A Metabolomics Chromatographic Peak Extraction Method Based on Secondary Mass Spectrometry Qualitative Results

Abstract

This invention discloses a method for extracting metabolomics chromatographic peaks based on secondary mass spectrometry qualitative results. This method starts with secondary mass spectrometry in metabolomics, utilizing the qualitative results from the secondary mass spectrometry in a qualitative library, combined with XCMS (XML Cryptographic Message Syntax) peak extraction results to obtain more comprehensive chromatographic peak information. This invention starts with the secondary mass spectrometry characteristics that contain more mass spectrometry information and have clear chemical meanings, improving the accuracy of chromatographic peak extraction and clarifying the specific biological significance of metabolomics chromatographic peaks. This is beneficial for further discovery of metabolomics differentials, pathway analysis, and interpretation of biological significance. Figure 1 in the accompanying drawings is a flowchart of this invention.

Description

Technical Field

[0001] This invention discloses "a method for extracting chromatographic peaks in metabolomics based on qualitative results of secondary mass spectrometry", which belongs to the field of data science. It is used to extract chromatographic peaks from high-resolution mass spectrometry detection data, improve the accuracy of chromatographic peak extraction, and enhance the biological significance of chromatographic peaks. Background Technology

[0002] Metabolomics uses high-resolution instruments to detect the content of metabolites in different types of samples (such as early, middle, and late stages of disease). By analyzing the patterns of change, it can uncover the changing trends of metabolites in different types of samples. It is an important part of systems biology and is widely used in fields including disease diagnosis, toxicology, botany, nutrition and food science, and environmental science, with very broad application prospects.

[0003] However, due to the complexity of metabolites, processing metabolomics data still presents many challenges. For example, it is estimated that human serum contains more than 1,000 metabolites, while plants contain 4,000 to 25,000. Moreover, the influence of background ions and random noise makes it even more challenging to accurately detect chromatographic peaks containing metabolite characteristics from metabolomics data.

[0004] Currently, commonly used chromatographic peak extraction methods in metabolomics analysis include XCMS, MZmine, MetAlign, and OpenMS. These methods all start from the metabolomics data itself, using chemometrics and other techniques, and extract chromatographic peaks from the detection data based on primary mass spectrometry information. However, these methods do not fully consider the biological information of the compounds contained in the chromatographic peaks, nor do they fully utilize the secondary mass spectrometry information of the detection data. This leads to frequent false and false detections of chromatographic peaks, affecting the results of subsequent qualitative identification, differential analysis, pathway analysis, and other metabolomics analysis procedures.

[0005] Based on this, the present invention develops a metabolomics chromatographic peak extraction method based on secondary mass spectrometry qualitative results. This method first fully utilizes the secondary mass spectrometry information of the detection data, assigning chemical and biological meanings to the secondary mass spectra through qualitative analysis. Then, based on the retention time and mass-to-charge ratio information of the secondary mass spectra, the search range of chromatographic peaks in the primary mass spectrometry data is precisely located, improving the accuracy of peak extraction while assigning clear chemical and biological meanings to the chromatographic peaks, reducing false detections and missed detections. Summary of the Invention

[0006] The problem to be solved by this invention is to provide a method for extracting metabolomics chromatographic peaks based on the qualitative results of secondary mass spectrometry.

[0007] To achieve the above objectives, the technical solution adopted by the present invention is as follows:

[0008] The metabolomics chromatographic peak extraction method based on secondary mass spectrometry qualitative results includes the following steps:

[0009] (1) Step 1: Extract secondary mass spectrometry data from metabolomics detection data and perform noise reduction preprocessing on the secondary mass spectrometry data.

[0010] Step 2: Screen the secondary mass spectrometry data based on their similarity.

[0011] Step 3: Based on the characteristics of secondary mass spectrometry and combined with a qualitative database, perform qualitative analysis of secondary mass spectrometry to determine the chemical substance meaning of the secondary mass spectrometer.

[0012] Step 4: Based on the qualitative results of secondary mass spectrometry, extract chromatographic peaks and construct a peak table of metabolomics detection data.

[0013] Compared with existing technologies, this invention develops a metabolomics chromatographic peak extraction method based on secondary mass spectrometry qualitative results, which has the following superior effects: ① Improved detection efficiency: This invention fully utilizes secondary mass spectrometry information for chromatographic peak extraction, narrowing the chromatographic peak search range and avoiding searching for chromatographic peaks across the entire retention time and mass-to-charge ratio range, thus improving the detection efficiency of chromatographic peaks; it also avoids missed detections and false detections; ② Avoided missed detections and false detections: This invention fully utilizes secondary mass spectrometry information for chromatographic peak extraction, determining the chromatographic peak search range based on the parent ion retention time and mass-to-charge ratio of the secondary mass spectrometer, avoiding missed detections and false detections due to system limitations. The invention addresses several issues: ① Missed or false detections of chromatographic peaks due to factors such as noise; ② The chromatographic peaks extracted in this invention possess sufficient and complete chemical and biological meaning. The purpose of chromatographic peak extraction is to facilitate subsequent qualitative identification, differential analysis, and pathway analysis in metabolomics, thereby uncovering the biological significance within / between samples. This invention extracts chromatographic peaks from secondary mass spectrometry samples with qualitative results (i.e., sufficient chemical and biological significance), ensuring that all extracted chromatographic peaks have sufficient chemical and biological significance. This avoids the impact of traditional methods on subsequent qualitative identification, differential analysis, and pathway analysis in metabolomics, where chromatographic peaks without specific chemical and biological significance are extracted. Attached Figure Description

[0014] Figure 1 This is a basic flowchart of the present invention.

[0015] Figure 2 This is an example of the screening results from secondary mass spectrometry.

[0016] Figure 3This is an example of the qualitative results of a secondary mass spectrometry test. The upper region (y>0) of the graph is the secondary mass spectrum to be determined, and the lower region (y<0) is the secondary mass spectrum that matches the target spectrum in the qualitative library.

[0017] Figure 4 This is a diagram showing the ion distribution in the ROI region of the chromatographic peak, as determined by the example secondary mass spectrometry.

[0018] Figure 5 This example illustrates the distribution of the distance between the mass-to-charge ratio of ions and the mass-to-charge ratio of the parent ion in the ROI region of the chromatographic peak corresponding to the secondary mass spectrometer.

[0019] Figure 6 This is a chromatogram of the final extracted peaks based on the example secondary mass spectrometry. Detailed Implementation

[0020] The present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments:

[0021] Example data: For 40 mice divided into 6 groups (normal group (5 mice), model group (8 mice), positive group (6 mice), low-dose group (7 mice), medium-dose group (7 mice), and high-dose group (7 mice), 40×4=160 mouse urine samples were collected at 4 stages: day 0, day 10, day 20, and day 30. After equal-quantitative mixing of the above 160 urine samples, 16 QC samples were obtained (total 160+16=176 experimental samples). The SCIEX 7600 instrument was used for detection experiments in positive ion ionization mode to obtain the corresponding 176 mass spectrometry detection data.

[0022] The classification of 176 mass spectrometry data obtained was analyzed.

[0023] Table 1. Classification of 1176 mass spectrometry detection data

[0024]

[0025] From the 176 mass spectrometry data points detected, 282,436 secondary mass spectra were extracted, and their noise intensity level was automatically analyzed to be 155.152.

[0026] After deduplication, 172,734 secondary mass spectra were finally selected for qualitative analysis.

[0027] After qualitative analysis of 172,734 secondary mass spectra in qualitative libraries such as HMDB and MoNA, 16,922 secondary mass spectra with qualitative results were finally obtained.

[0028] Among the 16,922 secondary mass spectra with qualitative results, one secondary mass spectrum with a qualitative result of DI-3,4-Dihydroxymandelic acid (DL-3,4-dihydroxymandelic acid) was selected as an example secondary mass spectrum (the retention time of the selected example secondary mass spectrum was 13.00 min, and the mass-to-charge ratio was 149.0235 Da). The method for extracting metabolomics chromatographic peaks based on the qualitative results of secondary mass spectrometry in this invention is described in detail, and how to extract chromatographic peaks from the data according to the secondary mass spectrum.

[0029] The selected example secondary mass spectrometry fragments and their noise levels are plotted as follows: Figure 2 As shown.

[0030] The matching plot of the selected example secondary mass spectrometer with the DI-3,4-Dihydroxymandelic acid fragment is shown below. Figure 3 As shown, Figure 3 The upper region (y < 0) of the graph shows the fragmentation plot of the example secondary mass spectrum, while the lower region (y < 0) shows the fragmentation plot of the DI-3,4-Dihydroxymandelic acid compound. To facilitate comparison, the fragment intensities of both have been normalized.

[0031] Based on the selected example secondary mass spectrometer, and according to its retention time and mass-to-charge ratio, the region in the detection mass spectrometry data where the retention time is in the range of [13.00-0.5, 13.00+0.5] and the mass-to-charge ratio is in the range of [149.0235-0.015, 149.0235+0.015] is defined as the ROI region corresponding to the chromatographic peak of the example secondary mass spectrometer. The mass spectrometric ion distribution in this region is as follows: Figure 4 As shown.

[0032] Calculate the absolute value of the difference between the mass-to-charge ratio of all mass spectrometer ions within the ROI region and 149.0235. The distribution of the absolute values ​​of the differences is as follows: Figure 5 As shown.

[0033] After clustering the mass-to-charge ratios of all mass-spectral ions within the ROI region based on the absolute value of their differences from 149.0235, all mass-spectral ions in clusters with an absolute difference ≤ 0.003 were selected, and chromatographic peaks were plotted as follows. Figure 6 As shown.

[0034] Following the steps above, the chromatographic peaks and their peak areas in the 176 mass spectrometry data corresponding to the example secondary mass spectrometry were obtained.

[0035] Following the steps above, 16,922 qualitative secondary mass spectrometry results were obtained from 176 mass spectrometry data points, along with their peak areas.

[0036] Finally, based on the metabolomics chromatographic peak extraction method of the present invention based on the qualitative results of secondary mass spectrometry, 16,922 chromatographic peaks with clear chemical and biological significance and distinct peak shapes were obtained from 176 mass spectrometry data.

[0037] The following table compares the number of chromatographic peaks extracted using the metabolomics chromatographic peak extraction method based on secondary mass spectrometry qualitative results of the same 176 mass spectrometry data sets with the number of chromatographic peaks obtained by extracting chromatographic peaks using XCMS, MZmine, MetAlign, and OpenMS, respectively.

[0038] Table 2 Comparison of the number of chromatographic peaks extracted by different methods

[0039]

[0040] As shown in the table above, the chromatographic peak extraction method provided by this invention not only extracts chromatographic peaks with clear chemical and biological significance, but also significantly increases the number of extracted chromatographic peaks compared to other chromatographic peak extraction methods such as XCMS (71.94%), MZmin (61.90%), MetAlign (99.27%), and OpenMS (27.29%), greatly reducing the chance of missed detections in chromatographic peak extraction.

Claims

1. A method of metabolomics peak picking based on qualitative results of secondary mass spectrometry, characterized by, The qualitative result of the secondary mass spectrum is used as the basis for extracting the chromatographic peak, which not only increases the number of metabolomics chromatographic peaks, but also clearly defines the specific biological significance of the metabolomics chromatographic peaks, which is conducive to further metabolomics difference discovery, pathway analysis and biological significance interpretation, including the following steps: Step 1: Extracting the secondary mass spectrum data in the metabolomics detection data, and performing denoising preprocessing on the secondary mass spectrum data; Step 2: According to the similarity of the secondary mass spectrum data, the secondary mass spectrum data is screened; Step 3: Based on the secondary mass spectrum characteristics, combined with the qualitative database, the secondary mass spectrum qualitative analysis is realized, and the chemical meaning of the secondary mass spectrum is determined; Step 4: Based on the qualitative result of the secondary mass spectrum, the chromatographic peak is extracted, and the peak table of the metabolomics detection data is constructed; Secondary mass spectrometry data with qualitative results wherein, is a set of secondary mass spectrometry data with qualitative results, according to , extracting chromatographic peaks from the raw data; The specific implementation steps of extracting the chromatographic peak based on the secondary mass spectrum information are as follows: ①For MS / MS The retention time of the peak is recorded as The mass-to-charge ratio of the peak is recorded as In the raw data raw_data, according to the retention time range , and the mass-to-charge ratio range , a region is demarcated Region of Interest, wherein, is a preset retention time range threshold, is a preset mass-to-charge ratio range threshold; ② In the original data, each characteristic ion set in the region is recorded as , and each characteristic ion in is calculated respectively , wherein the mass-to-charge ratio of is , and the distance between the mass-to-charge ratio of and the secondary mass spectrum is . : ; ③ according to the mass-to-charge ratio distance between the characteristic ions and the secondary mass spectrum , the characteristic ions are clustered by using an optimal k - mean clustering method, and the clustering result is recorded as ; in the cluster, the cluster with the minimum average distance between the characteristic ions and the secondary mass spectrum mass-to-charge ratio is recorded as ; IV All the characteristic ions are sorted by retention time, and the peak shape composed by connecting and smoothing the first derivative of the retention time is the MS / MS spectrum The peak area of the corresponding chromatographic peak is the MS / MS spectrum The chromatographic peak area in the sample.

2. The method of claim 1, wherein, The specific method of step 1 is as follows: An important feature of a metabolomics secondary mass spectrum data can be represented as a data structure wherein, represents the retention time of the parent ion of the secondary mass spectrum, represents the mass-to-charge ratio of the parent ion of the secondary mass spectrum, represents the collection of secondary mass spectrum fragments of the secondary mass spectrum data, and wherein, , respectively, represent the mass-to-charge ratio and intensity of the th secondary mass spectrum fragment. The flowchart of screening the secondary mass spectrum data is as follows: First, noise reduction is performed on all secondary mass spectrometers. Without loss of generality, noise reduction is then applied to the tertiary mass spectrometers. Secondary mass spectrometry data During preprocessing, look for The highest intensity secondary mass spectrometry feature is denoted as Follow the steps below to target The first in Secondary mass spectrometry features ,in, To process, if If any one of the following conditions ①②③ is satisfied, then it is considered that... Noise-related secondary mass spectrometry features must be removed; otherwise, the feature is considered acceptable and can be retained for further processing. ① ； ② , is a preset secondary mass spectrum characteristic intensity threshold value; iii. In the range of 0.1 to 10, There are multiple secondary mass spectrum features, and Among these secondary mass spectrum fragments, the intensity is not the highest.

3. The method of claim 1, wherein, The specific method of step 2 is as follows: Defining two secondary mass spectrometry data With The similarity calculation process is as follows: If , with the similarity value is 0, complete with similarity calculation, otherwise jump to ②; If , with the similarity value is 0, complete with the similarity calculation, otherwise jump to ③; ③statistics in the number of secondary mass spectrum features in the number of secondary mass spectrum features with a secondary mass spectrum mass-to-charge ratio distance less than a threshold ;​​​​ Based on the similarity calculation procedure as above, all the noise-removed secondary mass spectrum data to be screened According to the number of secondary mass spectrum data characteristics, the secondary mass spectrum data screening is performed in the following steps; , a set of secondary mass spectra to be culled ;​ ii) calculating the similarity between the two sets of secondary mass spectra with wherein the similarity between the two sets of secondary mass spectra is if then the secondary mass spectrum is put into the set of secondary mass spectra to be rejected to be rejected​ ③ setting for , loop ② until ; (4) removing the secondary mass spectra to be removed from the secondary mass spectrum data set the secondary mass spectra to be removed from the secondary mass spectrum data set The remaining secondary mass spectrum data is the screened secondary mass spectrum data set.

4. The method of claim 1, wherein, The specific method of step 3 is as follows: The qualitative analysis of undetermined secondary mass spectrometry data is based on the calculation of the matching degree between the secondary mass spectrometry data and the secondary mass spectrometry characteristics of known compounds in the qualitative library. Qualitative analysis requires comparison with all secondary mass spectrometers in the qualitative library. Perform matching degree calculations for undetermined secondary mass spectrometry. ,in, for The set of secondary mass spectrometry fragments, and the secondary mass spectrometry fragments in the qualitative library. ,in, for The matching degree of the secondary mass spectrometry fragment set is calculated as follows: ①According to ,get Mass-to-charge ratio set of secondary mass spectrometry fragments ,according to ,get Mass-to-charge ratio set of secondary mass spectrometry fragments ; ②For sets All of them ,like Not in the set Inside, the secondary mass spectrometry fragments will be... Add to In the end, a set of secondary mass spectrometry fragments was obtained. ; iii. For all , if is not in the set , add the secondary mass spectrum fragment to , and finally get the secondary mass spectrum fragment set ;​​​​​​​ ④ Through the aforementioned processing, the secondary mass spectrometry fragment set and secondary mass spectrometry fragment set The sets are of the same size, and all secondary mass spectrometry fragments have a one-to-one correspondence in mass-to-charge ratio. After sorting them according to the mass-to-charge ratio values ​​in ascending order, a mass-to-charge ratio sequence is obtained. mass-to-charge ratio sequence exist The corresponding fragment strength is denoted as mass-to-charge ratio sequence exist The corresponding fragment strength is denoted as ; (5) Calculation and Pearson correlation of two data sequences, whose formula is shown as follows; （1） Following the five steps ①②③④⑤ above, calculate the undetermined secondary mass spectrometry. Compared with all secondary mass spectrometers in the qualitative library The degree of matching, if with the undetermined secondary mass spectrometry The maximum matching degree with all secondary mass spectrometers in the qualitative library is The corresponding qualitative library contains secondary mass spectrometry data. ,like ,in If the preset qualitative threshold is used, then the qualitative library... The corresponding chemical information, such as compound name, molecular formula, and molecular weight, constitutes the undetermined secondary mass spectrometry. The qualitative results were used to complete the secondary mass spectrometry. Qualitative analysis; otherwise, secondary mass spectrometry. Qualitative failure, i.e., secondary mass spectrometry The term does not necessarily represent a specific compound. According to the above steps, the qualitative of all secondary mass spectrometry to be qualified is completed, and all secondary mass spectrometry to be qualified is divided into two categories according to whether the qualitative is successful: secondary mass spectrometry with qualitative result and secondary mass spectrometry with unsuccessful qualitative.

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