Method for identifying tortoise shell and belly shell of Chinese grass based on metabonomics

Abstract

A metabonomics-based method for identifying tortoise shells and belly shells of Chinese grass comprises the following steps: step 1, preparing a tortoise shell extract, drying tortoise shells, and crushing the tortoise shells to obtain tortoise shell powder; then adding the tortoise shell powder into water, heating for 0.5-2 hours in a water bath at 55-80 DEG C, and repeating for 1-5 times; concentrating the supernate to obtain a concentrated solution, namely a sample; and 2, metabonomics analysis: analyzing the sample by using a liquid chromatography-mass spectrometry technology. The metabonomics technology is adopted, the difference chemical components of the tortoise shells and the belly shells are clear for the first time, the first ten chemical markers with obvious difference are screened out, and a convenient, rapid, scientific and effective identification method is provided for promoting the resource utilization degree of the tortoise shells in the market and distinguishing the difference of the tortoise shells and the belly shells.

Description

Technical Field

[0001] The invention relates to a method for identifying the carapace and plastron of Chinese grass tortoise based on metabolomics, and belongs to the technical field of metabolomics. Background Art

[0002] Turtle shell is a biologically active aquatic byproduct used for both food and medicine. It consists of the carapace and plastron of turtles, a rich source of nutrients, including protein, fat, minerals, and amino acids. First recorded in the Shennong Bencao Jing (Shen Nong's Classic of Materia Medica), it was classified as a top-grade product. At the time, it was believed that only the plastron possessed nutritional and medicinal value, leading to significant waste of the carapace for a long time. It wasn't until the publication of the Chinese Pharmacopoeia that the two were considered and used as a single entity. Despite this, the plastron remains the primary component of clinical and traditional Chinese medicine, likely due to the lack of comprehensive research on its medicinal value. Chemical composition is often a key component in revealing the pharmacological mechanisms of traditional Chinese medicine. Therefore, further clarifying the chemical composition of the carapace and plastron of turtles is crucial for further research into the differences in their medicinal value, the biological mechanisms of their pharmacological effects, the full development and utilization of turtle shell resources, and the development of scientifically validated quality indicators and regulatory standards for identifying the carapace and plastron.

[0003] Untargeted metabolomics is a high-throughput metabolomics technology based on full-spectrum analysis. It can effectively analyze the distribution and quantity of chemical components in different parts of the same sample. The goal is to identify differential components and explain the causes of phenotypic differences between different tissue sites in the sample. This technology has the advantages of discovering unknown metabolites, wide detection coverage, and high sensitivity.

[0004] In summary, in order to scientifically and effectively identify the differences between the carapace and plastron, this paper uses the tortoise shell of Chinese grass turtle as the research object and uses non-metabolomics methods to identify the differential chemical components of the carapace and plastron extracts. It aims to provide certain theoretical guidance for the development and utilization of carapace resources, the provision of quality control and regulatory standards for the identification of carapace and plastron, and the basic research of its pharmacological effects. Summary of the Invention

[0005] The purpose of the present invention is to provide a method for identifying the carapace and plastron of Chinese grass turtle based on metabolomics.

[0006] To achieve the above-mentioned and other related purposes, the present invention provides a technical solution: a method for identifying the carapace and plastron of Chinese grass tortoise based on metabolomics, comprising the following steps: Step 1: Preparation of Tortoise Shell Extract The tortoise shell is dried and crushed to obtain tortoise shell powder; the tortoise shell powder is then added to water and heated in a water bath at 55-80°C for 0.5-2 hours, and repeated 1-5 times; the supernatant is concentrated to obtain a concentrate to obtain a sample; Step 2: Metabolomics analysis The samples were analyzed using liquid chromatography-mass spectrometry.

[0007] The preferred technical solution is: the sample analysis includes sample preparation, chromatographic separation and mass spectrometry detection; through data processing and peak identification and other steps, the chemical composition information is obtained, and matched, annotated and data processed with the database, and then the processed data is subjected to material classification statistics, principal component analysis, heat map analysis, orthogonal partial least squares discriminant analysis, and receiver operating characteristic curve analysis to screen and distinguish chemical markers between the carapace and plastron.

[0008] The preferred technical solution is: add the sample to the extract; grind at 35 Hz for 4 minutes, and ultrasonicate in an ice-water bath for 5 minutes; repeat the steps 2-3 times; let it stand at -40°C for 1 hour; centrifuge the sample at 4°C, 12,000 rpm, and a radius of 8.6 cm for 15 minutes; take the supernatant into a sampling bottle and test it on the machine; take an equal amount of supernatant from all samples and mix it into a QC sample for testing on the machine.

[0009] The preferred technical solution is: the extract is prepared by mixing methanol: acetonitrile: water in a volume ratio of 2: 2: 1, and contains an isotope-labeled internal standard mixture.

[0010] The preferred technical solution is: using a Vanquish ultra-high performance liquid chromatograph, the target compound is chromatographed on a Waters ACQUITY up-regulated LCBEH Amide liquid chromatography column7; the liquid chromatography phase A is an aqueous phase containing 25 mmol / L ammonium acetate and 25 mmol / L ammonia water, and the phase B is acetonitrile; the sample plate temperature is 4 °C, and the injection volume is 2 μL.

[0011] The preferred technical solution is: using a bioinformatics analysis website to perform substance classification statistics, principal component analysis and heat map analysis on the data analyzed by LC-MS.

[0012] The preferred technical solution is: using a supervised OPLS-DA model to characterize the difference between the carapace and plastron, and performing 200 permutation tests to determine whether the model has overfitting.

[0013] Due to the application of the above technical solution, the present invention has the following advantages compared with the prior art: The present invention uses metabolomics technology to clarify the differential chemical composition of the turtle carapace and plastron for the first time, and screens out the top 10 chemical markers with significant differences. In order to promote the utilization of carapace resources in the market and distinguish the differences between the carapace and plastron, a convenient, fast, scientific and effective identification method is provided. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] Figure 1ABase peak chromatograms of QC and TSE chemical components based on UHPLC-QE-MS; EIC plots of internal standard positive ions in all QC samples.

[0015] Figure 1B Base peak chromatograms of QC and TSE chemical components based on UHPLC-QE-MS; EIC graphs of internal standard negative ions in all QC samples.

[0016] Figure 1C Base peak chromatograms of QC and TSE chemical components based on UHPLC-QE-MS; EIC graphs of internal standard positive ions of blank samples and QC samples.

[0017] Figure 1D Base peak chromatograms of QC and TSE chemical components based on UHPLC-QE-MS; EIC graphs of internal standard negative ions of blank samples and QC samples.

[0018] Figure 1E Base peak chromatograms of QC and TSE chemical components based on UHPLC-QE-MS; TIC diagram of TS_C in positive ionization mode.

[0019] Figure 1F Base peak chromatograms of QC and TSE chemical components based on UHPLC-QE-MS; TIC diagram of F TS_C in negative ion mode.

[0020] Figure 1G Base peak chromatograms of QC and TSE chemical components based on UHPLC-QE-MS; TIC diagram of TS_P in positive ionization mode.

[0021] Figure 1H Base peak chromatograms of QC and TSE chemical components based on UHPLC-QE-MS; TIC diagram of TS_P in negative ion mode.

[0022] Figure 2A The distribution of chemical components of TS_C and TS_P (three replicates); the bar chart of chemical classification statistics.

[0023] Figure 2B Distribution of chemical components of TS_C and TS_P (three replicates); PCA analysis.

[0024] Figure 2C Distribution of chemical components of TS_C and TS_P (three replicates); heat map analysis (the redder the color, the higher the relative content of the chemical component, and the greener the color, the lower the relative content of the chemical component).

[0025] Figure 3A Screening of chemical markers for TS_C and TS_P; OPLS-DA diagram of TS_C and TS_P samples.

[0026] Figure 3B Screening of TS_C and TS_P chemical markers; 200 permutation test responses of the OPLS-DA prediction model.

[0027] Figure 3C Screening of TS_C and TS_P chemical markers; ROC curve analysis of chemical markers.

[0028] Figure 4 Information of the top 10 potential chemical markers between TS_C and TS_P samples. DETAILED DESCRIPTION

[0029] The following describes the implementation of the present invention through specific embodiments. People skilled in the art can easily understand other advantages and effects of the present invention from the contents disclosed in these embodiments.

[0030] See also Figure 1A-4 . It should be noted that the structures, proportions, sizes, etc. illustrated in the drawings of this specification are only used to match the contents disclosed in the specification for people familiar with this technology to understand and read, and are not used to limit the limiting conditions for the implementation of the present invention. Therefore, they have no technical substantive significance. Any modification of the structure, change in the proportional relationship or adjustment of the size. The following examples are provided for a better understanding of the present invention, but are not intended to limit the present invention. The experimental methods in the following examples are all conventional methods unless otherwise specified. The experimental materials used in the following examples are all purchased from conventional biochemical reagent stores unless otherwise specified.

[0031] Unless otherwise specified, the reagents or materials described in the following examples are commercially available.

[0032] The technical solution of the present invention is further described in detail below with reference to examples.

[0033] Example 1: A method for identifying the carapace and plastron of Chinese tortoises based on metabolomics The chemical components of TS_C and TS_P were identified and analyzed using LC-MS: 20 mg of sample was weighed and added to 1000 μL of extraction solution (methanol:acetonitrile:water = 2:2:1 (v / v) containing an isotopically labeled internal standard mixture); the sample was ground at 35 Hz for 4 minutes and sonicated for 5 minutes in an ice-water bath; steps 2 and 3 were repeated; the sample was allowed to stand at -40°C for 1 hour; the sample was centrifuged at 12,000 rpm (13,800 × g, radius 8.6 cm) at 4°C for 15 minutes; the supernatant was transferred to an injection vial for analysis; an equal amount of supernatant from all samples was combined to form a QC sample for analysis. The target compounds were separated using a Vanquish (Thermo Fisher Scientific) ultra-high performance liquid chromatograph on a Waters ACQUITY Up-regulated LCBEHAmide (2.1 mm × 100 mm, 1.7 μm) column. Phase A of the liquid chromatography system consisted of an aqueous phase containing 25 mmol / L ammonium acetate and 25 mmol / L ammonia, and phase B consisted of acetonitrile. The sample tray temperature was 4°C, and the injection volume was 2 μL. A Thermo Q Exactive HFX mass spectrometer was used for primary and secondary mass spectrometry data acquisition under the control of Xcalibur software (Thermo). Detailed parameters were as follows: sheath gas flow rate: 30 Arb, aux gas flow rate: 25 Arb, capillary temperature: 350°C, full MS resolution: 120,000, MS / MS resolution: 7500, collision energy: 10 / 30 / 60 in NCE mode, and spray voltage: 3.6 kV (positive) or -3.2 kV (negative). Subsequently, the raw data were converted into mzXML format using ProteoWizard software, and then processed using a self-written R package (with XCMS as the kernel) for peak identification, peak extraction, peak alignment, and integration. They were then matched with the self-built secondary mass spectrometry database of BiotreeDB (V2.1) for substance annotation, and the cutoff value of the algorithm score was set to 0.3.

[0034] The results are as follows Figure 1B 、 Figure 1C 、 Figure 1D and Figure 1EIt shows that in positive and negative ionization modes, TS_C and TS_P contain rich chromatographic peaks, including multiple chemical components, and have good chromatographic spectra, which are suitable for subsequent comprehensive characterization of chemical components. At the same time, the mass spectrometric behavior of the blank and QC sample internal standard is as follows Figure 1A and Figure 1B As shown, in the positive and negative ion modes, no obvious peaks were detected for all internal standards in all blank samples, indicating that the substance residue control was good and the cross-contamination between samples was within a controllable range. In addition, the retention time and response intensity of the internal standards in the QC samples were very stable, indicating that the instrument data acquisition stability was very good.

[0035] Example 2: The bioinformatics analysis website https: / / cloud.metware.cn / # / tools / tool-list was used to perform substance classification statistics, principal component analysis (PCA) and heat map analysis on the data analyzed by LC-MS.

[0036] As shown in Figure 2A, we detected a total of 935 metabolites, which were divided into 15 categories. The order of the number of metabolites of different types was as follows: amino acids, peptides and their analogs (219) > organic heterocyclic compounds (207) > lipids (128) > organic oxygen compounds (83) > benzenes (81) > organic acids and their derivatives (51) > phenylpropanoids and polyketides (43) > alkaloids and their derivatives (32) > organic nitrogen compounds (21) = nucleotides and their analogs (21) > terpenes (18) > lignans, neolignans and their related compounds (10) > coumarin (4) = vitamins (4). Among them, 893 and 906 metabolites were detected in TS_C and TS_P samples, respectively. The distribution of metabolites of different types was similar in both samples, with amino acids, peptides and their analogs, organic heterocyclic compounds and lipids as the main chemical components.

[0037] However, there are obvious differences in the distribution of different single compounds between TS_C and TS_P, such as Figure 2B As shown in Figure 2C, Figure 2B shows that the cumulative variance contribution of PC1 and PC2 reached 80.75%, indicating that the first and second principal components can reflect the majority of the original data information. Furthermore, TS_C and TS_P are clearly separated, indicating significant differences in carapace and plastron metabolites. Furthermore, all samples are closely clustered and partially overlap, demonstrating the good reproducibility and stability of this analytical method.

[0038] Figure 2C shows that the relative contents of TS_C and TS_P metabolites differed significantly, forming two clusters. The relative contents of metabolites in Cluster 1 were highest in the TS_C group, while those in Cluster 2 were higher in the TS_P group. This further demonstrates significant differences in the chemical composition of the carapace and plastron. Furthermore, different biological replicates clustered into the same cluster, demonstrating good homogeneity between biological replicates and the reliability of the data.

[0039] Example 3: Orthogonal partial least squares discriminant analysis (OPLS-DA) was performed 200 times to avoid overfitting. Using VIP > 1, P < 0.05, and FC > 2 or < 0.05 as criteria, the top ten chemical markers were selected based on MS2 scores > 0.75, AUC (receiver operating characteristic curve analysis) > 0.8, and VIP values.

[0040] In order to further screen out the differential chemical markers in TS_C and TS_P, we used the supervised OPLS-DA model to characterize the differences between TS_C and TS_P, and performed 200 permutation tests to determine whether the model was overfitting. Figure 3 AB shows the differences between TS_C and TS_P (R 2 Y=1,Q 2 =0.989, indicating that the model has good predictive ability). The score plot and permutation test results of the OPLS-DA model were divided into two different clusters, indicating that the metabolites between the two groups were significantly different. P <0.05, and combined with the criterion of FC>2 or <0.05, the top 10 components were selected as chemical markers according to the VIP value. Figure 4 Among them, the potential chemical markers of TS_C and TS_P are mainly Squamolone, 2',6'-Dihydroxy-4'-methoxyacetophenone, N-Acetylvaline, and N-Acetylserine. The ROC curve was used to verify their credibility as chemical markers, and the AUC (area under the curve) was 1 ( Figure 3C ), suggesting that the results of using these 10 chemical components to distinguish the differences between the carapace and plastron are true and reliable, and can be used as chemical markers to distinguish the two.

[0041] Example 4: A method for identifying the carapace and plastron of Chinese tortoises based on metabolomics A method for identifying the carapace and plastron of Chinese grass turtles based on metabolomics, comprising the following steps: Step 1: Preparation of Tortoise Shell Extract The tortoise shells were dried and crushed to obtain tortoise shell powder; the tortoise shell powder was then added to water and heated in a 55°C water bath for 0.5 h, and the process was repeated once; the supernatant was concentrated to obtain a concentrate to obtain a sample; Step 2: Metabolomics analysis The samples were analyzed using liquid chromatography-mass spectrometry.

[0042] A preferred embodiment is as follows: the sample analysis includes sample preparation, chromatographic separation and mass spectrometry detection; through steps such as data processing and peak identification, information on chemical components is obtained, and matched, annotated and data processed with the database, and then the processed data is subjected to material classification statistics, principal component analysis, heat map analysis, orthogonal partial least squares discriminant analysis, and receiver operating characteristic curve analysis to screen and distinguish chemical markers between the carapace and plastron.

[0043] The preferred embodiment is as follows: add the sample to the extract; grind at 35 Hz for 4 minutes, and ultrasonicate in an ice-water bath for 5 minutes; repeat the steps twice; let it stand at -40°C for 1 hour; centrifuge the sample at 4°C, 12,000 rpm, and a radius of 8.6 cm for 15 minutes; take the supernatant into a sample injection bottle and test it on the instrument; take an equal amount of supernatant from all samples and mix it into a QC sample for testing on the instrument.

[0044] A preferred embodiment is that the extract is prepared by mixing methanol: acetonitrile: water in a volume ratio of 2: 2: 1, and contains an isotope-labeled internal standard mixture.

[0045] A preferred embodiment is as follows: using a Vanquish ultra-high performance liquid chromatograph, the target compound is chromatographed on a Waters ACQUITY up-regulated LCBEH Amide liquid chromatography column7; the liquid chromatography phase A is an aqueous phase containing 25 mmol / L ammonium acetate and 25 mmol / L ammonia water, and the phase B is acetonitrile; the sample plate temperature is 4°C, and the injection volume is 2 μL.

[0046] A preferred embodiment is to use a bioinformatics analysis website to perform substance classification statistics, principal component analysis, and heat map analysis on the data analyzed by LC-MS.

[0047] A preferred embodiment is: using a supervised OPLS-DA model to characterize the difference between the carapace and the plastron, and performing 200 permutation tests to determine whether the model has overfitting.

[0048] Example 5: A method for identifying the carapace and plastron of Chinese tortoises based on metabolomics A method for identifying the carapace and plastron of Chinese grass turtles based on metabolomics, comprising the following steps: Step 1: Preparation of Tortoise Shell Extract The tortoise shells were dried and crushed to obtain tortoise shell powder; the tortoise shell powder was then added to water and heated in an 80°C water bath for 2 hours, and repeated 5 times; the supernatant was concentrated to obtain a concentrate to obtain a sample; Step 2: Metabolomics analysis The samples were analyzed using liquid chromatography-mass spectrometry.

[0049] A preferred embodiment is as follows: the sample analysis includes sample preparation, chromatographic separation and mass spectrometry detection; through steps such as data processing and peak identification, information on chemical components is obtained, and matched, annotated and data processed with the database, and then the processed data is subjected to material classification statistics, principal component analysis, heat map analysis, orthogonal partial least squares discriminant analysis, and receiver operating characteristic curve analysis to screen and distinguish chemical markers between the carapace and plastron.

[0050] The preferred embodiment is as follows: add the sample to the extract; grind at 35 Hz for 4 minutes, and ultrasonicate in an ice-water bath for 5 minutes; repeat the steps 3 times; let it stand at -40°C for 1 hour; centrifuge the sample at 4°C, 12,000 rpm, and a radius of 8.6 cm for 15 minutes; take the supernatant into a sample injection bottle and test it on the instrument; take an equal amount of supernatant from all samples and mix it into a QC sample for testing on the instrument.

[0051] A preferred embodiment is that the extract is prepared by mixing methanol: acetonitrile: water in a volume ratio of 2: 2: 1, and contains an isotope-labeled internal standard mixture.

[0052] A preferred embodiment is as follows: using a Vanquish ultra-high performance liquid chromatograph, the target compound is chromatographed on a Waters ACQUITY up-regulated LCBEH Amide liquid chromatography column7; the liquid chromatography phase A is an aqueous phase containing 25 mmol / L ammonium acetate and 25 mmol / L ammonia water, and the phase B is acetonitrile; the sample plate temperature is 4°C, and the injection volume is 2 μL.

[0053] A preferred embodiment is to use a bioinformatics analysis website to perform substance classification statistics, principal component analysis, and heat map analysis on the data analyzed by LC-MS.

[0054] A preferred embodiment is: using a supervised OPLS-DA model to characterize the difference between the carapace and the plastron, and performing 200 permutation tests to determine whether the model has overfitting.

[0055] The above description is only used to explain the preferred embodiments of the present invention and is not intended to limit the present invention in any form. Therefore, any modifications or changes made to the present invention under the same inventive spirit should still be included in the scope of protection intended by the present invention.

Claims

1. A method for identifying the carapace and plastron of Chinese tortoise based on metabolomics. Features: The following steps are involved: Step 1: Preparation of tortoise shell extract The tortoise shell is dried and crushed to obtain tortoise shell powder; the tortoise shell powder is then added to water, heated in a 55-80° C. water bath for 0.5-2 h, and repeated 1-5 times; the supernatant is concentrated to obtain a concentrated solution to obtain a sample; Step 2: Metabolomics analysis The samples were analyzed using liquid chromatography-mass spectrometry.

2. The method for identifying the carapace and plastron of Chinese tortoise based on metabolomics according to claim 1, Features: The sample analysis includes sample preparation, chromatographic separation and mass spectrometry detection; through data processing and peak identification and other steps, the information of chemical composition is obtained, and the data is matched, annotated and processed with the database, and then the processed data is subjected to material classification statistics, principal component analysis, heat map analysis, orthogonal partial least squares discriminant analysis, and receiver operating characteristic curve analysis to screen and distinguish chemical markers between the carapace and the plastron.

3. The method for identifying the carapace and plastron of Chinese tortoise based on metabolomics according to claim 2, Features: Add the sample to the extract; grind at 35 Hz for 4 min, and ultrasonicate in an ice-water bath for 5 min; repeat the steps 2-3 times; let stand at -40 ℃ for 1 h; centrifuge the sample at 4 ℃, 12000 rpm, radius 8.6 cm; for 15 min; take the supernatant into the injection bottle and test it on the machine; take an equal amount of supernatant from all samples and mix them into QC samples for test on the machine.

4. The method for identifying the carapace and plastron of Chinese tortoise based on metabolomics according to claim 3, Features: The extract was prepared by mixing methanol: acetonitrile: water in a volume ratio of 2: 2: 1, containing an isotope-labeled internal standard mixture.

5. The method for identifying the carapace and plastron of Chinese tortoise based on metabolomics according to claim 3, Features: The target compound was chromatographed on a Vanquish ultra-high performance liquid chromatograph using a Waters ACQUITY Up-regulated LCBEH Amide liquid chromatography column7; the liquid chromatography phase A was aqueous phase containing 25 mmol / L ammonium acetate and 25 mmol / L ammonia water, and the phase B was acetonitrile; the sample plate temperature was 4 °C, and the injection volume was 2 μL.

6. The method for identifying the carapace and plastron of Chinese tortoise based on metabolomics according to claim 2, Features: The bioinformatics analysis website was used to perform substance classification statistics, principal component analysis and heat map analysis on the LC-MS analysis data.

7. The method for identifying the carapace and plastron of Chinese tortoise based on metabolomics according to claim 2, Features: A supervised OPLS-DA model was used to characterize the difference between the carapace and the plastron, and 200 permutation tests were performed to determine whether the model was overfitting.

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