JP4606853B2 - Evaluation of test substances on cells - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To provide a method for attaining accurate and highly reproducible quantitative value on the action and/or effect of a test substance on a cell. <P>SOLUTION: The method for the evaluation of the action and/or effect of a test substance on a cell contains (1) a step to acquire a control curve function F(t) of an index of a cell number in the absence of the test substance to time and a test curve function G(t) of the index of a cell number in the presence of the test substance to time, (2) a step to calculate the integrated value of the formula (F(t)-G(t)) in a prescribed time interval, (3) a step to divide the integrated value by the prescribed time interval to obtain an area value and (4) a step to evaluate the action and/or effect of the test substance based on the area value. <P>COPYRIGHT: (C)2006,JPO&amp;NCIPI

Description

  The present invention relates to the evaluation of the property of a test substance to cells, and more particularly, the expression of transcriptional and / or translational products of cells or genes in which at least one gene is deficient, mutated or overexpressed is regulated. The present invention relates to a method for evaluating the action and / or effect of a test substance on a cell, a method for detecting a gene and / or protein affected by the test substance, and a program for executing the method.

  The mechanism by which the test substance acts and the identification of the target molecule are one of the difficult tasks even now that the genome structure has been clarified. Recently, attempts have been made to analyze the action of a test substance on a genome-wide basis by progress of post-genome technology such as DNA microarray (see, for example, Non-Patent Document 1). Among them, the budding yeast S. cerevisiae (hereinafter sometimes referred to as “yeast”) that has many human homologous genes and can be used for genetic techniques is considered to be a useful tool for elucidating the mechanism of action of test substances. (See, for example, Non-Patent Document 2).

  Recently, a project for destroying about 6000 species of yeast genes one by one has been completed (see, for example, Non-Patent Document 3), and a system using these yeasts has attracted attention. As a result, it is clear that about 1,200 genes out of about 6,000 species existing on the yeast genome are genes essential for survival, that is, if any of these genes is destroyed, the yeast is lethal. Became. On the other hand, it was clarified that the remaining about 4800 genes are genes in which the yeast can grow in a normal medium even if the gene is destroyed, and the yeast is not lethal.

  However, the growth rate varies from exactly the same as the parent strain that has not disrupted the gene to a very slow one. In addition, these gene-disrupted strains have different responsiveness to the surrounding environment. In other words, the role of the disrupted gene may affect growth under certain conditions. Conversely, it can be seen that a gene that is disrupted in a strain affected by growth under a certain condition has some role in the cellular response to that condition.

  One of the conditions at this time is to treat the cells with a test substance. For example, when a test substance is applied to about 4,800 kinds of non-essential gene disruption strains, and there is a non-essential gene disruption strain that is specifically affected by the test substance, that gene is the test substance. It turns out that it is related to the action of. Here, a non-essential gene means a cell even if the gene is destroyed (both two alleles are destroyed in the case of diploid cells, and one gene is destroyed in the case of haploid cells). Refers to a gene that can proliferate. In fact, test substance action mechanism analysis methods using this principle have been reported one after another (for example, see Non-Patent Documents 4 to 7). In addition, it has been reported that the action point of a test substance whose target is unknown can be seen by profiling a test substance sensitive strain for various test substances and comparing them (for example, non-patent literature). 7). This method is called the yeast deletion set method (yeast-disrupted strain set method (hereinafter sometimes referred to as “YDS method”)).

  By the way, the cell growth inhibitory activity by the test substance is usually represented by the ratio of the number of cells in the presence of the test substance to the number of cells in the absence of the test substance. However, since actually measuring the number of cells is a cumbersome operation, various methods for setting and quantifying an index that can replace the number of cells are used. For example, in the case of microorganisms (bacteria, yeast, etc.), methods such as measuring the turbidity of a culture solution at a certain time point or measuring the turbidity of a culture solution over time and using the growth rate delay time as an index are known. It has been.

  However, with these methods, it has been difficult to obtain quantitative values with high accuracy and high reproducibility when uniformly evaluating the growth inhibitory activity of about 4800 non-essential gene disrupted strains. The reason is as follows. That is, about 4,800 kinds of non-essential gene disrupted strains have different growth rates, and the growth inhibition patterns by the test substance are roughly divided into three types, that is, (A) a pattern in which entry into the logarithmic growth phase is delayed. (B) It is reported that the cell can be divided into a pattern in which the doubling time of the cell is extended and a pattern in which (C) the number of saturated cells is decreased (see, for example, Non-Patent Document 8, FIGS. 1 (A) to (C)). ). Therefore, in order to uniformly evaluate the growth inhibitory activity of these non-essential gene-disrupted strains, the method of measuring the turbidity of the culture solution at a certain time point uses the test substance untreated group and the test samples in all strains. It is impossible to take a time point that maximizes the difference between substance treatment groups (see FIG. 1). In the method using the delay of growth doubling time as an index, a sensitive strain is used when the number of saturated cells decreases. Missing outliers, being greatly affected by outliers, being unable to calculate if the measurement start time is delayed, being difficult to fit past data, In experiments, it is not always possible to obtain an ideal growth curve, and in methods such as obtaining the slope of the logarithmic growth phase, a large error may occur due to a shift in measurement points. .

  Moreover, in order to investigate the influence on cell proliferation, a method using a DNA microarray has also been reported (for example, see Non-Patent Documents 5 and 6), but it is necessary to extract genomic DNA from cells. It is not possible to follow growth over time using a sample. Also, the method using a DNA microarray is considered to be difficult to become a general method because the running cost is very expensive.

  On the other hand, in cultured mammalian cells including humans, the cell growth inhibitory activity of the test substance can be measured by measuring the incorporation of the labeled substrate into DNA (tritium thymidine method, etc.) and the chromogenic substrate for measuring mitochondrial activity. A method of using cell as an index of cell number (MTT method, Alamar Blue method, etc.), SRB method based on the principle of protein staining, and the like have been widely used. However, these methods require the cells to be killed for detection and are measured at a specific time point, so that they can only be detected when cell growth is suppressed at that time point, For measurement, it is necessary to prepare samples for measurement points. Under such circumstances, there is currently no known method for uniformly evaluating the growth inhibitory activity of a test substance against a wide variety of cells having different growth rates.

  As a method for evaluating the growth inhibitory activity, for example, a test substance concentration (IC50: 50% Inhibitory Concentration) showing 50% growth inhibitory activity is often used. The value may vary greatly from experiment to experiment.

  On the other hand, with the completion of the genome sequencing project for various species, genomic DNA base sequence information and protein amino acid sequence information based on this information can be easily obtained. However, at present, the role of each gene in the living body cannot be obtained from sequence information.

As described above, the YDS method is a method of finding the action of a test substance using an index indicating that the strain in which a certain gene is disrupted exhibits a change in sensitivity to the test substance. Therefore, it is possible to predict the action point of a test substance only when there is information on what physiological function the gene disrupted in the strain showing a change in sensitivity has.

  By the way, up to now, descriptions on the functional information of genes have been left to individual researchers, and no attempt has been made to define them in a unified manner. Moreover, incompatible words are used between different species, and it has been impossible to uniformly process gene function information by computer.

Gene Ontology (hereinafter sometimes referred to as GO) is a project that defines the vocabulary used to describe the functional information of genes and is being promoted by the Gene Ontology Consortium (The Gene Ontology Consortium, 2000). , Nature BioTenology, 25: 25-29). Gene Ontology has three ontologies: Biological Process (description of major biological phenomena), Molecular Function (description about the behavior of gene products at the biochemical level), and Cellular Component (subcellular localization of gene products and It is composed of a description of the polymer composite to which it belongs. Each ontology has a hierarchical structure, and has a structure in which a detailed description is obtained from a rough classification by following the hierarchy.
Huels et al, 2002, Drug Discovery Today, 7 (suppl.): 119-124. Simon and Bedalov, Nat Rev Cancer, 2004, 4: 481-92. Giaever et al, Nature 2002 418: 387-91. Giaever et al, Nat Genet, 1999, 21: 278-83. Giaever et al, Proc Natl Acad Sci USA, 2004, 101: 793-798. Lum et al, Cell, 2004, 116: 121-37. Parsons et al, Nat BioTechnol, 2004, 22: 62-9. Warringer et al, 2003, Proc Natl Acad Sci USA, 100: 15724-15729.

  The present invention has been made in view of such circumstances, and the problem to be solved by the present invention is to obtain a quantitative value with high accuracy and high reproducibility for the action and / or effect of a test substance on cells. Methods, methods for obtaining accurate and reproducible results for genes and / or proteins affected by the test substance, methods for easily obtaining functional information of genes simultaneously, and programs for executing these methods are provided. There is to do.

  In order to solve the above problems, the present inventors have made extensive studies on an index that best reflects the appearance of the proliferation graph, can cope with any sensitivity pattern, and is hardly affected by outliers. It was found to use “area” surrounded by growth curves drawn in the presence and presence. Furthermore, in order to enable comparison between different experiments, the value obtained by dividing this by the incubation time is used as an “area value” as an indicator for the number of cells, and it has been found that the number of cells can be evaluated. It was. This also makes it possible to simultaneously compare cell groups with greatly different growth rates and to uniformly evaluate cells that exhibit different sensitivity patterns. And it is shown that it is useful as a parameter | index of a sensitivity change in YDS method.

  Further, in the present invention, for information on a gene destroyed in a cell line showing a change in sensitivity to a test substance, the gene function information is obtained by referring to a database having gene function information, and the destroyed By determining whether a gene is included in a specific functional category, it is easy to detect a gene and / or protein affected by the test substance, and the action mechanism of the test substance and its target molecule The inventors have found that identification is possible and have completed the present invention.

  That is, according to one aspect of the present invention, the present invention relates to a method for evaluating the action and / or effect of a test substance on cells, and (1) relates to the number of cells in the absence of the test substance. Obtaining a function F (t) of the control curve with respect to the time of the index and a function G (t) of the test curve with respect to the time of the index with respect to the number of cells in the presence of the test substance; t)-calculating an integral value of G (t)) to obtain an area value; (3) evaluating the action and / or effect of the test substance based on the area value; An evaluation method including By using the area value, it is possible to evaluate the action and / or effect of the test substance on the cell.

  In a preferred embodiment of the evaluation method according to the present invention, the step (2) is performed within a predetermined time. Thus, by calculating the integral value of the equation (F (t) -G (t)) and obtaining the area value within a predetermined time, the error of the measurement time point can be reduced.

  In a preferred aspect of the evaluation method according to the present invention, the step (2) includes a step of calculating an integral value of the formula (F (t) −G (t)) within a predetermined time, and the integral value, An area value is obtained by dividing by the predetermined time. Such area values can be used to compare between different experiments.

  In a preferred embodiment of the evaluation method according to the present invention, the step (1) is performed in a cell in which at least one gene is deleted, mutated or overexpressed. Thus, by evaluating the number of cells in which a gene is deficient, mutated or overexpressed, knowledge about the role of the test substance in the cell response can be obtained.

  In a preferred embodiment of the evaluation method according to the present invention, the cell includes a plurality of cells, and each cell is a cell in which a different gene is deleted, mutated or overexpressed. By using cells in which different genes are deleted, mutated or overexpressed, it is possible to obtain knowledge about the correlation between a plurality of genes and / or proteins related to cellular responses.

  In a preferred embodiment of the evaluation method according to the present invention, the step (1) is performed in a cell in which expression of at least one gene transcription product and / or translation product is regulated. Thus, by evaluating the number of cells in which the expression of the transcription product and / or translation product of the gene is regulated, knowledge about the role of the test substance in the cellular response can be obtained.

  In a preferred embodiment of the evaluation method according to the present invention, the cell includes a plurality of cells, and each cell is a cell in which expression of a transcription product and / or translation product of a different gene is regulated. By using cells in which the expression of transcripts and / or translation products of different genes is regulated, knowledge about the correlation of multiple genes and / or proteins associated with cellular responses can be obtained.

  In a preferred embodiment of the evaluation method according to the present invention, based on each area value obtained in the plurality of cells, cells having an area value greater than or less than a predetermined value are classified, and the test substance Determine affected genes and / or proteins. In this way, the area value according to the present invention can be used to find genes and / or proteins affected by the test substance.

  According to another aspect of the present invention, the present invention provides a method for detecting a gene and / or protein affected by a test substance, wherein (1) an index relating to the number of cells in the absence of the test substance A function F (t) of the control curve with respect to the time of the test curve, and a function G (t) of the test curve with respect to the time of the index relating to the number of cells in the presence of the test substance, and the equation (2) (F (t )-Calculating an integral value of G (t)) to obtain an area value; and (3) detecting a gene and / or protein affected by the test substance based on the area value. A detection method is provided. By such a method, it is possible to obtain information on the relationship between the action and / or effect of the test substance and the gene and / or protein.

  In a preferred embodiment of the detection method according to the present invention, the step (2) is performed within a predetermined time. Thus, by calculating the integral value of the equation (F (t) -G (t)) and obtaining the area value within a predetermined time, the error of the measurement time point can be reduced.

  In a preferred aspect of the detection method according to the present invention, the step (2) includes a step of calculating an integral value of the formula (F (t) −G (t)) within a predetermined time, An area value is obtained by dividing by the predetermined time. Such area values can be used to compare between different experiments.

  In a preferred embodiment of the detection method according to the present invention, the cell includes a plurality of cells, and each of the cells is a cell in which a different gene is deleted, mutated or overexpressed. By using cells in which different genes are deleted, mutated or overexpressed, it is possible to obtain knowledge about the correlation between a plurality of genes and / or proteins related to cellular responses.

  In a preferred embodiment of the detection method according to the present invention, the cell includes a plurality of cells, and each cell is a cell in which expression of a transcription product and / or translation product of a different gene is regulated.

  In a preferred embodiment of the detection method according to the present invention, based on each area value obtained in the plurality of cells, cells having an area value greater than or less than a predetermined value are classified, and the test substance Find genes and / or proteins affected by action and / or effect.

  In a preferred embodiment of the evaluation and detection method according to the present invention, the method further includes (5) a step of displaying the relationship between the gene and / or protein and the area value. This process makes it possible to display genes and / or proteins that are affected by the test substance.

  Further, in a preferred embodiment of the evaluation and detection method according to the present invention, the method further comprises (6) a step of referring to a database having gene and / or protein function information to obtain the gene and / or protein function information. The step (6) includes a step of displaying the function information of the acquired gene and / or protein. In this way, the function of the gene and / or protein affected by the test substance is estimated.

  In a preferred embodiment of the evaluation and detection method according to the present invention, (6) the function information of the gene and / or protein is obtained by referring to a database having the function information of the gene and / or protein, and the gene has a specific function. The method further includes a step of determining whether or not it is included in the category. By such a process, the function of the gene and / or protein involved in the test substance is estimated.

  In a preferred embodiment of the evaluation and detection method according to the present invention, the step (6) includes a step of identifying and displaying whether or not the gene and / or protein is included in a specific function category. Such display makes it easy to evaluate whether each gene and / or protein has a specific function.

  In a preferred embodiment of the evaluation and detection method according to the present invention, the index relating to the number of cells is an index obtained by collecting a cell or a culture solution and / or using a non-destructive technique. Using these indicators, the number of cells can be evaluated.

  In a preferred embodiment of the evaluation and detection method according to the present invention, the indicator relating to the number of cells is an indicator selected from glucose consumption, turbidity, cell number, cell area, and fluorescence intensity. Using these indicators, the number of cells can be evaluated.

  In a preferred embodiment of the evaluation and detection method according to the present invention, the cell is a eukaryotic cell, and the eukaryotic cell is preferably a yeast and / or a mammalian cell.

  Furthermore, the present invention provides a program for executing the method according to the one or another aspect. Specifically, in yet another aspect of the present invention, there is provided a program for causing a computer to evaluate the action and / or effect of a test substance on cells, and (1) an index relating to the number of cells in the absence of the test substance. A function F (t) of the control curve with respect to the time of the test curve, and a function G (t) of the test curve with respect to the time of the index relating to the number of cells in the presence of the test substance, and the equation (2) (F (t )-Calculating an integral value of G (t)) to obtain an area value; and (3) evaluating the action and / or effect of the test substance based on the area value. Provide a program to be executed. With such a program, it is possible to cause a computer to evaluate the action and / or effect of a test substance on cells using an index called an area value.

  In a preferred aspect of the program according to the present invention, the step (2) is performed within a predetermined time. Thus, by calculating the integral value of the equation (F (t) -G (t)) and obtaining the area value within a predetermined time, the error of the measurement time point can be reduced.

  In a preferred aspect of the program according to the present invention, the step (2) includes a step of calculating an integral value of an expression (F (t) −G (t)) within a predetermined time, and Divide by a predetermined time to obtain the area value. Such area values can be used to compare between different experiments.

  In a preferred aspect of the program according to the present invention, the step (1) is performed in a cell in which at least one gene is deleted, mutated or overexpressed. Thus, by evaluating the number of cells in which a gene is deficient, mutated or overexpressed, knowledge about the role of the test substance in the cell response can be obtained.

  In a preferred embodiment of the program according to the present invention, the cell includes a plurality of cells, and each cell is a cell in which a different gene is deleted, mutated or overexpressed. By using cells in which different genes are deleted, mutated or overexpressed, it is possible to obtain knowledge about the correlation between a plurality of genes and / or proteins related to cellular responses.

  In a preferred embodiment of the program according to the present invention, the step (1) is performed in a cell in which expression of at least one gene transcription product and / or translation product is regulated.

  In a preferred embodiment of the program according to the present invention, the cell includes a plurality of cells, and each of the cells is a cell in which expression of a transcription product and / or translation product of a different gene is regulated.

  In a preferred aspect of the program according to the present invention, cells having an area value greater than or less than a predetermined value are classified based on each area value obtained by the plurality of cells, and the influence of the test substance Seeking genes and / or proteins to receive.

  Furthermore, in another aspect of the present invention, the present invention is a program for causing a computer to execute detection of a gene and / or protein affected by a test substance, and (1) in the absence of the test substance. Obtaining a function F (t) of the control curve with respect to the time of the index relating to the number of cells and a function G (t) of the test curve with respect to the time of the index relating to the number of cells in the presence of the test substance; Calculating an integral value of (F (t) -G (t)) to obtain an area value; and (3) a gene and / or protein affected by the test substance based on the area value. And a step of detecting the program. With such a program, it is possible to cause a computer to detect a gene and / or protein affected by a specific test substance using an index called an area value.

  In a preferred aspect of the program according to the present invention, the step (2) is performed within a predetermined time. Thus, by calculating the integral value of the equation (F (t) -G (t)) and obtaining the area value within a predetermined time, the error of the measurement time point can be reduced.

  In a preferred aspect of the program according to the present invention, the step (2), the step (2), and a step of calculating an integral value of the formula (F (t) -G (t)) within a predetermined time period; The integral value is divided by the predetermined time to obtain an area value. Such area values can be used to compare between different experiments.

  In a preferred aspect of the program according to the present invention, the step (1) is performed in a cell in which at least one gene is deleted, mutated or overexpressed. Thus, by evaluating the number of cells in which a gene is deficient, mutated or overexpressed, knowledge about the role of the test substance in the cell response can be obtained.

  In a preferred embodiment of the program according to the present invention, the cell includes a plurality of cells, and each cell is a cell in which a different gene is deleted, mutated or overexpressed. By using cells in which different genes are deleted, mutated or overexpressed, it is possible to obtain knowledge about the correlation between a plurality of genes and / or proteins related to cellular responses.

  In a preferred embodiment of the program according to the present invention, the cell includes a plurality of cells, and each of the cells is a cell in which expression of a transcription product and / or translation product of a different gene is regulated.

  In a preferred aspect of the program according to the present invention, cells having an area value greater than or equal to a predetermined value are classified based on each area value obtained by the plurality of cells, and are affected by the test substance. Find genes and / or proteins.

  In a preferred aspect of the program according to the present invention, the method further includes (5) a step of displaying a relationship between the gene and the area value.

  In a preferred embodiment of the program according to the present invention, the method further comprises (6) a step of referring to a database having gene and / or protein function information to obtain the function information of the gene and / or protein, and the step (6) And displaying the function information of the acquired gene and / or protein.

  In a preferred embodiment of the program according to the present invention, (6) the function information of the gene and / or protein is obtained by referring to a database having the function information of the gene and / or protein, and the gene and / or protein is specified. The method further includes a step of determining whether or not the function is included in the function category.

  In a preferred embodiment of the program according to the present invention, the step (6) includes a step of identifying and displaying the gene and / or protein depending on whether or not the gene and / or protein is included in a specific function category.

  In a preferred aspect of the program according to the present invention, the index relating to the number of cells is an index obtained by collecting a cell or a culture solution and / or using a non-destructive technique. Using these indicators, the number of cells can be evaluated.

  In a preferred aspect of the program according to the present invention, the index relating to the number of cells is an index selected from glucose consumption, turbidity, cell number, cell area, and fluorescence intensity.

  In a preferred embodiment of the program according to the present invention, the cell is a eukaryotic cell, and the eukaryotic cell is preferably a yeast and / or a mammalian cell.

  Furthermore, in a further aspect of the present invention, there is provided a method for displaying a gene having a specific function from gene function information based on the obtained gene expression data, wherein the gene function information is referred to the database having the gene function information. Obtaining gene function information and determining whether or not a related gene is included in a specific function category from the obtained gene expression data; and based on the determination result, the related gene And a step of identifying and displaying the related gene according to whether it is included in a category or not. According to this method, it is possible to classify and display genes by function.

  In a preferred embodiment of the method according to the present invention, the gene expression data is data relating to changes in expression of a plurality of genes.

  In a preferred embodiment of the method according to the present invention, the expression change is measured by a method selected from a DNA chip method, a differential display method, and a quantitative PCR method.

  In addition, in still another aspect of the present invention, a computer program for causing a computer to display a gene having a specific function from gene function information based on the obtained gene expression data, the database having the gene function information Obtaining the gene function information, determining whether the related gene is included in a category of a specific function from the obtained gene expression data, and based on the determination result, the related gene is And a step of identifying and displaying the related gene according to whether it is included in the category of the specific function. According to such a program, it is possible to cause a computer to execute classification and display of genes by function.

  In a preferred aspect of the program according to the present invention, the gene expression data is data relating to expression changes of a plurality of genes.

  In a preferred aspect of the program according to the present invention, the expression change is measured by a method selected from a DNA chip method, a differential display method, and a quantitative PCR method.

  The term “test substance” used in the present invention means not only known substances but also substances containing unknown substances that will be developed in the future. Further, the term “the action and / or effect of the test substance” used in the present invention refers to the properties, characteristics, etc. of the test substance.

  According to the evaluation and detection method and the program for executing the method according to the present invention, the influence of the test substance on the number of cells can be evaluated, and the gene or protein affected by the test substance can be detected. Furthermore, an effective analysis method for elucidating the action mechanism of the test substance is provided. Further, according to the present invention for evaluating the action and / or effect of a test substance on the number of cells using an index on the number of cells, the present invention is applicable not only to yeast but also to cells in general, for example, mammalian cells including humans. Yes, it is possible to detect various growth rates and subtle sensitivity patterns. In addition, it can be a parameter that can be widely used generally for measuring the activity of a compound (for example, antitumor activity or antibacterial activity) using proliferation ability as an index.

  Furthermore, according to the present invention, a gene that is deficient, mutated or overexpressed in a cell exhibiting a change in sensitivity to a test substance, a gene whose transcription product and / or translation product is regulated, and other gene expression A method of displaying data in association with functional information of the gene and / or protein and a program for executing the method are provided.

The following embodiment is an example for explaining the present invention, and is not intended to limit the present invention only to this embodiment. The present invention can be implemented in various forms without departing from the gist thereof. Documents, publications, patent gazettes and other patent documents cited in the present specification are incorporated into the present specification as references.
In the following description, yeast, which is one of the simplest eukaryotic cells, will be described as an example. However, the present invention is not limited to yeast as cells.

  In the present invention, cells in which a gene is deleted, mutated or overexpressed can be obtained by various methods. A method for producing a cell deficient in a gene can be produced by artificially inactivating a specific gene on the genome. Introducing a DNA fragment that is homologous to a specific sequence on the genome but does not function as a gene due to mutations such as deletion or insertion, causes recombination at the homologous part, and inactivates the specific gene it can. In addition, it is possible to introduce mutations into specific genes at the cellular and individual level by gene targeting that targets individuals to target specific genes in the genome. A deficient individual can also be obtained. In the present invention, cells from an individual deficient in the target gene can also be used. A cell in which a gene is deficient, mutated or overexpressed includes cancer cells.

  In the present invention, a cell in which expression of a gene transcription product and / or translation product is regulated may be RNAi, antisense, ribozyme, aptamer, DNA-RNA chimera, dominant inhibitory mutation (dominant negative), CALI method, artificial polyamide, It can be produced by a method such as a decoy method. Furthermore, by using these libraries, a cell group in which the expression of the transcription product and / or translation product of the gene is regulated can be prepared (BMC Cell Biol. 2004 Apr 30; 5 (1): 16. , Nature. 2004 Mar 25; 428 (6981): 431-7., Nature. 2004 Mar 25; 428 (6981): 427-31.).

  As described above, FIG. 1 shows a schematic diagram of growth inhibition patterns by typical test substances in about 4800 non-essential gene disrupted yeast strains. As can be seen from FIG. 1, about 4800 kinds of non-essential gene disrupted strains are roughly divided into three types of growth inhibition patterns by test substances, that is, a pattern in which entry into the logarithmic growth phase is delayed (A), A pattern (B) in which the doubling time is prolonged and a pattern (C) in which the number of saturated cells is reduced are roughly divided.

  FIG. 2 is an explanatory diagram for the analysis of the growth inhibition pattern exemplified in FIG. 2A and 2D show an analysis method for calculating the ratio of the number of cells at a certain time point. In this case, when cells having different growth rates are compared with each other, there is a drawback that the measured value varies greatly depending on the set time point. The analysis method shown in FIG. 2 (B) is a method in which a delay in reaching a certain number of cells is used as an index of the sensitivity of cell proliferation to a drug. In this case, as shown in FIG. 2E, in the case of a growth inhibition pattern in which the saturated cell number decreases, it is impossible to calculate a delay in the time to reach a certain cell number. Further, FIG. 2C shows an analysis method for calculating the doubling time by calculating the slope of the cell growth curve. However, as shown in FIG. 2 (F), there is a problem that the sensitivity of the drug to cell proliferation cannot be evaluated in a pattern in which the doubling time in the logarithmic growth phase does not change.

  Therefore, in the present invention, as shown in FIGS. 3 (G) to (I), paying attention to the area surrounded by two time-dependent growth curves in the absence and presence of the drug as the test substance, If such an area is taken as a measure of drug sensitivity to cells, it can be applied to any inhibition pattern shown in FIGS. In FIG. 3, the number of cells is displayed as an index of the number of cells. As a method for measuring the number of cells, a method of measuring the number of cells with a hemocytometer, flow cytometry, a cell coefficient analyzer (Coulter counter), or the like is preferable. As an indicator of cell number, as a destructive method, the amount of nucleic acid taken up (tritium thymidine method, etc.), mitochondrial activity (MTT method, Alamar Blue method, etc.), DNA amount, etc. Examples of the non-destructive method include glucose consumption, turbidity, a method for measuring cell number or cell area by image analysis, fluorescence intensity (method using fluorescently labeled cells), and the like. In the evaluation and detection method according to the present invention, glucose consumption, turbidity, a method of measuring cell number or cell area by image analysis, fluorescence intensity (method using fluorescently labeled cells) and the like are preferable.

  The “area surrounded by two time-dependent growth curves” as a measure of drug sensitivity to cells used in the present invention will be described below. The area surrounded by the two time-dependent growth curves is a function of a control curve (hereinafter referred to as “F (t)”) with respect to the time of the index related to the number of cells in the absence of the test substance, and in the presence of the test substance. A function of a test curve with respect to time of an index related to the number of cells in (hereinafter referred to as “G (t)”) is obtained (see FIG. 3G). Next, by integrating the difference between the function of the control curve and the function of the test curve, that is, the formula (F (t) −G (t)), the “two time-dependent growth curves are used. The “area surrounded” can be calculated.

  Here, how to obtain the functions F (t) and G (t) will be described. FIG. 4 is a schematic diagram of F (t) and G (t) used in the evaluation method according to the present invention when turbidity is used as an index of the number of cells. As shown in FIG. 4, the black square indicates the turbidity at each time in the absence of the test substance as the absorbance value, and the black circle indicates the turbidity at each time in the presence of the test substance as the absorbance value. . The functions F (t) and G (t) can be obtained, for example, by approximating the absorbance at two times actually measured with a straight line. Further, the functions F (t) and G (t) can be obtained by applying the idea of the least square method to the measured value. Then, by integrating the formula (F (t) −G (t)) from the obtained functions F (t) and G (t), “2” is used as a measure of drug sensitivity to the cells used in the present invention. The area S1 "surrounded by the growth curve of the book over time can be calculated.

  In this invention, when calculating | requiring a formula (F (t) -G (t)), it is preferable to integrate within predetermined time. Here, the predetermined time for integration will be described. The predetermined time needs to be a time shared by the two functions, and is represented by an effective time (Te-Ts) in FIG.

  Those skilled in the art will readily understand that the integrated areas S1 and S2 described above vary in the value of the area itself depending on the integration time, that is, the areas S1 and S2 are values that depend on the integration time. it can. Therefore, in the present invention, a value obtained by dividing the above-described area S2 by the predetermined time so as to enable comparison between measurements without depending on time is referred to as “area value” (hereinafter, “ARS”). As an index of the sensitivity of the test substance to cells.

  Other methods for calculating the area surrounded by two time-dependent growth curves include the Simpson method and the Romberg method. Since the absorbance over time of the growth curve is measured at irregular timing, data interpolation such as spline conversion and calculation of an approximate curve are required to calculate the area by these methods.

  In this way, in the absence and presence of the test substance, tracking with the indicators related to the number of cells, and evaluating the action and / or effect of the test substance on the cells by obtaining the aforementioned ARS Is possible.

  If ARS according to the present invention is used, data can be compared regardless of the shape of the growth curve. That is, it can be evaluated even when an ideal growth curve cannot be obtained. Specifically, in the ARS according to the present invention, the delay in the rise time of the growth curve and the difference in the maximum value arrival point are reflected as they are, so that the ARS is adopted as an index that can comprehensively evaluate the influence of the test substance.

  Furthermore, a gene and / or protein affected by a test substance can be obtained by using a cell in which a gene is deficient, mutated or overexpressed, and / or a cell in which expression of a gene transcription product and / or translation product is regulated. Can be detected. In addition, although the specific example using yeast is demonstrated below, this invention is not limited to yeast.

  A non-essential gene disruption strain can be used to detect genes and / or proteins affected by a test substance using synthetic lethal. Here, synthetic lethality refers to the property of causing lethality when a plurality of types of genes in a cell are simultaneously destroyed. In addition, a combination of genes leading to synthetic lethality is said to have a synthetic lethal relationship.

  For example, a disrupted strain of gene A or gene B, each of which is a non-essential gene, can grow, but a strain in which genes A and B are destroyed at the same time may be lethal. At this time, gene A and gene B can be said to be in a synthetic lethal relationship. For example, a gene B disrupted strain has a concentration at which growth of a strain that does not disrupt gene B is not completely inhibited by the action of a test substance that inhibits the transcription product and / or translation product of gene A. Even if it is, it is expected to be lethal. By applying this principle and identifying a strain that is lethal when a test substance is applied to a non-essential gene disruption strain, the gene that is destroyed in that strain and the synthetic lethal relationship are revealed. . Then, the transcription product and / or translation product of the gene related to the synthetic lethality is considered to be a target molecule of the test substance (Hartwell et al, Science, 1997, 278: 1064-8, Parsons et al, Nat Biotechnol, 2004, 22: 62-9).

  In addition, even if a gene that has a synthetic lethal relationship with a certain gene is not known, the target molecule of the test substance can be determined by comprehensively analyzing the effects on about 4800 non-essential gene disruption strains. It is also possible to estimate. For example, a substance whose target molecule is already known is allowed to act on about 4800 kinds of non-essential gene disruption strains, and comprehensive sensitivity patterns are obtained. This operation is performed for a plurality of possible substances. Next, a test substance whose target molecule is not known is allowed to act on about 4800 kinds of non-essential gene-disrupted strains to comprehensively acquire sensitivity patterns, and compare with the previously acquired sensitivity patterns of a plurality of substances. As a result, if there is a substance showing a sensitivity pattern that matches or resembles the pattern obtained by the test substance, the target molecule of the test substance is considered to be the same as the target molecule of the substance.

  Furthermore, for example, when a disrupted strain of a gene group present in a specific metabolic pathway is specifically sensitive, the target is either the metabolic pathway itself or a gene present in a metabolically related pathway. It becomes a molecular candidate.

  In addition, for an essential gene, a strain in which one of the two alleles is disrupted (hereinafter sometimes referred to as “hetero-deficient strain”), and / or a gene affected by the test substance and / or Protein can be detected. Here, the essential gene refers to a gene that fails to proliferate and die if both of the two alleles are destroyed. In addition, about 1200 genes out of about 6000 total genes of yeast are essential genes.

  For example, a hetero-deficient strain of gene C, which is an essential gene, is affected by a test substance that inhibits the transcription product and / or translation product of gene C, and the function of the transcription product and / or translation product of gene C decreases. As a result, it shows a specific sensitivity to the test substance (Drug-induced haploinsufficiency) (Giaever et al, Nature genetics, 1999, 21: 278-283). By applying this principle and identifying a strain that is lethal when a test substance is allowed to act on a hetero-deficient strain, the gene that has been destroyed in that strain becomes clear. A transcription product and / or translation product of a gene disrupted in the hetero-deficient strain is considered to be a target molecule for the test substance.

  Furthermore, using a non-essential gene-disrupted strain, it is possible to detect genes and / or proteins that are affected by the test substance using specific resistance to growth suppression by the test substance.

  For example, a disrupted strain of gene D, which is a non-essential gene, is disrupted even when the concentration of the wild-type strain is inhibited when a test substance that inhibits the transcription product and / or translation product of gene D is allowed to act. The growth of the strain may not be inhibited. By applying this principle and identifying a strain whose growth is not inhibited when a test substance is allowed to act on a non-essential gene-disrupted strain, the gene disrupted in that strain becomes clear. The transcript and / or translation product of the gene disrupted in the non-essential gene disruption strain is considered to be a target molecule of the test substance or a molecule present in the same signal transduction pathway as the target molecule (Heitman et al, Proc Natl Acad Sci US A. 1991, 88: 1948-52).

  FIG. 5 shows a hardware configuration diagram of an apparatus for executing the evaluation method and the detection method according to the present invention. As shown in FIG. 5, the analysis device 10 used in the present invention includes a CPU 12, an input device 14 such as a mouse and a keyboard, a display device 16 including a CRT, a RAM (Random Access Memory) 18, and a ROM. (Read Only Memory) 20, a portable recording medium driver 22 for accessing a portable recording medium 23 such as a CD-ROM or DVD-ROM, a hard disk device 24, and a communication control interface for controlling data exchange with the outside ( I / F) 26. The analysis device 10 used in the present invention is connected to the detection device 30 via an input / output control I / F, and communicates data obtained by the detection device 30 and data analyzed by the analysis device 10. It can be carried out. As is clear from FIG. 5, a personal computer or the like can be used as the apparatus 10 according to the present embodiment.

  The detection device 30 used in the present invention is not limited to the following devices, but is a flow cytometry analysis device that measures the number of cells, a spectrophotometer that detects turbidity as an index related to the number of cells, Examples include a fluorometer that detects fluorescence intensity, a device that detects the number of colonies and a cell area, and a device that detects the amount of DNA. When a spectrophotometer is used, data relating to absorbance can be taken into the analysis apparatus 10 of the present invention as data reflecting cell growth. On the other hand, for data relating to gene expression, for example, in an apparatus for detecting the amount of DNA, a DNA chip can be photographed with a CCD camera or the like, and data relating to the signal intensity for each spot can be sent to the analysis apparatus 10.

  The aforementioned portable recording medium stores a program for executing the data conversion process used in the present invention and a program for analyzing the processed data. Therefore, the portable recording medium drive 22 reads out the above program from the portable recording medium 23, stores it in the hard disk device 24, and starts it, whereby the personal computer uses the analysis used in the present invention. It becomes possible to operate as a device. Alternatively, the program may be downloaded via an external network such as the Internet.

  FIG. 6 is a functional block diagram of a main part of the analysis apparatus 10 according to the present invention. The analysis device 10 performs analysis based on the input unit 51 that obtains data serving as an index relating to the number of cells obtained by the above-described spectrophotometer, the data storage unit 52 that stores the data, and the data. A conversion unit 53 for converting the functions necessary for the above-mentioned functions, for example, the control curve function and the test curve function, a calculation unit 54 for performing integration using the function, and a result in the calculation unit 54 are displayed. Display unit 55. The data storage unit 52 can store data related to the function and the like obtained by the calculation unit 54.

  FIG. 7 is a flowchart conceptually showing a program for executing the evaluation method according to the present invention. In the following, for convenience of description of the evaluation method of the present invention, turbidity will be described as an index of the number of yeast cells using data on absorbance obtained with a spectrophotometer. In step S10, the absorbance for each time in the absence of the test substance is obtained from the spectrophotometer at the input unit 51. Thereafter, a function representing the change in absorbance actually measured by the conversion unit 53 is obtained from the change in absorbance with respect to the obtained time. As described above, this function can be obtained by a method of approximating the actually measured absorbance at two times with a straight line, a method of applying the least square method to the measured value, or the like. By this method, a function (F (t)) of the control curve of the number of cells in the absence of the test substance is obtained (see step S11). On the other hand, by adopting the same method, as shown in step S12, the absorbance for each time in the presence of the test substance is input from the spectrophotometer, and the function of the test curve of the number of cells in the presence of the test substance ( G (t)) can also be obtained (see step S13). In the present invention, even if the order of steps S10 and S11 and steps S12 and S13 is reversed, an “area value” described later can be calculated.

  In the calculation unit 54, the integration is performed by the equation (F (t) −G (t)) from the functions of F (t) and G (t). In a preferred embodiment of the present invention, as shown in step S14, a measurement time zone common to both functions (hereinafter referred to as “effective time”) is obtained from the functions of F (t) and G (t). Can do. Thereafter, integration can be performed using the formula (F (t) −G (t)) within the range of the effective time (see step S15). In the preferred embodiment of the present invention, as described above, the integral value depends on the effective time at the time of integration. Therefore, as shown in step S16, the integral value is divided by the effective time. Thus, the “area value” can be calculated. Based on this area value, it is possible to evaluate the action and / or effect of the test substance on the cells. Specifically, if the area value (absolute value) is a large value, it is estimated that the action and / or effect of the test substance on the cell is strong, and conversely, the area value (absolute value) is small. It is estimated that the action and / or effect of the test substance on the cells is weak. In FIG. 7, for the sake of convenience of explanation, it has been explained that data relating to the cell number index in the absence of the test substance is acquired. However, data acquisition relating to the cell number index in the presence of the test substance is started. However, a similar evaluation is possible.

  When carrying out the evaluation method according to the present invention described above, when a cell in which at least one gene is deficient, mutated or overexpressed or a cell in which the expression of the transcription product and / or translation product of the gene is regulated is used, With respect to the action and / or effect of the test substance on the cell, it can be evaluated whether or not the gene affects the cell. When the evaluation method according to the present invention is carried out using a cell in which a different gene is deleted, mutated or overexpressed, or a cell in which the expression of a transcription product and / or translation product of the gene is regulated, a gene that is deleted, mutated or overexpressed Alternatively, it may be possible to determine whether a test substance acts on a gene whose expression of a transcription product and / or translation product is regulated. Furthermore, the evaluation method according to the present invention is carried out using a cell in which a different gene is deleted, mutated or overexpressed in a plurality of cells, or a cell in which expression of a transcription product and / or translation product of a gene is regulated. Then, it is judged whether the test substance acts on the gene whose deletion, mutation or overexpression, or the gene whose transcription product and / or translation product is regulated, and is affected by the test substance. Genes and / or proteins can be determined. For example, based on the area value for each cell of a plurality of cells, genes and / or proteins having an area value greater than or less than a predetermined value are classified from the deviation value of the area value, and are affected by the test substance. Genes and / or proteins can be found. And by collating with the external database mentioned later, the information regarding the function regarding a gene and / or protein can be obtained, and the function information relevant to a test substance can also be acquired.

  In the evaluation method according to the present invention, the test substance itself can be applied to either a known or unknown substance. In addition, when the unknown substance is compared with a substance whose properties of the test substance itself are known, the cell growth inhibition pattern is almost the same, and the area value of the unknown substance is the same as the area value of the known substance In addition, it can be assumed that such an unknown substance has a similar effect to that of a known substance.

  The evaluation method according to the present invention can also be a method for detecting a gene affected by a test substance and a protein expressed from the gene. For example, when the function of a gene affected by a test substance is known, using the test substance, a cell whose disrupted gene is unknown is used in the same process as the evaluation method according to the present invention (see FIG. 7). If S10 to S17) are carried out and if the cell growth inhibition pattern and area value similar to the gene affected by the test substance are shown, it is assumed that the disrupted gene has the same properties as the gene of known function Is done.

  In this way, using a cell in which various genes are deleted, mutated or overexpressed, or a cell in which the expression of the transcription product and / or translation product of the gene is regulated, the sensitivity of the cell to a single test substance is determined as an area value. Can be evaluated. It is also possible to relate the relationship between a test substance and a gene whose deficient, mutated or over-expressed gene or transcription product and / or translation product is regulated and / or its protein as follows. FIG. 8 shows a gene and / or protein thereof whose expression of a defective, mutated or overexpressed gene or transcript and / or translation product is regulated based on the area value obtained by the evaluation method of the present invention. A flowchart of a method for associating a function with a function. First, in step S20, the genes to be destroyed are classified based on the area values obtained by the evaluation method according to the present invention. For example, deviation values can be calculated based on all area values and classified into those having a specific deviation value. Next, an external database having gene and / or protein function information is queried via the communication control I / F of the analysis apparatus 10 according to the present invention (see step S21). Functional information of the gene and / or its protein whose expression of the expressed gene or transcript and / or translation product is regulated can be obtained. Examples of the external database include LocusLink (http://www.ncbi.nlm.nih.gov/LocusLink/). This gene and / or protein functional information includes categories such as Gene Ontology (biological process), Gene Ontology (cellular component), Gene Ontology (molecular function), etc., and the functional information of such genes and / or proteins Can be obtained. Each Gene Ontology has a hierarchical function, and is classified into more detailed functions from the upper layer to the lower layer.

  Next, in step S23, it is determined whether or not a gene, and / or a protein thereof, in which the expression of a defective, mutated or overexpressed gene or transcription product and / or translation product is regulated, and / or its protein are included in the category. As a result, genes that are regulated in the expression of the deficient, mutated or overexpressed genes or transcripts and / or translation products and / or proteins thereof are not included if they are included in a specific functional category And / or can be identified and displayed as a protein. Such steps S20 to S24 are executed by the calculation unit 54 of the analysis apparatus 10 of the present invention (see FIG. 6). In addition, when identifying and displaying, it can also display by color.

  The method for displaying the genes described in FIG. 8 based on the functional information is not limited to the results obtained by the evaluation method according to the present invention, and uses gene expression data obtained from the analysis of a DNA chip or the like. It is also possible to determine whether or not it is included in a specific function category, and to display whether or not it is included in the category. The gene expression data is not limited to the data obtained by the above-described DNA chip method, and can also be applied to data obtained by the differential display method and the quantitative PCR method.

  The present invention will be described in more detail with reference to the following examples of the present invention, but these are illustrative, and the present invention is not limited to the following specific examples. Those skilled in the art can implement the present invention by making various modifications to the embodiments shown below, and such modifications are included in the scope of the claims of the present application.

[Example 1] Comparison of evaluation methods using the Yeast deletion set method In order to confirm that the method of the present invention is excellent as a method for evaluating the action and / or effect of a test substance on cells, about 4800 kinds are evaluated. The effect of benomyl and lovastatin was examined using a set of non-essential gene disruption strains (Invitrogen # 95401.H2 and Open biosystems, # YSC1066) consisting of the yeast cell strains.

  First, in order to determine the concentrations of benomyl and lovastatin used in the study, the following experiment was conducted. The concentration of benomyl (Sigma-aldrich, # 38,158-6) is 0.23μg / ml-120μg / ml and the concentration of lovastatin (Sigma-aldrich, # M2147) is 3.91μM-1000μM in a 96-well plate Added as follows. One colony was picked up from the parent strain (BY4743) (Open biosystems, # YSC1050), and then left for 2 days. Subsequently, static culture was performed at 30 ° C. for 2 days. Then, using a plate reader (ARVO, PerkinElmer), the absorbance at 650 nm was measured to obtain the turbidity of the culture solution. As a result, for benomyl and lovastatin, concentrations of 7.5 μg / mL and 500 μM were obtained, respectively, at which yeast growth was suppressed to 50% as compared to the absence of the compound.

  Next, about 4800 kinds of yeast cell lines contained in a set of non-essential gene disruption strains (Invitrogen # 95401.H2 and Open biosystems, # YSC1066) were glycerol stocked in a 96-well plate. Then, each yeast cell line stored in the glycerol stock was transferred to a 96-well plate at a 20-fold dilution and statically cultured for 3 days. On the other hand, 25 μl of YPAD (yeast extract-polypeptone-adenine-dextrose) medium containing 7.5 μg / ml benomyl or 500 μM lovastatin or YPAD medium containing no compound was added to wells in a 384 well plate. Each cultivated yeast cell strain (Invitrogen for Benomyl and Open Biosystems for lovastatin) was inoculated into the 384-well plate so as to be diluted 2000 times (0 hr). Then, it culture | cultivated at 25 degreeC.

  After starting the culture, the absorbance at 650 nm was measured over time using a plate reader (ARVO, Perkin Elmer) for about 15 to 65 hours or 85 hours to obtain the turbidity of the culture solution. Before the measurement, the plate was shaken with a shaker to suspend the culture solution uniformly.

  Based on the data obtained from these measurements, the turbidity of the culture solution was plotted for each yeast cell line in the absence of the compound and in the presence of benomyl or lovastatin to obtain a time-dependent growth curve for each yeast cell line. . The area value (ARS) was calculated from these two curves by the following method, and the sensitivity was ranked.

  ARS was calculated as follows. First, for each yeast cell line, Ts is the start time and end time of the time-dependent growth curve in the measurement time range of the time-dependent growth curve in the absence of compound and in the presence of benomyl or lovastatin. Was Te, and Te-Ts was the effective time. The time-dependent growth curve is obtained by connecting the absorbance at each measurement time with a straight line.A collection of regression lines that differ for each measurement time is used as the equation for the time-dependent growth curve. The equation was F (t), and the equation of the growth curve over time in the presence of benomyl or lovastatin was G (t). The area S of the part surrounded by two time-dependent growth curves at the effective time Te-Ts was calculated by the following formula.

  Here, since the effective time Te-Ts varies from experiment to experiment, it is not preferable to compare the area S2 between experiments. Therefore, in order to facilitate comparison between experiments, the area S2 divided by the effective time Te-Ts was defined as ARS, and the sensitive strains were ranked.

  On the other hand, for comparison with the conventional method, a parameter (hereinafter sometimes referred to as GDS) based on the delay of the cell growth rate was calculated based on the same data.

GDS was calculated as follows. For each yeast cell line, the absorbance of the culture medium in the absence of the compound and in the presence of benomyl or lovastatin was converted by Log2. For each time-dependent growth curve, out of the straight lines connecting the absorbance at each measurement time converted by Log2, the one with the largest slope was taken out and the slope was defined as a _max . Calculating the slope of the line in order from the measurement start time, the start point of the straight line that is first detected with a 55% or more of the slope of a _max and the starting point Ps of the logarithmic growth phase, 55% or less of a _max The end point Pe of the logarithmic growth phase is defined as the start point of a straight line having an inclination. An approximate straight line was obtained from the absorbance between Ps and Pe by the least square method, and this was used as a regression line in the logarithmic growth phase. Then, the absorbance at the end time of the time-dependent growth curve in the absence of the compound was defined as maxOD, and a value obtained by converting half of the absorbance into Log2 was defined as midOD. In the regression line obtained previously, the time for midOD in the absence of the compound and in the presence of benomyl or lovastatin was defined as Tc and Tt, respectively. And GDS was computed by Tt-Tc.

  FIG. 9 shows a typical graph pattern. From the results, the ARS according to the present invention reflected the appearance of the graph as compared with the GDS. Among these susceptible strains, strains that prolong the doubling time of cells by benomyl treatment (A), strains that delay entry into the logarithmic growth phase by benomyl treatment (B), and saturation cell count decreases by lovastatin treatment Stock (C) was included. From these results, it was revealed that the method of the present invention is excellent as a method for evaluating the action and / or effect of a test substance on cells (see FIG. 9D).

Example 2 Comparison of Evaluation Method and Detection Method Using Yeast Deletion Set Method The method of the present invention is excellent as a method for evaluating the action and / or effect of a test substance on cells and the test substance. To confirm that it is an excellent method for detecting affected genes and / or proteins, Tunica was used using a non-essential gene disruption strain set (Invitrogen # 95401.H2) consisting of approximately 4800 yeast cell lines. The effect of mycin was examined.

  First, the following experiment was conducted to determine the concentration of tunicamycin used in the study. Tunicamycin (T-7765, SIGMA) was added to a 96-well plate so that the concentration ranged from 0.2 μM to 100 μM. One parent colony (BY4743) (Open biosystems, # YSC1050) was picked up there, and then statically cultured for two days. Subsequently, static culture was performed at 30 ° C. for 2 days. Then, using a plate reader (Rainbow, SLT), the absorbance at 650 nm was measured to obtain the turbidity of the culture solution. As a result, a concentration of 0.5 μM was obtained for tunicamycin, in which the growth of yeast was suppressed to 50% compared to the absence of the compound.

  Next, about 4800 kinds of yeast cell lines contained in a non-essential gene disruption strain set (Open biosystems, # YSC1066) were glycerol stocked in a 96-well plate. Then, each yeast cell line stored in the glycerol stock was transferred to a 96-well plate at a 20-fold dilution and statically cultured for 3 days. On the other hand, 25 μl of YPAD medium containing 0.5 μM tunicamycin or YPAD medium containing no compound was added to wells in a 384 well plate. Then, each of the cultured yeast cell lines was inoculated into the 384 well plate so as to be diluted 2000 times (0 hr). Then, it culture | cultivated at 25 degreeC.

  After starting the culture, the absorbance at 650 nm was measured over time using a plate reader (ARVO, Perkin Elmer) for about 15 to 65 hours to obtain the turbidity of the culture solution. Before the measurement, the plate was shaken with a shaker to suspend the culture solution uniformly. Based on the data obtained by these measurements, the turbidity of the culture solution in the absence of the compound and in the presence of tunicamycin was plotted for each yeast cell line, and a time-dependent growth curve of each yeast cell line was obtained. ARS and GDS were calculated from these two curves, and those with a deviation value of 70 or more were judged as sensitive.

  As a result, when ARS was used as an index, 170 strains were determined to be sensitive, whereas when GDS was used as an index, 112 strains were determined to be sensitive. Of the 170 strains that were sensitive when using ARS as an index, 92 strains that did not become sensitive when using GDS as an index. All these strains could be judged as sensitive by the appearance of the graph. Some examples are shown in the figure (FIG. 10). The four strains listed here have been identified as sensitive strains in a report by Parsons et al. (Parsons et al, Nat Biotechnol, 2004, 22: 62-9). On the other hand, out of 112 strains that were sensitive when using GDS as an index, 35 strains that were not sensitive when using ARS as an index were 35 strains. Some of these strains were thought to be apparently not sensitive to the graph. Some examples are shown in the figure (FIG. 11). In this way, in GDS using the delay time of growth rate as an index, the growth curve over time is disturbed due to some outliers in turbidity measurement, and the regression line necessary for GDS calculation is not drawn properly, and accuracy is I can't get good results. In particular, about 4800 yeast cell lines are not suitable for uniformly detecting changes in sensitivity with the same index.

  From the above results, it was clarified that when ARS was used as an index, an evaluation consistent with the appearance of the graph was possible. On the other hand, when GDS is used as an index, even if the pattern is clearly sensitive to the appearance of the graph, it may not be judged to be sensitive, and conversely, the appearance of the graph is clearly not sensitive. It was shown that even a pattern to be determined may be determined to be sensitive.

  In addition, when YRS method was used to indicate ARS, YLR047C, SLG1, VMA13, and TPO1, which are known to be affected by tunicamycin, were detected. Since it was not detected, it was strongly suggested that ARS is a more accurate index than GDS.

[Example 3] Detection of drug-sensitive strains using the yeast deletion set method The method of the present invention is excellent as a method for evaluating the action and / or effect of a test substance on cells and has an influence on the test substance. In order to confirm that it is an excellent method for detecting the gene and / or protein to be received, an essential gene heterozygous strain set (Invitrogen, # 95401.H5R3) consisting of about 1200 yeast diploid cell lines was used. The effects of Zalagogic Acid A (Sigma-aldrich, # Z-2626) were examined. Here, about 1,200 kinds of yeast cell lines in the essential gene hetero-disrupted strain set are strains in which one of the two alleles of the essential gene is disrupted (hereinafter referred to as “hetero-deficient strain”). Sometimes). In addition, an essential gene refers to a gene in which cells cannot grow if both two alleles are destroyed. The screening of drug-sensitive strains using hetero-deficient strains is based on the principle that drug-induced haploinsufficiency shows specific sensitivity to the test substance as a result of a decrease in the gene copy number of the target molecule ( Giaever et al, Nature genetics, 1999, 21: 278-283).

  First, the following experiment was conducted in order to determine the concentration of zalagogic acid A used in the study. It added so that the density | concentration of Zaragogic acid A might become the range of 0.098micromol-50micromol to a 96 well plate. One parent colony (BY4743) (Open biosystems, # YSC1050) was picked up and colonized for 2 days, and then poured into 1/1000. Next, static culture was continued at 30 ° C. for 2 days. Then, using a plate reader (ARVO, PerkinElmer), the absorbance at 650 nm was measured to obtain the turbidity of the culture solution. As a result, for Zalagogic Acid A, a concentration of 20 μM was obtained at which the growth of yeast was suppressed to 50% compared to the absence of the compound.

  Next, about 1200 types of yeast cell lines included in the essential gene heterogeneous strain set were glycerol stocked in 384 well plates. Then, each yeast cell line stored in the glycerol stock was transferred to a 384-well plate at a 40-fold dilution, and statically cultured at 25 ° C. for 3 days. On the other hand, 25 μl of YPAD medium containing 20 μM of zalagogic acid A or YPAD medium containing no compound was added to wells in a 384 well plate. Then, the cultured yeast cell lines were inoculated into the 384-well plate so as to be diluted 1000 times (0 hr). Then, it culture | cultivated at 25 degreeC.

  After starting the culture, the absorbance at OD650 nm was measured over time using a plate reader (ARVO, Perkin Elmer) for about 20 to 31 hours, and the turbidity of the culture solution was obtained. Before the measurement, the plate was shaken with a shaker to suspend the culture solution uniformly. Based on the data obtained from these measurements, for each yeast cell line, plot the turbidity of the culture medium in the absence of the compound and in the presence of Zalagogic Acid A to obtain a growth curve over time for each yeast cell line. It was. ARS was calculated from these two curves, and the results are shown in Table 1. From the results shown in Table 1, the strain with the highest ARS was Δerg9 strain, which is a hetero-deficient strain of ERG9 (SGD accession number: S0001233), which is known as the target gene of Zaragogic Acid A (Kennedy et al , BBA, 1999, 1445: 110-122). Therefore, it was strongly suggested that ARS is a useful index in a method for detecting genes and / or proteins affected by a test substance using an essential gene disruption strain set. Moreover, it has been clarified that the method of the present invention is excellent as a method for detecting genes and / or proteins affected by a test substance.

  Table 1 shows ranking of genes, SGD accession number, ARS, and ARS deviation value in yeast cell lines corresponding to the top 10 rankings, ranking using ARS as an index.

[Example 4] Growth of mammalian cells by a method using cell area as an index Hela cells, which are human cancer cell lines, were treated with 10% fetal bovine serum, penicillin G (100 units / ml), streptomycin sulfate (100 µg / ml) and amphotericin. The cells were subcultured in DMEM medium containing B (250 ng / ml), and the cells were collected when they became confluent in the T-75 flask, and the number of cells was counted with a hemocytometer. After resuspending in the above medium so that the cell concentration becomes 1 × 10 ⁴ cells / ml, add 100 μl (1000 cells per well) to 6 wells of a 96-well culture plate, then at 37 ° C. and 5% CO ₂ . Cultured for 1 day. On the next day, 100 μl of the above medium was added (0 hr). Thereafter, the culture was continued at 37 ° C. and 5% CO ₂ . After 4 hours, 5 μl of 4 mg / ml cycloheximide (SIGMA C-6255) was added to 3 wells. Thereafter, after 17 hours, 28 hours, and 41 hours, the cell area per unit area was analyzed with a cell morphology screening apparatus ANAX (HTS-50, Panasonic) and used as an index regarding the number of cells. Based on the data obtained by the measurement, a time-dependent growth curve was prepared in the presence and absence of cycloheximide. The area value (ARS) was calculated from these two curves.

  FIG. 12 is a diagram showing the results obtained in Example 4 according to the present invention. From the results shown in FIG. 12, it is clear that ARS can be obtained not only in yeast but also in mammalian cells, and also when not only turbidity but also the cell area is used as an index relating to the number of cells. Became. And it became clear that ARS becomes an index of the cytostatic activity of cycloheximide. From the above, it was strongly suggested that the method of the present invention is useful as a method for evaluating the action and / or effect of a test substance on cells.

FIG. 1 shows a schematic diagram of growth inhibition patterns by typical test substances in 4800 kinds of non-essential gene disrupted strains. A solid line is a growth curve in the absence of the test substance, and a dotted line shows a growth curve in the presence of the test substance. FIG. 2 is an explanatory diagram of an analysis example of the growth inhibition pattern illustrated in FIG. FIG. 3 is a diagram for explaining an analysis in which an area surrounded by two growth curves in the absence (F (t)) and presence (G (t)) of a drug is used as an index relating to the number of cells. . FIG. 4 shows a schematic diagram of F (t) and G (t) used in the evaluation method according to the present invention when turbidity is used as an index relating to the number of cells. The black square indicates the turbidity at each time in the absence of the test substance as the absorbance value, and the black circle indicates the turbidity at each time in the presence of the test substance as the absorbance value. FIG. 5 is a block diagram showing an example of a hardware configuration of a computer which is an analysis apparatus according to the present invention. FIG. 6 is a block diagram illustrating an example of a functional configuration of an analysis apparatus that performs the evaluation method according to the present invention. FIG. 7 is a flowchart showing an outline of processing by the analyzing apparatus according to the present invention. FIG. 8 shows a flowchart of a method for associating a destroyed gene with a function based on the area value obtained by the evaluation method of the present invention. FIG. 9 shows the results obtained in Example 1 according to the present invention. In the figure, Δsec22, Δrsb1, and Δyhr116w indicate yeast cell lines in which SEC22 (SGD accession number: S0004258), RSB1 (SGD accession number: S0005575), and YHR116W (SGD accession number: S0001158) are destroyed, respectively. In the figure, “control” indicates the absorbance (OD 650 nm) of the culture solution with respect to the elapsed time in the absence of the compound. “Treatment” in FIGS. 9A and 9B shows the absorbance (OD 650 nm) of the culture solution with respect to the elapsed time in the presence of 7.5 μg / mL benomyl. “Treatment” in FIG. 9C shows the absorbance (OD 650 nm) of the culture solution with respect to the elapsed time in the presence of 500 μM lovastatin. FIG. 10 shows the results obtained in Example 2 according to the present invention. In the figure, Δylr047c, Δslg1, Δvma13, and Δtpo1 destroy YLR047C (SGD accession number: S0004037), SLG1 (SGD accession number: S0005534), VMA13 (SGD accession number: S0006240), and TPO1 (SGD accession number: S0003951), respectively. Shows the yeast cell line produced. In addition, “control” in the figure indicates the absorbance of the culture solution with respect to the elapsed time in the absence of tunicamycin (OD 650 nm), and “treatment” indicates the absorbance of the culture solution with respect to the elapsed time in the presence of 0.5 μM tunicamycin. (OD 650 nm). FIG. 11 shows the results obtained in Example 2 according to the present invention. In the figure, Δtfp1, Δgly1, Δcup5, and Δrpl39 destroy TFP1 (SGD accession number: S0002344), GLY1 (SGD accession number: S0000772), CUP5 (SGD accession number: S0000753), and RPL39 (SGD accession number: S0003725), respectively. Shows the yeast cell line produced. In the figure, “control” indicates the absorbance of the culture solution with respect to the elapsed time in the absence of tunicamycin (OD 650 nm), and “treatment” indicates the absorbance of the culture solution with respect to the elapsed time in the presence of 0.5 μM tunicamycin (OD). 650 nm). FIG. 12 shows the results obtained in Example 4 according to the present invention. In the figure, ◯ indicates the cell area per unit area with respect to the elapsed time in the absence of cycloheximide, and ● indicates the elapsed time in the presence of cycloheximide.

Explanation of symbols

DESCRIPTION OF SYMBOLS 10 ... Analyzing device, 12 ... CPU, 14 ... Input device, 16 ... Display device, 18 ... RAM, 20 ... ROM, 22 ... General recording medium driver, 23 ... General recording medium, 24 ... Hard disk device, 26 ... Communication control interface 30 ... Detection device 51 ... Input unit 52 ... Data storage unit 53 ... Conversion unit 54 ... Calculation unit 55 ... Display unit

Claims (48)

A method for evaluating the action and / or effect of a test substance on a cell, comprising:
(1) A function F (t) of the control curve with respect to the time of the index relating to the number of cells in the absence of the test substance, a function G (t) of the test curve with respect to the time of the index relating to the number of cells in the presence of the test substance, Obtaining a process;
(2) calculating an integral value of the equation (F (t) −G (t)) to obtain an area value;
(3) evaluating the action and / or effect of the test substance based on the area value;
Evaluation method including The step (2)
The method according to claim 1, which is a step of obtaining an area value by calculating an integral value of an expression (F (t) −G (t)) within a predetermined time. The step (2)
A step of calculating an integral value S2 of the formula (F (t) -G (t)) within a predetermined time (Te-Ts ) by the formula (1) ;

Dividing the integral value S2 by the predetermined time (Te−Ts) according to the equation (2) to obtain an area value ARS ;

The method of claim 1 comprising:   The method according to any one of claims 1 to 3, wherein the step (1) is performed in a cell in which at least one gene is deficient, mutated or overexpressed.   The method according to claim 4, wherein the steps (1) to (3) are performed on a plurality of cells, and each of the cells is a cell in which a different gene is deleted, mutated or overexpressed.   The method according to any one of claims 1 to 3, wherein the step (1) is performed in a cell in which expression of a transcription product and / or translation product of at least one gene is regulated.   The method according to claim 6, wherein the steps (1) to (3) are performed on a plurality of cells, and each of the cells is a cell in which expression of a transcription product and / or translation product of a different gene is regulated.   Based on each area value obtained in the plurality of cells, cells having an area value greater than or less than a predetermined value are classified, and a gene and / or protein affected by the test substance is obtained. The method according to claim 5 or 7. A method for detecting genes and / or proteins affected by a test substance,
(1) A function F (t) of the control curve with respect to the time of the index relating to the number of cells in the absence of the test substance, a function G (t) of the test curve with respect to the time of the index relating to the number of cells in the presence of the test substance, Obtaining a process;
(2) calculating an integral value of the equation (F (t) −G (t)) to obtain an area value;
(3) detecting a gene and / or protein affected by the test substance based on the area value;
A detection method comprising: The step (2)
The method according to claim 9, which is a step of obtaining an area value by calculating an integral value of an expression (F (t) −G (t)) within a predetermined time. The step (2)
A step of calculating an integral value S2 of the formula (F (t) -G (t)) within a predetermined time (Te-Ts ) by the formula (1) ;

Dividing the integral value S2 by the predetermined time (Te−Ts) according to the equation (2) to obtain an area value ARS ;

The method of claim 9, comprising:   The method according to any one of claims 9 to 11, wherein the steps (1) to (3) are performed on a plurality of cells, and each of the cells is a cell in which a different gene is deleted, mutated or overexpressed. .   The steps (1) to (3) are performed on a plurality of cells, and each of the cells is a cell in which expression of a transcription product and / or translation product of a different gene is regulated. The method according to one item.   Based on each area value obtained in the plurality of cells, classify cells having an area value greater than or equal to a predetermined value, and obtain a gene and / or protein affected by the test substance, 14. A method according to claim 12 or 13. (4) The method according to any one of claims 1 to 14, further comprising a step of displaying a relationship between a gene and / or protein and the area value. (5) The method according to claim 15, further comprising the step of querying a database having gene and / or protein function information to obtain the gene and / or protein function information. The method according to claim 16, comprising displaying the function information of the acquired gene and / or protein in the step (5) . (5) Querying a database having gene and / or protein function information to obtain the function information of the gene and / or protein, and whether or not the gene and / or protein is included in a specific function category The method of claim 15, further comprising the step of discriminating. The said (5) process includes the process of identifying and displaying according to whether the said gene and / or protein are contained in the category of a specific function, The method as described in any one of Claims 16 thru | or 18 Method.   20. The method according to any one of claims 1 to 19, wherein the indicator relating to the number of cells is an indicator by a non-destructive technique without collecting cells or culture medium.   21. The method according to claim 20, wherein the indicator relating to the number of cells is an indicator selected from glucose consumption, turbidity, cell number, cell area, and fluorescence intensity.   The method according to any one of claims 1 to 21, wherein the cell is a eukaryotic cell.   23. The method of claim 22, wherein the eukaryotic cell is yeast.   23. The method of claim 22, wherein the eukaryotic cell is a mammalian cell. A program for causing a computer to evaluate the action and / or effect of a test substance on a cell,
(1) A function F (t) of the control curve with respect to the time of the index relating to the number of cells in the absence of the test substance, a function G (t) of the test curve with respect to the time of the index relating to the number of cells in the presence of the test substance, Obtaining a process;
(2) calculating an integral value of the equation (F (t) −G (t)) to obtain an area value;
(3) evaluating the action and / or effect of the test substance based on the area value;
A program that executes. The step (2)
The program according to claim 25, which is a step of obtaining an area value by calculating an integral value of an expression (F (t) -G (t)) within a predetermined time. The step (2)
A step of calculating an integral value S2 of the formula (F (t) -G (t)) within a predetermined time (Te-Ts ) by the formula (1) ;

Dividing the integral value S2 by the predetermined time (Te−Ts) according to the equation (2) to obtain an area value ARS ;

The program according to claim 25, comprising:   The program according to any one of claims 25 to 27, wherein the step (1) is performed in a cell in which at least one gene is deleted, mutated or overexpressed.   The program according to claim 28, wherein the steps (1) to (3) are performed on a plurality of cells, and each of the cells is a cell in which a different gene is deleted, mutated or overexpressed.   The program according to any one of claims 25 to 27, wherein the step (1) is performed in a cell in which expression of a transcription product and / or translation product of at least one gene is regulated.   The program according to claim 25, wherein the steps (1) to (3) are performed on a plurality of cells, and each cell is a cell in which expression of a transcription product and / or translation product of a different gene is regulated.   Based on each area value obtained in the plurality of cells, cells having an area value greater than or less than a predetermined value are classified, and a gene and / or protein affected by the test substance is obtained. 32. The program according to claim 29 or 31. A program for causing a computer to detect genes and / or proteins affected by a test substance,
(1) A function F (t) of the control curve with respect to the time of the index relating to the number of cells in the absence of the test substance, a function G (t) of the test curve with respect to the time of the index relating to the number of cells in the presence of the test substance, Obtaining a process;
(2) calculating an integral value of the equation (F (t) −G (t)) to obtain an area value;
(3) detecting a gene and / or protein affected by the test substance based on the area value;
A program that executes. The step (2)
The program according to claim 33, which is a step of obtaining an area value by calculating an integral value of an expression (F (t) -G (t)) within a predetermined time. The step (2)
A step of calculating an integral value S2 of the formula (F (t) -G (t)) within a predetermined time (Te-Ts ) by the formula (1) ;

Dividing the integral value S2 by the predetermined time (Te−Ts) according to the equation (2) to obtain an area value ARS ;

34. The program of claim 33, comprising:   36. The program according to any one of claims 33 to 35, wherein the steps (1) to (3) are performed on a plurality of cells, and each of the cells is a cell in which a different gene is deleted, mutated or overexpressed. .   37. The process according to any one of claims 33 to 36, wherein the steps (1) to (3) are performed on a plurality of cells, and each of the cells is a cell in which expression of a transcription product and / or translation product of a different gene is regulated. The program according to one item.   The cells having an area value greater than or equal to a predetermined value are classified based on each area value obtained in the plurality of cells, and a gene and / or protein affected by the test substance is obtained. The program according to 36 or 37. (4) The program according to any one of claims 25 to 38, further including a step of displaying a relationship between the gene and / or protein and the area value. (5) The program according to claim 39, further comprising a step of referring to a database having gene and / or protein function information to obtain the gene and / or protein function information. 41. The program according to claim 40, comprising a step of displaying function information of the acquired gene and / or protein in the step (5) . (5) Querying a database having gene and / or protein function information to obtain the function information of the gene and / or protein, and whether or not the gene and / or protein is included in a specific function category 40. The program according to claim 39, further comprising a step of discriminating. The said (5) process includes the process of identifying and displaying by the said gene and / or protein being included in the category of a specific function, It is described in any one of Claims 40 thru | or 42 program.   44. The program according to any one of claims 25 to 43, wherein the index relating to the number of cells is an index obtained by collecting cells and / or a culture solution and / or using a non-destructive technique.   45. The program according to claim 44, wherein the indicator relating to the number of cells is an indicator selected from glucose consumption, turbidity, cell number, cell area, and fluorescence intensity.   The program according to any one of claims 25 to 45, wherein the cell is a eukaryotic cell. The program according to claim 46, wherein the eukaryotic cell is yeast. The program according to claim 46, wherein the eukaryotic cell is a mammalian cell.

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