High-sensitivity and high-throughput chemical substance annotation method and system

Abstract

A high-sensitivity and high-throughput chemical substance annotation method and system, relating to the technical field of chemical substance identification. The method comprises: by means of EISA technology, collecting parent ions and fragment ions in a sample under test; constructing a chemical exposome database; by sequentially taking chemical substances in the chemical exposome database as target chemical substances, extract a parent ion chromatogram of the sample under test; performing calibration to obtain a target chromatogram; screening all chromatographic peaks in the target chromatogram to obtain candidate chromatographic peaks and peak types thereof; for each candidate chromatographic peak, traversing matching target chemical substances, and obtaining a relevant characteristic score of each candidate chromatographic peak corresponding to the target chemical substances; on the basis of the peak types and the relevant characteristic scores, sorting all the candidate chromatographic peaks corresponding to the target chemical substances; and outputting the first several candidate chromatographic peaks in the sorting result as a final screening result of chemical substances in the sample under test. The present application can significantly increase the number of low-concentration chemical substances detected and has the advantages of high sensitivity and high throughput.

Description

A highly sensitive and high-throughput chemical substance annotation method and system Technical Field

[0001] The present invention relates to the technical field of chemical substance identification, and more particularly, to a highly sensitive, high-throughput chemical substance annotation method and system. Background Art

[0002] Chemical annotation is a crucial component of exposome research. The concept of exposure was originally developed to explain environmental drivers of health and disease. It now represents all exogenous and endogenous environmental exposures and their associated biological effects throughout the life cycle. Xenobiotic chemical concentrations in biological and environmental samples range widely, reaching low concentrations at the ppb or nanomolar level. Therefore, a highly sensitive chemical exposure mapping technology with broad chemical coverage is urgently needed to advance exposure-based research. Traditional chemical annotation requires the acquisition of parent ion mass spectrometry (MS) data and fragment ion mass spectrometry data using a tandem mass spectrometer. Parent ions, also known as precursor ions, are typically generated within the ion source. The generation of fragment ions typically requires combining an electrospray ionization (ESI) source with a tandem mass spectrometer. Once the parent ions enter the collision chamber, they react with inert gas molecules under the action of energy to produce fragment ions.

[0003] Targeted detection based on triple quadrupole mass spectrometry is generally considered the most sensitive technology for monitoring exposure biomarkers. However, this method can only monitor a limited number of chemicals, limiting its application in exposure studies. Non-targeted analysis methods based on high-resolution mass spectrometry (HRMS) can detect a wide range of chemicals. They typically use a full-scan acquisition method to obtain the m / z (mass-to-charge ratio) and retention time (RT) information of the precursor ion, and then use data-dependent acquisition (DDA) mode or data-independent acquisition (DIA) mode to generate the mass spectrum (MS / MS). Data-dependent acquisition (DDA) mode is a major mode of data acquisition in tandem mass spectrometry. In DDA mode, the mass spectrometer automatically performs MS / MS analysis on a list of precursor ions selected from the full-scan spectrum when performing an MS full scan. DDA mode is typically used to collect fragment spectra of exposure features of interest. The selection of parent ions depends on ion intensity, so mass spectral features of low-abundance exposures may never be selected to generate fragments in the collision cell. The advantage of DDA mode is high selectivity, but the throughput is low, making it difficult to achieve batch acquisition of chemical fragment ions. Data-independent acquisition (DIA) mode is a mode for batch acquisition of chemical fragment ions in mass spectrometry. In this mode, all ions within a selected m / z range are fragmented and analyzed in the second stage of tandem mass spectrometry. This mode obtains tandem mass spectrometry data by fragmenting all ions entering the mass spectrometer at a given time or by sequentially separating and fragmenting m / z ranges. Although DIA mode can achieve batch acquisition of chemical fragment ions, it has low selectivity.

[0004] Informatics algorithms have certain limitations in the annotation of chemical substances at lower levels. Currently, the data processing informatics algorithms used for autonomous chemical identification and annotation in exposure studies mainly draw on algorithms from the field of metabolomics. However, the concentrations of endogenous metabolites in biological samples are usually several orders of magnitude higher than those of exogenous chemicals in the same samples. Even in environmental samples, the concentrations of chemical pollutants are low, usually around ppb. Early studies have shown that traditional metabolomics data preprocessing software such as XCMS will miss a large number of metabolic features, that is, features with low abundance and / or poor shape. Therefore, traditional peak extraction algorithms will lead to feature loss and affect downstream substance identification.

[0005] The applicant previously proposed a highly sensitive chemical analysis technology (EISA) based on the high-energy fragmentation phenomenon in the mass spectrometry ion source. As a simple and effective method for generating in-source fragments in an electrospray ionization (ESI) source, EISA has changed the traditional tandem mass spectrometry fragment generation strategy. By optimizing the in-source fragmentation conditions, the in-source fragment generation uses the EISA technology full-scan mode HRMS to simulate the endogenous metabolites and peptides of the medium and high-energy MS / MS fragment spectra through collision-induced dissociation (CID) technology in the collision cell without affecting the intensity of the precursor ion, thereby effectively realizing the identification of low-concentration chemical substances. However, traditional mass spectrometry data analysis software such as XCMS cannot analyze EISA data. Therefore, there is an urgent need to propose a highly sensitive and high-throughput chemical substance annotation method.

[0006] The prior art provides a compound fragment ion prediction method and application, including: 1) determining the compound used for the experiment, the parent ion molecular formula of the compound, and the fragment ion molecular formula; 2) selecting a stable isotope based on the elemental composition of the parent ion and the fragment ion; 3) calculating the stable isotope labeling of the parent ion and the fragment ion based on the determined compound, the parent ion molecular formula and the fragment ion molecular formula, and the number of stable isotope elements in the parent ion and the fragment ion; 4) calculating the number of stable isotope labeling of all parent ions and all fragment ions; 5) calculating the accurate mass of the parent ion and fragment ion in all labeled cases based on the number of labeled cases obtained in step 4), and calculating the mass-to-charge ratio; 6) establishing a mass-to-charge ratio database of the compound fragment ions. This prior art requires a clear relationship between the parent ion and fragment ion in the compound used for the experiment, while the EISA technology collects all parent ions and fragment ions in a full scan. The relationship between the parent ion and the fragment ion is unclear and is not suitable for EISA data.

[0007] Summary of the Invention

[0008] In order to overcome the defects of the above-mentioned prior art that cannot accurately analyze EISA data and thus cannot achieve high-sensitivity and high-throughput chemical substance detection, the present invention provides a highly sensitive and high-throughput chemical substance annotation method and system, which significantly increases the number of low-concentration chemical substances detected, with high sensitivity and high throughput.

[0009] In order to solve the above technical problems, the technical solutions of the present invention are as follows:

[0010] The present invention provides a highly sensitive and high-throughput chemical substance annotation method, comprising:

[0011] S1: Based on EISA technology, the parent ions and fragment ions in the sample to be tested are collected;

[0012] S2: Build a chemical exposure group database, including several chemical substances and their mass spectrometry data;

[0013] S3: setting a mass accuracy standard, taking the chemical substances in the chemical exposure group database as target chemical substances in turn, and extracting the corresponding parent ion chromatograms of the samples to be tested;

[0014] S4: calibrating the parent ion chromatogram of the sample to be detected to obtain a target chromatogram; the target chromatogram includes several chromatographic peaks;

[0015] S5: Screening all chromatographic peaks to obtain candidate chromatographic peaks and their peak types;

[0016] S6: For each candidate chromatographic peak, traverse the matching target chemical substances and calculate the relevant feature score of each candidate chromatographic peak corresponding to the target chemical substance;

[0017] S7: sorting each candidate chromatographic peak corresponding to the target chemical substance based on the peak type and related feature score of the candidate chromatographic peak to obtain a sorting result;

[0018] S8: Output the top several candidate chromatographic peaks in the sorting results as the final screening results of the chemical substances in the sample to be detected.

[0019] Preferably, in step S2, a chemical exposure group database is constructed based on a local database of chemical standards, an open source mass spectrometry database, and mass spectrometry data from public literature; the chemical exposure group database includes several chemical substances and their mass spectrometry data, and the mass spectrometry data of each chemical substance includes the name of the chemical substance, the mass-to-charge ratio of the parent ion, the mass-to-charge ratio of the fragment ion, and the intensity.

[0020] Preferably, in step S3, a mass accuracy standard is set, and the chemical substances in the chemical exposure group database are sequentially used as target chemical substances. The specific method for extracting the parent ion chromatogram of the sample to be tested is:

[0021] The chemical substances in the chemical exposure group database are taken as target chemical substances in turn, and the mass-to-charge ratio range of the parent ions to be extracted is obtained according to the mass-to-charge ratio of the parent ions of the target chemical substances and the set mass accuracy standard; in the sample to be tested, for ions whose parent ion mass-to-charge ratio is within the parent ion mass-to-charge ratio range, an extraction and chromatogram construction operation is performed.

[0022] Preferably, in step S4, the parent ion chromatogram of the sample to be detected is corrected to obtain the target chromatogram by:

[0023] For the extracted chromatogram of the sample to be tested, the corresponding chromatogram parts before the start and after the end of the chromatographic elution are deleted, and the remaining chromatogram is used as the target chromatogram for subsequent analysis.

[0024] The chromatographic elution is set according to actual conditions, and the corresponding chromatogram parts before and after the elution are deleted, and only the chromatogram part during the elution process is retained, which reduces the occurrence of false positive features and makes the detection results more accurate.

[0025] Preferably, the specific method of step S5 is:

[0026] S5.1: Calculate the peak height and sawtooth index for all chromatographic peaks.

[0027] S5.2: Filter out the chromatographic peaks whose peak heights are lower than a preset peak height threshold, and use the remaining chromatographic peaks as candidate chromatographic peaks;

[0028] S5.3: Detect candidate chromatographic peaks using existing mass spectrometry data analysis algorithms;

[0029] S5.4: For candidate chromatographic peaks that can be detected by existing mass spectrometry data analysis algorithms, the peak type of the corresponding candidate chromatographic peak is classified as the first type; for candidate chromatographic peaks that cannot be detected by existing mass spectrometry data analysis algorithms, if their sawtooth index is less than a preset sawtooth index threshold, the peak type of the corresponding candidate chromatographic peak is classified as the second type; otherwise, the peak type of the corresponding candidate chromatographic peak is classified as the third type.

[0030] Filtering chromatographic peaks with peak heights lower than a preset peak height threshold can reduce the number of candidate chromatographic peaks without affecting the accuracy of the test results, thereby increasing the detection speed and reducing the occurrence of false positive features. Secondly, when classifying the peak types of candidate chromatographic peaks, not only whether they can be detected by existing mass spectrometry data analysis algorithms is considered, but also the sawtooth index is considered, retaining features that cannot be detected by existing mass spectrometry data analysis algorithms, thereby expanding the scope of chemical substance identification. The third type of candidate chromatographic peak is used as a reference type, and whether to further filter it is selected based on actual needs; if filtered, there are two types of peaks used for subsequent analysis, namely the first type and the second type; if not filtered, there are three types of peaks used for subsequent analysis.

[0031] Preferably, in step S5.1, if the target chemical substance has a retention time in the chemical exposure group database, only the peak height and sawtooth index of the chromatographic peak appearing in the retention time window are calculated.

[0032] By using the retention time window, the range and number of chromatographic peaks that need to be screened are narrowed, which can effectively improve the subsequent matching speed and accuracy.

[0033] Preferably, the specific method of step S6 is:

[0034] S6.1: For each candidate chromatographic peak, sequentially match the fragment ions corresponding to the top of the candidate chromatographic peak with the fragment ions of the target chemical in the chemical exposure group database to obtain the matching fragment ions at the top of each candidate chromatographic peak and their number, mass-to-charge ratio, and intensity.

[0035] S6.2: Calculate a first score and a second score based on the matching fragment ions at the top of the candidate chromatographic peak and the fragment ions of the target chemical in the chemical exposure group database;

[0036] S6.3: Calculate a relevant characteristic score of a candidate chromatographic peak corresponding to the target chemical substance based on the first score and the second score;

[0037] S6.4: Repeat steps S6.1-S6.3 to obtain the relevant characteristic score of each candidate chromatographic peak corresponding to the target chemical substance.

[0038] Preferably, in step S6.2, the specific method for calculating the first score is:

[0039] The first score is calculated based on the number of matching fragment ions at the top of the candidate chromatographic peak and the number of fragment ions of the target chemical in the chemical exposure group database. The calculation formula is:

[0040] Where, MFR i Indicates the first score of the fragment ion matched at the top of the i-th candidate chromatographic peak of the target chemical, N i Indicates the number of matching fragment ions at the top of the i-th candidate chromatographic peak, N T Represents the number of fragment ions of target chemicals in the chemical exposome database.

[0041] Preferably, in step S6.2, the specific method for calculating the second score is:

[0042] The second score is calculated based on the intensity of the fragment ion matched at the top of the candidate chromatographic peak and the intensity of the fragment ion of the target chemical in the chemical exposure group database. The calculation formula is:

[0043] Where, SSM i represents the second score of the fragment ion matched at the top of the i-th candidate chromatographic peak of the target chemical, W Qi represents the intensity of the fragment ion matched at the top of the i-th candidate chromatographic peak, W Ri represents the intensity of the i-th fragment ion of the target chemical in the chemical exposure group database.

[0044] Preferably, in step S6.3, the specific method for calculating the relevant characteristic scores of the candidate chromatographic peaks corresponding to the target chemical substance based on the first score and the second score is:

[0045] Assign weight coefficients to the first score and the second score respectively, and calculate the relevant feature scores of the candidate features corresponding to the target chemical substances: Score i =αMFR i +βSSM i

[0046] In the formula, Score i represents the relevant feature score of the candidate feature of the i-th candidate chromatographic peak corresponding to the target chemical substance, and α and β represent the first and second weight coefficients respectively.

[0047] Preferably, the specific method of step S7 is:

[0048] S7.1: Set the sorting priority of the peak types of candidate chromatographic peaks, from high to low, as first type, second type, and third type;

[0049] S7.2: For all candidate chromatographic peaks belonging to the same peak type, arrange their associated feature scores in descending order to obtain candidate features of the target chemical within each peak type;

[0050] S7.3: Concatenate the candidate features of the target chemical substances within each peak type according to the sorting priority of the peak type to obtain a sorting result.

[0051] The present invention also provides a highly sensitive, high-throughput chemical substance annotation system for implementing the above-mentioned annotation method, comprising:

[0052] A data acquisition module is used to collect parent ions and fragment ions in the sample to be detected based on EISA technology;

[0053] Database construction module, used to build a chemical exposure group database, including several chemical substances and their mass spectrometry data;

[0054] a chromatogram generation module, for setting mass accuracy standards, taking the chemical substances in the chemical exposure group database as target chemical substances in turn, and extracting corresponding parent ion chromatograms of the samples to be tested;

[0055] A chromatogram correction module is used to correct the parent ion chromatogram of the sample to be detected to obtain a target chromatogram; the target chromatogram includes several chromatographic peaks;

[0056] Chromatographic peak screening module, used to screen all chromatographic peaks to obtain candidate chromatographic peaks and their peak types;

[0057] A data matching module is used to traverse and match target chemicals for each candidate chromatographic peak and calculate the relevant feature score of each candidate chromatographic peak corresponding to the target chemical;

[0058] A sorting module is used to sort each candidate chromatographic peak corresponding to the target chemical substance based on the peak type and related feature score of the candidate chromatographic peak to obtain a sorting result;

[0059] The chemical substance detection module is used to output the first several candidate chromatographic peaks in the sorting results as the final screening results of the chemical substances in the sample to be detected.

[0060] Compared with the prior art, the beneficial effects of the technical solution of the present invention are:

[0061] The present invention first uses EISA technology to collect all parent ions and fragment ions of the sample to be tested; then constructs a chemical exposure group database including several chemical substances and their mass spectrometry data, extracts parent ion chromatograms of the sample to be tested using the chemical substances as target chemicals in turn; corrects the parent ion chromatogram to obtain a target chromatogram containing several chromatographic peaks; then screens all chromatographic peaks to obtain candidate chromatographic peaks and their peak types; for each candidate chromatographic peak, traverses and matches the target chemical substance to obtain the relevant feature score of each candidate chromatographic peak corresponding to the target chemical substance; finally, sorts each candidate chromatographic peak corresponding to the target chemical substance based on the peak type and relevant feature score of the candidate chromatographic peak, and outputs the top several candidate chromatographic peaks in the sorting result as the final screening result of the chemical substance in the sample to be tested. The present invention can significantly increase the number of low-concentration chemical substances detected, with high sensitivity and high throughput. BRIEF DESCRIPTION OF THE DRAWINGS

[0062] FIG1 is a flow chart of a highly sensitive, high-throughput chemical substance annotation method described in Example 1.

[0063] FIG2 is a schematic diagram of the chemical exposure group database described in Example 2.

[0064] FIG3 is a chromatogram of the sample to be detected extracted based on the preset mass accuracy standard described in Example 2.

[0065] FIG4 is a target chromatogram as described in Example 2.

[0066] FIG5 shows the chromatographic peaks to be processed when the retention time exists as described in Example 2.

[0067] FIG6 shows the chromatographic peaks to be processed when there is no retention time as described in Example 2.

[0068] FIG7 is a schematic diagram comparing the detection results of the method provided in this embodiment described in Example 2 and the traditional peak extraction algorithm at different concentrations.

[0069] FIG8 is a schematic diagram comparing the detection results of the method provided in this embodiment and the traditional TMM collection method at different concentrations described in Example 2.

[0070] FIG9 is a schematic structural diagram of a highly sensitive, high-throughput chemical substance annotation system described in Example 3. DETAILED DESCRIPTION

[0071] The accompanying drawings are for illustrative purposes only and are not to be construed as limiting this patent;

[0072] In order to better illustrate this embodiment, some parts in the drawings may be omitted, enlarged, or reduced, and do not represent the actual product size;

[0073] It is understandable to those skilled in the art that some well-known structures and descriptions thereof may be omitted in the drawings.

[0074] The technical solution of the present invention is further described below with reference to the accompanying drawings and embodiments.

[0075] Example 1

[0076] This embodiment provides a highly sensitive and high-throughput chemical substance annotation method, as shown in FIG1 , including:

[0077] S1: Based on EISA technology, the parent ions and fragment ions in the sample to be tested are collected;

[0078] S2: Build a chemical exposure group database, including several chemical substances and their mass spectrometry data;

[0079] S3: setting a mass accuracy standard, taking the chemical substances in the chemical exposure group database as target chemical substances in turn, and extracting the corresponding parent ion chromatograms of the samples to be tested;

[0080] S4: calibrating the parent ion chromatogram of the sample to be detected to obtain a target chromatogram; the target chromatogram includes several chromatographic peaks;

[0081] S5: Screening all chromatographic peaks to obtain candidate chromatographic peaks and their peak types;

[0082] S6: For each candidate chromatographic peak, traverse the matching target chemical substances and calculate the relevant feature score of each candidate chromatographic peak corresponding to the target chemical substance;

[0083] S7: sorting each candidate chromatographic peak corresponding to the target chemical substance based on the peak type and related feature score of the candidate chromatographic peak to obtain a sorting result;

[0084] S8: Output the top several candidate chromatographic peaks in the sorting results as the final screening results of the chemical substances in the sample to be detected.

[0085] In the specific implementation process, this embodiment first uses EISA technology to collect all parent ions and fragment ions of the sample to be detected; then constructs a chemical exposure group database including several chemical substances and their mass spectrometry data, and extracts the parent ion chromatograms of the sample to be detected as target chemical substances in turn; corrects the parent ion chromatogram to obtain a target chromatogram containing several chromatographic peaks; then screens all chromatographic peaks to obtain candidate chromatographic peaks and their peak types; for each candidate chromatographic peak, traverses and matches the target chemical substance to obtain the relevant feature score of each candidate chromatographic peak corresponding to the target chemical substance; finally, the peak type and relevant feature score of the candidate chromatographic peak are used to sort each candidate chromatographic peak corresponding to the target chemical substance, and the top several candidate chromatographic peaks in the sorting result are output as the final screening result of the chemical substance in the sample to be detected. This embodiment can significantly increase the number of low-concentration chemical substances detected, with high sensitivity and high throughput.

[0086] Example 2

[0087] This example provides a highly sensitive and high-throughput chemical substance annotation method, including:

[0088] S1 is based on EISA technology, which collects parent ions and fragment ions in the sample to be tested. EISA technology collects all parent ions and fragment ions in the sample to be tested in one full scan, and the correspondence between fragment ions and parent ions cannot be determined.

[0089] S2: Build a chemical exposure group database, including several chemical substances and their mass spectrometry data;

[0090] As shown in Figure 2, a chemical exposure group database was constructed based on the mass spectrometry data of a local chemical standard database, an open source mass spectrometry database, and public literature. The chemical exposure group database includes several chemical substances and their mass spectrometry data. The mass spectrometry data of each chemical substance includes the chemical substance name, parent ion mass-to-charge ratio, fragment ion mass-to-charge ratio, and intensity.

[0091] S3: setting a mass accuracy standard, taking the chemical substances in the chemical exposure group database as target chemical substances in turn, and extracting the corresponding parent ion chromatograms of the samples to be tested;

[0092] Specifically, the chemical substances in the chemical exposure group database are taken as target chemical substances in turn, and the parent ion mass-to-charge ratio range that needs to be extracted is obtained according to the parent ion mass-to-charge ratio of the target chemical substance and the set mass accuracy standard; in the sample to be detected, for ions whose parent ion mass-to-charge ratio is within the parent ion mass-to-charge ratio range, an operation of extracting and constructing a chromatogram is performed. For example, if the parent ion mass-to-charge ratio of the target chemical substance in the chemical exposure group database is 183.0991Da and the preset mass accuracy standard is ±0.01Da, the parent ion mass-to-charge ratio range that needs to be extracted in the sample to be detected is [183.0891, 183.1091]; as shown in Figure 3, in the sample to be detected, all ions whose parent ion mass-to-charge ratio is located at [183.0891, 183.1091] are extracted and a chromatogram is constructed;

[0093] S4: For the extracted chromatogram of the sample to be tested, the corresponding portions of the chromatogram before the start of chromatographic elution and after the end of chromatographic elution are deleted, and the remaining portion of the chromatogram is used as a target chromatogram for subsequent analysis; each target chromatogram includes a plurality of chromatographic peaks;

[0094] As shown in Figure 4, the chromatographic elution is set according to the actual situation, and the corresponding chromatogram parts before and after the elution are deleted, and only the chromatogram part during the elution process is retained, which reduces the occurrence of false positive features and makes the detection results more accurate. In this embodiment, the chromatographic system starts elution at 90s and ends elution at 900s, then the parts before 90s and after 900s of the entire chromatogram are deleted, and the part between 90s and 900s is retained to obtain the target chromatogram.

[0095] S5: Screen all chromatographic peaks to obtain candidate chromatographic peaks and their peak types; specifically:

[0096] S5.1: If the target chemical in the chemical exposure group database has a retention time, only the peak height and sawtooth index of the chromatographic peak appearing in the retention time window are calculated; as shown in Figure 5, if the target chemical in the chemical exposure group database has a retention time of 4.822 minutes, it is converted to 289.32 seconds; the chromatographic peaks are extracted from the chromatogram according to the preset time window and subsequent analysis is performed. In this embodiment, the time window is ±90 seconds, and the peak height and sawtooth index of the chromatographic peak appearing in the time period of 289.32 ± 90 seconds are calculated;

[0097] As described in Figure 6 , if the target chemical does not have a retention time in the chemical exposure group database, the peak height and sawtooth index of all occurring chromatographic peaks are calculated;

[0098] S5.2: Filter out the chromatographic peaks whose peak heights are lower than a preset peak height threshold, and use the remaining chromatographic peaks as candidate chromatographic peaks;

[0099] S5.3: Detect candidate chromatographic peaks using existing mass spectrometry data analysis algorithms;

[0100] S5.4: For candidate chromatographic peaks that can be detected by existing mass spectrometry data analysis algorithms, the peak type of the corresponding candidate chromatographic peak is classified as the first type; for candidate chromatographic peaks that cannot be detected by existing mass spectrometry data analysis algorithms, if their sawtooth index is less than a preset sawtooth index threshold, the peak type of the corresponding candidate chromatographic peak is classified as the second type; otherwise, the peak type of the corresponding candidate chromatographic peak is classified as the third type.

[0101] In this embodiment, the peak height threshold is 1000, the sawtooth index is 0.2, and the existing mass spectrometry data analysis algorithm is the XCMS algorithm.

[0102] If the retention time of the target chemical substance exists in the chemical exposure group database, the range and number of chromatographic peaks that need to be screened can be narrowed, which can effectively improve the subsequent matching speed and accuracy.

[0103] Filtering chromatographic peaks with a peak height lower than a preset peak height threshold or a sawtooth index greater than a preset sawtooth index threshold can reduce the number of candidate chromatographic peaks without affecting the accuracy of the test results, thereby improving the detection speed and reducing the false positive rate. In addition, when classifying the peak types of candidate chromatographic peaks, not only whether they can be detected by existing mass spectrometry data analysis algorithms is considered, but also the sawtooth index is considered, retaining features that cannot be detected by existing mass spectrometry data analysis algorithms, thereby expanding the scope of chemical substance identification. The third type of candidate chromatographic peak is used as a reference type, and whether to further filter it is selected according to actual needs; if filtered, there are two peak types used for subsequent analysis, namely the first type and the second type; if not filtered, there are three peak types used for subsequent analysis.

[0104] S6: For each candidate chromatographic peak, the target chemical substance is traversed and matched, and the relevant feature score of each candidate chromatographic peak corresponding to the target chemical substance is calculated; specifically:

[0105] S6.1: For each candidate chromatographic peak, sequentially match the fragment ions corresponding to the top of the candidate chromatographic peak with the fragment ions of the target chemical in the chemical exposure group database to obtain the matching fragment ions at the top of each candidate chromatographic peak and their number, mass-to-charge ratio, and intensity.

[0106] S6.2: Calculate a first score based on the number of matching fragment ions at the top of the candidate chromatographic peak and the number of fragment ions of the target chemical in the chemical exposure group database, using the following formula:

[0107] Where, MFR iIndicates the first score of the fragment ion matched at the top of the i-th candidate chromatographic peak of the target chemical, N i Indicates the number of matching fragment ions at the top of the i-th candidate chromatographic peak, N T represents the number of fragment ions of target chemicals in the chemical exposome database;

[0108] The second score is calculated based on the intensity of the fragment ion matched at the top of the candidate chromatographic peak and the intensity of the fragment ion of the target chemical in the chemical exposure group database. The calculation formula is:

[0109] Where, SSM i represents the second score of the fragment ion matched at the top of the i-th candidate chromatographic peak of the target chemical, W Qi represents the intensity of the fragment ion matched at the top of the i-th candidate chromatographic peak, W Ri represents the intensity of the i-th fragment ion of the target chemical in the chemical exposure group database;

[0110] S6.3: Based on the first score and the second score, the specific method for calculating the relevant characteristic score of the candidate chromatographic peak corresponding to the target chemical substance is as follows:

[0111] Assign weight coefficients to the first score and the second score respectively, and calculate the relevant feature scores of the candidate features corresponding to the target chemical substances: Score i =αMFR i +βSSM i

[0112] In the formula, Score i represents the relevant feature score of the candidate feature of the i-th candidate chromatographic peak corresponding to the target chemical substance, α and β represent the first and second weight coefficients respectively; in this embodiment, α = 0.7, β = 0.3;

[0113] S6.4: Repeat steps S6.1-S6.3 to obtain the relevant characteristic score of each candidate chromatographic peak corresponding to the target chemical substance.

[0114] S7: Sort each candidate chromatographic peak corresponding to the target chemical substance based on the peak type and related feature score of the candidate chromatographic peak to obtain a ranking result; specifically:

[0115] S7.1: Set the sorting priority of the peak types of candidate chromatographic peaks, from high to low, as first type, second type, and third type;

[0116] S7.2: For all candidate chromatographic peaks belonging to the same peak type, arrange their associated feature scores in descending order to obtain candidate features of the target chemical within each peak type;

[0117] S7.3: Concatenate the candidate features of the target chemical substances within each peak type according to the sorting priority of the peak type to obtain a sorting result.

[0118] S8: Output the top several candidate chromatographic peaks in the sorting results as the final screening results of the chemical substances in the sample to be detected.

[0119] During the specific implementation process, the method provided in this embodiment was compared with traditional peak extraction algorithms, such as the XCMS algorithm, the MZmine3 algorithm, and the MSDIAL algorithm, to perform characteristic detection of chemical substances at concentrations of 500 ppb and 0.8 ppb, respectively, and compared with the manual inspection results. The detection result comparison diagram is shown in Figure 7; it can be seen that the method of this embodiment detects the largest number of chemical substance features at 500 ppb and 0.8 ppb, and has higher sensitivity.

[0120] The method provided in this example was compared with a traditional TMM acquisition method using a standard mixture containing 50 pollutants. The number of pollutant signatures was determined at concentrations of 20 ppb, 4 ppb, and 0.8 ppb. As shown in Figure 8, the method provided in this example can detect chemical signatures with minimal change as concentrations decrease, significantly exceeding the number of chemical signatures detected using the traditional TMM acquisition method. The method provided in this example can accurately detect chemical signatures even at a concentration as low as 0.8 ppb, demonstrating high sensitivity and throughput.

[0121] Further experiments were conducted to verify the above. Dust samples were used as samples to be tested. The methods of this embodiment and the traditional TMM collection method were used for testing. The test results are shown in the following table:

[0122] In this experiment, the chemical exposure group database constructed includes 200 pesticides. It can be seen that the method of this embodiment identified 25 pesticides; while the TTM acquisition method identified 13 pesticides through manual inspection, and the chemical substances with MFR equal to 0 indicated that no parent ion was matched; and the intensity of the parent ion identified by the method of this embodiment was much higher than the intensity of the parent ion identified by the TTM acquisition method, that is, the method provided in this embodiment can collect the characteristics of fragment ions without affecting the abundance of the parent ion, thereby realizing high-sensitivity and high-throughput detection.

[0123] Example 3

[0124] This embodiment also provides a highly sensitive, high-throughput chemical substance annotation system for implementing the annotation method described in Example 1 or 2, as shown in FIG9 , comprising:

[0125] A data acquisition module is used to collect parent ions and fragment ions in the sample to be detected based on EISA technology;

[0126] Database construction module, used to build a chemical exposure group database, including several chemical substances and their mass spectrometry data;

[0127] a chromatogram generation module, for setting mass accuracy standards, taking the chemical substances in the chemical exposure group database as target chemical substances in turn, and extracting corresponding parent ion chromatograms of the samples to be tested;

[0128] A chromatogram correction module is used to correct the parent ion chromatogram of the sample to be detected to obtain a target chromatogram; the target chromatogram includes several chromatographic peaks;

[0129] Chromatographic peak screening module, used to screen all chromatographic peaks to obtain candidate chromatographic peaks and their peak types;

[0130] A data matching module is used to traverse and match target chemicals for each candidate chromatographic peak and calculate the relevant feature score of each candidate chromatographic peak corresponding to the target chemical;

[0131] A sorting module is used to sort each candidate chromatographic peak corresponding to the target chemical substance based on the peak type and related feature score of the candidate chromatographic peak to obtain a sorting result;

[0132] The chemical substance detection module is used to output the first several candidate chromatographic peaks in the sorting results as the final screening results of the chemical substances in the sample to be detected.

[0133] The same or similar reference numerals correspond to the same or similar components;

[0134] The terms used in the drawings to describe positional relationships are for illustrative purposes only and should not be construed as limiting this patent;

[0135] Obviously, the above embodiments of the present invention are merely examples for the purpose of clearly illustrating the present invention, and are not intended to limit the embodiments of the present invention. Those skilled in the art will appreciate that other variations or modifications can be made based on the above description. It is not necessary and impossible to enumerate all embodiments here. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention shall be included within the scope of protection of the claims of the present invention.

Claims

1. A highly sensitive and high-throughput chemical substance annotation method, characterized in that: include: S1: Based on EISA technology, the parent ions and fragment ions in the sample to be tested are collected; S2: Build a chemical exposure group database, including several chemical substances and their mass spectrometry data; S3: setting a mass accuracy standard, taking the chemical substances in the chemical exposure group database as target chemical substances in turn, and extracting the parent ion chromatogram of the sample to be tested accordingly; S4: calibrating the parent ion chromatogram of the sample to be detected to obtain a target chromatogram; the target chromatogram includes a plurality of chromatographic peaks; S5: Screening all chromatographic peaks to obtain candidate chromatographic peaks and their peak types; S6: For each candidate chromatographic peak, traverse the matching target chemical substances, and calculate the relevant feature score of each candidate chromatographic peak corresponding to the target chemical substance; S7: sorting each candidate chromatographic peak corresponding to the target chemical substance based on the peak type and the relevant characteristic score of the candidate chromatographic peak to obtain a sorting result; S8: Output the first several candidate chromatographic peaks in the sorting results as the final screening results of the chemical substances in the sample to be detected.

2. The highly sensitive and high-throughput chemical substance annotation method according to claim 1, characterized in that: In step S2, a chemical exposure group database is constructed based on a local database of chemical standards, an open source mass spectrometry database, and mass spectrometry data from public literature; the chemical exposure group database includes several chemical substances and their mass spectrometry data, and the mass spectrometry data of each chemical substance includes the name of the chemical substance, the mass-to-charge ratio of the parent ion, the mass-to-charge ratio of the fragment ion, and the intensity.

3. The highly sensitive and high-throughput chemical substance annotation method according to claim 1, characterized in that: In step S4, the parent ion chromatogram of the sample to be detected is corrected, and the specific method for obtaining the target chromatogram is: For the extracted chromatogram of the sample to be tested, the corresponding chromatogram parts before the start and after the end of the chromatographic elution are deleted, and the remaining part of the chromatogram is used as the target chromatogram for subsequent analysis.

4. The highly sensitive, high-throughput chemical substance annotation method according to claim 2 or 3, characterized in that: The specific method of step S5 is: S5.1: Calculate the peak height and sawtooth index of all chromatographic peaks; S5.2: Filter the chromatographic peaks whose peak heights are lower than a preset peak height threshold, and use the remaining chromatographic peaks as candidate chromatographic peaks; S5.3: Detect candidate chromatographic peaks using existing mass spectrometry data analysis algorithms; S5.4: For candidate chromatographic peaks that can be detected by the existing mass spectrometry data analysis algorithm, the peak type of the corresponding candidate chromatographic peak is classified as the first type; for candidate chromatographic peaks that cannot be detected by the existing mass spectrometry data analysis algorithm, if their sawtooth index is less than the preset sawtooth index threshold, the peak type of the corresponding candidate chromatographic peak is classified as the second type; otherwise, the peak type of the corresponding candidate chromatographic peak is classified as the third type.

5. The highly sensitive, high-throughput chemical substance annotation method according to claim 4, characterized in that: The specific method of step S6 is: S6.1: For each candidate chromatographic peak, the fragment ions corresponding to the top of the candidate chromatographic peak are matched with the fragment ions of the target chemical in the chemical exposure group database in sequence to obtain the matching fragment ions at the top of each candidate chromatographic peak and their quantity, mass-to-charge ratio and intensity; S6.2: Calculate a first score and a second score based on the matched fragment ions at the top of the candidate chromatographic peak and the fragment ions of the target chemical in the chemical exposure group database; S6.3: Calculate the relevant characteristic score of the candidate chromatographic peak corresponding to the target chemical substance based on the first score and the second score; S6.4: Repeat steps S6.1-S6.3 to obtain the relevant characteristic score of each candidate chromatographic peak corresponding to the target chemical substance.

6. The highly sensitive, high-throughput chemical substance annotation method according to claim 5, characterized in that: In step S6.2, the specific method for calculating the first score is: The first score is calculated based on the number of matching fragment ions at the top of the candidate chromatographic peak and the number of fragment ions of the target chemical in the chemical exposure group database, and the calculation formula is: Where, MFR i Indicates the first score of the fragment ion matched at the top of the i-th candidate chromatographic peak of the target chemical, N i represents the number of matching fragment ions at the top of the i-th candidate chromatographic peak, N T Represents the number of fragment ions of target chemicals in the chemical exposome database.

7. The highly sensitive, high-throughput chemical substance annotation method according to claim 5, characterized in that: In step S6.2, the specific method for calculating the second score is: The second score is calculated based on the intensity of the fragment ion matched at the top of the candidate chromatographic peak and the intensity of the fragment ion of the target chemical in the chemical exposure group database, and the calculation formula is: In the formula, SSM i represents the second score of the fragment ion matched at the top of the i-th candidate chromatographic peak of the target chemical substance, W Qi represents the intensity of the fragment ion matched at the top of the i-th candidate chromatographic peak, W Ri represents the intensity of the i-th fragment ion of the target chemical in the chemical exposure group database.

8. The highly sensitive, high-throughput chemical substance annotation method according to claim 6 or 7, characterized in that: In step S6.3, based on the first score and the second score, the specific method for calculating the relevant characteristic scores of the candidate chromatographic peaks corresponding to the target chemical substance is: Assign weight coefficients to the first score and the second score respectively, and calculate the relevant feature scores of the candidate features corresponding to the target chemical substance: Score i =αMFR i +βSSM i In the formula, Score i It represents the relevant feature score of the candidate feature of the i-th candidate chromatographic peak corresponding to the target chemical substance, and α and β represent the first and second weight coefficients respectively.

9. The highly sensitive, high-throughput chemical substance annotation method according to claim 8, characterized in that: The specific method of step S7 is: S7.1: Set the sorting priority of the peak types of candidate chromatographic peaks, from high to low, first type, second type, and third type; S7.2: For all candidate chromatographic peaks belonging to the same peak type, arrange their relevant feature scores in descending order to obtain candidate features of the target chemical substance within each peak type; S7.3: Concatenate the candidate features of the target chemical substance within each peak type according to the sorting priority of the peak type to obtain a sorting result.

10. A highly sensitive, high-throughput chemical substance annotation system, used to implement the annotation method according to any one of claims 1 to 9, characterized in that: include: A data acquisition module, used to collect parent ions and fragment ions in the sample to be detected based on EISA technology; A database construction module is used to construct a chemical exposure group database, including several chemical substances and their mass spectrometry data; The chromatogram generation module is used to set the mass accuracy standard and convert the chemical Chemical substances are taken as target chemical substances in turn, and the parent ion chromatogram of the sample to be tested is extracted accordingly; A chromatogram correction module is used to correct the parent ion chromatogram of the sample to be detected to obtain a target chromatogram; the target chromatogram includes a plurality of chromatographic peaks; A chromatographic peak screening module is used to screen all chromatographic peaks to obtain candidate chromatographic peaks and their peak types; A data matching module is used to traverse and match target chemical substances for each candidate chromatographic peak, and calculate the relevant characteristic score of each candidate chromatographic peak corresponding to the target chemical substance; A sorting module, used to sort each candidate chromatographic peak corresponding to the target chemical substance based on the peak type and related characteristic score of the candidate chromatographic peak to obtain a sorting result; The chemical substance detection module is used to output the first several candidate chromatographic peaks in the sorting results as the final screening results of the chemical substances in the sample to be detected.

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