UPLC-QEO / MS-based non-targeted metabonomics and lipidomics method for analyzing characteristic fingerprints of six syngnathus

Abstract

The invention discloses a method for analyzing six pipefish characteristic fingerprints based on UPLC-QEO / MS. The method comprises the following steps: adding a pipefish sample into a methanol-acetonitrile-aqueous solution, uniformly mixing, carrying out ultrasonic treatment in an ice-water bath, standing at low temperature, and centrifuging to obtain a supernatant as a metabolite; the method comprises the following steps: adding water and a methyl tertiary butyl ether-methanol lipid extracting solution into a syngnathus sample, mixing, carrying out ultrasonic homogenization in an ice-water bath, taking supernate, carrying out vacuum drying, redissolving with methanol, carrying out ultrasonic treatment in the ice-water bath, and centrifuging to obtain supernate, namely lipid; analyzing the metabolite by adopting a UPLC-QEO / MS (Ultra Performance Liquid Chromatography-Quadrature Emission Oscillator / Mass Spectrometry) chromatographic technology, detecting the metabolite type of the And analyzing the lipid by adopting a UPLC-QEO / MS (Ultra Performance Liquid Chromatography-Quadrature Emission Oscillation / Mass Spectrometry) chromatographic technology, detecting the lipid composition of the syngnathus, the method has the characteristics of accurately and comprehensively analyzing construction of the syngnathus fingerprint spectrum and species identification.

Description

Technical Field

[0001] The invention relates to a method for analyzing sea dragons, in particular to a method for analyzing characteristic fingerprints of six sea dragons based on non-targeted metabolomics and lipidomics of UPLC-QEO / MS. Background Art

[0002] Syngnathus is a group of small marine fish belonging to the family Syngnathidae. It is not only an aquatic economic animal but also an animal-derived Chinese medicine with great medicinal value. It is known as the "animal ginseng". It is rich in high-quality protein, minerals, polyunsaturated fatty acids (PUFAs) and other bioactive substances. It has significant advantages in anti-inflammatory, anti-fatigue, anti-cancer, and improving cardiovascular diseases. At present, due to the scarcity of wild resources, sea dragons are mainly from captive breeding. The main species are: Sharp sea dragon (SH), Sharp sea dragon (SL), Pseudo sea dragon (SB), Six-horned Sharp sea dragon (HSH), Four-horned Pseudo sea dragon (QSB), Small sea dragon (SE), etc.

[0003] With the rapid development of modern identification technology, omics technology has shown surprisingly high precision and high throughput in biomarker discovery, clinical research and toxicology compared with traditional identification technology. As an unbiased technology, non-targeted metabolomics can simultaneously conduct a comprehensive and systematic analysis of endogenous metabolites in an organism, but its sensitivity and qualitative and quantitative accuracy are poor. Lipidomics is a branch of metabolomics. Based on the complexity of lipids, it can simultaneously identify and quantify a large number of lipids and accurately and comprehensively provide full-fat information spectra of biological samples under different physiological conditions. However, due to the complex chemical composition of sea dragons, a single analytical method is difficult to fully reflect its composition.

[0004] Currently, the integration of metabolomics and lipidomics is becoming an emerging research strategy to provide a more complete fingerprint. However, the existing technology has not yet found that this method can be used to construct the fingerprint of sea dragons and identify species, and there is still no accurate and comprehensive detection method for the material composition of sea dragons and the composition differences between species. Summary of the invention

[0005] The purpose of the present invention is to provide a method for analyzing the characteristic fingerprints of six sea dragons based on non-targeted metabolomics and lipidomics of UPLC-QEO / MS. The present invention has the characteristics of accurate and comprehensive analysis of the construction of sea dragon fingerprints and species identification.

[0006] The technical solution of the present invention is a method for analyzing the characteristic fingerprints of six sea dragons based on non-targeted metabolomics and lipidomics of UPLC-QEO / MS, comprising the following steps:

[0007] S1. Sample extraction:

[0008] 1) Metabolite extraction:

[0009] a. Take a sea dragon sample and add it to a methanol-acetonitrile-water extraction solution with a volume ratio of 2:2:1 to obtain an extracted sample;

[0010] b. Vortex the extracted sample to mix evenly, and then ultrasonicate it in an ice water bath to obtain a homogenized sample;

[0011] c. Let the homogenized sample stand at low temperature, then centrifuge to obtain the supernatant, which is the metabolite;

[0012] 2) Lipid extraction:

[0013] a. Add water to the sea dragon sample to obtain a homogenous sample;

[0014] b. Add 2 to 3 times the volume of methyl tert-butyl ether-methanol lipid extract at a volume ratio of 5:1 to the homogenized sample and mix thoroughly to obtain a mixed sample;

[0015] c. Ultrasonic homogenize the mixed sample in an ice water bath, take the supernatant and vacuum dry it to obtain a dry sample;

[0016] d. Redissolve the dried sample in methanol, treat it by ultrasound in an ice-water bath, and centrifuge to obtain the supernatant, which is lipid;

[0017] S2. Non-targeted metabolomics analysis:

[0018] UPLC-QEO / MS chromatography technology was used to detect the metabolites of sea dragon and screen the differential metabolites; the chromatographic column used was an amide column, the mobile phase A was an aqueous phase containing 25mmol / L ammonium acetate and 25mmol / L ammonia, and the mobile phase B was acetonitrile;

[0019] S3. Lipidomics analysis:

[0020] UPLC-QEO / MS chromatography technology was used to detect the lipid composition of sea dragons and screen differential lipids; the chromatographic column used was a C18 chromatographic column, the mobile phase A was an acetonitrile-water solution with a volume ratio of 6:4 containing 10 mmol / L ammonium formate, and the mobile phase B was an isopropanol-acetonitrile solution with a volume ratio of 9:1 containing 10 mmol / L ammonium formate water.

[0021] In the aforementioned method for analyzing the characteristic fingerprints of six sea dragons by non-targeted metabolomics and lipidomics based on UPLC-QEO / MS, in step S1, the sea dragon sample is any one of the sea dragon, the sharp sea dragon, the pseudo-sea dragon, the six-horned sea dragon, the four-horned pseudo-sea dragon, and the small sea dragon.

[0022] In the aforementioned method for analyzing the characteristic fingerprints of six sea dragons by non-targeted metabolomics and lipidomics based on UPLC-QEO / MS, in step a of step 1), the ratio of sea dragon sample to extraction solution is (50-100) mg: (1-2) mL.

[0023] In the aforementioned method for analyzing the characteristic fingerprints of six sea dragons by non-targeted metabolomics and lipidomics based on UPLC-QEO / MS, in step b of step 1), the mixing conditions are a stirring frequency of 30 to 40 Hz and a stirring time of 3 to 5 min; and an ultrasonic treatment time of 3 to 8 min.

[0024] In the aforementioned method for analyzing the characteristic fingerprints of six sea dragons by non-targeted metabolomics and lipidomics based on UPLC-QEO / MS, in step c of step 1), the low-temperature standing temperature is -50°C to -30°C, and the standing time is 1 to 2 hours.

[0025] In the aforementioned method for analyzing the characteristic fingerprints of six sea dragons by non-targeted metabolomics and lipidomics based on UPLC-QEO / MS, in step c of step 1), the centrifugation temperature is 2-5°C, the centrifugal force is 13500-14000g, and the centrifugation time is 10-20min.

[0026] In the aforementioned method for analyzing the characteristic fingerprints of six sea dragons by non-targeted metabolomics and lipidomics based on UPLC-QEO / MS, in step c of step 2), the stirring frequency of the homogenization treatment is 30-40 Hz, the homogenization time is 3-5 min, and the ultrasonic treatment time is 3-8 min.

[0027] In the aforementioned method for analyzing the characteristic fingerprints of six sea dragons by non-targeted metabolomics and lipidomics based on UPLC-QEO / MS, in step 2) in step d, the ultrasonic treatment time is 8 to 15 minutes, the centrifugal temperature of the centrifugal treatment is 2 to 5°C, the centrifugal force is 16000 to 16500g, and the centrifugation time is 10 to 20 minutes.

[0028] In the aforementioned method for analyzing the characteristic fingerprints of six sea dragons by non-targeted metabolomics and lipidomics based on UPLC-QEO / MS, in the UPLC-QEO / MS chromatography technology in step S2 and step S3, the mass spectrometer parameters were set as follows: sheath gas flow rate of 50Arb, auxiliary gas flow rate of 15Arb, capillary temperature of 320°C, full MS resolution of 60000, MS / MS resolution of 15000, collision energy of SNCE 20 / 30 / 40, and spray voltage of 3.8kV or -3.4kV, respectively.

[0029] In the aforementioned method of analyzing the characteristic fingerprints of six sea dragons by non-targeted metabolomics and lipidomics based on UPLC-QEO / MS, PCA and PLS-DA were used in steps S2 and S3 to analyze the metabolite and lipid data of sea dragons and screen differential metabolites and lipids.

[0030] Compared with the prior art, the present invention has the following beneficial effects:

[0031] The present invention uses non-targeted metabolomics and lipidomics based on UPLC-QEO / MS to conduct a comprehensive fingerprint analysis of six sea dragons to screen the main differential metabolites and lipids in sea dragons.

[0032] Through ultra-high performance liquid chromatography-quadrupole electrospray ionization-orbitrap mass spectrometry (UPLC-QEO / MS), the molecular components of the six sea dragons were comprehensively analyzed and structurally identified, and small molecule metabolites and lipids in biological samples were detected and quantified, thereby generating an information map containing multiple molecules and effectively screening interspecies difference markers. Among them, non-targeted metabolomics was used for analysis, revealing a total of 18 categories and 2,264 metabolites, with lipids being the main differential metabolites; lipidomics was used for in-depth lipid detection and analysis, expanding the initial 412 lipids detected by non-targeted metabolomics to 2,078 lipids.

[0033] From the above multi-omics results, 47 differential metabolites and 138 differential lipids were screened out among the six species of sea dragons, including 25 polyunsaturated fatty acids (PUFAs) such as FA (18:3), TAG (18:1 / 20:4 / 20:5), LPC (22:6), TAG (16:0 / 18:2 / 20:4), and FAHFA (18:2 / 20:4).

[0034] Through mass spectrometry-based multi-omics technology, a unique fingerprint based on metabolite and lipid molecular characteristics is established for each sea dragon species, which can be used for species identification, quality control, biological research, etc., to facilitate the classification and further analysis of different sea dragon species.

[0035] The invention not only contributes to the species identification of six sea dragons, but also reveals that sea dragons have the potential to develop new functional foods.

[0036] Therefore, the present invention has the characteristics of accurate and comprehensive analysis of the construction of sea dragon fingerprint map and species identification. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] Figure 1 These are the non-targeted metabolomics TIC graphs of six sea dragons based on UPLC-QEO / MS in positive (A) and negative (B) ionization modes.

[0038] Figure 2 The following are the non-targeted metabolomics analysis diagrams of six sea dragons; (A) is the metabolic quantity diagram under positive and negative ion modes; (B) is the metabolite category and ratio diagram; (C) is the chord diagram of the metabolites of the six sea dragons; (D) is the clustered heat map of the metabolite species of the six sea dragons.

[0039] Figure 3 Figure 2 is a multivariate statistical analysis of the metabolomics of six sea dragons; (A) is the PCA score diagram of metabolites in positive ion mode; (B) is the PLS-DA score diagram of metabolites in positive ion mode; (C) is the VIP score diagram of the top 20 metabolites in positive ion mode; (D) is the PCA score diagram of metabolites in negative ion mode; (E) is the PLS-DA score diagram of metabolites in negative ion mode; (F) is the VIP score diagram of the top 20 metabolites in negative ion mode.

[0040] Figure 4 The validation graphs of the PLS-DA model in metabolomics using leave-one-out cross validation (LOOCV) and 1000 permutation tests; (A) is the positive ion mode graph; (B) is the negative ion mode graph.

[0041] Figure 5 This is the differential metabolite analysis diagram of the six sea dragons in the non-targeted metabolomics under positive ion mode; (A) is the differential metabolite quantity diagram under positive and negative ion modes; (B) is the 10 representative differential metabolites with the highest VIP values; (C) is the clustering heat map of 30 different metabolites under positive ion mode.

[0042] Figure 6 (A) is a graph of 17 differential metabolites in the negative ion mode of non-targeted metabolomics; (B) is a graph of the top 10 differential metabolites in the negative ion mode of non-targeted metabolomics.

[0043] Figure 7 These are lipidomics analysis diagrams of six sea dragon species; (A) is the TIC diagram for positive ion mode (top) and negative ion mode (bottom); (B) is a diagram of lipid types and proportions; (C) is a diagram of lipid quantities in positive and negative ion modes; (D) is a Mulkey diagram of lipid species in six sea dragon species.

[0044] Figure 8 These are multivariate statistical analysis graphs of the lipidomics of six sea dragon species; (A) is the PCA score graph of lipidomics in positive ion mode; (B) is the PLS-DA score graph of lipidomics in positive ion mode; (C) is the VIP score graph of the top 20 lipids in positive ion mode; (D) is the PCA score graph of lipidomics in negative ion mode; (E) is the PLS-DA score graph of lipidomics in negative ion mode; (F) is the VIP score graph of the top 20 lipids in negative ion mode.

[0045] Fig. 9 Validation graphs of the PLS-DA model in lipidomics using leave-one-out cross validation (LOOCV) and 1000 permutation tests; (A) is a positive ion mode graph; (B) is a negative ion mode graph.

[0046] Fig.10 Figure 2 is the differential lipid map of six sea dragon lipidomics under positive ion mode; (A) is the clustering heat map of different lipids under positive ion mode; (B) is the peak area of ​​all GLs under positive ion mode; (C) is the peak area of ​​all GPs under positive ion mode; (D) is the peak area of ​​all SPs under positive ion mode; (E) is the peak area of ​​the top 10 differential lipids under positive ion mode.

[0047] Fig.11 Figure 2 is the differential lipid map of six sea dragon lipidomics under negative ion mode; (A) is the clustering heat map of different lipids under negative ion mode; (B) is the peak area of ​​all FA under negative ion mode; (C) is the peak area of ​​all GP under negative ion mode; (D) is the peak area of ​​all SP under negative ion mode; (E) is the peak area of ​​the top 10 differential lipids under negative ion mode.

[0048] Fig.12 The figures are the analysis diagrams of all differential metabolites and PUFA in lipids of six sea dragons; (A) is the cluster heat map of n-3 polyunsaturated fatty acids; (B) is the cluster heat map of n-6 PUFA; (C) is the total peak area diagram of ALA, EPA, DHA, LA and AA; (D) is the percentage diagram of ALA, EPA, DHA, LA and AA in the total lipid peak area; (E) is the percentage diagram of different PUFA in QSB in ALA, EPA, DHA, LA and AA content. DETAILED DESCRIPTION

[0049] The present invention will be further described below in conjunction with the embodiments, but they are not intended to limit the present invention.

[0050] Example:

[0051] The method for analyzing the characteristic fingerprints of six sea dragons by non-targeted metabolomics and lipidomics based on UPLC-QEO / MS includes the following steps:

[0052] Materials and Reagents:

[0053] Dried sea dragons were purchased from Anhui Buyiyang Health Industry Co., Ltd. The six sea dragon species were sea dragons (SH), sea dragons (SL), sea dragons (SB), sea dragons (HSH), sea dragons (QSB), and sea dragons (SE). The sea dragon samples were crushed into powder and stored at 4 °C for further analysis. Methanol, acetonitrile, methyl tert-butyl ether (MTBE), ammonium formate, dichloromethane, and isopropanol were of chromatography grade and purchased from CNW Technology (Düsseldorf, Germany). Other chemicals and reagents were purchased from Merck Life Science (Darmstadt, Germany).

[0054] S1. Sample extraction:

[0055] 1) Metabolite extraction:

[0056] a. Accurately weigh 50 mg of sea dragon sample powder and add 1 mL of methanol: acetonitrile: H 2 The sample was extracted in an extraction solution with a volume ratio of 2:2:1 to O;

[0057] b. Vortex the extracted sample at a stirring frequency of 35 Hz for 4 min, and then ultrasonically treat it in an ice water bath for 5 min. Repeat the above steps three times to obtain a homogenized sample;

[0058] c. The homogenate sample was placed at -40°C for 1 hour, then centrifuged at 4°C and 13,800 g for 15 min, and the supernatant was taken as the metabolite extract for further analysis.

[0059] 2) Lipid extraction:

[0060] a. Accurately weigh 25 mg of sea dragon sample powder and add 200 μL of water to obtain a homogenous sample;

[0061] b. Add 2.5 times the volume of methyl tert-butyl ether-methanol lipid extract to the homogenized sample and mix thoroughly, wherein the volume ratio of methyl tert-butyl ether to methanol is 5:1, to obtain a mixed sample;

[0062] c. Homogenize the mixed sample at a stirring frequency of 35 Hz for 4 min, and ultrasonically treat it in an ice water bath for 5 min. Repeat this process three times, then take the supernatant and vacuum dry it to obtain a dry sample.

[0063] d. The dried sample was reconstituted with 200 μL methanol, sonicated in an ice-water bath for 10 min, and then centrifuged at 4°C and 16200 g for 15 min. 100 μL of the supernatant was taken as the lipid extract for subsequent analysis.

[0064] S2. Non-targeted metabolomics analysis:

[0065] The extracted metabolites were subjected to UPLC-QEO / MS chromatographic analysis. The UPLC chromatographic conditions were as follows: the chromatographic column was a Waters Acquity UPLC BEH amide column (2.1 mm × 50 mm, 1.7 μm), the mobile phase A was an aqueous phase containing 25 mmol / L ammonium acetate and 25 mmol / L ammonia, the mobile phase B was acetonitrile, the sample plate temperature was maintained at 4 °C, and the injection volume was 2 μL.

[0066] MS analysis was performed using an Orbitrap Exploris 120 mass spectrometer in positive and negative ion modes for metabolite detection, and data were collected by Xcalibur 4. The mass spectrometer parameters were set as follows: sheath gas flow rate was 50 Arb, auxiliary gas flow rate was 15 Arb, capillary temperature was 320 °C, full MS resolution was 60000, MS / MS resolution was 15000, collision energy was SNCE20 / 30 / 40, and spray voltage was 3.8 kV (positive) or -3.4 kV (negative), respectively.

[0067] S3. Lipidomics analysis:

[0068] The extracted lipids were subjected to UPLC-QEO / MS chromatographic analysis. The UPLC chromatographic conditions were as follows: a Phenomenex Kinetex C18 column (2.1 mm × 100 mm, 2.6 μm) was used as the chromatographic column, mobile phase A was an acetonitrile-water solution with a volume ratio of 6:4 containing 10 mmol / L ammonium formate, and mobile phase B was an isopropanol-acetonitrile solution with a volume ratio of 9:1 containing 10 mmol / L ammonium formate water.

[0069] MS analysis was performed using an Orbitrap Exploris 120 mass spectrometer in positive and negative ion modes for metabolite detection and data acquisition using an Xcalibur 4. The mass spectrometer parameters were set the same as in S2.

[0070] S4. Data analysis and processing:

[0071] The raw data files of non-targeted metabolomics and lipidomics were converted to mzXML format using the “msconvert” program of ProteoWizard software for analysis. The mass spectrometry data were corrected for retention time, peak identification, peak extraction, peak integration, and peak alignment using the CentWave algorithm in XCMS software, with minfrac set to 0.5 and cutoff set to 0.3. Metabolites of non-targeted metabolomics were characterized using the bio treedb (version 3.0) database. Lipidomic data were determined using the lipidblast database to calculate lipid (sub)classes, MS2. scores, accurate m / z, and retention times (rt).

[0072] Six replicate samples were set for each sea dragon from extraction to detection. Metabo analyst 6.0 was used to perform PCA and PLS-DA statistical analysis to process sample data. Data screening excluded features with standard deviation (SD) values ​​higher than 20%, and data scaling was set to center only. Variable importance projection (VIP) values ​​> 1 in PLS-DA analysis were considered to be contributing lipid components. Origin 2022 software, GraphPad Prism 9 software, and OmicStudio tools were mainly used to generate graphics.

[0073] S5. Results and Discussion:

[0074] For the analysis results of non-targeted metabolomics, the total ion current chromatograms in positive and negative ion modes are shown in Figure 2. Figure 1 As shown in (A) and (B) in Figure 2 As shown in (A) and (B), a total of 2264 metabolites were detected in all samples, of which 1266 were detected in positive ion mode and 998 were detected in negative ion mode. These metabolites were divided into 18 categories, mainly including fatty acids (37.97%), lipids and lipid molecules (25.77%), organic heterocyclic compounds (11.26%) and organic nitrogen compounds (5.86%). In general, fatty acids, lipids and lipid molecules and organic heterocyclic compounds were the most abundant metabolites, among which a total of 412 lipid components were detected, including 155 fatty acids and 257 lipids and lipid molecules.

[0075] The metabolite profiles of the six sea dragon species were analyzed, and the results showed that there were significant differences in the metabolic levels of the six sea dragons, such as Figure 2 (C) and (D). Among all metabolites, fatty acids, lipids and lipid molecules are the main components of the six sea dragons. This invention reveals the abundance level of sea dragon metabolites for the first time.

[0076] In order to further analyze the differences in metabolite levels among the six sea dragons, PCA and PLS-DA (VIP>1) were used to screen the key metabolites of sea dragons. Figure 3 The PLS-DA model was validated using leave-one-out cross validation (LOOCV) and 1000 permutation tests. The results showed that the model had good prediction performance. Figure 4 shown.

[0077] A total of 47 differential metabolites were screened based on VIP values ​​in positive and negative ion modes, such as Figure 5 (A) and the intensities of the top ten differential metabolites under the two modes are shown as follows Figure 5 (B) and Figure 6(B) shows the differences in metabolites and intensities of six sea dragon samples under two modes, including 30 differential metabolites in positive ion mode, see Figure 5 (C) and Table 1, and the 17 metabolites in negative ion mode, see Figure 6 (A) and Table 2.

[0078] Table 1. 30 differential metabolites in positive ion mode in non-targeted metabolomics

[0079]

[0080]

[0081] Table 2. Differential metabolites in 17 negative ion modes in non-targeted metabolomics

[0082]

[0083] As can be seen from the above, the most abundant differential metabolites in the positive ion mode are lipids and lipid-like molecules, such as LPC (16:0), glycerophosphocholine, and LPC (O-16:0 / 0:0). The most abundant differential metabolites in the negative ion mode are fatty acids. The results showed that there were significant differences in the metabolic levels of the six sea dragons, among which lipids are expected to be used as biomarkers for identifying sea dragons. However, non-targeted metabolomics has certain limitations in lipid detection, so a more comprehensive lipidomics is used to explore and analyze lipid components for more accurate marker analysis.

[0084] In order to further study the lipid differences of different types of sea dragons, this paper uses lipidomics methods to comprehensively reveal the lipid composition of sea dragons at the molecular level, solving the problem of incomplete lipid detection in previous metabolomics studies. The lipid composition of sea dragons was fully detected in positive and negative ion modes. The TIC diagram is shown in Figure 2. Figure 7 (A) As shown. The lipids in the body of the sea dragon include 6 major categories and 44 subcategories. A total of 2078 lipid molecules were detected, including 185 fatty acyl groups (FA), 9 glycolipids (SL), 9 sterol lipids (ST), 596 sphingolipids (SP), 737 glycerolipids (GL) and 492 glycerophospholipids (GP). The percentage of lipid subcategories in the total lipid content is shown in Figure 7 (B), where lipid subclasses with less than 0.1% in SP were combined in other groups. In positive ion mode, a total of 1090 lipid molecules from 21 subclasses of 5 major classes were detected; in negative ion mode, a total of 988 lipid molecules from 36 subclasses of 5 major classes were detected, such as Figure 7 (C) shown.

[0085] To further explore the differences in lipid composition among the six sea dragon species, the Sankey diagram shows the distribution of different lipid classes in sea dragons, e.g. Figure 7 (D) As shown. The results of lipidomics showed that triacylglycerol (TAG), diacylglycerol (DAG) and phosphatidylcholine (PC) were the most abundant lipid subclasses in the six sea dragons, showing significant differences. According to the above results, there are differences in lipid levels among the six sea dragons, so the distribution of lipid composition is helpful for the identification of sea dragon species.

[0086] PCA and PLS-DA were used to analyze the lipids of sea dragons. The PCA and PLS-DA results showed that there were significant differences among all six sea dragon samples, such as Figure 8 This confirms that lipid composition will help identify the species of sea dragons. To improve the reliability of the data, leave-one-out cross validation (LOOCV) and 1000 permutation tests were used to confirm that the PLS-DA model was highly predictive, and the results are shown in Fig. 9 In the positive ion and negative ion models, lipids with VIP>1 were taken as differential lipids, and the results of differential lipids are shown in Tables 3 and 4.

[0087] Table 3. 76 differential lipids in positive ion mode in lipidomics

[0088]

[0089]

[0090]

[0091]

[0092] Table 4. 62 differential lipids in negative ion mode in lipidomics

[0093]

[0094]

[0095]

[0096] A total of 76 differential lipids, including FA, ST, SP, GL, and GP, were screened in the positive ion mode. Fig.10 62 differential lipids were screened in negative ion mode, mainly including FA, SP and GP, as shown in Fig.11 It contains a variety of unsaturated fatty acids, such as α-linolenic acid, eicosapentaenoic acid, DHA, linoleic acid and arachidonic acid.

[0097] Summarizing the differential components of metabolomics and lipidomics, there are a total of 25 PUFAs, including 13 n-3PUFAs and 12 n-6PUFAs. FAHFA (20:5 / 18:2) exists in both series. The specific molecular information is shown in Table 5.

[0098] Table 5. All differential metabolites and fatty acids in lipids of the six sea dragon species

[0099]

[0100]

[0101] Polyunsaturated fatty acids (PUFA) are a class of fatty acids that are essential to human health and play an important role in regulating blood lipids, preventing cardiovascular diseases, and promoting brain development. Fig.12 A) and n-6 ​​polyunsaturated fatty acids (see Fig.12 B) show significant differences. n-3 polyunsaturated fatty acids mainly include ALA, EPA and DHA. As a marine fish, sea dragons have better advantages in EPA and DHA content. n-6 polyunsaturated fatty acids are also used as essential fatty acids, mainly composed of LA and ARA. LA is an important component of phospholipids that make up biological membranes. It is essential for maintaining normal cell membrane function and plays an important role in regulating cholesterol homeostasis. ARA plays a key role in maintaining the nervous system, regulating pancreatic islet function and improving cardiovascular disease. Under the catalysis of different enzyme systems in the body, ARA can produce important active substances such as prostaglandins, thromboxanes, prostacyclins and leukotrienes. Such as Fig.12 As shown in (C) and 12 (D), the peak intensities of the five PUFAs showed significant differences, especially the high content of each PUFA in QSB.

[0102] Based on this, QSB may have better biological activity. The relative contents of five fatty acids in QSB were calculated using the peak area method, such as Fig.12(E) As shown. The highest content in ALA is TAG (18:1 / 18:3 / 19:2), accounting for 10.15% of the total ALA. The highest content in EPA is TAG (18:1 / 20:4 / 20:5), accounting for 3.30% of the total EPA. The content of LPC (22:6) in DHA is as high as 5.78%. LA and ARA are mainly concentrated in TAGs and FAHFAs, and their total content is as high as 25% or more. The polyunsaturated fatty acids of QSB are mainly composed of TAGs and FAHFAs. TAGs were only detected in the positive ion mode, and TAGs accounted for 34 of the 76 differentiated lipids in the positive ion mode. FAHFAs were only detected in the negative ion mode, and FAHFAs accounted for 13 of the 62 differentiated lipids in the negative ion mode. Therefore, it is very important to effectively distinguish the six species of sea dragons by TAG and FAHFAs, such as TAG (18:1 / 18:3 / 19:2), TAG (18:1 / 20:4 / 20:5), TAG (16:0 / 18:2 / 20:4), FAHFAs (20:4 / 20:3) and FAHFAs (18:2 / 20:4). Therefore, sea dragons (especially QSB), as an emerging and unexplored marine organism, may have potential anti-inflammatory and cardiovascular disease regulation functions due to their rich polyunsaturated fatty acids, and are expected to become a new direction for the development of functional lipids, which will provide new resources for applications in drug development, health care and food development.

[0103] In summary, the present invention uses non-targeted metabolomics and non-targeted lipidomics for the first time to study the material composition of six sea dragons. Among them, non-targeted metabolomics screened out a total of 47 differential metabolites based on VIP values ​​(VIP>1) in positive and negative ion modes, with fatty acids, lipids and lipid-like molecules dominating. Non-targeted lipidomics further elaborated the lipid composition in the six sea dragon samples, and screened 76 and 62 differential lipids in positive and negative ion modes, respectively. In addition, the present invention found that sea dragons contain high levels of polyunsaturated fatty acids, such as TAG (18:1 / 18:3 / 19:2), FA (18:3), TAG (18:1 / 20:4 / 20:5), etc., which can be effectively used as potential markers for identifying these six sea dragons. Therefore, combining non-targeted metabolomics and lipidomics, the present invention extracts the composition characteristics of sea dragons for the first time, and realizes the effective identification of 6 sea dragons.

[0104] It should be understood that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. For those skilled in the art, the technical solutions described in the above embodiments can be modified, or some of the technical features therein can be replaced by equivalents; and all these modifications and replacements should fall within the scope of protection of the claims attached to the present invention.

Claims

1. A method for analyzing the characteristic fingerprints of six sea dragons based on non-targeted metabolomics and lipidomics using UPLC-QEO / MS, characterized by: The following steps are involved: S1. Sample extraction: 1) Metabolite extraction: a. Take a sea dragon sample and add it to a methanol-acetonitrile-water extraction solution with a volume ratio of 2:2:1 to obtain an extracted sample; b. Vortex the extracted sample to mix evenly, and then ultrasonicate it in an ice water bath to obtain a homogenized sample; c. Let the homogenized sample stand at low temperature, then centrifuge to obtain the supernatant, which is the metabolite; 2) Lipid extraction: a. Add water to the sea dragon sample to obtain a homogenous sample; b. Add 2 to 3 times the volume of methyl tert-butyl ether-methanol lipid extract at a volume ratio of 5:1 to the homogenized sample and mix thoroughly to obtain a mixed sample; c. Ultrasonic homogenize the mixed sample in an ice water bath, take the supernatant and vacuum dry it to obtain a dry sample; d. Redissolve the dried sample in methanol, treat it by ultrasound in an ice-water bath, and centrifuge to obtain the supernatant, which is lipid; S2. Non-targeted metabolomics analysis: UPLC-QEO / MS chromatography technology was used to detect the metabolites of sea dragon and screen the differential metabolites; the chromatographic column used was an amide column, the mobile phase A was an aqueous phase containing 25mmol / L ammonium acetate and 25mmol / L ammonia, and the mobile phase B was acetonitrile; S3. Lipidomics analysis: UPLC-QEO / MS chromatography technology was used to detect the lipid composition of sea dragons and screen differential lipids; the chromatographic column used was a C18 chromatographic column, the mobile phase A was an acetonitrile-water solution with a volume ratio of 6:4 containing 10 mmol / L ammonium formate, and the mobile phase B was an isopropanol-acetonitrile solution with a volume ratio of 9:1 containing 10 mmol / L ammonium formate water.

2. The method for analyzing the characteristic fingerprints of six sea dragons by non-targeted metabolomics and lipidomics based on UPLC-QEO / MS according to claim 1, characterized in that: In step S1, the sea dragon sample is any one of the sea dragon, sharp sea dragon, pseudo sea dragon, six-cornered sea dragon, four-cornered pseudo sea dragon, and small sea dragon.

3. The method for analyzing the characteristic fingerprints of six sea dragons by non-targeted metabolomics and lipidomics based on UPLC-QEO / MS according to claim 1, characterized in that: In step a of step 1), the ratio of sea dragon sample to extraction solution is (50-100) mg: (1-2) mL.

4. The method for analyzing the characteristic fingerprints of six sea dragons by non-targeted metabolomics and lipidomics based on UPLC-QEO / MS according to claim 1, characterized in that: In step b of step 1), the mixing conditions are a stirring frequency of 30 to 40 Hz, a stirring time of 3 to 5 min, and an ultrasonic treatment time of 3 to 8 min.

5. The method for analyzing the characteristic fingerprints of six sea dragons by non-targeted metabolomics and lipidomics based on UPLC-QEO / MS according to claim 1, characterized in that: In step c of step 1), the low temperature standing temperature is -50°C to -30°C, and the standing time is 1 to 2 hours.

6. The method for analyzing the characteristic fingerprints of six sea dragons by non-targeted metabolomics and lipidomics based on UPLC-QEO / MS according to claim 1, characterized in that: In step c of step 1), the centrifugal temperature is 2-5°C, the centrifugal force is 13500-14000g, and the centrifugal time is 10-20min.

7. The method for analyzing the characteristic fingerprints of six sea dragons by non-targeted metabolomics and lipidomics based on UPLC-QEO / MS according to claim 1, characterized in that: In step c of step 2), the stirring frequency of the homogenization treatment is 30 to 40 Hz, the homogenization time is 3 to 5 min, and the ultrasonic treatment time is 3 to 8 min.

8. The method for analyzing the characteristic fingerprints of six sea dragons by non-targeted metabolomics and lipidomics based on UPLC-QEO / MS according to claim 1, characterized in that: In step 2), in step d, the ultrasonic treatment time is 8 to 15 minutes, the centrifugal temperature is 2 to 5° C., the centrifugal force is 16000 to 16500 g, and the centrifugal time is 10 to 20 minutes.

9. The method for analyzing the characteristic fingerprints of six sea dragons by non-targeted metabolomics and lipidomics based on UPLC-QEO / MS according to claim 1, characterized in that: In the UPLC-QEO / MS chromatography techniques in step S2 and step S3, the mass spectrometer parameters were set as follows: sheath gas flow rate of 50 Arb, auxiliary gas flow rate of 15 Arb, capillary temperature of 320°C, full MS resolution of 60000, MS / MS resolution of 15000, collision energy of SNCE 20 / 30 / 40, and spray voltage of 3.8 kV or -3.4 kV, respectively.

10. The method for analyzing the characteristic fingerprints of six sea dragons by non-targeted metabolomics and lipidomics based on UPLC-QEO / MS according to claim 1, characterized in that: In both step S2 and step S3, PCA and PLS-DA were used to analyze the metabolite and lipid data of the sea dragon to screen for differential metabolites and lipids.

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