Method for quantitatively analyzing polypeptides by integrating multiple liquid chromatography-mass spectrometry maps, and application thereof

Abstract

A method for quantitatively analyzing polypeptides by integrating multiple liquid chromatography-mass spectrometry maps, and an application thereof, which belong to the cross technical field of analytical chemistry and computer science. The method comprises: using a liquid chromatography-mass spectrometry technique to analyze samples, so as to obtain multiple extracted ion flow chromatograms of secondary fragment ions; performing integration processing on multiple liquid chromatography-mass spectrometry maps, such that the original means of sequentially processing individual maps and then combining results is changed; by means of the consistency between multiple instances of analysis using the liquid chromatography-mass spectrometry technique in terms of the retention time, ion mass-to-charge ratio and relative strength of the same component, excluding inconsistent chromatographic peaks and secondary fragment ions among the multiple instances of analysis, such that the accuracy of quantitative chromatographic peaks and quantitative ions obtained by means of screening is improved; and using the quantitative chromatographic peaks and the quantitative ions obtained by means of screening to calculate the relative content of polypeptides between the samples, such that the quantitative accuracy of polypeptides and proteins is improved. The method can be applied to non-targeted proteome analysis of clinical samples and biological samples.

Description

A peptide quantitative analysis method integrating multiple liquid chromatography-mass spectrometry spectra and its application Technical Field

[0001] The present invention belongs to the technical field of intersection of analytical chemistry and computer science, and specifically relates to a polypeptide quantitative analysis method integrating multiple liquid chromatography-mass spectrometry (LC-MS / MS) spectra and its application. Background Art

[0002] Non-targeted proteomics analysis based on liquid chromatography-mass spectrometry (LC-MS) can simultaneously quantify thousands of proteins and is widely used to compare differences in protein expression between samples, thereby discovering important biomarkers. During the assay, proteins are typically first enzymatically hydrolyzed into peptides, and the relative content of the peptides is measured by LC-MS, which in turn derives the relative content of the protein. The accuracy of peptide quantification determines the accuracy of protein quantification.

[0003] In quantitative analysis, data-independent acquisition (DIA) is a widely used mass spectrometry scanning mode that can stably acquire fragment ion spectra, overcoming the semi-random sampling limitations of data-dependent acquisition (DDA) and significantly improving the reproducibility of multiple analysis results. DIA typically employs dozens of mass-to-charge ratio isolation windows, fragmenting parent ions within each isolation window and then scanning the resulting fragment ion spectra. Due to the significantly wider mass-to-charge ratio range of its isolation windows than DDA, and the inherent complexity of the sample composition (often containing over 100,000 peptides), the resulting fragment ion spectra are highly complex. Many parent ions of peptides with similar mass-to-charge ratios and sequences will generate fragment ions within the same isolation window, generating numerous interfering signals in the LC / MS spectra. These interfering signals can cause some target peptides to be misassigned to interfering chromatographic peaks and prevent some fragment ions from being used for peptide quantification due to interference, ultimately reducing quantitative accuracy. Therefore, improving quantitative accuracy while quantifying a large number of samples remains a key research challenge.

[0004] DIA-NN (V. Demichev, et al. DIA-NN: neural networks and interference correction enable deep proteome coverage in high throughput. Nat. Methods, 17, 41-44, 2020) and AvG (Vaca Jacome, A Set al. Avant-garde: an automated data-driven DIA data curation tool. Nat. Methods, 17, 1237-1244, 2020) are the two algorithms with the best quantitative accuracy reported so far. DIA-NN uses deep neural networks to distinguish between correct and incorrect candidate chromatographic peaks to improve the accuracy of identification and quantification, while AvG uses genetic algorithms to optimize the screening of quantitative ions. Spectronaut is currently the most commonly used commercial software. Due to its commercial operation, the specific algorithm principles of the current version have not been publicly reported. However, the high repeatability of DIA's multiple analysis results has not yet received sufficient attention and utilization. The data processing model of existing algorithms such as DIA-NN and AvG is still to process individual spectra in sequence and then merge the results of each spectrum for subsequent processing. The information contained in a single spectrum itself is sometimes insufficient to correctly screen chromatographic peaks and quantitative ions, and there is room for further improvement in quantitative accuracy.

[0005] Chinese patent publication CN115267033A discloses a mass spectrometry-based metaproteomics analysis method. The method comprises: selecting protein data from a microbial protein database, each selected protein data forming a first data set corresponding to each first mass spectrometry data set; extracting protein data from each first data set to form a second data set when the false discovery rate meets a first threshold; selecting protein data from the second data set based on each first mass spectrometry data set when the false discovery rate meets a second threshold, and constructing a first spectral library; optimizing the first spectral library to form a second spectral library; and performing qualitative and quantitative analysis on peptide segments and associated proteins contained in a second sample based on the second spectral library and the second mass spectrometry data to obtain analysis results. However, this method focuses on identifying peptides and proteins and does not compare quantitative accuracy.

[0006] In summary, it is necessary to build on existing technologies and utilize the high repeatability of DIA multiple analysis results to research and design a peptide quantitative analysis method with higher quantitative accuracy that integrates multiple LC-MS spectra.

[0007] Summary of the Invention

[0008] The present invention provides a method for quantitative analysis of peptides by integrating multiple liquid chromatography-mass spectrometry (LC-MS / MS) spectra. This method differs from the existing method of sequentially processing individual spectra and then combining the results for subsequent processing. It has high quantitative accuracy and low quantitative error rate.

[0009] The specific technical solutions adopted are as follows:

[0010] A peptide quantitative analysis method integrating multiple LC / MS spectra, comprising:

[0011] A data-independent acquisition mode is adopted, and each sample is analyzed multiple times by liquid chromatography-mass spectrometry technology, or multiple groups of samples are analyzed once or multiple times. The ion current chromatograms of secondary fragment ions in the original LC-MS data are extracted to obtain multiple LC-MS spectra. The consistency of the retention time, ion mass-to-charge ratio and relative intensity of the same component between multiple analyses is ensured by liquid chromatography-mass spectrometry technology. At the same time, the multiple LC-MS spectra are integrated and processed to eliminate inconsistent chromatographic peaks and secondary fragment ions between multiple analyses, thereby improving the accuracy of the quantitative chromatographic peaks and quantitative ions obtained by screening. The quantitative chromatographic peaks and quantitative ions obtained by screening are used to calculate the relative content of the identified polypeptides between samples.

[0012] The sample is a peptide sample, which can be specifically selected from enzymatic hydrolysates of one or more target proteins.

[0013] Specifically, the method for quantitative analysis of peptides by integrating multiple LC-MS spectra comprises the following steps:

[0014] (1) Using a data-independent acquisition mode, analyze each sample multiple times using liquid chromatography-mass spectrometry, or analyze multiple groups of samples once or multiple times to obtain raw liquid chromatography-mass spectrometry data;

[0015] (2) Predicting the retention time of each target peptide in the sample based on the data in the spectral library, extracting the scan data of the target peptide whose predicted retention time is within the allowable deviation range from each LC / MS raw data, obtaining the extracted ion current chromatogram of all secondary fragment ions corresponding to the target peptide within the allowable deviation range of mass-to-charge ratio, and taking the chromatographic peak obtained by integrating the extracted ion current chromatogram as the candidate chromatographic peak;

[0016] (3) For each candidate chromatographic peak, the consistency of the chromatographic peak shape of the secondary fragment ions of the same component is used to screen and exclude the secondary fragment ions with inconsistent peak shapes in the candidate chromatographic peaks, and then calculate the measured peak areas of the remaining secondary fragment ions and obtain the measured relative intensities. The relative intensities of the corresponding secondary fragment ions in the spectral library are used as a reference to exclude the secondary fragment ions with large relative intensity deviations;

[0017] (4) Based on the principle that multiple measurements are closer to the true value, it is easier to find measured data close to the library in multiple LC-MS spectra, and the library matching score of the candidate chromatographic peak is calculated based on this. Among all the candidate chromatographic peaks corresponding to the multiple LC-MS spectra, the candidate chromatographic peak with the highest library matching score is selected as the best matching peak (there is only one best matching peak);

[0018] (5) Using the best matching peak as a reference, find the chromatographic peak of the target peptide in the LC-MS spectrum other than the LC-MS spectrum where the best matching peak is located. Specifically, using the consistency of the retention time of the same component between multiple LC-MS analyses, the retention time of the best matching peak is aligned to the retention time of each LC-MS spectrum as the center, reducing the allowable deviation of the retention time, and retaining the candidate chromatographic peaks whose measured retention time is within the allowable deviation range; then, using the consistency of the ion mass-to-charge ratio and its relative intensity between multiple LC-MS analyses, calculate the similarity score between the retained candidate chromatographic peak and the best matching peak, and select the candidate chromatographic peak with the best matching peak from the candidate chromatographic peaks corresponding to each LC-MS spectrum. The largest candidate chromatographic peak is selected as the measured chromatographic peak, and the measured chromatographic peak and the best matching peak are combined into a chromatographic peak group. If the maximum similarity score in a certain LC-MS spectrum does not meet the critical value requirement (the critical value range of the similarity score between the candidate chromatographic peak and the best matching peak is 0.4-0.8), it is considered that the target peptide is not detected in the LC-MS spectrum; using the consistency of the secondary fragment ions measured for the same component between multiple LC-MS analyses, the chromatographic peaks containing secondary fragment ions that are significantly different from other chromatographic peaks are excluded from the chromatographic peak group, and the retained chromatographic peaks are used as quantitative chromatographic peaks for the final quantitative calculation, while the different secondary fragment ions between the retained quantitative chromatographic peaks are excluded;

[0019] (6) Utilizing the consistency of the relative intensities of ions between multiple LC-MS analyses, the quantitative ions are finally screened. Specifically, the ratio of the measured areas of the secondary fragment ions retained between the quantitative chromatographic peaks corresponding to each LC-MS analysis is calculated. If there are outliers in the ratio, the corresponding secondary fragment ions are excluded. The correlation between the measured areas of the retained secondary fragment ions in multiple quantitative chromatographic peaks is calculated, and the secondary fragment ions with low correlation are excluded. The retained secondary fragment ions are used as quantitative ions.

[0020] (7) Calculate the overall chromatographic peak group score based on the quantitative chromatographic peaks and quantitative ions screened from the chromatographic peak group, and then calculate the weighted geometric mean or weighted arithmetic of the chromatographic peak group score and the highest library match score to obtain a peptide level score. The peptide level score is used to characterize the reliability of the determination, and the weight coefficient range is 0.1 to 10;

[0021] (8) specifying a peptide level score critical value, and the target peptide with a peptide level score higher than the corresponding score critical value is the identified peptide, and the critical value range is 0.75 to 0.95;

[0022] (9) The area of ​​each chromatographic peak in the chromatographic peak group is obtained by summing the quantitative ion area, and the relative content of the identified polypeptide between samples is calculated based on the area of ​​each chromatographic peak in the sample chromatographic peak group.

[0023] Preferably, in step (2), the method for predicting the retention time of the target polypeptide is as follows: using the measured retention time of the reference polypeptide in each LC-MS spectrum as the dependent variable, the relative retention time (iRT value) in the spectral library as the independent variable, and the relative retention time of the target polypeptide as the sample point, linear interpolation or spline interpolation is performed to obtain the predicted retention time of the target polypeptide; the reference polypeptide is a polypeptide with a higher content that is additionally added to the sample before LC-MS analysis, or a polypeptide with a higher content contained in the sample, and the number of reference polypeptides is 5 to 200.

[0024] Preferably, in step (2), the allowable deviation range of the retention time does not exceed 10 min, and the allowable deviation range of the mass-to-charge ratio does not exceed 30 ppm.

[0025] Preferably, in step (3), the method for screening and excluding secondary fragment ions with inconsistent peak shapes in candidate chromatographic peaks is: when the peak top of a chromatographic peak is outside the overall range of the chromatographic peak, the secondary fragment ions corresponding to the chromatographic peak are directly excluded; when the peak top of a chromatographic peak is within the overall range of the chromatographic peak, the ranking of the intensity of each secondary fragment ion at the time point of the overall peak top of the chromatographic peak in the intensity of the ion at each time point within the chromatographic peak range (from large to small) is calculated, and the ranking is divided by the number of time points within the chromatographic peak range, and the secondary fragment ions with a ratio greater than 0.8 are excluded.

[0026] Preferably, in step (3), the method for excluding secondary fragment ions with large relative intensity deviation is: first calculate the root mean square error RMSE between the measured relative intensity of the secondary fragment ion and the relative intensity of the corresponding secondary fragment ion in the spectral library, and then calculate the root mean square error RMSE between the measured relative intensity after the secondary fragment ion is temporarily removed and the relative intensity of the corresponding secondary fragment ion in the spectral library. -1 , if the RMSE of a secondary fragment ion -1 If the RMSE is less than 0.05, the secondary fragment ion is excluded.

[0027] In step (4), the library matching score is obtained by taking a weighted geometric mean or a weighted arithmetic mean of multiple individual scores; the individual scores include: a similarity score between the peak area of ​​each secondary fragment ion characterized by the normalized root mean square error and its library intensity, a deviation score between the measured mass-to-charge ratio of each secondary fragment ion and the theoretical mass-to-charge ratio, a score for the ratio of the number of retained measured secondary fragment ions to the number of library secondary fragment ions, a score for the consistency of chromatographic peak tops between secondary fragment ions, a score for the deviation of the measured retention time from the predicted retention time, and a score for the sum of the peak areas of the secondary fragment ions; the weight coefficient of each individual score ranges from 0.01 to 100;

[0028] Specifically, a) the similarity score between the peak area of ​​each secondary fragment ion and its library intensity is calculated according to formula (1):

[0029] SRSS is the similarity score between the peak area of ​​the secondary fragment ion and its library intensity, and RMSE1 is the root mean square error between the measured relative intensity of the normalized secondary fragment ion and the relative intensity of the corresponding secondary fragment ion in the library. When RMSE1 ≥ 0.3, SRSS is set to 0.

[0030] b) The deviation score between the measured mass-to-charge ratio and the theoretical mass-to-charge ratio of each secondary fragment ion is calculated according to formula (2):

[0031] MES is the deviation score between the measured mass-to-charge ratio and the theoretical mass-to-charge ratio of the secondary fragment ion. The deviation between the measured mass-to-charge ratio and the theoretical mass-to-charge ratio of the currently retained secondary fragment ion is calculated, converted to ppm and its absolute value is taken. The median of the absolute values ​​of the deviations of the secondary fragment ions is then taken as Δmz. FP ; When Δmz FP When ≥30, MES is set to 0.

[0032] c) The score of the ratio of the number of retained measured secondary fragment ions to the number of retained secondary fragment ions in the library is calculated according to formula (3): FQS = n F-remain / n F (3)

[0033] FQS is the score of the ratio of the number of retained measured secondary fragment ions to the number of retained secondary fragment ions in the library; n F-remain is the number of fragment ions in the chromatographic peak that are not currently excluded, n F is the number of library ions.

[0034] d) The chromatographic peak consistency score between secondary fragment ions is calculated according to formula (4):

[0035] FPCS is the chromatographic peak consistency score between secondary fragment ions; for each secondary fragment ion that is not currently excluded, the intensity of the ion at the time point of the overall chromatographic peak is calculated from large to small within the chromatographic peak range. The average of each ranking is r apex,mean ; When r apex,mean When ≥6, FPCS is set to 0.

[0036] e) The deviation score between the measured retention time and the predicted retention time is calculated according to formula (5):

[0037] RTES is the score of the deviation between the measured retention time and the predicted retention time; RT error TW is the absolute value of the deviation between the measured retention time and the predicted retention time. 1 / 2 The permissible deviation of the retention time when extracting the ion current of the secondary fragment ions in step (2).

[0038] f) The sum score of the secondary fragment ion peak areas is calculated according to formula (6):

[0039] FIS is the sum of the secondary fragment ion peak areas; A sum is the sum of the peak areas of the secondary fragment ions that are not currently excluded; A max and A min are the A values ​​of all chromatographic peaks within the time range of the secondary fragment ion extraction ion flow. sum The maximum and minimum values ​​in .

[0040] Preferably, in step (5), the method for calculating the alignment of the retention time of the best matching peak to the retention time of each LC-MS spectrum is as follows: using the measured retention time of the reference polypeptide in each LC-MS spectrum as the dependent variable, using the measured retention time of the reference polypeptide in the LC-MS spectrum where the best matching peak is located as the independent variable, and using the retention time of the best matching peak as the sample point, interpolation is performed using a linear interpolation method or a spline interpolation method to obtain the aligned retention time. The purpose of alignment is to find the chromatographic peak corresponding to the component in the remaining LC-MS spectra (other than the LC-MS spectrum where the best matching peak is located).

[0041] Preferably, in step (5), the permissible deviation of the retention time is reduced to ±0.1 to ±3 min.

[0042] In step (5), the similarity score between the candidate chromatographic peak and the best matching peak is obtained by taking a weighted geometric mean or a weighted arithmetic mean of multiple individual scores; the individual scores include: the similarity score between the peak area of ​​each secondary fragment ion and the best matching peak intensity characterized by the normalized root mean square error, the deviation score between the measured mass-to-charge ratio of each secondary fragment ion and the theoretical mass-to-charge ratio, the ratio score of the number of retained measured secondary fragment ions to the number of best matching peak ions, and the chromatographic peak top consistency score between the secondary fragment ions; the weight coefficient of each individual score ranges from 0.01 to 100.

[0043] Specifically, in step (5), the similarity score between the peak area of ​​each secondary fragment ion and the intensity of the best matching peak is calculated for the currently retained secondary fragment ion according to formula (1), SRSS represents the similarity score between the peak area of ​​the secondary fragment ion and the intensity of the best matching peak, and RMSE1 is taken as the root mean square error between the measured relative intensity of the normalized secondary fragment ion and the relative intensity of the corresponding secondary fragment ion in the best matching peak; the deviation score between the measured mass-to-charge ratio and the theoretical mass-to-charge ratio of each secondary fragment ion is calculated for the currently retained secondary fragment ion according to formula (2); the ratio score of the number of retained measured secondary fragment ions to the number of best matching peak ions is calculated for the currently retained secondary fragment ions according to formula (3), FQS represents the ratio score of the number of retained measured ions to the number of best matching peak ions, n F The value is the number of the best matching peak ions; the chromatographic peak top consistency score between the secondary fragment ions is calculated according to formula (4) for the currently retained secondary fragment ions.

[0044] Preferably, in step (6), the peak areas of the secondary fragment ions retained in the quantitative chromatographic peak are used as vectors, and the cosine of the angles between each pair of vectors is used to characterize the "correlation between the measured areas of different secondary fragment ions in multiple quantitative chromatographic peaks". The secondary fragment ions are clustered and analyzed using the angle cosine distance, i.e., 1 minus the angle cosine. If the angle cosine distance exceeds a critical value, the corresponding secondary fragment ion is a secondary fragment ion with low correlation; the critical value range is 0.02 to 0.1.

[0045] In step (7), the chromatographic peak group score is obtained by taking a weighted geometric mean or a weighted arithmetic mean of multiple individual scores; the individual scores include: a score of similarity between the peak area of ​​each secondary fragment ion characterized by the normalized root mean square error and its library intensity, a score of deviation between the measured mass-to-charge ratio of each secondary fragment ion and the theoretical mass-to-charge ratio, a score of the ratio of the number of retained measured secondary fragment ions to the number of library secondary fragment ions, a score of consistency of chromatographic peak tops between secondary fragment ions, a score of deviation between the measured retention time and the predicted retention time, a score of relative standard deviation between the peak areas of multiple quantitative chromatographic peaks corresponding to the same sample, and a score of the ratio of the number of quantitative chromatographic peaks in the chromatographic peak group to the number of LC-MS spectra, and the weight coefficient of each individual score ranges from 0.01 to 100;

[0046] When multiple groups of samples are analyzed only once, the individual scores of the chromatographic peak group score do not include the relative standard deviation scores between the peak areas of multiple quantitative chromatographic peaks corresponding to the same sample.

[0047] Specifically, in step (7), the similarity score between the peak area of ​​each secondary fragment ion and its library intensity is calculated according to formula (1) for the currently retained secondary fragment ion; the deviation score between the measured mass-to-charge ratio and the theoretical mass-to-charge ratio of each secondary fragment ion is calculated according to formula (2) for the currently retained secondary fragment ion; the ratio score of the number of retained measured secondary fragment ions to the number of library secondary fragment ions is calculated according to formula (3) for the currently retained secondary fragment ion; the chromatographic peak top consistency score between the secondary fragment ions is calculated according to formula (4) for the currently retained secondary fragment ion; the deviation score between the measured retention time and the predicted retention time is calculated according to formula (5) for the currently retained secondary fragment ion;

[0048] The relative standard deviation scores between the peak areas of multiple quantitative chromatographic peaks corresponding to the same sample are calculated according to formula (7):

[0049] PARS is the relative standard deviation score between the peak areas of multiple quantitative chromatographic peaks corresponding to the same sample. For each sample, the corresponding peak in the chromatographic peak group is taken and the relative standard deviation (RSD) of the peak area is calculated. When the RSD is greater than 50%, it is set to 50%. The median RSD of all samples is calculated to obtain the RSD. CPG ; When multiple groups of samples are analyzed only once, this score is not used.

[0050] The ratio score of the number of quantitative chromatographic peaks in the chromatographic peak group to the number of LC-MS spectra was calculated according to formula (8):

[0051] VPQS is the score of the ratio of the number of quantitative chromatographic peaks in the chromatographic peak group to the number of LC-MS spectra; n runs-2 is the number of quantitative chromatographic peaks in the chromatographic peak group, n runs is the number of LC-MS spectra.

[0052] Preferably, in step (8), the method for specifying the polypeptide level score critical value is to repeat steps (2)-(7) for the pseudo-peptide library, merge and sort the polypeptide level scores of the target polypeptide and the pseudo-peptide, calculate the polypeptide level false discovery rate corresponding to each score critical value, and specify the polypeptide level score critical value according to the requirement of the polypeptide level false discovery rate; the requirement range of the false discovery rate is 0.1% to 10%.

[0053] The present invention also provides the application of the polypeptide quantitative analysis method integrating multiple LC-MS spectra in protein analysis; the relative content of proteins among samples is calculated based on the relative content of identified polypeptides among samples.

[0054] Specifically, the method for calculating the relative content of proteins between samples is as follows: In order to prevent the erroneous quantification of a protein by a polypeptide that does not actually exist due to random factors and obtains a higher polypeptide level score when a protein corresponds to multiple polypeptides, the formula (9) is used to calculate the requirement for the polypeptide level false discovery rate (FDR) when quantifying each protein. peptide ), FDR protein =1- (1-FDR peptide ) n (9)

[0055] Where n is the number of peptides corresponding to the protein, FDR protein It is the requirement for false discovery rate at protein level. According to the corresponding relationship between the critical value of peptide level score and the false discovery rate at peptide level, the FDR is set. peptide The corresponding polypeptide level score critical value is obtained, and the median of the relative content (i.e., content ratio) between samples of polypeptides with chromatographic peak group scores greater than the critical value is calculated to obtain the relative content of the protein between samples. At the same time, the sum of the polypeptide level scores of these polypeptides is used as the quantitative reliability score of each protein.

[0056] The present invention also provides an electronic device comprising at least a memory and a processor, wherein the memory stores a program, and the processor implements the polypeptide quantitative analysis method integrating multiple LC-MS spectra when executing the program on the memory.

[0057] Compared with the prior art, the present invention has the following beneficial effects:

[0058] (1) Under the premise that the liquid chromatography-mass spectrometry analysis process and data remain unchanged, the present invention significantly improves the quantitative accuracy and reduces the quantitative error rate by only changing the data processing mode without the need for additional experiments.

[0059] (2) The present invention takes the measured best matching peak as a reference, and part of the quantitative ion screening method does not rely on the spectral library, and has a good tolerance for the errors of the intensity of a few fragment ions in the spectral library.

[0060] (3) The improvement of the quantitative accuracy of the method of the present invention does not come at the expense of a reduction in the quantitative number.

[0061] (4) The process of screening quantitative chromatographic peaks and quantitative ions in the present invention is completely automatically implemented by software, without the need for manual operation by professionals. The algorithm parameters involved can be more robustly applied to different types of liquid chromatography-mass spectrometry data sets, without the need for special parameter optimization. BRIEF DESCRIPTION OF THE DRAWINGS

[0062] Figure 1 is a statistical graph of the error rates of the polypeptide ratios of three species measured by the method of the present invention, the DIA-NN method, and the AvG method in Example 1. The p value is obtained by performing a chi-square test on the accurate quantitative number and the incorrect quantitative number of the software, indicating that there is a significant difference in the error rate.

[0063] Figure 2 is a box plot of the correlation coefficient r between the ratio of polypeptide content measured by the present invention, the DIA-NN method, and Spectronaut in Example 2 and the ratio of the theoretical content. The middle horizontal line of the box plot represents the median, the upper and lower boundaries of the box represent the upper and lower quartiles, the cross represents the mean, the whiskers represent 1.5 times the interquartile range, and the dots represent outliers.

[0064] Figure 3 is a box plot of the standard deviation (SD) of the logarithmic (log2) transformation of the ratios of multiple peptides corresponding to the same protein in Example 3 using the present invention and Spectronaut. The middle horizontal line of the box plot represents the median, the upper and lower bounds of the box represent the upper and lower quartiles, the cross represents the mean, the whiskers represent 1.5 times the interquartile range, and the dots represent outliers. DETAILED DESCRIPTION

[0065] The present invention will be further described below with reference to the following examples and accompanying drawings. It should be understood that these examples are only intended to illustrate the present invention and are not intended to limit the scope of the present invention.

[0066] Example 1

[0067] This example uses the peptide quantitative analysis method integrating multiple LC-MS spectra to analyze proteomic hydrolysates. The method includes the following steps:

[0068] (1) Using the data-independent acquisition (DIA) mode, samples A and B were analyzed three times each by liquid chromatography-mass spectrometry (64 isolation windows with different mass-to-charge ratio window widths were used in the LC-MS analysis), and six LC-MS spectra were obtained as the original LC-MS data. Samples A and B were composed of proteomic hydrolysates of three species (human, Escherichia coli, and yeast), respectively. The mass fractions of the proteomic hydrolysates of human, Escherichia coli, and yeast in sample A were 67%, 3%, and 30%, respectively. The mass fractions of the proteomic hydrolysates of human, Escherichia coli, and yeast in sample B were 67%, 30%, and 3%, respectively.

[0069] The above steps have been completed and data is provided in the literature (Navarro, P. et al. A multicenter study benchmarks software tools for label-free proteome quantification. Nat. Biotechnol., 34, 1130-1136, 2016). The dataset download link is: http: / / proteomecentral.proteomexchange.org / cgi / GetDataset?ID=PXD002952.

[0070] Liquid chromatography-mass spectrometry (LC-MS) analysis was performed using data-dependent acquisition (DDA) mode to construct a spectral library of target peptides (the download link for this library is: https: / / ftp.pride.ebi.ac.uk / pride / data / archive / 2016 / 09 / PXD002952 / ecolihuman yeast_concat_mayu_IRR_cons_openswath_64var_curated.csv). For each peptide in the spectral library, the following steps (2)-(7) were performed separately.

[0071] (2) Based on the data in the spectral library constructed in the above steps, the measured retention time of the reference peptides (11 peptides with high content added to the sample before LC-MS analysis) in each LC-MS spectrum is used as the dependent variable, the relative retention time (iRT value) in the spectral library is used as the independent variable, and the iRT value of the target peptide is used as the sample point. The predicted retention time of the peptide is obtained after linear interpolation. Based on the mass-to-charge ratio of the parent ion and fragment ion of each peptide in the spectral library, the allowable deviation range of the retention time is set to 10 minutes and the allowable deviation range of the mass-to-charge ratio is set to 30 ppm. The extracted ion current chromatograms of all secondary fragment ions within the above range are extracted from the raw LC-MS data, and the chromatographic peaks obtained by integration of the extracted ion current chromatograms are used as candidate chromatographic peaks.

[0072] (3) For each candidate chromatographic peak, the consistency of the chromatographic peak type of the secondary fragment ions of the same component is used to preliminarily screen the secondary fragment ions and exclude the secondary fragment ions corresponding to the chromatographic peaks with inconsistent peak types. Specifically, when the peak top of a chromatographic peak is outside the overall range of the chromatographic peak, the secondary fragment ions corresponding to the chromatographic peak are directly excluded. When the peak top of a chromatographic peak is within the overall range of the chromatographic peak, the intensity of each secondary fragment ion at the time point of the overall peak top of the chromatographic peak is calculated in descending order among the ion intensities at each time point within the range of the chromatographic peak, and the intensity is divided by the number of time points within the range of the chromatographic peak. The secondary fragment ions with a ratio greater than 0.8 are excluded. Among them, the median of the start time of each secondary fragment ion peak in the chromatographic peak is taken as the start time of the overall chromatographic peak, and the median of the end time of each secondary fragment ion peak is taken as the end time of the overall chromatographic peak. The range from the start time to the end time of the overall chromatographic peak is called the overall range of the chromatographic peak.

[0073] The measured relative intensity is then calculated using the measured peak area of ​​the retained secondary fragment ion, and the relative intensity of the corresponding secondary fragment ion in the spectral library is used as a reference to exclude secondary fragment ions with large relative intensity deviations. Specifically, the root mean square error (RMSE) between the measured relative intensity of the secondary fragment ion and the relative intensity of the corresponding secondary fragment ion in the spectral library is first calculated, and then the root mean square error (RMSE) between the measured relative intensity of the secondary fragment ion after the secondary fragment ion is temporarily removed and the relative intensity of the corresponding secondary fragment ion in the spectral library is calculated. -1 , if the RMSE of a secondary fragment ion -1 If the RMSE is less than 0.05, the secondary fragment ion is excluded.

[0074] (4) Based on the principle that multiple measurements are closer to the true value, it is easier to find measured data that is close to the library spectrum in multiple LC-MS spectra. Based on this, the library matching score of the candidate chromatographic peak is calculated. Among all the candidate chromatographic peaks corresponding to the multiple LC-MS spectra, the candidate chromatographic peak with the highest library matching score is selected as the best matching peak;

[0075] The library match score is obtained by taking the weighted geometric average of multiple individual scores; the individual scores include: the similarity score between the peak area of ​​each secondary fragment ion and its library intensity represented by the normalized root mean square error, the deviation score between the measured mass-to-charge ratio of each secondary fragment ion and the theoretical mass-to-charge ratio, the ratio score of the number of retained measured secondary fragment ions to the number of library secondary fragment ions, the consistency score of the chromatographic peak tops between secondary fragment ions, the deviation score between the measured retention time and the predicted retention time, and the sum score of the secondary fragment ion peak areas; the weight coefficient of each individual score is 1;

[0076] Specifically, the similarity score between the peak area of ​​each secondary fragment ion and its library intensity is calculated according to formula (1); the deviation score between the measured mass-to-charge ratio and the theoretical mass-to-charge ratio of each secondary fragment ion is calculated according to formula (2); the score of the ratio of the number of retained measured secondary fragment ions to the number of library secondary fragment ions is calculated according to formula (3); the chromatographic peak top consistency score between secondary fragment ions is calculated according to formula (4); the deviation score between the measured retention time and the predicted retention time is calculated according to formula (5); and the sum score of the secondary fragment ion peak areas is calculated according to formula (6).

[0077] (5) Based on the best matching peak, find the chromatographic peak corresponding to the component in the remaining LC-MS spectra (other than the LC-MS spectra where the best matching peak is located). Specifically, using the consistency of the retention time of the same component between multiple LC-MS analyses, the retention time of the best matching peak is aligned to the retention time of each LC-MS spectra as the center, reducing the allowable deviation of the retention time, excluding candidate chromatographic peaks with large retention time deviations, and retaining candidate chromatographic peaks with measured retention times within the allowable deviation range. The calculation method for aligning the retention time of the best matching peak to the retention time of each LC-MS spectra is as follows: the measured retention time of the reference peptide (11 peptides with higher content added to the sample before LC-MS analysis) in each LC-MS spectra is used as the dependent variable, the measured retention time of the reference peptide in the LC-MS spectra where the best matching peak is located is used as the independent variable, the retention time of the best matching peak is used as the sample point, and linear interpolation or spline interpolation is used to interpolate to obtain the aligned retention time. The allowable deviation of the retention time was reduced to 0.27 min (obtained by the leave-one-out cross-validation of the retention times of the above 11 peptides).

[0078] Then, the consistency of the mass-to-charge ratio of ions and their relative intensities between multiple LC-MS analyses was used to calculate the similarity scores between the retained candidate chromatographic peaks and the best matching peak. Among the candidate chromatographic peaks corresponding to each LC-MS spectrum, the candidate chromatographic peak with the largest similarity score was selected as the measured chromatographic peak of the component selected in each measurement.

[0079] The similarity score between a candidate chromatographic peak and the best-matching peak is calculated by taking the weighted geometric mean or weighted arithmetic mean of multiple individual scores. The individual scores include: the similarity score between the peak area of ​​each secondary fragment ion and the best-matching peak intensity, expressed as the normalized root mean square error; the deviation score between the measured and theoretical mass-to-charge ratios of each secondary fragment ion; the score for the ratio of the number of retained measured secondary fragment ions to the number of best-matching peak ions; and the consistency score for the chromatographic peak tops between secondary fragment ions. Each individual score is weighted to 1. If the maximum similarity score in a particular LC / MS spectrum does not meet the critical value of 0.5 or does not reach the maximum similarity score of another LC / MS spectrum minus 0.2, the component is considered not to be detected in that LC / MS spectrum.

[0080] Specifically, the similarity score between the peak area of ​​each secondary fragment ion and the intensity of the best matching peak is calculated for the currently retained secondary fragment ions according to formula (1), SRSS represents the similarity score between the peak area of ​​the secondary fragment ion and the intensity of the best matching peak, and RMSE1 is taken as the root mean square error between the measured relative intensity of the normalized secondary fragment ion and the relative intensity of the corresponding secondary fragment ion in the best matching peak; the deviation score between the measured mass-to-charge ratio and the theoretical mass-to-charge ratio of each secondary fragment ion is calculated for the currently retained secondary fragment ions according to formula (2); the ratio score of the number of retained measured secondary fragment ions to the number of best matching peak ions is calculated for the currently retained secondary fragment ions according to formula (3), FQS represents the ratio score of the number of retained measured ions to the number of best matching peak ions, n F The value is the number of the best matching peak ions; the chromatographic peak top consistency score between the secondary fragment ions is calculated according to formula (4) for the currently retained secondary fragment ions.

[0081] The measured chromatographic peaks and the best matching peaks are combined into a chromatographic peak group. If the maximum similarity score in a certain LC-MS spectrum does not meet the critical value requirement, it is considered that the target peptide is not detected in the LC-MS spectrum. Using the consistency of the secondary fragment ions measured for the same component between multiple LC-MS analyses, chromatographic peaks containing secondary fragment ions that are significantly different from other chromatographic peaks are excluded from the chromatographic peak group. The retained chromatographic peaks are used as quantitative chromatographic peaks for the final quantitative calculation, and the different secondary fragment ions between the retained quantitative chromatographic peaks are excluded.

[0082] (6) Utilizing the consistency of the relative intensities of ions between multiple liquid chromatography-mass spectrometry analyses, the quantitative ions are finally screened. Specifically, the ratio of the measured areas of the secondary fragment ions retained between the quantitative chromatographic peaks corresponding to each liquid chromatography-mass spectrometry analysis is calculated. After the ratio is logarithmically transformed (log2) with a base of 2, the intensity of each secondary fragment ion in the spectral library is used as the weight coefficient for weighted average. If it exceeds the range of ±1 of the mean, it is an outlier. The secondary fragment ion corresponding to the outlier is excluded. The correlation between the measured areas of the retained secondary fragment ions in multiple quantitative chromatographic peaks is calculated, and the secondary fragment ions with low correlation are excluded. The retained secondary fragment ions are used as quantitative ions;

[0083] Specifically, the peak area of ​​each secondary fragment ion retained in the quantitative chromatographic peak is used as a vector, and the cosine of the angle between each pair of vectors is used to characterize the "correlation between the measured areas of different secondary fragment ions in multiple quantitative chromatographic peaks". The secondary fragment ions are clustered and analyzed based on the angle cosine distance, that is, 1 minus the angle cosine. The two secondary fragment ions with the smallest angle cosine distance are retained first, and the other secondary fragment ions are retained based on whether the angle cosine distance between them and the retained secondary fragment ions is within the critical value, and the unretained ions are excluded; the above critical value is the maximum value of 0.05 and twice the distance between the retained ions.

[0084] (7) Based on the quantitative chromatographic peaks and quantitative ions screened out from the chromatographic peak group, the chromatographic peak group score is calculated as a whole. Then, the weighted geometric average of the chromatographic peak group score and the highest library match score is calculated to obtain the peptide level score. The peptide level score is used to characterize the reliability of the determination, and the weight coefficients are all 1.

[0085] The chromatographic peak group score is obtained by taking the weighted geometric mean or weighted arithmetic mean of multiple individual scores. The individual scores include: the similarity score between the peak area of ​​each secondary fragment ion and its library intensity represented by the normalized root mean square error, the deviation score between the measured mass-to-charge ratio of each secondary fragment ion and the theoretical mass-to-charge ratio, the ratio score of the number of retained measured secondary fragment ions to the number of library secondary fragment ions, the chromatographic peak top consistency score between secondary fragment ions, the deviation score between the measured retention time and the predicted retention time, the relative standard deviation score between the peak areas of multiple quantitative chromatographic peaks corresponding to the same sample, and the ratio score of the number of quantitative chromatographic peaks in the chromatographic peak group to the number of LC-MS spectra. The weight coefficient of each individual score ranges from 0.01 to 100.

[0086] Specifically, in step (7), the similarity score between the peak area of ​​each secondary fragment ion and its library intensity is calculated according to formula (1) for the currently retained secondary fragment ion; the deviation score between the measured mass-to-charge ratio and the theoretical mass-to-charge ratio of each secondary fragment ion is calculated according to formula (2) for the currently retained secondary fragment ion; the ratio score of the number of retained measured secondary fragment ions to the number of best matching peak ions is calculated according to formula (3) for the currently retained secondary fragment ion; the chromatographic peak top consistency score between the secondary fragment ions is calculated according to formula (4) for the currently retained secondary fragment ion; the deviation score between the measured retention time and the predicted retention time is calculated according to formula (5) for the currently retained secondary fragment ion; the relative standard deviation score between the peak areas of multiple quantitative chromatographic peaks corresponding to the same sample is calculated according to formula (7); the ratio score of the number of quantitative chromatographic peaks in the chromatographic peak group to the number of LC-MS spectra is calculated according to formula (8).

[0087] (8) Repeat steps (2) to (7) above for a decoy peptide library (obtained by changing the amino acid sequence of the target peptide in the library, download link ftp: / / massive.ucsd.edu / MSV000085540 / quant / LFQBench / Skyline / HYE110_6600_64Var_Skyline_PublishedPB.sky.zip, and export the library using Skyline software). Then, the peptide level scores of the target peptide and the decoy peptide are combined and ranked, and the peptide level false discovery rate corresponding to each score cutoff is calculated. According to the requirement of 1% for the peptide level false discovery rate, peptides with a peptide level score higher than the corresponding score cutoff (0.85088) are identified peptides. The number of peptides obtained for humans, E. coli, and yeast is 15,823, 8,928, and 8,450, respectively (according to the library data and the processing method of the software used for comparison, the number of different parent ion charges of the same peptide in the library is counted separately, the same below).

[0088] (9) The relative content of the identified polypeptide between samples was calculated based on the area of ​​each peak in the sample chromatographic peak group. In order to demonstrate the advantage of the method of the present invention in quantitative accuracy, the quantitative results of two softwares, DIA-NN (download link https: / / files.osf.io / v1 / resources / 6g3ux / providers / osfstorage / 5dc188e896af97000f1942c7?action=download&direct&version=1) and AvG (download link https: / / static-content.springer.com / esm / art%3A10.1038%2Fs41592-020-00986-4 / MediaObjects / 41592_2020_986_MOESM3_ESM.zip) were compared. The relative error of the ratio of the measured content between samples A and B to the theoretical content was greater than 30% as the basis for judging the measurement error (the same below). DIA-NN determined the content ratios between samples A and B. The number of accurately determined polypeptides for human, E. coli, and yeast was 14,677, 3,369, and 2,665, respectively. The number of incorrectly determined polypeptides was 1,652, 1,820, and 1,196, respectively, with error rates of 10.1%, 35.1%, and 31.0%, respectively (Figure 1). By removing polypeptides with low level scores from the quantitative results of the present method, and reconciling the number of accurately determined polypeptides with that of DIA-NN, the number of incorrectly determined polypeptides was 1,527, 1,271, and 672, respectively, with error rates of 9.4%, 27.4%, and 20.1%, respectively (Figure 1), significantly lower than that of DIA-NN. This demonstrates the superiority of the present method in quantitative accuracy. AvG (which used some OpenSWATH software functions during data processing) obtained the content ratio between samples A and B. The number of accurately determined polypeptides for human, E. coli, and yeast was 12,096, 1,611, and 1,051, respectively, while the number of incorrectly determined polypeptides was 919, 593, and 432, respectively, with error rates of 7.1%, 26.9%, and 29.1%, respectively (Figure 1). When polypeptides with low polypeptide level scores were removed from the quantitative results of the present method, and the number of accurately determined polypeptides was the same as that of AvG, the number of incorrectly determined polypeptides was 925, 240, and 164, respectively, with error rates of 7.1%, 13.0%, and 13.5%, respectively (Figure 1), which were significantly lower than those of AvG, demonstrating the superiority of the present method in quantitative accuracy.

[0089] Furthermore, the relative content of the protein among the samples is calculated based on the relative content of the peptides identified in step (9). Specifically, the calculation method is as follows: in order to prevent a protein from being quantified incorrectly due to a higher peptide level score of a peptide that does not actually exist when a protein corresponds to multiple peptides due to random factors, the requirement for the peptide level false discovery rate when quantifying each protein is calculated using formula (9). In this embodiment, FDR protein 1%, according to the corresponding relationship between the score critical value obtained in step (8) and the false discovery rate at the peptide level, from FDR peptide The corresponding polypeptide level score critical value is obtained, and the median of the relative content (i.e., content ratio) between samples of polypeptides with polypeptide level scores greater than the critical value is calculated to obtain the relative content of the protein between samples. At the same time, the sum of the polypeptide level scores of these polypeptides is used as the quantitative reliability score of each protein.

[0090] To demonstrate the superiority of the method of the present invention in protein quantification accuracy, the quantitative results of DIA-NN were compared (AvG does not provide protein quantification results, so this comparison is not included here). Under the premise that at least two polypeptides were measured for each protein, DIA-NN obtained the content ratio between samples A and B. The number of accurately measured proteins for human, E. coli, and yeast was 1903, 488, and 427, respectively, while the number of incorrectly measured proteins was 47, 128, and 123, respectively, with error rates of 2.4%, 20.8%, and 22.4%, respectively. Under the premise that at least two polypeptides were measured for each protein, proteins with low reliability scores were removed from the quantitative results of the method of the present invention, and the number of accurately measured proteins was the same as that of DIA-NN. The number of incorrectly measured proteins was 30, 118, and 15, respectively, with error rates of 1.6%, 19.5%, and 3.4%, respectively, which are significantly lower than those of DIA-NN. This demonstrates that the method of the present invention still has an advantage in quantitative accuracy at the protein level.

[0091] Example 2

[0092] In this example, a proteomic hydrolysate was analyzed using the peptide quantitative analysis method integrating multiple LC-MS spectra. The method includes the following steps:

[0093] (1) Using data-independent acquisition mode Four samples, Y1, Y2, Y3, and Y4, were each analyzed three times using liquid chromatography-mass spectrometry (DIA) (64 isolation windows with a mass-to-charge ratio range of 400 to 1200 m / z, each 13.5 m / z wide, and with 1 m / z overlap between windows). Twelve LC-MS spectra were obtained as raw LC-MS data. Samples Y1, Y2, Y3, and Y4 were composed of mixtures of proteomic hydrolysates from two species (human and yeast), respectively. The mass of the human proteomic hydrolysate in all four samples was 800 ng (considered as background component interfering with the determination), while the mass of the yeast proteomic hydrolysate in samples Y1, Y2, Y3, and Y4 was 200, 100, 50, and 25 ng, respectively. The theoretical ratios of yeast-derived peptide content among the samples were Y2 / Y1 = 0.5, Y3 / Y1 = 0.25, and Y4 / Y1 = 0.125.

[0094] The measured data set can be downloaded from the PRIDE website (ID: PXD039399). Liquid chromatography-mass spectrometry (LC-MS) analysis of yeast proteome digests was performed using data-dependent acquisition (DDA) mode to obtain a library of yeast target peptides (which can be downloaded from the PRIDE website using the above ID). For each peptide in the library, the following steps (2)-(7) were performed separately.

[0095] (2) Based on the library data, the measured retention times of the reference peptides (11 peptides with high content in the sample: DSYVGDEAQSK, AGFAGDDAPR, ATAGDTHLGGEDFDNR, VATVSLPR, ELISNASDALDK, TTPSYVAFTDTER, VCENIPIVLCGNK, LGEHNIDVLEGNEQFINAAK, SYELPDGQVITIGNER, YFPTQALNFAFK, DSTLIMQLLR) in each LC / MS spectrum were used as the dependent variable, their iRT (relative retention time) values ​​were used as the independent variable, and the iRT value of the target peptide was used as the sample point. The predicted retention time of the peptide was obtained after linear interpolation. Based on the mass-to-charge ratio of the parent ion and fragment ion of each peptide in the library, the allowable deviation range of the retention time was set to 5 min and the allowable deviation range of the mass-to-charge ratio was set to 20 ppm. The extracted ion current chromatograms of all secondary fragment ions within the above range were extracted from the raw LC / MS data, and the chromatographic peaks therein were regarded as candidate chromatographic peaks and integrated.

[0096] Steps (3) to (7) in this embodiment are the same as those in Example 1, except that in step (5), the allowable deviation of the retention time is reduced to 0.92 min (obtained by the leave-one-out cross-validation of the retention times of the above 11 peptides).

[0097] (8) After repeating the above steps (2)-(7) for the decoy peptide library (obtained by changing the amino acid sequence of the target peptide in the library, which can be downloaded from the PRIDE website using the above ID), the peptide level scores of the target peptide and the decoy peptide are merged and sorted, and the peptide level false discovery rate corresponding to each score cutoff is calculated. According to the requirement of 1% for the peptide level false discovery rate, peptides with a peptide level score higher than the corresponding score cutoff (0.84490) are identified peptides. 8512 yeast peptides were obtained (based on the library data and the processing method of the comparison software, the different parent ion charge numbers of the same peptide in the library were counted separately, the same below).

[0098] (9) The relative content of the identified polypeptides between samples was calculated based on the area of ​​each peak in the chromatographic peak group. In order to demonstrate the advantages of the method of the present invention in terms of quantitative accuracy, the quantitative results of the two softwares, DIA-NN and Spectronaut, were compared. The relative error of the ratio of the measured content between samples to the ratio of the theoretical content (Y2 / Y1, Y3 / Y1, Y4 / Y1) > 30% was used as the basis for judging the measurement error (the same below). While examining the relative error of the ratio of the measured content to the theoretical content, the overall quantitative accuracy was examined using the correlation coefficient between the ratio of the measured content and the theoretical content. In order to prevent the correlation coefficient used in subsequent comparisons from being distorted by missing values, the polypeptides with missing values ​​in the content ratio (Y2 / Y1, Y3 / Y1, Y4 / Y1) were excluded before comparison. The number of yeast peptides (Y2 / Y1, Y3 / Y1, Y4 / Y1) accurately determined by DIA-NN was 6405, 4969, and 3764, respectively, and the number of incorrectly determined was 923, 2359, and 3564, respectively, with error rates of 12.6%, 32.2%, and 48.6%, respectively. The distribution of the correlation coefficient r between the measured content ratio and the theoretical content ratio is shown in Figure 2, with a mean of 0.9642. There were 431 peptides with r < 0.95. When the polypeptides with low polypeptide level scores in the quantitative results of the method of the present invention are removed and the number of measurements is the same as that of DIA-NN, the number of accurate measurements is 6649, 5329, and 4023, respectively, and the number of incorrect measurements is 679, 1999, and 3305, respectively. The error rates are 9.3%, 27.3%, and 45.1%, respectively, which are significantly lower than those of DIA-NN. At the same time, the distribution of the correlation coefficient r between the ratio of measured content and the ratio of theoretical content is shown in Figure 2, with a mean value of 0.9748. Among them, there are only 288 polypeptides with r < 0.95, which proves the advantage of the quantitative accuracy of the method of the present invention. Spectronaut determined that 4136, 3641, and 2951 yeast peptides (Y2 / Y1, Y3 / Y1, and Y4 / Y1) were accurately measured, respectively, and 363, 858, and 1548 were incorrectly measured, with error rates of 8.1%, 19.1%, and 34.4%, respectively. The distribution of the correlation coefficient r between the measured content ratio and the theoretical content ratio is shown in Figure 2, with a mean of 0.9757. There were 144 peptides with r < 0.95.When the peptides with low peptide level scores in the quantitative results of the method of the present invention are removed and the number of measurements is the same as that of Spectronaut, the number of accurate measurements is 4268, 3659, and 2893, respectively, and the number of incorrect measurements is 231, 840, and 1606, respectively. The error rates are 5.1%, 18.7%, and 35.7%, respectively, which are lower than Spectronaut overall. At the same time, the distribution of the correlation coefficient r between the ratio of measured content and the ratio of theoretical content is shown in Figure 2. Its mean is 0.9853, among which there are only 62 peptides with r < 0.95, which proves the advantage of the quantitative accuracy of the method of the present invention.

[0099] The method for calculating the relative content of protein between samples is different from that in Example 1 only in that the FDR protein5%. In order to demonstrate the advantage of the method of the present invention in quantitative accuracy, the quantitative results of the two softwares, DIA-NN and Spectronaut, were compared. The relative error of the ratio of the content of the measured samples to the ratio of the theoretical content (Y2 / Y1, Y3 / Y1, Y4 / Y1) > 30% was used as the basis for judging the measurement error (the same below). While investigating the relative error of the ratio of the measured content to the theoretical content, the overall quantitative accuracy was investigated by the correlation coefficient between the ratio of the measured content and the theoretical content. In order to prevent the correlation coefficient used in subsequent comparisons from being distorted by missing values, proteins with missing values ​​in the content ratio (Y2 / Y1, Y3 / Y1, Y4 / Y1) were excluded before comparison. DIA-NN obtained that the number of yeast proteins (Y2 / Y1, Y3 / Y1, Y4 / Y1) accurately measured were 1388, 983, and 679, respectively, and the number of incorrectly measured were 125, 530, and 834, respectively, with error rates of 8.3%, 35.0%, and 55.1%, respectively. At the same time, the correlation coefficient r between the measured content ratio and the theoretical content ratio had an average value of 0.9679, among which there were 121 proteins with r<0.95. When proteins with low reliability scores in the quantitative results of the method of the present invention are removed and the number of measurements is the same as that of DIA-NN, the number of accurate measurements is 1429, 1163, and 870, respectively, and the number of incorrect measurements is 84, 350, and 643, respectively. The error rates are 5.6%, 23.1%, and 42.5%, respectively, which are significantly lower than those of DIA-NN. At the same time, the correlation coefficient r between the ratio of measured content and the ratio of theoretical content has an average value of 0.9757, among which there are only 49 proteins with r<0.95, which proves the advantage in quantitative accuracy. Spectronaut found that the number of yeast proteins (Y2 / Y1, Y3 / Y1, Y4 / Y1) accurately measured was 978, 880, and 756, respectively, and the number of incorrectly measured was 128, 226, and 350, respectively, with error rates of 11.6%, 20.4%, and 31.6%, respectively. At the same time, the correlation coefficient r between the measured content ratio and the theoretical content ratio had an average value of 0.9625, of which 80 proteins had r<0.95. When proteins with low reliability scores in the quantitative results of the method of the present invention were removed and the number of measurements was the same as that of Spectronaut, the numbers of accurate measurements were 1079, 918, and 724, respectively, and the numbers of incorrect measurements were 27, 188, and 382, ​​respectively. The error rates were 2.4%, 17.0%, and 34.5%, respectively, which were lower than Spectronaut overall. At the same time, the correlation coefficient r between the ratio of measured content and the ratio of theoretical content had an average value of 0.9932, among which there were only 12 proteins with r < 0.95, which proved that it still had an advantage in quantitative accuracy at the protein level.

[0100] Example 3

[0101] In this example, a proteomic hydrolysate was analyzed using the peptide quantitative analysis method integrating multiple LC-MS spectra. The method includes the following steps:

[0102] (1) Data-independent acquisition (DIA) mode was adopted, and liquid chromatography-mass spectrometry technology was used to perform liquid chromatography-mass spectrometry on multiple samples (33 isolation windows were used in DIA liquid chromatography-mass spectrometry, and the width of each mass-to-charge ratio window was different). Each sample was analyzed only once (i.e., no repetition), and 60 liquid chromatography-mass spectrometry spectra were obtained as liquid chromatography-mass spectrometry raw data; the samples were cerebrospinal fluid of 60 people collected in Sweden according to the literature (Bader, JMet al. Proteome profiling in cerebrospinal fluid reveals novel biomarkers of Alzheimer's disease. Mol. Syst. Biol., 16, 1-17, 2020), and they were divided into Alzheimer's disease group (29 samples) and normal group (31 samples).

[0103] The above steps have been completed and data is provided in the literature (Bader, J.M. et al. Proteome profiling in cerebrospinal fluid reveals novel biomarkers of Alzheimer's disease. Mol. Syst. Biol., 16, 1-17, 2020). The dataset download link is https: / / www.ebi.ac.uk / pride / archive / projects / PXD016278.

[0104] Liquid chromatography-mass spectrometry (LC-MS) analysis was performed using the data-dependent acquisition (DDA) mode to obtain a spectral library of the target peptide (the download link of the spectral library is: https: / / ftp.pride.ebi.ac.uk / pride / data / archive / 2020 / 05 / PXD016278 / final%20hybrid%20library_used%20for%20main%20study%20and%20CV%20experiment.zip). For each peptide in the spectral library, the following steps (2)-(7) were performed respectively;

[0105] (2) Based on the data in the spectral library constructed in the above steps, the measured retention time of the reference peptides (8 peptides with high content in the sample: NLGKVGSK, ETCFAEEGKK, AAFTECCQAADK, AACLLPK, KVPQVSTPTLVEVSR, VPQVSTPTLVEVSR, LVAASQAALGL, HPYFYAPELLFFAKR) in each LC-MS spectrum was used as the dependent variable, the relative retention time (iRT value) was used as the independent variable, and the iRT value of the target peptide was used as the sample point. The predicted retention time of the peptide was obtained after linear interpolation. According to the mass-to-charge ratio of the parent ion and fragment ion of each peptide in the spectral library, the allowable deviation range of the retention time was set to ±10min, and the allowable deviation range of the mass-to-charge ratio was set to 20ppm. The extracted ion current chromatograms of all secondary fragment ions within the above range were extracted from the original LC-MS data, and the chromatographic peaks therein were regarded as candidate chromatographic peaks and integrated.

[0106] Steps (3) to (7) in this embodiment are the same as those in Example 1, with the only difference being that, in step (5), the allowable deviation of the retention time is reduced to 1.82 min (obtained by leave-one-out cross-validation of the retention times of the above-mentioned 8 peptides), and that in step (7), when calculating the overall peptide level score, the relative standard deviation of the peak areas of multiple quantitative chromatographic peaks corresponding to the same sample is not included.

[0107] (8) Calculate the relative content of the identified polypeptides between samples based on the area of ​​each peak in the chromatographic peak group. Since the samples in this embodiment are actual clinical samples, the actual content and ratio of polypeptides and proteins are unknown, so it is not possible to directly judge whether the quantification is accurate. Instead, it is possible to judge whether the polypeptide quantification is accurate based on the principle that the relative content of multiple polypeptides produced by the enzymatic hydrolysis of the same protein is consistent between samples. Specifically, the ratio between the Alzheimer's disease group and the normal group measured by multiple polypeptides corresponding to the same protein (according to the spectral library data and the processing method of the comparative software, the different parent ion charge numbers of the same polypeptide in the spectral library are counted separately, the same below) is logarithmically transformed (log2) with a base of 2, and its standard deviation (SD) is calculated to characterize the consistency of the polypeptide quantification results. At the same time, the number of proteins that are both upregulated (ratio greater than 1) and downregulated (ratio less than 1) corresponding to the multiple polypeptides measured is counted to characterize the inconsistency of the quantitative results. In addition, since the above-mentioned comparative quantitative accuracy index does not involve the polypeptide level false discovery rate, this embodiment does not need to calculate the false (decoy) polypeptide.

[0108] (9) In order to demonstrate the advantages of the method of the present invention in terms of quantitative accuracy, the quantitative results of Spectronaut were compared (download link: https: / / ftp.pride.ebi.ac.uk / pride / data / archive / 2020 / 05 / PXD016278 / full%20report_extra%20data.zip). Spectronaut measured 967 proteins (only counting proteins corresponding to multiple polypeptides), of which 724 proteins corresponded to multiple polypeptides that were both up-regulated and down-regulated. The SD distribution of the polypeptides is shown in Figure 3, with a median of 0.33. The polypeptides with low polypeptide level scores in the quantitative results of the method of the present invention were removed, so that the number of proteins measured (only counting proteins corresponding to multiple polypeptides) was also 967, of which the number of proteins corresponding to multiple polypeptides that were both up-regulated and down-regulated was reduced to 625, and the median of the SD of the polypeptides was reduced to 0.24, indicating that the degree of consistency of the polypeptide quantitative results obtained by the method of the present invention was significantly high, which proves that the quantitative accuracy of the method of the present invention still has advantages in actual clinical samples.

[0109] The embodiments described above provide a detailed description of the technical solutions of the present invention. It should be understood that the above are only specific embodiments of the present invention and are not intended to limit the present invention. Any modifications, supplements or similar substitutions made within the scope of the principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A method for quantitative analysis of peptides by integrating multiple LC-MS spectra, characterized in that: include: A data-independent acquisition mode is adopted, and each sample is analyzed multiple times by liquid chromatography-mass spectrometry technology, or multiple groups of samples are analyzed once or multiple times. The ion flow chromatograms of secondary fragment ions in the original LC-MS data are extracted to obtain multiple LC-MS spectra. The consistency of retention time, ion mass-to-charge ratio and relative intensity of the same component between multiple analyses by liquid chromatography-mass spectrometry technology is used. At the same time, multiple LC-MS spectra are integrated and processed to exclude inconsistent chromatographic peaks and secondary fragment ions between multiple analyses, improve the accuracy of the quantitative chromatographic peaks and quantitative ions obtained by screening, and use the quantitative chromatographic peaks and quantitative ions obtained by screening to calculate the relative content of the identified polypeptide between samples.

2. The method for quantitative analysis of peptides by integrating multiple LC-MS spectra according to claim 1, characterized in that: The specific steps include: (1) Using a data-independent acquisition mode, each sample is analyzed multiple times using liquid chromatography-mass spectrometry, or multiple groups of samples are analyzed once or multiple times to obtain liquid chromatography-mass spectrometry raw data; (2) Predicting the retention time of each target polypeptide in the sample based on the data in the spectral library, extracting the scan data of the target polypeptide predicted retention time within the allowable deviation range from each LC / MS raw data, obtaining an extracted ion current chromatogram of all secondary fragment ions corresponding to the target polypeptide within the allowable deviation range of mass-to-charge ratio, and taking the chromatographic peak obtained by integrating the extracted ion current chromatogram as a candidate chromatographic peak; (3) For each candidate chromatographic peak, the consistency of the chromatographic peak shape of the secondary fragment ions of the same component is used to screen and exclude the secondary fragment ions with inconsistent peak shapes in the candidate chromatographic peaks, and then the measured peak areas of the remaining secondary fragment ions are calculated and the measured relative intensities are obtained. The relative intensities of the corresponding secondary fragment ions in the spectral library are used as a reference to exclude the secondary fragment ions with large relative intensity deviations; (4) Based on the principle that multiple measurements are closer to the true value, it is easier to find measured data close to the library spectrum in multiple LC-MS spectra, and the library matching score of the candidate chromatographic peak is calculated accordingly. Among all the candidate chromatographic peaks corresponding to the multiple LC-MS spectra, the candidate chromatographic peak with the highest library matching score is selected as the best matching peak; (5) Using the best matching peak as a reference, find the chromatographic peak of the target polypeptide in the LC-MS spectrum other than the LC-MS spectrum where the best matching peak is located. Specifically, use the consistency of the retention time of the same component between multiple LC-MS analyses, align the retention time of the best matching peak to the retention time of each LC-MS spectrum as the center, reduce the allowable deviation of the retention time, and retain the candidate chromatographic peaks whose measured retention time is within the allowable deviation range; then use the consistency of the ion mass-to-charge ratio and its relative intensity between multiple LC-MS analyses to calculate the similarity score between the retained candidate chromatographic peak and the best matching peak. Among the candidate chromatographic peaks corresponding to each LC-MS spectrum, select the candidate chromatographic peak with the largest similarity score as the measured chromatographic peak, and form a chromatographic peak group with the measured chromatographic peak and the best matching peak. If the largest similarity score in a certain LC-MS spectrum does not meet the critical value requirement, it is considered that the target polypeptide is not detected in the LC-MS spectrum; By using the consistency of the secondary fragment ions measured for the same component in multiple LC / MS analyses, the chromatographic peaks containing secondary fragment ions that are greatly different from other chromatographic peaks are excluded from the chromatographic peak group. The retained chromatographic peaks are used as quantitative chromatographic peaks for the final quantitative calculation, and the different secondary fragment ions between the retained quantitative chromatographic peaks are excluded. (6) using the consistency of the relative intensity of ions between multiple liquid-mass mass analyses, the quantitative ions are finally screened. Specifically, the ratio of the measured areas of the secondary fragment ions retained between the quantitative chromatographic peaks corresponding to each liquid-mass mass analysis is calculated. If there is an outlier in the ratio, the corresponding secondary fragment ions are excluded. The correlation between the measured areas of the retained secondary fragment ions in multiple quantitative chromatographic peaks is calculated, and the secondary fragment ions with low correlation are excluded. The retained secondary fragment ions are used as quantitative ions; (7) Calculating the chromatographic peak group score as a whole based on the quantitative chromatographic peaks and quantitative ions screened out from the chromatographic peak group, and then taking the weighted geometric mean or weighted arithmetic of the chromatographic peak group score and the highest library match score to obtain a peptide level score, and using the peptide level score to characterize the reliability of the determination, wherein the weight coefficient ranges from 0.1 to 10; (8) specifying a peptide level score critical value, and the target peptide whose peptide level score is higher than the corresponding score critical value is the identified peptide, and the critical value range is 0.75 to 0.95; (9) The area of ​​each chromatographic peak in the chromatographic peak group is obtained by summing up the quantitative ion area, and the relative content of the identified polypeptide among the samples is calculated based on the area of ​​each chromatographic peak in the sample chromatographic peak group.

3. The method for quantitative analysis of polypeptides by integrating multiple LC-MS spectra according to claim 2, characterized in that: In step (2), the method for predicting the retention time of the target polypeptide is as follows: using the measured retention time of the reference polypeptide in each LC-MS spectrum as the dependent variable, the relative retention time in the spectral library as the independent variable, and the relative retention time of the target polypeptide as the sample point, and obtaining the predicted retention time of the target polypeptide after linear interpolation or spline interpolation; And / or, in step (2), the allowable deviation range of retention time does not exceed 10 min, and the allowable deviation range of mass-to-charge ratio does not exceed 30 ppm.

4. The method for quantitative analysis of polypeptides by integrating multiple LC-MS spectra according to claim 2, characterized in that: In step (3), the method for excluding secondary fragment ions with large relative intensity deviation is: first calculate the root mean square error RMSE between the measured relative intensity of the secondary fragment ion and the relative intensity of the corresponding secondary fragment ion in the spectral library, and then calculate the root mean square error RMSE between the measured relative intensity after the secondary fragment ion is temporarily removed and the relative intensity of the corresponding secondary fragment ion in the spectral library -1 , if the RMSE of a secondary fragment ion -1 If RMSE is less than 0.05, the secondary fragment ion is excluded.

5. The method for quantitative analysis of polypeptides by integrating multiple LC-MS spectra according to claim 2, characterized in that: In step (4), the library match score is obtained by taking a weighted geometric mean or a weighted arithmetic mean of multiple individual scores; the individual scores include: a similarity score between the peak area of ​​each secondary fragment ion characterized by the normalized root mean square error and its library intensity, a deviation score between the measured mass-to-charge ratio of each secondary fragment ion and the theoretical mass-to-charge ratio, a score for the ratio of the number of retained measured secondary fragment ions to the number of library secondary fragment ions, a score for the consistency of chromatographic peak tops between secondary fragment ions, a score for the deviation between the measured retention time and the predicted retention time, and a score for the sum of the secondary fragment ion peak areas; and the weight coefficient of each individual score ranges from 0.01 to 100.

6. The method for quantitative analysis of peptides by integrating multiple LC-MS spectra according to claim 2, characterized in that: In step (5), the calculation method for aligning the retention time of the best matching peak to the retention time of each LC-MS spectrum is as follows: taking the measured retention time of the reference peptide in each LC-MS spectrum as the dependent variable, taking the measured retention time of the reference peptide in the LC-MS spectrum where the best matching peak is located as the independent variable, taking the retention time of the best matching peak as the sample point, and interpolating by linear interpolation or spline interpolation method to obtain the aligned retention time; And / or, in step (5), the permissible deviation of the retention time is reduced to ±0.1 to ±3 min; And / or, in step (5), the similarity score between the candidate chromatographic peak and the best matching peak is obtained by taking a weighted geometric mean or a weighted arithmetic mean of multiple individual scores; the individual scores include: a similarity score between the peak area of ​​each secondary fragment ion and the best matching peak intensity characterized by the normalized root mean square error, a deviation score between the measured mass-to-charge ratio of each secondary fragment ion and the theoretical mass-to-charge ratio, a score for the ratio of the number of retained measured secondary fragment ions to the number of best matching peak ions, and a score for the consistency of chromatographic peak tops between secondary fragment ions; and the weight coefficient of each individual score ranges from 0.01 to 100.

7. The method for quantitative analysis of polypeptides by integrating multiple LC-MS spectra according to claim 2, characterized in that: In step (6), the peak areas of the secondary fragment ions retained in the quantitative chromatographic peaks are taken as vectors, and the cosine of the angles between the two vectors is used to characterize the "correlation between the measured areas of different secondary fragment ions in multiple quantitative chromatographic peaks". The secondary fragment ions are clustered and analyzed using the angle cosine distance, i.e., 1 minus the angle cosine. If the angle cosine distance exceeds a critical value, the corresponding secondary fragment ion is a secondary fragment ion with low correlation; the critical value range is 0.02 to 0.

1.

8. The method for quantitative analysis of peptides by integrating multiple LC-MS spectra according to claim 2, characterized in that: In step (7), the chromatographic peak group score is obtained by calculating the weighted geometric mean or weighted arithmetic mean of multiple individual scores; the individual scores include: the similarity score between the peak area of ​​each secondary fragment ion characterized by the normalized root mean square error and its library intensity, the deviation score between the measured mass-to-charge ratio of each secondary fragment ion and the theoretical mass-to-charge ratio, the ratio score of the number of retained measured secondary fragment ions to the number of library secondary fragment ions, the consistency score of the chromatographic peak tops between the secondary fragment ions, the deviation score between the measured retention time and the predicted retention time, the relative standard deviation score between the peak areas of multiple quantitative chromatographic peaks corresponding to the same sample, and the ratio score of the number of quantitative chromatographic peaks in the chromatographic peak group to the number of LC-MS spectra, and the weight coefficient of each individual score ranges from 0.01 to 100; When multiple groups of samples are analyzed only once, the individual scores of the chromatographic peak group score do not include the relative standard deviation scores between the peak areas of multiple quantitative chromatographic peaks corresponding to the same sample.

9. The method for quantitative analysis of polypeptides by integrating multiple LC-MS spectra according to claim 2, characterized in that: In step (8), the method for specifying the polypeptide level score critical value is to repeat steps (2)-(7) for the pseudo-peptide library, merge and sort the polypeptide level scores of the target polypeptide and the pseudo-peptide, calculate the polypeptide level false discovery rate corresponding to each score critical value, and specify the polypeptide level score critical value according to the requirement of the polypeptide level false discovery rate; the requirement range of the false discovery rate is 0.1% to 10%.

10. Use of the polypeptide quantitative analysis method integrating multiple LC-MS spectra according to any one of claims 1 to 9 in protein analysis.

11. An electronic device, characterized in that: The method comprises at least a memory and a processor, wherein the memory stores a program, and the processor implements the polypeptide quantitative analysis method integrating multiple LC-MS spectra as claimed in any one of claims 1 to 9 when executing the program on the memory.

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