KR102271698B1 - Biomarker for the discrimination of geographical origins of the soybeans and method for discriminating of geographical origin using the same - Google Patents

Abstract

The present invention relates to a biomarker for determining the origin of soybeans and a method for determining the origin using the same.
If the biomarker for determining the origin of soybeans of the present invention is used, the origin of soybeans grown in 7 provinces in Korea can be determined by using the change in the level of metabolites in the soybean. The biomarker of the present invention can be used as an important tool to crack down on acts of taking unfair profits by deceiving the country of origin by using it for actual enforcement, which can contribute to establishing market order for domestically distributed agricultural products and securing consumer trust.

Description

Biomarker for determining the origin of soybeans and a method for discriminating the origin using the same {Biomarker for the discrimination of geographical origins of the soybeans and method for discriminating of geographical origin using the same}

The present invention relates to a biomarker for determining the origin of soybeans and a method for determining the origin using the same.

Country of origin refers to the region where the goods were grown or produced, manufactured, and processed, and in the case of imported goods, it means nationality. With the expansion of global free trade agreements (FTAs), the possibility of agricultural products freely crossing national borders has increased. are gaining their distrust. Korea's country of origin labeling system has been in effect since July 1, 1991, and the Foreign Trade Act has regulations on 「Criteria for judging the country of origin」, 「Goods subject to labeling of the country of origin」, and 「Penalty rules for violations」. In the Customs Act, there are regulations on the confirmation of the country of origin and labeling at the time of customs clearance, and regulation on market distribution. The National Agricultural Products Quality Management Service reported that 4,290 companies in 2014 were caught selling the origin of agri-food by cheating, 4642 in 2012 and 4443 in 2013 were caught for counterfeiting the country of origin. Although the number of companies caught is slightly decreasing every year, more than 10 companies are still caught per day. The government has included “bad food” as one of the four major social evils and is working hard to eradicate it from various angles, but it cannot prevent the alteration of the country of origin of agricultural products that are used directly as food or are the main raw material of processed foods. The scale of counterfeiting and counterfeiting of domestic agricultural products and food is not known precisely, but considering the global trend, it is expected to account for about 10% of the total domestic market. In addition, it is estimated that about 5% of these, that is, about 0.5% of all agricultural products and foods distributed in Korea, are distributed with forged origins. Therefore, scientifically determining the origin of agricultural products is emerging as a nationally important social issue, and it is urgent to secure a scientific and objective method of identification.

So far, the origin of agricultural products has been mainly determined by isotope-ratio mass spectrometry (IRMS), HPLC, visible micro-Raman spectroscopy, ultraviolet-visible absorption spectroscopy (UV-vis), elemental analysis-like inductively coupled plasma-atomic emission spectrometry (ICP- AES) has been used for chemical analysis. However, all of these research methods have limitations as they are targeted approaches that have focused on specific components or groups.

Meanwhile, metabolomics is defined as the study that analyzes and studies metabolites present in agricultural products. In addition, metabolomics is an approach that analyzes all metabolomes in agricultural products in an un-targeted way, and it can efficiently identify differences in genetic or environmental changes. And many studies on the identification of the origin of medicinal crops are in progress.

Since 2010, the Agricultural Products Quality Control Institute has developed a kit for determining the origin of dried persimmon, wolfberry, and rice using single nucleotide polymorphism markers that mainly utilize genomic information, and has applied for or registered a patent. Studies to determine the origin of soybeans have not yet been conducted. In addition, since Korea's soybean consumption is mostly dependent on imports, it is necessary to clarify the country of origin.

Accordingly, the present inventors tried to develop a method for determining the origin of domestically grown soybeans using metabolites in order to solve the problems of the prior art as described above. As a result, using the difference in expression levels of tryptophan, malonylgenistin, malonyldaidzin, N-acetylornithine and allysine, which are metabolites in soybeans, By confirming that the origin of soybeans grown in Korea can be quickly and accurately determined, the present invention has been completed.

Accordingly, one object of the present invention is to provide a biomarker composition for determining the origin of soybeans.

Another object of the present invention is to provide a kit for determining the origin of soybeans comprising the composition.

Another object of the present invention is to provide a method for determining the origin of soybeans using a biomarker for determining the origin of soybeans.

Hereinafter, the present invention will be described in detail.

According to one aspect of the present invention, the present invention is from the group consisting of tryptophan, malonylgenistin, malonyldaidzin, N-acetylornithine and allysine. Provided is a biomarker composition for determining domestic origin of soybeans comprising three or more selected metabolites.

The biomarker for determining the domestic origin of soybeans of the present invention is characterized in that the origin of soybeans can be determined by using the difference in expression level of soybean metabolites by country of origin. The expression level of the metabolite, specifically, it should be understood that the highest expression or low expression among the domestic Gyeonggi-do, Gangwon-do, Chungcheong-do, Gyeongsangbuk-do, Gyeongsangnam-do, Jeollabuk-do and Jeollanam-do.

As used herein, the term "origin" refers to the region where the goods were grown, produced, manufactured, or processed, and in the case of imported and exported goods, refers to the nationality. Korea's country of origin labeling system has been in effect since July 1, 1991, and the Foreign Trade Act has regulations on 「Criteria for determining the country of origin」, 「Goods subject to labeling of the country of origin」, and 「Penalty for violations」. In the Customs Act, there are regulations on the confirmation of the country of origin and labeling at the time of customs clearance, and regulation on market distribution.

As used herein, the term "soybean" is also called "bean", and refers to an annual plant of the legume family or its seeds. Soybeans are the most nutritious and easy-to-digest food among legumes, and are rich in protein and one of the cheapest sources of protein. Soybeans contain 8.6% water, 40% protein, 18% fat, 3.5% fiber, 4.6% ash, 4.4% pentosan, and 7% sugar. The yellow soybean hull contains isoflavone-based pigment. Linoleic aicd, an essential fatty acid contained in soybeans, is effective in removing cholesterol from the blood vessel wall as well as forming a component of the human body. Lecithin has the same effect, so these two components prevent arteriosclerosis. effective in prevention.

As used herein, the term “discriminate” means to discriminate by determining where the soybean is of origin.

As used herein, the term “level difference” refers to high or low metabolite levels between groups for which a specific metabolite in soybean is to be compared.

As used herein, the term "biomarker for determining the origin of soybean" is tryptophan, malonylgenistin, malonyldaidzin, N-acetylornithine in soybeans from the origin. and allicin (Allysine) metabolites are expressed, meaning that they can be used as biomarkers capable of discriminating the origin using the expression level of the metabolites.

Tryptophan, malonylgenistin, Malonyldaidzin, N-acetylornithine and Allysine as the biomarker for determining the origin of soybean can be used alone or three or more types can

According to a preferred embodiment of the present invention, the biomarker composition for determining the origin of soybeans of the present invention is preferably tryptophan, malonylgenistin, malonyldaidzin, N-acetylornithine ( It may include 4 or more selected from the group consisting of N-acetylornithine) and allicin (Allysine). Most preferably, all of the above five species may be included. When using a biomarker composition for determining the origin of soybeans containing all five species, it is possible to more accurately determine the origin of soybeans produced in Gyeonggi-do, Gangwon-do, Chungcheong-do, Gyeongsangbuk-do, Gyeongsangnam-do, Jeollabuk-do and Jeollanam-do.

In one embodiment of the present invention, it was confirmed that there is no significant discriminating effect when using the biomarker composition for determining the origin of soybean including all 10 species out of 210 initially identified, thereby confirming that there is no significant discriminating effect. It was confirmed that the combination of biomarkers for discrimination was optimal.

In addition, the origin may be at least one selected from the group consisting of Gyeonggi-do, Gangwon-do, Chungcheong-do, Gyeongsangbuk-do, Gyeongsangnam-do, Jeollabuk-do and Jeollanam-do.

In addition, the composition may include an agent capable of measuring the level of a metabolite in the soybean, and the agent may measure the level of each metabolite in soybean samples produced from seven regions.

In addition, according to another aspect of the present invention, the present invention provides a kit for determining the domestic origin of soybeans, comprising the biomarker composition for determining the domestic origin of soybeans.

The kit for determining the domestic origin of soybeans of the present invention can be used to determine the origin of the soybean sample by detecting or quantitatively analyzing the metabolite from the soybean sample suspected of origin, but is not particularly limited thereto.

In addition, the kit for determining the domestic origin of soybeans may include direct means for detecting metabolites, as well as other components, solutions or devices used in the analysis method. Examples thereof may include test tubes, containers, reaction buffers, enzymes for analysis, sterile water, and the like.

The kit for determining the domestic origin of soybeans of the present invention is characterized in that it is possible to determine the origin of soybeans by quantitatively analyzing the metabolites of the sample including the three or more types of biomarkers described above.

The kit of the present invention may include a conventional well-shaped microtiter plate capable of carrying a sample. The well may include a porous support capable of adsorbing a sample and one or more biomarkers. The support includes an internal biomarker at a predetermined concentration in preparation for the addition of the soybean metabolite extract, and can also immobilize each sample. In addition, the porosity of the support allows maximum exposure to the extraction solvent added during sample analysis.

Accordingly, the support may be any support having a high level of porosity, and such support is known in the art or commercially available.

Specifically, it may be a solid support. More specifically, it is made of a material that absorbs liquids. The absorbent material may be an adsorbent or an adsorbent material.

The liquid absorbent material allows a solution of the biomarker and a subsequent sample for analysis to be constantly adsorbed or absorbed through the pores.

The absorbent material may include at least one of a carbohydrate material such as cellulose, glass fiber, glass beads, polyacrylamide gel, a porous plastic inert polymer, and porous graphite. More specifically, it may include a carbohydrate material such as agarose, agar, cellulose, dextran, chitosan, or konjac or a derivative thereof, carnaginan, gellan, or alginate. Most specifically, it may be cellulose or glass fibers.

It can be understood that the biomarker included in the kit of the present invention is an absolute amount of a comparative substance of known amount, which is used as a comparison to a similar or identical analog to quantify the amount of a metabolite present in a sample. The biomarker may be labeled with an isotope for proper differentiation from a metabolite of the sample.

In addition, the sample that can be used in the kit of the present invention is a metabolite extract for each origin of soybean, and may be provided in the kit in the form of a liquid sample.

The extraction method of the metabolite is not particularly limited, but preferably a solvent extraction method is used. The solvent is not particularly limited as long as it can dissolve soybean metabolites. For example, as the solvent, water; lower alcohols such as methanol, ethanol, propanol and butanol; acetone; trifluoroethanol; tetrahydrofuran; dichloromethane; phosphate; and mixed solvents thereof.

For example, the metabolite extract can be obtained by homogenizing soybeans in a mixed solvent of methanol and water, specifically 1:1 to 9:1 by volume, more specifically, in a mixed solvent of 7:3 by volume. It is not limiting.

In addition, in order to widen the extraction range of metabolites, a process of homogenizing the soybean sample in the solvent may be additionally performed.

In addition, the microtiter plate may further include a filter and an outlet for discharging the analyte, and their arrangement, discharging method, etc. can be adjusted within a range that can be understood by those skilled in the art.

In addition, the kit of the present invention may further include reagents, solvents, software systems, etc. included in an apparatus capable of preparing various metabolites for quantitative target analysis of a range of metabolites, typically in combination with an analysis device.

Since the kit of the present invention uses the above-described composition, the description of overlapping contents as described above is omitted in order to avoid excessive complexity of the present specification.

Further, according to another aspect of the present invention, the present invention provides a method for determining the domestic origin of soybeans, comprising the steps of:

(a) extracting metabolites from soybeans; and

(b) tryptophan, malonylgenistin, malonyldaidzin, N-acetylornithine and allicin among the metabolites extracted in step (a) Analyzing three or more metabolites selected from the group consisting of gas chromatography-mass spectrometry and liquid chromatography-mass spectrometry.

The origin is at least one selected from the group consisting of Gyeonggi-do, Gangwon-do, Chungcheong-do, Gyeongsangbuk-do, Gyeongsangnam-do, Jeollabuk-do and Jeollanam-do.

Preferably, the origin is determined by the difference in expression level between the metabolites of step (b).

In one embodiment of the present invention, the differentiation of metabolites between soybean samples of different origins is determined by the following method:

(1) After screening 5 metabolites (Tryptophan, Malonylgenistin, Malonyldaidzin, N-acetylornithine, Allysine) showing differences in 7 regions in Korea, orthogonal partial least squares discrimination (OPLS-DA) was performed on the selected metabolites. modeling response variables in a multivariate manner using

(2) comparing the relative level difference using the intensities of metabolites analyzed by GC/TOF MS and LC/Orbitrap MS;

(3) comparing AUC (Area Under the Curve) values by sequentially applying a method of verifying metabolite biomarkers using a ROC curve (Receiver Operating Characteristic curve); and

(4) Metabolite biomarker analysis from soybean samples by verifying metabolite biomarkers using ROC curve (Receiver Operating Characteristic curve).

Methods for measuring the level difference of metabolites in the soybean sample include a mass spectrometer, a chromatography instrument, a chromatography-combined mass spectrometer (Chromatography-mass spectrometer), and a nuclear magnetic resonance spectrometer (Nuclear Magnetic). Resonance spectrometer), Raman spectroscopy (Raman spectroscopy), light absorption analysis (light absorption analysis), flow injection analysis (flow injection analysis) analysis method using instruments such as; Quantitative analysis of metabolites using specific binding between the metabolite-specific antibody, eptamer, peptide, nucleic acid, or polymer and the metabolite; ELISA (enzyme linked immunosorbent asay), Western blot, Radioimmunoassay (RIA), radioimmunodiffusion, Ouchterlony immunodiffusion method, rocket immunoelectrophoresis, tissue immunostaining, immunity Precipitation assay (Immunoprecipitation assay), complement fixation assay (Complement Fixation Assay), FACS (Fluorescence activated cell sorter) or a method such as microarray (microarray) can be performed using a method, but is not limited thereto. Preferably, as a method for measuring the level of the metabolite, gas chromatography analysis, liquid chromatography, and mass spectrometry may be used.

Chromatography used in the present invention is gas chromatography (Gas Chromatography), liquid-solid chromatography (Liquid-Solid Chromatography, LSC), paper chromatography (Paper Chromatography, PC), thin-layer chromatography (Thin-Layer) Chromatography, TLC), Gas-Solid Chromatography (GSC), Liquid-Liquid Chromatography (LLC), Foam Chromatography (FC), Emulsion Chromatography (Emulsion Chromatography, EC), Gas-Liquid Chromatography (GLC), Ion Chromatography (IC), Gel Filtration Chromatography (GFC) or Gel Permeation Chromatography (GPC) It includes, but is not limited to, any chromatography for quantitative use commonly used in the art can be used. Preferably, the chromatography used in the present invention is gas chromatography and liquid chromatography. Preferably, the mass spectrometer used in the present invention is MALDI-TOF MS or TOF MS and Orbitrap MS, and more preferably TOF MS and Orbitrap MS.

In addition, when the analysis method using the apparatus is performed, the method may further include the step of extracting and obtaining a metabolite from the soybean sample, and treating the extracted metabolite with methoxyamine for derivatization.

In addition, in another embodiment of the present invention, the differentiation of metabolites between soybean samples of different origins is discriminated in the following way: First, in order to screen for biomarkers for determining the origin of soybeans, cultivated in 7 provinces in Korea Soybean samples were obtained and metabolites were extracted. The solvent is methanol:isopropanol:distilled water (3:3:2), and the extracted sample was derivatized with pyridine and MSTFA for effective Gas Chromatography Mass Spectrometer analysis. Thirteen different fatty acid methyl esters were added as internal retention markers. In addition, for liquid chromatography mass spectrometer analysis, reconsitution was performed with 80% methanol.

Thereafter, differences in metabolite profiles were compared and analyzed using GC/TOF MS and LC/Orbitrap MS. To this end, the analysis result was changed to a numerical value that can be processed statistically, and the difference was statistically verified using the converted value. As a result, 210 metabolites were identified. For standardization, the method of dividing the intensity from the GC/TOF MS and LC/Orbitrap MS analysis results by the sum of the metabolite intensity was used, and additionally, the displacement difference standardization method was performed.

In addition, in order to search for single biomarker candidates showing differences between groups, (1) principal component analysis (PCA); (2) VIP ranking search through orthogonal partial least squares analysis (OPLS-DA); (3) Common metabolites in ANOVA analysis were verified as candidates. In addition, complex biomarkers were searched through various combinations thereof. It is possible to model the response variable in a multivariate manner through orthogonal partial least squares discriminant analysis (OPLS-DA) and extract components such as principal component analysis.

In addition, as a result of confirming a total of six single metabolite candidates and 42 combinations thereof through ROC analysis, the AUC values between the four groups were all confirmed to be 0.7 or higher. In addition, an analysis for deriving a higher AUC value (AUC value > 0.8 for diagnosis of disease) was added and performed.

In addition, the group-specific metabolites could be identified through the t-test for each group. Group-specific metabolites were selected by comparing the magnitude of the significant difference of metabolites by fold change and analyzing the pattern in which the amount increased or decreased.

Among them, five newly selected metabolites (Tryptophan, Malonylgenistin, Malonyldaidzin, N-acetylornithine, Allysine) were selected as biomarkers that can discriminate the origin of soybeans grown in 7 provinces in Korea. By enabling reliable and accurate identification, it was made applicable to actual country of origin control.

Therefore, it was confirmed that the origin of soybeans could be determined more consistently and reliably when using the method for determining the origin of soybeans using the biomarker for determining the origin of soybeans of the present invention. In addition, this can be applied to the actual origin control, and can be applied to various agricultural products other than soybeans.

If the biomarker for determining the origin of soybeans of the present invention is used, the origin of soybeans grown in seven domestic provinces can be determined by using the change in the level of metabolites in the soybean. The biomarker of the present invention can be used as an important tool to crack down on acts of taking unfair profits by deceiving the country of origin by using it for actual enforcement, which can contribute to establishing market order for domestically distributed agricultural products and securing consumer confidence.

1 is a diagram showing the difference between metabolites detected in soybean samples grown in 7 provinces in Korea as a result of analyzing the results obtained through mass spectrometry using principal component analysis (PCA).
2 is a diagram showing the difference between metabolites detected in soybean samples grown in 7 provinces in Korea as a result of orthogonal partial least squares discriminant analysis (OPLS-DA).
3 is a result showing the relative abundances based on a hierarchical clustering analysis (HCA). The minimum 5 metabolites that can determine the origin of soybeans grown in 5 provinces in Korea ( Tryptophan, Malonylgenistin, Malonyldaidzin, N-acetylornithine, Allysine) are selected and each value is shown.
4 is a diagram showing the AUC curve results showing the discrimination results for each region when the five metabolites selected in the present invention are used.

Hereinafter, the present invention will be described in more detail based on examples. The examples are only for illustrating the present invention in more detail, and it will be apparent to those of ordinary skill in the art that the scope of the invention is not limited by these examples according to the gist of the present invention.

Example 1. In the sample metabolite extraction and derivatization

1-1. pretreatment of soybean samples and metabolite extraction

Soybean samples from Gyeonggi-do, Gangwon-do, Chungcheong-do, Gyeongsangbuk-do, Gyeongsangnam-do, Jeollabuk-do and Jeollanam-do were provided by the National Agricultural Products Quality Management Service. was pretreated with

For metabolite extraction in the soybean sample, 20 mg of the frozen soybean powder was put into a tube and 1 ml of an extraction solvent (methanol:isopropranol:distilled water, 3:3:2, v/v/v) ) was added. The mixture was sonicated at 4° C. for 10 minutes, centrifuged at 13,200 rpm for 5 minutes, and 850 μl of the supernatant was placed in another tube and dried using a speed vacuum concentrator. The dried extract was stored frozen at -80°C until analyzed by GC-TOF mass spectrometer and LC-Orbitrap mass spectrometer.

1-2. metabolite derivatization

For more effective analysis of the soybean metabolite sample extracted in Example 1-1, derivatization was performed. For this, 5 μl of methoxyamine hydrochloride at a concentration of 40 mg/ml was first added and reacted for 90 minutes. (200 rpm, 30 °C). Then, fatty acid methyl esters (Fatty acid methyl esters: FAME, C8, C9, C10, C12, C14, C16, C18, C20, C22, C24, C26, C28 and C30) using the retention time index index (internal retention) index markers), and after dissolving C8-C16 and C18-C30 in chloroform at a concentration of 0.8 mg/ml and 0.4 mg/ml, respectively, 2 μl of fatty acid methyl ester, N-methyl-N-trimethylsilyltrifluoroacetamide (MSTFA) + 1% TMCS, Thermo, USA) 45 μl was added and reacted for 1 hour at 200 rpm and 37°C.

1-3. metabolite resuspension

For more effective analysis of the soybean metabolite sample extracted in Example 1-1, resuspension was performed. For this, 100 μl of 80% methanol was added for reconstitution.

Example 2. metabolite Detection and analysis

2-1. Gas Chromatography Analysis

For the detection of metabolites in samples extracted from soybean samples, 0.5 μl of the metabolite sample derivatized in Example 1-2 was injected into gas chromatography using an Automatic Liquid Sampler (Agilent 7693 ALS, Agilent Technologies, Wilmington, DE). did. For gas chromatography, an Agilent 7890B gas chromatograph (Agilent Technologies, Wilmington, DE) and an RTX-5Sil MS column (30 m × 0.25 mm, 0.25 μm film thickness, Restek, Gelefonte, PA) were used and the first minute was at 50°C. , and thereafter, the temperature was increased by 20 °C per minute to reach 330 °C and maintained for 5 minutes. The transfer line temperature of gas chromatography was set to 280°C.

2-2. mass spectrometry analysis

In addition, mass spectrometry was performed using a mass spectrometer to detect metabolites in samples extracted from soybean samples. For mass spectrometry, a Pegasus HT TOF mass spectrometer based on the Pegasus HT time of flight (TOF) MS software 4.50 (LECO, St. Joseph, MI) program was used. Mass spectra of metabolites were obtained at the rate. The temperature of the ion source was adjusted to 250 °C, and electron impact ionization was performed at 70 eV.

2-3. Liquid chromatography analysis

For the detection of metabolites in samples extracted from soybean samples, 2 μl of the metabolite samples resuspended in Examples 1-3 were injected and separated by liquid chromatography. Liquid chromatography was performed using UltiMate 3000 (Thermo Fisher Scientific, MA, USA) and Waters Acquity UPLC BEH C18 Column (2.1 mm × 150 mm, 1.7 μm), and DW (Solvent A) containing 0.1% Formic acid as a mobile phase, respectively. and Acetonitrile (Solvent B) were used and analyzed at the following gradient at a flow rate of 300 μl/min; 0 - 2.0 min, 0% B; 2.0 - 30.0 min, 0% - 100% B; 30.0 - 32.0 min, 100% B; 32.0 - 32.1 min, 100% - 0% B; 32.1 - 35.0 min, 0% B.

2-4. mass spectrometry analysis

In addition, mass spectrometry was performed using a mass spectrometer to detect metabolites in the samples separated in Example 2-3. For mass spectrometry, a Q-Exactive Plus (Thermo Fisher Scientific, MA, USA) instrument was used, and mass spectra of metabolites were obtained in a positive ionization mode in a mass range of 100-1200 Da.

2-3. metabolite initial sympathy

For initial identification (annotation) of the metabolites analyzed in 2-1 and 2-2, a comparative analysis was performed through the coincidence of the spectrum using the Fiehn library (2007)/NIST library (2012), and then It was verified through direct comparison of the spectrum and retention time of the standard material. As a result, a total of 210 metabolites were detected in soybean samples through the above procedures.

Compound Compound Compound Compound 1-deoxyerythritol melibiose 9-Oxo-10(E),12(E)-octadecadienoic acid LysoPE 18:1 1-monopalmitin methionine Abscisic acid LysoPE 16:0 2-deoxyerythritol methionine sulfoxide Acetyldaidzin LysoPE 18:0 2-hydroxypyridine myo-inositol Acetylgenistin LysoPE 18:2 2-monopalmitin nicotinic acid Acetylglycitin LysoPE 18:3 3-hydroxypropionic acid n-methylalanine Adenosine 3'-monophosphate LysoSM 18:0 3-hydroxypyridine norvaline Adenosine Malonyldaidzin 3-phenyllactic acid oleic acid Agmatine Malonylgenistin 3-phosphoglycerate ornithine Allysine Malonylglycitin adenosine-5-monophosphate oxalic acid alpha-lactose Monoisobutyl phthalic acid alanine oxoproline Apigerin N(6)-(Octanoyl)lysine asparagine palmitic acid Argininosuccinic acid N-Acetyl-L-glutamate 5-semialdehyde asparagine dehydrated phenylalanine Aspartame N-Acetylornithine aspartate phosphoethanolamine Betaine Naringenin beta alanine pinitol Bis(2-ethylhexyl) amine Ophthalmic acid butane-2,3-diol proline Ceramide 34:1 Oxoglutaric acid butyrolactam pyrophosphate Choline Palmitic amide cellobiose pyruvic acid Cytosine PC 36:4 cholesterol ribitol Pantothenic acid p-Cymene citric acid ribose Aminoadipic acid PE 18:5 citrulline serine Daidzein PE 36:4 cysteine sorbitol Daidzin Phosphocholine enolpyruvate stearic acid DEET Quercetin erythritol succinic acid Dehydroascorbic acid Rutin ethanolamine sucrose DG 36:6 Safrole ethanol phosphate threonic acid Arginine sn-Glycero-3-phosphocholine fructose threonine Pipecolinic acid Soyasaponin 1 fumaric acid trehalose Stachydrine Soyasaponin 2 galactinol trehalose-6-phosphate Eriodictyol Soyasaponin 3 gamma-aminobutyric acid tris(ethylenglycol) Erucamide Soyasaponin 4 gluconic acid tryptophan Gamma-Glutamyltyrosine Soyasaponin 5 glucose tyrosine Genistein Soyasaponin αg glucose-6-phosphate uracil Genistin Soyasaponin Bd glutamine uridine Glycitein Soyasaponin Be glyceric acid valine Glycitin Soyasaponin βa glycerol xanthine Glycylprolylhydroxyproline Soyasaponin βg glycerol-alpha-phosphate xylose Hexamethylenetetramine Soyasaponin γa glycine (R)-N-Methylsalsolinol Homo-L-arginine Soyasaponin γg glycolic acid 1-(sn-Glycero-3-phospho)-1D-myo-inositol Indole-3-acrylic acid spermidine guanine 19-Nortestosterone Isorhamnetin Succinyladenosine guanosine 2-5-Furandicarboxylic acid Jasmonic acid Sulcatol heptadecanoic acid 3,5-di-tert-Butyl-4-hydroxybenzaldehyde Kaempferol Texanol hexitol 3,5-di-tert-Butylbenzaldehyde Kynurenic acid trans-4-Hydroxy-L-proline homoserine 3-Acetylindole Carnitine Triisopropanolamine hydroxylamine 3-Cresotinic acid Leucine Vinylacetylglycine inositol-4-monophosphate 3-Hydroxyadipic acid L-gamma-glutamyl-L-leucine isoleucine 3-Methylglutaconic acid L-gamma-glutamyl-L-valine isothreonic acid 4-Aminobenzoic acid Glutamic acid lactic acid 4-Guanidinobutanoic acid Histidine lactitol 4-Methoxycinnamaldehyde Linoleoyl ethanolamide lysine 5-(2'-Carboxyethyl)-4-6-Dihydroxypicolinate LysoPC 16:0 lyxitol 5-Hydroxymethyl-2-furaldehyde LysoPC 18:0 lyxose 8-Hydroxyadenine LysoPC 18:1 malic acid 9-10-DHOME LysoPC 18:2 maltotriose 9-HODE LysoPC 18:3

Example 3. metabolite biomarker Selection

3-1. principal component analysis, PCA )

As an analysis for biomarker selection among a total of 210 metabolites detected through the process of Examples 1 and 2, metabolites detected through principal component analysis (PCA) were first schematically illustrated, and the results are shown in Fig. 1 is shown.

As shown in FIG. 1 , it was confirmed that there was a difference in the metabolite distribution in the soybean sample by region.

3-2. Least squares discrimination of orthogonal parts orthogonal partial least squares discriminant analysis , OPLS -DA)

In addition, orthogonal partial least squares discriminant analysis (OPLS-DA) analysis was performed to confirm the distribution of metabolites according to domestic cultivation regions, and the results are shown in FIG. 2 .

As shown in FIG. 2 , it was confirmed that there was a difference in the metabolite distribution in the soybean sample by region.

3-3. Hierarchical clustering analysis, HCA )

In addition, for statistical analysis of the detected metabolites, hierarchical clustering analysis (HCA) using Multi Experiment Viewer (MeV, ver.4.8.1) was performed. Thereafter, based on the analysis results, statistically identifiable metabolites were selected and the relative abundances were analyzed, which is shown in FIG. 3 .

As shown in FIG. 3, the 5 metabolites Tryptophan, Malonylgenistin, Malonyldaidzin, N-acetylornithine and Allysine metabolites for each region It can be seen that there is a difference in the distribution of Therefore, they were selected as metabolite biomarkers.

Example 4. metabolite biomarker Verification and establishment

In order to verify and establish the metabolite biomarker selected in Example 3, a model using the selected metabolite biomarker was applied. At this time, the discrimination ability for each region is shown as an ROC curve, which is shown in FIG. 4 shown in

As shown in FIG. 4, the AUC values were 0.87 in Chungcheong-do and 0.907 in Gyeongsangnam-do, and 1 in Gyeonggi-do, Gangwon-do, Gyeongsangbuk-do, Jeollabuk-do, and Jeollanam-do, confirming that the selected biomarker had a very high discrimination power by soybean region.

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In conclusion, the metabolite markers for determining the origin of soybean selected through the present invention can determine the origin of domestic soybeans quickly and with high accuracy, and the development of biomarkers that can help prevent confusion in the domestic soybean industry distribution system in the future It is expected to be a cornerstone.

Metabolite marker ratios of soybeans for each region according to the present invention are as follows.

Gyeonggi-do soybeans contain a lot of metabolites N-acetylornithine and allicin, but relatively few tryptophan, malonylgenistine, and malonyldizine. When used as a biomarker of the present invention, the distribution ratio of tryptophan, malonylgenistine, malonyldizine, N-acetylornithine and allicin, which are metabolites in soybean produced in Gyeonggi-do, is 0.82: 0.88: 0.84: 1.31: 1.35.

Soybeans from Gangwon-do generally contain a lot of metabolites such as tryptophan, malonylgenistine, malonyldizine, N-acetylornithine and allicin. When used as a biomarker of the present invention, the distribution ratio of tryptophan, malonylgenistine, malonyldizine, N-acetylornithine and allicin, which are metabolites in soybean produced in Gangwon-do, is 1.26: 1.37: 1.25: 1.04: 1.12.

Soybeans from Chungcheong-do contain a lot of tryptophan, a metabolite, but in comparison, malonylgenistine, malonyldidine, N-acetylornithine and allicin are relatively low. When used as the biomarker of the present invention, the distribution ratio of tryptophan, malonylgenistine, malonyldizine, N-acetylornithine and allicin, which are metabolites in soybean produced in Chungcheong-do, is 1.14: 0.94: 0.91: 0.92: 0.88.

Soybeans from Gyeongsangbuk-do contain a lot of substances such as metabolites malonylgenistin and malonyldizine, but relatively little tryptophan, N-acetylornithine and allicin. When used as a biomarker of the present invention, the distribution ratio of tryptophan, malonylgenistine, malonyldizine, N-acetylornithine and allicin, which are metabolites in soybean from Gyeongsangbuk-do, is 0.86: 1.19: 1.34: 0.89: 0.76.

Soybeans from Gyeongsangnam-do contain a lot of metabolites such as malonylgenistine, malonyldizine, and N-acetylornithine, but relatively little tryptophan and allicin. When used as a biomarker of the present invention, the distribution ratio of tryptophan, malonylgenistine, malonyldizine, N-acetylornithine and allicin, which are metabolites in soybean from Gyeongsangnam-do, is 0.89: 1.19: 1.25: 1.09: 0.99.

Soybeans from Jeollabuk-do contain relatively low levels of metabolites such as tryptophan, malonylgenistine, malonyldizine, N-acetylornithine and allicin. When used as a biomarker of the present invention, the distribution ratio of tryptophan, malonylgenistine, malonyldizine, N-acetylornithine and allicin, which are metabolites in soybean from Jeollabuk-do, is 0.95: 0.82: 0.83: 0.83: 0.96.

Soybeans from Jeollanam-do contain a lot of tryptophan, a metabolite, but relatively low amounts of malonylgenistine, malonyldidine, N-acetylornithine and allicin. When used as the biomarker of the present invention, the distribution ratio of tryptophan, malonylgenistine, malonyldizine, N-acetylornithine and allicin, which are metabolites in soybean produced in Jeollanam-do, is 1.09: 0.61: 0.58: 0.93: 0.94.

Claims (6)

Extracted from soybean, including tryptophan, malonylgenistin, malonyldaidzin, N-acetylornithine and Allysine as metabolites, domestic soybean As a biomarker composition for discrimination of origin varieties,
analyzing the content of five metabolites extracted from the soybean by gas chromatography-mass spectrometry and liquid chromatography-mass spectrometry, and determining domestic origin varieties by the difference in the content level of the metabolites;
The domestic origin varieties of soybeans are from Gyeonggi-do, Gangwon-do, Chungcheong-do, Gyeongsangbuk-do, Gyeongsangnam-do, Jeollabuk-do and Jeollanam-do,
Biomarker composition for discrimination of domestic origin varieties of soybeans.
According to claim 1,
The content ratio of tryptophan, malonylgenistine, malonyldaidzine, N-acetylornithine and allicin in the Gyeonggi soybean is 0.82: 0.88: 0.84: 1.31: 1.35;
The content ratio of tryptophan, malonylgenistin, malonyldizine, N-acetylornithine and allicin in Gangwon-do soybean is 1.26: 1.37: 1.25: 1.04: 1.12;
The content ratio of tryptophan, malonylgenistine, malonyldizine, N-acetylornithine and allicin in the Chungcheong-do soybean is 1.14: 0.94: 0.91: 0.92: 0.88;
The content ratio of tryptophan, malonylgenistine, malonyldizine, N-acetylornithine and allicin in the Gyeongsangbuk-do soybean is 0.86: 1.19: 1.34: 0.89: 0.76;
The content ratio of tryptophan, malonylgenistine, malonyldizine, N-acetylornithine and allicin of the soybean produced in Gyeongsangnam-do is 0.89: 1.19: 1.25: 1.09: 0.99,
The Jeollabuk-do soybean has a content ratio of tryptophan, malonylgenistin, malonyldizine, N-acetylornithine and allicin of 0.95: 0.82: 0.83: 0.83: 0.96;
The Jeollanam-do soybean has a content ratio of tryptophan, malonylgenistine, malonyldaidzine, N-acetylornithine and allicin of 1.09: 0.61: 0.58: 0.93: 0.94. marker composition.
A kit for discriminating domestic origin varieties of soybeans, comprising the biomarker composition for identifying domestic origin varieties of soybeans of claim 1.
A method for determining domestic origin varieties of soybeans, comprising the following steps:
(a) extracting metabolites from soybeans; and
(b) of the metabolites extracted in step (a) of tryptophan, malonylgenistin, malonyldaidzin, N-acetylornithine and allicin Analyzing the content by gas chromatography-mass spectrometry and liquid chromatography-mass spectrometry, and determining the domestic origin variety by the difference in the content level of the metabolites.
5. The method of claim 4,
The content ratio of tryptophan, malonylgenistine, malonyldaidzine, N-acetylornithine and allicin in the Gyeonggi soybean is 0.82: 0.88: 0.84: 1.31: 1.35;
The content ratio of tryptophan, malonylgenistin, malonyldizine, N-acetylornithine and allicin in Gangwon-do soybean is 1.26: 1.37: 1.25: 1.04: 1.12;
The content ratio of tryptophan, malonylgenistine, malonyldizine, N-acetylornithine and allicin in the Chungcheong-do soybean is 1.14: 0.94: 0.91: 0.92: 0.88;
The content ratio of tryptophan, malonylgenistine, malonyldizine, N-acetylornithine and allicin in the Gyeongsangbuk-do soybean is 0.86: 1.19: 1.34: 0.89: 0.76;
The content ratio of tryptophan, malonylgenistine, malonyldizine, N-acetylornithine and allicin in the soybean from Gyeongsangnam-do is 0.89: 1.19: 1.25: 1.09: 0.99,
The Jeollabuk-do soybeans have a content ratio of tryptophan, malonylgenistin, malonyldizine, N-acetylornithine and allicin of 0.95: 0.82: 0.83: 0.83: 0.96;
The Jeollanam-do soybean is characterized in that the content ratio of tryptophan, malonylgenistin, malonyldizine, N-acetylornithine and allicin is 1.09: 0.61: 0.58: 0.93: 0.94,
A method for identifying domestic varieties of soybeans. delete

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