KR20200136669A - Biomarker for the Discriminating Geographical Origins of Sesame and Method for Discriminating Geographical Origin Using the Same - Google Patents

Abstract

The present invention relates to a biomarker for determining the origin of sesame seeds and a method for determining the origin of sesame seeds using the same. By using the biomarker for determining the origin of sesame seeds of the present invention, it is possible to determine whether it is domestic sesame seeds or imported sesame seeds by using a change in the level of metabolites in sesame seeds. The biomarker of the present invention can be used as an important tool to crack down on acts of deceiving origin and taking unreasonable profits by being used for actual crack down, which can contribute to establishing marker order of domestically distributed agricultural products and securing consumer trust.

Description

Biomarker for the Discriminating Geographical Origins of Sesame and Method for Discriminating Geographical Origin Using the Same}

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

Origin refers to the region where the product has grown, produced, manufactured, or processed, and in the case of import and export products, it refers to the nationality. With the expansion of the global Free Trade Agreement (FTA), the possibility of agricultural products freely crossing the borders of each country has increased.However, there are cases where the origin of agricultural products is forged and sold through trade between countries, disturbing the market order and causing consumers to People are buying distrust. The country of origin labeling system in Korea has been in force since July 1, 1991, and the Foreign Trade Act stipulates regulations on'country of origin criteria','products subject to country of origin', and'penalties for violations'.

The Customs Act establishes and operates regulations regarding verification of the country of origin and labeling at the time of customs clearance, and crackdowns in the distribution process on the market. The National Agricultural Products Quality Management Service revealed that in 2014, 4290 companies were caught selling agri-food by tricking them of the origin. In 2012, 4642 companies and in 2013 4443 companies were caught forging the country of origin. Although the number of companies caught year by year is declining slightly, there are still more than 10 companies detected per day. The government has included "defective food" as one of the four major social evils and is making various efforts to eradicate it, but it has not prevented the alteration of the origin of agricultural products that are directly used as food or are the main raw materials for processed foods. Although the scale of forgery and alteration of domestic agricultural products and foods is not accurately known, considering the global trend, it is predicted to account for about 10% of the total domestic market.

In addition, it is estimated that about 5% of them, that is, about 0.5% of all agricultural products and foods distributed in Korea, are being distributed due to the forgery of their origin. Therefore, scientifically determining the origin of agricultural products is emerging as an important social issue nationally, and securing a scientific and objective method of discrimination is urgent.

To date, the identification of the origin of agricultural products has mainly been 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), etc. have been used for chemical analysis. However, all of these research methods have limitations as targeted approaches that have focused on specific components or groups.

Meanwhile, metabolomics is defined as the study of analyzing and studying metabolites present in agricultural products. In addition, metabolomics is an approach that analyzes the metabolome in agricultural products in a non-targeted manner, and because it can efficiently identify differences in genetic differences or environmental changes, agricultural products using metabolomics And many studies on the identification of the origin of medicinal crops are being conducted.

Since 2010, the Agricultural Products Quality Management Service has developed a kit for determining the origin of dried persimmon, goji berry, rice, etc. using a single base polymorphism marker mainly using genomic information, and is pending or registered for a patent, but is grown in Korea using metabolites. Research to determine the origin of sesame seeds has not yet been conducted.

In addition, with the recent opening of the agricultural and marine products market, interest in the protection and promotion of domestic agricultural products such as management of the origin of agricultural products is increasing.In the case of sesame seeds, domestic production is 13% of the total consumption, and there are cases of illegal distribution of origin. Incessantly, in the case of the prior art, since it is not possible to provide a method for determining whether sesame seeds are domestically or imported, the development of a scientific method of determining origin is urgent.

Therefore, there is a need to develop a discrimination method for preserving income and preventing illegal distribution of domestically produced farmers by accurately distinguishing between domestic and imported sesame seeds.

Accordingly, the present inventors have made research efforts to develop a method for determining the origin of sesame seeds grown in Korea using metabolites in order to solve the problems of the prior art. As a result, the present inventors analyzed metabolites in sesame seeds showing differences in expression levels for each country of origin of Korean and imported sesame seeds, as markers for determining the origin of five types of sesame seeds, Valine, L-Glutathione ), 2-Amino-1,3,4-octadecanetriol, adenosine 5'-monophosphate and D-rapinose (D -Raffinose) was established, and it was confirmed that the country of origin of Korean and imported sesame seeds can be quickly and accurately determined, thereby completing the present invention.

Accordingly, an object of the present invention is to provide a biomarker composition for determining the origin of sesame seeds.

In addition, another object of the present invention is to provide a kit for determining the origin of sesame seeds comprising the composition.

In addition, another object of the present invention is to provide a method for determining the origin of sesame seeds by using a biomarker for determining the origin of sesame seeds.

Hereinafter, the present invention will be described in detail.

According to one aspect of the present invention, the present invention provides valine, L-glutathione, 2-amino-1,3,4-octadecantriol (2-Amino-1,3, 4-octadecanetriol), adenosine 5'-monophosphate (Adenosine 5'-monophosphate) and a biomarker composition for determining the origin of sesame seeds comprising at least one metabolite selected from the group consisting of D-Raffinose to provide.

The biomarker for determining the origin of sesame seeds of the present invention is characterized in that it is possible to determine the origin of sesame seeds by using a difference in the expression level of metabolites of sesame seeds by origin. It should be understood that the level of expression of the metabolite is, specifically, the most high or low expression among imported products.

As used herein, the term "country of origin" refers to an area in which the product has grown or has been produced, manufactured and processed, and means nationality in the case of import and export goods. The country's country of origin labeling system has been in force since July 1, 1991, and the Foreign Trade Act has regulations on “country of origin determination”, “products subject to labeling of origin”, and “penalties for violations”. The Customs Act establishes and operates regulations regarding verification of the country of origin and labeling at the time of customs clearance, and crackdowns in the distribution process on the market.

The term "sesame" as used herein is a perennial plant of the sesame family, or its seeds. It is an annual plant native to Western Asia, and is a paid crop widely distributed in East Asia, North America, and Africa, including Korea. Sesame seeds are divided into black sesame, white sesame, and pressed sesame according to their color, and classified according to their characteristics. Sesame seeds contain 45-55% fat and 36% protein, and are also high in vitamins B1 and E. Oil is edible. It is used as a seasoning by making sesame salt. It is also added to rice cakes, candy, and sweets. It is also used as a substitute for artificial butter, soap, and olive oil. Since it contains fatty oil, it is good for nutrient tonic and constipation treatment, and when combined with other herbal medicines, it is effective for recovery from weakness and illness. It is externally used for inflammation and is used as an antidote, emollient, and ointment.

The term "discrimination" as used herein means to determine and distinguish where the origin of sesame seeds is.

The term "level difference", as used herein, refers to a high or low metabolite level between groups in which a specific metabolite in sesame seeds is to be compared.

The term "biomarker for determining the origin of sesame seeds" as used herein refers to valine, L-glutathione, and 2-amino-1,3,4-octadecantriol in sesame seeds from the origin. (2-Amino-1,3,4-octadecanetriol), adenosine 5'-monophosphate (Adenosine 5'-monophosphate) and D-Raffinose metabolites were expressed to determine the level of expression of the metabolites. This means that it can be used as a biomarker that can identify the country of origin.

As biomarkers for determining the origin of sesame seeds, Valine, L-Glutathione, 2-Amino-1,3,4-octadecanetriol (2-Amino-1,3,4-octadecanetriol) ), adenosine 5'-monophosphate and D-Raffinose may be used alone or in combination of one or more.

According to a preferred embodiment of the present invention, the biomarker composition for determining the origin of sesame seeds of the present invention is a biomarker for determining the origin of sesame seeds, preferably Valine, L-Glutathione, 2 -Amino-1,3,4-octadecanetriol (2-Amino-1,3,4-octadecanetriol), adenosine 5'-monophosphate (Adenosine 5'-monophosphate) and D-Raffinose (D-Raffinose) It may include one or more selected from the group consisting of. Most preferably, it may contain all of the five types. When using a biomarker composition for determining the origin of sesame seeds containing all five species, it is possible to more accurately determine the origin of sesame seeds produced in domestic or overseas regions, preferably in China.

The biomarker for determining the origin of sesame seeds of the present invention is characterized in that it is possible to determine the origin of sesame seeds by using the difference in the frequency of expression of metabolites of sesame seeds by origin. It should be understood that the frequency of expression of the metabolite is specifically, most commonly expressed in Korea or China.

Valine, L-glutacion, 2-amino-1,3,4-octadecantriol, adenosine 5'-monophosphate, and D-rapinose can be used alone or two or more as biomarkers for determining the origin of sesame seeds. have.

More specifically, in the case of Korean sesame seeds, valine, L-glutacion, 2-amino-1,3,4-octadecantriol and adenosine 5'-monophosphate are expressed in large amounts.

In addition, in the case of Chinese sesame seeds, there is a characteristic that a large amount of D-rapinose is expressed.

Therefore, it is possible to determine the origin of sesame seeds by using them as biomarkers for determining the origin.

Accordingly, it is possible to clearly confirm the origin of sesame seeds, so that the reliability of the origin of sesame seeds can be secured, so that consumers can trust and purchase domestic sesame seeds, and producers can further activate the sesame sales market through securing reliability. There will be.

That is, the present invention has established a method and system for determining the origin of sesame seeds using metabolites as molecular markers for sesame varieties collected in Korea and abroad. According to the present invention, since domestic and imported sesame seeds can be identified, they can also be used in the country of origin labeling of agricultural products. Furthermore, it can contribute to fields such as identification of the authenticity of sesame varieties, mediation of seed disputes, and selection of control varieties for varieties applied for variety protection.

In one embodiment of the present invention, by confirming that there is no significant discrimination effect when using a biomarker composition for determining the origin of sesame seeds containing all five of the total 243 species initially identified, sesame seeds containing all five species of the present invention It was confirmed that the biomarker combination for determining the country of origin was optimal.

In addition, the composition may include a formulation capable of measuring the level of metabolites in sesame seeds, and the formulation may measure the level of each metabolite in a sesame sample produced from overseas.

In addition, according to another aspect of the present invention, the present invention provides a kit for determining the origin of sesame seeds, including the biomarker composition for determining the origin of sesame seeds described above.

The kit for determining the origin of sesame seeds of the present invention may be used to determine the origin of the sesame sample by detecting or quantitatively analyzing the metabolite from a sesame sample whose origin is suspected, but is not particularly limited thereto.

In addition, the kit for determining the origin of sesame seeds may include not only direct means for detecting metabolites, but also 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 origin of sesame seeds of the present invention is characterized in that it is possible to determine the origin of sesame seeds by quantitatively analyzing metabolites of a sample, including the above-described five or more biomarkers.

The kit of the present invention may include a microtiter plate in a conventional well form capable of carrying a sample. The well may include a porous support capable of absorbing a sample and one or more biomarkers. The support contains an internal biomarker at a predetermined concentration in preparation for the addition of the sesame metabolite extract, and each sample can be fixed. In addition, the porosity of the support may allow maximum exposure to the extraction solvent added during sample analysis.

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

Specifically, it may be a solid support. More specifically, it is composed of a material absorbing liquid. The absorbent material may be an adsorbent or an adsorbent material.

The liquid absorbent material allows the solution of the biomarker and the 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, carbohydrate substances such as agarose, agar, cellulose, dextran, chitosan, or konjac, or derivatives thereof, carnaginan, gellan, or alginate may be included. Most specifically, it may be cellulose or glass fibers.

The biomarker included in the kit of the present invention can be understood to be an absolute amount of a comparative substance with a known amount, which is used as a comparison for similar or identical analogs to quantify the amount of metabolites present in a sample. The biomarker may be labeled with an isotope to appropriately distinguish it from the metabolite of the sample.

In addition, a sample that can be used in the kit of the present invention is an extract of metabolites by origin of sesame seeds, and may be provided in the kit in the form of a liquid sample.

The method of extracting the metabolite is not particularly limited, but a solvent extraction method is preferably used. The solvent is not particularly limited as long as it can dissolve metabolites of sesame seeds. For example, as the solvent, water; Lower alcohols such as methanol, ethanol, propanol, and butanol; Acetone; Trifluoroethanol; Tetrahydrofuran; Dichloromethane; Phosphate; And a mixed solvent thereof may be used.

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

In addition, in order to widen the extraction range of metabolites, a process of homogenizing a sesame 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 and discharging method may 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 a reagent, a solvent, a software system, etc. included in a device capable of preparing various metabolites in order to quantitatively target a range of metabolites in combination with an analysis device.

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

In addition, according to another aspect of the present invention, the present invention provides a method for determining the origin of sesame seeds comprising the following steps:

(a) extracting metabolites from sesame seeds; And

(b) Among the metabolites extracted in step (a), Valine, L-Glutathione, 2-amino-1,3,4-octadecantriol (2-Amino-1) ,3,4-octadecanetriol), adenosine 5'-monophosphate (Adenosine 5'-monophosphate) and at least one metabolite selected from the group consisting of D-Raffinose was analyzed by liquid chromatography-mass spectrometry (LC -MS) analysis; And

(c) determining the origin of Korean and imported sesame seeds based on the difference in expression levels between metabolites in step (b).

Preferably, the imported product is made in China.

Preferably, the expression levels of valine, L-glutacion, 2-amino-1,3,4-octadecantriol, and adenosine 5'-monophosphate are increased in Korean production compared to imported sesame seeds.

Preferably, the expression level of D-Raffinose is increased in Chinese production compared to Korean sesame seeds.

For example, domestic sesame seeds contain a lot of substances such as valine, L-glutacion, 2-amino-1,3,4-octadecantriol, and adenosine 5'-monophosphate, but D-rapinose It contains relatively little.

When used as a biomarker of the present invention, valine, L-glutacion, 2-amino-1,3,4-octadecantriol, adenosine 5'-monophosphate and D-rapinose, which are metabolites in domestic sesame The distribution ratio is 1.53: 1.86: 1.32: 1.27: 0.53.

Chinese sesame seeds contain a lot of substances such as adenosine 5'-monophosphate and D-rapinose, but valine, L-glutacion, and 2-amino-1,3,4-octadecantriol are relatively low. Included. When used as a biomarker of the present invention, valine, L-glutacion, 2-amino-1,3,4-octadecantriol, adenosine 5'-monophosphate and D-rapinose, which are metabolites in sesame seeds from China The distribution ratio is 0.97: 0.86: 0.86: 1.01: 1.17.

Other imported sesame seeds contain a lot of substances such as D-rapinose, but compared to this, valine, L-glutacion, 2-amino-1,3,4-octadecantriol and adenosine 5'-monophosphate are relatively It contains less. When used as a biomarker of the present invention, the metabolites in imported sesame seeds, valine, L-glutacion, 2-amino-1,3,4-octadecantriol, adenosine 5'-monophosphate, and D-rapinose The distribution ratio is 0.50: 0.28: 0.81: 0.72: 1.30.

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

(1) Five metabolites showing differences in domestic and imported sesame samples (valine, L-glutacion, 2-amino-1,3,4-octadecantriol, adenosine 5'-monophosphate and D-rapi) Nose) after selection, modeling of response variables in a multivariate method using partial least prototyping (PLS-DA) for the selected metabolites;

(2) Comparison of the relative level difference using the strength of metabolites analyzed in gas chromatography and liquid chromatography;

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

(4) Metabolite biomarker analysis from sesame seeds through verification of metabolite biomarker using ROC curve (Receiver Operating Characteristic curve).

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 between metabolites by fold change and analyzing the pattern of increasing or decreasing the amount.

In the present invention, the method of measuring the level difference of metabolites in the sesame sample is a mass spectrometer, a chromatography instrument, a chromatography-mass spectrometer combined with chromatography, and nuclear magnetic resonance spectroscopy. An analysis method using instrumentation such as a Nuclear Magnetic Resonance spectrometer, a Raman spectroscopy, a light absorption analysis, and a flow injection analysis; Quantitative analysis of metabolites using specific binding between antibodies, aptamers, peptides, nucleic acids or polymers and metabolites specific to the metabolites; ELISA (enzyme linked immunosorbent asay), Western blot, radioimmunoassay (RIA), radioimmunodiffusion, Ouchterlony immune diffusion method, rocket immunoelectrophoresis, tissue immunostaining, immunity It can be performed using a method such as an Immunoprecipitation assay, a Complement Fixation Assay, a fluorescence activated cell sorter (FACS), or a microarray assay, but is not limited thereto. Preferably, liquid chromatography analysis and mass spectrometry may be used as a method of measuring the level of the metabolite.

Chromatography used in the present invention includes liquid-chromatography (LC), gas chromatography, liquid-solid chromatography (LSC), and paper chromatography. , PC), Thin-Layer Chromatography (TLC), Gas-Solid Chromatography (GSC), Liquid-Liquid Chromatography, LLC), Foam Chromatography , FC), Emulsion Chromatography (EC), Gas-Liquid Chromatography (GLC), Ion Chromatography (IC), Gel Filtration Chromatograhy (GFC) or Including gel permeation chromatography (GPC), but not limited thereto, all quantitative chromatography commonly used in the art may be used. Preferably, the chromatography used in the present invention is liquid chromatography.

Preferably, the mass spectrometer used in the present invention is a Liquid Chromatography-Mass Spectrometry (LC-MS) using liquid chromatography.

In the present invention, five kinds of metabolites having different expression levels in domestic or imported sesame samples were selected as biomarkers capable of discriminating the origin of sesame seeds, and when using them, a more consistent and highly reliable and accurate country of origin determination is possible. It was made applicable to the country of origin control.

Therefore, it was confirmed that when the method for determining the origin of sesame seeds using the biomarker for determining the origin of sesame seeds of the present invention was used, it was possible to determine the origin of sesame seeds with higher consistency and reliability. In addition, this can be applied to the control of the actual origin, and can also be applied to various agricultural products other than sesame seeds.

When the biomarker for determining the origin of sesame seeds of the present invention is used, the origin of sesame seeds can be determined by using the difference in the level of metabolites in sesame seeds. The biomarker of the present invention can be used as an important tool to crack down on acts of deceiting the country of origin and taking unreasonable profits by being used for actual crackdown, which can contribute to establishing market order of domestically distributed agricultural products and securing consumer trust.

1 shows a PCA score plot of volatile metabolites of domestic and imported sesame seeds.
Figure 2 shows a PLS-DA score plot of volatile metabolites of domestic and imported sesame seeds.
3 shows the SAM analysis.
4 shows the PLS-DA analysis.
5 shows the ROC analysis.
6 shows the FT-IR spectrum according to the presence or absence of liquid nitrogen during pretreatment of a sesame sample; (A) Stack of each spectrum (B) Overlay of each spectrum
7 shows the results of identifying major metabolite functional groups of sesame seeds.
FIG. 8 shows the results of PCA and PLS-DA analysis score plots (using the entire FT-IR spectrum) of sesame samples for each normalization method: (A) area normalization: a method of equalizing the area of the FT-IR peak; (B) min-max normalization: a method of setting the minimum point of the FT-IR peak to 0 and the maximum point to 1; (C) amide normalization: a method of normalizing based on the amide I peak among the FT-IR peaks; (D) vector first order normalization: a method of normalizing the FT-IR peak to Euclidean norm after first differentiation; (E) Vector second order normalization: A method of normalizing the FT-IR peak to the Euclidean norm after second derivative.
9 is a plot of (A) PCA, (B) PLS-DA and (C) OPLS-DA analysis score of sesame samples (using FT-IR sepctrum 1 region (CH stretching region, 3,050-2,800 cm-1)) results Show
10 shows the NMR spectrum of the water-soluble component (A) and the fat-soluble component (B) in sesame seeds extracted by the single extraction method and the Bligh & Dyer extraction method.
11 shows a 1H NMR spectrum for a sesame sample.
Figure 12 is (A) PLS score plot of sesame seeds from Korea and China, (B) permutation results of the predicted PLS-DA model for determining the origin of sesame seeds from Korea and China, (C) OPLS- for determining the origin of sesame seeds from Korea and China. DA score plot, (D) permutation results of the OPLS-DA model for determining the origin of sesame seeds from Korea and China, and (E) HCA results of sesame seeds from Korea and China.
13 shows (A) separation of five regions in Korea, (B) PCA score plot for determining the origin of sesame seeds in Korea, (C) PLS-DA score plot for determining the origin of sesame seeds in Korea, (D) It shows the permutation result of the predicted PLS-DA model for determining the origin.
Figure 14 is (A) separated into three regions of China, (B) PCA score plot for determining the origin of sesame seeds in China, (C) PLS-DA score plot for determining the origin of sesame seeds in China, (D) sesame seeds in China The permutation result of the predicted PLS-DA model for determining the origin of

Hereinafter, the present invention will be described in more detail based on examples. The examples are only for describing 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. Analysis of volatile metabolites in sesame samples

1-1. Extraction of volatile metabolites from sesame seeds

In order to analyze the volatile metabolites in sesame samples, the present inventors were provided with those produced in 2018 from the National Agricultural Products Quality Management Agency for sesame samples from 27 regions produced in Korea, and 6 species from China and 6 additional imported products (Ethiopia). 1 type of acid, 2 types of Nigeria, 1 type of Pakistan, 1 type of India and 1 type of additional purchase from China) were purchased and used. Sesame seeds produced in Hwawon-myeon, Haenam-gun, Jeollanam-do in 2018 were used as the QC sample. All samples used in the analysis were dried in a dry oven at 50℃ for 24 hours to reduce experimental errors due to moisture during pretreatment such as storage, roasting, extraction, etc., and then used after adjusting the moisture content to less than 2.5%.

In a 20 mL vial for SPME, 4.0 g of sesame seeds were put and sealed with a crimp cap. Roasted at 180°C for 10 minutes in MPS attached to GC/MS, and proceeded as a set of 6 vials to increase reproducibility. In order to ensure the reproducibility of the daily SPME method, the error was corrected by analyzing one QC sample for every four samples, and the QC sample was performed as an exception, a set of one vial. Samples roasted at 180°C were cooled in a refrigerator at 1±2°C for 15 minutes, and then 6 μL of each of 100 mg/L of internal standards was added using a 10 μL syringe. Internal standards include ethyl 2-methyl butyrate (CAS 7452-79-1, Sigma-Aldrich, St. Louis, MO, USA) and methyl salicylate (CAS 119- 36-8, Sigma-Aldrich) was used, and methanol was used as the solvent. DVB/CAR/PDMS SPME fiber (Supelco) was used to adsorb the volatile components of the sample contained in the vial. In order to collect the volatile components of the sample, a 20 mL vial containing the sample was stirred at 65°C for 10 minutes at 250 rpm to equilibrate, and then the volatile components were adsorbed for 30 minutes and desorbed at 230°C for 5 minutes.

1-2. Gas chromatography analysis of sesame seeds

lheim an der Ruhr, Germany)를 이용해 기체 크로마토그래피에 주입하였다. 기체 크로마토 그래피는 7890B GC system (Agilent Technologies, Wilmington, DE)과 HP-5MS (length 30m × inner diameter 0.250mm × film thickness 0.25 μm, Agilent Technologies)를 사용 하였다. Oven은 40℃에서 3분간 유지하고, 280℃까지 4℃/min으로 온도를 높여 63분간 분석하였다. 이동상 기체는 헬륨(helium)을 사용하여 0.8 mL/min로 흐르게 하였고, splitless mode로 설정하였다.The present inventors used Multi-Purpose Sampler (MPS, Gerstel, M) for the sample of Example 1-1 to detect metabolites in samples extracted from sesame seeds.

lheim an der Ruhr, Germany) was injected into gas chromatography. Gas chromatography was performed using a 7890B GC system (Agilent Technologies, Wilmington, DE) and HP-5MS (length 30m × inner diameter 0.250mm × film thickness 0.25 μm, Agilent Technologies). Oven was maintained at 40℃ for 3 minutes, and the temperature was increased to 280℃ at 4℃/min and analyzed for 63 minutes. The mobile phase gas was flowed at 0.8 mL/min using helium, and the splitless mode was set.

1-3. Mass spectrometry analysis

The present inventors performed mass spectrometry using a mass spectrometer to detect metabolites in samples extracted from sesame seeds. A 5977A MSD (Agilent Technologies) mass spectrometer was used for mass analysis, and mass spectra of metabolites were obtained at a rate of 4.5 spectra per second in the mass range of 35-350 m/z, and electron impact ionization was 70 eV. It was implemented with.

1-4. Metabolite qualitative and statistical analysis

The present inventors analyzed metabolites qualitatively and statistically.

Volatile metabolites of sesame seeds extracted by the SPME method were analyzed non-targeted, and mass profiler professional software (MPP, Agilent Technologies) was used. Using saturated alkanes C7~C30 (1 mg/mL in hexane) diluted in hexane as an external standard, the RI (Retention Index) of each volatile component was calculated and compared with the RI values in the literature. For all analyzed volatile metabolites, the RT (Retention Time) values were corrected based on the internal standards ethyl 2-methyl butyrate (100 mg/L) and methyl salicylate (100 mg/L). Multivariate statistical analysis was performed using the data extracted from MPP using SIMCA P+ software (SIMCA-P version 11.0, Umetrics, Umea, Sweden).

As a result, as shown in FIG. 1, the difference between domestic (blue) and imported (red) sesame samples was clearly confirmed through principal component analysis (PCA).

In addition, as shown in Figure 2, through partial least squares discriminant analysis (PLS-DA) it was clearly confirmed the difference between domestic and imported sesame samples.

In addition, by obtaining a Variable Important Plot (VIP) list through PLS-DA analysis, extracting the main peaks affecting the classification of PLS component 1 and PLS component 2, calculating RI, and comparing it with RI in the literature. The main components were analyzed, and a VIP (Variable Important Plot) list (>1.0) of the sesame volatile metabolite PLS-DA component1 is shown in Table 1, and the VIP list of the sesame volatile metabolite PLS-DA component2 ( >1.0).

As a result, as shown in Tables 1 and 2 below, only volatile metabolites with a VIP of 1.0 or more were selected and analyzed. As VIPs for PLS-DA component 1, 1 alcohol, 7 aldehydes, 1 ester, 3 hydrocarbons, 2 ketones, 1 fatty acid, and 1 phenol component were identified. As VIPs for PLS-DA component 2, 1 alcohol, 8 aldehydes, 1 ester, 3 hydrocarbons , 2 ketones, 1 fatty acid, 1 furan, and 1 phenol were identified.

Example 2. Discovery of specific indicators of origin in sesame samples using LC-MS

2-1. LC-MS analysis of sesame seeds

The present inventors analyzed the secondary metabolites of sesame seeds using LC-Orbitrap MS, and identified a total of 138 metabolites as a result of the data process.

2-2. Univariate statistics

The present inventors statistically verify the change of metabolites when comparing domestic and foreign products using Student's T-Test, and a list of metabolites that change significantly for each peninsula is shown in Table 3 below (Student's T-Test <0.05).

2-3. SAM (Significane Analysis for Microarrays) analysis

The present inventors compared domestic and imported products through a SAM (Significane Analysis for Microarrays) analysis.

As a result, as shown in FIG. 3, the expression levels of four metabolites (N2-Methylguanosine, 4-Coumaric acid, Valine, L-Glutathione (reduced type)) were analyzed characteristically. In general, it was confirmed that domestic products were up-regulated compared to imported products, and imported products were down-regulated.

2-4. Supervised multivariate statistics

As a result of analyzing the supervisory multivariate statistics, the present inventors confirmed that metabolite profiles between groups were well separated when applying partial least squares-discriminant analysis (PLS-DA) as shown in FIG. (R2Y = 0.955, Q2 = 0.794).

2-5. ROC curve analysis (Receiver operating characteristic Curve analysis)

The present inventors combined various metabolites in consideration of the VIP (Variable importance) score, and as a result, as shown in FIG. 5, finally, five metabolites (D-Raffinose, L-Glutathione (reduced), Adenosine 5 '-monophosphate, Valine, 2-Amino-1,3,4-octadecanetriol) were selected. Each AUC value is 0.954.

2-6. Quantitative DB construction of metabolic features present in sesame seeds

The present inventors constructed a quantitative DB of metabolic features present in domestic and imported sesame samples. As a result, as shown in Table 4 below, a platform for profiling target substances of secondary metabolites and functional metabolites of sesame seeds was constructed through LC-MS analysis.

Metabolite name Molecular Weight Metabolite name Molecular Weight Choline 103.09966 3-Hydroxypicolinic acid 139.0269 Pyrrole-2-carboxylic acid 111.03204 Guvacoline 141.079 Cytosine 111.04327 DL-Stachydrine 143.0946 Histamine 111.0796 8-Hydroxyquinoline 145.0527 Uracil 112.02726 4-Guanidinobutyric acid 145.0851 Creatinine 113.05894 Acetylcholine 145.1103 N-Methylhydantoin 114.04294 Spermidine 145.1579 D-(+)-Proline 115.06329 Coumarin 146.0368 Betaine 117.07894 D-(-)-Glutamine 146.069 Valine 117.07894 5,6-Dimethylbenzimidazole 146.0844 L-Threonine 119.05822 L-Lysine 146.1055 4-Hydroxybenzaldehyde 122.03676 L-Glutamic acid 147.053 Nicotinamide 122.04803 Methionine 149.0511 Nicotinic acid 123.03208 7-Methyladenine 149.0701 Maltol 126.03159 N6-Methyladenine 149.0702 Phloroglucinol 126.03161 4'-Methoxyacetophenone 150.068 Dihydrothymine 128.05851 Guanine 151.0494 L-Pyroglutamic acid 129.04262 2-Phenylglycine 151.0634 Isoquinoline 129.05782 L-(-)-Arabitol 152.0684 Pipecolic acid 129.07896 D-(+)-Camphor 152.1201 Skatole 131.07352 3-Hydroxyanthranilic acid 153.0426 Leucine 131.09463 L-Histidine 155.0695 L-Norleucine 131.09467 Imidazolelactic acid 156.0535 Ornithine 132.08991 3-(2-Hydroxyethyl)indole 161.084 L-Aspartic acid 133.03738 DL-Carnitine 161.1051 Adenine 135.0545 4-Hydroxycoumarin 162.0316 Hypoxanthine 136.03854 7-Hydroxycoumarine 162.0317 3-Methoxybenzaldehyde 136.05245 4-Methoxycinnamaldehyde 162.068 Trigonelline 137.04761 Methyl cinnamate 162.068 3,4-Dihydroxybenzaldehyde 138.03166 4-Coumaric acid 164.0473 7-Methylguanine 165.0651 Indole-3-pyruvic acid 203.0581 L-Phenylalanine 165.0789 Neocuproine 208.1 Uric acid 168.0283 Valylproline 214.1318 Norharman 168.0687 Kinetin 215.0808 Pyridoxine 169.0738 N-α-L-Acetyl-arginine 216.1222 1-Methylhistidine 169.0851 (+)-ar-Turmerone 216.1515 Glycylproline 172.0847 Nootkatone 218.1671 Tryptoline 172.1001 Sinapinic acid 224.0684 DL-Arginine 174.1117 Prolylleucine 228.1474 N-Methyltryptamine 174.1157 Radicinin 236.0681 Indole-3-acetic acid 175.0633 Cytidine 243.0854 Cotinine 176.0949 Coenzyme Q1 250.1217 Esculetin 178.0265 2'-Deoxyadenosine 251.1018 Kanosamine 179.0792 Palmitoleic acid 254.2244 Caffeic acid 180.0422 Hexadecanamide 255.256 L-Tyrosine 181.0739 Indirubin 262.0742 L-threo-3-Phenylserine 181.0739 Thiamine 264.1044 L-Iditol 182.079 Adenosine 267.0966 4'-(Imidazol-1-yl)acetophenone 186.0792 Inosine 268.0806 Indole-3-acrylic acid 187.0633 Galangin 270.0526 Glycyl-L-leucine 188.1161 Υ-L-Glutamyl-L-glutamic acid 276.0957 N6,N6,N6-Trimethyl-L-lysine 188.1524 L-Saccharopine 276.132 Kynurenic acid 189.0425 α-Aspartylphenylalanine 280.1058 Methyl indole-3-acetate 189.079 2'-O-Methyladenosine 281.1123 5-Hydroxyindole-3-acetic acid 191.0583 Oleamide 281.2717 Scopoletin 192.0422 Argininosuccinic acid 290.1223 trans-3-Hydroxycotinine 192.09 9-Oxo-10(E),12(E)-octadecadienoic acid 294.2193 Isoferulic acid 194.0578 5'-S-Methyl-5'-thioadenosine 297.0895 Ferulic acid 194.0579 N2-Methylguanosine 297.1073 N3,N4-Dimethyl-L-arginine 202.1429 Diosmetin 300.0633 Isotretinoin 300.2088 N-Acetylsphingosine 341.2929 L-Glutathione (reduced) 307.0836 α-Lactose 342.116 Isorhamnetin 316.0581 Adenosine 5'-monophosphate 347.0629 2-Amino-1,3,4-octadecanetriol 317.2929 S-Adenosylhomocysteine 384.1215 15-Deoxy-Δ12,14-prostaglandin A1 318.2194 Nobiletin 402.131 Adenosine 3'5'-cyclic monophosphate 329.0524 Kuromanin 448.1003 Aflatoxin G2 330.0739 Glycerophospho-N-palmitoyl ethanolamine 453.2853 Prostaglandin B1 336.2299 Scutellarin 462.0797 18-β-Glycyrrhetinic acid 470.3394 D-Raffinose 504.1687

Example 3. FT-IR based metabolite analysis

3-1. Establishment of sesame sample preparation

In order to check the difference in spectrum depending on the use of liquid nitrogen, the present inventors were immersed in liquid nitrogen for 10 seconds, then immediately taken out, put in a grinder, pulverized for 20 seconds, and then freeze-dried. It was pulverized for 20 seconds in a grinder without using and then lyophilized and used.

3-2. Establishment of FT-IR operating conditions

By applying the ATR mode, the present inventors simplified sample pretreatment because there was no limitation in sample thickness compared to the transmission/reflection method, and improved reproducibility of the analysis by using a diamond plate, which is a solid material. Bruker's device (TENSOR27) was used and the number of scans was 32, the measurement range was 400-4,000 cm-1, and the resolution 4 cm-1 was applied. Background scan was measured before sample analysis to remove H ₂ O and CO ₂ peaks, thereby reducing background noise and increasing the ratio of the signal.

3-3. Establishment of metabolite identification method

We used OMNIC software and references to establish a metabolite identification method.

As a result, as shown in FIG. 6, there was little difference in the type and size of the peaks appearing on the spectrum according to the presence or absence of liquid nitrogen during pretreatment of the sesame sample, but liquid nitrogen was used to inhibit the enzyme action present in the sesame seeds. The pulverized sample was used in this experiment.

In addition, as shown in Figure 7, the main metabolite functional groups shown in the sesame sample are esters, amines, carboxylic acids, aromatics, phenols, etc. Appeared. By functional group, ① CH stretching region (3,050-2,800 cm-1), ② C=O stretching region (1,800-1,600 cm-1), and ③ COC stretching and CH bending region (1,600-650 cm-1). .

3-4. Data preprocessing and multivariate statistical analysis

The present inventors performed multivariate statistical analysis using SIMCA P+ and Metaboanalyst for preprocessing data for various normalization methods (area, min-max, amide, vector first order, vector second order). One of the multivariate statistical analysis methods, PCA, PLS-DA, and OPLS-DA, was used to determine whether sesame samples from Korea and China were separated.

As a result, as shown in FIG. 8, when the entire area of the FT-IR spectrum (4,000 to 400 cm-1) is used, model suitability and predictive power index, component value, and component values for PCA and PLS-DA analysis for each normalization method are used. It was confirmed that the separation of domestic and Chinese sesame samples was insufficient due to the degree of separation of observations on the score plot and inadequate validation parameters.

Accordingly, the analysis was carried out by dividing the region for each functional group. As a result, as shown in FIG. 9, PCA, PLS-DA and OPLS-DA analysis in the first functional group region (CH stretching region, 3,050-2,800 cm-1) Distribution chart on the score plot, PCA model R2X, Q2X values (0.891, 0.840), PLS-DA model R2Y, Q2Y values (0.708, 0.614) OPLS-DA model R2Y, Q2Y values (0.759, 0.641), and permutation It was confirmed that domestic and Chinese products could be separated due to the test fit.

Example 4. NMR-based metabolite analysis

4-1. Optimization of sample extraction and analysis methods for analysis of metabolites derived from sesame seeds based on NMR

The present inventors have optimized a sample extraction method and an analysis method for analysis of metabolites derived from sesame seeds based on NMR.

Briefly, as a pretreatment method for metabolite analysis of sesame seeds using NMR, sesame seeds were immersed in liquid nitrogen for 10 seconds, taken out immediately, placed in a grinder, pulverized for 20 seconds, and lyophilized for use. For the analysis of the components of water-soluble metabolites of sesame seeds, methanol and water are used as solvents to extract water-soluble components alone, and methanol, chloroform, and water are used as solvents to mix and extract water-soluble and fat-soluble components. The degree of detection of the water-soluble metabolite component was compared.

The sole extraction method was to add methanol-d (0.05% 3-(tetramethylsilyl)-propionic-2,2,3,3-d4 acid sodium salt (TSP)) and D2O in a ratio of 4:1 to 0.1 g of lyophilized sesame seeds. After vortexing for 1 minute, sonication for 10 minutes, centrifugation, the supernatant was filtered with a 0.45 μm PTFE syringe filter, and 600 μL of the filtrate was transferred to a 5 mm NMR tube.

Bligh & Dyer analysis was performed by adding 1.8 mL of a cold mixture solvent (cold mixture (CHCl3:MeOH:H2O=2:2:1) to 0.10 g of lyophilized sesame seeds and vortexing for 1 minute. After reaction at 4℃ for 1 hour, centrifugation was performed. The supernatant (hyrosoluble phase) and the lower layer (organic phase) were collected separately, and the extract was filtered through a 0.45 μm PTFE syringe filter, and the filtrate was dried with nitrogen gas in 300-500 μL increments, and when drying was completed, D2O, CDCl3 500 μL of each was added and re-dissolved, and then 500 μL was transferred to an NMR tube To prevent signal movement during NMR measurement, a buffer solution was prepared by adding potassium phosphate to D2O, and 1 N NaOD was added to the pH of D2O. Was adjusted to 6. 0.05% 3-(tetramethylsilyl)-propionic-2,2,3,3-d4 acid sodium salt (TSP) contained in the MeOD solvent is an internal standard, and is the calibration reference for NMR shift. Was used as.

4-2. Establishment of NMR operating conditions

The present inventors prevented lowering the peak sensitivity of other metabolites and improved reproducibility by forming unnecessary peaks of water contained in the sesame sample by applying the pulse sequence. As 1D 1H-NMR operating conditions, the JNM-ECZ 600R (600.17 MHz, Jeol company) instrument was used as the NMR spectometer. The sesame sample extract was measured at 298 K (25° C.). As the pulse sequence, a zqpr presaturation pulse sequence that lowers the water peak was used, and the relaxation delay was 5 seconds, 128 scans, and a spectral width of 9,024.4 Hz was applied.

4-3. Establishment of metabolite identification method

The present inventors performed a qualitative analysis of each metabolite using a metabolite library, HMDB web site, etc. constructed in the Chenomx software program. In addition, qualitative analysis of metabolites contained in sesame samples was performed by matching the chemical shift (δ), splitting pattern, integral, and expected concentration information of metabolites using the Mestrenova software program.

As a result, as shown in FIG. 10, as a result of a preliminary experiment for establishing an analysis method for sesame seeds, in the case of the water-soluble component, when comparing the spectra of the two extraction methods, the peak intensity was found to be greater when extracted alone, and in the case of the fat-soluble component There was no significant difference in number and strength.

In addition, as shown in Table 5 below, from the list of water-soluble metabolite components in sesame seeds extracted by the NMR-based single extraction method and the Bligh & Dyer extraction method (preliminary experiment results), the result of identification of the water-soluble metabolite component having a difference in peak intensity alone extraction 58 water-soluble metabolite components were detected in the method, and 64 water-soluble metabolite components were detected when the Bligh & Dyer assay was used.

Therefore, when using the Bligh & Dyer analysis method, it was confirmed that the identification of metabolite was more effective by minimizing artifacts by separating and extracting the water-soluble component and the fat-soluble component.

Therefore, in this experiment to analyze sesame metabolites by country, the Bligh & Dyer analysis method was used, and the finally established analysis method is as follows:

To 0.10 g of freeze-dried sesame seeds, 1.6 mL of cold mixture solvent (cold mixture (CHCl3:MeOH=1:1) was added and vortexed for 1 minute. After extraction with a shaker at 4℃ for 1 hour, centrifugation (10,000 Xg, 4℃) , 10 minutes), the supernatant was collected, and 400 μL of water was added to separate the layers After filtering the supernatant (hydrosoluble phase) with a 0.45 μm PTFE syringe filter, 600 μL of the filtrate was dried with nitrogen and dried. After completion, add 600 μL of 70% methanol-d (D2O:MeOD (0.05% 3-(tetramethylsilyl)-propionic-2,2,3,3-d4 acid sodium salt (TSP)), pH 6) to re-dissolve. And transferred to a 5 mm NMR tube.

As a result of analyzing the list of metabolites detected through ¹ H NMR (600MHz) of sesame seeds from Korea and China based on the final established extraction method described above, a total of 28 water-soluble metabolites were detected as shown in Table 6 and FIG. Among them, 11 kinds of amino acids (Isoleucine, Leucine, Valine, Alanine, Proline, Asparagine, Betaine, Threonine, Tyrosine, Phenylalanine, Tryptophan), 7 kinds of organic acids (Valerate, Acetate, Malate, Succinate, Ascorbate, Gallate , Formate), carbohydrates, 5 species (Glucose, Xylose, Glyerol, Sucrose, Arabinose), and 5 other species (Butyrate, Choline, Indol-3-acetate, Uridine, Trigonelline).

Compounds Bligh&Dyer (64) Sole extraction (58) Alcohol Myo-Inositol Myo-Inositol Ethanol Ethanol Ethylene glycol Ethylene glycol Amino acids 2-Aminoadipate 2-Aminoadipate 5-Hydroxytryptophan 5-Hydroxytryptophan Alanine Alanine Anserine ND Arginine Arginine Asparagine Asparagine Aspartate Aspartate Betaine Betaine Cysteine Cysteine Glutamate Glutamate Guanidoacetate Guanidoacetate Homoserine ND Isoleucine ND N-Acetylglutamate N-Acetylglutamate N-Acetylglycine N-Acetylglycine Phenylalanine Phenylalanine Proline Proline Pyroglutamate Pyroglutamate Serine ND S-Sulfocysteine S-Sulfocysteine Threonine Threonine trans-4-Hydroxy-L-proline trans-4-Hydroxy-L-proline Tryptophan Tryptophan Valine Valine Benzoic aicds Anthranilate Anthranilate Protocatechuate Protocatechuate Fatty acids 2-Hydroxy-3-methylvalerate 2-Hydroxy-3-methylvalerate 2-Octenoate 2-Octenoate 3-Hydroxy-3-methylglutarate 3-Hydroxy-3-methylglutarate Caprylate Caprylate ND Isobutyrate Imidazoles Imidazole Imidazole Urocanate Urocanate Organic acid 2-Oxoglutarate 2-Oxoglutarate Acetate Acetate cis-Aconitate cis-Aconitate Fumarate Fumarate Gallate Gallate Lactate Lactate Malate ND O-Phosphoethanolamine ND Pyruvate Pyruvate Succinate ND trans-Aconitate trans-Aconitate Purines 1,7-Dimethylxanthine 1,7-Dimethylxanthine Oxypurinol Oxypurinol Sugars Fructose Fructose Sucrose Sucrose ND Xylitol Fructose ND Sugar acids 2-Phosphoglycerate 2-Phosphoglycerate Threonate Threonate Sugar alcohols Glycerol Glycerol Glucitol ND Others 1,6-Anhydro-β-D-glucose 1,6-Anhydro-β-D-glucose 2'-Deoxyadenosine 2'-Deoxyadenosine 3,4-Dihydroxymandelate 3,4-Dihydroxymandelate Cytosine Cytosine Epicatechin ND Ethanolamine Ethanolamine Mandelate ND ND Glucarate ND Acetone ND N-Acetylglucosamine ND Acetoin Nicotinate ND O-Phosphocholine O-Phosphocholine Trigonelline Trigonelline

NO. Compound Chemical shift Assignment method Reference One Valerate 0.87(t), 1.28-1.32(m), 2.14(t) 1D Pabio Scuibba et al ., 2014 2 Butyrate 0.88(t), 2.15(t) 1D Roverto consonni et al., 2012 3 Isoleucine 0.94(t), 0.99(d) 1D Pabio Scuibba et al ., 2014
Augusta Scuibba et al ., 2014
AI Olagunju et al ., 2013 4 Leucine 0.96(t) 1D Pabio Scuibba et al ., 2014 Augusta Scuibba et al ., 2014
AI Olagunju et al ., 2013 5 Valine 0.96(d), 1.02(d), 3.60(d) 1D Pabio Scuibba et al ., 2014 Augusta Scuibba et al ., 2014
AI Olagunju et al ., 2013 6 Threonine 1.33(d), 3.60(d) 1D Hong-Seok Son et al ., 2009
Xiangyu Wu et al ., 2014 7 Alanine 1.48(d), 3.79(q) 1D Pabio Scuibba et al ., 2014
Augusta Scuibba et al ., 2014
AI Olagunju et al ., 2013
Xiangyu Wu et al ., 2014 8 Acetate 1.90(s) 1D Pabio Scuibba et al ., 2014
Augusta Scuibba et al ., 2014 9 Proline 2.01-2.07(m), 2.00-2.07(m), 2.37-2.29(m) 1D Pabio Scuibba et al ., 2014 A. I. Olagunju et al ., 2013 10 Malate 2.38(dd), 2.67(dd) 1D Pabio Scuibba et al ., 2014
Augusta Scuibba et al ., 2014
Hong-Seok Son et al ., 2009 11 Succinate 2.39(s) 1D Augusta Scuibba et al ., 2014
Xiangyu Wu et al ., 2014 12 Asparagine 2.92-2.98(m) 1D Pabio Scuibba et al ., 2014 Augusta Scuibba et al ., 2014 13 Choline 3.22(s), 3.48-3.51(m) 1D Augusta Scuibba et al ., 2014 14 Betaine 3.24(s), 3.89(s) 1D Xiangyu Wu et al ., 2014 15 Glucose 3.38-3.42(m), 3.40-3.44(m),
3.51-3.55(dd), 3.82-3.86(m) 1D Pabio Scuibba et al ., 2014
Augusta Scuibba et al ., 2014
Hong-Seok Son et al ., 2009 16 Xylose 3.41(t) 1D Pabio Scuibba et al ., 2014 17 Glycerol 3.51-3.55(m) 1D Augusta Scuibba et al ., 2014
Hong-Seok Son et al ., 2009 18 Indol-3-acetate 3.64(s) 1D Augusta Scuibba et al ., 2014 19 Ascorbate 3.70-3.76(m) 1D Pabio Scuibba et al ., 2014 20 Sucrose 3.75(t), 3.79-3.84(m), 3.81-3.85(m), 3.82-3.87(m), 4.02(t), 5.40(d) 1D Pabio Scuibba et al ., 2014
Augusta Scuibba et al ., 2014 21 Arabinose 3.77(dd), 3.80(dd), 4.00-4.04(m) 1D Xiangyu Wu et al ., 2014 22 Trigonelline 4.45(s), 9.11(s) 1D Pabio Scuibba et al ., 2014
Augusta Scuibba et al ., 2014 23 Uridine 5.88(d), 5.89(d), 7.84(d) 1D Pabio Scuibba et al ., 2014 Augusta Scuibba et al ., 2014 24 Tyrosine 6.88-6.91(m), 7.15-7.18(m) 1D Pabio Scuibba et al ., 2014
Augusta Scuibba et al ., 2014
AI Olagunju et al ., 2013 25 Gallate 7.03(s) 1D Pabio Scuibba et al ., 2014
Augusta Scuibba et al ., 2014 26 Phenylalanine 7.33(d), 7.35-7.40(m) 1D Pabio Scuibba et al ., 2014 Xiangyu Wu et al ., 2014 27 Tryptophan 7.15-7.19(m), 7.32(s),7.53(d), 7.71(d) 1D Pabio Scuibba et al ., 2014
Augusta Scuibba et al ., 2014
AI Olagunju et al ., 2013 28 Formate 8.45(s) 1D Pabio Scuibba et al ., 2014
Augusta Scuibba et al ., 2014

4-4. Multivariate statistical analysis

The present inventors performed multivariate statistical analysis using SIMCA P+ and Metaboanalyst. Separation of sesame seeds by country (Korea, China) and within countries was confirmed using PCA, PLS-DA, and OPLS-DA as a multivariate statistical analysis method.

As a result, as shown in FIG. 12, total (area) normalization was used to separate sesame seeds from Korea and China, and separation was not well performed on the PCA score plot, but separation was performed when analyzing PLS-DA and OPLS-DA. It was confirmed that it became.

In addition, as shown in FIG. 13, standard normalization was used for regional separation in Korea, and as a result of PCA and PLS-DA analysis, it was confirmed that it was divided into 5 provinces (Gangwon-do, Gyeonggi-do, Chungcheong-do, Gyeongsang-do and Jeolla-do).

In addition, as shown in Fig. 14, standard normalization was used when separating regions within China, and PCA and PLS-DA analysis results showed that the northern region, the middle region, and the south region were It was confirmed that it was divided into 3 regions.

In addition, the optimal PLS-DA model according to VIP value by applying the conditions used in the PLS-DA model (Total area normalization, Pareto scaling, 6 components) to search for major biomarkers involved in the separation of sesame metabolites from Korea and China. Was selected.

Table 7 shows PLS model parameters obtained by VIP (Variable Importance of Projection) to determine the origin of sesame seeds from Korea and China.

As a result, as shown in Table 7 below, the final biomarkers selected by designating a VIP cut-off value of 0.4 were valerate, sucrose, arabinose, proline, valine, indol-3-acetate, alanine, xylose, betaine, glucose, A total of 24 species were found: choline, tyrosine, asparagine, threonine, succinate, butyrate, malate, ascorbate, acetate, isoleucine, glycerol, leucine, trigonelline and tryptophan.

In addition, the separation by country (Korea, China) was confirmed using HCA (Hierarchical Cluster AnalysisA), and Table 8 shows a list of biomarkers for determining the origin of sesame seeds from Korea and China.

As a result, as shown in FIG. 12 below, it could be seen that sesame seeds in Korea and China were clearly separated from the HCA analysis results, but sesame seeds in Korea and China were not clearly separated.

VIP cutoff R ² Y Q ² Y R ² Y intercept Q ² Y intercept Total normalization (Pareto Scaling, 6 components) 0.2 0.915 0.821 0.335 -0.702 0.3 0.915 0.822 0.293 -0.722 0.4 0.917 0.825 0.273 -0.803 0.5 0.916 0.821 0.211 -0.801 0.7 0.903 0.813 0.221 -0.792 0.8 0.875 0.776 0.235 -0.798 0.9 0.885 0.795 0.179 -0.833 1.0 0.784 0.624 0.109 -0.78

No Compound VIP value One Valerate 2.017 2 Sucrose 1.739 3 Arbinose 1.613 4 Proline 1.328 5 Valine 1.274 6 Indol-3-acetate 1.207 7 Alanine 1.182 8 Xylose 1.095 9 Betaine 1.066 10 Glucose 1.049 11 Choline 0.984 12 Tyrosine 0.931 13 Asparagine 0.911 14 Threonine 0.910 15 Succinate 0.909 16 Butyrate 0.896 17 Malate 0.889 18 Ascorbate 0.845 19 Acetate 0.753 20 Isoleucine 0.544 21 Glycerol 0.520 22 Leucine 0.472 23 Trigonelline 0.461 24 Tryptophan 0.406

In conclusion, the sesame origin determination metabolite markers selected through the present invention can quickly and accurately determine the origin of imported sesame seeds, particularly Chinese sesame seeds, and can help prevent confusion in the distribution system of the domestic sesame industry in the future. It is believed to be the cornerstone of marker development.

Claims (9)

Valine, L-Glutathione, 2-amino-1,3,4-octadecantriol (2-Amino-1,) showing differences in expression levels by country of origin of Korean and imported sesame seeds. 3,4-octadecanetriol), adenosine 5'-monophosphate (Adenosine 5'-monophosphate) and D-Raffinose (D-Raffinose) containing at least one metabolite selected from the group consisting of, sesame origin determination bio Marker composition.
The method of claim 1,
The biomarker composition for determining the origin of sesame seeds, characterized in that the imported product is made in China.
The method of claim 1,
The expression levels of valine, L-glutacion, 2-amino-1,3,4-octadecantriol and adenosine 5'-monophosphate are increased in Korean production compared to imported sesame seeds. Biomarker composition for determining the country of origin.
The method of claim 1,
The expression level of the D-Raffinose is characterized in that the increase in Chinese production compared to the Korean sesame seeds, biomarker composition for determining the origin of sesame seeds.
A kit for determining the origin of sesame seeds, comprising the biomarker composition for determining the origin of sesame seeds of claim 1.
Method for determining the origin of sesame seeds comprising the following steps:
(a) extracting metabolites from sesame seeds;
(b) Among the metabolites extracted in step (a), Valine, L-Glutathione, 2-amino-1,3,4-octadecantriol (2-Amino-1) ,3,4-octadecanetriol), adenosine 5'-monophosphate (Adenosine 5'-monophosphate) and at least one metabolite selected from the group consisting of D-Raffinose was analyzed by liquid chromatography-mass spectrometry (LC -MS) analysis; And
(c) determining the origin of Korean and imported sesame seeds based on the difference in expression levels between metabolites in step (b).
The method of claim 6,
The method for determining the origin of sesame seeds, characterized in that the imported products are made in China.
The method of claim 6,
The expression levels of valine, L-glutacion, 2-amino-1,3,4-octadecantriol and adenosine 5'-monophosphate are increased in Korean production compared to imported sesame seeds. How to determine the country of origin.
The method of claim 6,
The expression level of the D-rapinose is characterized in that the increase in Chinese-made compared to the Korean sesame, the method for determining the origin of sesame seeds.

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