA and 250 ng Random Primers (Invitrogen). Samples without reverse transcriptase and sample without RNA were used as negative controls for this reaction. Synthesis was done in a thermal cycler (Mastercycler, Eppendorf) at the following conditions: 5 min at 25° C., 60 min at 50° C.; reaction termination was conducted for 15 min at 70° C.
For analysis of gene expression, primers and probes for qRT-PCR (MGB TaqMan probes, Applied Biosystems) were designed to specifically anneal to the target sequences (SEQ ID NOS: 22, 23, 24). For sample normalization, control (glyceraldehyde 3-phosphate dehydrogenase (GAPDH)) Pre-Developed Assay reagents (TaqMaN, Applied Biosystems) were used. Reactions, including negative controls and positive controls (plasmid DNA), were set up in triplicates with 40 ng of cDNA in 50 μL reaction volume. The relative amounts of each of the three NaV 1.7 subunits being expressed were determined. All three subunits were successfully expressed in the produced stable NaV 1.7-expressing cell line.
Automated patch-clamp system was used to record sodium currents from the produced stable HEK293T cell lines expressing NaV 1.7 α, β1, and β2 subunits. The following illustrated protocol can also be used for QPatch, Sophion or Patchliner, Nanion systems. The extracellular Ringer's solution contained 140 mM NaCl, 4.7 mM KCl, 2.6 mM MgCl2, 11 mM glucose and 5 mM HEPES, pH 7.4 at room temperature. The intracellular Ringer's solution contained 120 mM CsF, 20 mM Cs-EGTA, 1 mM CaCl2, 1 mM MgCl2, and 10 mM HEPES, pH 7.2. Experiments were conducted at room temperature.
Cells stably expressing NaV 1.7 α, β1, and β2 subunits were grown under standard culturing protocols as described in Example 17. Cells were harvested and kept in suspension with continuous stirring for up to 4 hours with no significant change in quality or ability to patch. Electrophysiological experiment (whole-cell) was performed using the standard patch plate. The patch-clamp hole (micro-etched in the chip) is approximately 1 μm in diameter and has a resistance of ˜2 MΩ. The membrane potential was clamped to a holding potential of −100 mV.
Current-voltage relation and inactivation characteristics of voltage-gated human NaV 1.7 sodium channel stably expressed in HEK293T cells were characterized. Sodium currents were measured in response to 20 ms depolarization pulses from −80 mV to +50 mV with a holding potential of −100 mV. The resulting current-voltage (I-V) relationship for peak sodium channel currents was characterized. The activation threshold was −35 mV (midpoint of activation, Va=−24.9 mV+/−3.7 mV), and the maximal current amplitude was obtained at −10 mV. The inactivation graph for the sodium channel was plotted. The membrane potential was held at a holding potential of −100 mV, subsequently shifted to conditioning potentials ranging from −110 mV to +10 mV for 1000 ms, and finally the current was measured upon a step to 0 mV. The resulting current amplitude indicates the fraction of sodium channels in the inactivated state. At potentials more negative than −85 mV the channels were predominantly in the closed state, whereas at potentials above −50 mV they were predominantly in the inactivated state. The curve represents the Boltzmann fit from which the V1/2 for steady-state inactivation was estimated to be −74 mV. The current-voltage profile for the produced stable NaV 1.7-expressing cell lines is consistent with previously reported current-voltage profile (Va=−28.0 mV±1.1 mV; V1/2=−71.3 mV±0.8 mV) (Sheets et al., J Physiol. 581(Pt 3):1019-1031. (2007)).
The produced stable cells expressing NaV 1.7 α, β1, and β2 subunits were maintained under standard cell culture conditions in Dulbecco's Modified Eagles medium supplemented with 10% fetal bovine serum, glutamine and HEPES. On the day before assay, the cells were harvested from stock plates using cell dissociation buffer, e.g., CDB (GIBCO) or cell-stripper (Mediatech), and plated at 10,000-25,000 cells per well in 384 well plates in growth media. The assay plates were maintained in a 37° C. cell culture incubator under 5% CO2 for 22-24 hours. The media were then removed from the assay plates and blue fluorescence membrane potential dye (Molecular Devices Inc.) diluted in load buffer (137 mM NaCl, 5 mM KCl, 1.25 mM CaCl2, 25 mM HEPES, 10 mM glucose) was added. The cells were incubated with blue membrane potential dye for 1 hour at 37° C. The assay plates were then loaded onto the high-throughput fluorescent plate reader (Hamamastu FDSS). The fluorescent plate reader measures cell fluorescence in images taken of the cell plate once per second and displays the data as relative florescence units.
The assay response of stable NaV 1.7-expressing cells and control cells (i.e., HEK293T parental cells) to addition of buffer and channel activators (i.e., veratridine and scorpion venom (SV)) were measured. In a first addition step (i.e., Addition 1), only buffer was added, with no test compounds added. If desired, test compounds can be added in this step. In a second addition step, veratridine and scorpion venom, which are sodium channels activators, were diluted in assay buffer to the desired concentration (i.e., 25 μM veratridine and 5-25 μg/ml scorpion venom) and added into 384 well polypropylene microtiter plates. Once bound, veratridine and scorpion venom proteins modulate the activity of voltage-gated sodium channels through a combination of mechanisms, including an alteration of the activation and inactivation kinetics. The resulted activation of sodium channels in stable NaV 1.7-expressing cells changes cells membrane potential and the fluorescent signal increases. The above-described functional assay can also be used to characterize the relative potencies of test compounds at NaV 1.7 ion channels.
Pools of HEK293T cells were engineered to express various ratios of α and β subunits by manipulating the molar ratios of independent plasmid DNAs or α and control plasmids (e.g., α:β1:β2=1:1:1). After drug selection the subunits expression in six different cell pools were evaluated with qRT-PCR as described in Example 18. Comparative qRT-PCR indicated that α subunit expression in drug-selected cells detection was increased when all three human NaV 1.7 subunits (i.e., α, β1, and β2) were co-transfected in compared to only α subunit and control plasmid transfected. The presence of the β subunit transcripts affects α subunit gene expression, demonstrating the importance of co-expressing all three NaV 1.7 subunits for a physiologically relevant functional assay.
A membrane potential cell-based assay was used to measure the response to test compounds of the cells stably co-expressing all three NaV 1.7 subunits (i.e., α, β1, and β2) and control cells stably expressing only a NaV 1.7 α subunit. Two compounds (i.e., C18 and K21) were tested in the membrane potential assay performed substantially according to the protocol in Example 20. Specifically for this example, the test compounds were added in the first addition step.
C18 and K21 potentiated the response of clone C44 (expressing NaV 1.7 α, β1, and β2 subunits) and blocked the response of clone C60 (expressing NaV 1.7 α subunit only). The assay response of the two test compounds was normalized to the response of buffer alone for each of the two clones.
A membrane potential cell-based assay was used to measure the response to test compounds of different cell lines stably co-expressing all three NaV 1.7 subunits (i.e., α, β1, and β2). Dose-response analysis (DRC) for a set of compounds tested on four cell lines generated from cells positive for the expression of NaV 1.7 alpha, beta1 and beta2 subunits resulted in distinct functional profiles (
˜90 NaV 1.7 cell lines co-expressing all three NaV 1.7 subunits (i.e., α, β1, and β2) were grouped based on their functional pharmacological profile in cell based assays where each clonal cell line was tested using the same compounds (
longicaudatus
Mus musculus-1
Mus musculus-2
Anopheles Gambiae Olfactory Receptors
Homo sapiens
Mus musculus
Danio rerio
Pan troglodytes
Bos taurus
Bos taurus
Gallus gallus
Canis familiaris
Rattus
norvegicus
Homo sapiens
Mus musculus
Danio rerio
Pan troglodytes
Bos taurus
Gallus gallus
Canis familiaris
Rattus
norvegicus
Homo sapiens
Mus musculus
Drosophila
melanogaster
Bos taurus
Gallus gallus
Canis familiaris
Rattus
norvegicus
Homo sapiens
Mus musculus
Danio rerio
Pan troglodytes
Bos taurus
Gallus gallus
Canis familiaris
Rattus
norvegicus
Homo sapiens
Mus musculus
Drosophila
melanogaster
Caenorhabditis
elegans
Danio rerio
Bos taurus
Gallus gallus
Canis familiaris
Rattus
norvegicus
Homo sapiens
Mus musculus
Drosophila
melanogaster
Caenorhabditis
elegans
Danio rerio
Danio rerio
Pan troglodytes
Bos taurus
Gallus gallus
Canis familiaris
Rattus
norvegicus
Homo sapiens
Mus musculus
Pan troglodytes
Bos taurus
Gallus gallus
Rattus
norvegicus
Homo sapiens
Mus musculus
Danio rerio
Pan troglodytes
Bos taurus
Gallus gallus
Canis familiaris
Rattus
norvegicus
Homo sapiens
Mus musculus
Drosophila
melanogaster
Caenorhabditis
elegans
Danio rerio
Pan troglodytes
Gallus gallus
Canis familiaris
Rattus
norvegicus
Homo sapiens
Mus musculus
Danio rerio
Pan troglodytes
Bos taurus
Gallus gallus
Canis familiaris
Rattus
norvegicus
Homo sapiens
Mus musculus
Danio rerio
Bos taurus
Gallus gallus
Canis familiaris
Rattus
norvegicus
Homo sapiens
Mus musculus
Danio rerio
Gallus gallus
Rattus
norvegicus
Homo sapiens
Mus musculus
Danio rerio
Pan troglodytes
Bos taurus
Gallus gallus
Canis familiaris
Rattus
norvegicus
Homo sapiens
Mus musculus
Pan troglodytes
Bos taurus
Canis familiaris
Rattus
norvegicus
Homo sapiens
Mus musculus
Pan troglodytes
Bos taurus
Gallus gallus
Canis familiaris
Rattus
norvegicus
Homo sapiens
Mus musculus
Pan troglodytes
Bos taurus
Canis familiaris
Rattus
norvegicus
Homo sapiens
Mus musculus
Drosophila
melanogaster
Caenorhabditis
elegans
Danio rerio
Pan troglodytes
Bos taurus
Canis familiaris
Rattus
norvegicus
Homo sapiens
Mus musculus
Drosophila
melanogaster
Danio rerio
Pan troglodytes
Bos taurus
Gallus gallus
Canis familiaris
Rattus
norvegicus
Homo sapiens
Mus musculus
Danio rerio
Pan troglodytes
Bos taurus
Gallus gallus
Canis familiaris
Rattus
norvegicus
Homo sapiens
Mus musculus
Danio rerio
Pan troglodytes
Gallus gallus
Canis familiaris
Rattus
norvegicus
Homo sapiens
Mus musculus
Danio rerio
Pan troglodytes
Bos taurus
Gallus gallus
Rattus
norvegicus
Preferred G proteins in making bitter receptor cell lines include, but are not limited to Mouse Gα15 and Human GNA15.
Homo sapiens cystic
Homo sapiens cystic fibrosis transmembrane
Human odorant receptor homologs of the receptors listed in Table 22 can also be used with the methods and compositions of the invention.
Transfection
HEK293T (ATCC CRL-11268) were cotransfected with three separate plasmids, one encoding T1R1 (SEQ ID NO: 41), one encoding T1R3 (SEQ ID NO: 32) and the other encoding a signaling molecule (mouse Gα15, SEQ ID NO: 33). Although drug selection is optional in the methods of this invention, we included one drug resistance marker per plasmid. The sequences were under the control of the CMV promoter. An untranslated sequence encoding a tag for detection by a signaling probe was also present along with a sequence encoding a drug resistance marker. The target sequences utilized were Target Sequence 1 (SEQ ID NO: 28), Target Sequence 2 (SEQ ID NO: 29) and Target Sequence 3 (SEQ ID NO: 30). In these examples, the T1R1 gene vector contained Target Sequence 3, the T1R3 gene vector contained Target Sequence 1 and the Gα15 gene vector contained the Target Sequence 2. The cells were conventionally selected in media containing the drug for 10-14 days.
Exposure of Cells to Fluorogenic Probes
Selected cells were harvested and transfected with signaling probes (SEQ ID NO: 38-40). Signaling Probe 1 binds Tag Sequence 1 (SEQ ID NO:126), Signaling Probe 2 binds Tag Sequence 2 (SEQ ID NO:127) and Signaling Probe 3 binds Tag Sequence 3 (SEQ ID NO:128). The cells were then dissociated and collected for analysis and sorted using a fluorescence activated cell sorter (Beckman Coulter, Miami, Fla.). As will be appreciated by those of skill in the art, any reagent that is suitable for use with a chosen host cell may be used to introduce a nucleic acid, e.g. plasmid, oligonucleotide, labeled oligonucleotide, into a host cell with proper optimization. Examples of reagents that may be used to introduce nucleic acids into host cells include but are not limited to: Lipofectamine, Lipofectamine 2000, Oligofectamine, TFX reagents, Fugene 6, DOTAP/DOPE, Metafectine, or Fecturin.
CATCTGGGCCCGGAAAGCCTTTTTCTCTGTGATCCGGTACAGTCCTTCTG
GTCGTTCTGCGACATCTGGGCCCGGAAAGCGTTTAACTGATGGATGGAAC
Other target sequences and signaling probes could be used (see, e.g., as described in International Patent Application Publication No. WO2005/079462 published on Sep. 1, 2005 (Application No. PCT/US05/005080). For example, BHQ3 could be substituted with BHQ1 or a gold particle in Probe 1 or Probe 2. Note that BHQ1 could be substituted with BHQ2 or Dabcyl in Probe 3. A similar probe using a Quasar Dye (BioSearch) with spectral properties similar to Cy5 could be used in certain experiments. Note also that 5-MedC and 2-aminodA mixmer probes rather than DNA probes could be used in some instances.
Isolation of Positive Cells
Standard analytical methods were used to gate cells fluorescing above background and to isolate cells falling within that defined gate directly into 96-well plates. Cell sorting was operated such that a single cell was deposited per well. After selection, the cells were expanded in media lacking drug.
Functional Transformation
We maintained the umami taste receptor cells (selected and expanded as above) using both aliquots of the same cells and different cells in various growth conditions including, for example, low-glucose DMEM media or in glucose-free Leibovitz L-15 media with 10% serum or serum-free. Some cells were maintained in media containing various concentrations of other sugars such as galactose We then characterized cells of the umami taste receptor cell lines maintained under multiple conditions for their ability to respond appropriately to umami ligands and not respond to other stimuli (i.e., sugars).
Growth in the various media conditions, without wishing to be bound by theory, may functionally transform the cells, e.g. due to changes in gene expression levels, genomic organization and functional expression of receptors at the cell surface. Parameters in the various media that were evaluated and shown to affect a cell's functional assay response include serum concentration (i.e. low serum concentrations and serum deprivation), sugar deprivation and assay plate coating (for example, poly D lysine and laminin). These results demonstrated that characteristics of the cells of the umami taste receptor cell lines may be different when the cells are maintained in different media conditions. They also show that different cells selected by the fluorogenic probes may have different characteristics. One example of our characterization of cells selected by the fluorogenic probes is in
1. Confirmation and Quantification of Gene Expression.
Using qRT-PCR, we determined the relative amounts (RNA) of each of the umami taste receptor subunits being expressed in the above cells (“Final”). Using qRT-PCR, we determined the relative amounts of each of the umami taste receptor subunits being expressed. Total RNA was purified from 1-3×106 mammalian cells using a commercially available RNA purification kit (RNeasy Mini Kit, Qiagen). The RNA extract was then treated using a rigorous DNase treatment protocol (TURBO DNA-free Kit; Ambion). First strand cDNA synthesis was performed using a Reverse Transcriptase Kit (SuperScript III, Invitrogen) in 20 uL reaction volume with 1 uG DNA-free total RNA and 250 nG Random Primers (Invitrogen). Negative controls for this reaction included samples in which reverse transcriptase or RNA were left out during the cDNA synthesis step. cDNA and PCR product synthesis was carried out in a thermal cycler (Mastercycler Eppendorf) at the following conditions: 5 min at 25° C., 60 min at 50° C.; reaction termination was conducted for 15 min at 70° C.
For analysis of gene expression (RNA) probes against T1R1, T1R3 and mouse Gα15 cDNA (MGB TaqMan probes, Applied Biosystems) were used. For sample normalization control, the GAPDH, Pre-Developed TaqMaN Assay Reagents, Applied Biosystems was utilized. Reactions, including negative controls and positive controls (plasmid DNA), were set up in triplicates with 40 nG of cDNA in 50 uL reaction volume. The relative amounts of each of the umami taste receptor subunits being expressed (RNA) were determined.
Standard single endpoint RT-PCR procedures were used to assess T1R1, T1R3 and Gα15 gene expression (RNA) in one and nine month cultures of the umami taste receptor cell line generated according to the protocol described above (“Final”). Cells were grown in a 24-well plate format to 80% confluency and harvested and RNA was isolated using a commercially available RNA preparation kit (RNAqueous kit, Ambion). A range of 5 pg to 5 ug of purified total RNA was used to perform reverse transcription, according to the protocol of a commercial first strand cDNA synthesis kit (Superscript III kit, Invitrogen), with oligo (dT) 12,18 primers. Following first strand synthesis, oligo sets specific for the subunits of the umami taste receptor nucleic acids (T1R1, T1R3), as well as for the mouse Gα15 nucleic acids, were independently assembled in PCR reaction mixtures (HotStart Taq). Following a 45 cycle PCR, amplicon samples were further analyzed by agarose gel electrophoresis.
The results from these single-endpoint RT-PCR experiments are illustrated in
2. Cell-Based Assay for Modulators
Cells of this invention are seeded (75-125K) per well 24 hours prior to assay in 96 well plates in growth media (Low Glucose DMEM or L15 media, the media being supplemented with serum and standard growth additives). Following incubation, growth media is removed and the cells are placed in growth serum-free media. Cells are incubated for 2-3 hours. The media is then removed and the cells are loaded with a calcium-sensitive fluorescent dye (Calcium-3, Molecular Devices Corp.) which is diluted in umami assay buffer (130 mM NaCl, 1.1 mMKH2PO4, 1.3 mM CaCl, 20 mM HEPES and 3 mMNaHPO4.7H2O). Cells are incubated in this media for 1 hour. Plates are loaded onto a high throughput fluorescent plate reader (Hamamatsu FDSS). Test compounds are diluted in umami assay buffer to the desired concentration and added to each well. Calcium flux is detected for 90 seconds. Activators (i.e. MSG) diluted in buffer as above are added to each well in final concentrations ranged between 10 uM and 100 mM and change in relative fluorescence is recorded for an additional 90 seconds.
3. Determination of Z′ and EC50 Values for Umami Cell-Based Assay
In order to test the effectiveness of the umami taste receptor response in these umami taste receptor-expressing cell lines, the established umami taste receptor agonist monosodium glutamate (MSG) is utilized as a test compound in the assay described above. MSG (Sigma, G5889) is added to test wells at a concentration of 33 mM, and control wells receive buffer alone. In the final assay conditions, as reported by calcium flux measurements which are measured by a fluorescence plate reader. (FLIPR3 operating system, Molecular Devices). In one several times repeated assay the cell line had a Z′ value of 0.8. See
In order to test the sensitivity of the umami taste receptor response in an umami taste receptor-expressing cell line of this invention, a dose response experiment is performed by adding increasing doses of MSG to cells and measuring the responses as described above. In one assay (
As mentioned above, MSG is a known ligand of the umami taste receptor. It has also been demonstrated that the nucleotide inosine monophosphate (IMP, Sigma) can serve as a potentiator of umami taste receptor signaling when presented together with MSG. Using the assay protocol described above, a matrix of increasing MSG and increasing IMP concentrations are applied to the cell lines and responses are generated.
Similar to MSG, sodium cyclamate, an artificial sweetener, can serve as an activator of the umami taste receptor as it interacts with the subunit common to both sweet and umami receptors. Using the assay protocol described above, a matrix of increasing cyclamate (Sigma) concentrations are applied and responses are generated.
293T cells were cotransfected with two separate plasmids, one encoding a human TAS2R bitter receptor (one of SEQ ID NOS: 77-101), and the other encoding a mouse Gα15 signaling protein (SEQ ID NO: 102). As will be appreciated by those of skill in the art, any reagent that is suitable for use with a chosen host cell may be used to introduce a nucleic acid, e.g., a plasmid, oligonucleotide, or labeled oligonucleotide, into a host cell with proper optimization. Examples of reagents that may be used to introduce nucleic acids into host cells include, but are not limited to, Lipofectamine, Lipofectamine 2000, Oligofectamine, TFX reagents, Fugene 6, DOTAP/DOPE, Metafectine, and Fecturin. Although drug selection is optional in the methods of this invention, we included one mammalian drug resistance marker per plasmid. Plasmids used a CMV promoter for expression of the bitter receptor gene or the Gα15 gene. An untranslated sequence encoding a tag for detection by a signaling probe was also present in each vector, along with the sequence encoding the drug resistance marker, so that the tag was transcribed along with the protein the vector expressed, i.e., bitter receptor or Gα15. The target sequences utilized were Target Sequence 1 (SEQ ID NO: 46), and Target Sequence 2 (SEQ ID NO: 47). In these examples, the TAS2R gene-containing vectors contained Target Sequence 1, and the Gα15 gene-containing vector contained Target Sequence 2.
Transfected cells were grown for 2 days in Dulbecco's Modified Eagle Medium (DMEM) containing fetal bovine serum (FBS), followed by two weeks in antibiotic-containing DMEM-FBS. The antibiotic containing period had antibiotics added to the media as follows: Puromycin (0.15 ug/ml) and Hygromycin (100 ug/ml).
Following enrichment on antibiotic, and prior to introduction of fluorogenic signaling probes, cells were passaged 8 (p5-p13) more times in the absence of antibiotic selection to allow time for expression that is not stable over the selected period of time to subside.
Cells were harvested and transfected with signaling probes (SEQ ID NOS: 48 and 49). As will be appreciated by those of skill in the art, any reagent that is suitable for use with a chosen host cell may be used to introduce a nucleic acid, e.g. plasmid, oligonucleotide, labeled oligonucleotide, into a host cell with proper optimization. Examples of reagents that may be used to introduce nucleic acids into host cells include but are not limited to: Lipofectamine, Lipofectamine 2000, Oligofectamine, TFX reagents, Fugene 6, DOTAP/DOPE, Metafectine, or Fecturin.
A similar probe using a Quasar Dye (BioSearch) with spectral properties similar to Cy5 was used in certain experiments. Note also that 5-MedC and 2-aminodA mixmer probes rather than DNA probes were used in some instances.
A scrambled nontargeting fam probe was used as a delivery control (not shown).
The signaling probes were supplied as 1000 stocks.
Note that BHQ3 could be substituted with BHQ1 or a gold particle in Probe 1 or Probe 2.
BHQ3 could be substituted with BHQ2 or a gold particle in Probe 1 or Probe 2.
The cells were dissociated and collected for analysis and sorting using a fluorescence activated cell sorter (Beckman Coulter, Miami, Fla.). Standard analytical methods were used to gate cells fluorescing above background and to isolate individual cells falling within the gate into barcoded 96-well plates. The gating hierarchy was as follows: coincidence gate>singlets gate>live gate>sort gate. With this gating strategy, the top 0.1-1.3% of double-positive cells were marked for sorting into barcoding 96-well plates.
Step 6—Additional Cycles of Steps 1-5 and/or 3-5
The experiments were staged with very tightly timed logistics. As part of this campaign, there were two full cycles of steps 3-5 performed in order to have redundant sorts completed and additional clones obtained.
The plates were transferred to a Hamilton Microlabstar automated liquid handler. Cells were incubated for up to 20 days in a 1:1 mix of 2-3 day conditioned growth medium: fresh growth medium (DMEM/10% FBS) supplemented with 100 units penicillin/ml plus 0.1 mg/ml streptomycin. Plates were imaged between 7 and 20 days postsort to determine confluency of wells (Genetix). Each plate was focused for reliable image acquisition across the plate. Reported confluencies of greater than 70% were not relied upon. Confluency measurements were obtained 3 times over the time specified above and used to calculate growth rates.
Cells were binned (independently grouped and plated as a cohort) according to growth rate approximately 20 days postsort. Bins were independently collected and plated on individual 96 well plates for downstream handling, and there could be more than one target plate per specific bin. Bins were calculated by considering the spread of growth rates and bracketing a range covering a high percentage, at least about 90% (as an estimate) of the total number of populations of cells. 5 growth bins were used with average partitions of 1.2-3.5 days over the bins across the different bitter receptor cell lines. Therefore each bin corresponded to a growth rate or population doubling time difference of approximately 11 hours.
Cells can have doubling times from less than 1 day to more than 2 weeks—in order to process the most diverse clones that at the same time can be reasonably binned according to growth rate, we typically prefer to do 3-9 bins with a 0.25 to 0.7 day doubling time per bin. One skilled in the art would understand how to adjust the tightness of the bins and number of bins according to the particular situation, and tightness and number of bins could be further adjusted if cells were synchronized for their cell cycle
The plates were incubated under standard and fixed conditions (humidified 37, 5% CO2/95% air) in DMEM media/10% FBS without antibiotics. The plates of cells were split to produce 4 sets (the set consists of all plates with all growth bins—these steps ensured there were 4 replicates of the initial set) of target plates. Up to 3 target plate sets were committed for cryopreservation (see below), and the remaining set was scaled and further replica plated for passage and for functional assay experiments. Distinct and independent tissue culture reagents, incubators, personnel and carbon dioxide sources were used for each set of plates. Quality control steps were taken to ensure the proper production and quality of all tissue culture reagents: each component added to each bottle of media prepared for use was added by one designated person in one designated hood with only that reagent in the hood while a second designated person monitored to avoid mistakes. Conditions for liquid handling were set to eliminate cross contamination across wells. Fresh tips were used for all steps or stringent tip washing protocols were used. Liquid handling conditions were set for accurate volume transfer, efficient cell manipulation, washing cycles, pipetting speeds and locations, number of pipetting cycles for cell dispersal, and relative position of tip to plate.
Three sets of plates were frozen at −70 to −80° C. Plates in each set were first allowed to attain confluencies of 70 to 100%. Media was aspirated and 90% FBS and 10% DMSO was added. The plates were sealed with Parafilm and then individually surrounded by 1 to 5 cm of foam and placed into a −80° C. freezer.
The remaining set of plates were maintained as described above in step 9. All cell splitting was performed using liquid handling steps, including media removal, cell washing, trypsin addition and incubation, quenching and cell dispersal steps.
Due to the scale of the receptor cell panel, no normalization was used—instead the growth re-arrayed plates were quickly tested for functionality as the first priority (between 3-5 passages post-rearray), and a subset population of responders for each of the 25 bitter receptors was identified.
Clones were screened between 3.5 and 6 weeks post-sort with top clones being retested functionally and identified 5 to 6 weeks post-sort. The cells were maintained for up to 6 weeks to allow for their in vitro evolution under these conditions. During this time, we observed size, morphology, fragility, response to trypsinization or dissociation, roundness/average circularity post-dissociation, percentage viability, tendency towards microconfluency, or other aspects of cell maintenance such as adherence to culture plate surfaces.
Populations of cells were tested using functional criteria. Calcium mobilization dye kits (Calcium 3, Molecular Devices/MDS) were used according to manufacturer's instructions. Cells were tested at multiple different densities in 96 or 384-well plates and responses were analyzed. A variety of time points post plating were used, for instance 12-48 hours post plating. Different densities of plating were also tested for assay response differences.
The functional responses from experiments performed at low and higher passage numbers were compared to identify cells with the most consistent responses over defined periods of time, ranging from 6 to 11 weeks postsort. Other characteristics of the cells that changed over time were also noted, for example, time for cells to reattach post-dissociation.
Populations of cells meeting functional and other criteria were further evaluated to determine those most amenable to production of viable, stable and functional cell lines. Selected populations of cells were expanded in larger tissue culture vessels and the characterization steps described above were continued or repeated under these conditions. At this point, additional standardization steps were introduced for consistent and reliable passages. These included different plating cell densities, plate coatings, time of passage, culture dish size/format and coating, fluidics optimization, cell dissociation optimization (e.g., dissociation in the presence of Cell Dissociation Buffer (Invitrogen) vs trypsin), volume of dissociation reagent used, and length of time of dissociation), as well as washing steps. Glutamine concentrations were dose ranged for the culture medium. Also, viability of cells at each passage was determined. Manual intervention was increased and cells were more closely observed and monitored. This information was used to help identify and select final cell lines that retained the desired properties Final cell lines and back-up cell lines were selected that showed consistent growth, consistent (i.e. unchanging morphology) appropriate adherence, as well as functional response.
The low passage frozen plates (see above) corresponding to the final cell line and back-up cell lines were thawed at 37° C., washed two times with DMEM/10% FBS and incubated in humidified 37° C./5% CO2 conditions. The cells were then expanded for a period of 2-3 weeks. Cell banks for each final and back-up cell line consisting of 25-50 vials were established. Cells were cryopreserved in 50% DMEM/10% FBS, 40% FBS, and 10% DMSO, resulting from further optimization experiments.
At least one vial from the cell bank including the frozen stocks of the thawed cell lines, expanded and re-frozen, was thawed and expanded in culture. The resulting cells were tested to confirm that they met the same characteristics for which they were originally selected.
In order to identify and measure the ligand-induced responsiveness of bitter receptor-expressing HEK293 cells, receptor activation was monitored by measuring receptor-triggered alterations in intracellular calcium levels. Cells were either grown overnight in black-clear bottom plates in standard growth media or added to the black-clear bottom plates as a suspension in assay buffer (10 mM HEPES, 130 mM NaCl, 2 mM CaCl2, 5 mM KCl, 1.2 mM MgCl2, 10 mM glucose, pH 7.4). The cells were incubated for 1 hr at room temperature with the no-wash calcium-sensitive fluorescent dye Calcium-3 (Molecular Devices Corp.) in buffer. The cell plates and test compounds (0.01 μM-100 mM) were placed in the high throughput fluorescent plate reader (Hamamatsu FDSS) which collected images of the plate fluorescence before, during and after the instrument added test compounds to the cells. Software (Hamamatsu FDSS) analysis of images reported the change in relative fluorescence for each well in the cell plate.
A variety of compounds and extracts, many of which were reported as bitter-tasting, were assayed across the 25 bitter receptor cell lines as well as control cells in order to determine activity and to deorphan.
Transient transfection of native and tagged receptors followed by assay allowed the analysis of the functional difference between native and tagged receptors. As an example, functional assays were performed in human embryonic kidney (HEK) 293T cells 48 hours after transient transfection of the mouse Gα15 protein and either a native T2R16 bitter receptor or the same receptor carrying an N-terminal tag from the mouse rhodopsin gene. The cells were incubated for 1 hr at room temperature with the no-wash calcium-sensitive fluorescent dye Calcium-3 (Molecular Devices Corp.) in buffer (10 mM HEPES, 130 mM NaCl, 2 mM CaCl2, 5 mM KCL, 1.2 mM MgCl2, 10 mM glucose, pH 7.4). The assay response for bitter receptor activity was measured in a Hamamatsu FDSS fluorescent plate reader which collected images of the plate fluorescence before, during and after the instrument added a range of concentrations (0.01 uM-100 uM) of a bitter extract. The FDDS software analyzed images and reported the change in relative fluorescence for each well in the cell plate.
The results were plotted in
The success rate (number of clones expressing functionally active receptors over all clones isolated) is a critical parameter in determining the efficiency of generating stable cell lines. We performed functional assays of clones we isolated using the method described in Example 26, and found that greater than 80% of the clones isolated were functionally active.
As an example, individual clonal cell lines isolated for expression of specific human bitter receptor T2R41 were cultured in individual wells of a 96-well plate, and the presence of viable cells in each well was confirmed by initial calcium-sensitive dye load measurement. Wells with no or low dye loading were considered blank and indicated in black in
Homogeneity is another important parameter in generating stable cell lines. We used functional real-time imaging of bitter receptor response to determine the homogeneity of cells isolated using the method described in Example 26, as compared to those found by drug selection only. Cells expressing a bitter receptor and G protein were plated onto 96-well poly-D-lysine coated black-clear plates (Becton Dickinson) 24 hours prior to the assay. Cells were loaded with a calcium-sensitive fluorescent dye diluted in assay buffer (130 NaCl, 2 mM CaCl, 1.2 mM MgCl, 5 mM KCl, 10 mM glucose, 10 mM HEPES at pH 7.4). Cells were incubated for 1 hour and then a known activator of the bitter receptor was used at an appropriate concentration. Calcium flux responses of cells were recorded using an AxioVert 200 EPI-fluorescent microscope (Zeiss) with appropriate filters for 3 minutes. Data were analyzed using MetaMorph6.3r7 software (Molecular Devices).
Homogeneous bitter receptor responses were detected in an isolated clonal cell line (
Because bitter receptors are G protein coupled receptors (GPCRs), in order to make meaningful comparison of bitter responses between different bitter receptors in the presence of various compounds, it is important to determine that the G protein coupling functions uniformly in different cell lines. The relative responses of the different cell lines across a range of concentrations of a G protein coupling agonist should be uniform. To confirm this, we tested the uniformity in Gα15-mediated receptor responses of all 25 cell lines expressing the different human bitter receptors and the mouse Gα15 protein in dose response curve experiments with varying concentrations of isoproterenol, an agonist of the β-adrenergic receptor endogenously expressed in the cells. This endogenous receptor, when stimulated, can couple to the expressed Gα15 and evoke a change in intracellular free calcium. Percent response was plotted as a function of isoproterenol concentration, and the results were curve-fitted to calculate an EC50 value (concentration of half-maximal receptor activation) (see
Cell lines stably expressing native human bitter receptor genes, generated using the method of the invention (i.e., Example 26), were tested in functional cell-based receptor studies to detect their activation by a collection of chemically diverse compounds. Substances 1-12 eliciting dose-dependent activation of the corresponding human bitter receptor are listed alongside the receptor which they were found to activate in
The activity of a library of compounds against each of the 25 human bitter receptor cell lines was tested. Data were generated in functional cell-based assays for receptor activity upon addition of the compounds, and expressed as percent activity above the basal activity of the receptor (i.e., receptor activity upon addition of buffer alone). Activity of each compound at each receptor was then coded to highlight compounds with low (<100% above basal activity; white), medium (101-500% above basal activity; light gray), high (501-1000% above basal activity; dark gray), or very high (>1001% above basal activity, black) activity at each receptor (
To test the ability of the bitter receptor-expressing cell-based assays to identify analogues of compounds with similar functional activities, twenty-one structural analogues of a known bitter blocking compound are tested for their ability to inhibit an agonist-induced receptor activity of a bitter receptor. The structures of analogues that inhibit the bitter receptor's activity induced by the agonist are compared. Thus, the bitter receptor-expressing cell lines may aid discovery of potent bitter receptor antagonists.
Functional assays following transient transfections described in Example 28 showed that native and tagged human bitter receptors had distinct functional activity. This was also confirmed using cell lines expressing native bitter receptors as compared to cell lines expressing tagged bitter receptors. Briefly, bitter receptor assignments for saccharin were made using functional cell-based receptor assays measuring calcium mobilization with stable cell lines expressing native bitter receptors. Bitter receptor assignments for saccharin were also made as described in Pronin et al., “Identification of Ligands for Two Human Bitter T2R Receptors,” Chem. Senses, 29:583-593 (2004), using insect-produced recombinant receptor proteins carrying N-terminal mouse rhodopsin tag sequences, in a membrane fraction-based cell free assay for GTP hydrolysis. The different assignments are shown in
Transfection
HEK293T (ATCC CRL-11268) were co-transfected with three separate plasmids, one encoding T1R2 (SEQ ID NO: 31), one encoding T1R3 (SEQ ID NO: 32) and the other encoding a signaling molecule (mouse Gα15, SEQ ID NO: 33). Although drug selection is optional in the methods of this invention, we included one drug resistance marker per plasmid. The sequences were under the control of the CMV promoter. An untranslated sequence encoding a tag for detection by a signaling probe was also present along with a sequence encoding a drug resistance marker. The target sequences utilized were Target Sequence 1 (SEQ ID NO: 28; using the tag sequence of SEQ ID NO:123), Target Sequence 2 (SEQ ID NO: 29; using the tag sequence of SEQ ID NO:124) and Target Sequence 3 (SEQ ID NO: 30; using the tag sequence of SEQ ID NO:125). In these examples, the T1R2 gene vector contained Target Sequence 3, the T1R3 gene vector contained Target Sequence 1 and the Gα15 gene vector contained the Target Sequence 2. The cells were conventionally selected in media containing the drug for 10-14 days.
Exposure of Cells to Fluorogenic Probes
Selected cells were harvested and transfected with signaling probes (SEQ ID NO:38-40). Signaling Probe 1 binds Target Sequence 1, Signaling Probe 2 binds Target Sequence 2 and Signaling Probe 3 binds Target Sequence 3. The cells were then dissociated and collected for analysis and sorted using a fluorescence activated cell sorter (Beckman Coulter, Miami, Fla.).
As will be appreciated by those of skill in the art, any reagent that is suitable for use with a chosen host cell may be used to introduce a nucleic acid, e.g. plasmid, oligonucleotide, labeled oligonucleotide, into a host cell with proper optimization. Examples of reagents that may be used to introduce nucleic acids into host cells include but are not limited to: Lipofectamine, Lipofectamine 2000, Oligofectamine, TFX reagents, Fugene 6, DOTAP/DOPE, Metafectine, or Fecturin.
CATCTGGGCCCGGAAAGCCTTTTTCTCTGTGATCCGGTACAGTCCTTCTG
GTCGTTCTGCGACATCTGGGCCCGGAAAGCGTTTAACTGATGGATGGAAC
Other target sequences and signaling probes could be used (see, e.g., as described in International Patent Application Publication No. WO2005/079462 published on Sep. 1, 2005 (Application No. PCT/US05/005080). For example, BHQ3 could be substituted with BHQ1 or a gold particle in Probe 1 or Probe 2. Note that BHQ1 could be substituted with BHQ2 or Dabcyl in Probe 3. A similar probe using a Quasar Dye (BioSearch) with spectral properties similar to Cy5 could be used in certain experiments. Note also that 5-MedC and 2-aminodA mixmer probes rather than DNA probes could be used in some instances.
Isolation of Positive Cells
Standard analytical methods were used to gate cells fluorescing above background and to isolate cells falling within that defined gate directly into 96-well plates. Cell sorting was operated such that a single cell was deposited per well. After selection, the cells were expanded in media lacking drug.
Functional Transformation
We maintained the sweet taste receptor cells (selected and expanded as above) using both aliquots of the same cells and different cells in various growth conditions including, for example, low-glucose DMEM media or in glucose-free Leibovitz L-15 media with 10% serum or serum-free. Some cells were maintained in media containing various concentrations of other sugars such as galactose. We then characterized cells of the sweet taste receptor cell lines maintained under multiple conditions for their ability to respond appropriately to sweet ligands and not respond to other stimuli (MSG).
Growth in the various media conditions, without wishing to be bound by theory, may functionally transform the cells, e.g. due to changes in gene expression levels, genomic organization and functional expression of receptors at the cell surface. Parameters in the various media that were evaluated and shown to affect a cell's functional assay response include serum concentration (i.e. low serum concentrations and serum deprivation), sugar deprivation and assay plate coating (for example, poly D lysine and laminin). These results demonstrated that characteristics of the cells of the sweet taste receptor cell lines may be different when the cells are maintained in different media conditions. They also show that different cells selected by the fluorogenic probes may have different characteristics under the same growth conditions. One example of our characterization of cells selected by the fluorogenic probes is shown in
1. Confirmation and Quantification of Gene Expression.
Using qRT-PCR, we determined the relative amounts (RNA) of each of the sweet taste receptor subunits being expressed in the above cells (“Final”). Total RNA was purified from 1-3×106 mammalian cells using a commercially available RNA purification kit (RNeasy Mini Kit, Qiagen). The RNA extract was then treated using a rigorous DNase treatment protocol (TURBO DNA-free Kit; Ambion). First strand cDNA synthesis was performed using a Reverse Transcriptase Kit (SuperScript III, Invitrogen) in 20 uL reaction volume with 1 uG DNA-free total RNA and 250 nG Random Primers (Invitrogen). Negative controls for this reaction included samples in which reverse transcriptase or RNA were left out during the cDNA synthesis step. cDNA and PCR product synthesis was carried out in a thermal cycler (Mastercycler Eppendorf) at the following conditions: 5 min at 25° C., 60 min at 50° C.; reaction termination was conducted for 15 min at 70° C.
For analysis of gene expression (RNA) probes against T1R2, T1R3 and mouse Gα15 cDNA (MGB TaqMan probes, Applied Biosystems) were used. For sample normalization control, the GAPDH, Pre-Developed TaqMaN Assay Reagents, Applied Biosystems was utilized. Reactions, including negative controls and positive controls (plasmid DNA), were set up in triplicates with 40 nG of cDNA in 50 uL reaction volume. The relative amounts of each of the sweet taste receptor subunits being expressed (RNA) were determined.
Standard single endpoint RT-PCR procedures were used to assess T1R2, T1R3 and Gα15 gene expression (RNA) in one and nine month cultures of the sweet taste receptor cells generated according to the protocol described above (“Final”). Cells were grown in a 24-well plate format to 80% confluency and harvested and RNA was isolated using a commercially available RNA preparation kit (RNAqueous kit, Ambion). A range of 5 pg to 5 ug of purified total RNA was used to perform reverse transcription, according to the protocol of a commercial first strand cDNA synthesis kit (Superscript III kit, Invitrogen), with oligo (dT) 12,18 primers. Following first strand synthesis, oligo sets specific for the subunits of the sweet taste receptor nucleic acid (T1R2, T1R3), as well as for the mouse Gα15 nucleic acid, were independently assembled in PCR reaction mixtures (HotStart Taq). Following a 45 cycle PCR, amplicon samples were further analyzed by agarose gel electrophoresis.
The results from these single-endpoint RT-PCR experiments are illustrated in
2. Cell-Based Assay for Modulators
Forty-eight hours prior to assay, cells of this invention are seeded in growth media (Low Glucose DMEM or L15 media, the media being supplemented with serum and standard growth additives) at a high density in 10 cm dishes. Cells are dissociated from the culture matrix and are seeded 24 hours prior to assay in 96 well plates. Media removal is then followed by the addition of a calcium-sensitive fluorescent dye (Calcium-3, Molecular Devices Corp.) which is diluted in sweet assay buffer (130 mM NaCl, 1.1 mMKH2PO4, 1.3 mM CaCl, 20 mM HEPES and 3 mMNaHPO4.7H2O). Cells are incubated in this media for 1 hour. Plates are then loaded on a high throughput plate reader (Hamamatsu FDSS). Test compounds (i.e. fructose (Sigma), sucrose (Sigma), glucose (Sigma), Acesulfame K (Fluka), Na-saccharin (Sigma), Na-cyclamate (Aldrich), steviva (Steviva Brands Inc.), mogroside (Slim Sweet, Trimedica), and sorbitol (Sigma)) are diluted in sweet assay buffer and added to each well. Calcium flux is detected for 90 seconds. Activators are diluted in buffer as above are added to each well in final concentrations ranged between 10 uM and 100 mM and change in relative fluorescence is recorded for an additional 90 seconds.
3. Determination of Z′ and EC50 Values for Sweet Cell-Based Assay
In order to test the effectiveness of the sweet taste receptor response in these sweet taste receptor-expressing cells, the established sweet taste receptor agonist fructose is utilized as a test compound in the assay described above. Fructose is added to test wells (odd columns) at a concentration of 75 mM, and control wells (even columns) receive buffer alone. In the final assay conditions, as reported by calcium flux measurements which are measured by a fluorescence plate reader (FLIPR3 operating system, Molecular Devices). In one several times repeated assay the cells had a Z′ value of 0.8. See
In order to test the sensitivity of the sweet taste receptor response in a sweet taste receptor-expressing line of this invention, a series of dose response experiments were performed by adding increasing doses of various sweet receptor agonists to cells and measuring the responses as described above. In one assay (
In this assay, it was also found that the calcium flux response curve was different when the sweet taste receptor-expressing cells were exposed to different sweeteners. As illustrated in
Design of Signaling Probes
Signaling probes directed to sequences corresponding to the T1R2 or T1R3 genomic loci were designed. The signaling probes were directed to coding exons, non-coding introns or non-coding untranslated sequences as described in Table 23.
Signaling probes S21, S22, S23, R2-3U1 and R2-I1 comprise a Cy5.5 fluorescent label at the 5′ terminus and a BHQ2 quencher at the 3′ terminus. Signaling probes S31, S32, S33, R3-3U1 and R3-I31 comprise a 6-FAM fluorophore at the 5′ terminus and a BHQ1 at the 3′ terminus. Signaling probes could also comprise other fluorophores or quenchers. Signaling probes were synthesized, conjugated to their respective labels and purified at Genelink (Hawthorne, N.Y.).
Exposure of Cells to Fluorogenic Probes
Either HEK 293T (ATCC CRL-11268), HuTu (ATCC HTB-40) or H716 (ATCC CCL-251) cells were transfected with one of the following combinations of signaling probes in separate experiments: a) S21 and S31, b) S21 and S32, c) S21 and S33, d) S22 and S31, e) S22 and S32, f) S22 and S33, g) S23 and S31, h) S23 and S32, i) S23 and S33, j) R2-3U1 and R3-3U1, k) R2-3U1 and R3-I31, l) R2-I1 and R3-3U1 and m) R2-I1 and R3-I31. HEK 293T cells were maintained in Dulbecco's Modified Eagle media (Sigma #D5796) containing 10% Fetal Bovine Serum (FBS) (Sigma #SAC1203C), 2 mM L-Glutamine (Sigma G7513) and 10 mM HEPES (Sigma H0887), HuTu cells were maintained in Eagle's Minimal Essential Media (Sigma #D5650) containing 10% FBS (Sigma #2442), 2 mM L-Glutamine (Sigma #G7513) and 1 mM Sodium Pyruvate (Sigma #S8636) and H716 cells were maintained in Roswell Park Memorial Institute 1640 (Gibco #11875-093) containing 10% FBS (Sigma #F2442). As will be appreciated by those of skill in the art, any reagent suitable for use with a chosen host cell may be used to introduce a nucleic acid (e.g. plasmid, oligonucleotide, labeled oligonucleotide) into a host cell with proper optimization. Examples of reagents that may be used to introduce nucleic acids into host cells include but are not limited to: Lipofectamine, Lipofectamine 2000, Oligofectamine, TFX reagents, Fugene 6, DOTAP/DOPE, Metafectine, or Fecturin.
In different experiments, HEK 293T cells, HuTu cells and H716 cells either were treated with or without a mutagenic treatment (e.g. UV light) to induce random mutagenesis or gene-activation prior to introduction of fluorogenic probes as described below. Cells were resuspended in serum free media at 1.25×106 cells per milliliter and exposed to UV radiation to deliver 1 Joule/m2/s from a germicidal bulb (Sylvania) emitting mainly 254 nm wavelengths for 15 minutes. Other mutagenic treatments also could be used (e.g., chemical mutagenesis by exposure to mutagens such as ethyl methane sulfonate (EMS)). Cells could be incubated with a final concentration (e.g., 200 ug/ml) of ethyl methanesulfonate (EMS; Sigma) and incubated prior to their transfer to media lacking EMS.
The cells were then exposed to signaling probes, dissociated and collected for testing using a fluorescence activated cell sorter (Beckman Coulter, Miami, Fla.).
Isolation of Positive Cells
Standard analytical methods according to standard practice in the field of flow cytometry and familiar to one skilled in the art were used to gate, or select, positive fluorescing cells. Fluorescence activated cell sorting was used to isolate positive fluorescing cells falling within the desired gate, or having the desired fluorescence, directly into 96-well plates. Cell sorting parameters were set for the isolation of only one cell per well. Transfected cells associated with different absolute or relative fluorescence levels for at least one signaling probe were isolated by gating the top 1% of the cells with the highest signal intensity relative to the entire population.
In separate experiments, transfected cells associated with different absolute or relative fluorescence levels for at least one signaling probe were isolated by gating the top 0.1% of the cells with the highest signal intensity relative to the entire population.
Individual cells were isolated and maintained in media as described below. For each cell type, equal proportions of its respective conditioned and fresh media were combined for use. Conditioned media was prepared by culturing each cell type in its respective fresh media for two days, harvesting and then filtering the media. Individually isolated HEK 293T cells were isolated and maintained in Dulbecco's Modified Eagle media (Sigma #D5796) containing 10% FBS (Sigma #SAC1203C), 2 mM L-Glutamine (Sigma G7513), 10 mM HEPES (Sigma H0887) and a 1 to 50 dilution of penicillin/streptomycin solution (final concentration 100 units penicillin/100 μG streptomycin per mL) (Sigma #P4458). Individually isolated HuTu cells were isolated and maintained in Eagle's Minimal Essential Media (Sigma #D5650) containing 10% FBS (Sigma #2442), 2 mM L-Glutamine (Sigma #G7513), 1 mM Sodium Pyruvate (Sigma #S8636) and a 1 to 50 dilution of penicillin/streptomycin solution (final concentration 100 units penicillin/100 μG streptomycin per mL) (Sigma #P4458). Individually isolated H716 cells were isolated and maintained in Roswell Park Memorial Institute 1640 media (Gibco #11875-093) containing 10% FBS (Sigma #F2442) and a 1 to 50 dilution of penicillin/streptomycin solution (final concentration 100 units penicillin/100 μG streptomycin per mL) (Sigma #P4458).
Robotic cell culture methods were used to passage cells isolated and maintained in 96 well tissue culture plates. In particular, the MICROLAB STAR™ instrument was used to carry out a variety of automated cell culture tasks (e.g., removing media, replacing media, adding reagents, cell washing, removing wash solution, adding a dispersing agent, removing cells from a culture vessel, adding cells to a culture vessel and the like). Other cell culture methods, including manual methods, could also be used. Cells then were expanded into 10 cm tissue culture dishes and cultured using standard manual tissue culture techniques (e.g., removing media, washing cells, adding media).
Isolated cells were expanded in culture to give rise to populations of cells derived from an individually isolated cell. Individually isolated cells were expanded by culturing them in their respective media, as described below. HEK 293T cells were transferred for maintenance in Dulbecco's Modified Eagle media (Sigma #D5796) containing 10% FBS (Sigma #SAC1203C), 2 mM L-Glutamine (Sigma G7513) and 10 mM HEPES (Sigma H0887), HuTu cells were transferred for maintenance in Eagle's Minimal Essential Media (Sigma #D5650) containing 10% FBS (Sigma #2442), 2 mM L-Glutamine (Sigma #G7513) and 1 mM Sodium Pyruvate (Sigma #S8636). H716 cells were transferred for maintenance in Roswell Park Memorial Institute 1640 media (Gibco #11875-093) containing 10% FBS (Sigma #F2442).
Functional Testing
Populations of cells each resulting from the expansion of single isolated cells then were characterized for their ability to respond to a sweet ligand using functional cell-based assays. 15 mM fructose was used in these experiments. Depending on the cell type, different conditions were used as described below.
Forty-eight hours prior to assay, cells were seeded in growth media (L15 media (Sigma #L5520) supplemented with 10% serum (Sigma #SAC1203C), 4 mM L-Glutamine (Sigma G7513), 10 mM HEPES (Sigma H0887), and a 1 to 50 dilution of penicillin/streptomycin solution (final concentration 100 units penicillin/100 μG streptomycin per mL) (Sigma #P4458) at a high density, from 12 to 20 million cells, in 10 cm dishes. Cells were dissociated from the culture matrix and were seeded at 35,000 cells per well 24 hours prior to assay in 384 well plates. Media was removed after 18 to 24 hours. A calcium-sensitive fluorescent dye (Fluo-4, Invitrogen) diluted in sweet assay buffer (130 mM NaCl, 1.1 mMKH2PO4, 1.3 mM CaCl, 20 mM HEPES and 3 mMNaHPO4.7H2O) was added then to each well. Cells were incubated in this media for 1 hour. Plates then were loaded on a high throughput plate reader (Hamamatsu FDSS). Sweet assay buffer with DMSO was added to each well for a final concentration of 0.2% DMSO. Calcium flux or assay response was detected prior to, during and following addition of sweet assay buffer containing fructose to each well for a final concentration of 15 mM fructose. The assay can be optionally performed with a quencher of the calcium-sensitive fluorescent dye. Such Quenchers are well-known in the art and include, e.g., Dipicrylamine (DPA), Acid Violet 17 (AV17), Diazine Black (DB), HLB30818, trypan blue, Bromophenol Blue, HLB30701, HLB30702, HLB30703, Nitrazine Yellow, Nitro Red, DABCYL (Molecular Probes), QSY (Molecular Probes), Metal ion quenchers (e.g., Co2+, Ni2+, Cu2+), and Iodide ion.
Alternatively, cells were dissociated from the culture matrix and were seeded at cell densities from 2,500 to 20,000 per well for 24 or 48 hours prior to assay in Eagle's Minimal Essential Media (Sigma #D5650) containing 10% FBS (Sigma #2442), 2 mM L-Glutamine (Sigma #G7513) and 1 mM Sodium Pyruvate (Sigma #S8636) or a mixture of equal parts of this media and L-15 media (Sigma, L5520) in a 384 well plate. After 18 to 52 hours, the media was removed. A calcium-sensitive fluorescent dye (Fluo-4, Invitrogen) diluted in sweet assay buffer (130 mM NaCl, 1.1 mMKH2PO4, 1.3 mM CaCl, 20 mM HEPES and 3 mMNaHPO4.7H2O) was added then to each well. Cells were incubated in this media for 1 hour. Plates then were loaded on a high throughput plate reader (Hamamatsu FDSS). Sweet assay buffer with DMSO was added to each well for a final concentration of 0.2% DMSO. Calcium flux or assay response was detected prior to, during and following addition of sweet assay buffer containing fructose to each well for a final concentration of 15 mM fructose.
Alternatively, cells were pelleted and resuspended in calcium-sensitive fluorescent dye (Fluo-4, Invitrogen) diluted in sweet assay buffer (130 mM NaCl, 1.1 mMKH2PO4, 1.3 mM CaCl, 20 mM HEPES and 3 mMNaHPO4.7H2O). Cells were plated in 384 well plates and incubated in this media for 1 hour. Plates then were loaded on a high throughput plate reader (Hamamatsu FDSS). Sweet assay buffer with DMSO was added to each well for a final concentration of 0.2% DMSO. Calcium flux or assay response was detected prior to, during and following addition of sweet assay buffer containing fructose to each well for a final concentration of 15 mM fructose.
Other sweet ligands including high-intensity natural and artificial sweeteners and natural and artificial sweeteners could also be used, for examples sucrose (Sigma), glucose (Sigma), Acesulfame K (Fluka), Na-saccharin (Sigma), Na-cyclamate (Aldrich), steviva (Steviva Brands Inc.), mogroside (Slim Sweet, Trimedica), and sorbitol (Sigma)). In addition, other taste ligands including bitter, umami, fat, cool, hot and sour ligands or tastants, as well as compounds with no known or intrinsic taste could be used to determine selectivity and specificity of the sweet response. In addition, any of the tastants or ligands could be tested in the presence of additional compounds including enhancers or blockers, for instance the sweet enhancer Rebaudioside-C RP44 (RedPoint Bio) and the sucralose enhancer S2383 (Senomyx), and the Sucrose Enhancer S5742 (Senomyx).
In addition, other media and incubation steps could be used and other plate formats, for instance 96 well plates and 1536 well plates could be used.
Numerous cell populations cultured from individually isolated cells and found to express, naturally and/or by gene-activation, at least one subunit of the sweet taste receptor were identified as having a response to fructose by monitoring the response or activation kinetics of the cells in the functional fluorescent calcium flux reporter assay. See,
High Throughput Screening
Sweet agonists and/or modulators can be identified by using high throughput screening (HTS) to test the effects of compounds on cells plated according to the above methods. Sweet assay buffer is added to each well with, or without, one or more components or compounds of a natural or synthetic compound library, or extracts or extract fractions. DMSO or other organic solvents such as ethanol also are included to assist in compound or extract solubilization for a final concentration of less than 5% DMSO (e.g., instance 0.2%). Calcium flux is detected for a period of time (e.g., 90 seconds). Fructose, or another sweet ligand, diluted in sweet assay buffer is then added to each well for a final activating concentration (e.g., 15 mM). Change in relative fluorescence is recorded for an additional period of time (e.g., 90 seconds). A number of control compounds also will be tested.
This testing is repeated until part or all of a compound library is screened. The data is analyzed to identify active compounds. Agonists and modulators including blockers, potentiators, enhancers or allosteric modulators are identified using this or other assay protocols. Testing of compounds using different sweet ligands are used to identify compounds that modulate the response of the sweet receptor to just one, all or a subset of sweet ligands, for instance compounds that are selective or pan-active. This is done by independent high throughput screening of the same compounds or compound libraries but using one or more different sweet ligands in each screen.
By examining temporal kinetics of the response curve (e.g., rate of decay or magnitude or response), modulating compounds with other qualitative and quantitative effects are identified.
Taste Testing
Compounds identified using the sweet cell based assay are tested in human sensory tests according to standard practice in the field and familiar to one skilled in the art. Compounds are tested for their intrinsic taste characteristics (e.g. sweet, bitter, umami, salty, sour, cool or hot tastes and off-tastes) as well as other qualities or properties that can be perceived such as mouthfeel, numbing, pain, irritation and tingle. Testing is performed in one or more different formats or matrices including liquids, semi-solids, solids, powders, tablets, gels, gums, sprays, dissolvable strips, food or beverage product formulation. Samples with and without compound are evaluated to detect the sensory properties of the compounds. Different doses of the compounds may be tested. In certain experiments, compounds are tested in samples that additionally comprise other compounds or ingredients having a taste and the change, alteration, enhancement, potentiation or inhibition of the perception of such taste is assessed. The compound may be provided in the presence of an agent designed to solubilize it, including an alcohol such as ethanol, DMSO or other solvent. The samples may be heated, chilled or tested at room temperature. Compounds also are tested for their ability to enhance or block sweet or other tastes. Sensory testing is performed with or without nose-clips to identify any odor-related effects. Taste testing is performed using the “sip and spit” mode where low concentrations of compounds are used to limit human exposure. Compounds are tasted to determine their effect on the perception of one or more sweet ligands and sweeteners. Human or animal subjects being exposed to or evaluating the compounds may be studied using functional brain imaging or other imaging tests (e.g., magnetic resonance imaging) to correlate patterns of activity in vivo with a compound.
293T cells were cotransfected with two separate plasmids, one encoding a human odorant receptor (one of SEQ ID NOS: 134-135), and the other encoding a human Gα15 signaling protein (SEQ ID NO: 133). As will be appreciated by those of skill in the art, any reagent that is suitable for use with a chosen host cell may be used to introduce a nucleic acid, e.g., a plasmid, oligonucleotide, or labeled oligonucleotide, into a host cell with proper optimization. Examples of reagents that may be used to introduce nucleic acids into host cells include, but are not limited to, Lipofectamine, Lipofectamine 2000, Oligofectamine, TFX reagents, Fugene 6, DOTAP/DOPE, Metafectine, and Fecturin. Although drug selection is optional in the methods described herein, we included one mammalian drug resistance marker per plasmid. The plasmids used herein contain a CMV promoter for expression of the odorant receptor gene or the Gα15 gene. An untranslated sequence encoding a tag, which contains a target sequence, for detection by a signaling probe was also present in each plasmid, such that the tag was co-transcribed and fused with the odorant receptor or Gα15 transcript. A tag contains a target sequence capable of hybridizing to a signaling probe. The target sequences utilized were Target Sequence 1 (SEQ ID NO: 129), and Target Sequence 2 (SEQ ID NO: 130), and the tag sequences utilized are Tag Sequence 1 (SEQ ID NO: 136) and Tag Sequence 2 (SEQ ID NO: 137). In these examples, the odorant gene-encoding plasmid contains Target Sequence 1, and the Gα15 gene-encoding plasmid contains Target Sequence 2.
Transfected cells were grown for 1-4 days in Dulbecco's Modified Eagle Medium (DMEM) containing fetal bovine serum (FBS), followed by two weeks in antibiotic-containing DMEM-FBS. The antibiotic containing period had antibiotics added to the media as follows: Puromycin (0.3 ug/ml) and Hygromycin (110 ug/ml), Puromycin (0.15 ug/ml) and Hygromycin (75 ug/ml), and Puromycin (0.05 ug/ml) and Hygromycin (18 ug/ml).
Following enrichment by antibiotic selection, and prior to introduction of fluorogenic signaling probes, cells were passaged 3 to 15 (p3-p15) more times in the absence of antibiotic selection to allow time for any unstable expression to subside.
Cells were harvested and transfected with signaling probes (SEQ ID NOS: 131 and 132). As will be appreciated by those of skill in the art, any reagent that is suitable for use with a chosen host cell may be used to introduce a nucleic acid, e.g. plasmid, oligonucleotide, labeled oligonucleotide, into a host cell with proper optimization. Examples of reagents that may be used to introduce nucleic acids into host cells include but are not limited to: Lipofectamine, Lipofectamine 2000, Oligofectamine, TFX reagents, Fugene 6, DOTAP/DOPE, Metafectine, or Fecturin.
CATCTGGGCCCGGAAAGCCTTTTTCTCTGTGATCCGGTACAGTCCTTCTG
GTCGTTCTGCGACATCTGGGCCCGGAAAGCGTTTAACTGATGGATGGAAC
The signaling probes were supplied as 100 μM stocks.
Note also that 5-MedC and 2-aminodA mixmer probes rather than DNA probes were used in some instances.
A scrambled nontargeting 6-Fam probe was used as a delivery control (not shown) in some experiments.
The cells were dissociated and collected for analysis and sorting using a fluorescence activated cell sorter (Beckman Coulter, Miami, Fla.). Standard analytical methods were used to gate cells fluorescing above background and to isolate individual cells falling within the gate into barcoded 96-well plates. The gating hierarchy was as follows: coincidence gate>singlets gate>live gate>sort gate. With this gating strategy, the top 0.1-2% of double-positive cells were marked for sorting into barcoding 96-well plates.
Step 6—Additional Cycles of Steps 2-5 and/or 3-5
The experiments were staged with very tightly timed logistics. As part of this protocol, there were two full cycles of steps 2-5 or 3-5 performed in order to have redundant sorts completed and additional clones obtained.
The plates were transferred to a Hamilton Microlabstar automated liquid handler. Cells were incubated for up to 20 days in a 1:1 mix of 2-3 day conditioned growth medium: fresh growth medium (DMEM/10% FBS) supplemented with 100 units penicillin/ml plus 0.1 mg/ml streptomycin. Plates were imaged between 7 and 30 days postsort to determine confluency of wells (Genetix). Each plate was focused for reliable image acquisition across the plate. Reported confluencies of greater than 70% were not relied upon. Confluency measurements were obtained 3 times over the time specified above and used to calculate growth rates.
Cells were binned (independently grouped and plated as a cohort) according to growth rate approximately 20 to 30 days postsort. Bins were independently collected and plated on individual 96 well plates for downstream handling, and there could be more than one target plate per specific bin. Bins were calculated by considering the spread of growth rates and bracketing a range covering a high percentage, at least about 30 to 90% (as an estimate) of the total number of populations of cells. 9 growth bins were used with average partitions of approximately 15 to 40 hours over the bins across the different odorant receptor cell lines. Therefore each bin corresponded to a growth rate or population doubling time difference of approximately 1 to 5 hours.
Cells can have doubling times from less than 1 day to more than 2 weeks—in order to process the most diverse clones that at the same time can be reasonably binned according to growth rate; we typically prefer to do 3-9 bins with a 0.25 to 0.7 day doubling time per bin. One skilled in the art would understand how to adjust the tightness of the bins and number of bins according to the particular situation, and tightness and number of bins could be further adjusted if cells were synchronized for their cell cycle. In this example, cell lines with doubling times of 15 to 40 hours were selected for binning to increase tightness of the bins.
The plates were incubated under standard and fixed conditions (humidified 37, 5% CO2/95% air) in DMEM media/10% FBS with antibiotics (100 units penicillin/ml plus 0.1 mg/ml streptomycin). The plates of cells were split to produce 4 sets (the set consists of all plates with all growth bins—these steps ensured there were 4 replicates of the initial set) of target plates. Up to 3 target plate sets were committed for cryopreservation (see below), and the remaining sets were scaled and further replica plated for passage and for functional assay experiments. Distinct and independent tissue culture reagents, incubators, personnel and carbon dioxide sources were used for each set of plates. Quality control steps were taken to ensure the proper production and quality of all tissue culture reagents: each component added to each bottle of media prepared for use was added by one designated person in one designated hood with only that reagent in the hood while a second designated person monitored to avoid mistakes. Conditions for liquid handling were set to eliminate cross contamination across wells. Fresh tips were used for all steps or stringent tip washing protocols were used. Liquid handling conditions were set for accurate volume transfer, efficient cell manipulation, washing cycles, pipetting speeds and locations, number of pipetting cycles for cell dispersal, and relative position of tip to plate.
Two sets of plates were frozen at −70 to −80° C. Plates in each set were first allowed to attain a cell confluency of 70 to 100%. Media was aspirated and culture media or 90% FBS and 10% DMSO was added. The plates were sealed with Parafilm® and then individually surrounded by 1 to 5 cm of foam and placed into a −80° C. freezer.
The remaining 2 sets of plates were maintained as described above in step 9. All cell splitting was performed using liquid handling steps, including media removal, cell washing, trypsin addition and incubation, quenching and cell dispersal steps.
The consistency and standardization of cell and culture conditions for all populations of cells were controlled. Differences across plates due to slight differences in growth rates were controlled by normalization of cell numbers across plates and occurred every 2 to 8 passages after the rearray. Populations of cells that were outliers were detected and eliminated.
Clones were screened between 3.5 and 6 weeks post-sort with and top clones were retested functionally and were identified 5 to 6 weeks post-sort. The cells were maintained for up to 6 weeks to allow for their in vitro evolution under these conditions. During this time, we observed size, morphology, fragility, response to trypsinization or dissociation, roundness/average circularity post-dissociation, percentage viability, tendency towards microconfluency, or other aspects of cell maintenance such as adherence to culture plate surfaces.
Populations of cells were tested using functional criteria. Calcium mobilization dye Fluo-4 (Invitrogen) was used according to manufacturer's instructions. HEK293T cell lines stably expressing h-OR were maintained under standard cell culture conditions in DMEM medium supplemented with 10% fetal bovine serum and glutamine. On the day before assay, the cells were harvested from stock plates and plated into black clear-bottom 384 well assay plates. The assay plates were maintained in a 37° C. cell culture incubator under 5% CO2 for 22-48 hours. The media was then removed from the assay plates and calcium mobilization dye (Fluo-4, Invitrogen, Carlsbad, Calif.), diluted in buffer (130 mM NaCl, 5 mM KCl, 2 mM CaCl2, 1.2 mM MgCl2, 10 mM HEPES, 10 mM glucose, pH 7.0), was added and allowed to incubate for 1 hour at 37° C. with Trypan Ultra Blue (ABD Bioquest, CA) as a quencher, and diluted in the above buffer (130 mM NaCl, 5 mM KCl, 2 mM CaCl2, 1.2 mM MgCl2, 10 mM HEPES, 10 mM glucose, pH 7.0). The above-identified quencher may be substituted by a quencher well-known in the art, e.g., Dipicrylamine (DPA), Acid Violet 17 (AV17), Diazine Black (DB), HLB30818, Bromophenol Blue, HLB30701, HLB30702, HLB30703, Nitrazine Yellow, Nitro Red, DABCYL (Molecular Probes), QSY (Molecular Probes), Metal ion quenchers (e.g., Co2+, Ni2+, Cu2+), and Iodide ion. The assay plates were then loaded on a fluorescent plate reader (Hamamatsu FDSS) and agonist (4.5 mM Helional for OR3A1 and 0.3 mM Bourgeonal for OR1D2—
The functional responses from experiments performed at low and higher passage numbers are compared to identify cells with the most consistent responses over defined periods of time, ranging from 6 to 40 weeks post-sort. Other characteristics of the cells that change over time are also noted, for example, time for cells to reattach post-dissociation.
Populations of cells meeting functional and other criteria are further evaluated to determine those most amenable to production of viable, stable and functional cell lines. Selected populations of cells are expanded in larger tissue culture vessels and the characterization steps described above are continued or repeated under these conditions. At this point, additional standardization steps are introduced for consistent and reliable passages. These included different plating cell densities, plate coatings, time of passage, culture dish size/format and coating, fluidics optimization, cell dissociation optimization (e.g., dissociation in the presence of Cell Dissociation Buffer (Invitrogen) vs trypsin), volume of dissociation reagent used, and length of time of dissociation), as well as washing steps. Glutamine concentrations are dose ranged for the culture medium. Also, viability of cells at each passage are determined. Manual intervention is increased and cells are more closely observed and monitored. This information is used to help identify and select final cell lines that retain the desired properties. Final cell lines and back-up cell lines are selected that showed consistent growth, consistent (i.e. unchanging morphology) appropriate adherence, as well as functional response.
The low passage frozen plates (see above) corresponding to the final cell line and back-up cell lines are thawed at 37° C., washed two times with DMEM/10% FBS and incubated in humidified 37° C./5% CO2 conditions. The cells are then expanded for a period of 2-3 weeks. Cell banks for each final and back-up cell line consisting of 25-50 vials are established. Cells are cryopreserved in 50% DMEM/10% FBS, 40% FBS, and 10% DMSO, resulting from further optimization experiments.
At least one vial from the cell bank including the frozen stocks of the thawed cell lines, expanded and re-frozen, is thawed and expanded in culture. The resulting cells are tested to confirm that they meet the same characteristics for which they are originally selected.
In order to identify and measure the ligand-induced responsiveness of odorant receptor-expressing HEK293T cells, receptor activation are monitored by measuring receptor-triggered alterations in intracellular calcium levels. Cells are either grown overnight in black-clear bottom plates in standard growth media or added to the black-clear bottom plates as a suspension in assay buffer (130 mM NaCl, 5 mM KCl, 2 mM CaCl2, 1.2 mM MgCl2, 10 mM HEPES, 10 mM glucose, pH 7.0). The cells are incubated for 1 hr at room temperature with the no-wash calcium-sensitive fluorescent dye Fluo-4 (Invitrogen) in buffer with Trypan Ultra Blue (ABD Bioquest, CA) as a quencher, diluted in the above buffer (130 mM NaCl, 5 mM KCl, 2 mM CaCl2, 1.2 mM MgCl2, 10 mM HEPES, 10 mM glucose, pH 7.0). The above-identified quencher can be substituted by a quencher well-known in the art, e.g., Dipicrylamine (DPA), Acid Violet 17 (AV17), Diazine Black (DB), HLB30818, Trypan Blue, Bromophenol Blue, HLB30701, HLB30702, HLB30703, Nitrazine Yellow, Nitro Red, DABCYL (Molecular Probes), QSY (Molecular Probes), Metal ion quenchers (e.g., Co2+, Ni2+, Cu2+), and Iodide ion. The cell plates and test compounds (0.01 μM-100 mM) are placed in the high throughput fluorescent plate reader (Hamamatsu FDSS) which collects images of the plate fluorescence before, during and after the instrument added test compounds to the cells. Software (Hamamatsu FDSS) analysis of images reports the change in relative fluorescence for each well in the cell plate.
A variety of compounds and extracts, many of which were reported as odorants, are assayed across the odorant receptor cell lines as well as control cells in order to determine activity and to deorphan.
Because odorant receptors are G protein coupled receptors (GPCRs), in order to make meaningful comparison of responses between different odorant receptors in the presence of various compounds, it is important to determine that the G protein coupling receptors functions uniformly in different cell lines. The relative responses of the different cell lines across a range of concentrations of a G protein coupling agonist should be uniform. To confirm this, the uniformity in Gα15-mediated receptor responses of all cell lines expressing the different odorant receptors and the mouse Gα15 protein are tested in dose response curve experiments with varying concentrations of isoproterenol, an agonist of the β-adrenergic receptor endogenously expressed in the cells. This endogenous receptor, when stimulated, can couple to the expressed Gα15 and evoke a change in intracellular free calcium. Percent response is plotted as a function of isoproterenol concentration, and the results are curve-fitted to calculate an EC50 value (concentration of half-maximal receptor activation).
Cell lines stably expressing native human odorant receptor genes, generated using the method described herein (i.e., Example 39), are tested in functional cell-based receptor studies to detect their activation by a collection of chemically diverse compounds. This allows the identification of broadly tuned receptors, less broadly tuned, and narrowly tuned receptors.
The activity of a library of compounds against each of the odorant receptor cell lines is tested. Data are generated in functional cell-based assays for receptor activity upon addition of the compounds, and are expressed as percent activity above the basal activity of the receptor (i.e., receptor activity upon addition of buffer alone). Activity of each compound at each receptor is then coded to highlight compounds with low (e.g., <100% above basal activity; white), medium (e.g., 101-500% above basal activity; light gray), high (e.g., 501-1000% above basal activity; dark gray), or very high (e.g., >1001% above basal activity, black) activity at each receptor. The resulting pattern is used to provide a graphical representation of compounds active either selectively or broadly across odorant receptors and of receptors showing either broad or selective response to a chemically diverse set of compounds. Analysis of the data is used to assign or identify particular odorant receptors or pattern of odorant receptor activity with test compounds of interest and to identify modulators including blockers and potentiators. Analysis of this data can also be used to correlate patterns of odorant receptor activity with physiological effects of corresponding odorants tested.
To test the ability of the odorant receptor-expressing cell-based assays to identify analogues of compounds with similar functional activities, structural analogues of a known modulator or modulating compound are tested for their ability to inhibit an agonist-induced receptor activity of an odorant receptor. The structures of analogues that inhibit the odorant receptor's activity induced by the agonist are compared. Thus, the odorant receptor-expressing cell lines may aid discovery of potent odorant receptor antagonists. Modulators with different activities (e.g., potentiation, agonism, blocking, etc.) are also identified by operating the assay and testing and performing assay result analysis as would be known to one of skill in the art.
The embodiments of the present invention described above are intended to be merely exemplary, and those skilled in the art will recognize, or be able to ascertain using no more than routine experimentation, numerous equivalents to the specific procedures described herein. All such equivalents are considered to be within the scope of the present invention and are covered by the following claims. Additionally, ordinarily skilled artisans will recognize that operational sequences must be set forth in some specific order for the purpose of explanation and claiming, but the present invention contemplates various changes beyond such specific order.
All references cited herein are incorporated herein by reference in their entirety and for all purposes to the same extent as if each individual publication or patent or patent application was specifically and individually indicated to be incorporated by reference in its entirety for all purposes.
This application claims the benefit of U.S. Provisional Application No. 61/149,321 filed Feb. 2, 2009; U.S. Provisional Application No. 61/149,318 filed Feb. 2, 2009; U.S. Provisional Application No. 61/149,324 filed Feb. 2, 2009; U.S. Provisional Application No. 61/149,311 filed Feb. 2, 2009; U.S. Provisional Application No. 61/235,181 filed Aug. 19, 2009; and U.S. Provisional Application No. 61/230,536 filed Jul. 31, 2009, each of which is incorporated by reference herein in its entirety. The instant application contains a Sequence Listing which has been submitted via EFS-Web and is hereby incorporated by reference in its entirety. Said ASCII copy, created on Feb. 1, 2010, is named 0022980025SeqList.txt, and is 200,023 bytes in size.
| Filing Document | Filing Date | Country | Kind | 371c Date |
|---|---|---|---|---|
| PCT/US10/22781 | 2/1/2010 | WO | 00 | 7/29/2011 |
| Number | Date | Country | |
|---|---|---|---|
| 61149311 | Feb 2009 | US | |
| 61149318 | Feb 2009 | US | |
| 61149321 | Feb 2009 | US | |
| 61230536 | Jul 2009 | US | |
| 61235181 | Aug 2009 | US | |
| 61149324 | Feb 2009 | US |
