Isotope distribution ratio evaluation program, isotope distribution ratio evaluation method, isotope distribution ratio evaluation device, and metabolic flux analysis device

Abstract

The present disclosure proposes an isotope distribution ratio evaluation method in which: in order to evaluate the reliability of an isotope distribution ratio and perform a highly-reliable metabolic flux analysis, a plurality of isotopes are quantified from a fitting curve obtained by fitting, with a prescribed function, measurement values of a mass chromatogram of a plurality of isotopes having different mass numbers with respect to a compound fragment to be measured; the quantitative result for the plurality of isotopes is used to calculate an isotope distribution ratio of the compound fragment and quantitative reliability indices of the plurality of isotopes, which indicate the reliability of the quantitative result for the isotopes; the quantitative reliability indices of the plurality of isotopes are used to calculate a reliability index of the isotope distribution ratio; and the reliability index is displayed on a display screen (see Fig. 1A).

Description

Isotope distribution ratio evaluation program, isotope distribution ratio evaluation method, isotope distribution ratio evaluation device, and metabolic flux analysis device

[0001] The present disclosure relates to an isotope distribution ratio evaluation program, an isotope distribution ratio evaluation method, an isotope distribution ratio evaluation device, and a metabolic flux analyzer.

[0002] In regenerative medicine and drug discovery support, it is necessary to use high-quality cells cultured under appropriate conditions, and culture quality control is necessary. Currently, development is underway on a method for controlling culture quality using techniques such as component analysis of culture medium supernatant. In component analysis of culture medium supernatant, culture quality is controlled by monitoring changes in the concentrations of nutritional components such as amino acids and glucose, and metabolic components such as pyruvate and lactic acid. However, there is not enough knowledge about the advanced culture quality control required when inducing stem cell differentiation. The inventors have so far used metabolic flux analysis to identify metabolic pathways that are key to quality control of cell culture, identify metabolic components involved in those metabolic pathways, and develop a technology to systematically select metabolic components to be monitored. In metabolic flux analysis, first, 13 After culturing cells in a medium containing a C isotope-labeled substrate, the metabolites extracted from the cells are analyzed by mass spectrometry to determine the isotope distribution ratio of the metabolites. Then, based on a metabolic model defined by a network of metabolic reactions within the cells, 13 The diffusion of C atoms is calculated to reproduce the isotope distribution ratio of metabolites evaluated by mass spectrometry. From these results, the reaction rate of metabolites in each metabolic reaction is estimated, and metabolic pathways that are key to quality control of cell cultures are identified. Details of metabolic flux analysis technology are described, for example, in Non-Patent Document 1.

[0003] There are several documents regarding methods for evaluating isotope distribution ratios required for metabolic flux analysis. For example, Patent Document 1 discloses a technique for evaluating isotope distribution ratios by performing gas chromatography mass spectrometry on multiple metabolite samples with different concentrations under the same conditions to obtain data, selecting data for calculating isotope distribution ratios from the perspective of signal intensity, number of metabolites, and number of isotopes in a metabolite mass chromatogram (a graph in which signal intensity is plotted against elution time), quantifying each metabolite from the selected data, and calculating the isotope distribution ratio.

[0004] Furthermore, Non-Patent Document 2 discloses a method for quantifying metabolites from a fitting curve obtained by fitting a mass chromatogram with a function, and the results of examining multiple functions that can be applied to fitting the mass chromatogram.

[0005] International Publication No. 2023 / 002548

[0006] L.Quek et al., Microbial Cell Factories, 8, 25 (2009)M.Phillips et al., Journal of Chromatographic Science, 35, 76 (1997)

[0007] However, in samples with low metabolite concentrations, the isotope distribution ratio evaluated by mass spectrometry varies greatly due to the influence of contaminants in the sample, and even if the method disclosed in the above-mentioned document is used, the reliability of the calculated isotope distribution ratio cannot be determined. The isotope distribution ratio is calculated based on the quantification results of multiple isotopes of the metabolite being evaluated. Therefore, the reliability of the isotope distribution ratio must be evaluated based on the reliability of the quantification of each isotope.

[0008] However, the above-mentioned literature does not mention any technique for evaluating such reliability. Therefore, in order to perform metabolic flux analysis with higher reliability, it is desirable to be able to evaluate the reliability of the obtained isotope distribution ratio. The present disclosure has been made in consideration of such circumstances and provides a technique for evaluating the reliability of the isotope distribution ratio.

[0009] In order to solve the above-mentioned problems, the present disclosure proposes an isotope distribution ratio evaluation method executed by a processor, the method including: the processor acquiring measurement values ​​of a mass chromatogram of a plurality of isotopes having different mass numbers for a compound fragment to be measured; the processor quantifying the plurality of isotopes from a fitting curve obtained by fitting the mass chromatogram with a predetermined function; the processor calculating an isotope distribution ratio of the compound fragment using the quantification results of the plurality of isotopes; the processor calculating quantitative reliability indexes for a plurality of isotopes that indicate the reliability of the quantification results of the plurality of isotopes; the processor calculating a reliability index of the isotope distribution ratio using the quantitative reliability indexes for the plurality of isotopes; and outputting the reliability index of the isotope distribution ratio to an output unit that outputs a calculation result.

[0010] Further features related to the present disclosure will become apparent from the description of this specification and the accompanying drawings. Furthermore, aspects of the present disclosure are achieved and realized by the elements and combinations of various elements and the aspects of the following detailed description and the appended claims. It should be understood that the description of this specification is merely exemplary and does not limit the scope or application of the claims in any sense.

[0011] According to the technology of the present disclosure, it is possible to evaluate the reliability of the isotope distribution ratio, and it is also possible to perform a highly reliable metabolic flux analysis using the highly reliable isotope distribution ratio.

[0012] 1 is a diagram showing an overview of an isotope distribution ratio evaluation program according to an embodiment of the present disclosure. FIG. 2 is a block diagram showing an example configuration of a metabolic flux analyzer 100 having an isotope distribution ratio evaluation function according to this embodiment. FIG. 3 is a diagram showing evaluation results of the number of isotopes considered for calculating an isotope distribution ratio and the deviation from the true value of the isotope distribution ratio. FIG. 4 is a diagram showing an example configuration of a menu screen 300 of the program according to this embodiment. FIG. 5 is a diagram showing an analysis model used in metabolic flux analysis in the Examples and Comparative Examples. FIG. 6 is a list of metabolites (default) analyzed in the Examples and Comparative Examples. FIG. 7 is a diagram showing the isotope ratios of metabolites analyzed in a bar graph. FIG. 8 is a diagram showing a chromatogram of metabolite LAC123 in measurement sample 0421 and fitting results using a Gaussian function. FIG. 9 is a diagram showing reliability index values ​​of the isotope distribution ratios of each metabolite contained in multiple measurement samples (04101, 04201, 05101, 05201, 06101, 06201, etc.). FIG. 10 is a diagram showing the isotope ratios of metabolites analyzed in a bar graph. 1 is a diagram showing a chromatogram of metabolite SUC1234 in measurement sample 05101 and the results of fitting using a Gaussian function. It is a diagram showing reliability index values ​​of the isotope distribution ratios of each metabolite contained in multiple measurement samples (04101, 04201, 05101, 05201, 06101, 06201, etc.). It is a diagram showing the isotope ratios of the metabolites being analyzed in a bar graph. It is a diagram showing a chromatogram of metabolite LAC123 in measurement sample 0421 and the results of fitting using a Gaussian function. It is a diagram showing reliability index values ​​of the isotope distribution ratios of each metabolite contained in multiple measurement samples (04101, 04201, 05101, 05201, 06101, 06201, etc.) based on the coefficient of determination of fitting. It is a diagram showing the isotope ratios of the metabolites being analyzed in a bar graph. 1 shows a chromatogram of metabolite SUC1234 in measurement sample 05101 and the fitting results using a Gaussian function. 2 shows reliability index values ​​of the isotope distribution ratios of each metabolite contained in multiple measurement samples (04101, 04201, 05101, 05201, 06101, 06201, etc.).FIG. 1 shows the results of metabolic flux analysis in which metabolites with unreliable isotope distribution ratios were excluded from the analysis targets (Example: (a)), and the results of metabolic flux analysis in which all measured isotope distribution ratios were included in the analysis targets (Comparative Example: (b)).

[0013] The present embodiment relates to a method and program for evaluating isotope distribution ratios in metabolites, and a method and program for evaluating metabolic fluxes. The present embodiment also discloses a method for evaluating a reliability index of isotope distribution ratios and a highly reliable metabolic flux analysis method using the reliability index.

[0014] Hereinafter, the present embodiment will be described with reference to the accompanying drawings. In the accompanying drawings, functionally identical elements may be denoted by the same numerals, and redundant explanations will be omitted. Note that the accompanying drawings show specific embodiments and examples in accordance with the principles of the present disclosure, but these are intended to aid in understanding the present disclosure and are by no means to be used to interpret the present disclosure in a limiting manner.

[0015] Although the present embodiment has been described in sufficient detail to enable those skilled in the art to practice the present disclosure, it should be understood that other implementations and forms are possible, and that changes in configuration and structure and substitutions of various elements are possible without departing from the scope and spirit of the technical ideas of the present disclosure. Therefore, the following description should not be interpreted as being limited thereto.

[0016] <Outline of Isotope Distribution Ratio Evaluation Program> Figure 1A is a diagram showing an outline of an isotope distribution ratio evaluation program according to an embodiment of the present disclosure. The isotope distribution ratio evaluation program of this embodiment includes the steps of: measuring mass chromatograms of multiple isotopes with different mass numbers for a compound fragment to be measured by mass spectrometry (step 1); quantifying the multiple isotopes from multiple fitting curves obtained by fitting the mass chromatograms of the multiple isotopes with a function (step 2); calculating the isotope distribution ratio of the compound fragment using the quantification results of the multiple isotopes obtained in the quantification of the multiple isotopes (step 3); and displaying the isotope distribution ratio on a program screen (step 4). The step of quantifying the multiple isotopes (step 2) also includes a step of evaluating quantitative reliability indexes for the multiple isotopes. The isotope distribution ratio evaluation program of this embodiment further includes the steps of calculating a reliability index for the isotope distribution ratio using the quantitative reliability indexes for the multiple isotopes (step 5); and displaying the reliability index for the isotope distribution ratio on a program screen (step 6).

[0017] (i) Step 1 First, we will explain the step (step 1) of measuring mass chromatograms of multiple isotopes with different mass numbers for a compound fragment to be measured by mass spectrometry. It is generally known that there is a distribution in the number of neutrons in the constituent atoms of a compound. Therefore, the compound fragment to be measured also has a distribution in mass number. In this specification, following the usual practice, the isotope with the smallest mass number is denoted as M+0, and the isotope with n more neutrons in the compound than M+0 is denoted as M+n.

[0018] In step 1, a measurement sample containing cellular metabolites obtained by pretreating a culture supernatant from a cell culture is subjected to mass spectrometry, and a mass chromatogram of multiple isotopes with different mass numbers is measured for a target compound fragment. The target compound fragment includes ionized metabolites. Examples of metabolites include pyruvic acid, lactic acid, alanine, glycine, valine, leucine, succinic acid, fumaric acid, serine, threonine, α-ketoglutaric acid, malic acid, aspartic acid, glutamic acid, glutamine, and citric acid.

[0019] Pretreatment of the culture supernatant involves a contaminant removal process to remove as many contaminants as possible from the culture supernatant. Examples of pretreatment methods include solid-phase adsorption and ultrafiltration. Furthermore, to facilitate mass spectrometry, samples may be derivatized with a derivatizing agent, if necessary. Examples of derivatizing agents include methoxamine and N-methyl-N-tert-butyldimethylsilyltrifluoroacetamide (MTBSTFA). Examples of mass spectrometry methods include gas chromatography-mass spectrometry (GC-MS), liquid chromatography-mass spectrometry (LC-MS), and capillary electrophoresis-chromatography (CE-MS).

[0020] Note that step 1 can be substituted by a step of importing measured mass chromatogram data into the program of this embodiment. In this case, software for importing measured mass chromatogram data may be implemented in the program of this embodiment.

[0021] (ii) Step 2: Next, we will describe the step (step 2) of quantifying multiple isotopes from a fitting curve obtained by fitting multiple mass chromatograms with a function. In this step, multiple mass chromatograms are fitted using a function according to an algorithm such as the least-squares method (for example, fitting can be performed using the method disclosed in Non-Patent Document 2). The fitting parameters obtained in this step are used to quantify multiple isotopes and evaluate the quantitative reliability index for the multiple isotopes. Functions that can be used for fitting include Gaussian function, Bi-Gaussian function, Exponentially Modified Gaussian function, Fraser-Suzuki function, Log-normal function, Harrhoff-van der Lide function, Cauchy-Gaussian function, and Chesler-Cram function. Furthermore, isotopes can be quantified from the area values ​​of the mass chromatogram obtained from the fitting curve (the isotope ratio of each isotope can be calculated from the area ratio of the chromatograms). For example, when the Gaussian function defined by formula (1) is used, the isotope can be suitably quantified using formula (2).

[0022] Here, I is the signal intensity at elution time t, I0 is the maximum value of the signal intensity, a is the elution time, and σ is the peak width (standard deviation).

[0023] where A is the isotope amount, I ０ is the maximum signal intensity, and σ is the peak width (standard deviation).

[0024] Furthermore, the quantitative reliability index for multiple isotopes is not particularly limited as long as it is a fitting parameter obtained by fitting multiple mass chromatograms with a function or a value calculated using the fitting parameter. The fitting parameter may be a value obtained as a result of fitting, and examples include a fitting variable included in a function, a coefficient of determination for fitting, and a residual sum of squares. The quantitative reliability index for isotopes can be calculated using Equation (3).

[0025]

[0026] Here, n ｉ is the number of mass chromatogram data for isotope i, Y Ｄｉ，ｊ is the jth signal intensity of the mass chromatogram of isotope i, Y Ｆｉ，ｊ Is Y Ｄｉ，ｊ The signal intensity of the fitting curve of the mass chromatogram of isotope i at the same elution time, I ｍａｘ，Ｆ，ｉ is the maximum signal intensity of the fitting curve of the mass chromatogram of isotope i. Using equation (3), the quantitative reliability index of the isotope can be calculated based on the deviation of the measurement data from the fitting curve. In samples with low metabolite concentrations, the influence of impurities in the sample appears as a deviation between the measurement data and the fitting curve. Therefore, using equation (3) makes it possible to suitably calculate the reliability index of the isotope distribution ratio.

[0027] Another example of a quantitative reliability index is the coefficient of determination (r ２ ) are examples of the coefficient of determination. The coefficient of determination is an index that indicates the goodness of fit of a fitting formula model to measurement data, and is a value that can be easily obtained by fitting a mass chromatogram using a general-purpose programming language. The closer the coefficient of determination is to 1, the more accurate the fitting. Therefore, by using the coefficient of determination as a quantitative reliability index, it is possible to reduce the amount of calculation required by the program, which contributes to shortening the calculation time. There are no particular restrictions on the coefficient of determination, as long as it is an index that indicates the goodness of fit of a fitting formula model to measurement data. Equation (4) is known as an example of a definition formula for the coefficient of determination.

[0028] Here, n ｉ is the number of mass chromatogram data for isotope i, Y Ｄｉ，ｊ is the jth signal intensity of the mass chromatogram of isotope i, Y Ｆｉ，ｊ Is Y Ｄ，ｊ The signal intensity of the fitting curve of the mass chromatogram at the same elution time, Y Ｄｉ is the average signal intensity of the mass chromatogram of isotope i.

[0029] (iii) Step 3 Next, we will explain the step (step 3) of calculating the isotope distribution ratio of the compound fragment using the quantification results of multiple isotopes obtained in step 2. The isotope distribution ratio can be calculated using formula (5).

[0030] Here, r Ｍ＋ｎ is the isotope distribution ratio of the M+n isotope, and A Ｍ＋ｎ is the amount of M+n isotope.

[0031] In formula (5), it is preferable to calculate the isotope distribution ratio taking into account four or more isotopes. FIG. 2 is a diagram showing the results of an evaluation of the number of isotopes considered to calculate the isotope distribution ratio and the deviation from the true value of the isotope distribution ratio. In this evaluation, commercially available compounds were measured by GC-MS, and the isotope distribution ratio evaluated from the mass chromatogram of each compound fragment taking into account six isotopes (M+0 to M+5) was used as the true value. FIG. 2 shows that when the isotope distribution ratio is evaluated taking into account four or more isotopes (M+0 to M+3), the isotope distribution ratio can be evaluated with an accuracy of within 1%. Therefore, it is preferable to calculate the isotope distribution ratio taking into account four or more isotopes.

[0032] Furthermore, in the evaluation program and evaluation method of this embodiment, in addition to the isotope distribution ratio including the contribution of naturally occurring stable isotopes, the isotope distribution ratio corrected by subtracting the contribution of naturally occurring stable isotopes may also be output. 13 C is used to label carbon in metabolites, 13 The flux of intracellular metabolic reactions is estimated by simulating the isotope distribution ratio of metabolites after C labeling. However, it is difficult to perform simulations that take into account the contribution of natural stable isotopes. Therefore, metabolic flux analysis involves: 13Analysis is generally performed using the isotope distribution ratio corrected by subtracting the contribution of natural stable isotopes present in metabolites before C labeling. Note that isotope ratio correction can be performed using the proportion of naturally occurring stable isotopes using the matrix transformation described in the literature (R. Nilsson, Methematical Biosciences, 330, 108481 (2020)).

[0033] (iv) Step 4 Next, the step of displaying the isotope distribution ratio on the program screen (step 4) will be described. There are no particular restrictions on step 4, as long as it is a step of displaying the isotope distribution ratio evaluated in step 3 on the program screen. Step 4 may also be included in step 6, which will be described later.

[0034] (v) Step 5 Next, the step (step 5) of calculating the reliability index of the isotope distribution ratio using the quantitative reliability indexes of the multiple isotopes evaluated in step 3 will be described. In step 5, the reliability index of the isotope distribution ratio is calculated according to a defined calculation formula using the quantitative reliability indexes of the multiple isotopes. There are no particular limitations on the calculation formula as long as it is a formula that can calculate the reliability index of the isotope distribution ratio using the quantitative reliability indexes. As an example of the calculation formula, formula (6) can be used.

[0035]

[0036] where R is the reliability index of the isotope distribution ratio, w i is the weight of the quantitative reliability index of isotope i, d i is the quantitative reliability index for isotope i. When the coefficient of determination of fitting is used as the quantitative reliability index for isotope i, the larger the reliability index, the higher the reliability. On the other hand, when equation (3) is used as the quantitative reliability index for isotope i, the smaller the reliability index, the higher the reliability.

[0037] The weight of the quantitative reliability index of isotope i in formula (6) is not particularly limited as long as it indicates the contribution of the quantitative reliability index of isotope i to the reliability index of the isotope distribution ratio. When the contribution of the quantitative reliability index of isotope i to the reliability index is constant regardless of the type of isotope, it is given by formula (7).

[0038]

[0039] Here, w i is the weight of the quantitative reliability index for isotope i. For example, in the case of six isotopes (M+0 to M+5), i ranges from 0 to 5. If the contribution of the quantitative reliability index for isotope i to the reliability index is proportional to the ratio of the amount of isotope i to the total amount of isotopes, the weight of the determination coefficient for isotope i is given by equation (8).

[0040]

[0041] Here, w i is the weight of the quantitative reliability index of isotope i, and A i is the amount of isotope i. By using the weight of the quantitative reliability index of isotope i calculated using equation (7) or equation (8), the reliability index of the isotope distribution ratio can be suitably calculated using equation (6) depending on the contribution of the coefficient of determination of isotope i to the reliability index.

[0042] The reliability index of the isotope distribution ratio determined in step 5 can provide not only the reliability of the isotope distribution ratio but also insight into the measurement conditions of the mass spectrometry. For example, if leading or tailing occurs in the mass chromatogram as a result of mass spectrometry, the shape of the mass chromatogram will be distorted, resulting in a lower reliability index of the isotope distribution ratio determined using a fitting function (e.g., a Gaussian function) that does not address leading or tailing of the mass chromatogram. However, the reliability index of the isotope distribution ratio determined using a fitting function (e.g., an exponentially modified Gaussian function) that addresses leading or tailing of the mass chromatogram will exhibit a good value. On the other hand, if the mass chromatogram of the target compound fragment is overlapped with the peaks of contaminants, the reliability index of the isotope distribution ratio will be low, regardless of whether leading or tailing of the mass chromatogram is addressed. From the above example, by comprehensively evaluating the reliability indexes of the isotope distribution ratios obtained using multiple different fitting functions (e.g., by excluding metabolites with low isotope distribution ratios from the metabolic flux analysis, as described below), it is possible to obtain information about the cause of a decrease in the reliability index. Furthermore, the obtained information can also be used to estimate the failure mode of the mass chromatogram. For example, in the metabolic flux analyzer 100 described below, the processor 101 may display a sign (e.g., a black inverted display in Figure 6C described below) on the program screen indicating the possibility of a failure of the mass chromatogram (failure mode) when the reliability index of a specific isotope distribution ratio is below a predetermined threshold.

[0043] (vi) Step 6: Next, the step of displaying the reliability index of the isotope distribution ratio on the program screen will be described. Step 6 may be performed in any form, as long as it displays the reliability index of the isotope distribution ratio calculated in step 5 on the program screen. Step 6 may also be performed simultaneously with step 4. Furthermore, in step 4 or step 6, the mass chromatogram measured in step 1 and the fitting curve obtained in step 2 may be displayed on the same screen along with the isotope distribution ratio and the reliability index of the isotope distribution ratio. This display is effective for visually linking the reliability index with the presence or absence of impurities in the mass chromatogram. Furthermore, a GUI for selecting a display method for the isotope distribution ratio, the reliability index of the isotope distribution ratio, the mass chromatogram measured in step 1, and the fitting curve obtained in step 2 may be implemented in the program, allowing the user of the program to select the display method.

[0044] <Metabolic flux analysis> In metabolic flux analysis, first, 13 After culturing cells in a medium containing a C isotope-labeled substrate, the metabolites extracted from the cells are analyzed by mass spectrometry to determine the isotope distribution ratio. Then, based on a metabolic model defined by a network of metabolic reactions within the cells, the isotope distribution ratio in the metabolites is calculated. 13 The diffusion of C atoms is calculated to reproduce the isotope distribution ratio of the metabolites being analyzed, as evaluated by mass spectrometry. From these results, the reaction rate of the metabolites in each metabolic reaction (metabolic flux) can be estimated. Metabolic flux can be estimated from the isotope distribution ratio of the metabolites using metabolic flux estimation software (OpenFLUX, OpenMebius, etc.) available online.

[0045] In metabolic flux analysis, (i) the network of metabolic elementary reactions within the cell (intracellular metabolic model) and (ii) the metabolites to be analyzed must be determined at the start of the analysis. In the isotope distribution ratio evaluation program of this embodiment, metabolites included in the intracellular metabolic model are first selected from metabolites whose isotope distribution ratios have been calculated by mass spectrometry. Then, metabolites whose isotope distribution ratio reliability index of the selected metabolites exceeds a preset reliability index threshold are selected. While more data on the isotope distribution ratios of metabolites included in the intracellular metabolic model is preferable, unreliable isotope distribution ratios reduce the accuracy of metabolic flux estimation. Therefore, the isotope distribution ratio evaluation program of this embodiment enables highly reliable metabolic flux analysis.

[0046] The isotope distribution ratio evaluation program described above makes it possible to evaluate the reliability of the isotope distribution ratio. Furthermore, the use of highly reliable isotope distribution ratios makes it possible to perform highly reliable metabolic flux analysis.

[0047] <Metabolic Flux Analysis Apparatus Having Isotope Distribution Ratio Evaluation Function> FIG. 1B is a block diagram showing an example of the configuration of a metabolic flux analysis apparatus 100 having an isotope distribution ratio evaluation function according to this embodiment.

[0048] The metabolic flux analyzer 100 is an apparatus that executes the isotope distribution ratio evaluation program shown in FIG. 1A and can be realized by a computer. More specifically, the metabolic flux analyzer 100 includes a processor 101, a storage device 102 including a read-only memory (ROM) and a random access memory (RAM), an input device 103 including a keyboard, a mouse, and a touch panel, an output device 104 including a display device, a printer, and a communication device 105 for communicating with devices outside the apparatus. The storage device 102 may also be configured to include a drive for activating a memory (which may be a disk or USB) that stores the isotope distribution ratio evaluation program and the metabolic flux analysis program, reading data from the memory, and writing data to the memory.

[0049] The processor 101 reads the codes of the isotope distribution ratio evaluation program and the metabolic flux analysis program from the storage device 102 and expands them into an internal memory (not shown), thereby realizing various functional units 1011 to 1016. That is, the processor 101 includes therein a mass analysis unit 1011 that measures a mass chromatogram of a plurality of isotopes having different mass numbers by mass analysis, an isotope quantification unit 1012 that quantifies the plurality of isotopes and evaluates quantification reliability indexes for the plurality of isotopes, an isotope distribution ratio calculation unit 1013 that calculates an isotope distribution ratio of a compound fragment using the quantification results for the plurality of isotopes, an isotope distribution ratio reliability index calculation unit 1014 that calculates a reliability index for the isotope distribution ratio using the quantification reliability indexes for the plurality of isotopes, a display processing unit 1015 that performs processing to output the obtained isotope distribution ratio and the reliability index for the isotope distribution ratio to the output device 104, and a metabolic flux analysis unit 1016 that performs metabolic flux analysis by reflecting the obtained reliability index (evaluation result) of the isotope distribution ratio. The metabolic flux analysis device 100 may be configured without the metabolic flux analysis unit 1016, in which case it may be called an isotope distribution ratio evaluation device. The metabolic flux analysis device 100 includes the mass spectrometry unit 1011 as an internal component, but may be connected to a gas chromatograph to obtain the measurement results of a mass chromatogram therefrom.

[0050] Examples and comparative examples according to the present disclosure will be described below. In both the examples and comparative examples, 13 C glucose was metabolized by CHO cells cultured for different days, and the metabolites collected from the cells were used as measurement samples. The examples and comparative examples differ in that the former performs metabolic flux analysis in consideration of the above-mentioned isotope distribution ratio reliability data, whereas the latter performs metabolic flux analysis using all data obtained from the chromatogram.

[0051] CHO cells were cultured in Dulbecco's Modified Eagle's Medium (DMEM) as the basal medium according to the ATCC manual (temperature: 37°C, CO ２ Concentration: 5%). 24 hours before extracting metabolites from cells.13 The medium was replaced with one containing C-isotope-labeled glucose, and the cells were 13 C Glucose was metabolized in the medium. 13 The ratio of C glucose is [1- 13 C]glucose: [U- 13 The ratio of [C] glucose to unlabeled glucose was 1:1:2. The glucose concentration was 4.5 g / L. The culture days were 3, 4, 5, 6, and 7 days, and logarithmic growth of the cells was confirmed from the change in cell count during culture from 3 to 6 days.

[0052] Metabolites in CHO cells were extracted according to the following procedure. First, the medium was removed and the cells were washed three times with 1.0 mL of phosphate buffer. Then, 200 μL of methanol cooled to -20°C was added, and the cells were immobilized on ice for 10 minutes. Next, 300 μL of ultrapure water was added, and the cells were detached from the dish by rubbing with the tip of a pipette and collected together with the ultrapure water in a sample tube. The surface of the dish after cell detachment was then washed with 300 μL of ultrapure water, and the cells were collected together in a sample tube. The sample tube was immersed in vibrating water with floating ice and sonicated for 1 minute to disperse the recovered cells. Next, 800 μL of chloroform was added to the sample tube, and the mixture was vigorously shaken and stirred until cloudy, followed by another 30 minutes of vibration at 1,200 rpm and 4°C. The mixture was centrifuged at 11,500 rpm and 4°C for 30 minutes, and the upper layer containing dissolved metabolites was collected. The solvent was then removed using an evaporator to obtain intracellular metabolites.

[0053] The extracted intracellular metabolites were then derivatized for GC-MS analysis. First, 30 μL of 2% methoxamine hydrochloride (MOX reagent) was added to the intracellular metabolites obtained in the previous section, and the sample tube was immersed in ice-filled water and sonicated for 5 minutes. The sample was vigorously agitated, the solution in the sample tube was spun down, and then sonicated again, agitated, and spun down. The mixture was then left at 30°C for 2 hours with agitation at 1,200 rpm to allow the metabolites to react with methoxamine. Next, 45 μL of a mixed solution of N-Methyl-N-tert-butyldimethylsilyltrifluoroacetamide (MTBSTFA) and tert-butyldimethylchlorosilane (TBDMCS; 1%) was added, agitated using a vortex, spun down, and then reacted at 55°C for 1 hour with agitation at 1,200 rpm. Thereafter, the mixture was centrifuged at 13,300 rpm at 4° C. for 3 minutes, and the collected supernatant was used as a sample for GC-MS measurement.

[0054] The program of this example was created using MatLab (registered trademark) 2021a from MathWorks, Inc. Figure 3 is a diagram showing an example of the configuration of a menu screen 300 of the program of this example. The menu screen can include six types of menu items, for example, "0. Settings," "1-1. GC-MS measurement," "1-2. Data Retrieval," "2. Data Processing," "3. Results Display," and "4. Metabolic Flux Analysis." In addition, buttons corresponding to each menu item can be placed on the menu screen. The steps performed by clicking each button are described below.

[0055] <0. Settings> For example, an operator (user) can click the "0. Settings" button 310 shown in FIG. 3 to set detailed conditions for processes initiated by clicking other buttons. The configurable detailed conditions include the data format referenced in "1-2. Data Retrieval," the type of function used for data fitting of the mass chromatogram in "2. Data Processing," the formula for calculating the reliability index of the isotope distribution ratio in "3. Results Display," and the analytical model and number of simulations used in the metabolic flux analysis performed in "4. Metabolic Flux Analysis." The analytical model includes information on (i-1) an intracellular metabolic model and (i-2) metabolites to be analyzed. In this example and the comparative example, the data format was set to the ms1 format, the type of function was set to a Gaussian function, the formula for calculating the reliability index was set to Equation (7), the type of data to be displayed was set to "isotope distribution ratio, mass chromatogram and its fitting curve, and reliability index of the isotope distribution ratio," the analytical model was set to the model shown in FIG. 4, and the number of simulations was set to 50.

[0056] <1-1. GC-MS Measurement> For example, an operator (user) can launch the measurement program for the GC-MS instrument by clicking the "1-1. GC-MS Measurement" button 320 shown in Figure 3 (related to step 1 above). In this example and the comparative example, Chromeleon (registered trademark), software for operating a ThermoFisherScience GC-MS instrument (ISQ7000EI), was implemented. GC-MS measurements were performed in selected ion mode (SIM). The injection volume was 1 μL, and the helium flow rate was 1 mL / min. The split ratio during sample injection was 10, and the temperatures of the sample injection port, sample delivery line, and ion source were 250°C, 250°C, and 200°C, respectively. The measurement temperature range was 100°C to 300°C, and the column heating rate was 3.5°C / min. The measurement interval was 0.5 seconds. The measured mass chromatogram data was output in raw format and then converted to MS1 format. The data in ms1 format was then converted into a table of elution time x m / z.

[0057] <1-2. Data Retrieval> For example, an operator (user) can select the mass chromatogram data to be analyzed by clicking the "1-2. Data Retrieval" button 330 shown in Figure 3 (related to step 1 above). Clicking this button allows the user to load not only the mass chromatogram measured by clicking the "1-1. GC-MS measurement" button, but also mass chromatogram data measured separately. Furthermore, the selected MS1 format data is converted into a CSV file format in which signal intensities are arranged in a table of elution time x m / z, facilitating subsequent analysis. Pressing the "1-2. Data Retrieval" button 330 may also convert the acquired mass chromatogram data so that it can be processed by the isotope distribution ratio evaluation program.

[0058] <2. Data Processing> For example, an operator (user) clicks the "2. Data Processing" button 340 shown in Figure 3 to begin data analysis of the target mass chromatogram (related to steps 2, 3, and 5 above). In the programs of this example and the comparative example, after clicking the "2. Data Processing" button 340, the program first loads an analytical model for metabolic flux analysis and determines the target metabolite (default). The target metabolites (default) are shown in Figure 5. Next, the m / z and elution times of the isotopes (six types: M+0 to M+5) of the target metabolite (default) are loaded from the database, and this information is used to extract a mass chromatogram of the isotope of the target metabolite (default) from the target mass chromatogram data. Then, for each metabolite, the extracted mass chromatogram is fitted with a function to determine the isotope amount and the isotope quantification reliability index. In this example and comparative example, the mass chromatogram was fitted with a Gaussian function (Equation (1)) using the built-in function (fit) of MatLab® 2021, and the isotope amount was calculated using Equation (2). The quantitative reliability index of the isotope was then calculated using Equation (3) or Equation (4). The isotope distribution ratio was then calculated from the isotope amount using Equation (5), and the isotope distribution evaluation index was calculated from the quantitative reliability index using Equation (6) and Equation (7). The isotope distribution ratio, corrected by subtracting the contribution of naturally occurring stable isotopes, was also calculated using the matrix transformation described in the literature (R. Nilsson, Methematical Biosciences, 330, 108481 (2020)). Each metabolite can be determined by the time output from the gas chromatography column. Therefore, in tables such as Figure 6C, each row (horizontal cell) can be said to represent a time domain.

[0059] <3. Results Display> For example, an operator (user) can display the analysis results according to the type of display data set in "0. Settings" by clicking the "3. Results Display" button 350 shown in Fig. 3. In this example and comparative example, the type of display data was set to "isotope distribution ratio, mass chromatogram and its fitting curve, and reliability index of isotope distribution ratio." Note that the display format of the analysis results displayed on the program can be, for example, the formats shown in Figs. 6A to 6C (described below).

[0060] (Example of reliability index of isotope distribution ratio: form of presenting index value based on deviation from measurement data) Figures 6A and 7A are bar graphs showing the isotope ratio of the metabolite being analyzed. Figures 6A and 7A are designed to allow confirmation of the isotope distribution ratio of the metabolite being analyzed. Figure 6B is a diagram showing the chromatogram of metabolite LAC123 in measurement sample 0421 and the fitting results using a Gaussian function. Figure 6C is a diagram showing the reliability index values ​​of the isotope distribution ratio of each metabolite contained in multiple measurement samples (04101, 04201, 05101, 05201, 06101, 06201, etc.). Figure 7B is a diagram showing the chromatogram of metabolite SUC1234 in measurement sample 05101 and the fitting results using a Gaussian function. Similar to Fig. 6C, Fig. 7C is a diagram showing reliability index values ​​of the isotope distribution ratios of metabolites contained in multiple measurement samples (e.g., 04101, 04201, 05101, 05201, 06101, 06201, etc.). Note that in Fig. 6C and Fig. 7C (as well as Fig. 8C and Fig. 9C described below), taking 04101 as an example, the first two digits (04) of the measurement sample indicate the number of days the CHO cells have been cultured, and the next digit (101) indicates the lot number of the sample.

[0061] In this example, the quantitative reliability index of the isotope was calculated using Equation (3). The table in Figure 6C displays the reliability index of the isotope distribution ratio as a logarithmic reciprocal, with higher values ​​indicating higher reliability. Furthermore, in this example, cells in the table with an evaluation index (logarithmic value) of less than 1.5 are displayed in color (black inverted), allowing easy identification of metabolites for which low-reliability isotope distribution ratios were calculated. Furthermore, by clicking (selecting) any cell in the table, the measurement data points and fitting curves of the corresponding metabolite chromatograms (six types: M+0 to M+5) are displayed, as shown in Figures 6B and 7B. For example, the table in Figure 6C shows the metabolite LAC123 of sample 04201 selected. Unlike Figure 6C, Figure 7C shows the metabolite SUC1234 of sample 05101 selected.

[0062] As shown in FIG. 6B, the chromatogram of LAC123 (measurement sample: 4201), a metabolite with an evaluation index (logarithmic value) of 1.5 or more, shows that all measurement data points from M+0 to M+5 are well fitted with a Gaussian function. On the other hand, as shown in FIG. 7B, the chromatogram of SUC1234 (measurement sample: 05101), a metabolite with an evaluation index (logarithmic value) of less than 1.5, shows that in the measurement data with a molecular weight of M+5, a small peak overlaps the shoulder of the main peak, indicating that the measurement data points are not well fitted with a Gaussian function. In the case of FIG. 7B, at a molecular weight of M+5, the concentration of the metabolite is low and the influence of impurities is greater. This affects the fitting, and r ２ The value of the parameter (r ２ ) allows you to monitor the fitting status of the entire metabolite and determine whether the fitting is reliable.

[0063] From the above, it was found that the quality of fitting can be judged by displaying the reliability index of the isotope distribution ratio on the program screen. The quality of fitting affects the quantification of the isotope amounts used to calculate the isotope distribution ratio. Therefore, it was found that the reliability of the isotope distribution ratio can be judged by displaying the reliability index of the isotope distribution ratio on the program screen.

[0064] (Example of Reliability Indicator for Isotope Distribution Ratio: Presentation of Index Values ​​Based on the Coefficient of Determination) Next, we will explain an example in which the quantitative reliability index for isotopes is calculated using the coefficient of determination of fitting, and the analysis results are displayed in a table at the bottom right of the screen. Figures 8A and 9A are similar to Figures 6A and 7A, showing bar graphs of the isotope ratios of metabolites being analyzed. Figure 8B is similar to Figure 6B, showing the chromatogram of metabolite LAC123 in measurement sample 0421 and the fitting results using a Gaussian function. Figure 8C is a diagram showing the reliability index values ​​of the isotope distribution ratios of each metabolite contained in multiple measurement samples (04101, 04201, 05101, 05201, 06101, 06201, etc.) based on the coefficient of determination of fitting. Figure 8C shows the state in which metabolite LAC123 from sample 04201 is selected. Figure 9B, similar to Figure 7B, shows the chromatogram of metabolite SUC1234 in measurement sample 05101 and the results of fitting using a Gaussian function. Figure 9C, similar to Figure 8C, shows the reliability index values ​​of the isotope distribution ratios of each metabolite contained in multiple measurement samples (04101, 04201, 05101, 05201, 06101, 06201, etc.). However, unlike Figure 8C, Figure 9C shows the state in which metabolite SUC1234 of sample 05101 is selected. Note that in the tables of Figures 8C and 9C, the reliability evaluation index of the isotope distribution ratio is normalized to 100 when the quantitative reliability indexes of all fittings are full (1.000). In this example, cells in the table with an evaluation index value of less than 90 are displayed in color (black inverted display), making it easy to identify metabolites for which the isotope distribution ratio was calculated with low reliability. Furthermore, as in Figures 6C and 7C, clicking any cell in the table displays the measurement data points and fitting curves of the corresponding metabolite chromatograms (six types: M+0 to M+5), as in Figures 8B and 9B. For example, the table in Figure 8C shows that metabolite LAC123 of sample 04201 is selected. Unlike Figure 8C, the table in Figure 9C shows that metabolite SUC1234 of sample 05101 is selected.

[0065] Figure 8B shows the results of displaying a chromatogram of LAC123 (measurement sample: 4201), a metabolite with an evaluation index of 90 or more, and it can be seen that all measurement data points M+0 to M+5 are well fitted with a Gaussian function. On the other hand, Figure 9B shows the results of displaying a chromatogram of SUC1234 (measurement sample: 05101), a metabolite with an evaluation index of less than 90, and it can be seen that in the measurement data for M+5, a small peak overlaps the shoulder of the main peak, and the measurement data points cannot be well fitted with a Gaussian function.

[0066] From the above, it was found that even when the quantitative reliability index of isotopes is calculated using the coefficient of determination of fitting, the quality of the fitting can be judged by displaying the reliability index of the isotope distribution ratio on the program screen. The quality of fitting affects the quantification of the isotope amount used to calculate the isotope distribution ratio. Therefore, it was found that the reliability of the isotope distribution ratio can be judged by displaying the reliability index of the isotope distribution ratio on the program screen.

[0067] <4. Metabolic Flux Analysis> Clicking the "4. Metabolic Flux Analysis" button 360 allows the user to start metabolic flux analysis using the input and calculation results obtained up to that point. In this example, the program implemented OpenFLUX, a metabolic flux estimation software available online, to perform metabolic flux analysis. Furthermore, metabolic flux analysis was performed by excluding metabolites with unreliable isotope distribution ratios, which are displayed in color (black inverted) in Figure 6C, from the analysis target.

[0068] On the other hand, as a comparative example, metabolic flux analysis was performed without excluding the metabolites displayed in color (black inverted) in Figure 6C from the analysis. The metabolic flux analysis was performed on intracellular metabolites of CHO cells on day 7 of culture. The metabolic flux value was the average value of multiple metabolic fluxes obtained from the measurement sample group on day 7 of culture, and the width of the error bar was the standard deviation.

[0069] 10 shows the results of metabolic flux analysis in which metabolites with low-reliability isotope distribution ratios were excluded from the analysis target (Example: (a)), and the results of metabolic flux analysis in which all measured isotope distribution ratios were analyzed (Comparative Example: (b)). From FIG. 10 , it can be seen that the width of the error bars in the Example (the standard deviation of the results obtained by performing metabolic flux analysis N times (e.g., N=50) is displayed as an error bar) is smaller than that in the Comparative Example. Therefore, it can be seen that highly reliable metabolic flux analysis can be performed by selecting compound fragments to be analyzed using the reliability index of the isotope distribution ratio.

[0070] Summary of the Embodiment (i) In the metabolic flux analyzer 100 having an isotope distribution ratio evaluation function according to this embodiment, a computer (processor 101) acquires measured values ​​of a mass chromatogram of multiple isotopes with different mass numbers for a compound fragment (sample) to be measured. In this case, the processor 101 may read values ​​of a mass chromatogram that has already been measured from the storage device 102, or the processor 101 may operate a gas chromatograph connected to the metabolic flux analyzer 100 and acquire values ​​of a mass chromatogram immediately after measurement. The processor 101 also quantifies multiple isotopes from a fitting curve obtained by fitting the acquired mass chromatogram with a predetermined function (e.g., a Gaussian function), and calculates the isotope distribution ratio of the compound fragment using the quantification results of the multiple isotopes. The processor 101 then calculates quantitative reliability indices for multiple isotopes, indicating the reliability of the quantitative results for the multiple isotopes, and uses these to calculate a reliability index for the isotope distribution ratio, which is then displayed (output) on the display screen of the display device (output device 104). The calculated isotope distribution ratio value (see FIG. 6C , etc.) may also be displayed on the display screen. In this way, an operator (user) viewing the value of the isotope distribution ratio reliability index can perform metabolic flux analysis by excluding metabolites of the sample corresponding to isotope distribution ratio reliability indices with values ​​smaller than a predetermined threshold. This makes it possible to obtain more reliable metabolic flux analysis results.

[0071] (ii) When outputting the reliability index of the isotope distribution ratio, the processor 101 displays on the display screen the measurement results of mass chromatograms of multiple isotopes (see, for example, FIG. 6A ) and fitting curves obtained by fitting the mass chromatograms with a predetermined function (see, for example, FIG. 6B ), along with the reliability index of the isotope distribution ratio. At this time, the processor 101 displays on the display screen the measured values ​​of the mass chromatograms and fitting curves (see, for example, FIG. 6B ) corresponding to the metabolites of the sample selected in the table of reliability indexes of the isotope distribution ratio (see, for example, FIG. 6C ). When the user selects a metabolite of another sample in the display of, for example, FIG. 6C , the displayed measured values ​​of the mass chromatograms and fitting curves are also changed accordingly. For example, when the display target is changed from metabolite LAC123 of sample 04201 (selected in FIG. 6C ) to metabolite SUC1234 of sample 05101 (selected in FIG. 7C ), the display of the masked tomatogram measurement values ​​and fitting curve also changes from the display in FIG. 6B to the display in FIG. 7B . By doing this, if the reliability index value for the isotope distribution ratio is low, the user can simply select (click) that value to check whether the coefficient of determination in the fitting is good. In this case, if the reliability index value is low despite the coefficient of determination of the fitting being good, the user can know that the low reliability is not due to impurities, but that there may be another cause.

[0072] A display indicating the possibility of a defective mass chromatogram may be displayed on the display screen based on the reliability index of the isotope distribution ratio, or a selection target specific display that enables selection of compound fragments to be analyzed may be performed based on the reliability index of the isotope distribution ratio. The selection target specific display may be, for example, a display form that distinguishes compound fragments whose isotope distribution ratio reliability index values ​​are less than a predetermined threshold from compound fragments whose isotope distribution ratio reliability index values ​​are equal to or greater than the predetermined threshold (see the black inverted display in Figure 6C, etc.).

[0073] (iii) When calculating the reliability index of the isotope distribution ratio, the processor 101 preferably uses quantitative reliability indexes of four or more isotopes. By using four or more isotopes, the error in the isotope distribution ratio can be reduced (for example, within 1%), and as a result, the accuracy of the reliability index of the isotope distribution ratio can be improved.

[0074] (iv) The functions of this embodiment and each example can also be realized by software program code. In this case, a storage medium on which the program code is recorded is provided to a system or device, and the computer (or CPU or MPU) of that system or device reads the program code stored in the storage medium. In this case, the program code read from the storage medium itself realizes the functions of the above-mentioned embodiments, and the program code itself and the storage medium on which it is stored constitute the present disclosure. Examples of storage media for providing such program code include flexible disks, CD-ROMs, DVD-ROMs, hard disks, optical disks, magneto-optical disks, CD-Rs, magnetic tape, non-volatile memory cards, and ROMs.

[0075] Furthermore, an operating system (OS) running on a computer may perform some or all of the actual processing based on instructions in the program code, and the functions of the above-described embodiments may be realized by this processing.Furthermore, after the program code is read from a storage medium and written to memory on the computer, a CPU of the computer may perform some or all of the actual processing based on instructions in the program code, and the functions of the above-described embodiments may be realized by this processing.

[0076] Furthermore, the program code of the software that realizes the functions of the embodiments and each example may be distributed via a network and stored in a storage means such as a hard disk or memory of the system or device, or in a storage medium such as a CD-RW or CD-R, so that when used, the computer (or CPU or MPU) of the system or device reads and executes the program code stored in the storage means or storage medium.

[0077] The processes and techniques described herein are not inherently related to any specific device and can be implemented by a combination of components. Various types of general-purpose devices can also be added. A dedicated device may be constructed to perform the functions of this embodiment and each example. Various functions can also be formed by appropriately combining multiple components disclosed in this embodiment and each example. For example, some components may be omitted from all the components shown in the embodiment and each example, or components from different examples may be appropriately combined.

[0078] Although specific examples are described in this disclosure, they are in all respects for the purpose of explanation (understanding the technology of the present disclosure) and not for the purpose of limitation. Those skilled in the art will recognize that there are many combinations of hardware, software, and firmware suitable for implementing the technology of the present disclosure. For example, the software described can be implemented in a wide variety of programming or scripting languages, such as assembler, C / C++, Perl, Shell, PHP, Java (registered trademark), etc.

[0079] Furthermore, in the above-described embodiment, the control lines and information lines are those that are considered necessary for the explanation, and not all control lines and information lines in the product are necessarily shown. All components may be interconnected.

[0080] In addition, other implementations of the present disclosure will be apparent to those skilled in the art from consideration of the present embodiments and examples. The specification and examples are exemplary only, with the scope and spirit of the present disclosure being indicated by the following claims.

[0081] 100 Metabolic flux analysis device 101 Processor 102 Storage device 103 Input device 104 Output device 105 Communication device 1011 Mass analysis section 1012 Isotope quantification section 1013 Isotope distribution ratio calculation section 1014 Isotope distribution ratio reliability index calculation section 1015 Display processing section 1016 Metabolic flux analysis section 300 Program menu screen 310 "0. Settings" button 320 "1-1. GC-MS measurement" button 330 "1-2. Data Retrieval" button 340 "2. Data Processing" button 350 "3. Results Display" button 360 "4. Metabolic Flux Analysis" button

Claims

1. A program for causing a computer to execute an isotope distribution ratio evaluation method, the isotope distribution ratio evaluation method comprising: measuring a mass chromatogram of a plurality of isotopes having different mass numbers for a compound fragment to be measured by mass spectrometry; quantifying the plurality of isotopes from a fitting curve obtained by fitting the mass chromatogram with a predetermined function; calculating an isotope distribution ratio of the compound fragment using the quantification results of the plurality of isotopes; calculating quantitative reliability indexes of a plurality of isotopes indicating reliability of the quantification results of the plurality of isotopes; calculating a reliability index of the isotope distribution ratio using the quantitative reliability indexes of the plurality of isotopes; and outputting the reliability index of the isotope distribution ratio to an output unit that outputs the calculation results of the program.

2. A program according to claim 1, wherein the isotope distribution ratio evaluation method further includes outputting the isotope distribution ratio to the output section.

3. A program according to claim 1, wherein outputting the reliability index of the isotope distribution ratio includes outputting to the output section the measurement results of the mass chromatograms of the multiple isotopes, together with the reliability index of the isotope distribution ratio, and a fitting curve obtained by fitting the mass chromatogram with a predetermined function.

4. A program according to claim 3, wherein the isotope distribution ratio evaluation method further includes displaying on the output section, in response to a value of the reliability index of the isotope distribution ratio being selected, the measurement value of the mass chromatogram of the corresponding compound fragment and the corresponding fitting curve.

5. The program according to claim 1, wherein calculating the reliability index of the isotope distribution ratio includes calculating the reliability index of the isotope distribution ratio using quantitative reliability indexes of four or more isotopes.

6. The program according to claim 1, wherein the predetermined function is a Gaussian function.

7. The program according to claim 1, wherein the reliability index of the isotope distribution ratio is calculated by the following formula: where R is the reliability index of the isotope distribution ratio, w i is the weight of the quantitative reliability index of isotope i, and d i is the quantitative reliability index for isotope i.

8. The program according to claim 1, wherein the quantitative reliability index is calculated by the following formula: where d i is the quantitative reliability index for isotope i, n i is the number of mass chromatogram data for isotope i, Y Di,j is the jth signal intensity of the mass chromatogram of isotope i, Y Fi,j is Y Di,j The signal intensity of the fitted curve of the mass chromatogram of isotope i at the same elution time, I max,F,i is the maximum signal intensity of the fitting curve of the mass chromatogram of isotope i.

9. The program according to claim 1, wherein the quantitative reliability index is represented by a coefficient of determination when the mass chromatogram is fitted with the predetermined function.

10. A program according to claim 1, wherein the isotope distribution ratio evaluation method further includes outputting to the output section a display indicating a possibility of a defect in the mass chromatogram based on a reliability index of the isotope distribution ratio.

11. A program as claimed in claim 1, wherein the isotope distribution ratio evaluation method further includes outputting to the output section a selection target specific display that enables selection of a compound fragment to be analysed using a reliability index of the isotope distribution ratio.

12. A program as claimed in claim 11, wherein the selection target specific display is a display form that displays compound fragments whose isotope distribution ratio reliability index values ​​are less than a predetermined threshold value in distinction from compound fragments whose isotope distribution ratio reliability index values ​​are equal to or greater than the predetermined threshold value.

13. An isotope distribution ratio evaluation method executed by a processor, comprising: the processor acquiring measurement values ​​of a mass chromatogram of a plurality of isotopes having different mass numbers for a compound fragment to be measured; the processor quantifying the plurality of isotopes from a fitting curve obtained by fitting the mass chromatogram with a predetermined function; the processor calculating an isotope distribution ratio of the compound fragment using the quantification results of the plurality of isotopes; the processor calculating quantitative reliability indexes of a plurality of isotopes indicating the reliability of the quantification results of the plurality of isotopes; the processor calculating a reliability index of the isotope distribution ratio using the quantitative reliability indexes of the plurality of isotopes; and outputting the reliability index of the isotope distribution ratio to an output unit that outputs a calculation result.

14. The method of claim 13, further comprising the processor outputting the isotope distribution ratio to the output section.

15. An isotope distribution ratio evaluation method as described in claim 13, which includes, when outputting the reliability index of the isotope distribution ratio, outputting to the output section, together with the reliability index of the isotope distribution ratio, the measurement results of the mass chromatograms of the multiple isotopes, and a fitting curve obtained by fitting the mass chromatogram with a predetermined function.

16. The method for evaluating isotope distribution ratio according to claim 15, further comprising the processor displaying on the output section, in response to the selection of a value of the reliability index of the isotope distribution ratio, the measurement value of the mass chromatogram of the corresponding compound fragment and the corresponding fitting curve.

17. The isotope distribution ratio evaluation method according to claim 13, wherein calculating the reliability index of the isotope distribution ratio includes the processor calculating the reliability index of the isotope distribution ratio using quantitative reliability indexes of four or more isotopes.

18. The method for evaluating an isotope distribution ratio according to claim 13, wherein the predetermined function is a Gaussian function.

19. The isotope distribution ratio evaluation method according to claim 13, wherein the processor calculates a reliability index of the isotope distribution ratio using the following formula: where R is the reliability index of the isotope distribution ratio, w i is the weight of the quantitative reliability index of isotope i, and d i is the quantitative reliability index for isotope i.

20. The method for evaluating an isotope distribution ratio according to claim 13, wherein the processor calculates the quantitative reliability index using the following formula: where d i is the quantitative reliability index for isotope i, n i is the number of mass chromatogram data for isotope i, Y Di,j is the jth signal intensity of the mass chromatogram of isotope i, Y Fi,j is Y Di,j The signal intensity of the fitting curve of the mass chromatogram of isotope i at the same elution time, I max,F,i is the maximum signal intensity of the fitting curve of the mass chromatogram of isotope i.

21. The method for evaluating an isotope distribution ratio according to claim 13, wherein the processor expresses the quantitative reliability index as a coefficient of determination when the mass chromatogram is fitted with the predetermined function.

22. The method for evaluating an isotope distribution ratio according to claim 13, further comprising the processor outputting to the output section an indication indicating a possibility of a defect in the mass chromatogram based on a reliability index of the isotope distribution ratio.

23. The method for evaluating isotope distribution ratio according to claim 13, further comprising: outputting to the output section a selection target specific indication that enables the processor to select a compound fragment to be analyzed using a reliability index of the isotope distribution ratio.

24. The isotope distribution ratio evaluation method according to claim 23, wherein the selection target specific display is a display form in which compound fragments whose isotope distribution ratio reliability index values ​​are less than a predetermined threshold value are displayed in a manner that distinguishes them from compound fragments whose isotope distribution ratio reliability index values ​​are equal to or greater than the predetermined threshold value.

25. An isotope distribution ratio evaluation device comprising: a storage device that holds an evaluation program for causing a computer to execute an isotope distribution ratio evaluation method; and a processor that reads and executes the evaluation program from the storage device, wherein the processor executes the following processes: acquiring measurement values ​​of a mass chromatogram of a plurality of isotopes having different mass numbers for a compound fragment to be measured; quantifying the plurality of isotopes from a fitting curve obtained by fitting the mass chromatogram with a predetermined function; calculating an isotope distribution ratio of the compound fragment using the quantification results of the plurality of isotopes; calculating quantitative reliability indexes of a plurality of isotopes indicating the reliability of the quantification results of the plurality of isotopes; calculating a reliability index of the isotope distribution ratio using the quantitative reliability indexes of the plurality of isotopes; and outputting the reliability index of the isotope distribution ratio to an output unit that outputs the calculation results.

26. A metabolic flux analysis apparatus having the configuration and functions of the isotope distribution ratio evaluation apparatus described in claim 25, wherein the storage device further holds an analysis program for causing a computer to execute metabolic flux analysis, and the processor reads the analysis program from the storage device and executes the metabolic flux analysis for the compound fragment selected based on a reliability index of the isotope distribution ratio.

Images