D-protein large-scale screening method based on thermoproteomics technology

Abstract

The present invention discloses a D-protein scale screening method based on thermoproteomics technology, which includes: step one, by adding a protein treatment agent to cells and not adding a protein treatment agent, respectively, to obtain a D-protein up-regulation group and a blank group; step two, using thermoproteomics technology to obtain a list of thermostability differential proteins; step three, using isomerization retrieval technology to obtain a list of stereoisomerized proteins; step four, comparing and analyzing the thermostability differential protein list with the stereoisomerized protein list to obtain potential D-proteins; step five, based on APM enzyme cutting technology, obtaining the D site of potential D-proteins. The present invention realizes a high-throughput, high-coverage scale identification method of D-proteins by thermoproteomics technology, and can accurately locate D-amino acid sites, which is of great significance to the exploration of disease biomarkers and the exploration of the pathogenesis of major diseases.

Description

Technical Field

[0001] The present invention relates to the technical field of protein post-translational modification identification in the proteomics research direction, and in particular to a large-scale screening method for D-proteins that realizes high-throughput and high-coverage by using thermal proteomics technology. Background Art

[0002] In organisms, proteins are mainly composed of L-amino acids connected by peptide bonds. However, a small amount of D-amino acids has also been found in proteins of prokaryotes, eukaryotes, animals and humans. Previous studies have shown that these D-amino acids are mainly formed by racemization of L-amino acids. Racemization is considered to be a type of post-translational modification of proteins. In the human body, the racemization of aspartic acid is the main one, followed by serine and glutamic acid. The racemization of amino acids can affect the spatial structure and function of proteins, and has been shown to be related to the occurrence of certain diseases. Studies in recent years have shown that the racemization of amino acids is affected by multiple factors such as free radicals, pH, enzymes and temperature. Since D-amino acids and L-amino acids are exactly the same in molecular weight, it is impossible to directly monitor the racemization of amino acids in proteins using traditional mass spectrometry.

[0003] Therefore, it is urgent to develop a new technology for large-scale identification and screening of D-proteins. Thermoproteomics methods use the principle that proteins will denature and reduce solubility under heating conditions, and can be used to discover heat-sensitive proteins. At present, mass spectrometry-based thermoproteomics analysis methods have been widely used in a series of studies such as the discovery of glycosylation modifications, proteins and drug molecules, proteins and metabolites, and protein-protein interactions. Most D-proteins have higher thermal stability than classic L-proteins, so D-proteins can be identified by differences in thermal stability. However, due to technical difficulties in verification methods and data retrieval, there are still no reports on the discovery of D-proteins based on thermoproteomics technology.

[0004] By developing a thermal proteomics experimental process for large-scale discovery of D-proteins and a method for retrieving and extracting D-protein information from massive proteomic data, we can obtain information on potential target proteins from omics data sets with high sensitivity and coverage, and accurately identify potential isomerization modification domains and their sites. The development of such large-scale identification methods will help to more comprehensively study the effects of post-translational modifications of proteins on their physiological functions, discover and study more diseases related to amino acid racemization, and explore whether D-proteins can be used as potential biomarkers for diseases, etc., and provide new ideas. Summary of the invention

[0005] An object of the present invention is to solve at least the above problems and to provide at least the advantages which will be described hereinafter.

[0006] Another object of the present invention is to provide a D-protein large-scale screening method based on thermal proteomics technology, which firstly heats the proteomics extract by gradient, separates and collects the heated supernatant, analyzes the supernatant of the D-protein up-regulated group and the blank group by quantitative proteomics analysis method, and screens out potential D-proteins by stereoisomer retrieval, and then applies aminopeptidase digestion (APM digestion) technology to finally obtain the D site of D-protein; the present invention can obtain the information of potential target proteins with high sensitivity and high coverage, and assist in identifying potential isomerization modification domains and their sites. Compared with other methods for identifying protein racemization, the present invention has higher analytical throughput, sensitivity and selectivity, and provides a reliable technical means for large-scale screening of D-proteins.

[0007] In order to achieve these purposes and other advantages according to the present invention, a D-protein large-scale screening method based on thermoproteomics technology is provided, which comprises:

[0008] Step 1, by adding a protein treatment agent to the cells and not adding a protein treatment agent, a D-protein up-regulation group and a blank group are obtained;

[0009] Step 2: Based on the D-protein up-regulated group and the blank group, a list of differentially thermally stable proteins was obtained using thermoproteomics technology;

[0010] Step 3: Obtain a list of stereoisomeric proteins using isomeric search technology;

[0011] Step 4: Compare and analyze the list of proteins with different thermal stability obtained in step 2 with the list of stereoisomer proteins obtained in step 3, and take the intersection of the two to obtain potential D-proteins;

[0012] Step 5: Based on the APM enzyme cleavage technology, obtain the D site of the potential D-protein obtained in step 4.

[0013] Preferably, in the method for large-scale screening of D-protein based on thermoproteomics technology, step one is specifically as follows: cells in the logarithmic growth phase are taken, cultured until the cells adhere to the wall, and divided into two groups, 30 μM protein treatment agent is added to one group to obtain a D-protein up-regulation group, and no protein treatment agent is added to the other group to obtain a blank group.

[0014] Preferably, in the D-protein large-scale screening method based on thermoproteomics technology, step 2 is specifically as follows:

[0015] S201, suspending the D-protein up-regulation group and the blank group in a buffer solution, respectively, then adding a protease inhibitor to the buffer solution (the final volume fraction after the protease inhibitor is added is 1%), repeatedly freezing and thawing by liquid nitrogen three times, centrifuging and collecting the first supernatant to obtain a D-protein up-regulation histone solution and a blank histone solution, respectively;

[0016] S202, dividing the D-protein up-regulating histone solution / blank histone solution equally into a plurality of test tubes, placing the plurality of test tubes at different temperatures for heat treatment, and centrifuging each heat-treated test tube to collect a second supernatant;

[0017] S203, denaturing each second supernatant with urea, and then alkylating each second supernatant with DTT and IAA, enzymatically hydrolyzing each second supernatant after the denaturation and alkylation treatment, collecting the peptide segment solution by centrifugation, and redissolving it in a formic acid solution after desalting to obtain a peptide analysis sample;

[0018] S204, performing LC-MS / MS detection and analysis on each polypeptide analysis sample, collecting a proteomics data set, and sequentially using TPP data analysis and a non-parametric data analysis method of a response curve to analyze the proteomics data set to obtain a list of proteins with differential thermal stability.

[0019] Preferably, in the D-protein large-scale screening method based on thermoproteomics technology, step three is specifically as follows:

[0020] S301, acquiring conformation-resolved proteomics data corresponding to the lowest temperature from the proteomics data set acquired in step S204, including retention time information, tandem mass spectrometry information, collision cross-sectional area, and stereoisomer signal response intensity of stereoisomer polypeptides of the same amino acid sequence;

[0021] S302, extracting features of the amino acid sequence in the conformation-resolved proteomics data by searching a data set generated by a protein database to obtain multiple feature data of the protein sample, so as to establish a feature set for isomerization modification retrieval of the protein sample, wherein each feature data includes a protein name, an amino acid sequence, a chromatographic retention time, a charge, a signal response intensity, a mass-to-charge ratio, and a secondary mass spectrum;

[0022] S303. For the characteristic data under the same amino acid sequence, delete the data with a retention time difference of less than 2 minutes and / or a collision cross-sectional area difference of less than 1.5%, and obtain a list of stereoisomer proteins.

[0023] Preferably, the D-protein large-scale screening method based on thermoproteomics technology is characterized in that step five specifically comprises: enzymatically digesting the potential D-protein obtained in step four with aminopeptidase, collecting and analyzing omics data using LC-MS / MS, processing the mass spectrometry data with MaxQuant, analyzing the peptide file, and finding the corresponding D site.

[0024] Preferably, in the D-protein large-scale screening method based on thermoproteomics technology, the buffer solution in step S201 is PBS buffer solution.

[0025] Preferably, in the D-protein large-scale screening method based on thermoproteomics technology, the denaturation alkylation treatment of the second supernatant in step S202 is specifically as follows: adding the same volume of 16M urea to the second supernatant to denature the protein solution, then adding 100mM DTT to a final concentration of 10mM, incubating at 37°C for 30min, then adding 200mM IAA to a final concentration of 50mM, incubating at room temperature in the dark for 30min, then adding 100mM DTT to a final concentration of 10mM, and incubating for 5min.

[0026] Preferably, in the D-protein large-scale screening method based on thermoproteomics technology, in step S203, each second supernatant after the denatured alkylation treatment is hydrolyzed by adding trypsin, and the mass ratio of trypsin to soluble protein in the second supernatant after the denatured alkylation treatment is 1:100.

[0027] Preferably, in the D-protein large-scale screening method based on thermoproteomics technology, step S202 is specifically as follows: the D-protein up-regulated histone solution / blank histone solution is evenly divided into 10 test tubes, and heated at 37°C, 39°C, 42°C, 45°C, 49°C, 53°C, 57°C, 62°C, 65°C, and 67°C for 3 min, respectively, and then quickly placed in an ice water bath to cool for 4 min, and then centrifuged at 4°C and 20,000g centrifugal force for 15 min to collect the second supernatant.

[0028] The present invention has at least the following beneficial effects:

[0029] 1) High-throughput performance: Using thermal proteomics technology, a large number of D-proteins can be screened quickly and efficiently without pre-treatment of D-protein up-regulated histones, which provides feasibility for large-scale research and saves time and resource costs;

[0030] 2) High quantitative accuracy and cost-effectiveness: Compared with the traditional protein thermal stability TMT label quantitative method, this method uses DIA label-free quantitative technology. This method improves the reproducibility of data, the number of protein identifications and quantitative accuracy, simplifies experimental operations, and reduces reagent costs, thereby significantly improving the credibility of experimental results.

[0031] 3) Strong universality, wide coverage, and non-discrimination: The present invention adopts two screening methods to identify potential D-proteins, one is based on the difference in ΔTm between protein melting curves, and the other is to directly calculate the Benjamini&Hochberg corrected p-value of the fitting curve. This dual screening method avoids some proteins that are missed because the ΔTm cannot be calculated from the melting curve. It not only more intuitively reflects the changes in the thermal stability of proteins before and after stereoisomer modification, but also improves the identification coverage of D-proteins and reduces the possibility of false negative results.

[0032] 4) Wide applicability: The present invention is applicable to various types of samples, including biological tissues, cell cultures, biological fluids, etc., enabling researchers to discover and analyze D-proteins in different research subjects.

[0033] 5) Clinical application prospects: The present invention provides strong support for finding the potential value of D-protein in clinical applications such as disease diagnosis, treatment and prognosis assessment, and is expected to provide new ideas and methods for clinical translational research in related fields.

[0034] 6) Cost-effectiveness: The present invention can efficiently process a large number of samples, thereby reducing the processing cost of a single sample and improving the economic benefits of the research.

[0035] 7) Data sharing and comparison: The data generated by the present invention can be shared and compared by researchers, which will help to form a more comprehensive and systematic D-protein data resource and promote cooperation and development in related fields.

[0036] Other advantages, objectives and features of the present invention will be embodied in part through the following description, and in part will be understood by those skilled in the art through study and practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] Figure 1 This is a flow chart of the protein screening and identification method based on thermoproteomics and stereoisomer modification technology of the present invention;

[0038] Figure 2 is the protein information obtained by thermal proteomics screening in Example 1 of the present invention; wherein, Figure 2 A shows that 1424 proteins that can be analyzed by thermoproteomics were obtained through LC-MS / MS; Figure 2 B is the information of 464 proteins with thermal stability changes obtained by screening through TPP; Figure 2 C is the reproducibility result of two biological replicates of TPP experiments; Figure 2 D is the S-shaped curve of 278 stable proteins; Figure 2 E is the variation trend of Tm corresponding to 278 stable proteins; Figure 2 F is the S-shaped curve of 186 unstable proteins; Figure 2 G is the changing trend of WT and SR+Tm corresponding to 186 unstable proteins;

[0039] Figure 3 The stereoisomer search technology in Example 1 of the present invention assists in verifying the thermoproteomics results; wherein, Figure 3 A is one of the forms of chiral peptides in the WT group; Figure 3 B is a distribution diagram of the proportion of the D-type of one form of chiral polypeptide; Figure 3 C is a statistical diagram of the number of isomers of one form of chiral polypeptide; Figure 3 D is another form of the chiral peptide in the WT group; Figure 3 E is the ratio distribution diagram of the D-type of another form of chiral polypeptide; Figure 3 F is a statistical diagram of the number of isomers of one form of chiral polypeptide;

[0040] Figure 4 The protein information corresponding to the intersection of the screening results of the thermal proteomics technology and the stereoisomer search technology in Example 1 of the present invention; 4A is the 194 proteins obtained after the intersection of the proteins obtained by TPP and the isomer search; Figure 4 B is the relationship between the number of peptides undergoing isomerization and |ΔTm|; Figure 4 C is the relationship between the ratio of protein isomerization and |ΔTm|; Figure 4 D-4F are the biological processes, cellular components and molecular functions corresponding to the 194 proteins.

[0041] Figure 5 The isomerization site information is verified by APM enzyme in Example 1 of the present invention; wherein Figure 5 A is the APM enzyme activity verification diagram; Figure 5 B-5C is a map for screening enzyme-cutting peptides and searching for sites based on peptide strength; Figure 5 D is the frequency diagram of amino acids corresponding to the D site;

[0042] In each figure, SR+ represents the D-protein up-regulated group (AD group), and WT represents the blank group (Control group). DETAILED DESCRIPTION

[0043] The present invention is further described in detail below in conjunction with the accompanying drawings and embodiments so that those skilled in the art can implement the invention with reference to the description.

[0044] The present invention is described below with reference to specific examples. Those skilled in the art will appreciate that the experimental methods in the following examples are conventional methods unless otherwise specified; the raw materials, reagents, materials, etc. used in the following examples are commercially available products unless otherwise specified.

[0045] The present invention proposes a method for large-scale screening of D-proteins, which solves the problem of identifying stereoisomeric modifications in a large number of protein samples. Currently, there are relatively few studies on the discovery and identification of protein isomeric modifications. The main reasons are: on the one hand, the frequency of such modifications is low, and traditional mass spectrometry methods have difficulties in identifying modifications that do not change the molecular weight; on the other hand, the lack of reliable methods for identifying stereoisomeric variants of D-proteins limits the possibility of finding such modifications in biological samples. By proposing this method for large-scale screening of protein isomeric modifications, the present invention successfully overcomes the following difficulties:

[0046] 1) Low-frequency modifications: D-protein stereoisomer variants occur at relatively low frequencies in the proteome, so traditional mass spectrometry methods may not be able to effectively identify such low-frequency modifications. This low frequency makes it more difficult to identify and characterize D-protein stereoisomer variants.

[0047] 2) Limitations of traditional methods: Traditional mass spectrometry methods usually identify modifications based on analyzing the mass and molecular weight of proteins. However, D-protein stereoisomer variants do not lead to changes in molecular weight, so this method has limitations in identifying D-protein stereoisomer variants.

[0048] 3) Lack of reliable identification methods: The lack of specific and efficient identification methods for D-protein stereoisomer variants makes it more difficult to find this modification in biological samples. Currently, there are relatively few identification methods for this special type of modification, which limits the possibility of in-depth research and application.

[0049] 4) Sample complexity: Biological samples are usually highly complex, containing multiple proteins and various other biomolecules. In such a complex background, accurate identification and quantification of D-protein stereoisomer variants may be interfered by other components, increasing the difficulty of identification.

[0050] 5) Standardization and calibration: Determining the presence of stereoisomeric variants of D-proteins usually requires comparison with known standards or databases to ensure the accuracy and reliability of identification. However, the limited standards and databases currently available may affect the credibility of the identification results.

[0051] 6) Data analysis and interpretation: The data from large-scale screening require complex analysis and interpretation to determine which proteins are affected by D-protein stereoisomer variants. This involves developing efficient data processing and interpretation methods, as well as integrating multiple data sources to gain a more comprehensive understanding.

[0052] 7) Complexity of technology and methods: The implementation of large-scale screening of D-protein stereoisomer variants may involve a variety of complex technologies and experimental steps, including sample preparation, mass spectrometry analysis, data processing, etc., which requires professional technology and equipment support, and it is necessary to overcome technical problems and errors that may arise in the experiment.

[0053] In summary, low-frequency modification, limitations of traditional methods, and lack of reliable identification methods are the main difficulties currently faced in large-scale screening of D-protein stereoisomeric variants; sample complexity, standardization and calibration, data analysis and interpretation, and complexity of technical methods are all challenges that may be faced in the process of large-scale screening of D-protein stereoisomeric variants. To solve these challenges, it is necessary to comprehensively use a variety of technical means and conduct in-depth research and exploration. Through the method proposed in the present invention, these difficulties are overcome, providing new possibilities for further research and application of D-protein stereoisomeric variants.

[0054] The purpose of the present invention is to provide a large-scale, highly sensitive and highly covered D-protein identification method. First, different temperature groups are set from equal parts of D-protein up-regulation group and blank histone samples, and heat treatment is performed respectively, and then the heated supernatant is separated, and then the supernatant samples of D-protein up-regulation group and blank group are enzymatically hydrolyzed, and quantitative proteomics analysis is performed, supplemented by isomerization retrieval and aminopeptidase (APM) verification. This method can obtain information on potential target proteins with high sensitivity and high coverage in omics data sets, and assist in identifying potential isomerization modification domains and their sites. Compared with other methods for identifying protein racemization, the present invention has higher analytical throughput, sensitivity and selectivity, and provides a reliable technical means for large-scale screening of D-proteins.

[0055] The D-protein large-scale screening and identification method based on thermoproteomics technology and stereoisomer modification technology provided by the present invention has the following basic design ideas:

[0056] like Figure 1The specific process of the present invention is as follows: cells of the blank group (control group) and the D-protein up-regulated group (AD group) are collected, and then the protein is extracted, heated at ten temperatures, and the salt is removed by enzyme, and then the LC-MS / MS analysis is performed, and finally the data is normalized to obtain the thermal stability curve, and the screened protein is subsequently verified. Using isomeric search, the D-type polypeptide and the ratio of D-type occurrence are obtained; and then the site of D protein is obtained using the enzyme cutting technology of APM.

[0057] The present invention utilizes the basic principle of the difference in thermal stability of proteins before and after stereoisomerization, monitors the thermal stability changes of the whole protein during stereoisomerization by gradient heating of proteomic extracts, obtains a list of stereoisomer proteins by preliminary screening, and further combines D-amino acid specific recognition aminopeptidase (APM) to achieve recognition and verification of specific D sites, thereby achieving high-sensitivity and high-coverage identification of D-proteins;

[0058] The specific steps include:

[0059] a) Determine the optimal temperature range for precipitation of protein samples: take two equal amounts of cell solutions, one of which is treated (with protein treatment agent added) to obtain a D-protein up-regulation group, and the other is a normal growth group (without adding protein treatment agent) to obtain a blank group, extract proteins from the D-protein up-regulation group and the blank group to obtain supernatants, and divide them equally into several new EP tubes, heat the several EP tubes in each group at different temperatures within the temperature range of 25°C-75°C, separate the supernatants of the D-protein up-regulation group and the blank group after heating at each temperature, perform enzymatic hydrolysis and quantitative proteomics analysis, calculate the amount of remaining protein in the supernatant at each temperature, and select the temperature point at which most proteins precipitate more obviously as the optimal temperature range (preferably, the temperature point corresponding to the ratio of the amount of protein in the D-protein up-regulation group to the amount of protein in the blank group is 0.25:1);

[0060] The protein sample can be a cell extract, tissue extract, blood or other protein mixture or purified protein; the protein sample used should maintain the complete natural structure of the protein and should not be denatured. Some mild protein extraction methods should be adopted, such as liquid nitrogen repeated freeze-thaw method, liquid nitrogen grinding method and homogenization method, etc. The lysate used (the lysate obtained by suspending each group of cells in a buffer solution) should also be able to maintain the structure of the protein, such as phosphate buffered saline (PBS), etc.

[0061] b) Establishing a D-protein high expression model of protein samples; The AD (Alzheimer's disease) model constructed in the present invention is based on the logical chain of amyloid protein (Aβ 42 ) is one of the main pathological manifestations of AD (Aβ 42is a factor that causes Alzheimer's disease), the core component of senile plaques (because Aβ 42 It can over-activate N-methyl-D-aspartate (NMDA) receptors, abbreviated as NMDA, induce cell apoptosis, and thus lead to toxic damage to nerve cells. At the same time, D-serine is a co-activator of NMDA receptors in rats, and D-serine is produced by the enzymatic reaction of serine racemase (SR). ) The present application adds Aβ to the protein sample cultured until the cells are attached to the wall. 42 Amyloid protein (protein treatment agent, the amount of which is added to the protein sample with a concentration of 30 μM of the protein treatment agent) is obtained, namely the D-protein up-regulation group, which promotes the up-regulation of serine racemase, thereby constructing an Alzheimer's disease AD model. The verification method is Western blot (WB), with the expression of serine racemase (SR) as the experimental indicator, and Western blot is used to confirm whether the model construction is successful. If the model is successfully constructed and contains a model containing D-type protein, then the serine racemase (SR) in the D-protein up-regulation group is higher than that in the group without adding Aβ. 42 The blank group of amyloid protein (protein treatment agent) was upregulated, which further indicated that the model was successfully constructed.

[0062] The modeling reagents (protein treatment agents, in this application, amyloid protein is used as the protein treatment agent) for establishing disease models can be neurotoxic damage substances such as β-amyloid protein, glutamate, formaldehyde, etc., or oxidative stress damage substances such as hydrogen peroxide, advanced glycation end products and other types of molecules.

[0063] c) selecting multiple temperature points within the optimum temperature range to heat the D-protein up-regulation group and the protein group, causing protein denaturation and precipitation; the multiple temperature points herein include any two or more temperature points within the optimum temperature range; according to the number of set heating temperature points, taking equal amounts of protein solutions of the D-protein up-regulation group and the blank group into new EP tubes, and heating them at the set temperature;

[0064] d) separating the heated supernatant for enzymatic hydrolysis and quantitative proteomics analysis; separating the D-protein up-regulation group and the blank group at each temperature point and collecting the supernatant, subjecting the supernatant to denaturation alkylation treatment (by adding urea, DTT and IAA) and enzymatic hydrolysis (by adding Trypsin) once, collecting the peptide solution by centrifugation, and analyzing it by a quantitative proteomics analysis method, specifically, desalting the peptide solution (desalting can be performed using a desalting column) and then redissolving it in a formic acid solution to obtain a peptide analysis sample, subjecting the peptide analysis sample to LC-MS / MS detection and analysis, and collecting a proteomics data set;

[0065] e) Directly analyze the difference in protein quantitative results between the D-protein up-regulated group and the blank group to screen D-proteins; search the raw files obtained by mass spectrometry analysis using conventional proteomics analysis software, set the corresponding quantitative method, select proteins with higher credibility of quantitative results (proteins with higher credibility of results include proteins with at least two or more peptides with quantitative results), perform normalization, directly calculate the difference in quantitative values ​​of proteins between the D-protein up-regulated group and the blank group, the difference in proteins between the D-protein up-regulated group and the blank group includes the distance between the two protein melting curves or the difference in ΔTm values ​​obtained by the Euclidean distance, set a suitable threshold, and proteins that meet the set threshold or the p value of the fitting curve obtained by non-parametric analysis of the response curve < 0.01 are the potential D-proteins for initial screening;

[0066] The following two methods are used for screening:

[0067] The first is TPP data analysis, which screens the target protein by comparing the difference in the parameter Tm in the melting curve of the D-protein up-regulated group and the blank group. The specific screening conditions are: 1. The fitted protein thermal melting curve R 2 >0.8; 2. The platform of the curve is <0.3; 3. The slope of each melting curve is <-0.06; 4. The ΔTm value is >1 or <-1; Screen the proteins that meet the above four conditions at the same time to obtain the first target protein set;

[0068] The second is nonparametric analysis of response curves (NPARC), with the screening condition of Benjamini & Hochberg corrected p value, p value < 0.01, to obtain the second target protein set;

[0069] The union of the first target protein set and the second target protein set is taken to obtain a list of proteins with differential thermal stability;

[0070] The second screening method compares the entire melting curve without relying on a single parameter of Tm. Because the change in thermal stability caused by stereoisomeric modification of proteins may be small, the present invention uses an integrated approach to screen data to maximize the discovery of potential D-proteins. The dual screening method avoids some proteins that are missed because the melting curve cannot calculate ΔTm. It not only more intuitively reflects the change in thermal stability of proteins before and after stereoisomeric modification, but also improves the identification coverage of D-proteins and reduces the possibility of false negative results.

[0071] f) Verification of the D-protein obtained by screening, specifically, using a stereoisomer search method to analyze the proteomics data collected, and using the isomer search method to screen out polypeptides with the same molecular weight but changed retention time, confirming isomerically modified proteins, and the stereoisomer search method can determine the polypeptides and isomer ratios of the isomerized proteins. Further, the present invention uses aminopeptidase APM enzymatic hydrolysis technology to verify the D-site of isomerically modified proteins. This APM enzyme can selectively remove L-amino acids from the N-termini of oligopeptides, amides and aromatic amide derivatives. APM enzymes are added to the blank group and the D-protein up-regulation group, respectively, and LC-MS analysis is performed to screen the obtained polypeptide list, and the proteins obtained by thermal proteomics are verified to find the corresponding D-site.

[0072] The present invention is based on omics samples and proposes a method for large-scale discovery of D-proteins, which has the following differences compared with the prior art:

[0073] 1) High-throughput identification technology: The high-throughput omics sample analysis technology is used, which can analyze a large number of samples at the same time, thereby improving the efficiency and speed of D-protein identification.

[0074] 2) Thermal proteomics method: Compared with traditional proteomics methods, the thermal proteomics method uses the difference in thermal stability of proteins at different temperatures for identification, which has higher accuracy and specificity.

[0075] 3) Specific identification strategy: A specific identification strategy for D-protein was adopted, which improved the accuracy and reliability of D-protein identification by combining multiple analytical methods and bioinformatics tools.

[0076] 4) Big data analysis: Combining big data analysis methods, comprehensive analysis and mining of identification results can be carried out to discover potential D-protein markers or biological significance, thereby providing more clues for related research.

[0077] 5) Scope of application and practicality: This method has a wider scope of application and practicality, and can play an important role in biomedical research, clinical diagnosis, drug development and other fields, providing support and promotion for research and application in related fields.

[0078] 6) Sample sources and processing: A wider and more diverse sample source was used, and the samples were processed more finely and comprehensively to ensure that rich information of D-protein could be captured.

[0079] 7) Multi-level analysis strategy: A multi-level analysis strategy was adopted, including analysis at the molecular level, cellular level and other levels, to comprehensively explore the characteristics and functions of D-protein in the body.

[0080] 8) Data integration and cross-validation: A variety of data integration and cross-validation methods were combined, including integrated analysis of multi-omics data such as genomics, transcriptomics, and metabolomics, thereby improving the accuracy and comprehensiveness of D-protein identification and functional analysis.

[0081] In summary, these differences make the method provided by the present invention have greater advantages and potential in the field of D-protein identification and research, and provide more possibilities and opportunities for related research and applications.

[0082] The large-scale screening method of D-protein proposed in the present invention provides an innovative solution for the rapid discovery of relevant disease markers. The study of the relationship and connection between the production and discovery of D-protein and neurological diseases is of great significance, and these associations may have a profound impact on the pathogenesis, diagnosis and treatment of neurological diseases. The following are some of the key contributions and impacts that this invention may bring:

[0083] 1) In-depth exploration of the mechanism of D-protein production: The method provided by the present invention can provide a more comprehensive understanding of the mechanism of D-protein production, including factors such as isomerases related thereto, which will promote further exploration in the field of D-protein and provide important clues for understanding the molecular mechanisms of neurological diseases.

[0084] 2) Major breakthrough in neurological disease research: Linking D-protein with neurological diseases can help researchers in this field gain a deeper understanding of the pathogenesis of neurological diseases and provide new perspectives and strategies for the diagnosis, treatment and prevention of neurological diseases. This breakthrough discovery is expected to bring new changes to the field of neurological diseases.

[0085] 3) Revealing biomarkers: The present invention found that certain D-proteins may be used as biomarkers for neurodegenerative diseases, providing new possibilities for early diagnosis, treatment monitoring, etc. This will help to deepen the understanding of neurological diseases by those skilled in the art and provide a basis for the realization of precision medicine.

[0086] 4) Discovery of novel proteins: The method provided by the present invention can screen and identify some previously unknown novel D-proteins, bringing new discoveries and understandings to the field of biology.

[0087] 5) Promotion of precision medicine: The present invention will lay the foundation for the realization of personalized medicine through the large-scale discovery of D-protein, which will make medical treatment more precise and formulate targeted diagnosis and treatment plans based on individual characteristics, thereby improving treatment effects and patient survival rates.

[0088] 6) Innovation in science and technology: The method provided by the present invention will promote scientific and technological innovation in related fields, promote the development of proteomics research, and bring new possibilities for precision medicine and neurological disease research. This will provide scientists and doctors with more tools and methods to solve the major challenge of neurological diseases.

[0089] In general, this invention will bring new ideas to the field of neurological diseases, promote research and application in related fields, and provide new directions and inspirations for the realization of precision medicine and the treatment of neurological diseases.

[0090] The present invention provides a D-protein large-scale screening method based on thermoproteomics technology, which comprises:

[0091] Step 1: by adding a protein treatment agent to the cells and not adding a protein treatment agent, a D-protein up-regulation group and a blank group are obtained; the protein sample can be a cell extract, a tissue extract, a blood or other protein mixture or a purified protein; the protein treatment agent can also be called a modeling agent for establishing a disease model, which can be a neurotoxic damage substance such as β-amyloid protein, glutamate, formaldehyde, etc., or an oxidative stress damage substance such as hydrogen peroxide, advanced glycation end products and other molecules;

[0092] Preferably, step 1 specifically comprises taking cells corresponding to the protein sample in the logarithmic growth phase (PC12 cells are selected in the present invention), culturing them until the cells adhere to the wall, and equally dividing them into two groups, adding 30 μM protein treatment agent to one group to obtain a D-protein up-regulation group, and not adding the protein treatment agent to the other group to obtain a blank group; the setting of the D-protein up-regulation group and the blank group is also the construction process of the D-protein high expression model. The AD model is constructed in this application, and the construction model is based on the following logical chain: Aβ 42 It is one of the main pathological manifestations of AD, namely the core component of senile plaques, because Aβ 42 It can over-activate N-methyl-D-aspartate (NMDA) receptors, abbreviated as NMDA, and induce cell apoptosis, thereby causing toxic damage to nerve cells. At the same time, D-serine is a co-activator of NMDA receptors in rats, and D-serine is produced by the enzymatic reaction of serine racemase (SR). Therefore, the present invention adds Aβ to cells 42 Amyloid protein promotes the upregulation of serine racemase, thus constructing an Alzheimer's disease AD model. The verification method is WB, the primary antibody is serine racemase, if the model is successfully constructed, and contains a model containing D-type protein, then serine racemase is upregulated in the D-protein upregulation group;

[0093] Step 2: Based on the D-protein up-regulated group and the blank group, a list of differentially thermally stable proteins was obtained using thermoproteomics technology;

[0094] Preferably, step 2 is specifically:

[0095] S201, suspending the D-protein up-regulation group and the blank group in a buffer solution respectively, then adding a protease inhibitor to the buffer solution, and collecting the first supernatant by centrifugation after repeated freezing and thawing with liquid nitrogen for three times, to obtain a D-protein up-regulation histone solution and a blank histone solution respectively; in order to maintain the intact natural structure of the protein and prevent denaturation, the present invention adopts a mild protein extraction method, liquid nitrogen repeated freezing and thawing method, which is not limited to the extraction method described in the technical solution, and other mild methods such as liquid nitrogen grinding method and homogenization method can also be used; the buffer solution used is phosphate buffered saline (PBS), which can maintain the structure of the protein;

[0096] S202, dividing the D-protein up-regulating histone solution / blank histone solution equally into a plurality of test tubes, placing the plurality of test tubes at different temperatures for heat treatment, and centrifuging each heat-treated test tube to collect a second supernatant;

[0097] The determination of different temperature points is specifically as follows: the blank group and the D-protein up-regulation group are divided into multiple samples in equal amounts, and the multiple samples of each group are heated at multiple temperatures in the range of 25-75°C (e.g., evenly divided into 20 temperature points). At this time, a wider temperature range is selected, and each sample is centrifuged after heating to collect the supernatant, and the amount of remaining protein in the supernatant at each temperature point is analyzed. The multiple temperature points where most of the proteins are obviously precipitated form the optimal temperature range of different temperatures in step S202. For example, after the above analysis, the protein precipitation is more obvious at multiple temperature points in the range of 37°C to 67°C, and it can be confirmed that 37°C-67°C is the optimal temperature range. The different temperature points in S202 can be determined as multiple temperature points in the range of 37°C-67°C;

[0098] Preferably, the optimal temperature range determined by the present invention is 37°C-67°C, and in step 202, the D-protein up-regulation histone solution / blank histone solution is evenly divided into 10 test tubes, and respectively heated at 37°C, 39°C, 42°C, 45°C, 49°C, 53°C, 57°C, 62°C, 65°C, and 67°C for 3 minutes, and then quickly placed in an ice water bath to cool for 4 minutes, and then centrifuged at 4°C and 20,000g centrifugal force for 15 minutes to collect the second supernatant;

[0099] S203, performing denaturation alkylation treatment on each second supernatant using urea, DTT and IAA, performing enzymatic hydrolysis on each second supernatant after the denaturation alkylation treatment, collecting the peptide segment solution by centrifugation, and redissolving it in a formic acid solution after desalting to obtain a peptide analysis sample;

[0100] For the second supernatant corresponding to each temperature point of each group (D-protein up-regulation group or blank group), 30 μL of the second supernatant obtained in step S202 was placed in a new EP tube, and an equal volume of 16 M urea was added to the EP tube to denature the protein solution, and then 100 mM DTT (dithiothreitol) was added to make the final concentration of DTT 10 mM, and incubated at 37°C for 30 min. Then, 200mM IAA (indole-3-acetic acid) was added to make the final concentration of IAA 50mM, and the mixture was incubated at room temperature in the dark for 30 minutes. Finally, 100mM DTT was added to make the final concentration 10mM, and the mixture was incubated for 5 minutes to complete the denaturation reduction alkylation. Then, a buffer solution PBS was added to dilute the urea concentration in the EP tube to 1M, and then a protease (Trypsin was selected in the present invention) was added to the EP tube for enzymatic hydrolysis, and the mass ratio of the protease to the soluble protein in the solution in the EP tube was 1:100. After the enzymatic hydrolysis was completed, the EP tube was placed at 1,4000g for centrifugation to obtain a peptide solution, and after desalting (a desalting column can be used for desalting), the polypeptide concentration was determined using a kit, and the solution was freeze-dried and stored for later use. The freeze-dried polypeptide was redissolved in a 0.1% (v / v) formic acid solution to obtain a polypeptide analysis sample.

[0101] S204, performing LC-MS / MS detection and analysis on each polypeptide analysis sample, collecting a proteomics data set, and sequentially using TPP data analysis and a non-parametric data analysis method of a response curve to analyze the proteomics data set to obtain a list of proteins with differential thermal stability;

[0102] Peptide analysis samples were subjected to LC-MS / MS detection and analysis. 1 μg of peptide analysis samples were injected, and mass spectrometry was repeated twice for each sample. Liquid chromatography pre-column: 75 μm inner diameter, 2 cm length, filled with 3 μm C-18 filler; liquid chromatography analysis column: 75 μm inner diameter, 25 cm length, filled with 2 μm C18 filler. Mobile phase A: 0.1% formic acid, mobile phase B: acetonitrile; liquid phase gradient elution program: 0-120 min (3%-90% B), using the following gradient: 0-5 min, 3-8% B, 5-75 min, 8-18% B, 75-103 min, 18-28% B, 103-115 min, 28-90% B, 115-120 min, 90-90% B. The mass spectrometer was Thermo OrbitrapFusion Lumos. The instrument was operated by Xcalibur software, with a resolution of 120,000, a mass scan range of m / z 300-1,500, a maximum injection time of 50 ms, and an automatic gain control (AGC) of 3×10 6; Secondary scans were run in data-independent acquisition mode (DIA) with a mass scan range of m / z 600-1,200. Target AGC was 3e 6 ions with a maximum IT time of 54 ms. Resolution was 30,000. Ions isolated from the corresponding MS1 window were fragmented using HCD.

[0103] The human proteome database downloaded from the UniProt website was used as the background proteome database. The mass spectrometer was operated using Xcalibur software, and the database search software used was DIANN. The data was normalized by removing the amount of remaining protein in the supernatant corresponding to other heating temperatures from the amount of remaining protein in the supernatant corresponding to 37°C, and the relative amount of remaining protein in the supernatant at different temperatures was calculated.

[0104] The proteomics data set was collected to obtain the TPP R data package. The melting curves of the blank group and the D-protein up-regulated group were plotted according to the amount of residual protein in the supernatant at different temperatures. The target protein was determined by comparing the difference in the parameter Tm in the protein melting curve. The screening conditions were: 1. The fitted protein thermal melting curve R 2 >0.8, the platform of the curve <0.3, the slope of each melting curve <-0.06, and the proteins with ΔTm value >1 or <-1, and then screen to obtain the first target protein set (the thermal stability trend of the protein in the two repetitions is the same, ensuring that the thermal stability of the proteins in the two repetitions is either enhanced or increased)

[0105] Further, the non-parametric analysis method of the response curve was used to screen out the proteins corresponding to the Benjamini&Hochberg corrected p-value < 0.01 in the analysis data provided by the TPP R package, and the second target protein set was obtained;

[0106] Taking the union of the screening results obtained by the TPP data analysis method and the non-parametric data analysis method of the response curve to obtain a list of differentially thermostable proteins, that is, taking the union of the first target protein set and the second target protein set to obtain a list of differentially thermostable proteins;

[0107] Step 3: Obtain a list of stereoisomeric proteins using isomeric search technology;

[0108] Preferably, step three is specifically:

[0109] S301, acquiring conformation-resolved proteomics data corresponding to the lowest temperature (37° C.) from the proteomics data set acquired in step S204, including retention time information, tandem mass spectrometry information, collision cross-section area, and stereoisomer signal response intensity of stereoisomer polypeptides of the same amino acid sequence;

[0110] S302, extracting features of the amino acid sequence in the conformation-resolved proteomics data by searching a data set generated by a protein database to obtain multiple feature data of the protein sample, so as to establish a feature set for isomerization modification retrieval of the protein sample, wherein each feature data includes a protein name, an amino acid sequence, a chromatographic retention time, a charge, a signal response intensity, a mass-to-charge ratio, and a secondary mass spectrum;

[0111] S303. For the characteristic data under the same amino acid sequence, delete the data with a retention time difference of less than 2 minutes and / or a collision cross-sectional area difference of less than 1.5%, and obtain a list of stereoisomer proteins;

[0112] The specific plan is as follows:

[0113] 1) Preliminary extraction of proteomics data:

[0114] Step 1: Import the proteomics data obtained in step S204 into MaxQuant for database retrieval analysis. Select the corresponding database based on the type of input raw data, set appropriate parameters to perform database retrieval on the raw data, and a series of txt files will be obtained after the database search is completed. The goal of this step is to obtain data for heterogeneous retrieval.

[0115] Step 2: Extract the file named evidence and filter out the contamination library and anti-library. Convert the txt file into an excel table with the suffix .xlsx. Divide it into different sheets according to the number of sample collection needles for subsequent analysis, and use the excel table (including protein sequence, name, charge, m / z, retention time, intensity, ratio_d and other parameters) as the final heterogeneous search input file. The goal of this step is to obtain a data file that the algorithm can recognize.

[0116] 2) Scale-up screening of stereoisomerized proteins:

[0117] Step 3: Based on the information in the input file, delete the rows where the response intensity column is 0 or null. The goal of this step is to filter out invalid data.

[0118] Step 4: Depending on the specific experimental needs, delete or not delete the row with the value of "modified" in the modification column. This step is to ensure that each sequence has the same mass-to-charge ratio.

[0119] Step 5: Group the remaining rows by sequence and charge. Delete the charge information with low response values ​​according to the response intensity of different charges. The purpose of this step is to ensure that each sequence has a unique main charge peak.

[0120] Step 6: Calculate the retention time differences between adjacent peaks. Based on the retention time differences, remove rows with retention time differences less than 2 min or collision cross-section area differences less than 1.5%. The goal of this step is to filter the list of peptides with isomeric modifications based on retention time.

[0121] Step 7: Calculate the relative ratio of the target peaks under the same sequence and eliminate the false positive background fluctuation noise signals. Calculate the ratio value of the remaining target peaks to obtain the isomerization ratio and number of isomers for each sequence. The goal of this step is to ensure the reliability of the screened data.

[0122] Step 8: Run the algorithm and output a simplified isomerization modification list including protein name (Proteins), sequence (Sequence), charge (Charge), mass-to-charge ratio (m / z), retention time (RT), collision cross-section area (CCS), response intensity (Intensity), isomerization ratio (Ratio, etc.) and a list containing all input information, and generate an Excel file, which is the stereoisomerization protein list;

[0123] Step 4: Compare and analyze the list of proteins with different thermal stability obtained in step 2 with the list of stereoisomer proteins obtained in step 3, and take the intersection of the two to obtain potential D-proteins;

[0124] Step 5: Based on the APM enzyme digestion technology, the D site of the potential D-protein obtained in step 4 is obtained;

[0125] Preferably, step five specifically comprises: digesting the potential D-protein obtained in step four with APM, acquiring and analyzing omics data using LC-MS / MS, processing the mass spectrometry data with MaxQuant, analyzing the peptide file, and finding the corresponding D site.

[0126] Example 1

[0127] D-protein scale screening method based on thermoproteomics technology is used for the study of stereoisomerically modified proteins in PC12 cells (rat adrenal pheochromocytoma) (this application is not only applicable to the exemplified cell proteomics samples, but also to all types of proteomics samples such as animals and human tissues)

[0128] (1) Construction of D-protein upregulation cell model

[0129] PC12 cells in the logarithmic growth phase were collected and 5×10 3 The cells were seeded at a density of 100 cells / well in a 96-well plate and cultured for 24 h. After the cells adhered to the wall, 30 μM Aβ was added. 42 Cells were treated with amyloid protein. After treatment, the expression of serine racemase (SR) was used as an experimental indicator, and Western blot was used to confirm the success of the model construction. The present invention constructed an AD model. Aβ 42 It is one of the main pathological manifestations of AD, namely the core component of senile plaques, because Aβ 42 It can over-activate N-methyl-D-aspartate (NMDA) receptors, induce cell apoptosis, and thus lead to toxic damage to nerve cells. At the same time, D-serine is a co-activator of NMDA receptors in rats, and D-serine is produced by the enzymatic reaction of serine racemase (SR). Therefore, based on such a logical chain, the present invention adds Aβ to cells. 42 Amyloid protein promotes the upregulation of serine racemase, thereby constructing an Alzheimer's disease AD model. The verification method is WB, the primary antibody is serine racemase, if the model is successfully constructed, and contains a model containing D-type protein, then serine racemase is upregulated in the D-protein upregulation group.

[0130] Following the procedure in step 1, 30 μM Aβ was added 42 Amyloid protein was used as a protein treatment agent to prepare a D-protein up-regulation group and a blank group, and according to the above-mentioned "determination of different temperature points is specific", the most suitable temperature range was screened to be 37-67°C;

[0131] (2) Thermal proteomics TPP experiment

[0132] 1) One dish of cells from each of the D-protein up-regulation group and the blank group was collected and resuspended in 700 μL PBS buffer solution, and a protease inhibitor with a final volume concentration of 1% was added. After repeated freezing and thawing in liquid nitrogen three times, the cells were centrifuged at 10,0000 g for 30 min at 4°C, and the supernatant samples were collected;

[0133] 2) D- For the supernatant samples of the protein up-regulation group and the blank group, take 10 tubes of equal amount of protein solution, heat them at 37℃, 39℃, 42℃, 45℃, 49℃, 53℃, 57℃, 62℃, 65℃, and 67℃ for 3 min, then quickly cool them on ice for 4 min, then centrifuge them at 4℃ and 2,0000g for 15 min, take 30 μL of the supernatant in each EP tube and put them into ten new EP tubes;

[0134] 3) For each new EP tube, add the same volume of 16M urea to denature the protein solution, then add 100mM DTT to a final concentration of 10mM, and incubate at 37°C for 30min. Then add 200mM IAA to a final concentration of 50mM, incubate at room temperature in the dark for 30min, and finally add 100mM DTT to a final concentration of 10mM, incubate for 5min to complete the denaturation reduction alkylation;

[0135] 4) After the urea concentration in the solution was diluted to less than 1 M using a buffer solution PBS, a protease was added into the EP tube (the mass ratio of the protease to the soluble protein in the solution in the EP tube was 1:100) for enzymatic hydrolysis (the protease was Trypsin);

[0136] 5) The enzymatically hydrolyzed sample is centrifuged at 1,4000 g to obtain a peptide solution. After desalting (desalting can be performed using a desalting column), the peptide concentration is determined using a kit and freeze-dried for storage;

[0137] 6) The obtained peptide solutions were respectively redissolved in 0.1% (v / v) formic acid solution to obtain peptide analysis samples.

[0138] (3) DIA data collection and data analysis to obtain a list of proteins with differential thermal stability

[0139] Peptide analysis samples were analyzed by LC-MS / MS, using the data-independent acquisition DIA mode, liquid phase gradient elution program: 0-120min (3%-90% B), using the following gradient: 0-5min, 3-8% B, 5-75min, 8-18% B, 75-103min, 18-28% B, 103-115min, 28-90% B, 115-120min, 90-90% B. The mass spectrometer was operated by Xcalibur software, and the search software used DIANN. Data normalization was based on the amount of remaining protein in the supernatant corresponding to 37°C, removing the amount of remaining protein in the supernatant corresponding to other heating temperatures, and calculating the relative amount of remaining protein in the supernatant at different temperatures. The TPP R package was used to obtain a list of differentially thermally stable proteins.

[0140] (4) Heterogeneous Retrieval Cross-Validation

[0141] According to the isomerization search workflow described in step three, samples in the 37°C blank group and the D-protein up-regulation group were subjected to isomerization search to discover potential isomerization modifications and obtain a list of stereoisomerized proteins. The isomerization search results obtained were compared with the list of thermostability differentially expressed proteins, and the intersection was taken to screen out potential D-proteins. Relevant information including the number of isomerized modified peptides and isomer ratio was obtained, providing a basis for subsequent data analysis and research.

[0142] (5) APM enzyme (aminopeptidase) assisted D site verification

[0143] For the potential D protein obtained in (4), the D site was found with the assistance of APM enzyme. The D-protein up-regulated peptides obtained by APM digestion at 37°C were collected and analyzed using LC-MS. The mass spectrometry data was processed by Maxquant, and the peptide file was analyzed to find the corresponding D site when the amino acid before the N-terminus was not K or R following trypsin digestion. The data was analyzed to further explore the biological significance of protein isomeric modification and explore the association between protein isomeric modification and disease occurrence and development.

[0144] Experimental results and conclusions:

[0145] As attached Figure 2 (in Figure 2 A shows that 1424 proteins suitable for thermoproteomics analysis were obtained by LC-MSMS. Figure 2 B: Among the 1424 proteins, 464 proteins with changes in thermal stability were further screened using the TPP method. Figure 2 C is the reproducibility of two biological replicates of the TPP experiment. It can be seen that the reproducibility is very good, which shows the accuracy and reproducibility of the experiment. Figure 2 D-2G shows that 278 of the 464 proteins obtained have become more stable, with a ΔTm value range of 1.30±0.47°C; 186 proteins have become more unstable, with a ΔTm value range of -0.97±0.54°C. Among them, 2D is the S-type curve of 278 stable proteins, 2E is the change trend of their corresponding Tm; 2F is the S-type curve of 186 proteins with unstable change trends, and 2G is the trend of WT and SR+Tm changes). As shown in the figure, the present invention screened 464 proteins with potential changes in thermal stability from 1440 proteins of PC12 by TPP. The thermal stability of proteins obtained by this method has good reproducibility and consistent change trends. Among the 464 proteins that meet the screening conditions, 278 proteins have become more stable, with a ΔTm value range of 1.30±0.47°C; 186 proteins have become more unstable, with a ΔTm value range of -0.97±0.54°C.

[0146] Figure 3 (Figure 3 shows the results of heterogeneous search. Figure 3 A and Figure 3 D indicates that most of the chiral polypeptides in the WT group have two forms, ie, Isomer Number = 2. In addition to one all-L polypeptide, there is another isomer. Figure 3 B and Figure 3E is the ratio distribution diagram of the D-type Ratio of the polypeptide. Figure 3 C and Figure 3 F is the number of isomers of proteins analyzed. 65% of the proteins have only one polypeptide undergoing isomerization. ) is the result of screening the D-protein up-regulation group for isomerization search. The D-protein up-regulation group is two groups of biological repeats. Through analysis, the present invention found that the Isomer number of most polypeptides is 2, that is, there is only one isomer after removing the full L-type polypeptide. At the same time, the isomerized proteins were further processed, and 65% of the proteins had only one polypeptide undergoing isomerization.

[0147] Figure 4 ( Figure 4 It is the result obtained after searching and communicating the proteins and isomers obtained by TPP. Figure 4 A is the final intersection of 194 proteins. The number of interfering proteins was significantly reduced, indicating that protein isomerization would change thermal stability, further proving that protein thermal stability analysis has good selectivity for isomerized proteins, which can greatly reduce interference and improve the sensitivity of target protein identification. 3B results show that there is a positive correlation between the number of isomerized peptides and |ΔTm|. 3C results show that there is a positive correlation between the ratio of protein isomerization and |ΔTm|. 3D-3F: In-depth analysis of the biological processes and pathways of these 194 proteins. The results showed that pathways related to nervous system diseases, such as Parkinson's disease, were significantly upregulated, indicating that stereoisomerization may be closely related to nervous system diseases and may play a role in the pathogenesis of related diseases. These findings may help to further understand the association between stereoisomerization-modified proteins and nervous system diseases, and provide important insights and research directions for further research and treatment of nervous system-related diseases. ) The result is the result of taking the intersection of the results obtained by TPP screening and the isomer search results. Finally, 194 potential D-proteins were obtained, and the number of interfering proteins was significantly reduced, indicating that protein isomerization would change thermal stability, further proving that protein thermal stability analysis has good selectivity for isomerically modified proteins, which can greatly reduce interference and improve the sensitivity of target protein identification. The results showed that there was a positive correlation between the number of isomerized peptides and the isomer ratio of proteins and |ΔTm|. The biological processes and pathways of these 194 proteins were deeply analyzed. The results showed that pathways related to nervous system diseases, such as Parkinson's disease, were significantly upregulated, indicating that stereoisomeric modification may be closely related to nervous system diseases and may play a role in the pathogenesis of related diseases. These findings may help to deeply understand the association between stereoisomeric modified proteins and nervous system diseases, and provide important insights and research directions for further research and treatment of nervous system-related diseases.

[0148] Figure 5 ( Figure 5 To verify the isomeric site information by APM enzyme. This application adds GFFD and NdWFa standard polypeptides to the omics polypeptide to determine whether the enzyme is active. 5A shows that the enzyme activity of APM is normal. This application found that GFFD was cut by APM, indicating that the enzyme was active. 5B and 5C are methods for screening sites. By comparing the amount of polypeptides before and after, we finally obtained the sites of 1045 polypeptides. 5D is an arrangement of the sites where isomerization occurs, and the top five D-sites are: leucine, alanine, valine, glutamic acid, isoleucine and serine. ) To verify the isomeric site information by APM enzyme, this invention adds GFFD and NdWFa standard polypeptides to the omics polypeptide to determine whether the enzyme is active. Through experimental results, we found that GFFD was cut by APM, indicating that the enzyme was active. Screening by APM, the present invention finally obtained the sites of 1045 polypeptides, and the top five D-sites are: leucine, alanine, valine, glutamic acid, isoleucine and serine.

[0149] Table 1 shows the five isomeric modified proteins discovered by the present invention and their isomeric related information, including isomeric polypeptides and isomeric sites. Both verification methods show that thermoproteomics is indeed very selective for isomeric modified proteins, and is applicable to proteins with large and small changes in thermal stability, which can greatly reduce background interference and false negative rate, and improve the accuracy and selectivity of isomeric modified protein identification.

[0150] Table 1 shows the partial protein information of D-site of APM enzyme verification.

[0151]

[0152] The number of devices and processing scales described here are used to simplify the description of the present invention. Applications, modifications and variations of the present invention are obvious to those skilled in the art. Although the embodiments of the present invention have been disclosed as above, they are not limited to the applications listed in the specification and the implementation mode. They can be applied to various fields suitable for the present invention. For those familiar with the art, other modifications can be easily realized. Therefore, without departing from the general concept defined by the claims and the equivalent scope, the present invention is not limited to the specific details and the legends shown and described here.

Claims

1. A D-protein scale screening method based on thermoproteomics technology, characterized in that: include: Step 1: Adding a protein treatment agent to the cells and not adding a protein treatment agent to the cells respectively to obtain a D-protein up-regulation group and a blank group; specifically: taking cells in the logarithmic growth phase, culturing them until the cells adhere to the wall, and dividing them into two groups, adding 30 μM protein treatment agent to one group to obtain a D-protein up-regulation group, and not adding a protein treatment agent to the other group to obtain a blank group; Step 2: Based on the D-protein up-regulated group and the blank group, the thermoproteomics technology was used to obtain a list of differentially thermally stable proteins, specifically: S201, suspending the D-protein up-regulation group and the blank group in a buffer solution, respectively, then adding a protease inhibitor to the buffer solution, repeatedly freezing and thawing with liquid nitrogen three times, and centrifuging to collect the first supernatant to obtain a D-protein up-regulation group protein solution and a blank group protein solution, respectively; S202, dividing the D-protein up-regulating histone solution / blank histone solution equally into a plurality of test tubes, placing the plurality of test tubes at different temperatures for heat treatment, and centrifuging each heat-treated test tube to collect a second supernatant; S203, denaturing each second supernatant with urea, and then alkylating each second supernatant with DTT and IAA, enzymatically hydrolyzing each second supernatant after the denaturation and alkylation treatment, collecting the peptide segment solution by centrifugation, and redissolving it in a formic acid solution after desalting to obtain a peptide analysis sample; S204, performing LC-MS / MS detection and analysis on each polypeptide analysis sample, collecting a proteomics data set, and sequentially using TPP data analysis and a non-parametric data analysis method of a response curve to analyze the proteomics data set to obtain a list of proteins with differential thermal stability; Step 3: Use isomerization search technology to obtain a list of stereoisomerized proteins, specifically: S301, acquiring conformation-resolved proteomics data corresponding to the lowest temperature from the proteomics data set acquired in step S204, including retention time information, tandem mass spectrometry information, collision cross-sectional area, and stereoisomer signal response intensity of stereoisomer polypeptides of the same amino acid sequence; S302, extracting features of the amino acid sequence in the conformation-resolved proteomics data by searching a data set generated by a protein database to obtain multiple feature data of the protein sample, so as to establish a feature set for isomerization modification retrieval of the protein sample, wherein each feature data includes a protein name, an amino acid sequence, a chromatographic retention time, a charge, a signal response intensity, a mass-to-charge ratio, and a secondary mass spectrum; S303. For the characteristic data under the same amino acid sequence, delete the data with a retention time difference of less than 2 min and / or a collision cross-sectional area difference of less than 1.5%, and obtain a list of stereoisomer proteins; Step 4: Compare and analyze the list of proteins with different thermal stability obtained in step 2 with the list of stereoisomer proteins obtained in step 3, and take the intersection of the two to obtain potential D-proteins; Step 5: Based on the APM enzyme cleavage technology, obtain the D site of the potential D-protein obtained in step 4.

2. The D-protein large-scale screening method based on thermoproteomics technology according to claim 1, characterized in that: Step 5 is as follows: the potential D-protein obtained in step 4 is digested with aminopeptidase, LC-MS / MS is used for omics data collection and analysis, the mass spectrometry data is processed by MaxQuant, the peptide file is analyzed, and the corresponding D site is found.

3. The D-protein large-scale screening method based on thermoproteomics technology according to claim 1, characterized in that: The buffer solution in step S201 is a PBS buffer solution.

4. The D-protein large-scale screening method based on thermoproteomics technology according to claim 1, characterized in that: The denaturation alkylation treatment of the second supernatant in step S202 is specifically as follows: add the same volume of 16 M urea to the second supernatant to denature the protein solution, then add 100 mM DTT to a final concentration of 10 mM, incubate at 37°C for 30 min, then add 200 mM IAA to a final concentration of 50 mM, incubate at room temperature in the dark for 30 min, then add 100 mM DTT to a final concentration of 10 mM, and incubate for 5 min.

5. The D-protein large-scale screening method based on thermoproteomics technology according to claim 1, characterized in that: In step S203, trypsin is added to perform enzymatic hydrolysis on each second supernatant after the denaturation alkylation treatment, and the mass ratio of trypsin to soluble protein in the second supernatant after the denaturation alkylation treatment is 1:

100.

6. The D-protein large-scale screening method based on thermoproteomics technology according to claim 1, characterized in that: Step S202 is specifically as follows: the D-protein up-regulation histone solution / blank histone solution is evenly divided into 10 test tubes, and the tubes are heated at 37°C, 39°C, 42°C, 45°C, 49°C, 53°C, 57°C, 62°C, 65°C, and 67°C for 3 min, respectively, and then quickly cooled in an ice water bath for 4 min, and then centrifuged at 4°C and 20,000 g for 15 min to collect the second supernatant.

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