A data-independent non-target analysis method for the acquisition of mass spectrometry characteristic fragments

Abstract

The present invention discloses a non-target analysis method for data-independent acquisition of mass spectrometry characteristic fragments, which belongs to the technical field of non-target identification of compounds. The method of the present invention obtains high-resolution mass spectrometry data through a data-independent acquisition mode, converts the data into a universal format, extracts a chromatogram of characteristic fragment ions in the secondary mass spectrometry data, and obtains the retention time and peak width information of the characteristic fragment ions. The mass-to-charge ratio of each precursor ion in the primary mass spectrometry data and its corresponding intensity information are extracted within the retention time period of the characteristic fragment ion chromatogram, the similarity between the precursor ion and the characteristic fragment ion intensity is calculated, the precursor ion information corresponding to the characteristic fragment ion is judged by the similarity coefficient and the retention time deviation, and then the molecular formula of the compound is inferred to achieve non-target analysis of the compound. Compared with the traditional manual peak comparison method, the present invention can perform rapid and accurate non-target screening of compounds containing characteristic fragment ions.

Description

Technical Field

[0001] The present invention relates to the technical field of non-target identification of compounds, and in particular to a non-target analysis method for data-independent collection of mass spectrum characteristic fragments. Background Art

[0002] Liquid chromatography-tandem high-resolution mass spectrometry is widely used for the identification and screening of compounds (including environmental pollutants, metabolites, drugs, natural products, etc.), and has a wide range of applications in the fields of environment, chemical industry, medicine, life sciences, etc. Non-target analysis methods based on high-resolution mass spectrometry do not require the use of standards. Through accurate mass numbers and corresponding fragment information, they can perform structural analysis of unknown compounds in samples. They have wide applications in proteomics, metabolomics, and environmental pollutant screening. For example, Chinese patent document No. CN106645538A discloses a method for identifying the origin of acacia honey using ultra-high performance liquid chromatography-quadrupole / electrostatic field orbital hydrazine high-resolution mass spectrometry technology, and Chinese patent document No. CN110646554A discloses a method for screening pancreatic cancer diagnostic markers using high-performance liquid chromatography-mass spectrometry technology.

[0003] In non-targeted analysis, information on both precursor ions (primary mass spectrometry) and fragment ions (secondary mass spectrometry) can be collected simultaneously to facilitate molecular formula confirmation and structural inference. Currently, data acquisition modes for liquid chromatography-tandem high-resolution mass spectrometry are primarily categorized into data-dependent acquisition (DDA) and data-independent acquisition (DIA). The DDA mode performs secondary fragmentation on selected precursor ions (typically the highest intensity ions or ions specified by the experimenter), accurately providing precursor ion information corresponding to the fragment ions. However, the DDA mode suffers from the disadvantage of only collecting secondary fragments of a subset of highly abundant precursor ions in the sample, while losing information on the majority of precursor ions. The DIA mode fragments all precursor ions within a specific mass range, obtaining secondary fragment information for all precursor ions within that mass range. However, the disadvantage of DIA is that it cannot directly establish a one-to-one correspondence between secondary fragment information and precursor ions, requiring complex post-processing techniques such as deconvolution and peak alignment to match precursor ions with secondary fragments.

[0004] For a certain type of compounds with the same molecular structure or functional groups, they often have the same fragmentation rules in the mass spectrometry, so they can produce the same fragment ions in the secondary mass spectrometry, namely characteristic fragments. The characteristic fragmentation method is one of the commonly used methods in non-target analysis. It uses the characteristic fragment ions to match the corresponding precursor ions, and then obtains the molecular formula information of the compound through the precise mass and isotope distribution characteristics of the precursor ions, which can achieve non-target screening of a certain type of compounds with the same characteristic fragments. In the DDA mode, the characteristic fragment ions can directly correspond to the precursor ions without the need for complex data processing, but the information of components with lower abundance in the sample will be missed in this mode. The DIA mode can unbiasedly collect the secondary fragment information of all components in the sample, which is more suitable for non-target analysis of complex matrix samples, but the DIA mode cannot directly obtain the precursor ions corresponding to the characteristic fragment ions. The mass spectrometry data analysis software provided by instrument manufacturers does not have a separate module for non-target analysis based on characteristic fragments. While some commercial software (such as Compound Discoverer) and open-source mass spectrometry data analysis software (such as MS DIAL) can match primary and secondary mass spectrometry ions in DIA data, these software require deconvolution and peak alignment of all chromatographic peaks, which not only wastes computing resources but also results in a large number of false-positive results, increasing the complexity of the data. Currently, non-target analysis based on characteristic fragments for DIA data is still performed through manual comparison: the chromatogram of the characteristic fragment is compared with the chromatogram of the precursor ion. If the peak shapes of the two are consistent, the precursor ion is considered a candidate compound. However, due to the large number of precursor ions, the manual comparison process is time-consuming and inefficient. In addition, human judgment lacks fixed standards and is subject to large subjective errors.

[0005] Chinese patent publication CN106290684A discloses a method for analyzing mass spectrometry data in a data-independent acquisition mode. The method comprises the following steps: mixing a heavy isotope-labeled standard substance, not present in multiple analysis samples, into a sample to be tested; analyzing the sample using gas chromatography or liquid chromatography coupled with mass spectrometry; obtaining mass spectrometric information for the heavy isotope-labeled standard substance and each component in the sample to be tested from the data collected in each DDA mode, and creating a corresponding mass spectrometry database file; searching for mass spectrometric information for the heavy isotope-labeled standard substance from the data collected in each DIA mode; creating a mass spectrometry database file suitable for analyzing each DIA mode data file; and searching the DIA data using commercial mass spectrometry data software to obtain qualitative and quantitative results for each component of the sample. However, this method requires the prior collection of DDA data to create the database file, and compound analysis relies on the database, making it impossible to perform non-target analysis of compounds not in the database.

[0006] Therefore, existing technologies cannot achieve rapid and accurate non-target analysis of a certain type of structurally similar compounds in a sample through characteristic fragments. Summary of the Invention

[0007] The present invention provides a non-target analysis method for data-independent acquisition of mass spectrometry characteristic fragments. This method can realize non-target analysis of compounds through mass spectrometry characteristic fragments, greatly improving the efficiency and accuracy of compound identification, avoiding the tedious and time-consuming manual matching and verification process, and providing an effective solution for non-target analysis of compounds.

[0008] The specific technical solutions adopted are as follows:

[0009] A data-independent non-target analysis method for collecting mass spectrometry characteristic fragments comprises the following steps:

[0010] Step 1: Analyze the sample using gas chromatography-mass spectrometry or liquid chromatography-mass spectrometry. Acquire both primary and secondary mass spectrometry raw data simultaneously using a data-independent acquisition mode. Convert the mass spectrometry raw data into a common format using data conversion software.

[0011] Step 2: Extract the secondary mass spectrometry data under each isolation window from the mass spectrometry data in the universal format obtained in step 1, obtain the time information corresponding to all scanning points, extract the intensity information of the characteristic fragment ions at all scanning points within the mass error range, and draw a time-intensity curve;

[0012] Step 3: Obtain the retention time RT and peak width W of the characteristic fragment ion chromatographic peak from the time-intensity curve obtained in step 2, and extract the intensity information I (I1, I2, ..., I n );

[0013] Step 4: Extract the primary mass spectrum data from the mass spectrum data in the universal format obtained in step 1, extract the full scan data at the characteristic fragment ion RT in step 3, obtain the information of all the precursor ions within the isolation window, and extract the intensity information I'(I'1, I'2, ..., I') of each precursor ion within the RT ± W / 2 time period within the mass error range. n );

[0014] Step 5: Use a similarity algorithm to calculate the similarity between the intensity of each precursor ion in step 4 and the intensity of the characteristic fragment ion in step 3, and establish a precursor ion list based on the similarity coefficient;

[0015] Step 6: Obtain the retention time of each precursor ion in the precursor ion list of step 5, calculate its deviation from the RT of the characteristic fragment ion in step 3, and filter the precursor ions based on the retention time deviation;

[0016] Step 7: For the precursor ions screened out in step 6, filter the isotope ions, adduct ions and / or fragment ions to obtain the monoisotopic accurate mass, infer the molecular formula of the compound, and achieve non-target analysis of the compound.

[0017] Preferably, in step 1, the method of obtaining the secondary mass spectrometry raw data includes collision-induced fragmentation or in-source fragmentation.

[0018] The data conversion software includes but is not limited to MSConvert, GNPS_Vendor_Conversion, X2XML or other software with the same functions, and the universal format is mzXML format, mzML format or mzData format.

[0019] In step 2, the characteristic fragment ions are one or more common fragment ions generated by compounds with similar structures in the secondary mass spectrometry. Preferably, the mass error tolerance is ±5 ppm;

[0020] The formula for calculating mass error is:

[0021]

[0022] Preferably, in step 3, in order to accurately determine the chromatographic peak of the characteristic fragment ion, the number of all scanning points (n) within the RT±W / 2 time period is ≥5.

[0023] Preferably, in step 4, the mass error tolerance is allowed to be ±5 ppm, and the number of scanning points is the same as that in step 3.

[0024] In step 5, the similarity algorithm is the Pearson correlation coefficient algorithm or the cosine similarity algorithm; wherein the Pearson correlation coefficient r p The calculation formula is:

[0025]

[0026] Where n is the number of all scanning points within the time period of RT±W / 2, I i and I′ i Characteristics

[0027] The intensity of the fragment ion and the precursor ion at the i-th scanning point, and are the average intensities of characteristic fragment ions and precursor ions at all scanning points within the RT±W / 2 time period, respectively.

[0028] The calculation formula of cosine similarity cos is:

[0029]

[0030] Where n is the number of all scanning points within the time period of RT±W / 2, I i and I′ i are the intensities of the characteristic fragment ion and precursor ion at the i-th scanning point, respectively.

[0031] Preferably, the similarity between the intensity of the precursor ions in the precursor ion list and the intensity of the characteristic fragment ions in step 3 satisfies the Pearson correlation coefficient r p ≥0.85, or cosine similarity cos ≥0.9.

[0032] In step 6, the retention time of the precursor ion is the time corresponding to the scanning point with the highest intensity, and the precursor ion whose retention time deviates from the RT of the characteristic fragment ion in step 3 by less than 0.01 min is screened.

[0033] The present invention also provides the application of the data-independent non-target analysis method for collecting mass spectrum characteristic fragments in the detection field.

[0034] Compared with the prior art, the present invention has the following beneficial effects:

[0035] The present invention can automatically match the corresponding precursor ions based on the characteristic fragment ions produced by the compound in the secondary mass spectrometry through a similarity algorithm, greatly improving the efficiency and accuracy of non-target analysis, avoiding the tedious and time-consuming manual matching and verification process, and providing an effective solution for the non-target analysis of compounds. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] Figure 1 is a flow chart of the method of the present invention;

[0037] Figure 2 The characteristic fragment in Example 1 [Br] - Extraction chromatogram of

[0038] Figure 3 The characteristic fragment in Example 1 [Br] - Overlay chromatogram with the filtered precursor ions;

[0039] Figure 4 The characteristic fragment [C3F7] in Example 2 - Extraction chromatogram of

[0040] Figure 5 The characteristic fragment [C3F7] in Example 2 - Overlaid chromatogram with filtered precursor ions. DETAILED DESCRIPTION

[0041] The present invention will be further described below in conjunction with the examples and accompanying drawings. It should be understood that these examples are intended to illustrate the present invention only and are not intended to limit the scope of the invention. The operating methods in the following examples where no specific conditions are specified are generally performed under conventional conditions or as recommended by the manufacturer.

[0042] The flow chart of the method in the embodiment is as follows Figure 1 shown.

[0043] Example 1 Non-target analysis of Br-containing compounds in surface water samples

[0044] Br-containing compounds can produce [Br] - Characteristic fragments can be detected, so the characteristic fragment method can be used to perform non-target analysis of Br-containing compounds in samples.

[0045] Surface water samples were concentrated and enriched by solid-phase extraction, and high-resolution mass spectrometry raw data (primary mass spectrometry raw data and secondary mass spectrometry raw data) were collected using liquid chromatography-high-resolution mass spectrometry in DIA mode. The scanning parameters were as follows: the full scan mass range was 150–1000 m / z, and the resolution was set to 120,000; the secondary scan isolation window was 150–1000 m / z, the scan range was 50–500 m / z, and the resolution was set to 120,000. The mass spectrometry raw file data was converted to mzML format using MSConvert software. The mzML file was read using the Python pymzML package to extract the time information of all secondary mass spectrometry scan points and the [Br] - (m / z=78.9189), with a mass error of 5 ppm, [Br] - The time-intensity curve (i.e., the extracted chromatogram) is as follows Figure 2 As shown. Visible [Br] - A total of 5 chromatographic peaks were generated in the secondary mass spectrometry, with retention times of 3.82 min, 3.96 min, 4.38 min, 4.39 min, and 4.64 min, and peak widths of 0.15 min.

[0046] For the chromatographic peak with RT = 3.82 min, there are 9 scanning points (n = 9) within the peak width of 3.74–3.89 min. [Br] -The intensity I (I1, I2, ..., I9) of these 9 scanning points. Then, in the primary mass spectrometry data, the full scan data at 3.82 min was extracted to obtain the mass-to-charge ratios of all ions within the isolation window range (150–1000 m / z) in the primary mass spectrometry. A total of 59 precursor ions with different mass-to-charge ratios were extracted. The intensity I' (I'1, I'2, ..., I'9) of these ions at 9 scanning points within 3.74–3.89 min was extracted in sequence, and the mass error was set to 5 ppm. The intensity data (I') of each precursor ion within 3.74–3.89 min was compared with [Br] - The intensity data (I) is analyzed by cosine similarity and the cosine similarity coefficient (cos) is calculated:

[0047]

[0048] Where n = 9, I i and I′ i are the intensities of the characteristic fragment ion and precursor ion at the i-th scanning point, respectively.

[0049] The calculation results show that among the 59 precursor ions, 14 ions have a cosine similarity coefficient cos greater than 0.9. We further established a precursor ion list and extracted the chromatographic retention time of these 14 ions. - The retention time of the ions is 3.82 min, and the difference is within 0.01 min for 6 ions, as shown in Table 1. Among them, the mass differences of 193.9605 and 195.9584 with 273.9172 and 275.9155 are 79.9567 and 79.9571 respectively. Therefore, these two ions are fragment ions produced by the removal of SO3 from the precursor ions in the source. After filtering the isotope ions, [Br] - The monoisotopic mass of the corresponding precursor ion is 273.9172, and the inferred molecular formula is C8H6O3NBrS.

[0050] The same processing method was used to match the precursor ions of the chromatographic peaks at 3.96 min, 4.38 min, 4.39 min, and 4.64 min (Table 1). Among them, the precursor ion corresponding to the peak at 3.96 min was 315.8280, and its molecular formula was inferred to be C5H5O3NBr2S based on the isotopic characteristics; the chromatographic peaks at 4.38 min, 4.39 min, and 4.64 min were multiple peaks formed by isomers, and their precursor ion mass was 351.8282. Combined with the isotopic distribution characteristics, the molecular formula corresponding to this precursor ion was C8H5O3NBr2S. From [Br] - The superimposed extracted chromatogram with the screened precursor ions ( Figure 3) It can be seen that the chromatographic peaks of the characteristic fragment ions have an extremely high degree of match with the chromatographic peaks of the corresponding precursor ions. Therefore, the method of the present invention can replace the manual peak comparison process and realize fast and accurate non-target analysis.

[0051] Table 1[Br] - Corresponding precursor ions

[0052]

[0053] Example 2 Non-target analysis of perfluorinated compounds in fish liver samples

[0054] Perfluorinated compounds contain similar carbon-fluorine chain skeletons and can produce [C2F5] in secondary mass spectrometry. - , [C3F7] - Such characteristic fragments, this embodiment uses [C3F7] - The implementation process of the present invention is described with an example.

[0055] Fish liver samples were extracted with acetonitrile and cleaned up using a strong anion exchange solid-phase extraction cartridge. The samples were analyzed using liquid chromatography-high-resolution mass spectrometry. High-resolution mass spectrometric data (primary mass spectrometry raw data and secondary mass spectrometry raw data) were acquired in DIA mode with the following scanning parameters: a full scan mass range of 150–900 m / z with a resolution of 120,000; a secondary scan with an isolation window of 150–900 m / z, a scan range of 50–500 m / z, and a resolution of 60,000. The raw mass spectrometry file data was converted to mzXML format using MSConvert software. The mzXML file was read using the R package readMzXmlData to extract the time information for all secondary mass spectrometry scan points and the [C3F7] sequence from all secondary mass spectrometry scan points. - (m / z=168.9894), with a mass error of 5 ppm, [C3F7] - The time-intensity curve (i.e., the extracted chromatogram) is as follows Figure 4 As shown. [C3F7] - Six chromatographic peaks were generated in the secondary mass spectrometry, with retention times of 7.94 min, 8.33 min, 8.94 min, 9.39 min, 9.75 min, and 10.07 min, respectively. The peak width of the chromatographic peak with RT = 7.94 min was 0.2 min, and the peak widths of the other five peaks were 0.1 min.

[0056] For the chromatographic peak with RT = 7.94 min, there are 17 scanning points (n = 17) within the peak width of 7.84–8.04 min. [C3F7] - The intensities I(I1, I2, ..., I 17Then, the full scan data at 7.94 min was extracted from the primary mass spectrometry data to obtain the mass-to-charge ratios of all ions within the isolation window (150–900 m / z) in the primary mass spectrometry. A total of 260 precursor ions with different mass-to-charge ratios were extracted. The intensities I' (I'1, I'2, …, I' ) of these ions at 17 scanning points within 7.84–8.04 min were extracted in sequence. 17 ), and the mass error was set to 5ppm. The intensity data (I') of each precursor ion within 7.84–8.04min were compared with the [C3F7] - The intensity data (I) were analyzed for similarity and the Pearson correlation coefficient (r p ).

[0057]

[0058] Where n = 17, I i and I′ i are the intensities of the characteristic fragment ion and the precursor ion at the i-th scanning point, and are the average intensities of characteristic fragment ions and precursor ions at all scanning points within the RT±W / 2 time period, respectively.

[0059] The calculation results show that among the 260 precursor ions, there are 7 ions with Pearson correlation coefficients r p Greater than 0.85, further establish the precursor ion list and extract the chromatographic retention time of these 7 ions, and compare [C3F7] - The retention time of [C3F7] was 7.94 min, and the difference was within 0.01 min for 3 ions, as shown in Table 2. After filtering the isotope ions, [C3F7] - The corresponding monoisotopic mass of the precursor ion is 498.9289, and the inferred molecular formula is C8HF 17 SO3.

[0060] The same processing method was used to match the peaks at 8.33 min, 8.94 min, 9.39 min, 9.75 min, and 10.07 min. As shown in Table 2, the corresponding precursor ions are 562.9563, 612.9515, 662.9488, 712.9457, and 762.9433, respectively. Based on the isotopic characteristics, the molecular formula is inferred to be C 11 HF 21 O2, C 12 HF 23 O2, C 13 HF 25 O2, C 14 HF 27 O2, C 15HF 29 In addition to matching the target precursor ion and isotope ions, ions with a mass difference of 44 from the precursor ion were also extracted. These ions are fragment ions formed when the precursor ion removes a portion of CO2 in the source. Figure 5 [C3F7] - Compared with the superimposed extracted chromatograms of the corresponding precursor ions, the chromatographic peaks of the characteristic fragment ions have an extremely high degree of match with the chromatographic peaks of the corresponding precursor ions. Therefore, the method proposed in the present invention can replace the manual peak alignment process and realize fast and accurate non-target analysis.

[0061] Table 2 [C3F7] - Corresponding precursor ions

[0062]

[0063] 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 data-independent non-target analysis method for collecting mass spectrometry characteristic fragments, characterized in that: The following steps are involved: Step 1: Analyze the sample using gas chromatography-mass spectrometry or liquid chromatography-mass spectrometry. Acquire both primary and secondary mass spectrometry raw data simultaneously using a data-independent acquisition mode. Convert the mass spectrometry raw data into a common format using data conversion software. Step 2: Extract the secondary mass spectrometry data under each isolation window from the mass spectrometry data in the universal format obtained in step 1, obtain the time information corresponding to all scanning points, extract the intensity information of the characteristic fragment ions at all scanning points within the mass error range, and draw a time-intensity curve; Step 3: Obtain the retention time RT and peak width W of the characteristic fragment ion chromatographic peak from the time-intensity curve obtained in step 2, and extract the intensity information of all scanning points of the characteristic fragment ion within the RT±W / 2 time period I ( I 1 , I 2 , …, I n ); Step 4: Extract the primary mass spectrum data from the mass spectrum data in the universal format obtained in step 1, extract the full scan data at the characteristic fragment ion RT in step 3, obtain the information of all the precursor ions within the isolation window, and extract the intensity information of each precursor ion at the scanning point within the RT±W / 2 time period within the mass error allowable range. I’ ( I’ 1 , I’ 2 , …, I’ n ); Step 5: Use a similarity algorithm to calculate the similarity between the intensity of each precursor ion in step 4 and the intensity of the characteristic fragment ion in step 3, and establish a precursor ion list based on the similarity coefficient; Step 6: Obtain the retention time of each precursor ion in the precursor ion list of step 5, calculate its deviation from the RT of the characteristic fragment ion in step 3, and filter the precursor ions based on the retention time deviation; Step 7: For the precursor ions screened out in step 6, filter the isotope ions, adduct ions and / or fragment ions to obtain the monoisotopic accurate mass, infer the molecular formula of the compound, and achieve non-target analysis of the compound.

2. The data-independent non-target analysis method for collecting mass spectrometry characteristic fragments according to claim 1, characterized in that: In step 1, the raw data of the secondary mass spectrometry are obtained by collision-induced fragmentation or in-source fragmentation.

3. The data-independent non-target analysis method for collecting mass spectrometry characteristic fragments according to claim 1, characterized in that: The general format is mzXML format, mzML format or mzData format.

4. The data-independent non-target analysis method for collecting mass spectrometry characteristic fragments according to claim 1, characterized in that: In step 2, the mass error allowed range is ±5 ppm.

5. The data-independent non-target analysis method for collecting mass spectrometry characteristic fragments according to claim 1, characterized in that: In step 3, the number of all scanning points within the RT±W / 2 time period is ≥5.

6. The data-independent non-target analysis method for collecting mass spectrometry characteristic fragments according to claim 1, characterized in that: In step 4, the mass error allowed range is ±5 ppm, and the number of scanning points is the same as that in step 3.

7. The method for non-target analysis of mass spectrometry characteristic fragments by data-independent acquisition according to claim 1, characterized in that: In step 5, the similarity algorithm is a Pearson correlation coefficient algorithm or a cosine similarity algorithm.

8. The data-independent non-target analysis method for collecting mass spectrometry characteristic fragments according to claim 1, characterized in that: The similarity between the intensity of the precursor ion in the precursor ion list and the intensity of the characteristic fragment ion in step 3 satisfies the Pearson correlation coefficient r p ≥0.85, or cosine similarity cos ≥0.

9.

9. The data-independent non-target analysis method for collecting mass spectrometry characteristic fragments according to claim 1, characterized in that: In step 6, the retention time of the precursor ion is the time corresponding to the scanning point with the highest intensity, and the precursor ion whose retention time deviates from the RT of the characteristic fragment ion in step 3 by less than 0.01 min is screened.

10. Application of the non-target analysis method for data-independent acquisition of mass spectrometry characteristic fragments according to any one of claims 1 to 9 in the field of detection.

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