(1) Field of the Invention
This Invention concerns a DNA array and an analytical method of stress using said DNA array for the simple evaluation of degrees of stress. This Invention also concerns a method of evaluation of expression of gene groups related to certain diseases, not limiting to stress, by positioning oligonucleotides on substrate based on degree of correlation.
(2) Description of the Related Art
Increases in diseases associated with life style and atopic allergy are one of the factors that are responsible for the increase in today's medical burden to the nation. Reported also are increases in the numbers of suicides, lowering age of criminals and increases in patients with post-traumatic stress disorder (PTSD). Medical experts agree that stress play a role in background or life style-associated diseases, allergy, suicide, crime and PTSD.
Stress is defined as a reaction of the living body to sudden invasion, both as specific reaction to each invasion and as generic non-specific reaction, which has a fixed pattern regardless of the type of invasion. Stress-causing stimuli, or stressor, include abnormal temperature, burn, inflammation, immune reaction, noise, electric shock, ultraviolet light, bacterial toxin, bacteria, virus, operation, exercise, pain stimulus, physical restrain, hypoxia, hypoglycemia, ischemia, tests, interpersonal friction, deaths of relatives, loneliness, broken heart, despair, disappointment, social unrest, war, terrorism and earth quake. With advancement in knowledge of the maintenance mechanism of bodily homeostasis, it has become clear that there is a close relationship between abnormalities of the three major regulatory mechanisms of the body, the nerve, endocrine and immune system, and stress.
In conventional oligonucleotide array, it is decided first which genes are placed on chips, and then, according to the order, such as alphabetical order, designated to genes, genes are placed on a plate, such as a 96-well plate, using a spotter with several needles. In this method, although genes are lined up systematically, a step is required at the actual evaluation to confirm the positions of genes by consulting address information on files and images that show where and which genes are placed.
However, no medicophysiological diagnostic method has been developed by which the degree of stress can be evaluated objectively. For instance, blood concentrations of stress hormones, such as catecholamine and adrenocortical hormone, vary greatly among individuals and change with time. In other words, blood concentrations of stress hormones do not change uniformly in response to stress stimuli, and are known to be insufficient to be used for evaluation of degree of stress. In addition, it is extremely difficult to evaluate bodily reactions only by measuring these limited stress hormones because stress is the reaction of complex systems, requiring multilateral evaluations. Stress also is studied in the field of social psychology. Psychological tests in the form of interviews or questionnaires have been developed to evaluate degree of stress. However, it cannot be said that psychological tests substantiate sufficiently physiological reaction of the body. That is to say, currently, there scarcely are methods for objective evaluation of stress of individual persons. However, stress is an important phenomenon that is related to abnormalities of the automatic nervous system, endocrine and immune, gastric ulcer, acute lesions of gastric mucus, mental diseases and reproductive dysfunction. If it is possible to evaluate degree of stress readily at not only specialty medical organizations but also general-practitioners, health facilities at business and school and health screening centers, it is a useful measure, as feedback can be implemented in daily life at home, workplace and school. From that standpoint, development of diagnostic instruments is sought that can determine the degree of stress.
The objective of this Invention is to provide a diagnostic method, specifically, oligonucleotide array, by which degrees of stress can be determined readily and at low cost. In particular, this Invention aims at minimizing the number of DNA fragments placed on the array by specifying groups of genes, which are imperative in determination of degrees of stress, and at providing an array for stress analysis with high reproducibility and reliability. This Invention also aims at instant evaluation of the correlation between genes that are related a certain disease by devising regulations in how genes are arranged.
As mentioned above, stress is the complex reaction in which various organs, such as the nervous, endocrine and immune systems, play roles and must be evaluated from many angles. Expressed at the gene level, stress reaction, which is a phenomenon with complex sources, occurs when the on-and-off switches of groups of genes related to stress are turned on, the volume of stress-related protein increases or decreases. The body mechanism is thought to be regulated according to the balance in activities of the whole protein. In other words, abnormalities of the on-and-off mechanism in stress-related gene groups induce the abnormalities of the balance in protein activities, resulting in the abnormalities of regulation of body mechanism, or occurrence of stress. The switching on and off of genes is controlled, for example, by increases or decreases in the level of gene expression. The level of gene expression can be measured using the level of messenger RNA or the level of protein as an index. With techniques currently available, the measurement can be performed extremely easily using the level of messenger RNA as an index rather than using the level of protein. Therefore, stress is evaluated easily by observing the increase or decrease in the level of expression of messenger RNA of several stress-related genes. DNA array (also called oligonucleotide array) developed recently is the most suitable for this purpose.
Here, the state of expression is explained in detail. The state of expression is one of genotype, and expression in the term “the state of expression” means the state, where the region of genes on DNA is transcripted on to RNA, or protein is translated through transcribed RNA. The state in the term “the state of expression” means a row of “n” pieces of genes, or gene 1, gene 2, so forth, ending with gene “n”. When ON indicates that expression takes place and OFF indicated that expression does not take place, there is a row of (ON or OFF), (ON or OFF), repeating “n” times; this is called “state”. When with “n” pieces of genes, UP indicates increased level of RNA transcription, EVEN indicate unchanged, and DOWN indicates decreased, there is a row of (UP, EVEN or DOWN), (UP, EVEN or DOWN), repeating “n” times; this is called “state”. The correlation between 2 genes, any 2 among “n” pieces of genes, is “state”, that is to say, when the intensity of measurement signal of gene i is X and the intensity of measurement signal of gene j is Y, and mean of X and Y in N times of experiments are m(X) and m(Y), and standard deviations are S(X) and S(Y), respectively, the matrix of the correlation coefficient “r”, or r(i,j) is “state”. Correlation coefficient can be expressed, for example, in the following equation (1).
Changes in the above-mentioned the state expression, that is, changes in genotype induce changes in phenotype. Phenotype means phenomenon that can be observed from outside by some means. Phenotype, for example is disease or symptoms and sites of the body where symptoms appear. Disease is a pathophysiological state that physicians can diagnose by experience, such as diabetes mellitus and cancer. Symptom is a phenomenon persons feel subjectively, such as headache and abdominal pain. Symptom also is different from normal values that can be detected by test apparatus; for example, neutral fat is above the standard value in obesity. Included also in phenotype are some things that can be observed from outside by some means, excluding difference in cell configuration and in velocity of cell growth.
DNA array (oligonucleotide array) comprises plural DNA fragments (oligonucleotide) that are fixed on substrate. Each nucleotide corresponds to different genes. In measurement, complementary DNA (cDNA) fragments are synthesized in reaction with reverse transcriptase using messenger RNA as a template. At the time of the reaction with reverse transcriptase, an appropriate label binds with cDNA fragments or is incorporated when a strand is extended for labeling of cDNA (hereinafter, such cDNA is called labeled cDNA). Complementary binding takes place between oligonucleotide fixed on substrate and labeled cDNA fragments. Coordinates on substrate on which oligonucleotide are fixed, all differ. If it is known beforehand which oligonucleotide is fixed on which coordinates, increases or decreases in messenger RNA can be measured simultaneously in plural numbers of genes.
In order to achieve the objective that degree of stress is evaluated using oligonucleotide, this Inventors investigated and found that it is necessary to place on the same array many genes, or at least 30 or more different genes, and more desirably several hundred DNA fragments (oligonucleotide fragments; probe DNA). Those genes are; (1) internal; and external standard genes for proofreading (housekeeping genes), (2) stress-related genes such as heat shock protein (HSP) and hormone genes such as sex hormone that decreases under stress, (3) cytokine genes that induce immune response and inflammatory reaction, (4) genes that induce cell death, (5) genes related to anti-inflammation and wound healing, and genes related to cell growth inhibition, such as glucocorticoid, TGFβ and FGF, (6) transcription factor and signaling molecules related to immune response, (7) transcription factor and signaling molecules related to induction of cytokine, which causes cell injury, (8) transcription factor and signaling molecules related to growth inhibition, and (9) transcription factor and signaling molecules related to stress response. The above (1) to (5) are functional genes that govern specific functions in the body, and (6) to (9) are signal transfer genes that govern transmission of signals between functional genes.
This Inventors also found that by positioning DNA probes that are to be fixed on substrate according to gene classification of the above (1) to (9), results of measurement of DNA array can be understood and evaluated immediately. In addition, this Inventors found that by using leukocytes that are relatively easily collected from subjects, for whom messenger RNA is tested, as specimens for tests, degrees of stress can be easily evaluated. Thus, this Invention was completed. Concrete means to solve problems are explained below.
This Invention is an array on which plural oligonucleotides with different base sequences are fixed at known, different positions on a support medium, and the oligonucleotide array is characterized by the fact that the said oligonucleotides are those of genes mentioned in the above (1) to (9) or strands of complementary sequences on the said genes, and the base sequence of said oligonucleotides comprises bases that number at least 20 or more.
An oligonucleotide array of this Invention also is characterized by the fact that nucleotides are those of genes related to mediating factors that intermediate 3 parties of the endocrine, immune and nervous systems that are known to work in coordination in stress reaction, or those of strands of complementary sequences, and the base sequence of said oligonucleotides comprises bases numbering at least 20 or more. Examples of said mediating factors include corticotropin releasing hormone (CRH) and cytokine.
In addition, an oligonucleotide array of this Invention is characterized by the fact that oligonucleotides fixed on the same support medium have the base sequence comprising bases that number at least 20 or more, and consist of gene groups related to 2 or more different signal transfer pathways or strand groups of complementary sequences on said gene groups. Said gene groups comprise at least 2 or more types of genes that code intracellular signal transfer related protein groups that lie between cell membrane receptors and intranuclear receptors and transcription factors that are on the same signal transfer pathway.
Furthermore, this Invention is a gene expression analytical method using two oligonucleotide arrays. Using the first oligonucleotide array with plural oligonucleotides with different base sequences that are fixed on a support medium, gene expression analysis is conducted comprehensively to select gene groups that show changes in the level of expression and gene groups related to said gene groups. The second oligonucleotide array is made of oligonucleotides of the above selected gene groups, related gene groups and strands of complementary sequences on said selected gene groups and related gene groups. Said oligonucleotides have the base sequence comprising bases that number 20 or more and are fixed on a support medium. Said second oligonucleotide array also is used for gene expression analysis.
This invention was completed using the investigation results on stress response mentioned above. By using the oligonucleotide array of this invention, it is possible to easily evaluate the degree of disorder, malfunction, symptom (stress) judging from not only each gene but also focusing on the change of balance among the nervous system, endocrine system and immune system. Particularly, by arranging each gene on the substrate while taking into account two axes such as “life and death” and “inflammation and anti-inflammation”, intuitive evaluation of the results is possible. Also, since the oligonucleotide probes on the array of this invention are narrowed down to those that have a deep relationship with stress response, the number of oligonucleotide types to be used as probes for the array are greatly reduced, thus allowing to reduce the price. Furthermore, by fixing a single type of oligonucleotide in several positions as a probe, the signal intensity of multiple positions can be averaged to increase reliability. Also, by making a rule for arranging the gene groups, relationships between genes related to a certain disorder can be evaluated at a glance.
Other objects, features and advantages of the invention will become apparent from the following description of the embodiments of the invention taken in conjunction with the accompanying drawings.
In the drawings, numerals represent the following:
1. Substrate, 2. Probe DNA fixation region, 11. Probe DNA of housekeeping genes, 12. Probe DNA of stress-tolerance and survival-related genes and hormones, 13. Probe DNA of inflammation-, immune response-, and cell proliferation-related genes, 14. Probe DNA of apoptosis and cell death-inducing genes, 15. Probe DNA of gene related to anti-inflammation, wound-healing, and cell growth inhibition, 16. Probe DNA of immune response related transcription factors and signaling molecules, 17. Probe DNA of cytokine inductive transcription factors and signaling molecules, 18. Probe DNA of cell growth inhibition related transcription factors and signaling molecules, 19. Probe DNA of stress response related transcription factors and signaling molecules, 20. Fluorescence detector, 21. DNA probe, 22. Fluorescence labeled gene, 23. Supporter, 24. Example of probe positioning according to expression pattern, 25. Gene, 26. Correlation score, 27. Gene, 28. Inter-gene pass way, 29. Reagent, 30. Spotter, 31. Computer for controlling the spotter, 32. Chip (being made), 33. Chip (finished), 34. Fluorescence detector, 35. Computer for controlling the fluorescence detector, 36. Positioning information file, 37. Public database, 38. In-house database, 39. Network connected computer, 40, Probe stock, 41. Automatic dispenser, 42. Probe to be spotted, 46. Experimental results, 47. Computer for experimental data analysis.
Oligonucleotide, that is, DNA probe, is classified according to P value, FDD and SVD. The P value is a value called in statistics as significant probability, which expresses degrees of dissociation of statistics from null hypothesis in hypothesis testing. The P value is expressed between 0 and 1. The smaller the figure is the larger the dissociation is. The null hypothesis in the Specification of this application is defined as “there is no difference in the level of expression between gene A originating RNA and gene B originating RNA.” When P is 0, it means that gene A originating RNA differs from gene B originating RNA, and when P is 1, it means that gene A originating RNA is the same as gene B originating RNA. The P value can be obtained in, for example, parametric tests such as t-test and F-test or non-parametric tests such as Wilcoxon test.
Differential display is one of methods of detecting the difference in messenger RNA that expresses in cells under different conditions. The principle of the method is that messenger RNA that is reverse transcribed using oligo dT primer is combined with various primers. The combinations are amplified in PCR for comparison of band patterns in electrophoresis in each sample. When fluorescent labeling is used for signal detection, it is called fluorescent differential display (FDD). Messenger RNA that expresses can be either known or unknown.
Support vector machine (SVM) is a method based on machine learning used for classification of hand-written letters and images, and one of methods used to classify given data into plural categories. SVM is an algorithm with which differences among messenger RNA expressing in cells under different conditions are classified. Thus, SVM is an algorithm of classification that belongs to supervised methods. Similar methods include nearest neighbor, discriminant analysis, neural network and classification tree boosting bagging. Although the Specification of this application mentions SMV as the typical example, any classification methods can be used.
For example in order to evaluate degrees of stress, it is necessary to conduct highly accurate analysis of the mechanism of function of stress response. It is clearly avoided that DNA fragments that should have complementary binding with one kind of genes bind with other genes (cross hybridization). It becomes progressively difficult, as the number of genes that are fixed on a piece of array increases. Consequently, it is extremely difficult to eliminate completely cross hybridization among five-thousands to several ten-thousand genes on one DNA-array for detection. It became clear in investigation on sequence homology based on blast algorithm that when the base length of DNA fragments used as probes is not more than 1,000 bases, it is desirable to place less than 1,000 to 1,500 kinds of genes on one array. Therefore, if the purpose of use of DNA array is to elucidate the mechanism of action of stress response, it is desirable to collect the least possible number of genes that are related to the mechanism of action of stress response and use only these genes for array. It is not desirable to place on array genes that are not related to stress response, which will result in increases in cost of making probes, leading to eventual increases in cost of oligonucleotides. In this Invention, the number of kinds of oligonucleotides used as probes on array can be restricted, any one kind of oligonucleotides can be fixed as probes at plural positions. Signal intensity can be obtained from plural positions, increasing reliability.
Concrete examples of positioning methods of gene groups are explained below.
1. Positioning Methods of Gene Groups Using Bioinformatics.
1) According to Gene Functions (Classification No. 1)
For example, gene groups are positioned as shown in
Classification of genes into any among 11 to 19 is decided based on terminology defined in the ontology database constructed by the International Ontology Consortium. Gene related ontology can be searched on PubGene, which is one of publicly offered ontology database, or Gene Ontology (GO). The PubGene database connects gene with ontology through textual analysis of Medline, OMIM, etc. (refer to Tor-Kristian Jenssen et al. A literature network of human genes for high-throughput analysis of gene expression. Nature Genetics, vol. 28, pp21-28). In PubGene classification, HSPA1A, for example, which is a heat shock protein (HSP), is closely associated with Heat shock protein (GO No. 0003773) in the Functional Annotation and with transcription (GO No. 006350) and immune response (GO No. 0006955) in the Cell Process Annotation. Another HSP, HSPA1B, is classified to Heat shock protein (GO No. 0003773) in the Functional Annotation and apoptosis (GO No. 0006915) in the Cell Process Annotation. Therefore, according to the Functional Annotation in PubGene, for example, Both HSPA1A and HSPA1B belong to the same stress related gene, that is, heat stress protein. The two are classified to No. 12 Stress and survival-related genes and hormone genes. According to the Cell Process Annotation in PubGene, on the other hand, HSPA1A belongs to No. 13 Immune response related genes, and HSPA1B to No. 14 Apoptosis and cell death related genes. Ontology in the Functional Annotation and Cell Process Annotation in PubGene is listed in the order of scores. Therefore, ontology with the largest score or several numbers of ontology with relatively large scores are selected for classification. Along with PubGene, any tool or database can be used to search ontology based on gene names.
2) Gene Positioning within Fixation Regions (Classification No. 2)
The final positioning of genes that are distributed on fixation regions in the above 1) is decided according to any one or the combination of two or more of the following information; (1) gene correlation scores obtained through database, (2) information on pairing of ligand and receptor, (3) information on protein-protein interaction, and (4) information on gene pathway. The list of genes contained at each fixation region is obtained in Classification No. 1. Genes on the list are sorted out in the order of gene names (or gene symbol names) or put in order impromptu. For example, gene A on the top of list is fixed at the pre-determined position, such as at the corner or center of its fixation region. Then, genes that have strong correlation with gene A are sought. Supposing that gene B and gene C have strong correlation with gene A, then these two genes are positioned next to gene A. Gene B and gene C whose positions have been decided are eliminated from the list. Gene D, which is now at the top of the list, is positioned where genes A, B and C are not positioned. In the same manner as above, Gene E and gene F that have strong correlation with gene D are sought and positioned next to gene D. By repeating the process, genes with strong correlation with each other gather closely and form clusters within each fixation region. Methods of how to search for genes with strong correlations with each other are explained below.
In the method (1) above, it is regarded that the more frequently the two genes appear in the same sentence of the same database, the stronger the correlation between two genes is. The correlation score can be obtained, for example, by looking up PubGene database (refer to Tor-Kristian Jenssen et al. A Nature Genetics. Vol. 28, pp21-28.).
Positioning based on the above (2) information on pairing of ligand and receptor means that genes which proteins have a relationship of ligand and receptor are positioned adjacent to each other, for example insulin-like growth factor 1 (IGF1) and insulin-like growth factor 1 receptor (IGF1R) or insulin (INS) and insulin receptor (INSR) are positioned adjacent to each other.
Positioning based on the above (3) information on protein-protein interaction means that positioning of genes are decided according to protein interaction databases such as, for example, UCLA DIP (Database of Interacting Proteins by University California Los Angeles, USA, refer to I.Xenarios et al. DIP: the database of interacting proteins. Nucleic Acid Research. Vol. 28, pp. 289-291, 2000). In database of interacting proteins, proteins that interact each other are connected with lines as illustrated in
Positioning based on the above (4) information on gene pathway means that genes related to intracellular and intercellular information transfer are positioned according to correlations in pathway.
In this application, gene positioning on substrate on which DNA chips are fixed can be decided according to gene functions (Classification No. 1) using ontology in PubGene database, and gene positioning within fixation regions (Classification No. 2) can be decided based on gene correlations obtainable by searching PubGene database. However, the contents of PubGene database change, as information contained in literatures keeps increasing yearly. Consequently, gene correlation scores are expected to change, every time new findings appear. Accordingly, gene positionings on the fixation substrate have to change based on the content of information in literature. The positioning of DNA chips on the fixation substrate can be decided using, aside from PubGene, any or the combination of the following; gene interaction database based on experimental results, such as the above DIP, signal transfer pathway database, and metabolic pathway database. Furthermore, database describing gene interaction that will be newly constructed in the future.
2. Positioning Methods of Gene Groups Based on Experimental Data
The above 1, demonstrates concrete examples of gene positioning on DNA chip fixation substrate using Bioinformatics and not based on experimental data. In this paragraph, gene positioning methods are described based on experimental data.
1) Data Assembling by Chips or FDD
First, 2 kinds of specimens are collected for comparison, and RNA is extracted from each specimen. Two kinds of specimens for comparison consist of, for example, specimens from patients with some disease and those from healthy persons. Specimens can be any of tissues, blood and cells that contain RNA. It is desirable for the consideration of individual differences to collect plural numbers of specimens, or as many as possible, from both patients and healthy persons. Gene expression in specimens from both subjects is analyzed using DNA chips or FDD. The DNA chip can be, for example, cDNA chips that uses as a probe the PCR-amplified DNA fragments using cDNA clone as template, or can be oligo chips that are used by Aphimetrics Co. in the USA. It is desirable to have gene probes of DNA chips as many as possible for the utmost analysis of the state of gene expression. For example, human genes are thought to number 30,000 to 40,000 and the transcription products to total approximately 100,000 including alternative splicings. Therefore, it is ideal to use DNA chips loaded with several tens of thousands of gene probes. If it is not possible to use DNA chips with a large number of gene probes, the state of gene expression can be analyzed, for example, in transcription products using FDD.
2) Gene Positioning Based on Statistical Analysis
This paragraph describes methods of positioning of DNA chips on the fixation substrate in the Specification of this application, which are based on the results of measurement of the state of expression in 2 kinds of comparable specimens using DNA chip method or FDD method described above. When each of 2 kinds of specimens are plural, results of measurement are statistically analyzed and used for positioning of genes on the fixation substrate. Original data obtained in DNA chip experiments comprise the signal intensity of the 2 kinds of comparable specimens and ratios between the signal intensity of the 2 kinds of specimens. For example, when specimen 1 is labeled with fluorescent dye Cy3 and specimen 2 with Cy5, data obtained are Cy3 fluorescent intensity originated from specimen 1, Cy5 fluorescent intensity originated from specimen 2, and Cy3/Cy5, the ratio of fluorescent intensity.
Original data obtained in FDD experiments comprise the intensity of bands of lanes in electrophoresis of specimen 1, that of specimen 2, and the ratios between the intensities of bands derived from 2 specimens. For example, when both specimens 1 and 2 are labeled with the same dye (Cy3, for example), data obtained are Cy3 fluorescent intensity originating from specimen 1, that originated from specimen 2, and the ratio between 2 fluorescent intensities. Statistical analysis is conducted using (1) fluorescent intensity ratios or (2) fluorescent intensity originated from specimens 1 and 2.
TABLE 39 shows results of experiments using 2 kinds of specimens that are analyzed based on the above (1) fluorescent intensity ratios. Columns in TABLE 39 are, from the left, gene name (symbolic name in Unigene), mean fluorescent intensity ratios, standard deviation (SD) and CV value (SD/mean). In TABLE 39, specimen 1 is CD3+ cell (T cell) originating from peripheral blood of 3 healthy subjects, and specimen 2 is CD3− cell (lymphocytes other than T cell) originating from peripheral blood of 3 healthy subjects. Gene groups in specimens 1 and 2, the fluorescent intensity ratio of which is 3 or higher in the state of expression, are listed in the order of the mean value. TABLES 39 shows results of experiments using DNA chips with several thousands genes. Therefore, similar values can be obtained from other several thousands genes aside from those in TABLE 39, and these genes can be listed in the ascending or descending order of mean values, as one pleases. In TABLE 39, the fluorescent intensity ratios in the above (1) are those of CD3− cells/CD+ cells, and in (2) are those of CD+ cells/CD− cells. When DNA chips are newly created, the whole or part of several thousand gene probes can be positioned on the DNA chip fixation substrate according to the ascending or descending order of the mean fluorescent intensity. For example, probes can be positioned selecting genes among several thousand genes with the fluorescent intensity ratio 2 or higher, that is, the difference in gene expression between specimens 1 and 2 is twice or more.
TABLE 40 shows results of experiments using 2 kinds of specimens same to TABLE 39 that are analyzed based on the above (2) specimen 1-originating fluorescent intensity and specimen 2-originating fluorescent intensity. Columns in TABLE 40 are, from the left hand side, gene name (symbolic name in Unigene), t value that is statistic value obtained in t-test, and P value that is significant probability derived from t value. Genes with P value, or significant probability, 0.003 or lower, are listed in the ascending order. TABLE 40 shows the results of experiments using DNA chips with several thousands of genes. Therefore, similar values are obtained from other several thousands of genes aside from those in TABLE 40, and these genes can be listed in the ascending or descending order of t value or P value, as one pleases. When DNA chips are newly created, the whole or part of several thousands of gene probes can be positioned on the DNA chip fixation substrate according to the ascending or descending order of t value or P value. Gene probes can be positioned on the DNA chip fixation substrate in the similar way using other statistic values obtained in testing methods other than t test, such as rank sum test.
When DNA chips are newly created, the whole or part of several thousands of gene probes can be positioned on the DNA chip fixation substrate according to the ascending or descending order of t value. For example, suppose the significant probability P is lower than 0.2, that is, the difference in the gene expression between specimens 1 and 2 is zero, probes can be positioned selecting genes among several thousands of genes with the 20% probability that the supposition is incorrect. Probe positioning can also be decided based on results of FDD in the same process as in TABLES 39 and 40. Aside from statistic analysis, using support vector machine (SVM) algorithm, well known in the field of machine learning, weight matrix factor (wi) corresponding to each gene is obtained and probe positioning can be decided in the ascending or descending order of wi. Probe positioning can be decided using any method, aside from statistic analysis and machine learning, that can rank genes based on experimental data.
As regards effects of stress on the body, various genes related to the nervous, immune and endocrine systems are thought to play roles. Details have been unclear. Therefore, this Inventors investigated changes in gene expression profile in human peripheral blood samples by creating array with a large number of genes/EST as probes and selected genes, the expression of which changed markedly as stress load increased. As the probes of array, 15,000 kinds of genes/EST were purchased from IMAGE Consortium and used to create DNA probes array for screening. Exercise stress and gastric ulcer stress were chosen as typical stress stimulants.
With respect to exercise stress, subjects on bicycle ergometers received for a continuous 60 minutes the load of approximately 80% (80% VO2max) in relative value, when the maximal individual oxygen intake (VO2max, the maximum value of oxygen taken up by blood in unit time) is defined as 100%. When measured in actual subjects, the 80% VO2max is approximately 180 watts at bicycle ergometer intensity. Pulse rates during exercise were between 150 and 175/min. The lactate threshold (LT) corresponds to approximately 60% VO2max, and heart rates between 110 and 130/min. Therefore, the exercise load of 80% VO2max for 60 min was thought to be sufficient intensity as exercise stress load. Peripheral blood 50 cc was collected within 5 min after the completion of exercise. Messenger RNA was extracted from leukocyte and reverse transcribed in prescribed methods for DNA synthesis. At reverse transcription, fluorochrome-labeled DNA was synthesized using dCTP labeled with fluorescent dye Cy-5 (labeled cDNA: exercise stress load). Meanwhile, prior to exercise stress load, peripheral blood 50 cc was collected from the same subjects. Messenger RNA was extracted in the same process and reverse transcribed using Cy-3 labeled dCTP for cDNA synthesis (labeled cDNA: control).
Equivalent weight of labeled cDNA of exercise stress load and that of control were mixed, placed on the above-mentioned DNA probe array for screening, and hybridized under prescribed conditions. After rinsing, fluorescent intensity at each spot was measured using a laser scanner for evacuation of kinds and levels of genes expressed in cDNA of exercise stress load and that of control. TABLE 1 shows genes that had changes in the level of expression more than twice, when the level of expression was compared between the two. The increases in the level of expression in TABLE 1 are standardized assuming that the levels of expression of housekeeping genes, such as β-actin, HPRT and GAPDH, is stable. The level of expression of these genes is thought to be stable under various stimulations.
Under exercise stress, the increases in the level of expression were observed in genes related to hormones of the hypothalamic-posterior pituitary system such as vasopressin and anginine vasopressin, adrenocorticotropic hormone (ACTH) receptor genes and genes related to glucocorticoids (cortisol). The level of expression also increased in genes related to catecholamine such as monoamine oxidase. In addition, the expression increased in cytokine genes such as interleukin 6 (IL-6), transcription factors such as NF-KB, and HSP70 and HSP90, heat shock proteins. Observed also were changes in proton pump genes, that is, decreases in Ca2+ATPase, and increases in expression of apoptosis related genes called GADD34.
With respect to gastric ulcer stress, messenger RNA was extracted from peripheral blood 50 cc collected from patients with gastric ulcer, and reverse transcribed in prescribed methods for cDNA synthesis. At reverse transcription, fluorochrome-labeled cDNA was synthesized using dCTP labeled with fluorescent dye Cy-5 (labeled cDNA: gastric ulcer stress). Meanwhile, peripheral blood 50 cc was collected from healthy subjects who do not have gastric ulcer. Messenger RNA was extracted and reverse transcribed using Cy-3 labeled-dCTP for cDNA synthesis in the same process. (labeled cDNA: control).
Equivalent weight of labeled cDNA of gastric ulcer stress and that of control were mixed, placed on the above-described DNA probe array for screening and hybridized under prescribed conditions. After rinsing, fluorescent intensity at each spot was measured using a laser scanner for evaluation of kinds and levels of gene expression in cDNA of gastric ulcer stress and that of control. TABLE 2 shows genes that had changes in the level of expression more than twice, when the level of expression was compared between the two. The increases in the level of expression in TABLE 2 are standardized assuming that the level of expression of housekeeping genes, such as β-actin, HPRT and GAPDH, is stable. The level of expression of these genes is thought to be stable under various stimulations.
Under gastric ulcer stress, the increases in the level of expression were observed in genes related to hormones of the hypothalamic-anterior pituitary system such as CRH, and genes related to ACTH and glucocorticoid. Conversely, there were little changes in the level of expression of genes related to hormones of the hypothalamus-posterior pituitary system such as vasopressin. Observed also were, as in exercise stress, increases in the expression of cytokine genes such as IL-6 and HSP70 and HSP90, heat shock proteins. The expression of ERK6, a signal transfer gene, and JUN, a transcription factor, as well as anti-inflammation related genes such as prostaglandin increased.
The above findings suggested that genes that had more than twice increases in the level of expression, in either exercise stress or gastric ulcer stress, included genes related to corticotropin-releasing hormones (CRH) such as vasopressin and oxytocin, ACTH and adrenocortical hormones such as glucocorticoid, reflecting activation of the pituitary glands and adrenal cortex by excitation of the hypothalamus. Hereinafter, the hypothalamic-pituitary adrenocortical system is called HPA system. Involvement of catecholamine related genes reflected the activation of sympathetic adrenomedullary (SAM) system. Hormones produced by the endocrine system such as HPA system and SAM system were secreted into blood and bound with hormone receptors on blood cells, increasing the expression of G-proteins and intracellular signal transfer related genes, such as adenylatecyclase and NF-κB. Finally, the expression of cytokine gene was induced. The expression of stress proteins such as heat shock protein increased as a part of stress reaction at cell level. Activation of glucocorticoid receptor by adrenocortical hormones (glucocorticoid) induced apoptosis in the calcium pathway. Changes in expression occurred in the similar gene groups under 2 completely different stresses suggested that it would be useful in analysis of complex system of stress reaction to observe changes in the expression intensity of these gene groups. That is to say, for analysis of degree of stress, DNA array is the most appropriate, on which the necessary but minimal amount of the following genes are fixed; (1) internal and external standard genes for proofreading genes, (2) stress resistant and survival related genes and hormone genes such as HSP, (3) cytokine genes, (4) apoptosis and cell death related genes, (5) anti-inflammation and cell growth inhibition related genes such as glucocorticoid, (6) immune response related transcription factor or signaling molecules, (7) cell injury-inducing cytokine inductive transcription factor or signaling molecules, (8) cell growth inhibition related transcription factor or signaling molecules, and (9) stress response related transcription factor or signaling molecules.
By dividing probe fixation regions on the support medium according to the above classification (1) to (9), persons performing measurements are able to recognize results in patterns. If probe fixation regions are not divided by gene functions, processes of displaying results are required after fluorescent signals are obtained, which include changes in positions of spots using computer, number plotting and graph display. By classifying probe genes according to functions and positioning said genes on substrate according to functions, persons performing measurements are able to judge instantly the degree of stress just by displaying fluorescent signals on the screen. Thus, simplification of equipment structure and lowering cost can be achieved easily. Proofreading is necessary in order to eliminate manufacturing variations, when plural numbers of array are created. Oligonucleotides for proofreading are called internal and external standard genes for proofreading. An example of internal standard gene for proofreading is housekeeping gene. The housekeeping gene works in coding of structural proteins and enzymes of the energy metabolism system that are necessary for cell survival. The gene is thought to exist in any cell with different differentiation. For example, β-actin, GAPDH, HPRT, α-tubulin, transferrin receptor and ubiquitin are housekeeping genes. As the gene is already present in subjects' samples such as those of leukocyte, the gene can be the internal standard for proofreading. Internal standard means substances that are already present in samples without being added from outside and can be standard at proofreading. External standard genes for proofreading are gene sequences that are not present in humans but present in plants, microorganisms and insects. For example, Arabidopsis thaliana gene, plasmid DNA, bacteriophage DNA and firefly luciferase gene are external standard. As the gene is not present in subjects' samples such as those of leukocytes, external standard genes at known concentrations are added to samples at the time of measurement to be used as external standard for proofreading. External standard means substances that are not already present in samples and added separately from outside to be standard for proofreading.
Stress related genes are proteins that are induced at the time of stress caused by physical and environmental factors such as heat shock. For example, HSP, a kind of stress protein, expresses when cells are exposed to high temperature. This HSP expresses and increases by not only external stimulation such as exposure to high temperature but also direct injection of denatured protein into cells (Anathan, J. et al. Abnormal proteins serve as eukaryotic stress signals and trigger the activation of heat shock genes. Science, 232, 252-254, 1986). That is to say, the expression of HSP is not induced by the bodily systems such as nervous, endocrine and immune systems, but by changes occurring inside cells. HSP70, a HSP, is known to have the function of inhibition of apoptosis, which is called program cell death (Mosser, D. D. Roles of the human heat shock protein hsp70 in protection against stress-induced apoptosis. Mol. Cell Biol., 17, 5317-5327, 1997). Apoptosis is a form of cell death that occurs in cells that are exposed to viral infections, oxidation stress, radiation and anticancer drugs. Apoptosis is induced by excessive stress on cells. HSP70 inhibits cell death by providing cells with stress resistance. Cells in which HSP70 expresses are not only continuously resistant to stress that was the direct cause but also resistant to other stresses (cross resistance), suggesting that HSP is the stress reaction processing mechanism that cells possess. It is extremely useful to know degrees of, or increase or decrease in, expression of stress protein, in order to evaluate degrees of stress at the cellular level. More than 30 kinds of stress proteins are known to exist. Therefore, it is desirable to fix approximately 30 or more oligo probes, including stress proteins, on the oligonucleotide array of this Invention. Stress proteins include, for example, HSP27 (small HSP), HSP40 (Hdjl), HSP47, HSP60/HSP10, HSC70, HSP70, mtHSP70, HSP90, HSP100 (GRP95), HSP150 (ORP150), Bip (GRP78) and TriC.
Genes related to cell survival include, aside from stress proteins, for example, cyclin, which regulates cell cycle, cyclin dependent kinase (CDK), CDK inhibitors (CKI) such as cyclin A, cyclin B, cyclin D, cyclin E, CDK1, CDK2, CDK4 and CDK6.
“Hormones” means organic compounds that are produced in endocrine glands, secreted in blood and carried to target organs, where microdose demonstrates specific physiological actions. Typical endocrine systems include (a) HPA system, (b) SAM system, (c) automatic nervous-pancreatic endocrine system, (d) hypothalamic-sympathetic-renin angiotensin system, (e) hypothalamic-posterior pituitary system, and (f) opioid peptide system. Hormone-related genes include, for example, vasopressin (AVP), vasopressin receptor (AVPR), CRH, CRH receptor (CRHR), MC2R, REN, TH, TSHB and TSHR.
“Cytokines” are general names of bioactive peptides that induce cell growth differentiation and are secreted by blood cells. Cytokines differ from hormones in that cytokine works near where they are secreted and blood concentrations of cytokines are equal to or lower than those of hormones. Major cytokines include granulocyte-colony stimulating factor (G-CSF), macrophage-colony stimulating factor (M-CSF), granulocyte-macrophage colony stimulating factor (GM-CSF), erythropoietin, thrombopoietin, stem cell factor (SCF), interleukin-1, -2, -3, -4, -5, -6, -7, -8, -9, -10, -11, and -12, tumor necrosis factor (TNF) and interferon.
Most of the genes with functions of inducing cell death due to stress are thought to be apoptosis-related genes, because almost all cell deaths in the body are those called apoptosis. Pathways where apoptosis occurs include calcium pathway, death signal pathway, ceramid pathway, mitochondria pathway and DNA injury pathway. In calcium pathway, phosphatidyl-inositol-3-phosphate receptor, calmodulin, ALG2 and carpine play roles. In death signal pathway, TNFα, Fas ligand, TRADD, FADD, RAIDD, FADD, RIP, RAIDD, CASP8, CASP1, CASP3, TRAMP and TRAIL are known to play roles. In ceramid pathway, stress-activated protein kinase (SAPK)/Jun terminal-N kinase (JNK) plays a role. In mitochondria pathway, Bcl-2 associated X protein (Bax2), Bcl-2, Bcl-xL, and caspase gene play roles. In DNA injury pathway, p53, p21, p51, p73 and MDM2 genes play roles. Genes related to anti-inflammation such as glucocorticoid and genes related to growth inhibition include cytochrome P450 gene 11B1 (CYP11B1), CYP11B2, CYP17, CYP21A2, glucocorticoid modulatory element binding protein (GMEB), glucocorticoid receptor repression factor (GRLF), myocilin (MYOC), glucocorticoid receptor α (NR3C1), proopiomelanocortin (POMC) and prostaglandin G/H synthase precursor.
Transcription factors and signaling molecules related to immune response, cytokine induction, growth inhibition and stress resistance include, for example, ATF/CREB transcription factor, NF-κB transcription factor, JUN gene and 14-3-3n gene. In most signal transfers, signals are generally transferred in the mechanism that protein is activated by chemical change of phosphorylation and the activated protein in turn induces phosphorylation of the adjacent protein, and so forth. Signal transfer pathways are called pathways, which are generally differentiated by naming with representative proteins on pathways. Known are, for example, MAPK (mitogen activated protein kinase), ATM (ataxia telangiectasia mutated), BCR (B cell receptor), CD40 (related to tumor necrosis factor receptor), CXCR4 (related to chemokine receptor), EGF (epidermal growth factor), EPO (erythropoietin), FAS (fatty-acyl-CoA synthase), FcEpsilon (Fc fragment of IgE receptor), IFN (interferon) alpha, IFN (interferon) gamma, IGF-1 (insulin-like growth factor-1), IL (interleukin)-2, -3, -4, -5, -6, and -18, NFκB (nuclear factor κB), NCF (nerve growth factor), p53, PDGF (platelet derived growth factor), PLC (phospholipase C), SODD (silencer of death domains), TCR (T cell receptor), TGFβ (transforming growth factor β), TNFR1 (tumor necrosis factor receptor 1), TNFR2 (tumor necrosis factor receptor 2), TPO (thrombopoietin), and Wnt (wingless/int-1). By placing genes that work in coding of proteins that are keys of these pathways on array as probes, signal transfer pathways induced by stress stimulation can be identified. In particular, for patients with chronic stress, which is caused due to dysfunction of one of the proteins on the signal transfer pathway, treatment plans can be determined by identifying the site where signal transfer is interrupted.
Another example of DNA chip is described, in which oligonucleotides are placed in such a way so that the presence or absence of stress can be understood instantly. This example of practice is one of the examples of gene positioning based on experimental data.
One week before and 5 hours after an examination, peripheral blood 10 cc was collected from one person (patient A) who became excessively tense during examination and 5 persons (control A, B, C, D and E) who did not feel much tension during the same examination. Total RNA was extracted from lymphocytes from both groups. Degrees of stress of patient A, who experienced excessive tension and 5 controls were significantly different in tests by interview conducted by a specialist. Tests by interview confirmed that 5 persons who did not feel excessive tension were not in the state of stress. In experiments with DNA chip housing several thousands genes, the state of expression 1 week before examination was compared with that 5 hours after examination in control A to E. The difference in the state of expression was small between the two. Correlation (R2) between fluorescent intensity before examination and that after examination was 0.94 to 0.97.
In order to place the oligonucleotides with the sequence of the above-described genes as probes on the array, it is necessary to decide which parts of the gene sequences are the probes. What must be taken into consideration at that time are melting temperature (Tm) and cross hybridization. In order to carry out highly accurate and highly stringent hybridization between DNA fragments fixed on the DNA array and DNA fragments originating from samples, the relationship is important between hybridization temperature (Th) and Tm of fixed DNA fragment. It is necessary that the difference between the Tm of fixed DNA fragments and the Th does not exceed 30° C. Cross hybridization occurs when there is high homology among DNA sequences. Therefore, in order to prevent cross hybridization from occurring, it is necessary that any of fixed DNA fragments and sample-originated DNA fragments have low homology with DNA fragments that do not hybridize originally with fixed DNA fragments. Furthermore, it is desirable that these DNA fragments do not contain portions that have high homology with sequences with mini hair pin structure or repetitive sequence that is known in human genes as Alu sequence. It is also necessary to calculate the homology not only between gene sequences fixed on one piece of array but also between DNA sequences and gene sequences of species listed on GENBANK etc. It is desirable not to select DNA sequences for fixed DNA fragments that have high homology with DNA sequences of gene groups that are possibly contained in samples to be measured.
DNA fragments to be fixed as probes can be synthesized in PCR reaction using commercially available cDNA library as template. Oligonucleotide array can be created from synthesized DNA fragments by preparing prescribed concentrations (0.1 to 1.0 μG/μL), and spotting using a spotter on slide glasses that are already coated with polylysine or aminosilane. Degrees of stress are studied using the above-described oligonucleotide array in the following procedure. First, peripheral blood samples are collected from several volunteers who do not have stress symptoms, and messenger RNA is extracted from leukocytes. For example, a messenger RNA pool of average healthy people can be obtained by mixing messenger RNA from many persons. This messenger RNA pool is described hereinafter in the Specification of this application as Universal Control. Next, peripheral blood samples are collected from test subjects, and messenger RNA is extracted from leukocytes. With messenger RNA of peripheral blood of test subjects, labeled cDNA is synthesized using Cy5-dCTP in reverse transcription using oligo dT primer. With messenger RNA in Universal control, labeled cDNA is synthesized using Cy3-dCTP. Test subjects' cDNA (Cy5 labeled) and Universal control cDNA (Cy3 labeled) are mixed and placed on the same, above-described oligonucleotide array for hybridization at prescribed temperature and duration. It is desirable to have hybridization temperature between 45° C. and 70° C., and time between 6 and 18 hours. Following hybridization, fluorescent intensity of Cy5 and Cy3 at each site where genes are spotted is measured using a fluorescent scanner and compared for the difference in the level of expression. Extraction of messenger RNA is performed with either monocytes, which account for 3 to 7% of leukocytes, or lymphocytes, which account for 25 to 33%. Analysis can be expected to reflect better the degrees of stress, because the monocyte has capability to differentiate to macrophage, which is an important cell in the natural immune system, and the lymphocyte to T cell and B cell, which are important cells in the acquired immune system. In addition, these leukocytes have difference cell rotation (dynamics) including maturation in bone marrow, retention time in peripheral blood and life duration. Therefore, it is possible to evaluate acute bioresponse using polynuclear leukocytes (neutrophil), short-term reaction using monocytes and relatively long-term bioresponse using lymphocytes.
Below is an example in which changes in degrees of stress in daily activities were studied in one subject.
The 793 genes (TABLE 3 and TABLE 38) were selected from GENBANK Unigene by way of key words retrieval, etc. based on the rationale described in the above “Summary of the Invention”. These genes work in coding of (1) internal and external standard genes for proofreading, (2) stress resistance and survival related genes such as HSP and hormone genes, (3) cytokine genes, (4) apoptosis and cell death related genes, (5) anti-inflammation related genes such as glucocorticoid and cell growth inhibition related genes, (6) immune response related transcription factor and signaling molecules, (7) cell injury inducing cytokine inductive transcription factor and signaling molecules, (8) cell growth inhibition related transcription factor and signaling molecules, and (9) stress response related transcription factor and signaling molecules.
Next, 793 oligonucleotide probes with highly specific and similar Tm were designed following algorithm consisting of the following procedures; 1. Reading of gene sequence files, 2. Input of salt concentrations and experimental conditions at hybridization, 3. Input of length of fixed DNA fragments, 4. Calculation of melting temperature (Tm) of fixed DNA fragments, followed by elimination from lists of candidates of DNA fragments whose melting temperature does not meet a certain range of Tm, 5. Elimination from the candidate lists of DNA fragments with specific superorganization or repetitive sequences, 6. Elimination from the candidate lists of DNA fragments with high homology with repetitive sequences such as Alu sequence, and 7. Elimination from the candidate lists of DNA fragments with high homology with other gene sequences. Each of the designed 793 sequences were synthesized using an oligonucleotide synthesizer. The total 796 kinds oligonucleotides comprising the above 793 human gene probes and 3 kinds of oligonucleotide sequences that are not present in humans (lambda DNA, pUC18 plasmid DNA and M13 mp18DNA) and are added as external standard genes for proofreading were fixed on a glass substrate in the method published below.
First, commercially available slide glasses (manufactured by Gold Seal Brand) were soaked at room temperature for 2 hours in alkaline solution (sodium hydroxide; 50 g, distilled water; 150 ml and 95% ethanol; 200 ml). The slide glasses were transferred to distilled water for rinsing three times to remove alkaline solution completely. The rinsed slide glasses were soaked for 1 hour in 10% poly-L-lysine solution (manufactured by Sigma), pulled out of solution and centrifuged at 500 rpm for 1 min in a centrifuge for microtiter plate to remove poly-L-lysine solution. The slide glasses were placed in suction incubator for drying at 40° C. for 5 minutes. Amino group was introduced on the slide glasses. The slide glasses with amino group were soaked for 2 hours in 1 mM GMBS (by PIERCE) dimethyl sulfoxide solution and rinsed with dimethyl sulfoxide. Maleamide group was introduced on the surface of the slide glasses. Using a DNA synthesizer (manufactured by Applied Biosystem, model 394), oligonucleotides to which thiol group was introduced were synthesized, and purified in high performance liquid chromatography (HPLC). Next, 1 μl of 2 μM synthesized purified oligonucleotides, 4 μL of HEPES buffer (N-2-hydroxyethylpiperazine-N, -2-ethane sulfonic acid; 10 mM, pH 6.5), and 5 μl of additive (ethylene glycol) were mixed to make spotting solution. The prepared spotting solution was spotted randomly on slide glasses using a spotter (manufactured by Hitachi Soft, SPB10 2000). The slide glasses were left at room temperature to fix oligonucleotides on slide glasses.
At that time, with the intention that persons performing measurements can instantly recognize and judge results on the array, probes were fixed in the positions that were published in
Peripheral blood 50 cc was collected from a test subject who sat up for 3 nights immediately after the sit-up completed. Immediately, messenger RNA was extracted from leukocytes and preserved at −80° C. Peripheral blood 50 cc was collected from the same test subject after a good rest for 1 week. Messenger RNA was extracted in the same manner. From messenger RNA obtained immediately after sit-up, Cy5-labeled cDNA was synthesized in reverse transcription using Cy5-dCTP. From messenger RNA obtained after good rest, Cy3-labeled cDNA was synthesized in reverse transcription using Cy3-dCTP.
Equivalent weight of Cy5-labeled cDNA and Cy3-labeled cDNA were mixed, placed on the above-described oligonucleotide array for hybridization at 62° C. for 2 hours. After rinsing, the fluorescent intensity at each spot was measured using a scanner (manufactured by GSI-Lumonics, ScanArray 5000).
Cancer can be diagnosed by using DNA chips on which genes that play major roles in cancerization, infiltration and metastasis such as cancer genes, cancer inhibition genes, growth factor, transcription factor, cytokine, apoptosis, cell cycle modulator and DNA repair genes are fixed. Particularly, by positioning at opposites to each other on the support medium the probes that hybridize with cancer genes and probes that hybridize with transcription products of cancer inhibition genes, it will become easier to recognize instantly the correlation between cancer genes and cancer inhibition genes.
Methods of Evaluation
Method for Labeling RNA to Produce cDNA
From the total RNA or messenger RNA extracted from cells and tissues, cDNA is synthesized in transcription reaction originating at primer such as oligo-dT primer using transcription enzymes. At the DNA synthesis, for example, fluorescent labels are taken up by cDNA by adding to solution deoxynucleotides to which fluorescent dyes such as Cy3-dCTP, Cy3-dUTP, Cy5-dCTP and Cy5-dUTP are bound. By hybridizing the fluorescent-labeled cDNA with probes fixed on the DNA chip substrate, RNA profile of genes can be measured using the level of fluorescence.
When the level of the total RNA or messenger RNA in cells and tissues is low, labeling is performed using RNA amplification. Amplifications include, for example, T7 or SP3 amplification using T7 or SP3 polymerase reaction. In T7 amplification, transcription originates at T7dT primer that has T7 sequence and a sequence with several tens of T bases. T7 sequence is present at the terminal of synthesized cDNA in reverse transcription. Synthesis of RNA that is complementary on cDNA and recognizes this T7 sequence is called in vitro transcription using T7. RNA can be amplified several tens to several hundreds times in in vitro transcription. Fluorescent-labeled cDNA can be synthesized using RNA obtained in this RNA amplification in the same method described above as synthesis of cDNA labeled with RNA. By hybridizing this fluorescent-labeled cDNA with probes fixed on the DNA chip substrate, RNA profile of genes can be measured by the level of fluorescence.
Manufacturing Methods of Chip
When oligonucleotide groups are positioned on the DNA chip using a spotter, it is necessary to house beforehand oligonucleotide group in a 96- or 384-well plate. Positioning of wells of the 96- or 384-well plate on coordinates on the DNA chip is determined by how a spotter is set up. When the positioning on the DNA chip is already determined based on Bioinformatics or experimental data as in the Specification of this application, it is necessary to establish the housing positions of oligonucleotide groups on a 96- or 384-well plate according to the establishment of the spotter. Conventionally, the position of oligonucleotide groups on the DNA chip was established according to the housing position of oligonucleotide groups in a 96-well plate. In the Specification of this application, conversely, the housing position of oligonucleotide groups on a 96-well plate is established according to the position of oligonucleotide groups on the DNA chip.
Methods of Display
1. Real Display
The value of fluorescent intensity of Cy5 and Cy3 labeling are displayed in quasi-color according to the intensity. In another quasi-color display, red indicates Cy5 labeling and green Cy3 labeling. On quasi-color images, boarder lines that divide plural sections can be overlapped for display. It is possible to convert images in left and right, or top and bottom inversions and rotation. Graphic displays with bars are possible according to the fluorescent intensity. Three-dimensional bar graphs can be displayed corresponding to the probe fixation positions.
2. Virtual Display
More than 2 DNA chips can be displayed on one piece. For example, using quasi-colors, the mean value of each probe, the largeness of standard deviation, correlation between one probe and another probe can be displayed in the order of the size of correlation. Re-positioning can be displayed based on information of probe positions already registered on computer.
DNA Chip Making Kit
DNA chip making kit can be offered, which is not a completed DNA kit but a partially completed one. For example, as shown in
As described above, degrees of stress can be evaluated by using the array of this Invention. It is thought that various changes in and close interaction among the three systems or the nervous, endocrine and immune systems lead to complex stress reaction. Conventional methods of measurement of specific hormones in blood are only measuring the endocrine system, but ignoring the interactions among the three, the nervous, endocrine and immune systems. Consequently, it is difficult to find the correlation between hormone level and degrees of stress in conventional methods because of the individual differences in hormone level and other reasons. In view of defects of conventional methods, this Invention took notice of not only changes in each of the nervous, endocrine and immune systems but also interactions among the three systems, particularly the balance in the interactions. Thus, this Invention was achieved.
It should be further understood by those skilled in the art that the foregoing description has been made on embodiments of the invention and that various changes and modifications may be made in the invention without departing from the spirit of the invention and the scope of the appended claims.
For example, other aspects of this invention are as follows:
(11) A method of displaying results of label detection of hybridization wherein labeled cell-derived RNA are hybridized to an oligonucleotide array comprising multiple subblock regions and oligonucleotides with different base sequences positioned to each of said multiple subblock regions, wherein said oligonucleotides are positioned according to an arrangement pattern wherein oligonucleotides with a first correlation degree are positioned closer to each other than oligonucleotides that have a lower correlation degree; and results of label detection of said hybridization are displayed.
(12) A method of displaying results of label detection of hybridization wherein labeled cell-derived RNA are hybridized to an oligonucleotide array comprising multiple subblock regions and oligonucleotides with different base sequences positioned to each of said multiple subblock regions, wherein said oligonucleotides are positioned according to an arrangement pattern wherein oligonucleotides with a first correlation degree are positioned closer to each other than oligonucleotides that have a lower correlation degree; and results of label detection of said hybridization are rearranged on a screen with determined correlation between oligonucleotides.
(13) A kit for fabrication of an oligonucleotide array comprising multiple subblock regions and oligonucleotides with different base sequences positioned to each of said multiple subblock regions, wherein said oligonucleotides are positioned according to an arrangement pattern wherein oligonucleotides with a first correlation value are positioned closer to each other than oligonucleotides that have a lower correlation value, wherein said kit comprises an oligonucleotide fixation substrate, fixation probes, probe positioning information, a spotter to spot said probes, a monitor screen to display addressing information of the spotter and detection results, or a computer with a monitor that determined the correlation value are provided.
Homo sapiens apoptosis associated protein (GADD34)
Homo sapiens myocilin
Homo sapiens vascular cell adhesion molecule 1
Homo sapiens P-glycoprotein (PGY1) mRNA (MDR1)
Homo sapiens dipeptidyl carboxypeptidase 1 (angiotensin I
Homo sapiens snake venom-like protease (cSVP) mRNA,
Homo sapiens adenylate cyclase 1 (ADCY1); Human fetal
Homo sapiens clone 24648 adenylyl cyclase mRNA, partial
Homo sapiens adenylate cyclase 3 (ADCY3)
Homo sapiens adenylyl cyclase type VI mRNA
Homo sapiens adenylate cyclase 7 (ADCY7)
H. sapiens mRNA for adenylyl cyclase
Homo sapiens adenylate cyclase 9 (ADCY9)
Homo sapiens adenylate cyclase activating polypeptide 1
Homo sapiens adenylate cyclase activating polypeptide 1
H. sapiens mRNA for angiotensin II receptor
Homo sapiens angiotensin receptor 2 (AGTR2)
Homo sapiens angiotensin receptor-like 1 (AGTRL1)
Homo sapiens angiotensin receptor-like 2 (AGTRL2)
Homo sapiens A kinase (PRKA) anchor protein 1 (AKAP1)
Homo sapiens A kinase (PRKA) anchor protein 10
Homo sapiens mRNA for KIAA0629 protein, partial cds
Homo sapiens A kinase (PRKA) anchor protein (gravin)
Homo sapiens A kinase (PRKA) anchor protein 2 (AKAP2)
Homo sapiens A kinase (PRKA) anchor protein 3 (AKAP3)
Homo sapiens A kinase (PRKA) anchor protein 4 (AKAP4)
Homo sapiens A kinase (PRKA) anchor protein 5 (AKAP5)
Homo sapiens A kinase (PRKA) anchor
Homo sapiens A kinase (PRKA) anchor
Homo sapiens A kinase (PRKA) anchor
Homo sapiens A kinase (PRKA) anchor
Homo sapiens AP1S1adaptor-related
Homo sapiens adaptor-related protein
Homo sapiens apoptotic protease
Homo sapiens mRNA for heat shock
H. sapiens rhoB gene mRNA; Ras homolog
Homo sapiens GTPase (rhoC) mRNA,
H. sapiens mRNA for Rho8 protein;
H. sapiens rhoG mRNA for GTPase;
H. sapiens partial C1 mRNA; Rho
Homo sapiens GTPase-activating
Homo sapiens Rho GTPase activating
H. sapiens mRNA for rho GDP-
Homo sapiens GDI-dissociation
H. sapiens TTF mRNA for small G
Homo sapiens putative tumor
Homo sapiens activating transcription
Homo sapiens activating transcription
Homo sapiens activating transcription
Homo sapiens activating transcription
Homo sapiens activating transcription
Homo sapiens arginine vasopressin
H. sapiens mRNA for antidiuretic
Homo sapiens axin (AXIN1), partial
Homo sapiens axin 2 (conductin, axil)
Homo sapiens Bcl-2-binding protein
Homo sapiens silencer of death domains
Homo sapiens BAI1-associated protein 2
H.sapiens bcl-xL mRNA; BCL2-like 1
H.sapiens atk mRNA for agammaglobulinaemia
Homo sapiens mRNA for beta-transducin repeat
H.sapiens mRNA for cytokine inducible nuclear protein;
Homo sapiens cyclin D3 (CCND3) mRNA,
Homo sapiens CD163 antigen (CD163)
Homo sapiens CD3D antigen, delta
Homo sapiens T-cell surface protein T8
Homo sapiens PITSLRE protein kinase
Homo sapiens HsCdc18p (HsCdc18)
Homo sapiens CDC2-related protein
H. sapiens mRNA cdk3 for serine/threonine
H. sapiens mRNA PSSALRE for serine/
H. sapiens p35 mRNA for regulatory
H. sapiens mRNA PLSTIRE for serine/
H. sapiens CDK activating kinase mRNA
Homo sapiens mRNA for CDK8 protein kinase.
Homo sapiens CDC2-related kinase
Homo sapiens cyclin-dependent kinase
Homo sapiens cyclin-dependent kinase
Homo sapiens cyclin-dependent kinase
Homo sapiens CCAAT/enhancer binding
Homo sapiens Casper mRNA; CASP8 and
Homo sapiens IkB kinase alpha subunit
Homo sapiens clk1 mRNA; CDC-like
Homo sapiens clk2 mRNA; CDC-like
Homo sapiens clk3 mRNA; CDC-like
Homo sapiens catechol-O-methyltransferase
Homo sapiens carboxypeptidase E (CPE)
Homo sapiens cAMP responsive element
Homo sapiens corticotropin releasing
Homo sapiens chorionic somatomammotropin
Homo sapiens casein kinase I alpha
H. sapiens mRNA for beta-catenin
Homo sapiens delta-catenin mRNA,
Homo sapiens cytochrome P450, subfamily
Homo sapiens cytochrome P450, subfamily
H. sapiens DAP-kinase mRNA
Homo sapiens Fas-binding protein Daxx
Homo sapiens gadd153 mRNA for CHOP
Homo sapiens angiotensin converting
H. sapiens CL 100 mRNA for protein
Homo sapiens dishevelled 2 (homologous
Homo sapiens (E2F-1) pRB-binding
Homo sapiens eukaryotic translation
Homo sapiens mRNA for Fas-associated
Homo sapiens mRNA for growth factor FIGF;
H. sapiens Flt4 mRNA for transmembrane
Homo sapiens frequently rearranged in
Homo sapiens follicle stimulating hormone,
Homo sapiens mRNA for frizzled-1, complete
Homo sapiens apoptosis associated protein
Homo sapiens growth arrest and DNA-damage-
Homo sapiens growth arrest and DNA-damage-
Homo sapiens gastrin (GAS)
Homo sapiens growth hormone 1 (GH1)
Homo sapiens growth hormone receptor (GHR)
Homo sapiens growth hormone releasing
Homo sapiens growth hormone secretagogue
Homo sapiens glucocorticoid modulatory
Homo sapiens glucocorticoid modulatory
Homo sapiens guanine nucleotide-binding
Homo sapiens G protein beta 5 subunit mRNA;
Homo sapiens guanine nucleotide binding
Homo sapiens clone 24733 mRNA sequence;
Homo sapiens G protein gamma 5 subunit
Homo sapiens mRNA for G-protein gamma 7;
Homo sapiens growth factor receptor-bound
Homo sapiens epidermal growth factor
Homo sapiens protein kinase C inhibitor
Homo sapiens heat shock protein hsp40
Homo sapiens activator of apoptosis Hrk
Homo sapiens heat shock factor binding
Homo sapiens heat shock protein hsp40-3
Homo sapiens hydroxysteroid (11-beta)
Homo sapiens hydroxy-delta-5-steroid
Homo sapiens mRNA for HSF2BP; Heat shock
Homo sapiens mRNA for heat shock
H. sapiens HSJ1 mRNA; Heat shock protein,
Homo sapiens heat shock 70 kD protein 10
Homo sapiens heat shock 70 kD protein 1
Homo sapiens heat shock 70 kD protein 1
Homo sapiens HSPA1L mRNA for Heat shock
H. sapiens mRNA for BiP protein; Heat
Homo sapiens mitochondrial HSP75 mRNA; Heat
Homo sapiens mRNA for MKBP; Heat shock 27
Homo sapiens heat shock 17 kD protein 3
Homo sapiens mRNA for cardiovascular heat
Homo sapiens Hsp89-alpha-delta-N mRNA; Heat
Homo sapiens DnaJ protein (HSPF2) mRNA,
Homo sapiens DNA-binding protein mRNA
Homo sapiens interferon, gamma-inducible
H. sapiens p27 mRNA (interferon, alpha-
Homo sapiens interferon induced
H. sapiens mRNA for interferon alpha/beta
Homo sapiens clone 24645 insulin-like growth
Homo sapiens IkappaB kinase complex
Homo sapiens IkB kinase-b (IKK-beta) mRNA,
Homo sapiens IkB kinase gamma subunit
Homo sapiens mRNA for transmebrane receptor
H. sapiens mRNA for interleukin-11 receptor
Homo sapiens interleukin 13 mRNA,
H. sapiens mRNA for IL13 receptor
Homo sapiens clone 24607 mRNA sequence
Homo sapiens interleukin 15 precursor
Homo sapiens putative IL-16 protein
Homo sapiens interleukin 17B (IL17B),
Homo sapiens interleukin 17C (IL17C),
Homo sapiens IL-17 receptor mRNA,
Homo sapiens mRNA for interferon-gamma
Homo sapiens mRNA for interleukin-18
Homo sapiens interleukin 19 (IL19),
H. sapiens IL-1R2 mRNA for type II
Homo sapiens mRNA for ST2 protein
H. sapiens mRNA for IRAP
Homo sapiens interleukin 8 receptor
Homo sapiens interleukin 8 receptor
Homo sapiens growth inhibitor p33ING1
Homo sapiens inhibitor of growth
Homo sapiens insulin (INS), mRNA
Homo sapiens insulin induced gene 1
Homo sapiens insulin receptor (INSR),
Homo sapiens insulin promoter factor 1,
Homo sapiens interleukin-1 receptor-
Homo sapiens interleukin-1 receptor-
H. sapiens mRNA for interferon regulatory
Homo sapiens interferon regulatory factor
Homo sapiens interferon regulatory factor
Homo sapiens insulin receptor substrate 2
Homo sapiens insulin receptor substrate
Homo sapiens insulin upstream factor 1 (IUF1)
Homo sapiens receptor-associated tyrosine
Homo sapiens v-jun avian sarcoma virus 17
H. sapiens mRNA for growth factor receptor
sapiens mRNA for stress protein Herp
Homo sapiens linker for activation of T cells
Homo sapiens luteinizing hormone beta
Homo sapiens lutropin/choriogonadotropin
Homo sapiens GTP-binding protein Sara (LOC51128)
Homo sapiens insulin induced protein 2 mRNA,
Homo sapiens insulin receptor tyrosine kinase
Homo sapiens MAP kinase-activating death
Homo sapiens mad protein homolog (hMAD-3)
Homo sapiens Smad6 mRNA, complete cds
Homo sapiens MAD-related gene SMAD7 (SMAD7)
Homo sapiens monoamine oxidase A (MAOA),
Homo sapiens ERK activator kinase (MEK1) mRNA
Homo sapiens ERK activator kinase (MEK2) mRNA
Homo sapiens mitogen-activated protein kinase
Homo sapiens MEK kinase 1 (MEKK1) mRNA,
H. sapiens mRNA for serine/threonine protein
Homo sapiens mitogen-activated protein kinase
Homo sapiens HPK/GCK-like kinase HGK mRNA,
Homo sapiens mitogen activated protein kinase
H. sapiens ERK6 mRNA for extracellular signal
H. sapiens ERK6 mRNA for extracellular signal
Homo sapiens stress-activated protein kinase 4
H. sapiens max mRNA
Homo sapiens melanocortin 2 receptor
Homo sapiens macrophage migration inhibitory
H. sapiens Humig mRNA
Homo sapiens mRNA for MRJ
H. sapiens RON mRNA for tyrosine kinase;
Homo sapiens myocilin, trabecular meshwork
Homo sapiens NF-AT4c mRNA, complete cds
Homo sapiens NF-AT3 mRNA, complete cds
H. sapiens mRNA for NF-kB subunit (p49/p100)
Homo sapiens MAD-3 mRNA encoding IkB-like
Homo sapiens thyroid receptor interactor (TRIP9)
H. sapiens IKBL mRNA
H. sapiens mRNA for oxytocin receptor
Homo sapiens purinergic receptor P2Y5 mRNA
Homo sapiens proliferating cell nuclear antigen
Homo sapiens apoptosis-inducing factor AIF mRNA,
Homo sapiens proenkephalin (PENK), mRNA
H. sapiens mRNA for placenta growth factor
H. sapiens mRNA for phosphoinositide 3-kinase;
H. sapiens mRNA for phosphoinositide 3-kinase,
Homo sapiens mRNA for C2 domain containing PI3-
H. sapiens mRNA for phosphatidylinositol 3-
H. sapiens mRNA for phosphatidylinositol 3
H. sapiens mRNA for p85 beta subunit of
Homo sapiens mRNA for p55pik, Phosphoinositide-
H. sapiens mRNA for adaptor protein p150,
Homo sapiens phospholipase A2, group VI
Homo sapiens macrophage inhibitory cytokine-
Homo sapiens phospholipase C-beta-2 mRNA;
H. sapiens mRNA encoding phospholipase c;
Homo sapiens phospholipase C beta 4
Homo sapiens proopiomelanocortin
Homo sapiens POU domain, class 1,
Homo sapiens protein kinase C-binding protein
Homo sapiens mRNA for protein kinase C delta-
H. sapiens mRNA for protein kinase C-Epsilon;
H. sapiens mRNA for protein kinase C gamma
H. sapiens mRNA for protein kinase C mu;
Homo sapiens EPK2 mRNA for serine/threonine
H. sapiens mRNA for protein kinase C
Homo sapiens DNA-dependent protein kinase
Homo sapiens SH-PTP3 mRNA for protein-
H. sapiens PTP1C mRNA for protein-tyrosine
Homo sapiens herpesvirus entry protein C
Homo sapiens retinoblastoma-binding protein 1
H. sapiens RBQ-3 mRNA
H. sapiens RBQ-1 mRNA
Homo sapiens retinoblastoma-interacting protein
Homo sapiens retinoblastoma binding protein
Homo sapiens I-Rel mRNA, complete cds.
Homo sapiens renin (REN)
Homo sapiens regulator of G protein signaling
Homo sapiens RIP protein kinase mRNA, Receptor
Homo sapiens serine/threonine kinase RICK
H. sapiens mRNA for 23 kD highly basic protein
Homo sapiens lymphocyte secreted C-type lectin
H. sapiens mRNA for chemokine HCC-1; Small
Homo sapiens MIP-1 delta mRNA; Small inducible
Homo sapiens liver CC chemokine-1 precursor
Homo sapiens mRNA for alternative activated
Homo sapiens beta chemokine mRNA; Small
Homo sapiens mRNA for CC chemokine eotaxin3;
Homo sapiens mRNA for CCL27 chemokine,
Homo sapiens mRNA for monocyte chemotactic
H. sapiens mRNA for monocyte chemotactic
Homo sapiens interferon stimulated T-cell
Homo sapiens CXC chemokine BRAK mRNA,
H. sapiens ENA-78 mRNA; Small inducible
Homo sapiens small inducible cytokine
H. sapiens SHC mRNA, Src homology 2 domain-
Homo sapiens solute carrier family 6
Homo sapiens superoxide dismutase 1, soluble
Homo sapiens secreted phosphoprotein 1
Homo sapiens mRNA for stac, (src homology three
Homo sapiens transcription factor ISGF-3 mRNA,
Homo sapiens interferon alpha induced
Homo sapiens DNA-binding protein (APRF) mRNA,
Homo sapiens STAT4 mRNA, complete cds
Homo sapiens signal transducer and activator of
Homo sapiens protein tyrosine kinase (Syk) mRNA;
Homo sapiens TAK1 binding protein (TAB1) mRNA,
Homo sapiens transcription factor (HTF4) mRNA,
Homo sapiens HKL1 mRNA, complete cds
Homo sapiens transcription factor 19 (SC1)
Homo sapiens AR1 (TCF20) mRNA, partial cds
Homo sapiens epicardin mRNA, complete cds.
Homo sapiens transcription factor 4 (TCF4)
Homo sapiens transcription factor 7 (T-cell
Homo sapiens mRNA for hTCF-4
Homo sapiens TCFL5 mRNA for transcription
Homo sapiens teratocarcinoma-derived growth
Homo sapiens E2F-related transcription factor
Homo sapiens transferrin receptor 2 (TFR2), mRNA
H. sapiens mRNA for transforming growth factor
Homo sapiens mRNA for TGF-betaIIR alpha,
Homo sapiens tyrosine hydroxylase (TH), mRNA
Homo sapiens Thy-1 cell surface antigen (THY1),
Homo sapiens Toll-like receptor 1 (TLR1) mRNA,
Homo sapiens Toll-like receptor 2 (TLR2) mRNA,
Homo sapiens Toll-like receptor 3 (TLR3) mRNA,
Homo sapiens Toll-like receptor 4 (TLR4) mRNA,
Homo sapiens Toll-like receptor 5 (TLR5) mRNA,
Homo sapiens death receptor 5 (DR5) mRNA, Tumor
Homo sapiens TRAIL receptor 3 mRNA, complete cds
Homo sapiens receptor activator of nuclear
Homo sapiens tumor necrosis factor receptor
H. sapiens TNF-R mRNA for tumor necrosis factor
H. sapiens mRNA for 0X40 homologue
H. sapiens mRNA for APO-1 cell surface antigen,
H. sapiens lymphocyte activation antigen CD30
Homo sapiens osteoprotegerin ligand mRNA,
Homo sapiens vascular endothelial cell growth
Homo sapiens CD30 ligand mRNA, complete cds.
Homo sapiens tumor protein p73 (TP73) mRNA:
Homo sapiens TNF receptor-1 associated protein
Homo sapiens TNF receptor-associated factor
Homo sapiens TNF receptor-associated factor 3
H. sapiens MLN62 mRNA (TNF receptor-associated
Homo sapiens mRNA for TRAF5, complete cds
Homo sapiens heat shock protein 75 (hsp75)
Homo sapiens thyroid stimulating hormone, beta
Homo sapiens thyroid stimulating hormone receptor
Homo sapiens U-snRNP-associated cyclophilin
Homo sapiens vascular cell adhesion molecule
Homo sapiens connective tissue growth factor
Homo sapiens connective tissue growth factor
Homo sapiens connective tissue growth factor
Homo sapiens mRNA for WNT11 gene
H. sapiens Wnt-13 mRNA
H. sapiens mRNA for WNT-8B protein
Number | Date | Country | Kind |
---|---|---|---|
2001-053465 | Feb 2001 | JP | national |
2002-022682 | Jan 2002 | JP | national |
This application is a Divisional of U.S. Ser. No. 10/083,550 filed Feb. 27, 2002 now abandoned. Priority is claimed based on U.S. Ser. No. 10/083,550 filed Feb. 27, 2002, which claims priority to Japanese Patent Application Nos. 2001-053465 and 2002-022682 filed on Feb. 28, 2001 and Jan. 31, 2002, respectively.
Number | Name | Date | Kind |
---|---|---|---|
6372249 | Smith et al. | Apr 2002 | B1 |
Number | Date | Country |
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WO 9853103 | May 1998 | WO |
Number | Date | Country | |
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20050208561 A1 | Sep 2005 | US |
Number | Date | Country | |
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Parent | 10083550 | Feb 2002 | US |
Child | 11113195 | US |