Quantitative analysis method and quantitative analysis device

Abstract

The present invention provides a quantitative analysis method for quantifying a target compound contained in a sample derived from a biological organism, which can quantify sugars without generating a standard curve by the user and reducing the matrix effect. The method comprises: a category selection step (S12), receiving a category containing a target sample selected by the user from a plurality of categories predetermined for the sample; a pretreatment step (S11), performing a prescribed pretreatment including derivatization on the target sample; a measurement execution step (S14, S15), performing GC / MS analysis on the target sample that has completed the pretreatment based on the analysis conditions provided from a database storing the analysis conditions in the GC / MS analysis and the standard curve information for performing quantitative analysis based on the standard addition method for each of the plurality of categories; and a quantitative processing step (S13, S16), performing quantitative processing based on the data obtained by the measurement execution step using the standard curve information corresponding to the category selected in the category selection step provided by the database.

Description

Technical Field

[0001] The present invention relates to a method and an apparatus for quantitatively analyzing organic compounds contained in a sample derived from a living being. Background Art

[0002] In the food derived from organisms such as agricultural products, livestock products, and aquatic products, various organic compounds as metabolites such as sugars, fatty acids, and amino acids are included. In recent years, due to the improvement of consumers' health intentions, the development of functional foods has been activated, and with this, the demand for useful compounds contained in various foods has increased. Generally, for the qualitative or quantitative analysis of such compounds contained in a sample, liquid chromatograph (LC) devices or gas chromatograph (GC) devices, or liquid chromatograph mass analyzers (LC-MS) and gas chromatograph mass analyzers (GC-MS) combining these devices with mass analyzers are widely used.

[0003] When the target compound in the sample is quantified using the above-mentioned analysis apparatus, generally, either an external standard method (also called an absolute standard curve method) or an internal standard method is used as the quantification method (see Non-Patent Document 1, etc.).

[0004] In the external standard method, a standard sample containing a target compound prepared to a known concentration is analyzed by an analytical device, the area or height of the chromatographic peak corresponding to the target compound is obtained, and a standard curve showing the relationship between concentration and area (or height) is generated in advance. Then, with reference to the standard curve, the concentration value is calculated based on the area (or height) value of the chromatographic peak corresponding to the target compound obtained by analyzing the unknown sample.

[0005] On the other hand, in the internal standard method, a standard sample containing a target compound and an internal standard substance completely separated from the target compound on the chromatogram at known concentrations is analyzed by an analytical device, the area ratio (or height ratio) of the chromatographic peaks of the two compounds is obtained, and a standard curve showing the relationship between the concentration and the area ratio is generated in advance. Then, an unknown sample to which an internal standard substance of known concentration is added is analyzed with reference to the standard curve, and the concentration value is calculated based on the peak area ratio thus obtained.

[0006] The internal standard method requires the preparation of an internal standard substance that does not overlap with compounds originally contained in the unknown sample on the chromatogram, which is complicated, but has the advantage of being able to correct errors in the injection amount of the sample that may occur in the external standard method.

[0007] Prior art literature

[0008] Patent Literature

[0009] Patent Document 1: Japanese Patent Application Publication No. 2002-168844

[0010] Non-patent literature

[0011] Non-patent document 1: “Basics of GC analysis 2. Analysis results 2.4. Quantitative methods”, [Online], [retrieved on October 25, 2021], Shimadzu Corporation, URL <URL:https: / / www.an.shimadzu.co.jp / gc / support / faq / fundamentals / quantitative_method.htm#gc_2_4>

[0012] Non-patent document 2: Ke Li et al., "Optimized GC-MS Method To Simultaneously Quantify Acetylated Aldose, Ketose and Alditol for Plant Tissues Based on Derivatization in a Methyl Sulfoxide / 1-Methylimidazole System", Journal of Agricultural and Food Chemistry, 2013, No. 61, pp. 4011-4018 Summary of the invention

[0013] Technical problem to be solved by the invention

[0014] In food samples such as agricultural products, livestock products, and aquatic products, in addition to the target organic compounds such as sugars that are the objects of quantification, there are also a large number of various compounds. Therefore, due to the matrix effect caused by such inclusions other than the target compounds, the response when analyzing unknown samples is very different from the response to the standard sample when the standard curve is generated, which often damages the accuracy of the quantitative value. Since the degree of matrix effect varies depending on the combination and content of multiple inclusions in the sample, the degree of change in response varies depending on the type of food sample, etc., and sometimes it is impossible to obtain fully reliable quantification depending on the situation.

[0015] As a method to solve such a problem, there is a standard addition method, which adds a target compound of known concentration to the actual sample (unknown sample) to generate a standard curve, and calculates the concentration of the target compound in the actual sample based on the standard curve. Non-patent document 1 and patent document 1 also record that the standard addition method is effective in reducing the matrix effect.

[0016] However, in the standard addition method, in order to generate a standard curve, it is necessary to add target compounds of multiple concentrations to unknown samples to prepare multiple standard samples, and analyze the multiple standard samples respectively. That is, even if the target compounds are the same, it is necessary to generate a standard curve for each unknown sample. In addition, when quantifying multiple target compounds contained in the sample, if the concentration of the target compound originally contained in the sample varies greatly depending on the compound, it is impossible to calculate the concentration of multiple target compounds by one standard addition method. In this case, it is necessary to change the range of known concentrations added to the sample by each target compound to generate a standard curve based on the standard addition method.

[0017] Therefore, sample preparation and analysis for quantitative analysis of multiple target compounds in unknown samples takes considerable effort and time. In particular, when quantifying sugars and the like using a gas chromatograph, sample pretreatment including derivatization requires time and effort, so if multiple compounds are to be quantified for multiple unknown samples, it takes a huge amount of time and effort.

[0018] The present invention is completed to solve the above-mentioned technical problems, and its main purpose is to provide a quantitative analysis method and device that can reduce the burden of the user's tedious, labor-intensive and time-consuming sample preparation and analysis operations required to generate a standard curve for each unknown sample based on the standard addition method, and obtain quantitative results with sufficient accuracy for practical use.

[0019] Solutions for solving the above technical problems

[0020] One embodiment of the quantitative analysis method of the present invention made to solve the above-mentioned technical problems is a quantitative analysis method for quantifying a target compound contained in a sample derived from a biological organism, comprising:

[0021] a category selection step of receiving a user's request to select a category including a target sample from a plurality of categories predetermined for the sample;

[0022] A pretreatment step, performing a prescribed pretreatment including derivatization on the target sample;

[0023] a measurement execution step of executing gas chromatography mass analysis of the target sample pre-processed by the pre-processing step based on the analysis conditions provided from a database storing analysis conditions in gas chromatography mass analysis and standard curve information for quantitative analysis based on a standard addition method for each of the plurality of categories;

[0024] The quantitative processing step performs quantitative processing based on the data obtained in the measurement execution step using the standard curve information corresponding to the category selected in the category selection step and provided by the database.

[0025] One embodiment of the quantitative analysis device of the present invention, which has been made to solve the above-mentioned technical problems, is a quantitative analysis device for quantitatively analyzing a target compound contained in a sample derived from a biological organism, and comprises:

[0026] A database storing analysis conditions in gas chromatography mass analysis and standard curve information for performing quantification based on a standard addition method for each of a plurality of categories, the plurality of categories being predetermined for the sample;

[0027] A category selection unit receives a user's selection of a category including a target sample from the plurality of categories;

[0028] a measuring unit that performs gas chromatography mass analysis on the target sample subjected to a predetermined preprocessing based on the analysis conditions provided by the database;

[0029] The quantitative processing unit performs quantitative processing based on the data obtained by the measuring unit using the calibration curve information corresponding to the one category selected by the category selecting unit and provided by the database.

[0030] Effects of the Invention

[0031] According to the above scheme of the quantitative analysis method and the quantitative analysis device of the present invention, sufficient quantitative accuracy for practical use can be ensured, and the burden of sample preparation and analysis required for generating a standard curve for each unknown sample based on the standard addition method, which is complicated and time-consuming, can be reduced. Thus, for example, quantitative analysis of multiple sugars in a large number of unknown samples can be performed efficiently and labor-savingly. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] Figure 1 This is a schematic diagram of the structure of a sugar quantitative analysis system according to one embodiment of the present invention.

[0033] Figure 2 This is a flowchart showing the flow of quantitative analysis of sugars and the flow of processing performed using the sugar quantitative analysis system of this embodiment.

[0034] Figure 3 This is an explanatory diagram of the outline of the quantitative analysis method performed using the sugar quantitative analysis system according to the present embodiment.

[0035] Figure 4 This is a diagram showing an example of quantitative results of sugars when a calibration curve based on a food sample of the same type as the unknown sample is used.

[0036] Figure 5 This is a diagram showing an example of quantitative results of sugars when a calibration curve based on a food sample of a different type from that of an unknown sample is used. DETAILED DESCRIPTION

[0037] [Sample and Quantitative Compound]

[0038] In the above-mentioned aspects of the quantitative analysis method and the quantitative analysis device of the present invention, the "organism" of the "sample derived from organism" may include plants, animals (including humans), and microorganisms.

[0039] In addition, "biologically derived samples" specifically refer to, for example, biologically derived food samples, such as vegetables (leafy and stem vegetables, root vegetables, fruit vegetables, melon and fruit vegetables, spice vegetables, etc.) or agricultural products such as fruits, fungi, and grains, livestock products mainly edible meat, and aquatic products mainly fish. In addition, agricultural products, livestock products, and aquatic products are usually unprocessed or low-processed food samples, that is, raw materials themselves or close to them, but processed products such as fermentation and drying can also be included here.

[0040] Furthermore, the "biologically derived sample" may include, in addition to the above-mentioned food samples, samples derived from living organisms, such as blood, urine, sweat, body fluids collected from humans, or samples extracted therefrom, such as plasma.

[0041] In the above scheme of the quantitative analysis method and the quantitative analysis device of the present invention, the "multiple categories" are different according to the types of the above-mentioned "biologically derived samples". For example, in the case where the "biologically derived samples" are the above-mentioned food samples, agricultural products, livestock products, and aquatic products can be set as one category respectively. In addition, agricultural products can also be divided into categories such as vegetables and fruits, fungi, and cereals, and can be further divided into finer categories such as leafy vegetables, root vegetables, fruit vegetables, melons and vegetables, and spice vegetables. In addition, multiple such subdivided categories can also be concentrated into one category. In addition, for aquatic products, they can also be divided into categories such as fish, shellfish, and crustaceans.

[0042] Such categories can basically be set according to taxonomic classifications such as animal taxonomy and plant taxonomy, but this is not necessary. For example, in the case of vegetables, generally speaking, classifications can be made not only based on the characteristics of the plant but also based on the viewpoint of cultivation. Of course, classifications based not only on such theoretical or academic definitions but also on experimental verification can be made.

[0043] In addition, it is desirable that the correspondence between the type of each sample (e.g., a certain type of vegetable) and the category is easy to understand. This is because when the user selects which category the target sample is included in, it is inappropriate to waste time being confused about the selection. Therefore, when the user uses common sense to judge that a certain sample is included in a certain category, it is not necessarily guaranteed that the standard curve information associated with the category is the most quantitative standard curve information for the sample (that is, it is possible that the standard curve information associated with other categories is more quantitative).

[0044] In addition, in the above scheme of the quantitative analysis method and the quantitative analysis device of the present invention, the "target compound" as the quantitative object is an organic compound that can be contained in a sample derived from an organism, typically a metabolite (usually a secondary metabolite) such as a sugar, a fatty acid, and an amino acid. However, in general, for fatty acids or amino acids, a quantitative method using LC / MS analysis is effective, while for sugars, it is difficult to fully quantify by such a method. Therefore, it can be said that the present invention is particularly effective for the quantification of a variety of sugars contained in a sample derived from an organism.

[0045] [Sample measurement method]

[0046] LC-MS is often used in the analysis of organic compounds in food samples. There are many isomers with similar structures in sugars, and it is difficult to separate them by mass-to-charge ratio (m / z). Therefore, separation in chromatography is very important. If you want to use LC or LC-MS to obtain higher separation performance in chromatography, a longer analysis time of more than 1 hour is usually required. In contrast, in GC-MS, although it is impossible to separate isomers of sugars by m / z like LC-MS, the separation performance of chromatography is high and separation can be performed with a smaller half width than LC. Therefore, multiple components can be analyzed at the same time in a relatively short analysis time. Therefore, in the above-mentioned scheme of the present invention, GC / MS analysis is used as a measurement method for the sample.

[0047] In addition, as is known, gas chromatography-tandem mass spectrometry (GC-MS / MS) can perform two-stage mass separation, and is therefore good at separating sugars from other components contained in food samples, which is beneficial for reducing the detection limit and expanding the dynamic range. Therefore, it is more preferred to use GC / MS / MS as a measurement method for samples.

[0048] [Quantitative Analysis Method and Apparatus as One Embodiment of the Present Invention]

[0049] An embodiment of the quantitative analysis method and the quantitative analysis device of the present invention will be described in detail below.

[0050] This embodiment mainly performs quantitative analysis of various sugars in food samples, mainly agricultural products, livestock products, and marine products.

[0051] <Overview of quantitative analysis method>

[0052] Figure 3 It is a schematic diagram for explaining the quantitative analysis method of this embodiment.

[0053] Usually, when using analytical devices such as GC, LC, GC-MS, LC-MS for quantitative analysis, before the quantification of unknown samples, it is necessary to use standard samples to generate a calibration curve. However, as mentioned above, in addition to the target carbohydrates, the food sample also contains various components, and the matrix effect brought by such inclusions becomes a problem. In order to alleviate the matrix effect, it is expected to use the standard addition method as a quantitative method, but for each unknown sample, a standard sample is prepared to generate a calibration curve, which is a heavy burden for the user. So, in this quantitative analysis method, a standard curve based on the standard addition method for quantitative analysis is generated in advance by the manufacturer and databased to provide it to the user.

[0054] However, the types of food that users want to perform quantitative analysis on are huge, and it is not realistic for the manufacturer to generate a standard curve based on the standard addition method for all the food types due to the huge workload. Of course, if the types of food that can be quantified are limited to a considerable extent, a standard curve can be prepared for each type of food, but such a device lacks versatility. Therefore, in the quantitative analysis method of this embodiment, multiple ( Figure 3 In the example of 5) food categories, the manufacturer prepares a standard curve for each of the food categories and each of the target compounds. Before quantification, the user specifies the food category containing the target sample, and the standard curve associated with the food category is used to perform quantitative analysis of the target sample.

[0055] like Figure 3 As shown in FIG. 1 , in this quantitative analysis method, five food categories are identified: vegetables, root vegetables, grains, edible meat, and fish. The vegetables mentioned here include leafy and stem vegetables other than root vegetables, fruit vegetables, melon and fruit vegetables, and spice vegetables. The operator who is responsible for generating the standard curve (usually the person in charge of the device manufacturer or the software development manufacturer installed on the device, etc.) prepares representative food samples for each food category ( Figure 3 Vegetables A, root vegetables B, grains C, meat D, fish E) in the sample were used to generate a standard curve using the following process.

[0056] When GC / MS analysis is performed on sugars, since sugars cannot be sufficiently separated as they are, a pretreatment including derivatization is performed. The specific flow of this pretreatment will be described later.

[0057] The operator divides a food sample (e.g., vegetable A) for generating a standard curve into a plurality of equal parts. Then, a plurality of compounds (sugars) a, b, ..., which are quantitative objects, are added to the divided food samples at known concentrations, and the concentrations of the added target compounds a, b, ... are changed in multiple stages, thereby preparing a plurality of standard samples. The plurality of standard samples prepared in this way and the food sample to which the compounds a, b, ... are not added are pretreated, and the pretreated samples obtained are measured by GC-MS under predetermined analysis conditions (GC analysis conditions and MS analysis conditions) to obtain data.

[0058] In addition, during pretreatment, a specified internal standard substance is also added to the sample. This is due to the use of the area ratio (or height ratio) of the chromatographic peaks of compounds a, b, ... and the internal standard substance rather than the area (or height) of the chromatographic peaks of compounds a, b, ... to generate a standard curve. Thus, it is possible to generate a standard curve having a function of correcting the difference in the recovery rate of the compound during pretreatment. That is, although the standard curve generated here is basically a standard curve based on the standard addition method, it can also be regarded as a standard curve obtained by combining the internal standard method with the standard addition method. In addition, the behavior of using such an internal standard method and the standard addition method itself is also known in patent document 1, etc.

[0059] The GC analysis conditions during the analysis include information on the retention time corresponding to each compound a, b, ... and the internal standard substance, and the MS analysis conditions include information on the m / z value of the monitoring ions corresponding to each compound a, b, ... and the internal standard substance. In the GC / MS analysis, corresponding to each compound a, b, ... and the internal standard substance, the extracted ion chromatogram data at the m / z value corresponding to the compound and the internal standard substance within a specified time range near the retention time of the compound and the internal standard substance is obtained. Thus, the ratio of the chromatographic peak area of ​​each compound a, b, ... to the chromatographic peak area of ​​the internal standard substance can be obtained based on the extracted ion chromatogram. Then, a standard curve is generated based on the relationship between the concentration of each compound a, b, ... in a plurality of standard samples and the peak area ratio, and the slope of the standard curve, specifically, the information of the slope coefficient of the linear or quadratic formula is obtained as the standard curve information.

[0060] Therefore, if Figure 3As shown, for each food sample such as vegetable A used to generate a standard curve, standard curve information for each compound a, b, ... is obtained. Although there are differences in the recovery rate of each compound extracted during pretreatment depending on the type of sample, by using the peak area ratio, that is, by using the internal standard method, a standard curve corrected for the difference in recovery rate can be obtained. For example, the device manufacturer makes the standard curve information obtained in this way into a database as standard curve information corresponding to each food category and provides it to the user.

[0061] When the user wants to quantify compounds a, b, ... contained in a target sample (unknown sample), he / she selects the food category containing the target sample. Figure 3 As shown in the figure, if the target sample is a tomato, select the vegetable category, and if the target sample is a tuna or a sardine, select the fish category. Then, the user performs a predetermined pretreatment on the target sample, measures the target sample that has completed the pretreatment by GC-MS under the predetermined analysis conditions (GC analysis conditions and MS analysis conditions), and obtains data.

[0062] The pretreatment is specified by the device manufacturer and is basically the same as the pretreatment performed when the standard curve is generated. Therefore, during the pretreatment, an internal standard substance of a specified concentration is added to the target sample. In addition, the analysis conditions in GC-MS are also specified by the device manufacturer and are basically the same as the analysis conditions for GC / MS analysis performed when the standard curve is generated.

[0063] By GC / MS analysis of the target sample, corresponding to each compound a, b, ... and the internal standard substance, extracted ion chromatogram data at the m / z value corresponding to the compound and the internal standard substance within a specified time range near the retention time of the compound and the internal standard substance is obtained. Based on the extracted ion chromatogram, the ratio of the chromatographic peak area of ​​each compound a, b, ... to the chromatographic peak area of ​​the internal standard substance is calculated. The value of the peak area ratio is compared with the standard curve information of each compound a, b, ... associated with the initially selected food category to calculate the respective concentrations.

[0064] As described above, in the quantitative analysis method of the present embodiment, it is not necessary for the user to generate a standard curve based on a complicated and time-consuming standard addition method, but it is possible to quantify various sugars contained in the food sample using a standard curve generated in advance by the device manufacturer. The standard curve used at this time is a curve generated by the standard addition method, so the matrix effect caused by various inclusions other than sugars contained in the food can be reduced. In addition, since the internal standard method is also used in the generation of the standard curve, the difference in the recovery rate of the compound in the pretreatment can be corrected.

[0065] Furthermore, in the quantitative analysis method of the present embodiment, since a large number of food samples are classified and the standard curve information is registered in the database for use in each food category, it is possible to provide a quantitative analysis that is not limited to a specific type of food but is highly versatile for a variety of foods, while reducing the labor and time spent on generating a standard curve.

[0066] The above-mentioned quantitative analysis method can be modified as follows.

[0067] Some sugars, such as glucose, fructose, sucrose and other major sugars, may be contained in biologically derived foods at relatively high concentrations. Therefore, when generating a standard curve using such compounds as the object, the concentration of the compound in the standard sample used is high, and the accuracy of the standard curve may be reduced, especially in the low concentration range. Therefore, for such specific compounds, using a standard containing, for example, deuterium ( 2 H) and carbon 13 ( 13 C) is used to determine a calibration curve using the stable isotopes of compounds of elements with a smaller abundance ratio, rather than the isotope with the highest abundance ratio, and the slope coefficient of the calibration curve is registered in the database as calibration curve information.

[0068] When the compound in the target sample is quantified, the above-mentioned stable isotope with a smaller presence ratio of the compound is selectively detected, and the peak area ratio of the stable isotope is compared with the standard curve information to calculate the concentration. Thus, as described above, even for compounds with a high concentration contained in food, quantification under a wide dynamic range can be performed, that is, regardless of the concentration of the compound contained in the food, quantification under a wide dynamic range can be performed.

[0069] <Specific example of pretreatment method>

[0070] Here, a specific example of pretreatment when performing GC / MS analysis on a food sample will be described. Of course, the pretreatment that can be used in the quantitative analysis method of this embodiment is not limited to this.

[0071] This pretreatment can be roughly divided into two steps: a component extraction step and a derivatization step.

[0072] (1) Component extraction process

[0073] First, a predetermined amount of freeze-dried food sample is measured, and a predetermined amount of solvent (e.g., a mixed solvent of water: methanol: chloroform (1:2.5:1)) and an internal standard substance are added. As an example, ribitol or a stable isotope of a sugar that is not used in the generation of the standard curve can be used as an internal standard substance. Then, the food sample to which the solvent is added is shaken at a temperature of 37°C for 20 minutes, thereby dissolving the compounds contained in the food sample in the solvent. Next, the solution is centrifuged at 16,000g to collect the supernatant. Ultrapure water is added to the collected supernatant, and after stirring and centrifugation again, a predetermined amount of supernatant is collected. The collected supernatant is freeze-dried to prepare an extraction sample, thereby completing the component extraction process.

[0074] (2) Derivatization process

[0075] Dimethyl sulfoxide (DMSO) is added as a solvent to the above-mentioned extract sample obtained by freeze drying, and the sample is stirred thoroughly to dissolve the components in the extract sample in the solvent. Here, by using DMSO as an aprotic solvent as a solvent, epimerization or isomerization of the stereo configuration reversal of the asymmetric carbon can be prevented. Then, 1-methylimidazole and acetic anhydride are added to the solution as derivative reagents, stirred, and allowed to stand at room temperature for 10 minutes to promote the derivatization (acetylation) reaction. Next, ultrapure water is added to the solution to stop the derivatization reaction, and the components obtained by derivatization are extracted using an organic solvent such as dichloromethane to terminate the derivatization process.

[0076] As also reported in Non-Patent Document 2, by using DMSO as a solvent for derivatization, multiple peaks corresponding to multiple stereoisomers of the same compound that appear in the chromatogram can be combined into one peak. In addition, by combining acetic anhydride with 1-methylimidazole as a derivatization reagent, the efficiency of the derivatization reaction can be improved.

[0077] <Configuration and Operation of an Example of Quantitative Analysis System>

[0078] Figure 1 This is a schematic block diagram of an example of a sugar quantitative analysis system using GC-MS that can implement the above-mentioned quantitative analysis method. Figure 2 This is a flowchart showing the flow of quantitative analysis and the flow of processing using the sugar quantitative analysis system.

[0079] like Figure 1As shown, the sugar quantitative analysis system comprises: a pre-processing device 2; a measuring unit 1, comprising a gas chromatograph (GC) unit 11 and a mass spectrometer (MS) unit 12; an analysis control unit 3, respectively controlling the operations of the GC unit 11 and the MS unit 12; a data processing unit 4, processing the data collected by the measuring unit 1; a control unit 5, responsible for the control of the entire system; an input unit 6 and a display unit 7, both connected to the control unit 5. The data processing unit 4 comprises a data storage unit 41, a chromatogram generating unit 42, a quantitative analysis unit 43 and a sugar quantitative database 44 as functional modules. The MS unit 12 may also be a mass spectrometer that performs a conventional mass analysis without the dissociation operation of ions, or a mass spectrometer that can perform MS / MS analysis or MS n Any of the tandem mass spectrometers used for analysis.

[0080] The carbohydrate quantitative database 44 stores GC analysis conditions, MS analysis conditions, and standard curve information classified by food category. In the GC analysis conditions, for example, in addition to the flow rate program of the carrier gas and the temperature program of the column oven as general GC analysis conditions, the retention time of each carbohydrate (compound) as the quantitative object is also included. In the MS analysis conditions, for example, in addition to the measurement mode (positive and negative polarity, voltage applied to each part, etc.), the m / z value of the monitoring ion of each carbohydrate as the quantitative object, the confirmation ion ratio, etc. are also included. As described above, these analysis conditions are usually set to be the same as the analysis conditions when the standard curve is generated. The standard curve information classified by food category is as described above, for example, the standard curve information of each compound a, b, ... corresponding to each food category generated by the device manufacturer.

[0081] Generally, the analysis control unit 3, the data processing unit 4, and the control unit 5 can realize at least a part of their functions by using a personal computer or a higher-performance computer called a workstation that includes a CPU, a memory, etc. as hardware, and executing a dedicated processing and control software (computer program) pre-installed in the computer on the computer. The sugar quantitative database 44 may be included in the processing and control software, or may be software for sugar quantitative analysis that is separate from the processing and control software.

[0082] The computer program can be provided to the user by being stored in a non-temporary recording medium readable by a computer, such as a CD-ROM, a DVD-ROM, a memory card, a USB memory (protection lock), etc. In addition, the program can also be provided to the user in the form of data transmission via a communication line such as the Internet. Furthermore, the program can also be pre-installed in a computer that is part of the system (strictly speaking, a storage device that is part of the computer) at the time when the user purchases the system.

[0083] The flow and operation of quantitatively analyzing sugars in a target sample (food sample) using the sugar quantitative analysis system will be described.

[0084] The user sets the target sample in the pretreatment device 2, and the pretreatment device 2 performs the pretreatment according to the process as illustrated (step S11). Here, it is assumed that the pretreatment device 2 automatically performs the pretreatment based on the process as described above, but the user can also perform the pretreatment by manual operation. In this pretreatment, an internal standard substance of a predetermined concentration is added to the target sample, and the sugar (compound) in the target sample is derivatized.

[0085] Before the measurement unit 1 performs GC / MS analysis on the target sample that has undergone pretreatment, the user performs a predetermined operation through the input unit 6 to select a food category that includes the target sample (step S12). That is, the control unit 5 generates a screen that lists a plurality of food categories registered in the carbohydrate quantitative database 44 and displays it on the display unit 7. The user sees the screen and selects a food category through the input unit 6. Figure 1 (and Figure 3 ) shows five food categories, namely, edible meat, fish, vegetables, root vegetables, and grains, as food categories, and the user selects one from them. The control unit 5 receives the selection of the food category by the user.

[0086] After receiving the selection of the food category, in the data processing unit 4, the quantitative analysis unit 43 obtains the standard curve information of each compound associated with the selected food category from the carbohydrate quantitative database 44 (step S13). In addition, the analysis control unit 3 obtains the GC analysis conditions and the MS analysis conditions from the carbohydrate quantitative database 44 (step S14).

[0087] For example, after receiving the instruction issued by the user, the analysis control unit 3 controls the GC unit 11 and the MS unit 12 according to the acquired GC analysis conditions and MS analysis conditions, respectively, and performs GC / MS analysis on the target sample that has completed the pretreatment (step S15). As the analysis proceeds, the data obtained by the MS unit 12 is input to the data processing unit 4 and stored in the data storage unit 41.

[0088] Then, the chromatogram generation unit 42 reads data from the data storage unit 41, generates an extracted ion chromatogram corresponding to each compound, and uses the retention time and confirmation ion ratio of each compound to identify each compound. That is, confirm whether the detected compound is the target compound. Next, when the target compound is detected, the quantitative analysis unit 43 calculates the area ratio of the peak observed in the extracted ion chromatogram relative to the target compound and the internal standard substance, compares the value of the area ratio with the standard curve of the compound, and calculates the quantitative value (concentration value) (step S16). The control unit 5 displays the quantitative value of each target compound as a quantitative analysis result on the display unit 7.

[0089] As described above, in this sugar quantitative analysis system, the concentration values ​​of various sugars contained in the target sample can be obtained without the user having to perform any operation of generating a calibration curve.

[0090] In addition, in the above description, in the carbohydrate quantitative database 44, the standard curve information generated by actually analyzing a food sample included in the food category is stored, but the standard curve information can be adjusted appropriately. That is, it is also possible to use the standard curve information generated by actually analyzing a plurality of food samples included in the same food category, for example, instead of using the standard curve information for a certain food sample and performing statistical processing such as taking the average value to obtain the final standard curve information. Thus, for various food samples included in a food category, the overall or average quantitative accuracy can be improved. Of course, the user does not need to know by which method or which algorithm the standard curve information is generated.

[0091] [Experimental results of quantitative analysis]

[0092] In the quantitative analysis method of this embodiment, in most cases, the food used for quantitative analysis is different from the food type when the standard curve information stored in the sugar quantitative database 44 is generated. Therefore, in order to confirm that the standard curve information can be used even if the food type is different if it is included in the same food category, the following experiment was performed.

[0093] First, for the vegetable food category, strawberry, which is one of the fruits and vegetables, was used, and for the grain food category, wheat was used, and standard curve information was generated for multiple sugars according to the above process. Here, the sugars used for quantitative analysis were meso-erythritol, rhamnose, fucose, nucleose, mannitol, trehalose, maltose, and isomaltose.

[0094] Tomatoes included in the vegetable food category were prepared as target samples, and 50 ng of the above-mentioned sugars were added to the samples, followed by pretreatment. The samples that had undergone the pretreatment were subjected to GC / MS analysis, and based on the data obtained, the quantitative values ​​of each sugar were calculated using the standard curve information of the above-mentioned vegetable food category and grain food category. The concentration of the sugars originally contained in the target sample was measured separately, and the quantitative value corresponding to the amount of 50 ng added was obtained by subtracting the concentration.

[0095] Figure 4 This is a quantitative result using the calibration curve information in the vegetable food category (the food sample when the calibration curve was generated was strawberry). Figure 5 This is the quantitative result using the standard curve information in the grain-based food category (the food sample when the standard curve was generated was wheat).

[0096] like Figure 4 As shown in Figure 1, the accuracy of the quantitative values ​​obtained using the standard curve information in the same food category is within 100±5%. Figure 5 As shown in the figure, the accuracy of the quantitative value obtained using the standard curve information in different food categories deviates by more than 15% in mannitol, trehalose, maltose and isomaltose. It is speculated that the reason for this deviation is that the matrix is ​​affected by the different types of food. In other words, by appropriately determining a plurality of food categories in a manner that includes foods with a similar degree of influence of the matrix, it is possible to ensure sufficient quantitative accuracy for actual use even if the standard curve information generated for a food sample of a different type from the target sample and associated with each food category is used to quantify the target sample.

[0097] The above-described embodiments and modifications are merely examples of the present invention, and appropriate corrections, changes, and additions within the scope of the gist of the present invention are also intended to be included in the scope of the claims of the present invention.

[0098] For example, in the above embodiment, the sample is food, but as mentioned above, a biological sample such as blood may be used as the object. In this case, it is reasonable to change the category appropriately accordingly. In addition, the organic compound to be quantified may be not only sugars but also fatty acids, amino acids, etc. When these compounds are analyzed by GC, it is well known to perform derivatization, and a pretreatment method corresponding to the compound can be selected.

[0099] [Various options]

[0100] Those skilled in the art may understand that the above exemplary embodiments are specific examples of the following schemes.

[0101] (Item 1) One embodiment of the quantitative analysis method of the present invention is a quantitative analysis method for quantifying a target compound contained in a sample derived from a living organism, comprising:

[0102] a category selection step of receiving a user's request to select a category including a target sample from a plurality of categories predetermined for the sample;

[0103] A pretreatment step, performing a prescribed pretreatment including derivatization on the target sample;

[0104] a measurement execution step of executing gas chromatography mass analysis of the target sample pre-processed by the pre-processing step based on the analysis conditions provided from a database storing analysis conditions in gas chromatography mass analysis and standard curve information for quantitative analysis based on a standard addition method for each of the plurality of categories;

[0105] The quantitative processing step performs quantitative processing based on the data obtained in the measurement execution step using the standard curve information corresponding to the category selected in the category selection step and provided by the database.

[0106] (Item 8) In addition, one embodiment of the quantitative analysis device of the present invention is a quantitative analysis device for quantitatively analyzing a target compound contained in a sample derived from a living organism, comprising:

[0107] A database storing analysis conditions in gas chromatography mass analysis and standard curve information for performing quantification based on a standard addition method for each of a plurality of categories, the plurality of categories being predetermined for the sample;

[0108] A category selection unit receives a user's selection of a category including a target sample from the plurality of categories;

[0109] a measuring unit that performs gas chromatography mass analysis on the target sample subjected to a predetermined preprocessing based on the analysis conditions provided by the database;

[0110] The quantitative processing unit performs quantitative processing based on the data obtained by the measuring unit using the calibration curve information corresponding to the one category selected by the category selecting unit and provided by the database.

[0111] According to the quantitative analysis method described in item 1 and the quantitative analysis device described in item 8, sufficient quantitative accuracy for practical use can be ensured, and the burden of sample preparation and analysis work required for generating a standard curve based on the standard addition method for each unknown sample and each target compound, which is complicated and time-consuming, can be reduced. Thus, for example, quantitative analysis of multiple sugars in a large number of unknown samples can be performed efficiently and labor-savingly.

[0112] (Item 2) In the quantitative analysis method described in Item 1, the sample may be a food derived from a living organism.

[0113] The quantitative analysis method according to item 2 is effective for detecting organic compounds useful to the human body contained in various foods, for example.

[0114] (Item 3) In the quantitative analysis method described in Item 2, the target compound may be a sugar.

[0115] According to the quantitative analysis method described in Item 3, a plurality of sugars contained in a food can be quantitatively determined at once.

[0116] (Item 4) In the quantitative analysis method described in Item 2 or 3, the plurality of categories may be groups such as agricultural products, livestock products, and marine products, or groups in which at least one of the categories is further subdivided.

[0117] According to the quantitative analysis method described in Item 4, by placing foods having similar matrix effects into the same category, the quantitative accuracy can be improved.

[0118] (Item 5) In the quantitative analysis method described in any one of Items 1 to 4, the standard curve information can be standard curve information based on a standard addition method and an internal standard method, generated by using a ratio of an area or a height of a chromatographic peak of a predetermined internal standard substance added to a sample during pretreatment and a target compound added to the sample,

[0119] In the pretreatment step, the internal standard substance is added to the target sample, and in the quantitative treatment step, the quantitative value is obtained based on the area ratio or height ratio of the chromatographic peaks of the internal standard substance and the target compound.

[0120] According to the quantitative analysis method described in item 5, it is possible to correct quantitative errors caused by differences in the recovery rate of compounds during sample pretreatment and differences in the injection amount when injecting the sample into the gas chromatograph, etc. Thus, even when derivatization is performed with large differences in the recovery rate, for example, quantitative accuracy can be improved.

[0121] (Item 6) In the quantitative analysis method described in any one of Items 1 to 5, the standard curve information for a specific target compound can be generated by a standard addition method using a stable isotope of the target compound containing deuterium or carbon 13 with a relatively low abundance ratio.

[0122] According to the quantitative analysis method described in Item 6, for compounds contained in a sample at a relatively high concentration, it is possible to avoid the concentration range of the calibration curve being too wide, thereby improving the accuracy of the calibration curve.

[0123] (Item 7) In the quantitative analysis method described in any one of Items 1 to 6, the target compound can be a sugar, and the pretreatment step includes an extraction step of extracting the compound contained in the sample into a solvent to obtain an extracted sample, and a derivatization step of derivatizing the extracted sample. In the derivatization step, an operation of adding a non-protonic solvent such as dimethyl sulfoxide and stirring, and an operation of adding at least acetic anhydride and stirring are performed.

[0124] According to the quantitative analysis method described in Item 7, the generation of isomers that are likely to occur when sugars are pretreated can be prevented, and the quantitative performance can be improved by aggregating the chromatographic peaks corresponding to the target compound.

[0125] Description of Reference Numerals

[0126] 1 Measurement Department

[0127] 11 GC Department

[0128] 12 MS Department

[0129] 2 Pre-treatment device

[0130] 3 Analysis and Control Department

[0131] 4 Data Processing Department

[0132] 41 Data storage unit

[0133] 42 Chromatogram generation unit

[0134] 43 Quantitative Analysis Department

[0135] 44 Sugar Quantification Database

[0136] 5. Control Unit

[0137] 6 Input section

[0138] 7 Display unit.

Claims

1. A quantitative analysis method for quantifying a target compound contained in a sample derived from a biological organism, characterized in that: have: a category selection step of receiving a user's request to select a category including a target sample from a plurality of categories predetermined for the sample; A pretreatment step, performing a prescribed pretreatment including derivatization on the target sample; a measurement execution step of executing gas chromatography mass analysis of the target sample pre-processed by the pre-processing step based on the analysis conditions provided from a database storing analysis conditions in gas chromatography mass analysis and standard curve information for quantitative analysis based on a standard addition method for each of the plurality of categories; The quantitative processing step performs quantitative processing based on the data obtained in the measurement execution step using the standard curve information corresponding to the category selected in the category selection step and provided by the database.

2. The quantitative analysis method according to claim 1, characterized in that The sample is a food derived from a living organism.

3. The quantitative analysis method according to claim 2, characterized in that: The target compounds are sugars.

4. The quantitative analysis method according to claim 2, characterized in that: The multiple categories are groups such as agricultural products, livestock products, and aquatic products, or groups in which at least one of them is further subdivided.

5. The quantitative analysis method according to claim 1, characterized in that The calibration curve information is generated based on the standard addition method and the internal standard method using the ratio of the area or height of the chromatographic peak of a predetermined internal standard substance added to the sample during pretreatment and the target compound added to the sample. In the pretreatment step, the internal standard substance is added to the target sample, and in the quantitative treatment step, the quantitative value is obtained based on the area ratio or height ratio of the chromatographic peaks of the internal standard substance and the target compound.

6. The quantitative analysis method according to claim 1, characterized in that: The calibration curve information for a specific target compound is generated by the standard addition method using a stable isotope of the target compound containing deuterium or carbon 13 at a relatively low abundance ratio.

7. The quantitative analysis method according to claim 1, characterized in that: The target compound is a sugar, and the pretreatment step includes an extraction step of extracting the compound contained in the sample into a solvent to obtain an extracted sample, a derivatization step of derivatizing the extracted sample, and in the derivatization step, an operation of adding an aprotic solvent and stirring, and an operation of adding at least acetic anhydride and stirring are implemented.

8. A quantitative analysis device for quantitatively analyzing a target compound contained in a sample derived from a biological organism, characterized in that: have: A database storing analysis conditions in gas chromatography mass analysis and standard curve information for performing quantification based on a standard addition method for each of a plurality of categories, the plurality of categories being predetermined for the sample; A category selection unit receives a user's selection of a category including a target sample from the plurality of categories; a measuring unit that performs gas chromatography mass analysis on the target sample subjected to a predetermined preprocessing based on the analysis conditions provided by the database; The quantitative processing unit performs quantitative processing based on the data obtained by the measuring unit using the calibration curve information corresponding to the one category selected by the category selecting unit and provided by the database.

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