Quantitative analysis method and quantitative analysis apparatus

Abstract

To quantitate sugars in which a matrix effect is reduced without any need for a user to create a calibration curve.SOLUTION: A quantification method of an object compound contained in a biological sample has: a category selection step S12 for receiving selection of one category in which an object sample is contained from among multiple categories predetermined for samples; a pretreatment step S11 for executing predetermined pretreatment including derivatization to the object sample; measurement execution steps S14 and S15 for executing a GC / MS analysis on the basis of an analysis condition provided from a database for storing an analysis condition in the GC / MS analysis and calibration curve information for quantification by the standard addition method for each of multiple categories; and quantification treatment steps S13, S16 for executing quantification treatment based on data obtained by the measurement steps by utilizing the calibration curve information that is provided by the database and corresponds to the category selected in the category selection step.SELECTED DRAWING: Figure 2

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 biological source.

Background Art

[0002] Foods derived from organisms such as agricultural products, livestock products, and fishery products contain organic compounds that are various metabolites such as saccharides, fatty acids, and amino acids. In recent years, with the increasing health consciousness of consumers, the development of functional foods has been active, and along with this, the desire to search for useful compounds contained in various foods has been increasing. Generally, for the qualitative or quantitative determination of such compounds contained in a sample, an analytical apparatus such as a liquid chromatograph (LC) apparatus, a gas chromatograph (GC) apparatus, or a liquid chromatograph-mass spectrometer (LC-MS) or a gas chromatograph-mass spectrometer (GC-MS) that combines these apparatuses with a mass spectrometer is widely used.

[0003] When quantifying a target compound in a sample using the above analytical apparatus, generally, either an external standard method (also referred to as an absolute calibration curve method) or an internal standard method is used as a quantification method (see Non-Patent Document 1, etc.).

[0004] In the external standard method, a standard sample containing a target compound prepared at a known concentration is analyzed with an analytical apparatus to obtain the area or height of a chromatographic peak corresponding to the target compound, and a calibration curve showing the relationship between the concentration and the area (or height) is created in advance. Then, referring to the calibration curve, the concentration value is calculated from the area (or height) value of the chromatogram peak corresponding to the target compound obtained by analyzing an unknown sample.

[0005] On the other hand, in the internal standard method, a standard sample containing a target compound and an internal standard substance that is completely separated from the target compound on the chromatogram at known concentrations is analyzed using an analytical instrument. The area ratio (or height ratio) of the chromatographic peaks of both compounds is obtained, and a calibration curve showing the relationship between the concentration and the area ratio is created in advance. After that, by referring to the calibration curve, the concentration value is calculated from the peak area ratio obtained by analyzing an unknown sample to which an internal standard substance of known concentration has been added.

[0006] Although there is a complication in the internal standard method that it is necessary to prepare an internal standard substance that does not overlap with the compound originally contained in the unknown sample on the chromatogram, it has the advantage of being able to correct the error in the injection volume of the sample that can occur in the external standard method.

Prior Art Documents

Patent Documents

[0007]

Patent Document 1

Non-Patent Documents

[0008]

Non-Patent Document 1

Non-Patent Document 2

Summary of the Invention

Problems to be Solved by the Invention

[0009] Food samples such as agricultural products, livestock products, and fishery products contain a large number of various compounds in addition to the target organic compounds such as saccharides to be quantified. Therefore, due to the matrix effect caused by such contaminants other than the target compound, the response when analyzing an unknown sample is often significantly different from the response to the standard sample when preparing the calibration curve, impairing the accuracy of the quantitative value. Since the degree of the matrix effect varies depending on the combination and content of multiple contaminants in the sample, the degree of change in the response varies depending on the type of food sample, etc., and in some cases, reliable quantification may not be obtained.

[0010] As one method to solve such problems, there is a standard addition method in which a target compound with a known concentration is added to the actual sample (unknown sample) to prepare a calibration curve, and the concentration of the target compound in the actual sample is determined from the calibration curve. The effectiveness of the standard addition method in reducing the matrix effect is also described in Non-Patent Document 1 and Patent Document 1.

[0011] However, in the standard addition method, in order to create a calibration curve, it is necessary to add target compounds of multiple concentrations to an unknown sample respectively to prepare multiple standard samples, and then analyze each of the multiple standard samples. That is, even if the target compounds are the same, it is necessary to perform the operation of creating a calibration curve for each unknown sample. In addition, when quantifying multiple target compounds contained in a sample, if the concentrations of the target compounds originally contained in the sample vary greatly depending on the compound, it may not be possible to calculate the concentrations of the multiple target compounds by a single standard addition method. In that case, it is necessary to create a calibration curve by the standard addition method while changing the range of known concentrations added to the sample for each target compound.

[0012] Therefore, sample preparation and analysis for quantifying multiple target compounds in an unknown sample take a considerable amount of labor and time. In particular, when quantifying saccharides and the like using gas chromatography, since sample pretreatment including derivatization requires labor and time, it takes a great deal of time and labor to quantify multiple types of compounds for a large number of unknown samples.

[0013] The present invention has been made to solve the above problems, and its main object is to provide a quantitative analysis method and apparatus capable of obtaining quantitative results with practically sufficient accuracy while reducing the burden of sample preparation and analysis operations required for creating a calibration curve by the standard addition method for each unknown sample, which is complicated, laborious, and time-consuming for the user.

Means for Solving the Problems

[0014] One aspect of the quantitative analysis method according to the present invention made to solve the above problems is a quantitative analysis method for quantifying a target compound contained in a sample derived from a living organism, comprising: a category selection step of receiving, by the user, a selection of one category containing the target sample from a plurality of predetermined categories for the sample; a pretreatment step of performing a predetermined pretreatment including derivatization on the target sample; Based on the analysis conditions in gas chromatography-mass spectrometry and the calibration curve information for quantification by the standard addition method for each of the plurality of categories provided from a database storing the same, a measurement execution step of performing gas chromatography-mass spectrometry on the pretreated target sample by the pretreatment step; A quantification processing step of performing quantification processing based on the data obtained in the measurement step using the calibration curve information corresponding to the category selected in the category selection step provided by the database; Execution and it has.

[0015] One aspect of a quantitative analysis apparatus according to the present invention made to solve the above problems is a quantitative analysis apparatus for quantifying a target compound contained in a sample derived from an organism, A database storing analysis conditions in gas chromatography-mass spectrometry and calibration curve information for quantification by the standard addition method for each of a plurality of predetermined categories for the sample; A category selection unit that accepts selection by a user of one category containing the target sample from among the plurality of categories; A measurement unit that performs gas chromatography-mass spectrometry on the target sample subjected to predetermined pretreatment based on the analysis conditions provided by the database; A quantification processing unit that performs quantification processing based on the data obtained by the measurement unit using the calibration curve information corresponding to the one category selected by the category selection unit provided by the database; and it includes.

Effect of the Invention

[0016] According to the above aspects of the quantitative analysis method and the quantitative analysis apparatus according to the present invention, while ensuring practically sufficient quantitative accuracy, it is possible to reduce the burden of sample preparation and analysis work required for creating a calibration curve by the standard addition method for each unknown sample, which is complicated, time-consuming, and laborious for the user. Thereby, for example, quantitative analysis of multiple types of saccharides for a large number of unknown samples can be performed efficiently and labor-savingly.

Brief Description of Drawings

[0017]

Figure 1

Figure 2

Figure 3

Figure 4

Figure 5

Embodiments for Carrying Out the Invention

[0018] [Sample and Compound to be Quantified] In the above aspects of the quantitative analysis method and the quantitative analysis apparatus according to the present invention, the "organism" in the "sample derived from an organism" may include plants, animals (including humans), and microorganisms.

[0019] In addition, the "sample derived from a living organism" specifically refers to, for example, a food sample derived from a living organism, such as agricultural products like vegetables (leafy vegetables, root vegetables, fruit vegetables, fruiting vegetables, aromatic vegetables, etc.), fruits, mushrooms, grains, livestock products mainly consisting of meat, and fishery products mainly consisting of fish. Also, agricultural products, livestock products, and fishery products are usually unprocessed or have a low degree of processing, that is, they are food samples that are the raw materials themselves or close to them. Here, however, it can include processed products that have undergone processes such as fermentation and drying, for example.

[0020] In addition to the above food samples, the "sample derived from a living organism" can include samples derived from a living body, such as blood, urine, sweat, body fluids, etc. collected from humans, or, for example, plasma extracted therefrom.

[0021] In the above aspects of the quantitative analysis method and the quantitative analysis apparatus according to the present invention, the "plurality of categories" varies depending on the type of the above "sample derived from a living organism". For example, when the "sample derived from a living organism" is a food sample as described above, for example, agricultural products, livestock products, and fishery products can each be regarded as one category. Also, among agricultural products, they can be divided into categories such as vegetables and fruits, mushrooms, and grains, and further, they can be divided into finer categories such as leafy vegetables, root vegetables, fruit vegetables, fruiting vegetables, and aromatic vegetables. Also, it is possible to group a plurality of such finely divided categories into one category. Similarly, in the case of fishery products, they can be divided into categories such as fish, shellfish, and crustaceans.

[0022] Such categories can basically be set according to the classifications in taxonomy such as animal taxonomy and plant taxonomy, but that is not essential. For example, in the case of vegetables, etc., generally, not only the characteristics as a plant but also the classification from the perspective of cultivation is considered, and categorization according to that is also possible. Of course, not only categorization based on such theoretical or academic definitions, but also categorization based on experimental verification is possible.

[0023] It is desirable that the correspondence between the type of each sample (e.g., a certain type of vegetable) and the category be easy to understand. This is because it is not appropriate for the user to be confused and waste time when selecting which category the target sample belongs to. Therefore, when a user commonsensically determines that a certain sample belongs to a certain category, it is not necessarily guaranteed that the calibration curve information associated with that category is the calibration curve information that provides the best quantification for that sample (i.e., it is possible that using the calibration curve information associated with another category may result in higher quantification).

[0024] Also, in the above aspects of the quantitative analysis method and quantitative analysis apparatus according to the present invention, the "target compound" to be quantified is an organic compound that can be contained in a sample derived from a living organism, and typically is a metabolite (usually a secondary metabolite) such as a saccharide, a fatty acid, or an amino acid. However, generally, for fatty acids and amino acids, a method using LC / MS analysis or the like is effective for quantification, whereas for saccharides, it is difficult to perform sufficient quantification by such a method. Therefore, the present invention can be said to be particularly effective for the quantification of multiple types of saccharides contained in a sample derived from a living organism.

[0025] [Measurement method of sample] Generally, LC-MS is often used for the analysis of organic compounds in food samples. However, saccharides have many isomers with similar structures, and it is difficult to separate them by mass-to-charge ratio (m / z). Therefore, separation by chromatography is important. When attempting to obtain high separation performance by chromatography using LC or LC-MS, usually, an analysis time of one hour or more is required. On the other hand, in GC-MS, although it is not possible to separate saccharide isomers by m / z as in LC-MS, the separation performance of chromatography is high, and separation with a smaller half-value width compared to LC is possible. Therefore, multi-component simultaneous analysis can be performed in a relatively short analysis time. Thus, in the above aspect of the present invention, GC / MS analysis is used as the measurement method for the sample.

[0026] As is well known, since a gas chromatograph-tandem mass spectrometer (GC-MS / MS) enables two-stage mass separation, it is excellent for separating saccharides from other components in a food sample, and is advantageous for reducing the detection limit and expanding the dynamic range. Therefore, more preferably, GC / MS / MS may be used as a measurement method for the sample.

[0027] [Quantitative Analysis Method and Apparatus According to an Embodiment of the Present Invention] An embodiment of the quantitative analysis method and quantitative analysis apparatus according to the present invention will be described in detail below. This embodiment mainly performs quantitative analysis of multiple types of saccharides in food samples centered on agricultural products, livestock products, and fishery products.

[0028] [Outline of the Quantitative Analysis Method] FIG. 3 is a schematic diagram for explaining the quantitative analysis method of this embodiment. Generally, when performing quantitative analysis using an analyzer such as GC, LC, GC-MS, or LC-MS, prior to quantifying an unknown sample, it is necessary to create a calibration curve using a standard sample. However, as described above, food samples contain various components in addition to the target saccharides, and the matrix effect caused by such contaminants becomes a problem. Although it is desirable to use the standard addition method as a quantification method to reduce the matrix effect, it is a heavy burden on the user to prepare a standard sample for each unknown sample and create a calibration curve. Therefore, in this quantitative analysis method, a calibration curve obtained by the standard addition method used for quantification is created in advance by the manufacturer, stored in a database, and provided to the user.

[0029] However, the types of foods that users want to quantitatively analyze are enormous, and it is not practical for manufacturers to create calibration curves for all of these foods using the standard addition method for each type because the workload would be enormous. Of course, if the types of foods that can be quantified are considerably limited, it is possible to prepare calibration curves for each type of food, but such devices lack versatility. Therefore, in the quantitative analysis method of the present embodiment, a plurality (five in the example of FIG. 3) of food categories that may include various foods are defined, and manufacturers prepare calibration curves for each of these food categories and for each target compound. Prior to quantification, the user designates the food category containing the target sample and performs quantitative analysis on the target sample using the calibration curve associated with that food category.

[0030] As shown in FIG. 3, in this quantitative analysis method, five food categories are defined: vegetables, root vegetables, grains, meats, and fish. Here, the vegetables referred to here include leafy vegetables, fruit vegetables, fruiting vegetables, and spice vegetables, excluding root vegetables. An operator in charge of creating the calibration curve (usually a person in charge of the device manufacturer or the software development manufacturer that installs the software on the device) prepares representative food samples (vegetable A, root vegetable B, grain C, meat D, and fish E in FIG. 3) for each food category and creates a calibration curve using the following procedure with these food samples.

[0031] When performing GC / MS analysis on saccharides, pretreatment including derivatization is carried out because saccharides cannot be sufficiently separated as they are. The specific procedure for this pretreatment will be described later. The operator aliquot a plurality of food samples for calibration curve creation (for example, vegetable A). Then, a plurality of types of compounds (saccharides) a, b,... to be quantified are added to the aliquoted food samples at known concentrations, and a plurality of standard samples are prepared by changing the concentrations of the target compounds a, b,... to be added in multiple steps. Pretreatment is performed on each of the plurality of standard samples thus prepared and the food sample to which no compounds a, b,... have been added, and the samples after pretreatment thus obtained are each measured by GC-MS under predetermined analysis conditions (GC analysis conditions and MS analysis conditions) to acquire data.

[0032] In addition, during the pretreatment, a predetermined internal standard substance is also added to the sample. This is because a calibration curve is created using 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, ... themselves. Thereby, a calibration curve having a function of correcting the difference in the recovery rate of the compound during pretreatment can be created. That is, although the calibration curve created here is basically a calibration curve by the standard addition method, it can also be regarded as a combination of the internal standard method and the standard addition method in essence. Note that the combined use of such an internal standard method and a standard addition method itself is known in Patent Document 1 and the like.

[0033] The GC analysis conditions during analysis include information on the retention times corresponding to each of the compounds a, b, ... and the internal standard substance, and the MS analysis conditions include information on the m / z values of the monitoring ions corresponding to each of the compounds a, b, ... and the internal standard substance. In GC / MS analysis, for each of the compounds a, b, ... and the internal standard substance, extracted ion chromatogram data at the m / z values corresponding to the compound and the internal standard substance in a predetermined time range near the retention time at which the compound and the internal standard substance are observed is acquired. Thereby, from the extracted ion chromatogram, the ratio of the chromatographic peak area of each of the compounds a, b, ... to the chromatographic peak area of the internal standard substance can be obtained. Then, a calibration curve is created from the relationship between the concentrations of each of the compounds a, b, ... and the peak area ratio in a plurality of standard samples, and information on the slope of the calibration curve, specifically, the gradient coefficient information of a linear equation or a quadratic equation, is acquired as calibration curve information.

[0034] Thereby, as shown in FIG. 3, calibration curve information for each of the compounds a, b, ... is obtained for each food sample for creating a calibration curve such as vegetable A. Although there are differences in the recovery rates at which each compound is extracted during pretreatment depending on the type of sample, by using the peak area ratio, that is, by using the internal standard method, a calibration curve in which the difference in the recovery rate is corrected can be obtained. For example, on the device manufacturer side, the calibration curve information thus obtained is stored in a database as calibration curve information corresponding to each food category and provided to the user.

[0035] When the user wants to quantify compounds a, b, … contained in a target sample (unknown sample), the user selects the food category to which the target sample belongs. As shown in FIG. 3, if the target sample is tomato, the user selects the category of vegetables, and if the target sample is tuna or sardine, the user selects the category of fish. Then, the user performs a prescribed pretreatment on the target sample, measures the pretreated target sample by GC-MS under predetermined analysis conditions (GC analysis conditions and MS analysis conditions), and acquires data.

[0036] The pretreatment is specified by the device manufacturer and is basically the same as the pretreatment performed when creating the calibration curve. Therefore, a predetermined concentration of an internal standard substance is added to the target sample during pretreatment. Also, the analysis conditions for GC-MS are specified by the device manufacturer and are basically the same as the GC / MS analysis performed when creating the calibration curve.

[0037] By performing GC / MS analysis on the target sample, extraction ion chromatogram data at m / z values corresponding to each of the compounds a, b, … and the internal standard substance in a predetermined time range near the retention time at which the compound and the internal standard substance are observed are obtained for each of the compounds a, b, … and the internal standard substance. From this extraction ion chromatogram, the ratio of the chromatographic peak area of each of the compounds a, b, … to the chromatographic peak area of the internal standard substance is determined. The concentration of each of the compounds a, b, … is calculated by comparing the value of this peak area ratio with the calibration curve information for each of the compounds a, b, … associated with the food category initially selected. Reference substance Thus, in the quantitative analysis method of the present embodiment, without the user creating a calibration curve based on the complicated and time-consuming standard addition method,

[0038] Device ​Using a calibration curve pre-created on the manufacturer side, various saccharides contained in a food sample can be quantified. Since the calibration curve used at this time is created by the standard addition method, matrix effects caused by various contaminants other than the saccharides contained in the food can be reduced. Also, since the internal standard method is used in combination when creating the calibration curve, it is possible to correct for differences in the recovery rate of compounds in the pretreatment.

[0039] Furthermore, in the quantitative analysis method of the present embodiment, a large number of food samples are categorized, and calibration curve information is registered in and used from a database for each food category. Therefore, not only can the labor and effort required to create a calibration curve be reduced, but also a highly versatile quantitative analysis for various foods, not limited to specific types of foods, can be provided.

[0040] The following modifications can be made to the above quantitative analysis method. Some saccharides, such as glucose, fructose, and sucrose, which are major saccharides, can originally be contained in bio-derived foods at relatively high concentrations. Therefore, when creating a calibration curve for such compounds, the concentration of the compound in the standard sample used is high, and there is a possibility that the accuracy of the calibration curve in the low concentration range particularly decreases. Thus, for some of these specific compounds, instead of the isotope with the largest abundance ratio, a calibration curve is obtained using a stable isotope of the compound containing a stable isotope element with a small abundance ratio, such as deuterium ( 2 H) or carbon-13 ( 13 C), and the slope coefficient of the calibration curve is registered in the database as calibration curve information.

[0041] When quantifying the compound in the target sample, the above stable isotope with a small abundance ratio of the compound is selectively detected, and the concentration is calculated by comparing the peak area ratio of the stable isotope with the calibration curve information. Thereby, as described above, for compounds with high concentrations contained in foods, that is, regardless of the concentration of the compounds contained in foods, quantification can be performed over a wide dynamic range.

[0042] <Specific examples of the pretreatment method> Here, specific examples of the pretreatment when analyzing a food sample by GC / MS will be described. Of course, the pretreatment applicable to the quantitative analysis method of this embodiment is not limited to this. This pretreatment can be broadly classified into two steps: a component extraction step and a derivatization step.

[0043] (1) Component extraction step First, weigh a prescribed amount of the freeze-dried food sample, and add a prescribed amount of a solvent (for example, a mixed solvent of water: methanol: chloroform (1: 2.5: 1)) and an internal standard substance. As an example, as the internal standard substance, ribitol or a stable isotope of a saccharide not used for calibration curve creation can be used. Then, shake the food sample added with the solvent etc. at a temperature of 37°C for 20 minutes to dissolve the compounds contained in the food sample in the solvent. Next, centrifuge the solution under the condition of 16,000 g and collect the supernatant. Add ultrapure water to the collected supernatant, stir and centrifuge again, and then collect a prescribed amount of the supernatant. Freeze-dry the collected supernatant to obtain an extraction sample and finish the component extraction step.

[0044] (2) Derivatization step Add dimethyl sulfoxide (DMSO) as a solvent to the freeze-dried extraction sample and stir well to dissolve the components in the extraction sample in the solvent. Here, by using DMSO, an aprotic solvent, as the solvent, epimerization and isomerization in which the configuration of asymmetric carbon is inverted can be prevented. Then, add 1-methylimidazole and acetic anhydride as derivative reagents to the solution, stir, and then let it stand at room temperature for 10 minutes to promote the derivatization (acetylation) reaction. Then, add ultrapure water to the solution to stop the derivatization reaction, extract the derivatized components using an organic solvent such as dichloromethane, and finish the derivatization step.

[0045] Although it has also been reported in Non-Patent Document 2 and the like, by using DMSO as a solvent when performing derivatization, a plurality of peaks appearing in the chromatogram corresponding to a plurality of stereoisomers of the same compound can be aggregated into one peak. Further, by combining acetic anhydride with 1-methylimidazole as a derivative reagent, the efficiency of the derivatization reaction can be increased.

[0046] <Configuration and Operation of an Example of a Quantitative Analysis System> FIG. 1 is a schematic block configuration diagram of an example of a saccharide quantitative analysis system using GC-MS, which can implement the above-described quantitative analysis method. FIG. 2 is a flowchart showing the procedure and processing flow of quantitative analysis using this saccharide quantitative analysis system.

[0047] As shown in FIG. 1, this saccharide quantitative analysis system includes a pretreatment device 2, a measurement unit 1 including a gas chromatograph (GC) unit 11 and a mass spectrometry (MS) unit 12, an analysis control unit 3 that controls the operations of the GC unit 11 and the MS unit 12 respectively, a data processing unit 4 that processes the data collected by the measurement unit 1, a control unit 5 that is responsible for controlling the entire system, and an input unit 6 and a display unit 7 that are both connected to the control unit 5. The data processing unit 4 includes, as functional blocks, a data storage unit 41, a chromatogram creation unit 42, a quantitative analysis unit 43, and a saccharide quantitative database 44. The MS unit 12 may be any of a mass spectrometer that performs normal mass spectrometry without an ion dissociation operation, or a tandem mass spectrometer capable of MS / MS analysis or MS n analysis.

[0048] The saccharide quantification database 44 stores GC analysis conditions, MS analysis conditions, and calibration curve information for each food category. The GC analysis conditions include, for example, the flow rate program of the carrier gas and the temperature program of the column oven, which are common GC analysis conditions, as well as the retention times of each saccharide (compound) to be quantified. The MS analysis conditions include, for example, the measurement mode (positive and negative polarities, applied voltage to each part, etc.), as well as the m / z values of the monitoring ions of each saccharide to be quantified and the confirmation ion ratios. As described above, usually, these analysis conditions are determined to be the same as those at the time of calibration curve creation. The calibration curve information for each food category is, as described above, for example, the calibration curve information for each compound a, b,... corresponding to each food category, created by the device manufacturer side.

[0049] Generally, the analysis control unit 3, the data processing unit 4, and the control unit 5 are configured with a computer such as a personal computer or a more high-performance workstation including a CPU, a memory, etc. as hardware, and at least a part of their functions can be realized by executing a dedicated processing / control software (computer program) pre-installed on the computer on the computer. The saccharide quantification database 44 may be included in the processing / control software, or may be another software for saccharide quantification analysis.

[0050] The above computer program can be 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 (dongle), etc., and provided to the user. Also, the above program can be provided to the user in the form of data transfer via a communication line such as the Internet. Furthermore, the above program can also be pre-installed in a computer (strictly speaking, a storage device that is a part of the computer), which is a part of the system, when the user purchases the system.

[0051] The procedure and operation for quantifying saccharides in a target sample (food sample) using the saccharide quantification analysis system will be described. The user sets the target sample in the pretreatment device 2, and the pretreatment device 2 executes pretreatment according to the procedure as already exemplified (step S11). Here, it is assumed that the pretreatment device 2 automatically performs pretreatment according to the procedure as described above, but the user may perform pretreatment manually. In this pretreatment, an internal standard substance with a predetermined concentration is added to the target sample, and the saccharides (compounds) in the target sample are derivatized.

[0052] Prior to performing GC / MS analysis on the pretreated target sample with the measurement unit 1, the user selects the food category containing the target sample by performing a predetermined operation on the input unit 6 (step S12). That is, the control unit 5 creates a screen that lists a plurality of food categories registered in the saccharide quantification database 44 and displays it on the display unit 7, and the user views it and selects one food category with the input unit 6. In the example shown in FIG. 1 (and FIG. 3), five food categories, namely meat, fish, vegetables, root vegetables, and grains, are shown as food categories, and the user selects one from them. The control unit 5 accepts the selection of the food category by the user.

[0053] Upon receiving the selection of the food category, in the data processing unit 4, the quantification analysis unit 43 acquires the calibration curve information of each compound associated with the selected food category from the saccharide quantification database 44 (step S13). Also, the analysis control unit 3 acquires the GC analysis conditions and MS analysis conditions from the saccharide quantification database 44 (step S14).

[0054] For example, upon receiving an instruction from 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 pretreated target sample (step S15). As the analysis progresses, the data obtained by the MS unit 12 is input to the data processing unit 4 and stored in the data storage unit 41.

[0055] After that, the chromatogram creation unit 42 reads data from the data storage unit 41, creates an extracted ion chromatogram corresponding to each compound, and identifies each compound using the retention time and confirmation ion ratio of each compound. That is, it is confirmed whether the detected compound is the target compound. When the target compound is detected, the quantitative analysis unit 43 calculates the area ratio of the peaks observed in the extracted ion chromatograms for the target compound and the internal standard substance, and calculates the quantitative value (concentration value) by referring to the calibration curve of that compound based on the value of the area ratio (step S16). The control unit 5 displays the quantitative value for each target compound on the display unit 7 as the quantitative analysis result.

[0056] In this way, in this saccharide quantitative analysis system, it is possible to obtain the concentration values of various saccharides contained in the target sample without the user having to perform any work to create a calibration curve.

[0057] In the above description, the calibration curve information created by actually analyzing one food sample included in the food category was stored in the saccharide quantitative database 44, but this calibration curve information can be adjusted as appropriate. That is, instead of the calibration curve information for a certain type of food sample, for example, the calibration curve information created by actually analyzing a plurality of types of food samples included in the same food category can be used, and the final calibration curve information can be obtained by performing statistical processing such as taking their average. Thereby, the overall or average quantitative accuracy can be improved for various food samples included in one food category. Of course, the user does not need to be aware at all of how the calibration curve information was created or by what algorithm.

[0058] [Experimental Results of Quantitative Analysis] In the quantitative analysis method of this embodiment, in most cases, the type of the food subjected to quantitative analysis is different from the food when the calibration curve information stored in the saccharide quantitative database 44 was created. Therefore, in order to confirm that calibration curve information can be used even if the types of foods are different as long as they are foods included in the same food category, the following experiment was conducted.

[0059] First, for the food category of vegetables, strawberries, which are one of the fruiting vegetables, were used. On the other hand, for the food category of grains, wheat was used, and calibration curve information was created for each of the plurality of saccharides according to the procedure described above. Here, the saccharides to be quantified were meso-erythritol, rhamnose, fucose, lyxose, mannitol, trehalose, maltose, and isomaltose.

[0060] Tomatoes included in the food category of vegetables were prepared as target samples, and 50 ng of each of the above saccharides was added to the samples, followed by pretreatment. GC / MS analysis was performed on the pretreated samples, and from the data obtained thereby, the quantitative values of each saccharide were calculated using the calibration curve information for each of the above food categories of vegetables and grains. However, the concentration of the saccharides originally contained in the target samples was measured separately, and by subtracting it, the quantitative value corresponding to the added amount of 50 ng was obtained. Figure 4 shows the quantitative results using the calibration curve information in the food category of vegetables (the food sample at the time of creating the calibration curve was strawberries). Figure 5 shows the quantitative results using the calibration curve information in the food category of grains (the food sample at the time of creating the calibration curve was wheat).

[0061] As shown in Figure 4, the accuracy of the quantitative values obtained using the calibration curve information in the same food category is within 100 ± 5%. In contrast, as shown in Figure 5, the accuracy of the quantitative values obtained using the calibration curve information in different food categories deviates by more than 15% in mannitol, trehalose, maltose, and isomaltose. This deviation is presumably due to the influence of the matrix being affected by the difference in the type of food. In other words, by appropriately defining a plurality of food categories so that they include foods with similar degrees of matrix influence, even when quantifying the target sample using the calibration curve information created using food samples of different types from the target sample associated with each food category, it can be said that practically sufficient quantification accuracy can be ensured.

[0062] Note that each of the above-described embodiments and modifications is merely an example of the present invention, and it is natural that appropriate corrections, changes, and additions may be made within the scope of the gist of the present invention and still be included in the scope of the claims of this application.

[0063] For example, in the above-described embodiment, the sample is food, but as described above, a biological sample such as blood may also be targeted. In that case, it is natural that the category is appropriately changed accordingly. Further, the organic compound to be quantified may be not only saccharides but also fatty acids, amino acids, etc. When performing GC analysis on these compounds, derivatization is well known, and a pretreatment method corresponding to the compound can be selected.

[0064] [Various Aspects] It is understood by those skilled in the art that the above-described exemplary embodiments are specific examples of the following aspects.

[0065] (Item 1) One aspect of the quantitative analysis method according to the present invention is a quantitative analysis method for quantifying a target compound contained in a sample derived from a living organism, a category selection step of receiving, from a plurality of predetermined categories for the sample, a selection by a user of one category containing the target sample; a pretreatment step of performing a predetermined pretreatment including derivatization on the target sample; a measurement execution step of performing gas chromatography-mass spectrometry on the pretreated target sample by the pretreatment step based on the analysis conditions provided from a database storing the analysis conditions in gas chromatography-mass spectrometry and the calibration curve information for quantification by the standard addition method for each of the plurality of categories; a quantitative processing step of performing a quantitative processing based on the data obtained by the measurement step using the calibration curve information corresponding to the category selected in the category selection step provided by the database; Execution and has.

[0066] (Item 8) Further, one aspect of the quantitative analyzer according to the present invention is a quantitative analyzer for quantifying a target compound contained in a sample derived from an organism, comprising: a database storing analysis conditions in gas chromatography-mass spectrometry and calibration curve information for quantification by the standard addition method for each of a plurality of predetermined categories of samples; a category selection unit that receives selection by a user of one category containing the target sample from among the plurality of categories; a measurement unit that performs gas chromatography-mass spectrometry on the target sample on which predetermined pretreatment has been performed based on the analysis conditions provided by the database; a quantitative processing unit that performs a quantitative process based on the data obtained by the measurement unit using the calibration curve information corresponding to one category selected by the category selection unit and provided by the database; and comprising.

[0067] According to the quantitative analysis method described in Item 1 and the quantitative analyzer described in Item 8, while ensuring practically sufficient quantitative accuracy, it is possible to reduce the burden of sample preparation and analysis work required for creating a calibration curve by the standard addition method for each unknown sample and for each target compound, which is complicated, time-consuming, and labor-intensive for the user. Thereby, for example, quantitative analysis of multiple types of saccharides in a large number of unknown samples can be performed efficiently and labor-savingly.

[0068] (Item 2) In the quantitative analysis method described in Item 1, the sample can be a food product derived from an organism.

[0069] According to the quantitative analysis method described in Item 2, for example, it is effective for searching for organic compounds useful for the human body contained in various foods.

[0070] (Item 3) In the quantitative analysis method described in Item 2, the target compound can be a saccharide.

[0071] According to the quantitative analysis method described in claim 3, a plurality of types of saccharides contained in food can be quantified simultaneously.

[0072] (Claim 4) In the quantitative analysis method described in claim 2 or claim 3, the plurality of categories can be grouped as agricultural products, livestock products, fishery products, or a grouping obtained by further subdividing at least one of them.

[0073] According to the quantitative analysis method described in claim 4, by classifying foods with similar matrix effects into the same category, the quantification accuracy can be improved.

[0074] (Claim 5) The quantitative analysis method according to any one of claims 1 to 4, wherein the calibration curve information is calibration curve information based on the standard addition method and the internal standard method, which is created by 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 quantification step, the quantification value can be obtained from the area ratio or height ratio of the chromatographic peaks of the internal standard substance and the target compound.

[0075] According to the quantitative analysis method described in claim 5, quantification errors caused by differences in the recovery rate of compounds during sample pretreatment or differences in the injection volume when injecting the sample into the gas chromatograph can be corrected. Thereby, for example, even in the case where derivatization with a large variation in recovery rate is performed, the quantification accuracy can be improved.

[0076] (Claim 6) The quantitative analysis method according to any one of claims 1 to 5, wherein the calibration curve information for a specific target compound can be created by the standard addition method using a stable isotope of the target compound containing deuterium or carbon 13 with a relatively low abundance ratio.

[0077] According to the quantitative analysis method described in item 6, for a compound with a relatively high original concentration in the sample, it is possible to avoid the calibration curve concentration range becoming too wide and improve the accuracy of the calibration curve.

[0078] (Item 7) The quantitative analysis method according to any one of items 1 to 6, wherein the target compound is a saccharide, and the pretreatment step includes an extraction step of obtaining an extraction sample in which the compound contained in the sample is extracted into a solvent, and a derivatization step of performing derivatization on the extraction sample. In the derivatization step, an operation of adding an aprotic solvent such as dimethyl sulfoxide and stirring, and an operation of adding at least acetic anhydride and stirring can be performed.

[0079] According to the quantitative analysis method described in item 7, it is possible to prevent the generation of isomers that are likely to occur during the pretreatment of saccharides, and by aggregating chromatographic peaks corresponding to the target compound, the quantification ability can be enhanced.

Explanation of symbols

[0080] 1... Measurement unit 11... GC unit 12... MS unit 2... Pretreatment device 3... Analysis control unit 4... Data processing unit 41... Data storage unit 42... Chromatogram creation unit 43... Quantitative analysis unit 44... Saccharide quantification database 5... Control unit 6... Input unit 7... Display unit

Claims

1. A quantitative analysis method for quantifying a target compound contained in a sample derived from a biological source, comprising: A category selection step of receiving, from a plurality of predetermined categories for the sample, a selection by a user of one category containing the target sample; A pretreatment step of performing a predetermined pretreatment including derivatization on the target sample; A measurement execution step of performing gas chromatography-mass spectrometry on the pretreated target sample by the pretreatment step based on the analysis conditions provided from a database storing the analysis conditions in gas chromatography-mass spectrometry and the calibration curve information for quantification by the standard addition method for each of the plurality of categories; A quantitative processing step of performing a quantitative process based on the data obtained by the measurement execution step by using the calibration curve information corresponding to the category selected in the category selection step provided by the database; A quantitative analysis method having the above steps.

2. The quantitative analysis method according to claim 1, wherein the sample is a food derived from a biological source.

3. The quantitative analysis method according to claim 2, wherein the target compound is a saccharide.

4. The quantitative analysis method according to claim 2 or 3, wherein the plurality of categories are grouped as agricultural products, livestock products, fishery products, or a grouping obtained by further subdividing at least one of them.

5. The calibration curve information is calibration curve information based on the standard addition method and the internal standard method, which is created by 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 processing step, a quantitative value is obtained from the area ratio or height ratio of the chromatographic peaks of the internal standard substance and the target compound. The quantitative analysis method according to any one of claims 1 to 4.

6. The calibration curve information for a specific target compound is created by the standard addition method using a stable isotope of the target compound containing deuterium or carbon 13 with a relatively low abundance ratio, according to any one of claims 1 to 5.

7. The target compound is a saccharide, and the pretreatment step includes an extraction step of obtaining an extraction sample in which the compounds contained in the sample are extracted into a solvent, and a derivatization step of performing derivatization on the extraction sample. 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 performed, according to any one of claims 1 to 6.

8. A quantitative analysis apparatus for quantifying a target compound contained in a sample derived from a living organism, a database storing analysis conditions in gas chromatography-mass spectrometry and calibration curve information for quantification by the standard addition method for each of a plurality of predetermined categories of samples, a category selection unit that accepts selection by a user of one category containing the target sample from among the plurality of categories, a measurement unit that performs gas chromatography-mass spectrometry on the target sample on which predetermined pretreatment has been performed based on the analysis conditions provided by the database, a quantitative processing unit that performs a quantitative process based on the data obtained by the measurement unit using the calibration curve information corresponding to one category selected by the category selection unit and provided by the database, A quantitative analysis apparatus comprising the above.

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