System for identifying wild and culture sources of chubs and application of system

Abstract

The invention relates to the field of aquatic food traceability, in particular to a system for identifying wild and culture sources of chubs and application of the system. The system comprises: a sample processing module, wherein the sample processing module is at least used for processing a chub sample to obtain original data of a polypeptide as shown in any one of SEQ ID NO.1-4, and obtaining proteome component response of a to-be-detected sample; the data processing module is at least used for importing the proteome component response of the sample to be detected into an OPLS-DA classification discriminant analysis model to obtain a score plot for discriminant analysis of subsequent sample data; and the result output module is at least used for outputting a result. The system can be effectively used for identifying wild and culture sources of silver carps, is high in stability and specificity, does not need to use a large instrument, is low in detection cost, and has a wide application prospect in the aspect of aquatic product traceability.

Description

Technical Field

[0001] This invention relates to the field of aquatic food traceability technology, specifically to a system for identifying the wild and farmed origins of silver carp and its application. Background Technology

[0002] Silver carp, an important freshwater economic fish in my country, is facing a decline in its wild population due to overfishing and habitat destruction. Meanwhile, the large-scale development of the aquaculture industry has led to confusion between wild and farmed products in the market. Following the implementation of the ten-year fishing ban in the Yangtze River basin, the need for the protection of wild silver carp resources has become increasingly urgent, and the market's demand for traceability of authentic origin information has also significantly increased. Currently, some merchants are using false "wild" labeling to inflate prices, which not only harms consumer rights but also threatens the sustainable use of fishery resources. Against this backdrop, establishing accurate and efficient technologies for identifying the wild and farmed origins of silver carp has become crucial for supporting resource protection enforcement and market supervision.

[0003] Compared to the limitations of metabolic biomarkers, which are susceptible to environmental fluctuations, protein biomarkers, with their high stability and specificity, demonstrate unique value in the field of biomarker identification. As direct products of gene expression, proteins' expression patterns better reflect the genetic and physiological characteristics of an organism's long-term adaptation to its environment, and are less prone to significant fluctuations due to short-term changes in feeding conditions. Among existing identification techniques, morphological methods rely on empirical judgment, resulting in low accuracy; isotope analysis, while reflecting food chain differences, is costly and dependent on large instruments; and while metabolomics can capture immediate physiological states, it struggles to distinguish between short-term stress and long-term adaptive differences. The maturity of proteomics technology provides a new approach to overcoming these bottlenecks. By systematically analyzing the differences in protein expression profiles between wild and farmed silver carp populations, it is hoped that a combination of biomarkers with origin-specific characteristics can be screened, laying the foundation for establishing standardized identification methods. Summary of the Invention

[0004] To address the shortcomings of existing technologies, this invention provides a system for identifying the wild and farmed origins of silver carp and its application. The specific details of this invention are as follows: In a first aspect, this invention analyzes proteins from wild and farmed silver carp using label-free quantitative proteomics. To ensure the high reliability and statistical significance of the screened differentially expressed proteins and their corresponding peptides, strict screening parameters are set. Specifically, at the protein quantification level, the Protein Group FDR (False Discovery Rate) is set to >1%; at the peptide quantification level, the Precursor FDR is set to >1%. Only peptides and their corresponding proteins that simultaneously meet these two core parameters are included in the subsequent differential analysis candidate library. Based on this, a system for identifying the wild and farmed origins of silver carp is provided. The system includes at least: Sample processing module: The sample processing module is at least used to process silver carp samples to obtain raw data of polypeptides as shown in any of SEQ ID NO. 1-4, and to obtain the proteomic component response of the sample to be tested; Data processing module: The data processing module is at least used to import the proteomic component responses of the sample to be tested into the OPLS-DA classification and discriminant analysis model to obtain a score plot for subsequent discriminant analysis of the sample data; Result output module: The result output module is used at least to output results.

[0005] Further, the specific operation of the sample processing module is as follows: pre-processing the sample to be tested for proteomics determination to obtain a polypeptide solution including at least one of the polypeptide markers described in SEQ ID NO.1-4, and determining the obtained polypeptide solution by liquid chromatography-mass spectrometry to obtain the proteomics component response of the sample to be tested.

[0006] Furthermore, the liquid chromatography conditions for determining the polypeptide solution by liquid chromatography-mass spectrometry are as follows: Column: bioZen TM Peptide PS-C18 (100 mm × 2.1 mm, 1.6 μm) (Phenomenex, Torrance, CA, USA); Column temperature: 40℃; Mobile phase A: 0.1% formic acid-acetonitrile; Mobile phase B: 0.1% formic acid-water; Mobile phase gradient: 0–2 min, 5% A; 2–27 min, 5–20% A; 27–37 min, 20–55% A; 37–39 min, 55–80% A; 39–42 min, 80% A; 42–46 min, 5% A; Flow rate: 0.25 mL / min; Injection volume: 40 μL; Washing time: 46 min; Mass spectrometry conditions: TOF scan range: 350-1500 Da; Positive ion reaction mode, GS1: 60, GS2: 50, Curtain Gas: 40, ISVF: 5500, TEM: 525, DP: 100, CE: 10.

[0007] Furthermore, the method for preparing the OPLS-DA classification and discriminant analysis model in the judgment module is as follows: S1: Protein extraction step: The muscle powder of wild and domestic grass carp samples is pretreated for proteomics analysis to obtain a polypeptide solution containing at least the polypeptide markers described in SEQ ID NO.1-4; S2: Protein detection step: The polypeptide solution obtained in step S1 is determined by liquid chromatography-mass spectrometry to obtain the liquid chromatography-mass spectrometry analysis results; S3: Import the liquid chromatography-mass spectrometry analysis results from step S2 into PEAKS Online software for database retrieval and relative quantitative analysis. The parameters are set as follows: the database is the Cyprinidae database (sourced from NCBI); the enzyme digestion method is set to Trypsin; the maximum number of missed cleavage sites is set to 2; the precursor ion mass error is 10 ppm; the fragment ion mass error is 0.02 Da; and the false positive rate (FDR) thresholds for both peptide and protein levels are set to 1%. S4: The protein identification list and normalized expression levels of each protein in all samples obtained from the PEAKS software in step S3 are used as the initial data matrix. This matrix and the corresponding wild and farmed sample grouping information are imported into the SIMCA software (MKS Umetrics AB) to obtain the OPLS-DA classification discriminant analysis model. Differential proteins are screened by comparing the OPLS-DA models of wild and farmed animals. The screening parameters are set as follows: VIP>1; in S-plot analysis, |p[corr]|>0.75; the confidence interval of the load plot knife-cut method does not include the zero point; in pairwise comparisons of OPLS-DA, the parameter change factor is >1.4 (or <0.71) and p<0.05.

[0008] Further, the discriminant analysis steps are as follows: The score plot output by the model is used for discriminant analysis of subsequent sample data. The sample region represented by the position where the subsequent data is projected onto the score plot is predicted as the growth mode of the test sample. Differential proteins are screened by comparing OPLS-DA models for wild and domesticated farming methods. The screening parameters are set as follows: VIP>1; in S-plot analysis, |p[corr]|>0.75; the confidence interval for the load plot cut-off method does not include zero; in pairwise comparisons in OPLS-DA, the parameter change factor >1.4 (or <0.71), and p<0.05.

[0009] Furthermore, the polypeptide is derived from at least one of the proteins hypothetical protein G5714_020006 and hypothetical protein cypCar_00017051.

[0010] Optionally, the polypeptides derived from hypothetical protein G5714_020006 include: AALQGLLNR (SEQ ID NO.1), LAAAFGVTR (SEQ ID NO.2), and TPFLLSGTTYADLMPHDLAR (SEQ ID NO.3).

[0011] The polypeptides derived from hypothetical protein cypCar_00017051 include: ALQASALTAWRGVK (SEQ ID NO.4).

[0012] Furthermore, the peptides described in SEQ ID NO. 1-4 are detected by peak elution time, as follows: The elution times of the peptide derived from hypothetical protein G5714_020006 were: SEQ ID NO.1 RT: 17.25 min; SEQ ID NO.2 RT: 13.78 min; SEQ ID NO.3 RT: 31.85 min.

[0013] The elution time of the peptide derived from hypothetical protein cypCar_00017051 was: SEQ ID NO.4 RT: 17.65 min.

[0014] In a second aspect, the present invention provides a method for identifying the wild and farmed origins of silver carp, the method comprising the step of using the system described above to analyze and determine the origin of the silver carp.

[0015] Furthermore, the method includes at least the following steps: S1: Protein extraction step: Perform pretreatment of the sample to be tested for proteomics analysis to obtain a protein solution comprising at least one of the polypeptides described in SEQ ID NO. 1-4: S2: Protein detection step: The protein solution obtained in step S1 is determined by liquid chromatography-mass spectrometry to obtain the liquid chromatography-mass spectrometry analysis results of any of the peptides described in SEQ ID NO.1-4; S3: Data analysis step: Import the liquid chromatography-mass spectrometry analysis results obtained in step S2 into the system to obtain the analysis results.

[0016] Furthermore, the pretreatment for proteomics assay in step S1 includes at least the step of adding trypsin to the sample protein solution for enzymatic digestion.

[0017] Furthermore, the specific operation of step S1 is as follows: S1-1: Weigh a certain amount of fish sample, homogenize it into powder, add protein extraction solution, shake to extract protein, centrifuge at high speed and low temperature, and take the supernatant. Optionally, the protein extraction solution includes 8M urea and 50mM NH4HCO3. S1-2: Add dithiothreitol to the supernatant obtained in step S1-1 and react for a certain time to obtain reaction solution 1; S1-3: Add the freshly prepared iodoacetamide solution to the reaction solution 1 obtained in step (2) which has been cooled to room temperature, and react the reaction solution 2 at room temperature in the dark; S1-4: Use a 10K filter membrane for ultrafiltration for 25-35 min to obtain reaction solution 2 in step (3), and repeatedly rinse the filter membrane with ammonium bicarbonate solution to obtain proteome solution; S1-5: Digest the proteome solution obtained in step (5) with protease solution for 16-18 hours; S1-6: Ultrafiltration is performed using a 10K membrane, and the filtrate collected from the lower layer is the polypeptide solution.

[0018] Optionally, steps S1-4 are repeated at least 3 times and the proteome solutions obtained each time are combined.

[0019] Optionally, the proteases described in S1-5 include at least one of serine protease, cysteine ​​protease, aspartic protease, metalloproteinase, threonine protease, and glutamate protease.

[0020] Furthermore, the serine protease includes at least one of trypsin, thrombin, elastase, and subtilisin; the cysteine ​​protease includes at least one of papain, bromelain, and cathepsin; the aspartic protease includes at least one of pepsin and renin; and the metalloproteinase includes at least one of collagenase, thermophilic protease, and angiotensin-converting enzyme.

[0021] In a specific embodiment of the present invention, the protease is a serine protease, preferably a trypsin.

[0022] Furthermore, the specific operation of step S2 is as follows: Detection was performed using liquid chromatography-quadrupole / time-of-flight mass spectrometry. Mobile phase A: 0.1% formic acid-acetonitrile, Mobile phase B: 0.1% formic acid-water. Mobile phase gradient: 0–2 min, 5% A; 2–27 min, 5–20% A; 27–37 min, 20–55% A; 37–39 min, 55–80% A; 39–42 min, 80% A; 42–46 min, 5% A.

[0023] Optionally, the method includes at least the following steps: (1) Weigh 1g of sample and homogenize it into powder. Add 10mL of protein extraction solution (8M urea, 50mM NH4HCO3) and shake to extract the protein. Centrifuge at 4℃ at high speed and low temperature (10000r / min). Take 400µl of the supernatant and transfer it to an EP tube. (2) Add 8µL of 1mol / L DTT to the above protein solution, shake in a water bath at 60℃, and react for 30 min; (3) Cool to room temperature, then add 5µL of freshly prepared 1mol / L IAA and react at room temperature in the dark for 1 hour; (4) Use a 10K filter membrane at 8000g for ultrafiltration for 20 minutes, rinse the upper layer of the filter membrane repeatedly with 200µL of 50mmol / L ammonium bicarbonate solution, and transfer it to a new EP tube; (5) Add 200µL of ammonium bicarbonate solution and repeat this step. Combine the solutions to complete the extraction of proteins under the membrane. (6) Use a nucleic acid protein concentration analyzer to determine the protein solution concentration, add trypsin to the protein solution at an enzyme / substrate ratio of 1:50 (w / w), mix well, and then enzymatically digest on a membrane at 37 °C for 16-18 h; (7) Use a 10K filter membrane with 8000g for ultrafiltration for 20 minutes, collect the lower layer of peptide filtrate, and wait for instrument testing.

[0024] (ii) On-machine testing, Detection was performed using liquid chromatography-quadrupole / time-of-flight mass spectrometry. Liquid chromatography conditions: Column: bioZen TM Peptide PS-C18 (100 mm × 2.1 mm, 1.6 μm) (Phenomenex, Torrance, CA, USA); Column temperature: 40℃; Mobile phase A: 0.1% formic acid-acetonitrile; Mobile phase B: 0.1% formic acid-water; Mobile phase gradient: 0–2 min, 5% A; 2–27 min, 5–20% A; 27–37 min, 20–55% A; 37–39 min, 55–80% A; 39–42 min, 80% A; 42–46 min, 5% A; Flow rate: 0.25 mL / min; Injection volume: 40 μL; Washing time: 46 min; Mass spectrometry conditions: TOF scan range: 350-1500 Da; Positive ion reaction mode, GS1: 60, GS2: 50, Curtain Gas: 40, ISVF: 5500, TEM: 525, DP: 100, CE: 10.

[0025] Using the pretreatment and liquid chromatography-mass spectrometry analysis results described above, the obtained raw data were imported into PEAKSOnline software (version 12, Bioinformatics Solutions Inc.) for database retrieval and relative quantitative analysis. The following parameters were used: the database was the Cyprinidae database (sourced from NCBI); the enzyme digestion method was set to Trypsin; the maximum number of missed cleavage sites was set to 2; the precursor ion mass error was 10 ppm; the fragment ion mass error was 0.02 Da; and the false positive rate (FDR) thresholds for both peptide and protein levels were set to 1%.

[0026] Subsequently, the protein identification list exported from PEAKS software and the normalized expression levels of each protein across all samples were used as the initial data matrix. This matrix, along with the corresponding wild- and farmed sample grouping information, was imported into SIMCA software (MKSUmetrics AB) to construct a multivariate analysis model. Before OPLS-DA modeling, the data underwent Pareto scaling preprocessing to enhance the model's stability and interpretability.

[0027] Diagram of the constructed OPLS-DA classification and discriminant analysis model.

[0028] The score plot output by the model is used for discriminant analysis of subsequent sample data. The sample region represented by the position where subsequent data is projected onto the score plot is predicted as the growth mode of the test sample.

[0029] pass R 2 X (cum) R 2 Y (cum) and Q 2 The quality of the OPLS-DA model was evaluated using parameters such as (cum). The robustness of the model was assessed using 200 permutation tests. Differential proteins were screened by comparing OPLS-DA models from wild and domesticated farming methods. The screening parameters were set as follows: VIP>1; in S-plot analysis, |p[corr]|>0.75; the confidence interval of the load plot knife-cut method did not include the zero point; in pairwise comparisons of OPLS-DA, the parameter change factor was >1.4 (or <0.71), and p<0.05.

[0030] The polypeptides from silver carp include SEQ ID NO.1-4, and the OPLS-DA model constructed in the system... R 2 X (cum) R 2 Y (cum) Q 2 The (cum) values ​​were 0.877, 0.998, and 0.764, respectively, indicating that the system has good fitting and predictive abilities. In a specific embodiment of this aspect, the evaluation results of 200 permutation tests show that... R 2 Y and Q 2 The intercepts of the regression lines are 0.996 and -0.654, respectively, and the slope of the regression lines is greater than 0, indicating that the system has good robustness.

[0031] In a third aspect, the present invention provides a kit for identifying wild and farmed silver carp, the kit comprising at least reagents for quantitative and / or qualitative detection of the polypeptides described in any one of SEQ ID NO. 1-4.

[0032] Furthermore, the kit includes at least one of a protein extraction reagent and a protein detection reagent.

[0033] Further, the protein extraction reagent includes at least one of the following: protein extraction solution, DTT (dithiothreitol), IAA (iodoacetamide), ammonium bicarbonate solution, and protease solution; the protein detection reagent includes at least one mobile phase solution. Optionally, the protease includes at least one of serine protease, cysteine ​​protease, aspartic protease, metalloproteinase, threonine protease, and glutamate protease; the serine protease includes at least one of trypsin, thrombin, elastase, and subtilisin; the cysteine ​​protease includes at least one of papain, bromelain, and cathepsin; the aspartic protease includes at least one of pepsin and renin; the metalloproteinase includes at least one of collagenase, thermophilic protease, and angiotensin-converting enzyme; the mobile phase solution includes mobile phase A comprising 0.1% formic acid-acetonitrile, and mobile phase B comprising mobile phase B: 0.1% formic acid-water.

[0034] In a specific embodiment of the present invention, the kit includes at least a lysis buffer, a reducing agent, an alkylating agent, a protease, and a buffer.

[0035] Optionally, the lysis buffer includes at least one of urea extract, SDS denaturing buffer, and Tris-HCl solution; The reducing agent includes dithiothreitol (DTT). The alkylating agent includes iodoacetamide (IAA); The protease includes at least one of trypsin, Lys-C protease, and Glu-C protease; The buffer solution includes an ammonium bicarbonate solution.

[0036] In a fourth aspect, the present invention provides the application of the system, method, or kit described herein in the preparation of products for identifying wild and farmed silver carp.

[0037] Furthermore, the method for identifying the wild and farmed sources of silver carp includes at least one of wild-farmed fish from the Huai River, wild-farmed fish from Qili Lake, and domesticated fish.

[0038] The beneficial effects of the present invention include, but are not limited to: The system disclosed in this invention for identifying the wild and farmed origins of silver carp can be effectively used to distinguish between wild and farmed silver carp. It has high stability and strong specificity, does not require the use of large instruments, has low detection costs, and has broad application prospects in the traceability of aquatic food products.

[0039] The obtained proteomic component responses were combined with data from wild-caught and farmed fish samples to form a multivariate analysis matrix. After OPLS-DA classification and discrimination, an analysis system was constructed. The OPLS-DA model constructed in this system... R 2 X (cum) R 2 Y (cum) Q 2 The (cum) values ​​were 0.877, 0.998, and 0.764, respectively, indicating that the system has good fitting and predictive abilities. In a specific embodiment of this aspect, the evaluation results of 200 permutation tests show that... R 2 Y and Q 2 The intercepts of the regression lines are 0.996 and -0.654, respectively, and the slope of the regression lines is greater than 0, indicating that the system has good robustness. Attached Figure Description

[0040] The accompanying drawings, which are included to provide a further understanding of the invention and form part of this invention, illustrate exemplary embodiments of the invention and are used to explain the invention, but do not constitute an undue limitation of the invention. In the drawings: Figure 1 This is a fingerprint analysis result of the proteome of silver carp in two standards, one wild and one farmed, in an embodiment of the present invention. In this figure, P1 is hypothetical protein G5714_020006 and P2 is hypothetical protein cypCar_00017051. Figure 2 These are proteomic chromatographic fingerprints of silver carp in wild and farmed conditions, as described in this embodiment of the invention. Figure 3 These are the proteomic mass spectrometry fingerprints of silver carp in wild and farmed conditions according to embodiments of the present invention; Figure 4 This is a diagram of the OPLS-DA classification and discriminant analysis model for wild and farmed silver carp in this embodiment of the invention; Figure 5 This is a graph showing the results of 200 permutations of the OPLS-DA model for wild and farmed silver carp in this embodiment of the invention. Figure 6 This is a schematic diagram illustrating the predictive analysis results of the wild and farmed modes of the OPLS-DA classification discriminant analysis model for the test sample in this embodiment of the invention. Detailed Implementation

[0041] The present invention is described in detail below with reference to the embodiments, but the present invention is not limited to these embodiments. Unless otherwise specified, the raw materials and catalysts in the embodiments of the present invention are all purchased through commercial channels.

[0042] Example 1: Fingerprint analysis of proteome in standards from both wild and cultured sources. Wild and farmed silver carp samples were selected from the Huai River and Qili Lake basins. Samples were taken from the upper back muscles of the silver carp, and immediately frozen at -80℃ after collection for later use. First, the samples were pretreated for proteomic analysis, as follows: (1) Weigh 1g of sample, homogenize it into powder, add 10mL of protein extraction solution (8M urea, 50mM NH4HCO3), shake to extract protein, centrifuge at high speed and low temperature (10000r / min), and transfer 400µl of supernatant to EP tube; (2) Add 8µL of 1mol / L DTT (dithiothreitol) to the above protein supernatant, shake in a water bath at 60℃, and react for 30 minutes; (3) Cool to room temperature, then add 5µL of freshly prepared 1mol / L IAA (iodoacetamide), and react at room temperature in the dark for 1 hour; (4) Use a 10K filter membrane at 8000g for ultrafiltration for 20 minutes, rinse the upper layer of the filter membrane repeatedly with 200µL of 50mmol / L ammonium bicarbonate solution, and transfer it to a new EP tube; (5) Add 200 μL of ammonium bicarbonate solution and repeat this step. Combine the solutions to complete the submembrane protein extraction and obtain the protein solution. (6) Use a nucleic acid protein concentration analyzer to determine the protein solution concentration, add trypsin to the protein solution at an enzyme / substrate ratio of 1:50 (w / w), mix well, and then enzymatically digest on a membrane at 37 °C for 16-18 h; (7) Use a 10K filter membrane with 8000g for ultrafiltration for 20 minutes, collect the lower layer of polypeptide filtrate, and wait for instrument detection.

[0043] Secondly, the protein composition of the solution was analyzed by liquid chromatography-mass spectrometry (LC-MS). The method of LC-MS is as follows: Detection was performed using liquid chromatography-quadrupole / time-of-flight mass spectrometry. Liquid chromatography conditions: Column: bioZen TM Peptide PS-C18 (100 mm × 2.1 mm, 1.6 μm) (Phenomenex, Torrance, CA, USA); Column temperature: 40℃; Mobile phase A: 0.1% formic acid-acetonitrile; Mobile phase B: 0.1% formic acid-water; Mobile phase gradient: 0–2 min, 5% A; 2–27 min, 5–20% A; 27–37 min, 20–55% A; 37–39 min, 55–80% A; 39–42 min, 80% A; 42–46 min, 5% A; Flow rate: 0.25 mL / min; Injection volume: 40 μL; Washing time: 46 min; Mass spectrometry conditions: TOF scan range: 350-1500 Da; Positive ion reaction mode, GS1: 60, GS2: 50, Curtain Gas: 40, ISVF: 5500, TEM: 525, DP: 100, CE: 10.

[0044] In proteomics analysis, quality control samples were prepared using a pooled sample method, with 100 μL of each extract taken and thoroughly mixed to serve as the quality control samples. The injection sequence and frequency of the quality control samples were arranged as follows: Before the injection sequence, the QC sample was injected three times consecutively to equilibrate the entire LC-MS system; during the sequence, a QC sample was inserted every 12 samples, for a total of 6 insertions to cover the entire injection sequence and ensure stability assessment of the entire analysis process. Simultaneously, throughout the entire injection sequence, calibration was performed using positive ion mass axis calibration solution at a frequency of once every 5 samples.

[0045] The proteome was quantitatively analyzed by mass spectrometry and statistical software, and significant differences were found between wild and farmed silver carp samples (see...). Figure 1 ), where P1 is hypothetical protein G5714_020006 and P2 is hypothetical protein cypCar_00017051.

[0046] Example 2: Chromatographic fingerprints of the proteome in wild and farmed silver carp The protein solution prepared in Example 1 was subjected to chromatographic analysis using the same method as in Example 1. Column: bioZen TM Peptide PS-C18 (100 mm × 2.1 mm, 1.6 μm) (Phenomenex, Torrance, CA, USA); Column temperature: 40℃; Mobile phase A: 0.1% formic acid-acetonitrile; Mobile phase B: 0.1% formic acid-water; Mobile phase gradient: 0–2 min, 5% A; 2–27 min, 5–20% A; 27–37 min, 20–55% A; 37–39 min, 55–80% A; 39–42 min, 80% A; 42–46 min, 5% A; Flow rate: 0.25 mL / min; Injection volume: 40 μL; Washing time: 46 min.

[0047] The results showed that the chromatographic patterns of the proteome differed significantly between the wild and farmed samples of silver carp (see...). Figure 2 ).

[0048] The elution times of each polypeptide are as follows: The elution times of the peptide derived from hypothetical protein G5714_020006 were: SEQ ID NO.1 RT: 17.25 min; SEQ ID NO.2 RT: 13.78 min; SEQ ID NO.3 RT: 31.85 min.

[0049] The elution time of the peptide derived from hypothetical protein cypCar_00017051 was: SEQ ID NO.4 RT: 17.65 min.

[0050] Example 3: Mass spectrometric fingerprints of the proteome in wild and farmed silver carp The polypeptide solution prepared in Example 1 was analyzed by mass spectrometry, using the same method and parameters as in Example 1. The results showed that the mass spectra of the polypeptides differed significantly between the wild and farmed silver carp samples (see Example 1). Figure 3 ).

[0051] Example 4: Construction of OPLS-DA models and screening of differential proteins for wild and farmed silver carp. Using the pretreatment and liquid chromatography-mass spectrometry analysis results described in Examples 1-3, the obtained raw data were imported into PEAKS Online software (version 12, Bioinformatics Solutions Inc.) for database retrieval and relative quantitative analysis. The following parameters were used: the database was the Cyprinidae database (sourced from NCBI); the enzyme digestion method was set to Trypsin, and the maximum number of missed cleavage sites was set to 2; the precursor ion mass error was 10 ppm, and the fragment ion mass error was 0.02 Da; the false positive rate (FDR) threshold for both peptide and protein levels was set to 1%. The database search results are shown in Table 1.

[0052] Table 1. Relative quantification results of peptides corresponding to differentially expressed protein markers.

[0053] Among them, KAF4099880.1 is hypothetical protein G5714_020006 and KTG43840.1 is hypothetical protein cypCar_00017051.

[0054] Subsequently, the protein identification list exported from PEAKS software and the normalized expression levels of each protein across all samples were used as the initial data matrix. This matrix, along with the corresponding wild- and farmed sample grouping information, was imported into SIMCA software (MKSUmetrics AB) to construct a multivariate analysis model. Before OPLS-DA modeling, the data underwent Pareto scaling preprocessing to enhance the model's stability and interpretability.

[0055] The constructed OPLS-DA classification and discriminant analysis model is shown in the figure. Figure 4 (Each point in the figure represents a standard sample).

[0056] The score plot output by the model is used for discriminant analysis of subsequent sample data. The sample region represented by the location where subsequent data is projected onto the score plot is predicted as the growth pattern of the test sample. R 2 X (cum) R 2 Y (cum) and Q 2 The quality of the OPLS-DA model was evaluated using parameters such as (cum). The robustness of the model was assessed using 200 permutation tests. Figure 5 As shown, differentially expressed proteins were screened by comparing OPLS-DA models of wild and domesticated animals. The screening parameters were set as follows: VIP>1; in S-plot analysis, |p[corr]|>0.75; the confidence interval of the load plot knife-cut method did not include the zero point; in pairwise comparisons of OPLS-DA, the parameter change factor was >1.4 (or <0.71) and p<0.05.

[0057] The polypeptides from silver carp include SEQ ID No. 1-4, and the constructed OPLS-DA model... R 2 X (cum) R 2 Y (cum) Q 2 The cum values ​​were 0.877, 0.998, and 0.764, respectively, indicating that the model has good fitting and predictive abilities. The evaluation results of 200 permutation tests show that... R 2 Y and Q 2 The intercepts of the regression lines are 0.996 and -0.654, respectively, and the slope of the regression lines is greater than 0, indicating that the model has good robustness.

[0058] Example 5: Sample processing and detection steps for silver carp to be tested. Three wild silver carp samples were taken for testing. The processing and analysis steps were the same as the standard sample processing steps described in Example 1, specifically including: (a) Sample pretreatment steps: (1) Weigh 1g of sample and homogenize it into powder. Add 10mL of protein extraction solution (8M urea, 50mM NH4HCO3) and shake to extract the protein. Centrifuge at 4℃ at high speed and low temperature (10000r / min). Take 400µl of the supernatant and transfer it to an EP tube. (2) Add 8µL of 1mol / L DTT to the above protein solution, shake in a water bath at 60℃, and react for 30 min; (3) Cool to room temperature, then add 5µL of freshly prepared 1mol / L IAA and react at room temperature in the dark for 1 hour; (4) Use a 10K filter membrane at 8000g for ultrafiltration for 20 minutes, rinse the upper layer of the filter membrane repeatedly with 200µL of 50mmol / L ammonium bicarbonate solution, and transfer it to a new EP tube; (5) Add 200µL of ammonium bicarbonate solution and repeat this step. Combine the solutions to complete the extraction of proteins under the membrane. (6) Use a nucleic acid protein concentration analyzer to determine the protein solution concentration, add trypsin to the protein solution at an enzyme / substrate ratio of 1:50 (w / w), mix well, and then enzymatically digest on a membrane at 37 °C for 16-18 h; (7) Use a 10K filter membrane with 8000g for ultrafiltration for 20 minutes, collect the lower layer of peptide filtrate, and wait for instrument testing.

[0059] (ii) On-machine testing, Detection was performed using liquid chromatography-quadrupole / time-of-flight mass spectrometry. Liquid chromatography conditions: Column: bioZen TM Peptide PS-C18 (100 mm × 2.1 mm, 1.6 μm) (Phenomenex, Torrance, CA, USA); Column temperature: 40℃; Mobile phase A: 0.1% formic acid-acetonitrile; Mobile phase B: 0.1% formic acid-water; Mobile phase gradient: 0–2 min, 5% A; 2–27 min, 5–20% A; 27–37 min, 20–55% A; 37–39 min, 55–80% A; 39–42 min, 80% A; 42–46 min, 5% A; Flow rate: 0.25 mL / min; Injection volume: 40 μL; Washing time: 46 min; Mass spectrometry conditions: TOF scan range: 350-1500 Da; Positive ion reaction mode, GS1: 60, GS2: 50, Curtain Gas: 40, ISVF: 5500, TEM: 525, DP: 100, CE: 10.

[0060] Using the OPLS-DA classification and discriminant analysis model for wild and farmed silver carp samples constructed in this invention, the proteomic component responses of the test samples are input into the model for predictive analysis, and the species and growth mode of the test samples are automatically calculated by the model.

[0061] The results of the identification are as follows Figure 6 As shown, the data points of the test sample are all clustered in the wild sample section on the right, indicating that it belongs to wild conditions and the model has good robustness. Therefore, the test sample can be classified and analyzed using the model, and the analysis results are accurate.

[0062] The above description is merely an embodiment of the present invention, and the scope of protection of the present invention is not limited to these specific embodiments, but is determined by the claims of the present invention. For those skilled in the art, the present invention can have various modifications and variations. Any modifications, equivalent substitutions, improvements, etc., made within the technical concept and principle of the present invention should be included within the scope of protection of the present invention.

Claims

1. A system for discriminating between wild and farmed origin of silver carp, characterized in that, The system comprises at least: a sample processing module, which is used at least for processing a silver carp sample to obtain original data of a polypeptide as shown in any one of SEQ ID NO. 1-4, and obtaining a proteome component response of the sample to be tested; a data processing module, which is used at least for importing the proteome component response of the sample to be tested into an OPLS-DA classification discriminant analysis model, obtaining a score plot for subsequent discriminant analysis of sample data; a result output module, which is used at least for outputting results.

2. The system of claim 1, wherein, The sample processing module specifically operates as follows: performing proteome determination pretreatment on the sample to be tested to obtain a polypeptide solution comprising at least the polypeptide marker as shown in any one of SEQ ID NO. 1-4, and determining the obtained polypeptide solution by liquid chromatography-mass spectrometry to obtain a proteome component response of the sample to be tested.

3. The system of claim 1, wherein, The preparation method of the OPLS-DA classification discriminant analysis model in the data processing module is as follows: S1: Protein extraction step: performing proteome determination pretreatment on muscle powder of wild and domestic silver carp samples to obtain a polypeptide solution comprising the polypeptides as shown in SEQ ID NO. 1-4: S2: Protein detection step: determining the polypeptide solution obtained in step S1 by liquid chromatography-mass spectrometry to obtain liquid chromatography-mass spectrometry analysis results; S3: Importing the liquid chromatography-mass spectrometry analysis results in step S2 into PEAKS Online software for database retrieval and relative quantitative analysis, with the following parameter settings: the database is the Cyprinidae (Cyprinidae) database; the enzyme cutting mode is Trypsin (trypsin), the maximum number of missed cutting sites is 2; the precursor ion mass error is 10 ppm, the fragment ion mass error is 0.02 Da; the false positive rate (FDR) threshold at the peptide and protein levels is set to 1%; S4: Taking the protein identification list exported by the PEAKS software obtained in step S3 and the normalized expression of each protein in all samples as an initial data matrix, importing the matrix and the corresponding grouping information of wild and domestic samples into SIMCA software (MKS Umetrics AB) to obtain an OPLS-DA classification discriminant analysis model, wherein the OPLS-DA models of wild and domestic samples are compared to screen differential proteins, with the following screening parameter settings: VIP>1; |p[corr]|>0.75 in S-plot analysis; the zero point is not included in the confidence interval of the loading chart; in pairwise comparison of OPLS-DA, the parameter change multiple is >1.4 (or <0.71), and p<0.

05.

4. The system of claim 1, wherein, The steps for discriminant analysis are as follows: using the score plot output by the model to perform discriminant analysis of subsequent sample data, and the position where the subsequent data is projected in the score plot represents the sample area of the test sample, which is predicted as the growth mode.

5. A method for discriminating between wild and farmed origin of silver carp, characterized in that, The method comprises the steps of applying the system of any one of claims 1-4 to analyze and determine the source of silver carp.

6. A kit for discriminating between wild and farmed origin of silver carp, characterized in that, The kit at least comprises reagents for quantitative and / or qualitative detection of the polypeptide according to any one of SEQ ID NO. 1-4.

7. The kit of claim 6, wherein The kit at least comprises at least one of protein extraction reagent and protein detection reagent.

8. The kit of claim 7, wherein The protein extraction reagent at least comprises at least one of protein extraction solution, DTT (dithiothreitol), IAA (iodoacetamide), ammonium bicarbonate solution, and protease solution; and the protein detection reagent at least comprises mobile phase solution.

9. Use of the system according to any one of claims 1-4 or the method according to claim 5 or the kit according to any one of claims 6-8 in the preparation of a product for identifying wild and farmed sources of silver carp.

10. Use according to claim 9, characterized in that, The identification of wild and farmed sources of silver carp comprises at least one of wild farming in Huaihe River, wild farming in Qili Lake, and domestication.

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