Isotope distribution data creation method

Abstract

An isotope distribution data production method according to the present invention includes: preparing, as samples each containing a metabolite of cells cultured in a culture medium containing a substrate labeled with a stable isotope, a plurality of analysis samples in which the concentrations of the metabolite are varied; subjecting the plurality of analysis sample to mass spectrometry separately under the same analysis conditions; and subjecting the plurality of analysis samples to the analysis of mass spectrum data obtained by the mass spectrometry to identify the type of the metabolite contained in each of the analysis samples and to determine the number of metabolites included in a metabolite group consisting of a metabolite of a non-labeled type and / or a metabolite of a labeled type and the signal intensity of a mass peak corresponding to each of all isotopomers included in the metabolite group. Subsequently, the number of the metabolites included in the metabolite group and the signal intensities of a mass peak of each of the metabolites included in the metabolite group and corresponding to the all types of the metabolites, which have been determined above, are compared among the plurality of analysis samples to select an analysis sample to be used for the determination of an isotope distribution of each metabolite. The data about the isotope distributions of the metabolites, which are obtained by the analysis of the mass spectrum data for the selected analysis sample for each metabolite are integrated together to produce an isotope distribution data of the metabolites.

Description

[Technical field]

[0001] The present invention relates to a method for generating data on isotope distribution in metabolites in cultured cells. [Background technology]

[0002] In vivo, protein activity changes with fluctuations in transcription and translation of genomic DNA due to environmental influences such as diet, drugs, exercise, and various stresses. Such changes are thought to be reflected in the metabolism of various substances, including organic acids, amino acids, and other low molecular weight compounds, within cells. Therefore, analyzing intracellular metabolic flux is useful for elucidating the causes of specific diseases, screening for drug discovery, and evaluating the productivity of substance-producing cells. A series of techniques for analyzing intracellular metabolic flux is called metabolic flux analysis.

[0003] Metabolic flux analysis often involves the use of stable carbon isotopes. 13 Cells are cultured in a medium containing a substrate labeled with C, and the culture solution is prepared to prepare a sample for analysis. The intracellular metabolites contained in the sample are then qualitatively and quantitatively measured, and based on the results, it is estimated which metabolic pathway consumed the substrate taken up into the cells and what substance it was taken up into. For example, 13 C-substituted glucose (hereafter, [1- 13 When cells were cultured using glucose as a substrate, the amount of [1- 13 C] When glucose is consumed in glycolysis, one 13 C-containing pyruvate (called labeled pyruvate) 13 Pyruvate that does not contain C (called unlabeled pyruvate) is produced in a 1:1 ratio. On the other hand, [1- 13When [C] glucose is consumed in the pentose phosphate pathway, only unlabeled pyruvate is produced. Therefore, if pyruvate is identified as one of the types of metabolites contained in a sample and the distribution of the proportion of labeled pyruvate and the proportion of unlabeled pyruvate in the total pyruvate (i.e., the distribution of isotopes) in the sample is obtained, the branching ratio between glycolysis and the pentose phosphate pathway can be estimated.

[0004] The types of all metabolites contained in a sample are identified, and the isotope distributions of each metabolite are calculated. The results are then processed using a specified analysis tool to obtain a metabolic map that illustrates the metabolic pathway. Software used as an analysis tool for metabolic flux analysis is individually developed by researchers and companies. In recent years, information platforms that comply with application programming interfaces (APIs) have been provided to make data interchangeable between various software used in the biomedical field (Non-Patent Document 1). [Prior art documents] [Non-patent literature]

[0005] [Non-Patent Document 1] Garuda Platform, NPO Systems Biology Research Institute, [online], [Retrieved June 21, 2021], Internet<http: / / www.garuda-alliance.org / about.html> Summary of the Invention [Problem to be solved by the invention]

[0006] Cells contain various types of metabolites. Therefore, in metabolic flux analysis, it is common to perform comprehensive qualitative and quantitative analysis of intracellular metabolites using a mass spectrometer. However, the amount of metabolites in cells varies depending on the type. In addition, in order to obtain the isotope distribution of various metabolites, it is necessary to measure the amount of multiple metabolites of the same type that have different mass numbers equal to the number of stable isotopes incorporated, but the amounts of these metabolites often differ greatly. In the following explanation, metabolites that have incorporated stable isotopes (metabolites in which some of the constituent elements of the metabolite have been replaced with stable isotopes) are called "isotope isomers."

[0007] Because the dynamic range of the mass spectrometer limits the range of detectable signal intensity, it is impossible to measure the amount of all metabolites contained in a sample in a single analysis. Conventionally, when the mass spectrum obtained by performing mass spectrometry on a certain sample contains a peak whose signal intensity exceeds the upper limit of quantitative measurement (saturation) or is near the lower limit, the amount of metabolites was determined by trial and error, such as diluting or concentrating the sample to create a new sample for analysis and performing mass spectrometry again. This caused a problem in that it took a long time to identify all the types of metabolites in the cell and determine the distribution of isotopes in each type of metabolite.

[0008] Note that, although we have described here the problems involved in the analysis of intracellular metabolites using a mass spectrometer for the purpose of metabolic flux analysis, similar problems exist in the analysis of low molecular weight metabolites using a mass spectrometer for the purposes of lipidomics analysis, proteomics analysis, etc.

[0009] An object of the present invention is to provide a method for rapidly obtaining data on the distribution of isotope isomers in intracellular metabolites. [Means for solving the problem]

[0010] In order to solve the above problems, the isotope distribution data creation method according to the present invention comprises the steps of: A preparation step of preparing a plurality of analysis samples having different concentrations of metabolites as samples containing metabolites of cells cultured in a medium containing a substrate labeled with a stable isotope; an analysis step of performing mass spectrometry on each of the plurality of analytical samples under the same analysis conditions; a determination step of identifying the type of the metabolites contained in each of the plurality of analytical samples by analyzing the mass spectrum data obtained by the mass spectrometry, and determining the number of metabolites contained in a metabolite group consisting of unlabeled metabolites, which are metabolites of the same type but not incorporating the stable isotope, and / or isotope isomers, which are metabolites incorporating one or more stable isotopes, and the signal intensities of mass peaks corresponding to all of the metabolites contained in the metabolite group; a selection step of selecting an analysis sample for determining the isotope distribution of each metabolite by comparing the number of metabolites included in the metabolite group corresponding to all types of metabolites determined in the determination step and the signal intensities of the mass peaks of the metabolites included in the metabolite group among the multiple analysis samples; a data creation step of integrating data on the isotope distribution of each metabolite obtained by analyzing the mass spectrum data of the analytical sample selected for each metabolite, and creating isotope distribution data of all types of metabolites determined in the determination step; It has the following characteristics. Effect of the Invention

[0011] According to the present invention, data on the isotope distribution of intracellular metabolites can be obtained more quickly than in conventional methods in which mass spectrometry was performed through repeated trial and error to determine the types and amounts of intracellular metabolites. [Brief description of the drawings]

[0012] [Figure 1] 1 is a flowchart of an embodiment of a method for generating isotope distribution data according to the present invention. [Figure 2A]Table showing the relative signal intensities of mass peaks of metabolites in seven metabolite groups obtained for each analytical sample diluted 10-fold, 100-fold, and 1000-fold. [Figure 2B] Table showing the relative signal intensities of mass peaks of metabolites in six metabolite groups obtained for each analytical sample diluted 10-fold, 100-fold, and 1000-fold. [Diagram 3] Isotope distribution data converted for analysis tools. [Figure 4] An example of a metabolic map. [Diagram 5] A bar graph showing the ratio of the contents of metabolites contained in the lactate metabolite group 12 hours and 24 hours after the start of culture, inserted into the metabolic map. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0013] The present invention will be described in detail below.

[0014] 1 is a flow chart showing one embodiment of the isotope distribution data creation method according to the present invention. In the isotope distribution data creation method according to the present invention, first, a plurality of analytical samples with different concentrations of metabolites are prepared as samples for mass spectrometry of metabolites in cells cultured in a medium containing a substrate labeled with a stable isotope (Step 1). Step 1 corresponds to the preparation step of the present invention.

[0015] In the present invention, the sample to be analyzed is typically a sample derived from a living organism. Examples of samples derived from a living organism include blood, tissues, and cells collected from a living organism, or feces, urine, nasal mucus, and saliva discharged from a living organism to the outside of the living organism. In addition to samples derived from a living organism, samples to be analyzed may also include plants, soil, water collected from the sea, rivers, lakes, and the like, sewage, and industrial wastewater. Examples of cells include microorganisms such as mold, yeast, and bacteria, or cells or tissues of multicellular organisms. In the present invention, a raw sample containing intracellular metabolites is obtained by culturing cells that are the sample to be analyzed themselves, or cells contained in the sample to be analyzed. In this case, a culture solution is collected from a medium in which cells are cultured, and the culture solution is centrifuged or unnecessary components contained in the culture solution are filtered using a filter to recover only the cells, and the intracellular metabolites are extracted using an organic solvent or the like to prepare a raw sample, and the raw sample is diluted or concentrated at different magnifications to prepare an analytical sample. Methods for concentrating the raw sample include removing the solvent from the raw sample by solid-phase extraction, and reducing the amount of solvent added when preparing the raw sample. By diluting or concentrating the raw material sample, the concentration of metabolites in the analytical sample can be lowered or increased. When preparing the raw material sample, it is advisable to carry out a pretreatment for mass spectrometry to remove substances that interfere with the ionization of metabolites contained in cells.

[0016] Next, each of the multiple analysis samples is introduced into a mass spectrometer, and mass analysis of the metabolites contained in the analysis samples is performed under the same conditions (step 2). Step 2 corresponds to the analysis step of the present invention. The mass spectrometer is not particularly limited, but it is preferable to use a type of device that has high resolution and can measure accurate mass. Examples of such mass spectrometers include quadrupole mass spectrometers and time-of-flight mass spectrometers. Liquid chromatograph mass spectrometers and gas chromatograph mass spectrometers can also be used. In addition, the ionization method of the mass spectrometer can be ESI (electrospray ionization), APCI (atmospheric pressure chemical ionization), or MALDI (matrix-assisted laser desorption ionization).

[0017] Stable isotopes are typically 13 C, but also 2 H, 15 N, 18 O. A substrate labeled with a stable isotope is a compound that can be taken up by the body and contains carbon, hydrogen, nitrogen, oxygen, etc. One example is the stable isotope 13 C-labeled glucose, specifically, the 1-carbon 13 Glucose substituted with C or all carbons 13 C substituted glucose.

[0018] When cells are cultured in a medium containing a substrate labeled with a stable isotope, the substrate is taken up into the cells and consumed in a metabolic pathway. As a result, metabolites into which a stable isotope has been incorporated (isotope isomers) or metabolites into which a stable isotope has not been incorporated (unlabeled metabolites) are produced, and mass peaks of unlabeled metabolites and / or isotope isomers appear on the mass spectrum obtained by performing mass spectrometry on an analytical sample. Usually, the mass-to-charge ratio m / z of the mass peak of an unlabeled metabolite is known. In addition, the mass numbers of unlabeled metabolites and isotope isomers differ by the number of isotopes incorporated into the metabolite. Therefore, if the mass peak of an unlabeled metabolite is identified, the mass peak of an isotope isomer constituting the same metabolite as the unlabeled metabolite can be identified.

[0019] In the method according to the present invention, mass spectrometry is performed on all analytical samples, and when mass spectrum data is obtained, the mass spectrum data is analyzed to identify the type of metabolite contained in each analytical sample, and the number of metabolites contained in a metabolite group consisting of unlabeled metabolites and / or isotope isomers and the signal intensities of mass peaks corresponding to all metabolites contained in the metabolite group are determined (Step 3). Step 3 corresponds to the determination step of the present invention.

[0020] Next, the number of metabolites contained in the metabolite group corresponding to all types of metabolites and the signal intensities of the mass peaks of all metabolites contained in the metabolite group are compared between multiple analytical samples, and an analytical sample for determining the isotope distribution of each metabolite is selected (Step 4). Step 4 corresponds to the selection step of the present invention.

[0021] The criteria for selecting samples for analysis may be, for example: <Criterion 1> An analytical sample in which the signal intensities of mass peaks corresponding to all metabolites contained in a certain metabolite group are within a predetermined range and which contains the largest number of metabolites in the metabolite group is selected as the analytical sample for determining the isotope distribution of the metabolites in that metabolite group.

[0022] The predetermined range refers to a detectable range set in the mass spectrometer, or a particularly reliable range within the detectable range.

[0023] For example, when there are samples obtained by diluting the raw material sample 10-fold, 100-fold, and 1000-fold as analytical samples, and there are m metabolites whose types have been identified by analyzing the mass spectrum data of each sample, it is examined whether the sample that satisfies the above criterion 1 is a 10-fold, 100-fold, or 1000-fold diluted sample for all of the m metabolite groups corresponding to those m metabolites. In criterion 1, a sample with a small dilution ratio tends to be selected as the analytical sample for determining the isotope distribution in the case of a metabolite that is present in a small amount in cells, and a sample with a large dilution ratio tends to be selected as the analytical sample for determining the isotope distribution in the case of a metabolite that is present in a large amount in cells and has a relatively uniform stable isotope distribution.

[0024] <Criterion 2> If multiple analytical samples for determining the isotope distribution are selected as a result of the selection based on criterion 1, the maximum mass peak, which is the mass peak with the greatest signal intensity among the mass peaks corresponding to all metabolites contained in the metabolite group, is further compared between the multiple analytical samples, and the analytical sample with the maximum mass peak having the greatest signal intensity is selected as the analytical sample for determining the isotope distribution of metabolites in the metabolite group.

[0025] According to criterion 2, the signal intensity of the mass peak is large, and the isotope distribution in the metabolite can be determined based on the highly reliable mass spectrum data.

[0026] <Criterion 3> The spectral data selected for each metabolite group is determined so as to maximize the number of metabolite groups from which a common sample for analysis will be selected. Criterion 3 allows for the generation of data on the isotope distribution of as many metabolites as possible using mass spectral data obtained from a single sample, thereby minimizing the impact of differences in dilution and concentration rates on the analytical results.

[0027] The data on the isotope distribution of each metabolite obtained by analyzing the mass spectrum data of the analytical sample selected for each metabolite is integrated to generate isotope distribution data of all types of metabolites (Step 5). Step 5 corresponds to the data generation step of the present invention.

[0028] The data generated by the method of the present invention can be processed, for example, by the open platform "Garuda", and the processed results can be inserted, for example, into a metabolic map that illustrates metabolic pathways. The metabolic pathways included in the metabolic map can include the glucose metabolic system, which is a basic metabolic pathway of microorganisms. The glucose metabolic system includes the glycolysis pathway, the pentose phosphate pathway, the citric acid cycle, and the like. road etc. Includes:

[0029] [Specific example] Next, the method for generating isotope distribution data according to the present invention will be described with a specific example. As a substrate, [1- 13 C] A microorganism (Escherichia coli) was cultured in a medium containing glucose, and the culture solution was sampled over time and filtered to obtain a bacterial cell pellet. Then, the bacterial cell constituent proteins contained in the bacterial cell pellet were extracted using an organic solvent to prepare a raw material sample, which was then diluted 10-fold, 100-fold, and 1000-fold to prepare analytical samples. Hereinafter, these samples will be referred to as the 10-fold diluted sample, the 100-fold diluted sample, and the 1000-fold diluted sample, respectively.

[0030] Next, these 10- to 1000-fold diluted samples were analyzed by LC-MS (liquid chromatography mass spectrometry) to obtain mass spectrum data for each sample. As a result of analyzing these mass spectrum data, the types of metabolites were identified as alanine, aspartic acid, glutamic acid, proline, glycine, serine, pyruvic acid, lactic acid, citric acid, α-ketoglutaric acid, succinic acid, fumaric acid, and malic acid, and the mass peaks of the unlabeled metabolites and isotopic isomers (metabolite groups) of these 13 types of metabolites were identified.

[0031] Of the 13 types of metabolites, pyruvate and lactate are representative metabolites of the glycolytic pathway, while citric acid, α-ketoglutaric acid, fumaric acid, succinic acid, and malic acid are representative metabolites of the citric acid cycle. Other metabolites of the glycolytic pathway include glucose 6-phosphate and phosphoenolpyruvate. Erythrose 4-phosphate and ribulose 5-phosphate are also known as representative metabolites of the pentose phosphate pathway mentioned above. Alanine, aspartic acid, glutamic acid, proline, glycine, and serine are representative metabolites of amino acids.

[0032] Figures 2A and 2B show the relative signal intensities of the mass peaks of the metabolites contained in the above 13 types of metabolites, which were obtained by analyzing the mass spectrum data of each sample. In Figures 2A and 2B, "n" in "M+n" represents the number of molecules incorporated into the metabolite. 13 It represents the number of C. In other words, "M+0" is a metabolite. 13"M+1" indicates that no C was incorporated into the metabolite. 13 C is incorporated. The metabolites labeled with "M+0" correspond to the unlabeled metabolites of the present invention, and the metabolites labeled with "M+1" to "M+6" correspond to the isotopic isomers.

[0033] In addition, in Figures 2A and 2B, metabolites with a relative signal intensity of "0" are metabolites that were not present in the sample or were present in trace amounts and had signal intensities below the lower limit. Therefore, Figures 2A and 2B show that, for example, the metabolite group of "alanine" contained one unlabeled metabolite and three isotope isomers, and the metabolite group of "proline" contained one unlabeled metabolite and five isotope isomers.

[0034] In addition, in Figures 2A and 2B, the signal intensity of each metabolite is expressed as a relative value so that the sum of the signal intensities of the metabolites contained in each metabolite group is "1". Therefore, the isotope distribution of each metabolite group can be known from the relative values ​​shown in Figures 2A and 2B. For example, the signal intensities of each metabolite of alanine metabolite group in a 10-fold diluted sample are "M+0": 27%, "M+1": 8.6%, "M+2": 15%, "M+3": 49 %, and "M+4":0%.

[0035] In this embodiment, the analysis results are compared between a 10-fold diluted sample, a 100-fold diluted sample, and a 1000-fold diluted sample according to the above-mentioned criteria 1 to 3, and a sample for determining the isotope distribution is selected.

[0036] For example, in the case of the glutamic acid metabolite group, the 10-fold and 100-fold diluted samples detected mass peaks of six types of metabolites (one type of unlabeled metabolite and five types of isotope isomers), whereas the 1000-fold diluted sample detected zero mass peaks, so the 1000-fold diluted sample was excluded from the selection. Also, by simply comparing the values ​​shown in Figure 2A, no difference was observed between the 10-fold diluted sample and the 100-fold diluted sample, but the mass peak signal intensity was generally low and unstable in the 100-fold diluted sample, whereas the mass peak signal intensity was reproducible in the 10-fold diluted sample. From the above, the 10-fold diluted sample was adopted as the sample for determining the isotope distribution in the glutamic acid metabolite group.

[0037] For example, in the case of the metabolites of lactic acid, B Although it cannot be determined by simply comparing the values ​​shown in the table, the signal intensity of the "M+0" mass peak in the 10-fold and 100-fold diluted samples was beyond the detectable range (saturated), so the 1000-fold diluted sample was used as the sample for determining the isotope distribution.

[0038] Figure 3 shows excerpts of isotope distribution data for some of the 13 types of metabolites (lactate, alanine, glycine, succinate) 12 hours and 24 hours after the start of culture. The isotope distribution data in Figure 3 was created by selecting any of 10- to 1000-fold diluted samples as analytical samples that satisfy the above-mentioned criterion 1, or criterion 1 and criterion 2, or criterion 3 for the signal intensities of the mass peaks of unlabeled metabolites and isotope isomers contained in the 13 types of metabolites, and integrating data on the isotope distribution of the metabolites obtained by analyzing the respective mass spectrum data.

[0039] The results of analyzing the isotope distribution data shown in FIG. 3 using a specified analysis tool are inserted into a metabolic map, for example, as shown in FIG. 4. Examples of analytical results inserted into the metabolic map include bar graphs, as shown in FIG. 5. The left side of each bar graph in FIG. 5 shows the signal intensity (relative value) of the mass peak of lactate after 12 hours of culture, and the right side shows the signal intensity (relative value) of the mass peak of lactate after 24 hours of culture. From these bar graphs, it is possible to determine the amount of lactate that has been imported. 13 The amount of lactate with 0 to 2 C was decreased after 24 hours of incubation compared to after 12 hours of incubation, whereas the amount of lactate taken up was decreased after 24 hours of incubation compared to after 12 hours of incubation. 13 It can be seen that the content of lactate with 3 and 4 C's increased after 24 hours of culture compared to after 12 hours of culture. Therefore, by inserting such a bar graph into the metabolic map, the metabolic flux can be visually understood.

[0040] [Aspects] It will be appreciated by those skilled in the art that the exemplary embodiments described above are examples of the following aspects.

[0041] (Section 1) A method for generating isotope distribution data according to one aspect of the present invention includes the steps of: A preparation step of preparing a plurality of analysis samples having different concentrations of metabolites as samples containing metabolites of cells cultured in a medium containing a substrate labeled with a stable isotope; an analysis step of performing mass spectrometry on each of the plurality of analytical samples under the same analysis conditions; a determination step of identifying the type of the metabolites contained in each of the plurality of analytical samples by analyzing the mass spectrum data obtained by the mass spectrometry, and determining the number of metabolites contained in a metabolite group consisting of unlabeled metabolites, which are metabolites of the same type but not incorporating the stable isotope, and / or isotope isomers, which are metabolites incorporating one or more stable isotopes, and the signal intensities of mass peaks corresponding to the metabolites contained in the metabolite group; a selection step of selecting an analysis sample for determining the isotope distribution of each metabolite by comparing the number of metabolites included in the metabolite group corresponding to all types of metabolites determined in the determination step and the signal intensities of the mass peaks of the metabolites included in the metabolite group among the multiple analysis samples; a data creation step of integrating data on the isotope distribution of each metabolite obtained by analyzing the mass spectrum data of the analytical sample selected for each metabolite, and creating isotope distribution data of all types of metabolites determined in the determination step; It has the following characteristics.

[0042] In the method for generating isotope distribution data described in paragraph 1, multiple analytical samples with different metabolite concentrations are prepared in advance, and these multiple analytical samples are subjected to mass spectrometry under the same conditions. trout Then, the spectral data obtained for each of the plurality of analytical samples is trout The spectral data is analyzed to identify the type of metabolites contained in each analytical sample, and to determine the number of unlabeled metabolites and isotope isomers contained in a metabolite group corresponding to each type of metabolite, and the signal intensity of the mass peak corresponding to the metabolite contained in the metabolite group. The unlabeled metabolites contained in a certain metabolite group can be identified from a mass peak of a known mass number observed on a mass spectrum. On the other hand, the isotope isomers can be identified from a plurality of mass peaks whose mass numbers differ from the mass peak of the unlabeled metabolite by an amount corresponding to the number of stable isotopes. Note that when the metabolite group includes both unlabeled metabolites and isotope isomers, it may include only a plurality of isotope isomers whose number of stable isotopes differs.

[0043] After the number of metabolites included in the metabolite group corresponding to each type of metabolite and the signal intensities of the mass peaks corresponding to the metabolites included in the metabolite group are determined, the determined number of metabolites and signal intensities are compared between the multiple analysis samples to select an analysis sample for determining the isotope distribution of each metabolite, and one piece of isotope distribution data is generated regarding the isotope distribution of all types of metabolites determined in the determination step. The conditions for selecting an analysis sample for generating data regarding the isotope distribution of each metabolite include the number of metabolites included in the metabolite group and the signal intensities of the mass peaks corresponding to the metabolites included in the metabolite group. all Examples of the requirements include that the signal intensities of the mass peaks corresponding to the metabolites are within a predetermined range, that the number of metabolites contained in the metabolite group is large, that the signal intensities of the mass peaks corresponding to the metabolites contained in the metabolite group are highly reproducible or stable, etc. Also, an analytical sample for determining the isotope distribution of each metabolite may be selected so as to maximize the number of metabolite groups for which a common analytical sample is selected.

[0044] According to the method for generating isotope distribution data described in the first paragraph, data on the isotope distribution of intracellular metabolites can be obtained more quickly than in the conventional method in which mass spectrometry was performed through repeated trial and error to determine the types and amounts of intracellular metabolites.

[0045] (Section 2) In the method for creating isotope distribution data in paragraph 1, The selection step is carried out to select a group of metabolites. All An analytical sample in which the signal intensity of the mass peak corresponding to the metabolite falls within a predetermined range and which contains the largest number of metabolites in the metabolite group can be selected as the analytical sample for determining the isotopic distribution of the metabolites in that metabolite group.

[0046] In the method for generating isotope distribution data in Section 2, data on stable isotopes in metabolites can be obtained by using mass spectrum data of an appropriate analytical sample according to its intracellular content.

[0047] (Section 3) In the method for generating isotope distribution data according to the second aspect, the selection step further comprises: A maximum mass peak, which is the mass peak with the greatest signal intensity among the mass peaks corresponding to the metabolites contained in the metabolite group, can be compared between the multiple analytical samples, and the analytical sample with the maximum mass peak with the greatest signal intensity can be selected as the analytical sample for determining the isotope distribution of the metabolites in that metabolite group.

[0048] In the method for generating isotope distribution data in the third paragraph, the signal intensity of the mass peak is large, and the isotope distribution in the metabolite can be obtained based on the highly reliable mass spectrum data.

[0049] (Section 4) In the method for creating isotope distribution data in paragraph 1, The selection step may determine the spectral data selected for each metabolite group so as to maximize the number of metabolite groups for which a common sample for analysis will be selected.

[0050] The method for generating isotope distribution data described in Section 4 can generate data on the isotope distribution of as many metabolites as possible using mass spectral data obtained from a single analytical sample, thereby minimizing the effects of differences in dilution and concentration ratios on the analytical results.

Claims

1. A preparation step of preparing a plurality of analysis samples having different concentrations of metabolites as samples containing metabolites of cells cultured in a medium containing a substrate labeled with a stable isotope; an analysis step of performing mass spectrometry on each of the plurality of analytical samples under the same analysis conditions; a determination step of identifying the type of the metabolites contained in each of the plurality of analytical samples by analyzing the mass spectrum data obtained by the mass spectrometry, and determining the number of metabolites contained in a metabolite group consisting of unlabeled metabolites, which are metabolites of the same type but not incorporating the stable isotope, and / or isotope isomers, which are metabolites incorporating one or more stable isotopes, and the signal intensities of mass peaks corresponding to the metabolites contained in the metabolite group; a selection step of selecting an analysis sample for determining the isotope distribution of each metabolite by comparing, among the plurality of analysis samples, the number of metabolites included in the metabolite group corresponding to all types of metabolites determined in the determination step and the signal intensities of the mass peaks of the metabolites included in the metabolite group; a data creation step of integrating data on the isotope distribution of each metabolite obtained by analyzing the mass spectrum data of the analytical sample selected for each metabolite, and creating isotope distribution data of all types of metabolites determined in the determination step; The method for generating isotope distribution data comprises:

2. The selection step comprises:

2. The method for generating isotope distribution data according to claim 1, wherein an analytical sample in which the signal intensities of mass peaks corresponding to all metabolites included in a certain metabolite group are within a predetermined range and which contains the largest number of metabolites in the metabolite group is selected as the analytical sample for determining the isotope distribution of metabolites in the metabolite group.

3. The selection step further comprises:

3. The isotope distribution data creation method according to claim 2, further comprising the steps of: comparing, among the mass peaks corresponding to all metabolites included in the metabolite group, a maximum mass peak which is a mass peak with the greatest signal intensity among the plurality of analytical samples; and selecting, as the analytical sample for determining the isotope distribution of metabolites in the metabolite group, the analytical sample having the maximum mass peak with the greatest signal intensity.

4. The selection step comprises: determining which spectral data are selected for each metabolite group so as to maximize the number of metabolite groups for which a common analytical sample will be selected; The method for generating isotope distribution data according to claim 1 .

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