CN110687236B - Method for evaluating freezing and thawing degree of meat based on iTRAQ marker protein - Google Patents
Method for evaluating freezing and thawing degree of meat based on iTRAQ marker protein Download PDFInfo
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Abstract
The invention discloses a method for evaluating the freezing and thawing degree of meat based on iTRAQ labeled protein, which adopts iTRAQ labeled quantitative proteomics to carry out quantification and qualification on protein in freezing and thawing treated meat, and takes protein with protein level having obvious difference in the freezing and thawing treated meat as labeled protein, thereby judging the freezing and thawing degree of the meat according to the content of the labeled protein in the meat. The invention identifies the protein in the frozen and thawed meat for the first time, provides a basis for screening the labeled protein reflecting the freezing and thawing quality of the meat, can judge the freezing and thawing degree of the meat according to the protein level result, provides a new quality evaluation method, is beneficial to creating more profits for meat enterprises, and has wide application prospect.
Description
Technical Field
The invention belongs to the technical field of meat product quality detection, and particularly relates to a method for evaluating freezing and thawing degree of meat based on iTRAQ labeled protein.
Background
Meat is one of important foods in life of people, and along with the higher living standard of people, the requirements of people on meat not only stay on the basis of quantity, but also increase the quality requirements on meat. According to different processing modes, the meat circulating on the market at present mainly comprises two types of traditional frozen meat and fresh meat. Compared with frozen meat, fresh meat has the advantages of nutritional characteristics and sensory characteristics, when the frozen meat is frozen, the ice crystals formed by water are increased in volume to damage cell membranes, juice is lost after thawing, nutritional ingredients such as protein and a plurality of flavor substances are lost, and in addition, as the deliquescence and maturation are not completed at a proper temperature, the fresh meat still has a delicious taste and a special aroma. Therefore, chilled meat is not frozen and is superior to frozen meat in flavor, texture, and processing characteristics. The repeatedly unfrozen meat is mechanically damaged due to the volume change of ice crystals in the freezing process, so that the water retention is poorer, and the repeatedly unfreezing process is easily polluted or deteriorated, so that the quality of the repeatedly unfrozen meat is poorer than that of a common frozen product.
Goat meat is not only traditional meat used as both food and medicine, but also one of important red meat in diet, has no religious culture contraindication, has a long history of eating in various countries in the world, and is a flavor food in China. Compared with other animals, mutton has low fat and high protein, and is rich in various nutrients. The mutton yield value of China is steadily increased in recent years, the market demand is large, and most of mutton is circulated in the market in a freezing mode. Due to the fact that repeated freezing and thawing of meat is easily caused due to the fact that the cold chain of the meat is not perfect in the circulation process, the method for accurately identifying the freezing and thawing degree of the mutton has important practical significance.
Researchers have determined freezing and thawing of meat for many years by a variety of methods, such as water retention, texture analysis, protein solubility, volatile basic nitrogen (TVB-N) and lipoprotein oxidation, enzymology, nuclear magnetic resonance, microscopic observations, and the like. However, these methods study the change of the meat freezing and thawing quality in terms of appearance and chemical substances, and the identification of the freezing and thawing quality fails to deeply explain the mechanism and has the disadvantage of poor accuracy. The factors influencing the quality of mutton are more, and the structure and functional characteristics of protein in the slaughtered muscle have more obvious influence on the quality of meat and meat products. In recent years, the application of proteomics in the meat quality field also achieves a series of valuable results, which greatly helps people to understand complex meat biological mechanisms and quality-related biomarkers, so that the protein can be used as a protein marker reflecting the freezing and thawing degree of mutton. Meanwhile, the technology of labeling relative and absolute quantification (iTRAQ) is a new and powerful method capable of simultaneously performing absolute and relative quantitative research on four samples. The method provides a more comprehensive protein map, has good precision and high accuracy, so that proteomics analysis based on the iTRAQ technology draws more attention.
Disclosure of Invention
The invention aims to provide a method for screening marker proteins reflecting the freezing and thawing degree of meat based on iTRAQ marker quantitative proteomics and evaluating the freezing and thawing degree of meat by using the marker proteins, aiming at the defects that the conventional meat evaluation method is difficult to deeply explain the freezing and thawing quality mechanism of the meat, poor accuracy and the like.
Aiming at the purposes, the technical scheme adopted by the invention comprises the following steps:
1. collecting a fresh meat sample and freeze-thaw meat samples with different freeze-thaw times, extracting proteins in the fresh meat sample and the freeze-thaw meat sample, and performing enzymolysis on the obtained proteins to obtain a peptide segment in the sample.
2. Carrying out iTRAQ labeling on the peptide fragments obtained in the step 1, separating the labeled peptide fragments, and carrying out qualitative and quantitative analysis by using a biological mass spectrum, wherein a logarithmic value of a ratio of relative quantitative values of the qualitative peptide fragments in the frozen-thawed meat sample and the fresh meat sample is used as a basis for judging the change of the protein abundance level, the logarithmic value is larger than 1.5, the protein is up-regulated, the logarithmic value is smaller than 2/3, the protein level is down-regulated, and the logarithmic value is between 1.5 and 2/3, so that the protein abundance has no significant change in the fresh meat sample and the frozen-thawed meat sample.
3. And (3) analyzing the result of the step 2 by using a Venn diagram, wherein if the logarithmic value is more than 1.5 or less than 2/3, the content of the protein abundance in the freeze-thaw meat sample is obviously different from that in the fresh meat sample, and the protein with the obvious content difference is used as a marker protein.
4. Detecting the content of the marker protein in different meat samples to be detected according to the method in the step 1-3, judging the freezing and thawing degree of the meat samples to be detected according to the content of the marker protein, wherein if the marker protein is a positive correlation marker protein, the higher the content of the marker protein is, the more the freezing and thawing times of the meat samples to be detected are; if the marker protein is a negative related marker protein, the lower the content of the marker protein is, the more times of freezing and thawing the meat sample to be detected is.
The method can be used for evaluating freeze-thaw degree of mutton, beef, pork, etc.
When the meat is mutton, in the step 1, the method for extracting mutton protein is a urea method; carrying out FASP enzyme digestion on the obtained mutton protein by using trypsin at 37 ℃ to obtain a peptide fragment.
When the meat is mutton, in the step 2, preferably, RP C18 chromatographic columns are adopted to separate the marked peptide fragments, the separated peptide fragments are dissolved by a mobile phase A and then loaded to a liquid chromatograph-mass spectrometer for gradient elution and mass spectrum detection, wherein the mobile phase A is a formic acid aqueous solution with the mass concentration of 0.1%, the mobile phase B is a formic acid acetonitrile solution with the mass concentration of 0.1%, the mobile phase gradient is selected from 0 to 37.5 minutes, the A: B is 97% to 3% to 84% to 16%, the A: B is 75% to 25% to 70% to 30%, the A: B is kept for 20% to 80% in 48 to 54 minutes, the elution flow rate is 300nL/min, the full-scanning range m/z of a mass spectrum is detected to be 350-1600, and parent ions are fragmented by an HCD method.
In the step 2, the qualitative and quantitative analysis conditions of the biological mass spectrum are as follows: the mass spectrum original data is subjected to data analysis based on an Ovis protein database, database searching calculation analysis is carried out by using protome discover software according to a sequence algorithm, highly reliable polypeptides under the condition of less than 1% of FDR are selected as filtering parameters for qualitative identification of the proteins, and specific polypeptides are selected for relative quantitative analysis of the proteins among different samples.
When the meat is mutton, the marker proteins are elongation factor 1-gamma, cAMP-dependent protein kinase catalytic subunit alpha, ribosomal protein S12 and collagen alpha-2 (IV) chain, wherein the elongation factor 1-gamma, the cAMP-dependent protein kinase catalytic subunit alpha and 40S ribosomal protein S12 are positively correlated marker proteins, and the collagen alpha-2 (IV) chain is negatively correlated marker proteins.
The protein in the frozen and thawed meat is quantified and qualified through the iTRAQ proteomics technology, and the protein with the protein level obviously different from that of the thawed meat is taken as the marker protein, so that the freezing and thawing degree of the meat is judged according to the content of the marker protein in the meat. Compared with the existing meat quality identification method, the method has the following beneficial effects:
1. the invention identifies the protein in the frozen and thawed meat for the first time and provides a basis for screening the marker protein reflecting the frozen and thawed meat quality.
2. The invention can judge the meat freezing degree according to the protein level result and provides a new quality evaluation method.
3. The invention has wide application prospect and is helpful for people to know the protein change of the meat quality reduction in the freeze-thaw processing process.
4. The invention has important significance for the quality control of meat in the transportation and storage processes, and is beneficial to creating more profits for meat enterprises.
5. The invention can be extended to molecular and gene level, and embodies the mechanism of meat quality reduction and change in the process of freeze-thawing processing, thereby deeply knowing the change of meat quality.
Drawings
FIG. 1 is a graph of the amount of mutton differential protein identified in different comparison groups.
FIG. 2 is a Venn diagram of up-regulated protein.
Figure 3 is a venn diagram of down-regulated proteins.
Figure 4 is a graph of differential protein GO classification results.
Figure 5 is a graph of differential protein KEGG metabolic classifications.
Detailed Description
The invention will be further described in detail with reference to the following figures and examples, but the scope of the invention is not limited to these examples.
Example 1
1. 3 horizontal white cashmere goats (ram, average weight 23.12 +/-1.62 kg) with similar weights and the same feeding modes are selected and taken for 36 hours after slaughter to obtain the longissimus dorsi muscle on any side. Samples were randomly divided into 3 groups, each group containing three biological replicates, and approximately 200g of samples were freeze-thawed 0, 1, 2 times and denoted by CON, DR1, DR2, respectively, wherein freeze-thaw 0 times represents a fresh lamb sample. The sample circulating freeze-thaw conditions are as follows: freezing at-18 deg.C for 24 hr, and refrigerating at 4 deg.C for 12 hr. Mutton samples of about 10g, which were frozen and thawed at different times, were weighed into small pieces, and about 1g was placed in a 10mL centrifuge tube, 6mL of buffer solution (7M urea, 2M thiourea, 0.1% CHAPS, phosphatase inhibitor, protease inhibitor) was added, vortexed and mixed well. The samples were disrupted and homogenized by an ultrasonic cell disrupter (time 60 s/time 3 times total, amplitude 22%), homogenized, then left at room temperature for 30min and centrifuged at 15000r/min at 4 ℃ for 20min, the supernatant was collected, and the protein concentration was determined by BCA method. Taking the supernatant with the protein content of 100 mu g, putting the supernatant into a 1.5mL centrifuge tube, adding 8M urea (containing 0.1% SDS) and ultrapure water (containing 0.1% SDS), and adding 4.5 mu L of 1M triethylammonium bicarbonate (TEAB) aqueous solution to make the total volume of the solution 100 mu L and the final concentration of the urea 4M; then 5. mu.L of 200mM aqueous TCEP solution was added and reacted at 55 ℃ for 1 hour; then 5. mu.L of 375mM iodoacetamide solution was added for iodoacetylation, and 660. mu.L of acetone was added for overnight precipitation. After the precipitation, acetone washing was performed, and then 2.5. mu.g of trypsin was added to perform FASP digestion at 37 ℃ overnight, to obtain a peptide fragment.
2. According to AB Sciex company iTRAQTMThe reagent kit (catalog number 4390812) specification processes and marks the peptide fragment obtained in the step 1, then uses high performance liquid chromatography (dean NCS3500, USA) and RP C18 chromatographic column to separate the marked peptide fragment, dissolves the separated peptide fragment with mobile phase A, then loads the dissolved peptide fragment to a liquid chromatograph-mass spectrometer, carries out gradient elution and carries out mass spectrum detection. The mobile phase A is a formic acid aqueous solution with the mass concentration of 0.1%, the mobile phase B is a formic acid acetonitrile solution with the mass concentration of 0.1%, and the mobile phase gradient and the elution flow rate are shown in the following table 1. The mass spectrometer is a Q active mass spectrometer of Thermo Scientific company, the m/z of the full scanning range of the detected mass spectrum is 350-1600, and parent ions are fragmented by using an HCD method.
TABLE 1 flow phase separation gradient
| Time (min) | Buffer A | Buffer B | Flow rate (nL/min) |
| 0 | 97％ | 3％ | 300 |
| 5 | 97％ | 3％ | 300 |
| 6 | 94％ | 6％ | 300 |
| 37.5 | 84％ | 16％ | 300 |
| 46 | 75％ | 25％ | 300 |
| 48 | 70％ | 30％ | 300 |
| 49 | 20％ | 80％ | 300 |
| 54 | 20％ | 80％ | 300 |
| 54.5 | 97％ | 3％ | 300 |
| 65 | 97％ | 3％ | 300 |
The mass spectrum raw data is subjected to data analysis based on an Ovis protein database. And (3) carrying out library searching calculation analysis on the generated mass spectrum detection original data in the database by using a protocol scanner software (PD software for short). The highly reliable polypeptide under the condition of FDR of less than 1 percent is selected as the filtering parameter for the qualitative identification of the protein, and the specific polypeptide is selected for the relative quantitative analysis of the protein among different samples. Taking a logarithmic value of the ratio of the relative quantitative values of the qualitative peptide fragments in the frozen-thawed mutton sample and the fresh mutton sample as a basis for judging the change of the protein abundance level, namely, if the logarithmic value is more than 1.5, the protein is up-regulated, if the logarithmic value is less than 2/3, the protein level is down-regulated, and if the logarithmic value is between 1.5 and 2/3, the protein abundance has no significant change in the fresh mutton sample and the frozen-thawed mutton sample. The results of the analysis are shown in FIG. 1.
As can be seen from FIG. 1, the total number of identified proteins was 951, the number of quantifiable proteins 835, the number of identified polypeptide species 7624, and the number of identified polypeptides 26806. Analysis of the differential proteins in the frozen-thawed mutton samples and fresh mutton samples (DR 1/CON, DR2/DR1 and DR2/CON, respectively) determined 29 (up: 25, down: 4), 127 (up: 106, down: 21) and 133 (up: 112, down: 21) differential proteins, respectively.
3. Further analysis of up-regulated and down-regulated proteins in the differential comparison groups DR1/CON and DR2/DR1 was performed using venn plots, and the results are shown in fig. 2 and 3.
There were 10 consensus proteins for both differential comparison groups, of which 3 were co-upregulated (fig. 2), respectively: elongation factor 1-gamma (EEF1G), cAMP dependent protein kinase catalytic subunit alpha (PKA C-alpha), ribosomal protein S12(RPS 12); 1 of the co-downregulated proteins (fig. 3), collagen alpha-2 (IV) chain (COL4a 2); the remaining 6 differential proteins: tropomyosin alpha-1 chain (TPM1), isocitrate dehydrogenase [ NAD ] subunit beta (IDH3B), catechol O-methyltransferase (COMT), vacuolar protein sorting-related protein 37B (VPS37B), ras-related protein Rab-2A (RAB2A) and lipoprotein Lipase Precursor (LPL) were up-down regulated in a heterogeneous manner. Therefore, the invention takes the elongation factor 1-gamma, the cAMP-dependent protein kinase catalytic subunit alpha, the ribosomal protein S12 and the collagen alpha-2 (IV) chain as the marker proteins, wherein the elongation factor 1-gamma, the cAMP-dependent protein kinase catalytic subunit alpha and the 40S ribosomal protein S12 are positively related marker proteins, and the collagen alpha-2 (IV) chain is negatively related marker proteins.
GO enrichment classification of the differential proteins detected in step 2 was performed using blast2GO 2.8 software, the results are shown in fig. 4, and the KEGG metabolic pathways of the differential proteins were analyzed using online DAVID software, the results are shown in fig. 5. To analyze the functional classification of all the different proteins, GO functional annotation was performed according to Cellular Composition (CC), Molecular Function (MF) and Biological Process (BP), as shown in fig. 4. According to the BP classification results, the differential proteins are involved in cellular processes, monobiological processes, metabolic processes, biological regulation and biological process regulation. For CC, the main six subclasses are organelles, cells, cell parts, organelle parts, extracellular region parts, and extracellular regions. For MF, several major sub-classes are binding, catalytic activity, structural molecule activity and transporter activity. As can be seen from fig. 5, the KEGG metabolic pathway in which all the differential proteins participate is mainly energy, amino acid and carbohydrate metabolism.
4. Detecting the content of the marker protein in different mutton samples to be detected by adopting a series LC-MS composed of a Q-active mass spectrometer and an NCS3500 high-performance liquid phase according to the methods in the steps 1 and 2, and judging the freeze-thaw degree of the mutton samples to be detected according to the content of the marker protein: if the marker protein is a marker protein with positive correlation, the higher the content of the marker protein is, the more the number of times of freezing and thawing of the mutton sample to be detected is; if the marker protein is a negative related marker protein, the lower the content of the marker protein is, the more the number of times of freezing and thawing of the mutton sample to be detected is.
Claims (2)
1. A method for evaluating the freezing and thawing degree of meat based on iTRAQ marker protein is characterized by comprising the following steps:
(1) collecting a fresh slaughtered mutton sample and freeze-thaw mutton samples with different freeze-thaw times, extracting proteins in the fresh mutton sample and the freeze-thaw mutton sample by a urea method, and performing FASP enzyme digestion on the obtained proteins by using trypsin at 37 ℃ to obtain peptide fragments;
(2) carrying out iTRAQ labeling on the peptide fragments obtained in the step (1), separating the labeled peptide fragments, and carrying out qualitative and quantitative analysis by using a biological mass spectrum, wherein a logarithmic value of a ratio of relative quantitative values of the qualitative peptide fragments in the frozen-thawed mutton sample and the fresh mutton sample is used as a basis for judging the change of the protein abundance level, the protein is up-regulated if the logarithmic value is greater than 1.5, the protein level is down-regulated if the logarithmic value is less than 2/3, and the protein abundance is not significantly changed in the fresh mutton sample and the frozen-thawed mutton sample if the logarithmic value is between 1.5 and 2/3;
the method for separating the marked peptide segment comprises the following steps: separating the marked peptide by adopting an RP C18 chromatographic column, dissolving the separated peptide by using a mobile phase A, loading the dissolved peptide into a liquid chromatograph-mass spectrometer, performing gradient elution and performing mass spectrometry, wherein the mobile phase A is a formic acid aqueous solution with the mass concentration of 0.1%, the mobile phase B is a formic acid acetonitrile solution with the mass concentration of 0.1%, the mobile phase gradient is selected from 0 to 37.5 minutes, A is 97% to 3% to 84% and 16% of B, 37.5 to 48 minutes, A is 75% to 25% to 70% and 30% of B, 48 to 54 minutes, B is kept for 20% to 80%, the elution flow rate is 300nL/min, the full scanning range m/z of the detected mass spectrum is 350-1600, and parent ions are fragmented by using an HCD method;
(3) analyzing the result of the step (2) by using a Venn diagram, wherein if the logarithm value is more than 1.5 or less than 2/3, the content difference of the abundance of the protein in the frozen-thawed mutton sample and the fresh mutton sample is obvious, and the protein with the obvious content difference is used as a marker protein; the marker proteins are elongation factor 1-gamma, cAMP-dependent protein kinase catalytic subunit alpha, ribosomal protein S12 and collagen alpha-2 (IV) chain, wherein the elongation factor 1-gamma, cAMP-dependent protein kinase catalytic subunit alpha and 40S ribosomal protein S12 are positively correlated marker proteins, and the collagen alpha-2 (IV) chain is negatively correlated marker proteins;
(4) detecting the content of the marker protein in different mutton samples to be detected according to the methods in the steps (1) to (3), judging the freezing and thawing degree of the mutton samples to be detected according to the content of the marker protein, wherein if the marker protein is positively correlated marker protein, the higher the content of the marker protein is, the more the freezing and thawing times of the mutton samples to be detected are; if the marker protein is a negative related marker protein, the lower the content of the marker protein is, the more the number of times of freezing and thawing of the mutton sample to be detected is.
2. The method for evaluating the degree of freezing and thawing of meat based on iTRAQ marker proteins of claim 1, wherein: in the step (2), the qualitative and quantitative analysis conditions of the biological mass spectrum are as follows: the mass spectrum original data is subjected to data analysis based on an Ovis protein database, library searching calculation analysis is carried out by using protome discover software according to a sequence algorithm, highly reliable polypeptides under the condition of less than 1% FDR are selected as filtering parameters for qualitative identification of proteins, and specific polypeptides are selected for relative quantitative analysis of proteins among different samples.
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