A method for accurate identification of polypeptides in proteomic samples based on heavy isotope technology

Abstract

The present application provides a heavy-labeled polypeptide database. The present application also provides a method for constructing the heavy-labeled polypeptide database. The present application further provides a method for accurately identifying polypeptides in a proteomic sample based on heavy-labeled isotope technology. The present application provides a method for accurately identifying polypeptides in a proteomic sample based on heavy-labeled isotope technology, which further confirms the identification information of light-labeled polypeptides by the identification information of heavy-labeled polypeptides, thereby improving the accuracy of the identification results of polypeptides in the sample.

Description

Technical Field

[0001] This invention belongs to the technical field of peptide identification in proteomics based on mass spectrometry, and relates to an accurate identification method for peptides in proteomics samples based on relabeled isotope technology. Specifically, it relates to an accurate identification method for peptides in proteomics samples by combining relabeled isotope labeling technology with a relabeled isotope peptide database. Background Technology

[0002] Classical mass spectrometry proteomics identification techniques are based on peptide identification. This involves digesting protein samples with specific enzymes (such as trypsin) to form peptides, then using mass spectrometry to acquire data from the peptide samples, and finally using relevant software to analyze the acquired data.

[0003] There are two main challenges in peptide identification: 1. The peptide samples are extremely complex; 2. Some peptides have very low abundance. When different peptides are simultaneously detected by mass spectrometry, they may interfere with each other, such as suppressing ion peaks (in Orbitrap-type mass spectrometers, in the same mass spectrum, a peptide with a strong signal can suppress the signal of a peptide with a similar mass-to-charge ratio but a weaker signal). During DIA data acquisition, fragment ions of peptides with very similar mass-to-charge ratios and retention times may also interfere with each other, thus affecting qualitative and quantitative analysis. These interferences occur more frequently when the peptide types are very complex. In addition, some peptides have very low abundance. In this case, the peptide signal intensity is very weak and easily buried by noise. Coupled with the possibility that the mass spectrometry sensitivity is insufficient, the detection efficiency of low-abundance peptides is low.

[0004] With the development of mass spectrometry-based proteomics technology, the Discrete-Anatomical (DIA) acquisition mode has gradually become the preferred mode for proteomics data acquisition using mass spectrometry equipment, and data analysis software based on the DIA format has also gradually become mainstream. In DIA acquisition mode, the mass spectrometer needs to acquire data on all peptides within a certain m / z range in a single scan. During the acquisition process, these peptides simultaneously enter the collision chamber and are broken down, with all fragments being acquired simultaneously in a single mass spectrum. Therefore, the mass spectrum of DIA is more complex, has more interference, is more difficult to interpret, and has a higher false positive rate than that of the earlier classic Discrete-Anatomical (DDA) acquisition mode.

[0005] Another significant reason for the high false positive rate in DIA data stems from the database used. Early DIA data analysis first used DDA data acquisition mode to comprehensively identify peptides in the sample, obtaining information such as retention time and fragment ion characteristics. This information was then compiled into a database, which was used to analyze the data acquired in DIA mode. While this method was relatively reliable due to the use of DDA identification data, its workload was substantial, and the number of proteins that could be identified was relatively limited. Therefore, this method was gradually replaced by Library-Free mode. In Library-Free mode, DDA identification data is no longer used as the database; instead, FASTA data (which only includes the protein species of the species and the theoretical amino acid sequence information for each protein) is used. The software predicts potential peptides based on the FASTA database, and the predicted peptide information is used as the database to analyze the data acquired in DIA mode. This purely predictive approach greatly improves efficiency and reduces workload, but it also increases the false positive rate, especially for low-abundance peptides with weak signals, strong noise, and insufficient fragment ion abundance.

[0006] The foregoing background information is intended to help those skilled in the art understand prior art that is similar to the present invention, and to facilitate the understanding of the inventive concept and technical solution of this application. It should be clearly stated that, in the absence of clear evidence that the above content was disclosed before the filing date of this patent application, the foregoing background information should not be used to evaluate the novelty of the technical solution of this application. Summary of the Invention

[0007] In view of the shortcomings of the prior art described above, the purpose of this invention is to provide an accurate identification method for peptides in proteomic samples based on relabeled isotope technology. By mixing a pre-prepared relabeled peptide mixture with the sample to be tested and then collecting data, the identification information of the relabeled peptides is used to further confirm the identification information of the lightly labeled peptides, thereby improving the reliability of peptide identification results in the sample and achieving more accurate identification and quantification of peptides in proteomics.

[0008] To achieve the above and other related objectives, the first aspect of the present invention provides a relabeled peptide database, wherein the data in the relabeled peptide database meets at least one of the following screening criteria: 1) In the polypeptide spectrum, the total number of detected peptide bond break sites exceeds 30% of the total number of peptide bonds in the polypeptide; 2) The isotope peaks in the primary spectrum match the theoretical values ​​by more than 80%; 3) The noise peaks in the secondary spectrum account for less than 10%; 4) The number of matched fragment ions is more than 4; 5) The average mass error is less than 30 ppm.

[0009] A second aspect of the present invention provides a method for constructing a relabeled peptide database, comprising: detecting a relabeled isotope-labeled peptide sample using liquid chromatography-mass spectrometry in a first data acquisition mode, wherein the obtained detection data meets the screening criteria for data in the relabeled peptide database provided in the first aspect of the present invention, and is included to constitute the relabeled peptide database.

[0010] The third aspect of this invention provides an accurate identification method for peptides in proteomic samples based on relabeled isotope technology, comprising: mixing the sample to be tested with a relabeled peptide sample to obtain a mixed peptide (HL Mix), detecting the mixed peptide using liquid chromatography-mass spectrometry in a second data acquisition mode, matching the obtained detection data with peptide feature signals of the same amino acid sequence in a lightly labeled peptide database and a relabeled peptide database provided in the first aspect of this invention, comparing the retention times of the matched peptide feature signals, and determining the presence of a certain peptide in the sample to be tested when the retention times (RT) are consistent.

[0011] As described above, the present invention provides an accurate method for identifying peptides in proteomic samples based on relabeled isotope technology, which has the following beneficial effects: (1) The present invention provides an accurate identification method for peptides in proteomic samples based on relabeled isotope technology. On the basis of traditional analysis methods, it provides an additional dimension to verify the authenticity of peptides obtained by traditional analysis methods. It gives more reliable scores to truly identified peptides and provides risk warnings for peptides that the software considers reliable but whose authenticity is questionable.

[0012] (2) The present invention provides an accurate identification method for peptides in proteomic samples based on relabeling isotope technology, which can improve the reliability of some peptides in proteomic samples, especially for some low-abundance proteins, where only one peptide is often identified. If the peptide is verified as a high-confidence peptide, the identification of the protein will be more reliable. Conversely, if only one peptide is identified in some low-abundance proteins, but the retention time obtained by relabeling and unlabeling of this peptide differs significantly, the identification of the protein may not be reliable and additional experiments are needed to verify it.

[0013] (3) This invention provides an accurate identification method for peptides in proteomic samples based on relabeled isotope technology. This method uses relabeled isotope labeling technology combined with a relabeled isotope peptide database to accurately identify proteomic samples. By utilizing a mixture of relabeled isotope-labeled peptides and its accompanying high-quality secondary spectra library, both lightly labeled and heavily labeled peptides are simultaneously identified in the lightly and heavily labeled mixed samples. Based on the chemical property that the lightly labeled and heavily labeled forms of peptides must be consistent in the retention time dimension, the retention time of the lightly labeled form and the retention time of the heavily labeled form of the same peptide in the identification results are compared, thereby achieving the effect of verifying the reliability of the lightly labeled peptide through the heavily labeled peptide. The identification work of this method is first based on the traditional identification process, obtaining the same identification results as the traditional identification process. Then, based on the traditional identification method, a secondary confirmation of the retention time dimension of the heavily labeled peptide is provided for some peptides. This improves the overall accuracy of peptide identification and quantification to a certain extent. Attached Figure Description

[0014] Figure 1a The image shown is a high-quality secondary spectrum from this invention.

[0015] Figure 1b The image shown is a low-quality secondary spectrum from this invention.

[0016] Figure 2 The diagram shows the ion chromatograms of the polypeptide with the sequence NFINNPLAQADWAAK analyzed in Example 1 of the present invention. The upper diagram shows the ion chromatogram of the polypeptide in its light-labeled form, and the lower diagram shows the ion chromatogram of the polypeptide in its heavy-labeled form.

[0017] Figure 3 The diagram shows the ion chromatograms of the polypeptide with the sequence GHDLNEDGLVSWEEYK analyzed in Example 1 of the present invention. The upper left image is the ion chromatogram for identifying the polypeptide with light-labeled signals, the lower left image is the ion chromatogram for identifying the polypeptide with heavy-labeled signals, and the right image is the high-quality spectrum information diagram of the corresponding heavy-labeled polypeptide spectrum library.

[0018] Figure 4 The diagram shows the ion chromatograms of the polypeptide with the sequence ILIDSIYK analyzed in Example 2 of the present invention. The upper left image is the ion chromatogram for identifying the polypeptide with light-labeled signals, the lower left image is the ion chromatogram for identifying the polypeptide with heavy-labeled signals, and the right image is the high-quality spectrum information diagram of the corresponding heavy-labeled polypeptide spectrum library. Detailed Implementation

[0019] The inventors of this application have developed an accurate method for identifying peptides in proteomic samples based on relabeled isotope technology, which is described in detail below.

[0020] The first aspect of this invention provides a relabeled peptide database, wherein the data in the relabeled peptide database meets at least one of the following screening criteria: 1) In the polypeptide spectrum, the total number of detected peptide bond break sites exceeds 30% of the total number of peptide bonds in the polypeptide; 2) The isotope peaks in the primary spectrum match the theoretical values ​​by more than 80%; 3) The noise peaks in the secondary spectrum account for less than 10%; 4) The number of matched fragment ions is more than 4; 5) The average mass error is less than 30 ppm.

[0021] In condition 1) above, the total number of detected peptide bond breakage sites in the polypeptide spectrum exceeds 50% of the total number of peptide bonds in the polypeptide.

[0022] Under condition 2) above, the isotope peaks in the first-order spectrum match the theoretical values ​​by more than 90%.

[0023] In condition 4) above, among the number of matched fragment ions, there are more than 3 strong response fragment ions with an intensity index exceeding 30K and more than 6 relatively strong response fragment ions with an intensity index exceeding 10K.

[0024] In condition 5) above, the mean mass error is less than 20 ppm.

[0025] The aforementioned relabeled peptide database enables more accurate identification of relabeled peptides. The number of relabeled peptides that can be identified in a single study can range from several thousand to tens of thousands, depending on the sample type.

[0026] The mass error mentioned above refers to the degree of deviation between the measured accurate mass-to-charge ratio and the theoretical accurate mass-to-charge ratio.

[0027] The intensity index mentioned above refers to the intensity of the ion signal.

[0028] A second aspect of the present invention provides a method for constructing a relabeled peptide database, comprising: detecting a relabeled isotope-labeled peptide sample using liquid chromatography-mass spectrometry in a first data acquisition mode, wherein the obtained detection data meets the screening criteria for data in the relabeled peptide database provided in the first aspect of the present invention, and is included to constitute the relabeled peptide database.

[0029] In the above method, the relabeled isotope-labeled polypeptide sample is obtained by using SILAC culture technology to obtain a relabeled isotope-labeled protein sample, which is then digested with enzymes. The relabeled isotope-labeled polypeptide sample is obtained by introducing stable isotope amino acids into a cell culture system, labeling them, extracting the label, and then cleaving them with a protease.

[0030] Specifically, the SILAC (Stable isotope labeling using amino acids in cell culture) culture technique is the conventionally used SILAC culture technique, which involves using relabeled amino acids for stable isotope labeling in cell culture. The cell culture system is a mixed culture of at least two different cell lines.

[0031] In one embodiment, the SILAC culture technique involves culturing cells for at least seven generations, with a cell passage ratio of 1:1 to 1:3, preferably 1:2. This ensures that the relabeling efficiency of the final relabeled peptide is approximately 99%.

[0032] In one embodiment, the SILAC culture technique involves culturing and then mixing cells from 3 to 5 different cell lines to ensure that the sample contains as many types of proteins as possible.

[0033] In a preferred embodiment, the cell lines include, but are not limited to, various human cell lines such as HEK 293T, HEK293, hela, HepG2, A549, MCF-7, Huh-7, NCI-H1299, PC-9, MDA-MB-231, K562, Jurkat, and HCT-116.

[0034] In a more preferred embodiment, the cell line is selected from one or more human cell lines selected from HEK 293T, HEK293, hela, HepG2, A549, MCF-7, Huh-7, NCI-H1299, PC-9, MDA-MB-231, K562, Jurkat, and HCT-116.

[0035] In a further preferred embodiment, the cell line is selected from one or more human cell lines selected from HEK293, hela, HepG2, A549, and MCF-7.

[0036] Specifically, reductive alkylation is performed before enzyme digestion. This reductive alkylation ensures that the disulfide bonds are opened and then blocked, ensuring adequate identification of the peptide.

[0037] In one embodiment, the reductive alkylation involves reducing cellular proteins with a dithiothreitol solution followed by alkylation with an iodoacetamide solution.

[0038] In a preferred embodiment, the ratio of the added cellular protein (in μg) to the added dithiothreitol solution (in μmol) is 150-250:4, preferably 200:4.

[0039] In a preferred embodiment, the ratio of the added cellular protein (in μg) to the added iodoacetamide solution (in μmol) is 150-250:10, preferably 200:10.

[0040] In a preferred embodiment, the dithiothreitol solution is an aqueous solution of dithiothreitol with a final molar concentration of 20-60 mmol / L (mM), preferably 40 mmol / L.

[0041] In a preferred embodiment, the iodoacetamide solution is an aqueous solution of iodoacetamide with a final molar concentration of 80-120 mmol / L (mM), preferably 100 mmol / L.

[0042] Specifically, the enzymatic digestion refers to the digestion of proteins using enzymes.

[0043] In one embodiment, the mass ratio of the enzyme to the protein is 1:5 to 1:200, preferably 1:50.

[0044] In one embodiment, the enzyme is selected from one or more of trypsin, Glu-C, chemotrypsin, Asp-N, and Lys-C.

[0045] In a preferred embodiment, the trypsin is a conventionally used trypsin, preferably Promega sequencing-grade trypsin. The preferred trypsin has the advantages of reliability and stability, enabling stable acquisition of the target polypeptide.

[0046] In one embodiment, the enzyme digestion time is 1-12 hours, preferably 8-12 hours, and more preferably 10-12 hours. The enzyme digestion process can be carried out overnight.

[0047] In the above method, before the relabeled isotope-labeled peptide samples are detected by liquid chromatography-mass spectrometry in the first data acquisition mode, high-pH reverse-phase fractionation is performed by liquid chromatography. Before constructing the relabeled peptide spectral library, the relabeled isotope peptide samples may be subjected to liquid chromatography fractionation as appropriate.

[0048] In one embodiment, the liquid chromatograph is a conventional nanoliter ultra-high performance liquid chromatograph, preferably a Vanquish Neo UHPLC system operated Neo UHPLC system (manufactured by Thermo Scientific).

[0049] In one embodiment, the high pH reversed-phase fractionation processing conditions are as follows: the number of groups is 2-1000; the chromatographic column is a C18 column tolerant to high pH conditions, preferably a C18 column with the product name ChromCore 120 (length 15cm × inner diameter 4.6mm, particle size 5μm); the column temperature is 20-60℃, preferably 25℃; the injection volume is 1-1000μL, preferably 200μL; the flow rate is 200nL-1.2mL / min, preferably 1mL / min; mobile phase A is a mixed solution of water, acetonitrile, and ammonia, preferably 980ml water, 20mL acetonitrile, and 280μL 26% ammonia; mobile phase B is a mixed solution of water, acetonitrile, and ammonia, preferably 100mL water, 900mL acetonitrile, and 480μL 26% ammonia; the analysis time is 10min-300min, preferably 130min; gradient elution.

[0050] In the mobile phases A and B described above, the water is chromatographic grade pure water, and the acetonitrile is chromatographic grade acetonitrile. The 26% ammonia solution is ammonia solution with a mass fraction of 26%.

[0051] The specific procedure for gradient elution is a process where phase A is eluted from low to high. Specifically, the gradient elution involves eluting phase A from low to high and then lowering it to achieve equilibration.

[0052] In a preferred embodiment, the specific procedure for gradient elution is as follows: From 0 to 10 min, the volume ratio of phase A to phase B was 97.6~98.4:1.6~2.4 - 96.6~97.4:2.6~3.4; 10-10.01 min, the volume ratio of phase A to phase B is 96.6~97.4:2.6~3.4-94.5~95.5:4.5~5.5; 10.01-90 min, the volume ratio of phase A: phase B is 94.5~95.5:4.5~5.5-79~81:19~21; 90-105 min, the volume ratio of phase A to phase B is 79~81:19~21-69~71:29~31; 105-113 min, the volume ratio of phase A to phase B is 69~71:29~31-29~31:69~71; 113-118 min, the volume ratio of phase A to phase B is 29~31:69~71; 118-118.01 min, the volume ratio of phase A to phase B is 29~31:69~71-9~11:89~91; 118.01-125 min, the volume ratio of phase A to phase B is 9~11:89~91-9~11:89~91; 125-125.01 min, the volume ratio of phase A to phase B is 9~11:89~91-97.6~98.4:1.6~2.4; 125.01-300 min, the volume ratio of phase A to phase B is 97.6~98.4:1.6~2.4-97.6~98.4:1.6~2.4.

[0053] In a further preferred embodiment, the specific procedure for gradient elution is shown in Table 1, as follows: 0-10 min, the volume ratio of phase A: phase B is 98:2-97:3; 10-10.01 min, the volume ratio of phase A to phase B is 97:3-95:5; 10.01-90 min, the volume ratio of phase A to phase B is 95:5-80:20; 90-105 min, the volume ratio of phase A to phase B is 80:20-70:30; 105-113 min, the volume ratio of phase A to phase B is 70:30-30:70; 113-118 min, the volume ratio of phase A to phase B is 30:70-30:70; 118-118.01 min, the volume ratio of phase A to phase B is 30:70-10:90; 118.01-125 min, the volume ratio of phase A to phase B is 10:90-10:90; 125-125.01 min, the volume ratio of phase A to phase B is 10:90-98:2; 125.01-130 min, the volume ratio of phase A to phase B is 98:2-98:2.

[0054] In a preferred embodiment, the high-pH reverse-phase fractionation of the relabeled isotope-labeled polypeptide sample further requires desiccation and reconstitution.

[0055] In a further preferred embodiment, the drying process is vacuum drying.

[0056] In a further preferred embodiment, the solvent for resolution is a 0.09-0.11 v / v% formic acid aqueous solution, preferably a 0.1 v / v% formic acid aqueous solution.

[0057] In a further preferred embodiment, the volume of the reconstitution is 190-210 μL, preferably 200 μL.

[0058] The high-pH reverse-phase fractionation process described above can fractionate the obtained relabeled peptide samples, collect DDA data of the peptides in each fractionated fraction, and collect one fraction every minute during the peptide elution phase, thereby improving the quality of the peptide secondary spectrum and the efficiency of peptide identification.

[0059] In the above method, the liquid chromatography-mass spectrometry method in the first data acquisition mode is to perform separation by liquid chromatography and then detect by mass spectrometry in the data acquisition mode.

[0060] In one embodiment, the data acquisition mode is selected from any one of data-dependent acquisition (DDA), data-independent acquisition (DIA), or parallel response monitoring (PRM) modes.

[0061] In a preferred embodiment, the DDA (data dependent acquisition) mode is a data-dependent acquisition mode commonly used in mass spectrometry detection.

[0062] In a preferred embodiment, the DIA (data independent acquisition) mode is a conventionally used mass spectrometry data acquisition mode that is independent of the data source. The DIA mode is a mass spectrometry data acquisition mode commonly used in routine analytical procedures.

[0063] In a preferred embodiment, the PRM mode is a conventional mass spectrometry data parallel reaction monitoring and acquisition mode.

[0064] The spectra of the relabeled peptide database are obtained from relabeled peptide spectra based on DDA, DIA, or PRM data acquisition and data analysis.

[0065] In the above method, the liquid chromatography-mass spectrometry method uses a conventional liquid chromatograph, preferably a Vanquish Neo UHPLC system (manufactured by Thermo Scientific).

[0066] In the above method, the detection conditions for liquid chromatography-mass spectrometry are as follows: the chromatographic column is a C18 column, preferably a ThermoFisher ES906 EASY-SPRAY series PEPMAP RSLC. C18 column (inner diameter 15cm × 150μm, particle size 2μm); column temperature 30-70℃, preferably 50℃; injection volume 50-500ng, preferably 300ng; flow rate 0.8-2.5mL / min, preferably 2.0mL / min; mobile phase A is 0.01-1% formic acid aqueous solution, preferably 0.1% formic acid aqueous solution; mobile phase B is 0.01-1% formic acid acetonitrile aqueous solution (acetonitrile to water volume ratio 70-30:99.9-0.1), preferably 0.1% formic acid acetonitrile aqueous solution (acetonitrile to water volume ratio 80:20); analysis time 3-90min, preferably 22.6min; gradient elution.

[0067] The specific procedure for gradient elution is a process where phase A is eluted from low to high. Specifically, the gradient elution involves eluting phase A from low to high and then lowering it to achieve equilibration.

[0068] In a preferred embodiment, the specific procedure for gradient elution is as follows: 0-0.5 min, flow rate 1.3 μL / min, A phase:B phase volume ratio 95~97:3~5-95~97:3~5; The flow rate changed from 1.3 μL / min to 0.8 μL / min over a period of 0.5-0.6 min, and the volume ratio of phase A to phase B was 95-97:3-91.8-92.2:7.8-8.2. 0.6-0.9 min, flow rate of 0.8 μL / min, A phase:B phase volume ratio of 91.8~92.2:7.8~8.2-91.3~91.7:8.3~8.7; 0.9-13.9 min, flow rate of 0.8 μL / min, A phase:B phase volume ratio of 91.3~91.7:8.3~8.7-77~78:22~23; 13.9-20.8 min, flow rate of 0.8 μL / min, A phase:B phase volume ratio of 77~78:22~23-64~66:34~36; From 20.8 to 21.2 min, the flow rate changed from 0.8 μL / min to 2.5 μL / min, and the volume ratio of phase A to phase B was 64~66:34~36-44~46:54~56; 21.2-21.7 min, flow rate 2.5 μL / min, A phase:B phase volume ratio 44~46:54~56-0.5~1.5:98.5~99.5; 21.7-90 min, flow rate 2.5 μL / min, A phase:B phase volume ratio 0.5~1.5:98.5~99.5-0.5~1.5:98.5~99.5.

[0069] In a further preferred embodiment, the specific procedure for gradient elution is shown in Table 2, as follows: 0-0.5 min, flow rate of 1.3 μL / min, A phase:B phase volume ratio of 96:4-96:4; The flow rate changed from 1.3 μL / min to 0.8 μL / min over a period of 0.5-0.6 min, and the volume ratio of phase A to phase B was 96:4-92:8. 0.6-0.9 min, flow rate of 0.8 μL / min, A phase:B phase volume ratio of 92:8-91.5:8.5; The flow rate was 0.8 μL / min, and the volume ratio of phase A to phase B was 91.5:8.5-77.5:22.5. 13.9-20.8 min, flow rate of 0.8 μL / min, A phase:B phase volume ratio of 77.5:22.5-65:35; From 20.8 to 21.2 min, the flow rate changed from 0.8 μL / min to 2.5 μL / min, and the volume ratio of phase A to phase B was 65:35-45:55; 21.2-21.7 min, flow rate of 2.5 μL / min, A phase:B phase volume ratio of 45:55-1:99; 21.7-22.6 min, flow rate 2.5 μL / min, A phase:B phase volume ratio 1:99-1:99.

[0070] In the above method, the liquid chromatography-mass spectrometry method uses a conventionally used mass spectrometer, such as the Pro / Pro2 / HT model timsTOF mass spectrometer and the Astral, Astral Zoom model Orbitrap combined with TOF mass spectrometer, preferably the Astral model Orbitrap combined with TOF mass spectrometer.

[0071] In the above method, the detection conditions for the liquid chromatography-mass spectrometry method are shown in Table 3.

[0072] In one embodiment, the detection conditions for the mass spectrometry are shown in Table 4.

[0073] In the above method, the detection data meeting the screening criteria of the relabeled peptide database are analyzed using PD, MaxQuant software, PEAKS Studio 12, Thermo Proteome Discoverer, Scaffold DDA, Skyline, phenyx, MHCquant, or other proteomics DDA analysis software. Specifically, the PD software is Proteome Discoverer Software developed by Thermo Fisher Scientific. The MaxQuant software is a proteomics analysis software developed by Max Planck Institute for Biochemistry.

[0074] In the above method, the detection data is peptide secondary spectrum information.

[0075] In the above method, the identification parameters for constructing the relabeled peptide database also include precursor ion parameters and fragment ion parameters. The relabeled peptide database is constructed by reviewing the identification parameters to remove secondary spectra with low confidence and retain high-quality, high-confidence secondary spectra. High-quality and low-quality secondary spectra are shown below. Figure 1a , Figure 1b .

[0076] In one embodiment, the precursor ion parameter is selected from at least one of the following: precursor ion modification status, precursor ion amino acid quantity, whether the precursor ion is a unique sequence, precursor ion signal intensity, precursor ion isotope peak distribution, and precursor ion different valence state distribution.

[0077] In a preferred embodiment, the identification of the parent ion modification requires selection from at least one of oxidation, acetylation, phosphorylation, and acetamination.

[0078] In a preferred embodiment, the number of parent ion amino acids is 5-40 amino acids.

[0079] In a preferred embodiment, whether the precursor ion is a unique sequence refers to confirming whether the precursor ion is a unique sequence.

[0080] In a preferred embodiment, the mother ion signal intensity refers to the specific signal intensity of the mother ion.

[0081] In a preferred embodiment, the distribution of the parent ion isotope peaks refers to the specific distribution of the parent ion isotope peaks, which can be shown on the spectrum.

[0082] In a preferred embodiment, the identification requirement for the different valence states of the parent ion is 2-4 valence states.

[0083] In one embodiment, the fragment ion parameters are selected from at least one of the following: fragment ion type, fragment ion molecular weight distribution, fragment ion relative intensity distribution, consistency of fragment ions with the same parent ion in different valence states, b-ion identification, y-ion identification, fragment ion neutral loss, proportion of fragment ions not identified but expected to exist, and fragment ion signal intensity.

[0084] In a preferred embodiment, the identification requirements for the fragment ion species are b ions, y ions, and the corresponding dehydration peak fragment ions.

[0085] In a preferred embodiment, the molecular weight distribution of the fragment ions is required to be 50-2000, preferably 100-1500.

[0086] In a preferred embodiment, the relative intensity distribution of fragment ions refers to the distribution of the relative intensity of conventional fragment ions.

[0087] In a preferred embodiment, the requirement for identifying the consistency of fragments of the same parent ion with different valence states is that the consistency of fragments of the same parent ion with different valence states reaches more than 60%.

[0088] In a preferred embodiment, the requirement for identifying the b-ion is a mass deviation of less than 10 ppm.

[0089] In a preferred embodiment, the requirement for identifying the gamma ion is a mass deviation of less than 10 ppm.

[0090] In a preferred embodiment, the identification requirement for the neutral loss of fragment ions is a mass deviation of less than 10 ppm and the presence of a non-neutral loss peak.

[0091] In a preferred embodiment, the requirement for the proportion of unidentified but expected fragment ions is that the proportion is less than 50%.

[0092] In a preferred embodiment, the requirement for identifying the fragment ion signal intensity is greater than 300 for Tims TOF mass spectrometers such as Pro / Pro2 / HT, and greater than 1000 for Orbitrap-type mass spectrometers such as Astral.

[0093] In the above method, the inclusion criteria for the relabeled peptide database are based on the mass spectra of the relabeled peptides obtained through data analysis. All relabeled peptide mass spectra are screened, and spectra that meet the screening criteria are included in the database. Spectra that do not meet the screening criteria, even if identified as reliable peptides by the software, are not included in the database. In other words, based on software identification, a more stringent standard is used to include only high-quality peptide spectra.

[0094] The third aspect of this invention provides an accurate identification method for peptides in proteomic samples based on relabeled isotope technology, comprising: mixing the sample to be tested with a relabeled peptide sample to obtain a mixed peptide (HL Mix), detecting the mixed peptide using liquid chromatography-mass spectrometry in a second data acquisition mode, matching the obtained detection data with peptide feature signals of the same amino acid sequence in a lightly labeled peptide database and a relabeled peptide database provided in the first aspect of this invention, comparing the retention times of the matched peptide feature signals, and determining the presence of a certain peptide in the sample to be tested when the retention times (RT) are consistent.

[0095] In the above method, the sample to be tested is a polypeptide sample after enzymatic digestion of the sample to be tested in the experiment.

[0096] In one implementation, when there are a large number of samples to be tested, a pooled sample of the samples to be tested needs to be constructed.

[0097] In a preferred embodiment, the mixing process involves vortexing for 5-15 seconds, preferably 10 seconds, to achieve uniform mixing.

[0098] In the above method, the mixing mass ratio of the relabeled polypeptide sample to the test sample is selected from any one of 1:4, 1:3, 1:2, 1:1, 2:1, 3:1, and 4:1, preferably 1:1.

[0099] In the above method, the liquid chromatography-mass spectrometry method in the second data acquisition mode is to perform separation by liquid chromatography and then detect by mass spectrometry in the data acquisition mode.

[0100] In one embodiment, the data acquisition mode is selected from any one of data-dependent acquisition (DDA), data-independent acquisition (DIA), or parallel response monitoring (PRM) modes.

[0101] In the above method, the liquid chromatography-mass spectrometry method uses a conventional liquid chromatograph, preferably a Vanquish Neo UHPLC system (manufactured by Thermo Scientific).

[0102] In the above method, the liquid chromatography-mass spectrometry method uses a conventionally used mass spectrometer, such as the Pro / Pro2 / HT model timsTOF mass spectrometer, the Astral model Orbitrap mass spectrometer, and preferably the OrbitrapAstral mass spectrometer.

[0103] In the above method, the detection conditions for the liquid chromatography-mass spectrometry method are shown in Table 5.

[0104] In the above method, the detection data is feature extracted and matched in a relabeled peptide database, analyzed using DIANN software, and a high-quality relabeled peptide database is used as the library. The software identification parameters are shown in Table 6 below.

[0105] In the above method, the light-labeled peptide database is a conventionally used light-labeled peptide database, preferably a FASTA sequence library. The FASTA sequence library is a conventionally used FASTA library for the corresponding species.

[0106] In one embodiment, the requirements for identifying the FASTA sequence library are as follows: the search sequence file is uniprot_taxonomy_id_9606_Homo sapiens (species)-AND_reviewed.fasta, which is downloaded from uniprot.org and contains the amino acid sequence information of the reviewed human proteins. The software identification parameters are shown in Table 7 below.

[0107] In a preferred embodiment, the detection conditions for the mass spectrometry are shown in Table 8.

[0108] In the above method, the retention time comparison of the matched peptide feature signals is performed by comparing the retention time of the peptide feature signals matched in the light-labeled peptide database with the retention time of the peptide feature signals matched in the heavy-labeled peptide database. Through the comparison and verification between heavy-labeled and light-labeled peptides, the reliability of thousands of peptides can be verified at once, clearly identifying which are more reliable and which are risky.

[0109] In the above method, the retention time (RT) is kept consistent under the condition that the deviation between the retention time of the peptide feature signal matched in the lightly labeled peptide database and the retention time of the peptide feature signal matched in the heavily labeled peptide database is within the allowable time drift tolerance range.

[0110] In one embodiment, the time drift tolerance range is less than 5 times the cycle time (ΔRT < 5 s), preferably 2 times the cycle time (ΔRT < 2 s), to ensure the reliability of the comparison. The time drift tolerance range is dynamically set or a fixed time threshold is set based on chromatographic elution peak width, mass spectrometry scan cycle, and retention time dynamic characteristics.

[0111] When the retention time (RT) remains consistent, the presence of the target peptide in the sample to be tested is confirmed, and a high-confidence tag is generated for the identification result of the light-labeled peptide sequence; a peptide identification report containing the high-confidence tag is output.

[0112] This method collects data by mixing a pre-prepared mixed sample of heavily labeled peptides with the sample to be tested, and performs in-depth verification of the identification information based on the consistency of the retention time (RT) of the lightly labeled and heavily labeled peptides. Those skilled in the art should understand that although a combination of DDA library construction and DIA detection is used in the specific embodiments, the construction of the spectral library of this invention is not limited to the DDA mode. High-quality reference sequences can also be obtained by using parallel reaction monitoring (PRM) or directly using DIA data for library construction; the actual detection of mixed samples is also applicable to high-throughput DIA screening or high-sensitivity PRM targeted verification. Furthermore, the "cell culture system" described in this invention includes, but is not limited to, a mixture of various mammalian or human cell lines such as HEK293 and HeLa, aiming to achieve high-coverage expression of complex background proteomes.

[0113] Meanwhile, this invention introduces a dynamic or fixed threshold setting based on the tolerance of system time drift in the consistency determination. As a highly preferred embodiment, the absolute value threshold of this time deviation can be precisely set to be less than or equal to 5 cycle times (preferably 2 cycle times) during data acquisition by the mass spectrometer. In complex cyclic scanning mechanisms, the theoretical maximum tolerance of system time drift for the same molecule is approximately 5 times the cycle time, preferably 2 times the cycle time. Using this as a judgment boundary can maximize the preservation of true low-abundance peptide signals while achieving a precipitous cutoff of noise caused by structurally similar interference or matrix co-elution. Those skilled in the art can also achieve this objective through other equivalent statistical methods, such as extracting a specific proportion of the chromatographic elution half-peak width, all yielding unexpectedly high confidence identification results.

[0114] Specifically, SILAC culture technology is used to obtain cell lines with relabeled amino acids. Proteins in these cell lines are then digested using enzymes to extract relabeled amino acid-labeled peptides (relabeled peptide mixture samples). These peptide samples are then comprehensively and accurately identified using a data acquisition mode, and reliable peptides are manually retained to create a high-quality relabeled peptide database. In actual project analysis, the relabeled amino acid-labeled peptides are mixed with the test samples at a specific ratio (the mixed peptides are called HL Mix), and data is collected from this sample using a data acquisition mode. For peptide identification, the relabeled peptides in the HL Mix are identified using the high-quality relabeled peptide database to obtain the relabeled peptide identification results; the unlabeled peptides in the HL Mix are identified using the corresponding species' FASTA library to obtain the unlabeled peptide identification results. If the relabeled peptide identification results and the lightly labeled peptide identification results contain peptides with identical amino acid sequences, and the RT (Resolution Time) of this peptide in the relabeled peptide identification result is completely consistent with the RT in the lightly labeled peptide identification result (ΔRT < 5s, preferably ΔRT < 2s), then this peptide has undergone lightly labeled identification, relabeled identification, and light-heavy-label RT matching. Its identification reliability is level one, which is higher than the reliability of other peptides identified by the classic procedure. For a large number of samples, first construct a pool of the test samples, then construct a light-heavy-label pool of the test sample pool and the relabeled peptide. The identification result of this light-heavy-label pool represents the identification result of reliable peptides in all the large number of samples.

[0115] Specifically, the analysis of heavily labeled and lightly labeled peptides in HL Mix was conducted independently. For the analysis of heavily labeled peptides, the heavily labeled peptide database constructed in step 2) was used as the database for the analysis software. Each peptide in this database contains information obtained during the experimental process in step 2), including retention time, precursor ion mass-to-charge ratio, detected b / y ion types, and signal intensity of each b / y ion. Using this database, the analysis of heavily labeled peptides yielded information such as the types, retention times, and signal intensities of the heavily labeled peptides in HL Mix. For the analysis of lightly labeled peptides in HL Mix, a classic proteomics workflow was used, downloading the human database (uniprot_taxonomy_id_9606_Homo sapiens (species)-AND_reviewed.fasta) from www.uniprot.org (a recognized source of proteomics databases). This database contains the names of approximately 20,000 human proteins and their amino acid sequences. The analysis software predicts all possible peptides that humans can generate, and all possible fragment ions for each peptide, based on this database. The predicted results are then compared with the raw mass spectrometry data to obtain proteomics analysis results. These results include the types of peptides relabeled in the HL Mix, retention times, signal intensities, and other information. When comparing the identification results of lightly and heavily labeled peptides in the HL Mix, the intersection of the peptide amino acid sequences (the Stripped.Sequence column in the analysis table) can be used to obtain a list of peptides identified by both light and heavy labeling. The retention times (the RT column in the analysis table) of the peptides in this list are then compared between the lightly and heavily labeled identification results. The results are obtained by using ΔRT (i.e., RT...). heavy -RT light The value of ΔRT is used to assess whether the retention time is consistent. If ΔRT is extremely close, then the RT is considered to be completely consistent. In this case, the peptide passed two completely independent identification events in the same sample and obtained exactly the same RT. That is, the reliability of the light-labeled peptide is verified by the consistency of the RT of the light-labeled peptide.

[0116] The present invention will be further illustrated below with reference to specific embodiments. It should be understood that these embodiments are for illustrative purposes only and are not intended to limit the scope of protection of the present invention.

[0117] The following specific examples illustrate the implementation of the present invention. Those skilled in the art can easily understand other advantages and effects of the present invention from the content disclosed in this specification. The present invention can also be implemented or applied through other different specific embodiments, and various details in this specification can also be modified or changed based on different viewpoints and applications without departing from the spirit of the present invention.

[0118] Unless otherwise defined, the technical and scientific terms used herein have the same meanings as commonly understood by one of ordinary skill in the art to which this invention pertains. This invention uses the methods and materials described herein; however, other suitable methods and materials known in the art may also be used. The materials, methods, and examples described herein are illustrative only and are not intended to be limiting. All publications, patent applications, patent cases, provisional applications, database entries, and other references mentioned herein are incorporated herein by reference in their entirety. In case of conflict, the definitions included in this specification shall prevail.

[0119] Unless otherwise specified, the materials, methods, and examples described herein are exemplary and not limiting. While similar or equivalent methods and materials can be used to implement or test the invention, suitable methods and materials are described herein.

[0120] Unless otherwise specified, all reagents or instruments used in the following examples are commercially available products.

[0121] Example 1 In proteomics research, due to the highly complex types of peptide samples and the presence of numerous low-abundance proteins / peptides, false positives frequently occur during peptide identification, especially with low-abundance proteins and peptides. When the authenticity of low-abundance peptide identification results cannot be accurately determined, relabeled peptides can be used for further confirmation. Specifically, an accurate identification method for peptides in proteomic samples based on relabeled isotope technology, as shown in Figure 1, includes the following steps: (1) Protein samples labeled with relabeled isotopes were obtained using SILAC culture technology. In SILAC culture technology, four different cell lines, HEK293, hela, HepG2, and A549, were selected and cultured together. The cells were cultured for 7 generations, with a cell passage ratio of 1:2 per generation to ensure that the relabeling efficiency of the final relabeled peptides was 99%. The protein samples labeled with relabeled isotopes were then reduced with 40 mmol / L dithiothreitol aqueous solution and alkylated with 100 mmol / L iodoacetamide aqueous solution. The ratio of the mass of cell protein added (μg) to the molar amount of dithiothreitol solution added (μmol) was 200:4, and the ratio of the mass of cell protein added (μg) to the molar amount of iodoacetamide solution added (μmol) was 200:10. The protein was then digested with trypsin for 11 hours at a mass ratio of 1:50. The trypsin used was Promega sequencing-grade trypsin. The resulting relabeled isotope-labeled peptide samples were used as relabeled peptide samples.

[0122] (2) The relabeled peptide samples were first subjected to high-pH reversed-phase fractionation by liquid chromatography. The high-pH reversed-phase fractionation conditions were as follows: 50 groups; ChromCore 120 C18 column (15cm length × 4.6mm inner diameter, 5μm particle size); column temperature 25℃; injection volume 200μL; flow rate 1mL / min; mobile phase A consisted of 980mL chromatographic water, 20mL chromatographic acetonitrile, and 280μL 26% ammonia; mobile phase B consisted of 100mL chromatographic water, 900mL chromatographic acetonitrile, and 480μL 26% ammonia; analysis time 130min; gradient elution. The specific procedure for gradient elution is shown in Table 1.

[0123] The relabeled peptide samples were then detected by liquid chromatography (LC) followed by mass spectrometry (MS) in DDA data acquisition mode. The LC detection conditions were as follows: Thermo Fisher ES906 EASY-SPRAY series PEPMAP RSLC C18 column (15 cm × 150 μm inner diameter, 2 μm particle size); column temperature 50℃; injection volume 300 ng; flow rate 2.0 mL / min; mobile phase A was 0.1% formic acid aqueous solution; mobile phase B was 0.1% formic acid acetonitrile aqueous solution (acetonitrile to water volume ratio 80:20); analysis time 22.6 min; gradient elution. The specific gradient elution procedure is shown in Table 2. The MS was performed using an Astral Orbitrap combined with a TOF-type mass spectrometer, and the detection conditions are shown in Table 4.

[0124] Further identification using PD software yielded secondary polypeptide spectral information, as shown in the attached image. Figure 1a , Figure 1bWe constructed a relabeled peptide database.

[0125] The data in the recalibrated peptide database meet the following criteria: (a) the total number of detected peptide bond breakage sites in the peptide spectrum exceeds 50% of the total number of peptide bonds in the peptide; (b) the isotope peaks in the primary spectrum match the theoretical values ​​by 91%; (c) the noise peaks in the secondary spectrum account for 9%; (d) among the matched fragment ions, there are 4 strong response fragment ions with an intensity index exceeding 30K and 7 relatively strong response fragment ions with an intensity index exceeding 10K; (e) the average mass error is 9.2 ppm, which is less than 10 ppm.

[0126] The identification parameters for constructing the relabeled peptide database also include precursor ion parameters and fragment ion parameters. For precursor ion parameters, the precursor ion contains 30 amino acids to confirm its unique sequence. The requirement for identifying the distribution of different valence states of the precursor ion is 2-4 valence states. For fragment ion parameters, the fragment ion types are b-ions, y-ions, and their corresponding dehydration peak fragment ions. The fragment ion molecular weight distribution is 100-1500. The requirement for the consistency of fragment ions of the same precursor ion with different valence states is that the consistency of fragment ions of the same precursor ion with different valence states reaches more than 70%. The identification requirements for b-ion identification are a mass deviation within 10 ppm, for y-ion identification are a mass deviation within 10 ppm, for identification of neutral loss fragment ions are a mass deviation within 10 ppm, and for the presence of non-neutral loss peaks, the requirement for the proportion of unidentified but expected fragment ions is less than 50%, and the requirement for fragment ion signal intensity is greater than 1000.

[0127] (3) The peptide samples to be tested in the experiment were digested with trypsin. The trypsin digestion process was the same as in step (1). The relabeled peptide sample obtained in step (1) was mixed with the sample to be tested at a mass ratio of 1:1 for 10 seconds. The resulting mixed peptide (HL Mix) was detected by liquid chromatography and then by mass spectrometry in DIA data acquisition mode.

[0128] The detection conditions for liquid chromatography are the same as in step (2). The mass spectrometer is an Astral Orbitrap combined with a TOF mass spectrometer. The detection conditions are shown in Table 5. The obtained detection data are identified using the relabeled peptide database obtained in step (2) through DIANN software. The software identification parameters are shown in Table 6. The relabeled peptide identification results are obtained, which are the retention times of the characteristic signals of peptides that match the same amino acid sequence in the relabeled peptide database.

[0129] (4) Mix the relabeled polypeptide sample obtained in step (1) with the test sample obtained in step (3) at a mass ratio of 1:1 for 10s to obtain the mixed polypeptide (HL Mix). The mixed polypeptide (HL Mix) is detected by liquid chromatography and then by mass spectrometry in DIA data acquisition mode.

[0130] The detection conditions for liquid chromatography were the same as in step (2). The mass spectrometer used was an Astral Orbitrap combined with a TOF-type mass spectrometer. The detection conditions are shown in Table 5. The obtained detection data were identified using the FASTA sequence library. The software identification parameters are shown in Table 8. The identification results of the light-labeled peptides were obtained, which are the retention times of the characteristic signals of peptides that match the same amino acid sequence in the light-labeled peptide database.

[0131] (5) Compare the amino acid sequences of the relabeled peptide identification results obtained in step (3) and the light-labeled peptide identification results obtained in step (4). That is, compare the retention time of the peptide characteristic signal matched in the light-labeled peptide database with the retention time of the peptide characteristic signal matched in the relabeled peptide database. Confirm whether the target peptide is actually present in the sample based on the retention time deviation being within the allowable time drift tolerance range. When the retention time (RT) is consistent, that is, when peptides with the same sequence are identified simultaneously by the peptide characteristic signals matched in the light-labeled peptide database and the relabeled peptide database, and the time drift tolerance range of the retention time is ΔRT < 2s, the correctness is confirmed. Based on this principle, if the abundance of the peptide (light-labeled form) in the sample is very low and the signal is weak, but the abundance of the relabeled form of the peptide in the HL Mix is ​​high and the signal is strong, the reliability of the light-labeled identification result can be judged by the identification result of the relabeled form.

[0132] A polypeptide with the sequence NFINNPLAQADWAAK was detected. See the detailed detection results below. Figure 2 .like Figure 2 As shown, for peptides with the same sequence, their light and heavy forms exhibit completely identical chromatographic behavior, including retention time and peak shape. That is, a characteristic of peptide chromatographic behavior—that is, the light and heavy forms of a peptide always have exactly the same retention time, and their peak shape, relative strength of fragment ions, and other information are always very similar—confirms the presence of the target peptide in the sample.

[0133] A polypeptide with the sequence GHDLNEDGLVSWEEYK was also detected. See the detailed detection results below. Figure 3 .like Figure 3As shown, for peptides with the same sequence, if the retention times of their light-labeled and heavy-labeled forms are identical after identification, the reliability of the light-labeled peptide can be further confirmed through reliable identification of the heavy-labeled form. In the identification results of this peptide, the retention time of the heavy-labeled peptide was completely consistent with that of the light-labeled peptide, at 15.1 minutes. However, the light-labeled peptide showed a very weak signal and strong noise, making its identification less reliable. But because the heavy-labeled form of this peptide exhibited a peak at the same retention time and had a strong signal, and was compared with spectra in a high-quality heavy-labeled spectral database, its reliability was very high. This indicates that the retention time of the target peptide was confirmed to be 15.1 minutes. In other words, the authenticity of the light-labeled form was further confirmed through the heavy-labeled form, significantly improving the authenticity / reliability of the peptide.

[0134] Example 2 Using the same method as in Example 1, a polypeptide with the sequence ILIDSIYK was detected. Specific detection results are shown below. Figure 4 .like Figure 4 As shown, for peptides with identical sequences, if the retention times of their light-labeled and heavy-labeled forms differ after identification, the reliability of the heavy-labeled form can be used to assess the reliability of identification of certain peptides in the results obtained from classic proteomics workflows. In this case, the heavy-labeled peptide was identified by the software as having a retention time of 14.8 minutes, while the light-labeled peptide was identified as having a retention time of 13.9 minutes, indicating a difference in retention times. The light-labeled form of this peptide showed a weak signal and incomplete fragment ions, resulting in low identification reliability. Conversely, the heavy-labeled peptide showed a strong signal, abundant fragment ions, and its reliability was high when compared with spectra in a high-quality heavy-labeled spectral database. This suggests that the target peptide's retention time is more likely to be 14.8 minutes, rather than the 13.9 minutes found in the light-labeled sample. Therefore, the method of this invention can identify peptides with identification risks in proteomics software results.

[0135] The above embodiments are merely illustrative of the principles and effects of the present invention and are not intended to limit the invention. Any person skilled in the art can modify or alter the above embodiments without departing from the spirit and scope of the present invention. Therefore, all equivalent modifications or alterations made by those skilled in the art without departing from the spirit and technical concept disclosed in the present invention should still be covered by the claims of the present invention.

Claims

1. A relabeled peptide database, wherein the data in the relabeled peptide database meets at least one of the following screening criteria: 1) In the polypeptide spectrum, the total number of detected peptide bond break sites exceeds 30% of the total number of peptide bonds in the polypeptide; 2) The isotope peaks in the primary spectrum match the theoretical values ​​by more than 80%; 3) The noise peaks in the secondary spectrum account for less than 10%; 4) The number of matched fragment ions is more than 4; 5) The average mass error is less than 30 ppm.

2. A method for constructing a relabeled peptide database, comprising: The relabeled isotope-labeled peptide samples were detected by liquid chromatography-mass spectrometry in the first data acquisition mode. The obtained detection data met the screening conditions for data in the relabeled peptide database according to claim 1 and were included to constitute the relabeled peptide database.

3. The method for constructing a relabeled polypeptide database according to claim 2, characterized in that, The relabeled isotope-labeled polypeptide samples are obtained by using SILAC culture technology to obtain relabeled isotope-labeled protein samples, and then the relabeled isotope-labeled protein samples are digested with enzymes.

4. The method for constructing a relabeled peptide database according to claim 2, characterized in that, It also includes one or more of the following conditions: A1) The liquid chromatography-mass spectrometry method in the first data acquisition mode is to separate the components using liquid chromatography and then detect them using mass spectrometry in the data acquisition mode; preferably, the data acquisition mode is selected from any one of data-dependent acquisition (DDA), data-independent acquisition (DIA), or parallel reaction monitoring (PRM) mode. A2) Before the relabeled isotope-labeled polypeptide sample is detected by liquid chromatography-mass spectrometry in the first data acquisition mode, it is subjected to high pH reverse-phase fractionation by liquid chromatography.

5. An accurate method for identifying peptides in proteomic samples based on relabeled isotope technology, comprising: The mixed peptide obtained by mixing the test sample with the relabeled peptide sample is detected by liquid chromatography-mass spectrometry in the second data acquisition mode. The obtained detection data are matched with peptide feature signals of the same amino acid sequence in the light-labeled peptide database and the relabeled peptide database according to claim 1. The retention times of the matched peptide feature signals are compared. When the retention times are consistent, it is determined that a certain peptide exists in the test sample.

6. The method for accurate identification of peptides in proteomic samples based on relabeled isotope technology according to claim 5, characterized in that, The sample to be tested is a polypeptide sample that has been digested with trypsin and is to be tested in the experiment; and / or, the mass ratio of the relabeled polypeptide sample to the sample to be tested is selected from any one of 1:4, 1:3, 1:2, 1:1, 2:1, 3:1, and 4:

1.

7. The method for accurate identification of peptides in proteomic samples based on relabeled isotope technology according to claim 5, characterized in that, The liquid chromatography-mass spectrometry method in the second data acquisition mode is to perform separation by liquid chromatography and then detect by mass spectrometry in the data acquisition mode; preferably, the data acquisition mode is selected from any one of data-dependent acquisition (DDA), data-independent acquisition (DIA), or parallel reaction monitoring (PRM) mode.

8. The method for accurate identification of peptides in proteomic samples based on relabeled isotope technology according to claim 5, characterized in that, The light-labeled polypeptide database is the FASTA sequence library.

9. The method for accurate identification of polypeptides in proteomic samples based on relabeled isotope technology according to claim 5, characterized in that, The condition for maintaining consistent retention times is that the deviation between the retention times of peptide feature signals matched in the light-labeled peptide database and those matched in the heavy-labeled peptide database is within the allowable time drift tolerance range.

10. The method for accurate identification of peptides in proteomic samples based on relabeled isotope technology according to claim 9, characterized in that, The time drift tolerance range is less than 5 times the cycle time, i.e., ΔRT < 5s.

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