Patent Application
20240085387
Carbohydrates or “glycans” are abundant biological macro-molecules that make up the majority of the glycocalyx on cells in the form of glycoconjugates. Glycosylation is one of the most common and complex post-translational modifications (PTMs) of secreted and cell surface proteins, enabling diverse biological processes like cell adhesion, cell-cell communication, and immune responses (Varki, A. Biological roles of glycans. Glycobiology 2017, 27, 3-49; Reily, C.; Stewart, T. J.; Renfrow, M. B.; Novak, J. Glycosylation in health and disease. Nat. Rev. Nephrol. 2019, 15, 346-366; Gahmberg, C. G.; Tolvanen, M. Why mammalian cell surface proteins are glycoproteins. Trends Biochem. Sci. 1996, 21, 308-311). Unlike proteins and nucleic acids which are linear polymers built from a template, glycan structures are the sum result of many glycosidase and glycosyltransferase enzymes that can result in polymers with various branching patterns (Varki, A. Evolutionary forces shaping the Golgi glycosylation machinery: why cell surface glycans are universal to living cells. Cold Spring Harbor Perspect. Biol. 2011, 3, a005462). Additional structural complexity stems from glycans having various positional isomers, linkage stereochemistry (α/β anomers), and different compositions of the various monosaccharide building blocks.
Mass spectrometry (MS) is one of the primary techniques used to investigate the immense diversity of glycans, and a great deal of effort has been invested into understanding the gas-phase behavior of carbohydrates. However, MS-based glycan analysis is often confounded by the technique's inability to distinguish among the many potential isomeric structures from a mass measurement.
A thorough characterization of the tandem MS behavior of permethylated oligosaccharides can pave the way for effective discrimination among potential isomers (Sheeley, D. M.; Reinhold, V. N. Structural Characterization of Carbohydrate Sequence, Linkage, and Branching in a Quadrupole Ion Trap Mass Spectrometer: Neutral Oligosaccharides and N-Linked Glycans. Anal. Chem. 1998, 70, 3053-3059). Protonated carbohydrates present additional challenges, as they can undergo rearrangement reactions, most notably migration of fucose during collision-induced dissociation (CID) (Wuhrer, M.; Koeleman, C. A. M.; Hokke, C. H.; Deelder, A. M. Mass spectrometry of proton adducts of fucosylated N-glycans: fucose transfer between antennae gives rise to misleading fragments. Rapid Commun. Mass Spectrom. 2006, 20, 1747-1754). This migration process is still under investigation (Mucha, E.; Lettow, M.; Marianski, M.; Thomas, D. A.; Struwe, W. B.; Harvey, D. J.; Meijer, G.; Seeberger, P. H.; von Heiden, G.; Pagel, K. Fucose Migration in Intact Protonated Glycan Ions: A Universal Phenomenon in Mass Spectrometry. Angew. Chem., Int. Ed. 2018, 57, 7440-7443; Sastre Toraño, J.; Gagarinov, I. A.; Vos, G. M.; Broszeit, F.; Srivastava, A. D.; Palmer, M.; Langridge, J. I.; Aizpurua-Olaizola, O.; Somovilla, V. J.; Boons, G.-J. Ion-Mobility Spectrometry Can Assign Exact Fucosyl Positions in Glycans and Prevent Misinterpretation of Mass-Spectrometry Data After Gas-Phase Rearrangement. Angew. Chem., Int. Ed. 2019, 58, 17616-17620; Lettow, M.; Mucha, E.; Manz, C.; Thomas, D. A.; Marianski, M.; Meijer, G.; von Heiden, G.; Pagel, K. The role of the mobile proton in fucose migration. Anal. Bioanal. Chem. 2019, 411, 4637-4645), and a general structural understanding of the even simple protonated carbohydrate systems is only now starting to emerge (Bythell, B. J.; Abutokaikah, M. T.; Wagoner, A. R.; Guan, S.; Rabus, J. M. Cationized Carbohydrate Gas-Phase Fragmentation Chemistry. J. Am. Soc. Mass Spectrom. 2017, 28, 688-70).
For intact glycoconjugates (e.g., glycopeptides), which are typically analyzed as protonated ions, tandem MS is incapable of providing full information on the branching pattern, linkage information, or stereochemistry of the glycan (Pap, A.; Klement, E.; Hunyadi-Gulyas, E.; Darula, Z.; Medzihradszky, K. F. Status Report on the High-Throughput Characterization of Complex Intact O-Glycopeptide Mixtures. J. Am. Soc. Mass Spectrom. 2018, 29, 1210-1220). Understanding glycobiology at the highest level of detail, including site-specific localization of all glycan structural isomers within glycoproteins (Schumacher, K. N.; Dodds, E. D. A case for protein-level and site-level specificity in glycoproteomic studies of disease. Glycoconjugate J. 2016, 33, 377-385), can be achieved by a thorough understanding of the properties of carbohydrate fragment ions. Tools complementary to MS including ion mobility (IM) and spectroscopic techniques like cryogenic ion spectroscopy and ultraviolet photodissociation have emerged as powerful gas-phase techniques with potential applications in glycobiology (Clowers, B. H.; Dwivedi, P.; Steiner, W. E.; Hill, H. H.; Bendiak, B. Separation of Sodiated Isobaric Disaccharides and Trisaccharides Using Electrospray Ionization-Atmospheric Pressure Ion Mobility-Time of Flight Mass Spectrometry. J. Am. Soc. Mass Spectrom. 2005, 16, 660-669; Dwivedi, P.; Bendiak, B.; Clowers, B. H.; Hill, H. H. Rapid Resolution of Carbohydrate Isomers by Electrospray Ionization Ambient Pressure Ion Mobility Spectrometry-Time-of-Flight Mass Spectrometry (ESI-APIMS-TOFMS). J. Am. Soc. Mass Spectrom. 2007, 18, 1163-1175; Brodbelt, J. S. Photodissociation mass spectrometry: new tools for characterization of biological molecules. Chem. Soc. Rev. 2014, 43, 2757-2783; Tan, Y.; Polfer, N. C. Linkage and Anomeric Differentiation in Trisaccharides by Sequential Fragmentation and Variable-Wavelength Infrared Photodissociation. J. Am. Soc. Mass Spectrom. 2015, 26, 359-368; Gray, C. J.; Schindler, B.; Migas, L. G.; Picm̆ anova{acute over (,)} M.; Allouche, A. R.; Green, A. P.; Mandal, S.; Motawia, M. S.; Sańchez-Peŕez, R.; Bjarnholt, N.; Møller, B. L.; Rijs, A. M.; Barran, P. E.; Compagnon, I.; Eyers, C. E.; Flitsch, S. L. Bottom-Up Elucidation of Glycosidic Bond Stereochemistry. Anal. Chem. 2017, 89, 4540-4549; Mucha, E.; Gonzaĺez Floŕez, A. I.; Marianski, M.; Thomas, D. A.; Hoffmann, W.; Struwe, W. B.; Hahm, H. S.; Gewinner, S.; Schöllkopf, W.; Seeberger, P. H.; von Heiden, G.; Pagel, K. Glycan Fingerprinting via Cold-Ion Infrared Spectroscopy. Angew. Chem., Int. Ed. 2017, 56, 11248-11251; Riggs, D. L.; Hofmann, J.; Hahm, H. S.; Seeberger, P. H.; Pagel, K.; Julian, R. R. Glycan Isomer Identification Using Ultraviolet Photodissociation Initiated Radical Chemistry. Anal. Chem. 2018, 90, 11581-11588; Ben Faleh, A.; Warnke, S.; Rizzo, T. R. Combining Ultrahigh-Resolution Ion-Mobility Spectrometry with Cryogenic Infrared Spectroscopy for the Analysis of Glycan Mixtures. Anal. Chem. 2019, 91, 4876-4882; Gray, C. J.; Migas, L. G.; Barran, P. E.; Pagel, K.; Seeberger, P. H.; Eyers, C. E.; Boons, G.-J.; Pohl, N. L. B.; Compagnon, I.; Widmalm, G.; Flitsch, S. L. Advancing Solutions to the Carbohydrate Sequencing Challenge. J. Am. Chem. Soc. 2019, 141, 14463-14479).
Ion mobility with mass spectrometry (IM-MS) separates ions by their charge, size, and shape due to interactions with an inert gas. IM-MS has shed light on the structural details of carbohydrates in the gas phase (Gray, C. J et al., 2017; Mookherjee, A.; Uppal, S. S.; Guttman, M. Dissection of Fragmentation Pathways in Protonated N-Acetylhexosamines. Anal. Chem. 2018, 90, 11883-11891), and the emerging next-generation of high-resolution IM-MS shows much promise at resolving even subtle isomeric variants within larger glycans (Ben Faleh, A et al., 2019; Ujma, J.; Ropartz, D.; Giles, K.; Richardson, K.; Langridge, D.; Wildgoose, J.; Green, M.; Pringle, S. Cyclic Ion Mobility Mass Spectrometry Distinguishes Anomers and Open-Ring Forms of Pentasaccharides. J. Am. Soc. Mass Spectrom. 2019, 30, 1028-1037; Wojcik, R.; Webb, I. K.; Deng, L.; Garimella, S. V.; Prost, S. A.; Ibrahim, Y. M.; Baker, E. S.; Smith, R. D. Lipid and Glycolipid Isomer Analyses Using Ultra-High Resolution Ion Mobility Spectrometry Separations. Int. J. Mol. Sci. 2017, 18, 183). Gas-phase spectroscopy is emerging to define structural variations in carbohydrates and their structures on its own or in combination with IM-MS (Mucha, E et al., 2017; Ben Faleh, A et al., 2019; Scutelnic, V.; Rizzo, T. R. Cryogenic Ion Spectroscopy for Identification of Monosaccharide Anomers. J. Phys. Chem. A 2019, 123, 2815-2819; Khanal, N.; Masellis, C.; Kamrath, M. Z.; Clemmer, D. E.; Rizzo, T. R. Cryogenic IR spectroscopy combined with ion mobility spectrometry for the analysis of human milk oligosaccharides. Analyst 2018, 143, 1846-1852; Warnke, S.; Ben Faleh, A.; Pellegrinelli, R. P.; Yalovenko, N.; Rizzo, T. R. Combining ultra-high resolution ion mobility spectrometry with cryogenic IR spectroscopy for the study of biomolecular ions. Faraday Discuss. 2019, 217, 114-125).
Gas-phase hydrogen/deuterium exchange (gHDX), which tracks the exchangeability of various labile protons in an ion, has also been shown effective at distinguishing isomers including carbohydrates (Ausloos, P.; Lias, S. G. Thermoneutral isotope-exchange reactions of cations in the gas phase. J. Am. Chem. Soc. 1981, 103, 3641-3647; Cheng, X.; Fenselau, C. Hydrogen/deuterium exchange of mass-selected peptide ions with ND3 in a tandem sector mass spectrometer. Int. J. Mass Spectrom. Ion Processes 1992, 122, 109-119; Gard, E.; Green, M. K.; Bregar, J.; Lebrilla, C. B. Gas-phase hydrogen/deuterium exchange as a molecular probe for the interaction of methanol and protonated peptides. J. Am. Soc. Mass Spectrom. 1994, 5, 623-631; Zhang, J.; Brodbelt, J. S. Gas-Phase Hydrogen/Deuterium Exchange and Conformations of Deprotonated Flavonoids and Gas-Phase Acidities of Flavonoids. J. Am. Chem. Soc. 2004, 126, 5906-5919; Uppal, S. S.; Beasley, S. E.; Scian, M.; Guttman, M. Gas-Phase Hydrogen/Deuterium Exchange for Distinguishing Isomeric Carbo-hydrate Ions. Anal. Chem. 2017, 89, 4737-4742; Majuta, S. N.; Li, C.; Jayasundara, K.; Kiani Karanji, A.; Attanayake, K.; Ranganathan, N.; Li, P.; Valentine, S. J. Rapid Solution-Phase Hydrogen/Deuterium Exchange for Metabolite Compound Identification. J. Am. Soc. Mass Spectrom. 2019, 30, 1102-1114; Liyanage, O. T.; Quintero, A. V.; Hatvany, J. B.; Gallagher, E. S. Distinguishing Carbohydrate Isomers with Rapid Hydrogen/Deuterium Exchange-Mass Spectrometry. J. Am. Soc. Mass Spectrom. 2020, DOI: 10.1021/jasms.0c00314).
Thanks to their ability to resolve structural isomers, these new techniques have also shown examples of multiple distinct gas-phase chemical structures obtained for a single distinct carbohydrate, often attributed to the site of protonation or deprotonation (Struwe, W. B.; Baldauf, C.; Hofmann, J.; Rudd, P. M.; Pagel, K. Ion mobility separation of deprotonated oligosaccharide isomers—evidence for gas-phase charge migration. Chem. Commun. 2016, 52, 12353-12356). Recent studies have further illustrated the complexity of fragmentation of protonated carbohydrates. Gray et al. using IM-MS found that B-ion fragments of carbohydrates retain information on the stereochemistry at their reducing end even after losing their reducing end (“anomeric memory”) (Gray, C. J. et al., 2017). This is thought to arise from the generation of different isomeric fragment ion structures, whose ensemble is affected by the structure of the precursor. Similar “memory effects” were also observed by both IM-MS and MSn relative fragmentation propensities even after multistage MS (Mookherjee, A. et al., 2018).
Many of the drawings submitted herein are better understood in color. Applicant considers the color versions of the drawings as part of the original submission and reserves the right to present color images of the drawings in later proceedings.
As used herein, “glycan” (or “polysaccharide”) may refer to synonyms meaning “compounds consisting of a large number of monosaccharides linked glycosidically. Furthermore, in practice “glycan” can refer to the carbohydrate portion of a glycoconjugate, such as a glycoprotein, glycolipid, or a proteoglycan, even if the carbohydrate is only an oligosaccharide. Glycans can consist solely of O-glycosidic linkages of monosaccharides. Glycans can be homo-or heteropolymers of monosaccharide residues, and can be linear or branched.
As used herein, an “O-glycosidic bond” or “O-glycosidic linkage” (or “glycosidic bond” or “glycosidic linkage”) may refer to a type of ether bond that joins a carbohydrate (sugar) molecule to another group, which may or may not be another carbohydrate. A glycosidic bond is formed between the hemiacetal or hemiketal group of a saccharide (or a molecule derived from a saccharide) and the hydroxyl group of some compound such as an alcohol. A substance containing a glycosidic bond is a glycoside. For example, the formation of ethyl glucoside by the combination of glucose and ethanol (with water as a byproduct) is shown in
As used herein, “anomer” or “anomers” may refer to a pair of near-identical stereoisomers that differ at only the anomeric carbon, the carbon that bears the aldehyde or ketone functional group in the sugar's open-chain form. “Anomerization” is the process of conversion of one anomer to the other. In various examples, different anomers have different physical properties, melting points and specific rotations.
As used herein, “isomer” or “isomers” may refer to molecules or polyatomic ions with identical molecular formulae—that is, same number of atoms of each element—but distinct arrangements of atoms in space. “Isomerism” is existence or possibility of isomers.
As used herein, “sialylation” may refer to the covalent addition of sialic acid to the terminal end of glycoproteins. “Sialylated glycan” refers to a glycan that has undergone sialylation.
As used herein, “sialic acid” or “sialic acids” may refer to a class of alpha-keto acid sugars with a nine-carbon backbone. The sialic acid family includes derivatives of the nine-carbon sugar neuraminic acid (Neu), having the structure:
The N- or O-substituted derivatives of Neu form many examples of sialic acids. Examples include N-Acetylneuraminic acid (Neu5Ac; or NeuAc) and 2-Keto-3-deoxyunonic acid (Kdn) having the structures:
In particular cases, the LC-MS instrument generates a first spectrum that includes first peaks. The first spectrum may be represented as data. In various implementations, the first peaks correspond to specific abundance values in the first spectrum that correspond to predetermined m/z values. The predetermined m/z values correspond to specific known structural characteristics.
In various implementations, the MS and/or the LC-MS instrument is configured to perform multiple MS rounds on the carbohydrate sample. For instance, the MS, or LC-MS instrument performs an MS1 round to generate the first spectrum. Further, the MS, or LC-MS instrument performs an MS2 round on at least a portion of the carbohydrate sample to generate a second spectrum including second peaks. The portion of the carbohydrate sample utilized by the MS or LC-MS instrument in the MS2 round, for instance, is defined according to one or more of the first peaks in the first spectrum. Although
The first spectrum and the second spectrum are input into an analysis system for further processing. In various implementations, the analysis system is embodied in at least one computing device. For instance, one or more processors are configured to execute the functions of the analysis system. In some cases, the processor(s) execute instructions stored in memory, a non-transitory computer readable medium, or both. Although the analysis system is illustrated, in
The analysis system is configured to identify a structural characteristic of the carbohydrate sample by analyzing the first spectra and the second spectra. In various implementations, the analysis system identifies relative abundance values represented by at least one of the first peaks and/or at least one of the second peaks. In particular cases, the analysis system identifies the relative abundance values in the first peaks and/or second peaks that correspond to two or more predetermined m/z values. Further, the analysis system may calculate ratios of two or more of the relative abundance values. In some cases, the ratios are between a first relative abundance value and a sum of two or more second relative abundance values among the relative abundance values. Thus, the analysis system generates one or more ratios corresponding to the original carbohydrate sample.
In various implementations of the present disclosure, the analysis system identifies the structural characteristic based on the one or more ratios. For example, the analysis system may determine that an example ratio of the carbohydrate sample is within a predetermined range of a predetermined ratio corresponding to a predetermined structural characteristic. In some cases, the analysis system compares multiple ratios of the carbohydrate sample to multiple predetermined ratios in order to determine whether the carbohydrate sample has one or more of multiple predetermined characteristics. Specific examples of the predetermined m/z values, the predetermined ratios, the predetermined ranges, and the predetermined characteristics are described below. In some cases, the predetermined range associated with a predetermined ratio is adjusted based on the variability or uncertainty in the measurement of the ratio. For instance, the predetermined range may be adjusted based the total ion counts of a given MSn spectrum performed by the LC-MS instrument.
In various implementations, the analysis system outputs the structural characteristic, the first spectra, the second spectra, or any combination thereof, to a user. For example, the analysis system may include a display that visually presents information to the user.
According to some cases, the analysis system outputs the structural characteristic, the first spectra, the second spectra, or any combination thereof, to an external device, such as an external computing device. For instance, the analysis system includes one or more transceivers that encode data representing information into one or more communication signals that the transceiver(s) transmit to the external device. In some examples, the external device performs additional processing on the data, or outputs the data to a user.
The memory 204 may include component(s) 218. The component(s) 218 may include at least one of instruction(s), program(s), database(s), software, operating system(s), etc. In some implementations, the component(s) 218 include instructions that are executed by processor(s) 206 and/or other components of the device 200. For example, the component(s) 218 may include instructions for generating spectra, generating ratios based on predetermined m/z values, comparing ratios to one or more predetermined ratios, and identifying structural characteristics.
In some embodiments, the processor(s) 206 include a central processing unit (CPU), a graphics processing unit (GPU), or both CPU and GPU, or other processing unit or component known in the art.
The device 200 may also include additional data storage devices (removable and/or non-removable) such as, for example, magnetic disks, optical disks, or tape. Such additional storage is illustrated in
The device 200 may be configured to communicate over a telecommunications network using any common wireless and/or wired network access technology. Moreover, the device 200 may be configured to run any compatible device Operating System (OS), including but not limited to, Microsoft Windows Mobile, Google Android, Apple iOS, Linux Mobile, as well as any other common mobile device OS.
The device 200 also can include input device(s) 212, such as an LC component, an MS component, an LC-MS instrument, one or more analog-to-digital converters (ADCs), keypad, a cursor control, a touch-sensitive display, voice input device, etc. The device 200 further includes output device(s) 214 such as a display, speakers, printers, etc.
As illustrated in
At 217, the entity identifies spectra data. In various implementations, the spectra data is indicative of one or more spectra of m/z versus relative abundance of a glycan sample. The spectra, for instance, are generated by an MS instrument, such as an LC-MS instrument. In some cases, the instrument includes an ion trap MS instrument, a collision-induced dissociation (CID) MS instrument, or the like. The glycan sample, in various cases, can include a protonated glycan including an oligosaccharide.
According to various implementations, the spectra are generated using multiple MS rounds. For example, n spectra are generated based on respective MSn rounds, wherein n is an integer that is greater than 1 or 2. In some cases, n is in a range of 2 to 4.
At 218, the entity generates a ratio. For instance, the entity calculates the ratio using the following equation:
Wherein a is a magnitude of one or more first peaks in the spectra and b is the magnitude of one or more second peaks in the spectra. The magnitudes of the peaks, for instance, are magnitudes of relative abundance at predetermined m/z ratios.
At 219, the entity determines that the ratio is within a predetermined range. The predetermined range, in some implementations, is determined based on a number of ion counts identified by the instrument generating the spectra. For instance, the predetermined range is dependent on the amount of the glycan sample analyzed by the instrument.
At 220, the entity determines that a predetermined structural characteristic is present in the glycan sample. For instance, the predetermined structural characteristic is an identity of the glycan, a connectivity of linkages within a polysaccharide of the glycan, a configuration of one or more monosaccharides in the glycan, or any combination thereof.
At 221, the entity outputs an indication of the predetermined structural characteristic. In some implementations, the entity visually presents the indication on a display. In some cases, the entity outputs the indication by a speaker as an audio signal. According to various cases, the entity transmits a communication signal encoding the indication to an external device.
The masses in each panel: m/z 384, 368, 366, 350, and 204 have been selected for each stage of MSn shown by the arrows. Structures of each disaccharide are shown in the panel. The symbols show the three monosaccharides GlcNAc (in blue), galactose (in yellow), and fucose (in red) that form the six disaccharides, while the solid/dashed lines denote the glycosidic bond between the monosaccharides with the angle of the line specifying a linkage configuration (see
N2, He, and CO2 were used as the drift gas for
Deuterium uptake for the various fragment ions is shown as a function of incubation time with ND3. The points and error bars represent the average and standard deviations from triplicate measurements. The blue and red fits indicate the two populations that are resolved, and the relative abundance of the red population is indicated in the inset.
The deuterium exchange time points are indicated in the inset with the undeuterated shown on top. Purple dashed lines indicate positions of centroid of all isotopic peaks (red circles). For the 10 ms time points of the 366 ions the multiple populations (pop.) were fit to a combination of binomial distributions (blue and red fits). Orange x's indicate overlapping unrelated peaks from M+ND3-H2O species.
The deuterium exchange time points are indicated in the inset with the undeuterated shown on top. Purple dashed lines indicate positions of centroid of all isotopic peaks (red circles). For the 10 ms time points of the 350 ions the multiple populations (pop.) were fit to a combination of binomial distributions (blue and red fits). In the case of Fuc(α1-4)GlcNAc there was a third population (purple) that did not undergo any gHDX. Orange x's indicate overlapping unrelated peaks from M+ND3-H2O species.
Experiments are performed under different collision energies (CEs). For m/z 366 and 350, low CE=5 eV and high CE=10 eV, for m/z 204 from m/z 366 low CE=10 and high CE=17, and for m/z 204 from m/z 350 low CE=10 eV and high CE=22 eV. Error bars represent standard deviation from triplicate measurements.
The present disclosure provides a method of analyzing the structure of a glycan sample, the method including:
In implementations, the glycan sample includes a protonated glycan including an oligosaccharide. A protonated glycan includes an O-glycan or an N-glycan.
N-glycans are covalently attached to protein at asparagine (Asn) residues by an N-glycosidic bond. A common N-glycan linkage is the attachment of N-acetylglucosamine to asparagine (GlcNAcβ1-Asn). An example of such an N-glycan is: GlcNAcβ(1-2)Manα(1-3)[GlcNAcβ(1-2)Manα(1-6)]Manβ(1-4)GlcNAcβ(1-4)GlcNAc-Asn, which has the structure:
Various examples of O-glycans have N-acetylgalactosamine (GalNAc) as a common core, although other cores are also possible. O-glycans result from O-glycosylation that is a common covalent modification of serine and threonine residues of mammalian glycoproteins. In mucins, O-glycans can be covalently α-linked via an N-acetylgalactosamine (GalNAc) moiety to the —OH of serine or threonine by an O-glycosidic bond, and the structures are named mucin O-glycans or O-GalNAc glycans. An example of an O-glycan is Galβ(1-3)GalNAc-α-1-O-Serine (also represented as H-Ser(Gal(β(1-3)GalNAc)-OH) having the structure:
Another example of an O-glycan is O-[2-Acetamido-2-deoxy-3-O-(β-D-galactopyranosyl)-α-D-galactopyranosyl]-L-threonine, having the structure:
In implementations, the protonated glycan of this disclosure includes a sialylated glycan.
In implementations, the glycan of this disclosure includes an oligosaccharide, and wherein the monosaccharides of the oligosaccharide are linked through O-glycosidic linkages.
In implementations, the predetermined structural characteristic includes:
In implementations, the connectivity of the O-glycosidic linkages can, for example, be (1-2), (1-3), (1-6) positional linkages connecting two monosaccharides of an oligosaccharide of the glycan. As an example, using Fucose and GlcNAc as the two monomers of a disaccharide, these linkages can be represented structurally as:
The configuration of the anomeric carbons of each monomer can be a (alpha) or β (beta), and the O-glycosidic linkage can be α or β.
As an example,
In implementations, the predetermined ratio of the disclosure has a variability (uncertainty; ratio error) associated with it, which is based on the number of ion counts associated with the one or more spectra. Accordingly, the presently disclosed method of analyzing the structure of a glycan sample further includes determining the variability of the predetermined ration based on a number of ion counts associated with the one or more spectra.
As set forth in
In implementations, the presently disclosed method of analyzing the structure of a glycan sample further includes:
In implementations, obtaining, by the MS instrument, the one or more spectra includes: obtaining, by the MS instrument, a first MS spectrum (MS1 spectrum) by passing the glycan sample through the MS instrument a first time;
In implementations, the portion of the glycan sample referred to immediately above is a first portion of the glycan sample, and
In implementations, obtaining, by the MS instrument, the one or more spectra, referred to immediately above, further includes:
Accordingly, in implementations, the presently disclosed method of analyzing the structure of a glycan sample involves tandem mass spectrometry, also known as MS/MS (or MS-MS), where two or more mass analyzers are coupled together using an additional reaction step to increase their abilities to analyze chemical samples, such as glycans, proteins, peptides, and other biomolecules.
The molecules of a given sample are ionized and the first spectrometer (designated MS1) separates these ions by their mass-to-charge ratio (often given as m/z or m/Q). Ions of a particular m/z-ratio coming from MS1 are selected and then made to split into smaller fragment ions, e.g., by collision-induced dissociation, ion-molecule reaction, or photodissociation. These fragments are then introduced into the second mass spectrometer (MS2), which in turn separates the fragments by their m/z-ratio and detects them. Fragments from MS2 can also be introduced, into a third mass spectrometer (MS3), and fragments from MS3 can also be introduced, for structure elucidation of the sample into a fourth mass spectrometer (MS4) for additional information. In some examples, the same spectrometer device performs each MSn round, where n is a positive integer. The fragmentation steps make it possible to identify and separate ions that have very similar m/z-ratios in regular mass spectrometers.
In implementations, prior to obtaining by the MS instrument, the one or more spectra by passing the glycan sample through the MS instrument, the glycan sample is passed through a liquid chromatography (LC) instrument, and a portion of the glycan sample corresponding to a particular peak in the liquid chromatogram is obtained and passed through the MS instrument. Accordingly, this method employs what is commonly known as liquid chromatography with tandem mass spectrometry (LC-MS-MS), which is a powerful analytical technique that combines the separating power of liquid chromatography with the highly sensitive and selective mass analysis capability of triple quadruple mass spectrometry.
In implementations, in the presently disclosed method of analyzing the structure of a glycan sample, the one or more first peaks are defined at an m/z of 138 and the one or more second peaks are defined at an m/z of 144 in an MSn spectrum derived from fragmentation of a portion of the sample corresponding to m/z 204 in an MSn−1 spectrum,
N-acetylgalactosamine (GalNAc), for instance, has the structure:
and in Haworth projection
N-acetylglucosamine (GlcNAc) has the structure:
and in Haworth projection
N-acetylmannosamine (ManNAc) has the structure:
and in Haworth projection
As used herein, “the reducing end” of a sugar refers to the sugar structure with a free aldehyde or ketone group. The end of the molecule with the free anomeric carbon is referred to as the reducing end.
Thus, in implementations, the ratio (m/z 138)/(m/z 138+m/z 144) from the fragmentation of m/z 204 may distinguish between GalNAc, GlcNAc & ManNAc—composition isomers having same m/z but differ at one stereochemistry of hydroxyl at one carbon. Thus, GalNAc and GlcNAC differ in the configuration of the anomeric carbon, whereas GlCNAc and ManNAC differ in the configuration of the carbon atom bearing the N-acetyl group. This ratio can also be used to assess whether larger carbohydrates (e.g., tri/tetra-saccharides) have GalNAc or GlcNAc on their reducing end.
As an illustration, the structure of Gal(β1-3)GalNAc is:
the structure of Gal(β1-4)GlcNAc is:
and the structure of Fuc(α1-4)GlcNAc is:
In implementations, the ratios of 0.37, 0.81, or 0.73 for (m/z 138)/(m/z 138+m/z 144) all have variabilities associated with them. In implementations, the variability associated with the ratio of 0.37 is ±0.05. In implementations, the variability associated with the ratio of 0.81 is ±0.04. In implementations, the variability associated with the ratio of 0.73 is ±0.11.
In implementations, in the presently disclosed method of analyzing the structure of a glycan sample, the one or more first peaks are defined at an m/z of 84 and 126 and the one or more second peaks are defined at an m/z of 138, 144, 168, and 186 in an MSn spectrum derived from fragmentation of a portion of the sample corresponding to m/z 204 in an MSn−1 spectrum,
In implementations, the two monosaccharides include: Fucα and GlcNAc; or Galβ and GlcNAc. This is illustrated in
In implementations, in the presently disclosed method of analyzing the structure of a glycan sample, wherein the one or more first peaks are defined at an m/z of 138 and 168, and the one more second peaks are defined at an m/z of 126, 144, and 186 in an MSn spectrum derived from fragmentation of a portion of the sample corresponding to an m/z of 366 in an MSn−1 spectrum,
In implementations, the two monosaccharides include Galβ and GlcNAc; or Fucβ and GlcNAc. Thus, for example, Gal(β1-6)GlcNAc appears at a ratio of 0.536; Neu5Ac(α2-3)Gal(β1-3)GlcNAc(β1-3)Glc appears at a ratio of 0.621; and Gal(β1-6)GlcNAc appears at a ratio of 0.536. Neu5Ac is N-Acetylneuraminic acid (also known as NANA), and has the structure:
In implementations, the ratios of 0.621, 0.843, or 0.536 for (m/z 138+m/z 168)/(m/z 138+m/z 168+m/z 126+m/z 144) all have variabilities associated with them. In implementations, the variability associated with the ratio of 0.621 is ±0.012. In implementations, the variability associated with the ratio of 0.843 is ±0.007. In implementations, the variability associated with the ratio of 0.536 is ±0.02.
In implementations, in the presently disclosed method of analyzing the structure of a glycan sample, the one or more first peaks are defined at an m/z of 186 and 204, and the one or more second peaks are defined at an m/z of 256, 274, 292, 454, and 495 in an MSn spectrum derived from fragmentation of a portion of the carbohydrate sample corresponding to an m/z of 657 in an MSn−1 spectrum;
In implementations, one of the two monosaccharides is Neu5Ac. In implementations, one of the two monosaccharides in Neu5Ac, and the other is Gal. Thus for example, Neu5Ac(α2-6)Gal(β1-4)GlcNAc appears at a ratio of 0.426, and Neu5Ac(α2-3)Gal(β1-4)GlcNAc appears at a ratio of 0.219.
In implementations, the ratios of 0.426 and 0.219 for (m/z 186+m/z 204)/(m/z 186+m/z 204+m/z 256+m/z 274+m/z 292+m/z 454+m/z 495) all have variabilities associated with them. In implementations, the variability associated with the ratio of 0.426 is ±0.03. In implementations, the variability associated with the ratio of 0.219 is ±0.007.
In implementations, in the presently disclosed method of analyzing the structure of a glycan sample, the one or more first peaks are defined at an m/z of 204 and 366, and the one or more second peaks are defined at an m/z of 274, 292, 454, 472 and 495 in an MSn spectrum derived from fragmentation of a portion of the carbohydrate sample corresponding to an m/z of 657 in an MSn−1 spectrum,
In implementations, wherein the O-glycosidic linkage between Neu5Ac and Gal is an (α2-6) or an (α2-3) linkage, Neu5Ac(α2-6)Gal(β1-4)GlcNAc appears at a ratio of 0.758, and Neu5Ac(α2-3)Gal(β1-4)GlcNAc appears at a ratio of 0.531.
In implementations, wherein the O-glycosidic linkage between Gal and GlcNAc is a 031-4) or an (β1-3) linkage in the tetrasaccharide Neu5Ac(α2-3)GalGlcNAc(β1-3)Glc, Neu5Ac(α2-3)Gal(β1-4)GlcNAc(β1-3)Glc appears at a ratio of 0.403, and Neu5Ac(α2-3)Gal(β1-3)GlcNAc(β1-3)Glc appears at a ratio of 0.234.
In implementations, wherein the O-glycosidic linkage between Gal and GlcNAc-OH is a (β1-3), (β1-4) or a (β1-6) linkage, in the disaccharide Gal-GlcNAc-OH (in this disaccharide, GlaNAc is understood to be the reducing end), Gal(β1-3)GlcNAc-OH appears at a ratio of 0.685, Gal(β1-4)GlcNAc-OH appears at a ratio of 0.867, and Gal(β1-6)GlcNAc-OH appears at a ratio of 0.536.
In implementations, the ratios of 0.867, 0.758, 0.685, 0.536, 0.531, 0.403, or 0.234 for (m/z 204+m/z 366)/(m/z 204+m/z 366+m/z 274+m/z 292+m/z 454+m/z 472+m/z 495) all have variabilities associated with them. In implementations, the variability associated with the ratio of 0.758 is ±0.044. In implementations, the variability associated with the ratio of 0.531 is ±0.052. In implementations, the variability associated with the ratio of 0.403 is ±0.046. In implementations, the variability associated with the ratio of 0.234 is ±0.009. In implementations, the variability associated with the ratio of 0.685 is ±0.007. In implementations, the variability associated with the ratio of 0.867 is ±0.004. In implementations, the variability associated with the ratio of 0.536 is ±0.02.
In implementations, in the presently disclosed method of analyzing the structure of a glycan sample, the one or more first peaks are defined at an m/z of 204 and 495, and the one or more second peaks are defined at an m/z of 366 in an MSn spectrum derived from fragmentation of a portion of the carbohydrate sample corresponding to an m/z of 657 in an MSn−1 spectrum,
Thus Neu5Ac(α2-3)Gal(β1-3)GalNAc-Ser appears at a ratio of 0.315, and Gal(β1-3)[Neu5Ac(α2-6)]GalNAc-Ser appears at a ratio of 0.704.
In implementations, the ratios of 0.315, and 0.704 for (m/z 204+m/z 495)/(m/z 204+m/z 495+m/z 366) all have variabilities associated with them. In implementations, the variability associated with the ratio of 0.685 is ±0.007. In implementations, the variability associated with the ratio of 0.315 is ±0.022. In implementations, the variability associated with the ratio of 0.704 is ±0.031.
In implementations, in the presently disclosed method of analyzing the structure of a glycan sample, the MS instrument includes an ion trap MS instrument. In implementations, the ion trap MS instrument employs collision-induced dissociation.
Reagents. The standards Gal(β1-4)GlcNAc, Gal(β1-6)-GlcNAc, Gal(β1-3)GlcNAc, Fuc(α1-4)GlcNAc, Fuc(α1-3)-GlcNAc, and Fuc(α1-6)GlcNAc were purchased from Carbosynth (Compton, U.K.). Deuterated ammonia (ND3, 99%) and 18O (98%) water were purchased from Cambridge Isotope Laboratories (Tewksbury, MA). All standards from stock solutions were verified by 1H NMR to ensure purity and conformational identity (
Ion Trap Mass Spectrometry. Carbohydrates were resuspended in LC-MS grade optima water and diluted to a working concentration of 10 μM in 0.1% formic acid. 180 labeling of the reducing end hydroxyl of GlcNAc was performed as described previously (Viseux, N.; de Hoffmann, E.; Domon, B. Structural Assignment of Permethylated Oligosaccharide Subunits Using Sequential Tandem Mass Spectrometry. Anal. Chem. 1998, 70, 4951-4959). Samples were analyzed on a LTQ Orbitrap mass spectrometer (Thermo Fisher Scientific) by direct infusion at a rate of ˜5 μL/min. The protonated precursor ion was subjected to CID using a range of normalized collision energies (CE) of 15-20. Full (MS1) scans were acquired followed by selection of the most intense fragment ions for further fragmentation with up to four rounds of MS/MS (MS4). All the multistage tandem MS experiments were performed in triplicate. Spectra were extracted and analyzed using Xcalibur software. MS analysis was coupled to liquid chromatography (Waters Acquity I-class) to resolve α/β anomers. A volume of 1 μL of a 10-50 μM solution of each was injected in pure water and resolved over a 2.1×150 mm 300 Å BEH amide column (Waters) using a gradient of 90% B to 55% B over 20 min (A, water with 0.1% formic acid; B, acetonitrile with 0.1% formic acid).
Ion Mobility-Mass Spectrometry (IM-MS). Ion mobility measurements were performed on a Waters Synapt G2-Si mass spectrometer. 50 μM glycans in 0.1% formic acid were directly infused at 5 μL/min. The sample cone voltage was optimized to generate each carbohydrate fragment ion of interest (m/z 366 for Gal-GlcNAcs or 350 for Fuc-GlcNAcs) and mass selected using the quadrupole to avoid any artifacts of ion decay during or after the IM stage. IM measurements in different gases were collected using the following settings: N2 flow rate of 90 mL/min, traveling wave (TVV) velocity of 500 m/s, and height of 25 V; He flow rate of 120 mL/min, TW velocity, and height were 800 m/s and 8 V; and CO2 flow rate of 42 mL/min, TW velocity, and height were 400 m/s and 16 V. The ion current was kept below 10×105 counts/s to avoid detector saturation, which may lead to broader than expected arrival time distributions (ATDs). For isomer ATDs that indicated two well-resolved species, the relative intensity of each species was approximated by fitting to two Gaussian distributions using custom Excel (Microsoft, Redmond, WA) scripts.
Gas-Phase Hydrogen/Deuterium Exchange (gHDX). Instrumental modifications to the Waters Synapt HDMS mass spectrometer to enable infusion of ND3 and He have been described previously.32 Analytes were resuspended in Optima LC-MS grade water from Fischer Scientific (Hampton, NH) and diluted to a working concentration of 400 μM in aqueous 0.1% formic acid.
An elevated cone voltage was used to generate water loss fragment ions in the source (m/z 350 and 366) which were then mass selected with the quadrupole and fragmented in the trap ion guide. A series of acquisitions were collected using a trap collision energy of 5, 10, and 17 for Gal(β1-4)GlcNAc and Gal(β1-3)GlcNAc, 5, 10, and 22 for Gal(β1-6)GlcNAc, and 5, 10, and 15 for Fuc(α1-4)GlcNAc, Fuc(α1-3)GlcNAc, and Fuc(α1-6)GlcNAc. gHDX was performed in the transfer TW ion guide (after the ion mobility stage and immediately before the TOF region).
Transfer wave heights of 8 V and multiple traveling wave velocities (8-512 m/s−1) were used to sample a temporal-range of ˜0.1-10 ms. Unless specified, all other MS settings were source temperature 100 ° C., capillary voltage 2.5 kV, sampling cone voltage 30 V, extraction cone voltage 3.3 V, trap CE 15 V, trap bias 8 V, IM TW velocity 100 m/s, IM TW height 5 V, RF confining voltage 350 V, transfer TW height 8 V. All samples were collected in triplicate, and all carbohydrates in this study were run on the same day to minimize any intersample variation.
As an additional control to ensure identical sampling of all analytes, the “lock” channel was used to infuse TrisMix, an exchange standard, cosampled along with the analyte of interest and used to verify that the exchange conditions were identical.38 Data was batch converted using scripts in UniDec.39 Quantification of deuterium uptake, binomial fitting, and bimodal deconvolution were performed using HX-Express v2.40 Unlike solution HDX which generate a binomial isotopic distribution, the labile protons probed by gHDX can exchange at drastically different time-scales and cannot be modeled by a single binomial distribution.41 Instead a combination of two binomial distributions to account for relatively fast and slow exchanging sites in the exchange profile was applied and convoluted.
Characterization of Linkage and Anomeric Memory by Tandem MS. Two sets of isomeric disaccharides by MSn to examine their fragmentation behavior were first investigated. Both sets of disaccharides, Gal(β1-x)GlcNAc and Fuc(α1-x)GlcNAc, where x=3, 4, and 6, are compositionally identical but different in their linkage configurations (
In the case of the protonated Gal(β1-x)GlcNAcs, all three isomeric precursors fragment to the same product ions but with differing propensities. While m/z 222 is the classic Y1 ion formed by cleavage of the glycosidic bond, resulting in protonated GlcNAc, m/z 204 is formed by further loss of the reducing end of the protonated GlcNAc. The relative abundances of m/z 222 and 204 are visibly distinct for Gal(β1-6)GlcNAc compared to the other two disaccharides (
Taking it a step further, MS4 (
Interestingly, fragmentation of the 204 ion appears similar from Gal(β1-3)GlcNAc and Gal(β1-4)GlcNAc in their relative abundances and markedly distinct from Gal(β1-6)GlcNAc. Even more interesting is the MS4 of the fucosylated disaccharides (368→350→204→) that showed distinct fragmentation spectra for all three isomers (
0.65
0.65
For both sets of disaccharides, the 126/186 ratio is significantly different for the (1-6) linkage as compared to the (1-4) linkage. For the fucosylated disaccharides, there was also a significant difference even between the (1-3) and (1-4) linkages. These varying ratios indicate that the fragmentation propensity and thereby the structures of the 204 ions differ when generated from precursors of different linkages.
All experiments thus far were performed using direct infusion and thus would probe both the α/β anomers that are present in solution. To examine how the reducing end anomeric configuration influences the structures generated from the precursor, the analyses using online hydrophilic interaction chromatography (HILIC) were repeated to resolve the α/β anomers of each disaccharide (
Differences in the 126/186 ratios were found to be statistically significant between the 1-3 and 1-4 anomer pairs as assessed from triplicate measurements (p-values shown in
Characterization of Linkage and Anomeric Memory by IM-MS. Ion mobility spectrometry was applied to further characterize and compare the fragment ions from the isomeric disaccharides. The arrival time distributions (ATDs) of the m/z 366 and 350 ions from Gal-GlcNAc and Fuc-GlcNAc are shown in
To investigate the gas-phase structures of the fragment ions in greater detail, LC-IM-MS experiments were applied to resolve the α/β anomers and performed the analysis using N2, He, and CO2 as drift gases to maximize our ability to resolve subtle structural differences.42 Both anomers of the Gal-GlcNAc (m/z 366) and Fuc-GlcNAcs (m/z 350) yielded the same trends between the linkage isomers in all three drift gases, as the direct infusion data (
Taking it a step further, the mobilities of the m/z 204 ions formed from the m/z 366 and 350 ions from the LC-resolved peaks were examined. While the ATD from the (1-3) and (1-4) look indistinguishable, there is a clear shift in the ATDs from the (1-6) linked disaccharides (
Characterization of Linkage Memory by gHDX. gHDX was used as an orthogonal tool for resolving structural variations in the m/z 366, 350, and 204 fragments. The deuterium exchange kinetics for the 350 and 366 ions from each of the disaccharides is different, consistent with having different structures (
The m/z 204 fragments generated from all the disaccharides show a maximum exchange of 4 deuterium, consistent with the number of exchangeable protons but exhibit some notable differences in their gHDX rates (
The influence of the collision energy (CE) used to generate the fragment ions were also examined as this has been observed to influence gHDX kinetics (Uppal, S. S.; Beasley, S. E.; Scian, M.; Guttman, M. Gas-Phase Hydrogen/Deuterium Exchange for Distinguishing Isomeric Carbo-hydrate Ions. Anal. Chem. 2017, 89, 4737-4742). The profiles of the 366 and 350 ions are indeed offset by altered CE, especially with the 1-6 linkage structures (
Multiple Conformations of Protonated Disaccharides. Computational and structural studies have provided a wealth of information on carbohydrate fragmentation (Bythell, B. J. et al., 2017; Struwe, W. B. et al., 2016; Rabus, J. M.; Abutokaikah, M. T.; Ross, R. T.; Bythell, B. J. Sodium-cationized carbohydrate gas-phase fragmentation chemistry: influence of glycosidic linkage position. Phys. Chem. Chem. Phys. 2017, 19, 25643-25652; Mucha, E.; Stuckmann, A.; Marianski, M.; Struwe, W. B.; Meijer, G.; Pagel, K. In-depth structural analysis of glycans in the gas phase. Chemical Science 2019, 10, 1272-1284; Rossich Molina, E.; Eizaguirre, A.; Haldys, V.; Urban, D.; Doisneau, G.; Bourdreux, Y.; Beau, J.-M.; Salpin, J.-Y.; Spezia, R. Characterization of Protonated Model Disaccharides from Tandem Mass Spectrometry and Chemical Dynamics Simulations. ChemPhysChem 2017, 18, 2812-2823; Yamagaki, T.; Fukui, K.; Tachibana, K. Analysis of Glycosyl Bond Cleavage and Related Isotope Effects in Collision-Induced Dissociation Quadrupole-Time-of-Flight Mass Spectrometry of Isomeric Trehaloses. Anal. Chem. 2006, 78, 1015-1022; Fentabil, M. A.; Daneshfar, R.; Kitova, E. N.; Klassen, J. S. Blackbody Infrared Radiative Dissociation of Protonated Oligosaccharides. J. Am. Soc. Mass Spectrom. 2011, 22, 2171-2178). A set of disaccharides structures that are common motifs within many glycoconjugates have been examined here. An emphasis was placed on the behavior of the water loss (B-type) fragments as these are generated in high abundance during CID of protonated glycoconjugates and are often used as diagnostic ions for identifying glycopeptides (Nwosu, C. C.; Seipert, R. R.; Strum, J. S.; Hua, S. S.; An, H. J.; Zivkovic, A. M.; German, B. J.; Lebrilla, C. B. Simultaneous and Extensive Site-specific N- and O-Glycosylation Analysis in Protein Mixtures. J. Proteome Res. 2011, 10, 2612-2624). The 180 labeling experiments (
The 350 and 366 ions can sample multiple conformations. This is most evident from the IM-MS and gHDX data of the (1-6) linked structures and to some extent in the (1-3) linked structures. The distribution of the two conformers of the (1-6) linked 366/350 ions is dependent on the collision energy used to generate the fragments (
The large difference in the subpopulations seen by IM-MS for the (1-6) structures could be attributed to the extra rotational degree of freedom (O6-C6-C5), which bestows additional flexibility allowing a wider range of extended conformations, whereas the (1-3) and (1-4) are more constrained and can only access fewer conformations (details below). The discovery of “anomeric memory” has revealed a new paradigm where carbohydrate fragment structures are heavily influenced by the stereochemistry at leaving groups. Despite the loss of the reducing end, the original anomeric configuration influences the structure of B-type ions (Gray, C. J. et al., 2017; Ujma, J. et al., 2019).
This anomeric memory effect is directly observed in the water-loss B ions in the anomer-resolved LC-MS data. Interestingly, the stereochemistry at the anomeric end influenced nearly all of 350/366 ions as seen by IM-MS. In the case of the (1-4) and (1-3) linkages, the effect is a shift of the seemingly single ATD, whereas with the (1-6) linkage, it influences the relative intensity of each partially resolved peak (
Linkage Memory in Carbohydrate Fragments. The most intriguing finding from this study was obtained by examining the product ion resulting from a second round of fragmentation of the disaccharides. The m/z 350 and 366 ions fragment primarily to an abundant Y-type ion corresponding to the GlcNAc that has already lost its reducing end hydroxyl (m/z 204). By the methods employed, the structure(s) of the 204 ion generated from each linkage isomer was distinct, revealing that carbohydrate ions not only retain anomeric memory but also a linkage memory. Specifically, the 204 ions generated from the (1-6) disaccharides showed a longer ATD, indicating that they have an extended conformation compared to the other two 204 ions (
The uniqueness of the 204 ion of the (1-6) linked disaccharides is also highlighted in subtle, but significant, differences in the gHDX profiles of the 204 ion (
In some cases, the properties of the 204 ion revealed both linkage and anomeric memory. Particularly with the (1-4) linked 350 and (1-3) linked 366 disaccharides, the fragmentation propensity of the 204 is distinct for the α/β anomers, despite two rounds of fragmentation since the initial loss of the reducing end. At this stage, the GlcNAc has lost both its reducing end, which confers the α/β anomericity, and the sugar at the nonreducing end, which defined its linkage connectivity. Nevertheless, the properties of the 204 ion are characteristic of both its former anomericity and linkage connectivity, and thus it is encoded with memory from both ends.
In fact, not only does the attachment at a particular linkage site impact the resulting Y-type fragment ions, the linkage stereochemistry and identity of the attached sugar moiety also appear to matter. The CID products of the 204 ion from Gal(β1-3)GlcNAc and Fuc(α1-3)GlcNAc (
Further support is provided by the gHDX comparisons of the differently linked 204 ions of Gal-GlcNAc and Fuc-GlcNAcs, which show subtle differences for all six m/z 204 ions (
Structural Rationalization of Linkage Memory. The mechanisms underlying linkage memory tie back to the structure(s) of the m/z 204 ion. Gray et al. proposed the presence of various bridged, open ring, and enol structures in the ensemble where the relative abundances of these structures is influenced by the original anomeric configuration (Gray, C. J. et al., 2017). Indeed, the present studies together with previous structural studies of protonated GlcNAc (Bythell, B. J. et al., 2017; Mookherjee, A. et al., 2018) can be used to rationalize the linkage memory. With disaccharides, the initial loss of water to generate m/z 350 or 366 may also lead to the formation of bridged structures (
In the case of the (1-4) linkage, there is no hydroxyl at the O4 position and thus no O4-C1 bridged structure at the GlcNAc can form. Similarly, the (1-6) linked structure cannot form the O6-C1 bridged structure. Previous mapping of the fragmentation pathways of GlcNAc revealed that the 204 ion dissociates through two competing pathways to generate either (1) primarily m/z 186 through water loss or (2) m/z 126 through a ring rearrangement reaction (Mookherjee, A. et al., 2018). The O4-C1 bridge structure was proposed to initiate the ring rearrangement to form m/z 126. From current data, the (1-4) linked disaccharides generated the lowest amount of 126 (
It should be emphasized that the reaction mechanisms of the formation of the 350/366 ions and its tentative structures proposed here are likely oversimplified, yet they provide a plausible explanation for the observed linkage memory in the subsequent 204 ions.
The direct observation of multiple gas-phase structures from several disaccharides further strengthens the existing argument that carbohydrate fragment ions exist as ensembles of structures (Bythell, B. J. et al., 2017; Gray, C. J. et al., 2017; Rossich Molina, E. et al., 2017; Fentabil, M. A. et al., 2011). The structural ensemble of both B- and Y-type fragments are influenced by the identity of their precursors and both the reducing and nonreducing ends. Even an apparently simple chemically homogeneous structure can form several conformers that are poorly, partially, or well-resolved in the gas-phase. Furthermore, the presence of multiple conformers of both parent and fragment ions will have to be considered when benchmarking properties of carbohydrate ions, such as IM databases seeking to standardize collision cross section values.
Though protonated carbohydrates have proven more complex than metal adducted or derivatized carbohydrates, a fundamental understanding of carbohydrate fragments and the principles that govern their formation will be useful not only for structural studies but for the development of much needed technologies to characterize the complex biological functions of the diverse glycan and glycoconjugate repertoire. Overall, the diagnostic CID patterns, ion mobilities, and gHDX behavior of the differently linked Y fragments illustrate the potential of fragment ions in determining intact precursor carbohydrate structures.
A database of fragmentation ratios for structural elucidation. Data sets on a broad range of glycan standards representing biologically relevant sialylated glycans found on both O-linked and N-linked glycans have been exhaustively collected. All data were collected using collision induced dissociation (CID) within an ion trap at a wide range of collision energies (CE) to ensure the ratios we report are CE-independent. From this extensive dataset the most reliable ion ratios that are diagnostic of glycan structures have now been computed (Table 3).
Data from both MS2 and MS3 spectra were collected to ensure ratios are reliable at different stages of MS, which can be observed using some larger sialylated oligosaccharides where MS2 selection and fragmentation of the 366 ion produces similar results to MS3 spectrum where the 657 ion is first selected, fragmented and the 366 ion is further selected and fragmented (bold entries in Table 3). By using a combination of the fragment ion ratios it is possible to distinguish (2-6) vs. (2-3) linked sialylation, as well as 1-3, 1-4, and 1-6 linkage between galactose and N-acetylglucosamine (GlcNAc). Lastly, a metric has now been identified using the 145 and 163 ions generated during fragmentation of N-acetylgalactosamine (GalNAc) containing disaccharides that can differentiate between 1-6 and 1-3 linkage, which has thus far not been possible. The errors in the table reflect replicates among different collision energies, thus ensuring these ratios to be useful for structural determination with a wide range of acquisition settings.
Acquisition protocol for glycopeptide LC-MSn. With the aim of making MS3 and MS4 feasible on an LC timescale with complex samples, data-dependent acquisition protocols have now been established within Xcalibur (Thermo) to identify, select, and subsequently target glycopeptides for MS3 and MS4 analysis. Glycopeptide obtained from a combined Operator and trypsin digest of bovine fetuin were resolved over C18 nanoLC chromatography.
These proteases were found optimal for generating several glycopeptides containing a single O-linked glycan. Both MS3 and MS4 spectra could be obtained from data-dependent analysis (
The plots show the expected relationship: the more counts of the ions the lower the error associated with each calculated ratio (
In various implementations, a multi-stage tandem MS approach is established that integrates characteristic fragment ion ratios and analytical software tools to provide detailed glycan structural analysis. This approach utilizes existing MS instrumentation that is already widely available within glycobiology and proteomics communities, and therefore can be seamlessly adopted by researchers.
In one implementation, a database of fragment ion abundance ratios at the MS3 and MS4 level for discrimination of isomeric protonated glycans using collision induced dissociation (CID) is established. A library of commercial synthetic oligosaccharides, purified milk oligosaccharides, and glycopeptides are used to catalogue the fragmentation patterns of various structures that encompass biologically relevant carbohydrate structures. This study is conducted on two ion trap MS platforms under different conditions to test the reproducibility and robustness of fragment abundance ratio metrices across different platforms.
In one implementation, a LC-MS acquisition protocol for obtaining maximum glycan structural information in a short time window is developed. Glycopeptides from well-studied glycoproteins are analyzed by LC-MS protocols that trigger subsequent multistage tandem MS (MSn) upon detection of specific glycan fragment ions. A combination of MSn scans are optimized to assess the feasibility of performing the MSn steps on a chromatographic timescale and the cleanest (highest signal to noise) and most informative ions to use for structural interpretation are identified.
In one implementation, Byonic and Byomap software, which Protein Metrics' tools for detached glycan and glycopeptide analysis, respectively, are modified to output glycan/glycopeptide fragment peaks, intensities, and matched glycan compositions. Prototype software are developed to score glycan structures that best explain the observed MSn data.
As shown in
However, MS often cannot differentiate among potential structural isomers, so glycan structural details remain ambiguous and are only inferred from likely biological pathways. Alternative methods for complete detailed structural elucidation of glycans require their prior release from the glycoprotein: a step which sacrifices linkage information. Previously, there was no single approach that could provide both detailed structural analysis of glycans and their specific attachment site to the protein (‘site-specific’ glycan analysis). A MS-based approach compatible with existing proteomics platforms that could distinguish subtle glycan isomers has the potential to reduce the ambiguity in assigning glycan structures, ushering a new era in glycoproteomics. With this in mind, fragment ion abundances of underivatized protonated glycans can be explored to distinguish glycan isomers. While MSn for structural elucidation of carbohydrates has been well-established for some time, it has largely been limited to examining permethylated or metal adducted oligosaccharides (Reinhold, V., Zhang, H., Hanneman, A. & Ashline, D. Toward a Platform for Comprehensive Glycan Sequencing. Molecular & Cellular Proteomics: MCP 12, 866-873, doi:10.1074/mcp.R112.026823 (2013)), which is not amenable to site-specific glycan analysis as glycoproteomics is performed on protonated underivatized glycopeptides.
Protein Metrics and Bios (
Glycopeptide analysis was performed in Byonic, which handles LC-MS/MS data with many fragmentation modes including CID, high energy collision dissociation (HCD), electron transfer dissociation (ETD), and ETD with HCD (EThcD). Carbohydrate fragments were annotated and provided some structural information.
Previously, Byomap and Byonic had two at least two limitations: 1) glycan composition is determined automatically, but exact structural assignment is left to the user; 2) tandem mass spectra are analyzed individually and independently. These limitations can be addressed through implementations of the present disclosure.
Several recent reports have highlighted the use of ion abundance ratios for protonated carbohydrate ions to discern between classes of isomers (Halim, A. et al. Assignment of Saccharide Identities through Analysis of Oxonium Ion Fragmentation Profiles in LC-MS/MS of Glycopeptides. Journal of Proteome Research 13, 6024-6032, doi:10.1021/pr500898r (2014); Mookherjee, A., Uppal, S. S. & Guttman, M. Dissection of Fragmentation Pathways in Protonated N-Acetylhexosamines. Anal Chem 90, 11883-11891, doi:10.1021/acs.analchem.8b01963 (2018); Pett, C. et al. Effective Assignment of alpha2,3/alpha2,6-Sialic Acid Isomers by LC-MS/MS-Based Glycoproteomics. Angewandte Chemie (International ed. in English) 57, 9320-9324, doi:10.1002/anie.201803540 (2018)). However, the previous approaches are limited with respect to information content and reproducibility across different MS platforms.
In one implementation, CID performed in an ion trap mass analyzer can be used for reproducible measurement of fragmentation propensities. Due to resonance excitation, the primary fragment ions generated are not activated further so subsequent cleavage pathways are limited. This enables more reproducible fragmentation across different instruments. In contrast, in beam-type CID, as performed in a quadrupole (e.g., in Q-TOF), or in HCD, primary fragment ions are further activated and can undergo extensive secondary fragmentation. While this is beneficial because it generates more types of ions, it can hinder reproducible fragmentation that is essential for reliable structural assignments.
In one implementation, a combination of MSn spectra from a glycopeptide precursor is collected. Glycopeptides generate several carbohydrate oxonium-type fragment ions that are often used for recognizing glycopeptides (Pap, A., Klement, E., Hunyadi-Gulyas, E., Darula, Z. & Medzihradszky, K. F. Status Report on the High-Throughput Characterization of Complex Intact O-Glycopeptide Mixtures. J Am Sac Mass Spectrom 29, 1210-1220, doi:10.1007/s13361-018-1945-7 (2018)).
To further interrogate the trisaccharide structure, the m/z 366 is isolated and fragmented to produce another key set of ions: m/z 126, 138, 168, and 186 (
Furthermore, the m/z 204 from either 366 or 657 was isolated for further fragmentation (MS4). This step provides additional ion ratios that can be used to assign the identity of the N-acetylhexosamine (GlcNAc vs. GalNAc as seen in
In implementations, three aims were achieved to evaluate the feasibility of developing a reliable MSn tool incorporated with glycoproteomics software. Extensive MSn data were collected on a variety of glycan samples. Optimal LC-MSn acquisition protocols were developed for glycopeptides. In parallel, software was implemented to extract, curate, and query MS″ information for glycan structural prediction.
Aim 1: Building a database of fragmentation ratios for structural elucidation. MSn was first collected on synthetic carbohydrate standards, purified milk oligosaccharides, and released glycans from glycoproteins. Subsequently, MSn data was collected on glycopeptides from proteolytic digests of well-studied glycoproteins including: Bovine Fetuin, Erythropoietin, C1 inhibitor, hemopexin, GP1 b alpha, bovine submaxillary mucins, and porcine gastric mucins (Riley, N. M. et al., Journal of Proteome Research 19, 3286-3301, doi:10.1021/acs.jproteome.0c00218 (2020); Royle, L., Dwek, R. A. & Rudd, P. M. Determining the structure of oligosaccharides N- and O-linked to glycoproteins. Curr Protoc Protein Sci Chapter 12, Unit 12 16 (2006); Huang, L. J. et al, Identification of protein O-glycosylation site and corresponding glycans using liquid chromatography-tandem mass spectrometry via mapping accurate mass and retention time shift. Journal of chromatography. A 1371, 136-145, doi:10.1016/j.chroma.2014.10.046 (2014)). Standards were analyzed by LC-MSn using hydrophilic interaction chromatography (HILIC). This step helped to minimize potential interference from sample impurities and also resolve the α/β anomers that exist on the reducing end, which can influence fragmentation propensities (Mookherjee, A. et al., Anal Chem 90, 11883-11891, doi:10.1021/acs.analchem.8b01963 (2018); Gray, C. J. et al. Bottom-Up Elucidation of Glycosidic Bond Stereochemistry. Anal Chem 89, 4540-4549, doi:10.1021/acs.analchem.6b04998 (2017)). This ensures that glycans were structurally well-defined and homogeneous so that fragmentation data are reliable.
Fragmentation data were obtained on two ion trap platforms: a Thermo L TQ ion trap and a Thermo Fusion Orbitrap. Access to the L TQ allowed the performance of much of the MSn intensity ratio mapping and sample screening and optimization steps Access to a Thermo L TQ Orbitrap and nano LC systems are also available. While preliminary data suggested that the intensity ratios are similar across different ion trap platforms, having MSn data sets from two different commonly used MS instruments added rigor to this study and ensured downstream reproducibility. Each sample was collected with multiple dilutions and across a range of CEs (20-60). Other parameters that may influence fragmentation propensities are also adjusted including He pressure, trap Q, and ion transfer optics to understand their impact and ensure all potential sources of variability are accounted for. Variability in fragment ratios due to source settings, ion optics, gas pressure, collision energy, and across ion trap platforms allow the establishment of ‘ratio thresholds or bounds’ and a “ratio range” for each specific carbohydrate structure in the MS3 database, that was used later to assess certainty when assigning structure.
One of the inherent caveats of working with protonated glycans is the well-established phenomenon of structural rearrangements during CID, particularly fucose migration. While new information regarding the mechanism of the migration process is emerging, the exact mechanism is yet be understood (Wuhrer, M., Koeleman, C. A., Hokke, C. H. & Deelder, A. M. Mass spectrometry of proton adducts of fucosylated N-glycans: fucose transfer between antennae gives rise to misleading fragments. Rapid Commun Mass Spectrom 20, 1747-1754 (2006); Mucha, E. et al. Fucose Migration in Intact Protonated Glycan Ions: A Universal Phenomenon in Mass Spectrometry. Angewandte Chemie (International ed. in English) 57, 7440-7443, doi:10.1002/anie.201801418 (2018)). Thus, fucose containing oligosaccharide ions (m/z 350, 512) were monitored specifically for potential migration events, and this also enabled better interpretation of the profiles of the original native structure.
Aim 1 was successfully performed by: 1) performing validation that fragment ion abundance ratios from oxonium ions (m/z 204, 350, 366, etc.) were unambiguously characteristic to each specific isomeric structure; and 2) determining that the fragment abundance ratios were reproducible across multiple ion trap instruments.
Aim 2. Optimize an acquisition protocol for glycopeptide LC-MSn. As a first step for benchmarking LC-MSn protocol, suitable LC conditions were set up for resolving glycopeptides. As conventional C18 chromatography is often unable to resolve isomeric glycans within glycopeptides (‘glycoforms’). HILIC and porous graphilic chromatography (PGC) were applied to resolve glycoforms (Melmer, M., Stangler, T., Premstaller, A. & Lindner, W. Comparison of hydrophilic-interaction, reversed-phase and porous graphitic carbon chromatography for glycan analysis. Journal of chromatography. A 1218, 118-123, doi:10.1016/j.chroma.2010.10.122 (2011); Huang, Y., Nie, Y., Boyes, B. & Orlando, R. Resolving Isomeric Glycopeptide Glycoforms with Hydrophilic Interaction Chromatography (HILIC). Journal of biomolecular techniques: JBT 27, 98-104, doi:10.7171/jbt.16-2703-003 (2016)). Initial experiments were to utilize data-dependent (DDA) acquisition methods to analyze eluting peptides for MS/MS, enabling the targeting of glycopeptides that contain characteristic diagnostic ions (Pap, A. et al., J Am Soc Mass Spectrom 29, 1210-1220, doi:10.1007/s13361-018-1945-7 (2018)). Subsequent DDA methods were to select glycopeptides and perform MS3 and MS4 on oxonium ions from the targeted glycopeptide precursors. When working on an LC timescale there was a limited acquisition time window during peak elution from the column (ranging from 15 seconds to over 1 minute). Though MS/MS acquisition is relatively rapid (lens to hundreds of milliseconds), the additional isolation and fragmentation steps for MS3 and MS4, along with the potential need for longer scans for improving signal to noise, limits data collection speed. It is noted that these disadvantages were platform dependent as the mass isolation and scanning speeds of the two instruments utilized here (L TQ and Fusion Orbitrap) are different, and limitations observed with the L TQ may not be present on the Fusion. Ultimately, the a set of acquisition protocols that produce the highest level of information on glycan structure in the shortest amount of time were generated and described herein.
Optimization of MSn on the Fusion Orbitrap was to incorporate the use of additional MS2 fragmentation including HCD, ETD, and EThCD for more detailed information on the peptide portion, including site-localization of glycans in cases where the attachment site is ambiguous (Riley, N. et al., Journal of Proteome Research 19, 3286-3301, doi:10.1021/acs.jproteome.0c00218 (2020)). It is noted that ETD and HCD methods and analysis software are well-established, so these are evaluated to test their synergy and limitations when combined with MSn approach for glycan structural prediction. A consequence of working within the time constraints of collecting LC-MSn data was that the standard approach for error assessment from replicates is not practical. An alternative approach for estimating an error from a single spectrum was to utilize the total signal intensity information; as signal quality correlates with precision. A dilution series of a handful of standards are performed that cover each oxonium ion of interest, each in triplicate, on both the LTQ and the Fusion to map the relationship between signal intensity (total ion counts) and precision (error from replicates). Knowing this relationship enabled each intensity ratio measured on a given MS platform to have a corresponding level of uncertainty, Therefore, if the spectra contained weak signal, this error assessment prevented erroneous interpretation or misassignment of glycan structural information.
One anticipated caveat with glycopeptide analysis is that even with various orthogonal modes of chromatography, several isomeric glycoforms may perfectly co-elute, and therefore be co-sampled. Co-isolation and fragmentation of isomeric structures can generate anomalous fragmentation propensities that could be at best uninterpretable, and at worst misleading. To account for this potential pitfall, a series of analyses were performed on two or more carbohydrate isomers mixed at different ratios to assess the overall effect on the MSn ion ratios at each stage. This helped to identify the source of the varying MSn ratios and potentially highlight any key spectral features or specific ion ratios that can reveal the presence of co-sampled isomers. This is also useful for proper analysis of complex N-linked glycans where the multiple branches may have different isomeric structures that fragment to produce the same m/z oxonium ions.
Success of Aim 2 was the validation that MS3 and MS4 can be performed on biologically relevant samples within a time frame of LC-MS and still provide the required level of information for structure prediction. Specifically, it was determined whether the majority of detectable glycopeptides from a mixture of glycoproteins will generate the signal at the MS3 and MS4 stages for reliable structural assessment.
Aim 3. Software for Glycan Structure Assignments. Software was developed using diagnostic peaks and MSn fragmentation propensities to infer glycan structure for both detached glycans and glycopeptides.
Byomap and Byonic can output key peak information (m/z's, intensities, and annotations) and composition-level glycan or glycopeptide assignments for each spectrum. The new software reads in this information, along with a database of glycan structures, and output all the structures in the database tied for the highest score. For Phase I, peak information and glycan compositions were passed in a plain text format (.csv), and software was written in Python. For Phase II, intermediate data is kept in SQLite and software was written in C++.
Key Peaks. Most of the key peaks (126, 138, 144, 204, 366, etc.) were oxonium ions with fixed m/z values. For both detached glycans and glycopeptides, however, there are also peaks with “movable” masses, that is, the glycan fragments with a reducing end label (including +18.011 Da for aldehyde or +20.026 Da for alditol) or a peptide attached. The total number of key peaks is not large, <100 for mammalian glycans, so key peaks can be represented as either peak lists (m/z and intensity pairs) or as fixed-length vectors (e.g., 4th entry is always m/z 204 intensity) with zeros for missing entries. In either case, lists or vectors were linked into a tree structure to represent the “parental” relationships in the MS″ analysis. (Links between mass spectra have many other benefits beyond MSn analysis: connecting ETD/HCD pairs, detecting in-source dissociation, combining scans to improve signal-to-noise ratio or search speed.) It may be assumed that that each spectrum included a “nearly correct” glycan composition, because glycan mass translates almost directly to composition. There are two notable exceptions: 2 deoxyhexoses (dHex2) has mass only 1.01 Da greater than Neu5Ac, and dHex1Neu5Gc1 has exactly the same mass as Hex1Neu5Ac1. Both Byomap and Byonic can confuse these alternatives, so the structure assignment code described in this implementation also corrects compositional ambiguities.
Glycan Database. Phase I used small glycan databases suitable for the target glycans and glycoproteins to be studied. Each glycan structure had complete linkage information, and uncertainty was represented simply by the list of alternate structures. This approach gives a straightforward way to utilize biological knowledge (unlikely glycans are left out) as well as a way to measure success (reduction in the number of alternatives).
The GlyTouCan database (https://lglytoucan.org) contained an accession for each level of uncertainty, and GNOme (see https:/lwww.glygen.org) provided a “subsumption ontology” for GlyTouCan accessions. Coverage, however, was not necessarily complete. For example, the glycan in
Scoring Glycan Structures. To mitigate risk, two different approaches were taken to glycan scoring: a “handcrafted” classifier, and a more automatic approach that learned classification features from less processed data. The handcrafted approach included two steps: (1) scoring topologies using diagnostic peaks, and (2) assigning monosaccharides and linkages using fragment abundance ratios. Here “topology” is used to mean a tree graph of monosaccharide nodes (e.g., HexNAc) connected by edges without linkage information. Previously (Goldberg, D., Bern, M., Li, B. & Lebrilla, C. B. Automatic determination of O-glycan structure from fragmentation spectra. J Proteome Res 5, 1429-1434, doi:10.1021/pr060035j (2006)), summed tandem MS spectra (i.e., no parental relationships) were used. Topologies were scored for detached O-glycans by (# ions observed)−ε·(# ions missing), where theoretical ions were predicted by successive loss of monosaccharides from the non-reducing termini, and ε was a small constant (e.g., 0.01) so that missing ions are used to break ties. Starting with this simple scorer, it was iteratively improved using parental relationships and peak intensities.
After step (1), the set of glycan structures were reduced to a small number of topologies; for example, the large peak at m/z 690 in
Step (2) then fills in missing information in the topologies from biosynthetic rules and available MSn spectra on both specific monosaccharides (e.g., GlcNAc vs. GalNAc, as shown in
Furthermore, a more modern, automated machine learning (ML) approach for glycan structure identification is described. This approach utilizes training data (MSn data) paired with labeled outputs (glycan structures or substructures) for supervised learning. An MSn data set was specified by fixed-length vectors of key peaks, e.g. an MS2 spectrum of 657 followed by an MS3 spectrum of 366. ML was used to produce a method for classifying unknown inputs. Several ML methods were explored, including classification trees and CNNs (convolutional neural networks). Data-intensive ML methods such as CNNs can benefit from synthetic or semisynthetic data in which a generative model (learned “adversarially”) produces training data for the classification algorithm. This “Software 2.0” approach was compared to the handcrafted approach.
The software was tested in three stages: 1) on purified disaccharides and trisaccharides; 2) tests on mixtures of released glycans from standard reference proteins; and 3) a mixture of glycopeptides from glycoperoteins described in Aim 1. The goal was automatic structural classification at human expert level performance. Numerical goals depended upon the difficulty of the problem; for example, GlcNAc vs GalNAc was relatively easy and close to perfect classification is expected. A high accuracy rate (>90%) was also observed for assigning linkage of antennary galactose (β1-3 vs. β1-4) and terminal sialic acid (α.2-3 vs. α.2-6). Correct assignment of fucosylation linkage is expected to be a more complicated iterative process, dependent upon the emerging information obtained from Aims 1 and 2, in part due to the likelihood of migration during CID.
The following clauses represent various implementations of the present disclosure.
As will be understood by one of ordinary skill in the art, each implementation disclosed herein can comprise, consist essentially of or consist of its particular stated element, step, ingredient or component. Thus, the terms “include” or “including” should be interpreted to recite: “comprise, consist of, or consist essentially of.” The transition term “comprise” or “comprises” means includes, but is not limited to, and allows for the inclusion of unspecified elements, steps, ingredients, or components, even in major amounts. The transitional phrase “consisting of” excludes any element, step, ingredient or component not specified. The transition phrase “consisting essentially of” limits the scope of the implementation to the specified elements, steps, ingredients or components and to those that do not materially affect the implementation. A material effect would cause a statistically significant reduction in the ability to obtain a claimed effect according to a relevant experimental method described in the current disclosure.
Unless otherwise indicated, all numbers expressing quantities of ingredients, properties such as molecular weight, reaction conditions, and so forth used in the specification and claims are to be understood as being modified in all instances by the term “about.” Accordingly, unless indicated to the contrary, the numerical parameters set forth in the specification and attached claims are approximations that may vary depending upon the desired properties sought to be obtained by the present invention. At the very least, and not as an attempt to limit the application of the doctrine of equivalents to the scope of the claims, each numerical parameter should at least be construed in light of the number of reported significant digits and by applying ordinary rounding techniques. When further clarity is required, the term “about” has the meaning reasonably ascribed to it by a person skilled in the art when used in conjunction with a stated numerical value or range, i.e. denoting somewhat more or somewhat less than the stated value or range, to within a range of ±20% of the stated value; ±19% of the stated value; ±18% of the stated value; ±17% of the stated value; ±16% of the stated value; ±15% of the stated value; ±14% of the stated value; ±13% of the stated value; ±12% of the stated value; ±11% of the stated value; ±10% of the stated value; ±9% of the stated value; ±8% of the stated value; ±7% of the stated value; ±6% of the stated value; ±5% of the stated value; ±4% of the stated value; ±3% of the stated value; ±2% of the stated value; or ±1% of the stated value.
Notwithstanding that the numerical ranges and parameters setting forth the broad scope of the invention are approximations, the numerical values set forth in the specific examples are reported as precisely as possible. Any numerical value, however, inherently contains certain errors necessarily resulting from the standard deviation found in their respective testing measurements.
The terms “a,” “an,” “the” and similar referents used in the context of describing the invention (especially in the context of the following claims) are to be construed to cover both the singular and the plural, unless otherwise indicated herein or clearly contradicted by context. Recitation of ranges of values herein is merely intended to serve as a shorthand method of referring individually to each separate value falling within the range. Unless otherwise indicated herein, each individual value is incorporated into the specification as if it were individually recited herein. All methods described herein can be performed in any suitable order unless otherwise indicated herein or otherwise clearly contradicted by context. The use of any and all examples, or exemplary language (e.g., “such as”) provided herein is intended merely to better illuminate the invention and does not pose a limitation on the scope of the invention otherwise claimed. No language in the specification should be construed as indicating any non-claimed element essential to the practice of the invention.
Groupings of alternative elements or implementations of the invention disclosed herein are not to be construed as limitations. Each group member may be referred to and claimed individually or in any combination with other members of the group or other elements found herein. It is anticipated that one or more members of a group may be included in, or deleted from, a group for reasons of convenience and/or patentability. When any such inclusion or deletion occurs, the specification is deemed to contain the group as modified thus fulfilling the written description of all Markush groups used in the appended claims.
Certain implementations of this invention are described herein, including the best mode known to the inventors for carrying out the invention. Of course, variations on these described implementations will become apparent to those of ordinary skill in the art upon reading the foregoing description. The inventor expects skilled artisans to employ such variations as appropriate, and the inventors intend for the invention to be practiced otherwise than specifically described herein. Accordingly, this invention includes all modifications and equivalents of the subject matter recited in the claims appended hereto as permitted by applicable law. Moreover, any combination of the above-described elements in all possible variations thereof is encompassed by the invention unless otherwise indicated herein or otherwise clearly contradicted by context.
Furthermore, numerous references have been made to patents, printed publications, journal articles and other written text throughout this specification (referenced materials herein). Each of the referenced materials are individually incorporated herein by reference in their entirety for their referenced teaching.
In closing, it is to be understood that the implementations of the invention disclosed herein are illustrative of the principles of the present invention. Other modifications that may be employed are within the scope of the invention. Thus, by way of example, but not of limitation, alternative configurations of the present invention may be utilized in accordance with the teachings herein. Accordingly, the present invention is not limited to that precisely as shown and described.
The particulars shown herein are by way of example and for purposes of illustrative discussion of the preferred implementations of the present invention only and are presented in the cause of providing what is believed to be the most useful and readily understood description of the principles and conceptual aspects of various implementations of the invention. In this regard, no attempt is made to show structural details of the invention in more detail than is necessary for the fundamental understanding of the invention, the description taken with the drawings and/or examples making apparent to those skilled in the art how the several forms of the invention may be embodied in practice.
Definitions and explanations used in the present disclosure are meant and intended to be controlling in any future construction unless clearly and unambiguously modified in the examples or when application of the meaning renders any construction meaningless or essentially meaningless. In cases where the construction of the term would render it meaningless or essentially meaningless, the definition should be taken from Webster's Dictionary, 3rd Edition or a dictionary known to those of ordinary skill in the art, such as the Oxford Dictionary of Biochemistry and Molecular Biology (Eds. Attwood T et al., Oxford University Press, Oxford, 2006).
This application claims the benefit of and priority to U.S. Provisional Application Ser. No. 63/349,851, filed on Jun. 7, 2022, which is incorporated by reference herein in its entirety.
This invention was made with government support under grant Nos. GM127579 and GM 142363, awarded by the National Institutes of Health. The government has certain rights in the invention.
| Number | Date | Country | |
|---|---|---|---|
| 63349851 | Jun 2022 | US |
