A mass spectrometry acquisition method, device, equipment and computer program product

Abstract

The present invention belongs to the field of bioinformatics, and specifically relates to a mass spectrometry acquisition method, device, equipment and computer program product, the method comprising: performing biological sample processing on a provided biological sample; performing liquid chromatography separation on the treated biological sample; performing mass spectrometry analysis on the biological sample after liquid chromatography separation; after the mass spectrometry analysis is completed, using the AIE-MS automatic exclusion method to identify and exclude interference signals in the mass spectrometry data, and iteratively acquiring secondary mass spectrometry data. The depth of metabolite identification in the prior art is still at a relatively low level compared to other omics. The mass spectrometry acquisition method, device, equipment and computer program product provided by the present invention can significantly increase the number of compound identifications, aiming to solve the core problem of low metabolite identification depth in existing LC-MS non-targeted metabolomics analysis, and has great potential in improving LC-MS metabolomics identification flux and improving data quality.

Description

Technical Field

[0001] The present invention belongs to the field of bioinformatics, and specifically relates to a mass spectrometry acquisition method, device, equipment and computer program product. Background Art

[0002] Metabolomics is the newest member of the “omics” family, which aims to comprehensively characterize the types and abundance information of small molecule compounds in biological samples. After decades of development, metabolomics has made significant progress, but the depth of metabolite identification is still at a lower level compared with other omics, and currently only about 5-10% of the identification rate can be achieved.

[0003] The analysis platform based on LC-MS (Liquid chromatography - mass spectrometry) is the most widely used research method for non-targeted metabolomics. Its qualitative process is not complicated, that is, the chromatographic mass spectrometry information of metabolites in the collected samples is compared with the chromatographic mass spectrometry information of the standard substances. Once the matching is completed, qualitative analysis can be achieved. The matching information mainly includes MS1 (First stage of the tandem mass spectrometer, primary mass spectrometry), MS2 (Second stage of the tandem mass spectrometer, secondary mass spectrometry) and RT (Retention time). Among them, the collection and analysis of MS2 secondary mass spectrometry data is a very critical step, and the richness of the collected information will directly determine the depth of metabolite identification. Traditional MS2 data acquisition methods usually use data-dependent acquisition strategies (Data Dependent Acquisition, DDA). However, this method has major problems and limitations such as limited collection quantity, high abundance signal influence, and background interference. Summary of the invention

[0004] In view of the shortcomings of the above-mentioned existing methods, the present invention provides a mass spectrometry acquisition method, device, equipment and computer program product, aiming to solve the core problem of low metabolite identification depth in existing LC-MS non-targeted metabolomics analysis.

[0005] To achieve the above-mentioned purpose, the present invention is implemented by the following technical solutions:

[0006] A mass spectrometry acquisition method, the method comprising the following steps:

[0007] S10: performing biological sample processing on the biological sample to be processed;

[0008] S20: performing liquid chromatography separation on the treated biological sample, wherein the liquid chromatography separation uses an ACQUITY UPLC HSS T3 chromatographic column;

[0009] S30: after liquid chromatography separation, the biological sample is subjected to mass spectrometry analysis using a ThermoOrbitrap Exploris 120 mass spectrometer;

[0010] S40: After the mass spectrometry analysis is completed, the AIE-MS (Automated iterative exclusion - Mass Spectrometry) automatic exclusion method is used to identify and exclude interference signals in the mass spectrometry data, and the secondary mass spectrometry data is acquired iteratively.

[0011] Furthermore, the AIE-MS automatic exclusion method in S40 includes:

[0012] S401: Setting the mass range and abundance threshold of ion signals in mass spectrometry data.

[0013] S402: Identify and exclude ion signals within the mass range of set mass spectrum data and not higher than the abundance threshold, and obtain secondary mass spectrum data.

[0014] Furthermore, the mass range and abundance threshold of the ion signal in S401 need to be set by an automatic exclusion list obtained by an AIE-MS mass spectrum acquisition method, and the AIE-MS mass spectrum acquisition method includes:

[0015] S4011: Select ion data in the clean and non-mixed peak segment according to the total ion chromatogram of the background ions of the Blank sample;

[0016] S4012: Selecting ion information of the ion data;

[0017] S4013: Screen out the ions that simultaneously appear in all Blank samples with the selected ion information as Blank sample background ions;

[0018] S4014: Extracting MS2 information in the pool sample using MSConvert software based on the background exclusion ions obtained;

[0019] S4015: Generate an AIE-MS automatic exclusion list based on the extracted MS2 information;

[0020] S4016: Setting the mass range and abundance threshold of the ion signal in the mass spectrometry data according to the obtained AIE-MS automatic exclusion list.

[0021] Furthermore, the identification and exclusion of ion signals within a set mass range and not higher than an abundance threshold adopt an iterative exclusion method, and the ion signals in the set mass spectrum data are iteratively excluded at set time intervals, and the set number of iterations is 4-5 times.

[0022] Furthermore, the biological sample processing step in S10 includes:

[0023] S101: using an organic solvent to precipitate proteins from a provided biological sample, and centrifuging to obtain a supernatant;

[0024] S102: vacuum concentrating the supernatant obtained by centrifugation;

[0025] S103: using a reconstitution solution to reconcentrate the supernatant after vacuum concentration;

[0026] S104: filtering the reconstituted and concentrated supernatant to remove residual impurities;

[0027] Wherein, the organic solvent is a mixture of methanol and acetonitrile, and the reconstituted solution is methanol.

[0028] Furthermore, the biological sample processing method in S10 is applicable to processing different types of biological samples including plasma samples, liver tissue samples, plant tissue samples, etc.

[0029] In addition, to achieve the above object, the present invention also proposes a mass spectrum acquisition device, the mass spectrum acquisition device comprising:

[0030] A sample pre-processing module, used for performing biological sample processing on the biological sample to be processed;

[0031] A sample separation module, used for performing liquid chromatography separation on the processed biological samples;

[0032] A mass spectrometry analysis module is used to perform mass spectrometry analysis on biological samples after liquid chromatography separation;

[0033] Automatic exclusion module: used to identify and exclude interference signals in mass spectrometry data using the AIE-MS automatic exclusion method after mass spectrometry analysis is completed, and to iteratively acquire secondary mass spectrometry data;

[0034] Wherein, the liquid chromatography separation uses an ACQUITY UPLC HST3 chromatographic column, and the mass spectrometry analysis uses a Thermo Orbitrap Exploris 120 mass spectrometer;

[0035] Among them, the automatic exclusion module also includes:

[0036] Data setting submodule: used to set the mass range and abundance threshold of ion signals in mass spectrometry data;

[0037] Identification and exclusion submodule: used to identify and exclude ion signals within the mass range of the set mass spectrometry data and not higher than the abundance threshold, and obtain secondary mass spectrometry data;

[0038] The data setting submodule sets the mass range and abundance threshold of the ion signal in the mass spectrometry data, which is set by the automatic exclusion list obtained by the AIE-MS mass spectrometry acquisition method, including:

[0039] Ion data selection sub-module: used to select clean, non-mixed peak ion data in the segment based on the total ion chromatogram of the background ions of the Blank sample;

[0040] Ion information selection sub-module: used for selecting ion information of the ion data;

[0041] Background ion selection sub-module: used to screen out ions that simultaneously appear in all Blank samples with the selected ion information as Blank sample background ions;

[0042] Information extraction sub-module: used to extract MS2 information in the pool sample using MSConvert software based on the obtained background exclusion ions;

[0043] Automatic exclusion list generation sub-module: used to generate AIE-MS automatic exclusion list based on the extracted MS2 information;

[0044] Data determination sub-module: used to determine the mass range and abundance threshold of ion signals in mass spectrometry data based on the obtained AIE-MS automatic exclusion list;

[0045] Wherein, the Blank sample is a blank sample, and the pool sample is a biological sample.

[0046] In addition, to achieve the above-mentioned purpose, the present invention also proposes a mass spectrometry acquisition device, which includes: a memory, a processor, and a mass spectrometry acquisition program stored in the memory and executable on the processor, and when the mass spectrometry acquisition program is executed by the processor, the steps of the mass spectrometry acquisition method described above are implemented.

[0047] In addition, to achieve the above-mentioned purpose, the present invention also provides a computer program product, which includes a mass spectrometry acquisition program, and when the mass spectrometry acquisition program is executed by a processor, it implements the mass spectrometry acquisition method described above.

[0048] The advantages and effects of the present invention are:

[0049] The method of the present invention greatly reduces the interference of background ions, increases the proportion of effective mass spectrometry information collected, can collect more secondary mass spectrometry information of low-abundance metabolites, and significantly increases the number of metabolite identifications; improves analysis efficiency, and improves the efficiency of data collection and processing while ensuring high-throughput analysis; reduces analysis costs, and reduces the need for repeated experiments through efficient collection strategies, thereby reducing overall experimental costs. In summary, the present invention is a mass spectrometry method that can significantly increase the number of compound identifications, and has great potential in improving LC-MS metabolomics identification throughput and improving data quality. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0051] Figure 1 The figure is a schematic diagram of a mass spectrometry acquisition method of the present invention.

[0052] Figure 2 It is a schematic flow chart of the automatic exclusion method of the present invention.

[0053] Figure 3 Schematic diagram of the AIE-MS mass spectrum acquisition method of the present invention.

[0054] Figure 4 Schematic diagram of the biological sample processing method of the present invention.

[0055] Figure 5 It is a schematic diagram of the structure of the mass spectrometry acquisition device of the present invention.

[0056] Figure 6 It is a schematic block diagram of the structure of the mass spectrometry acquisition electronic device of the present invention.

[0057] Figure 7 The figure is a comparison of the MS2 acquisition amount and the metabolite identification amount in the plasma tissue experiment using the mass spectrometry acquisition method of the present invention.

[0058] Figure 8 The figure is a comparison of the MS2 acquisition amount and the metabolite identification amount in the liver tissue experiment using the mass spectrometry acquisition method of the present invention.

[0059] Fig. 9 The figure is a comparison of the MS2 acquisition amount and the metabolite identification amount in the plant tissue experiment using the mass spectrometry acquisition method of the present invention. DETAILED DESCRIPTION

[0060] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0061] The present invention provides a mass spectrometry acquisition method, the method is composed as follows Figure 1 As shown, the following steps are included:

[0062] S10: Process the provided biological sample to obtain a pool sample.

[0063] Specifically, the biological sample processing steps are as follows Figure 4 As shown, including:

[0064] S101: using an organic solvent to precipitate proteins in a biological sample to be processed, and centrifuging to obtain a supernatant;

[0065] S102: vacuum concentrating the supernatant obtained by centrifugation;

[0066] S103: using a reconstitution solution to reconcentrate the supernatant after vacuum concentration;

[0067] S104: filtering the reconstituted and concentrated supernatant to remove residual impurities;

[0068] Specifically, the preparation process of the pool sample is to mix the mouse plasma sample, mouse liver tissue sample and Arabidopsis tissue sample into a pool sample after the above treatment, and perform 10 data acquisitions, of which 5 are performed using the conventional DDA mode and the remaining 5 are performed using the AIE-MS acquisition method of the present invention. Before the formal pool sample is loaded, 3 blank samples are loaded.

[0069] Specifically, the biological sample processing method is suitable for processing different types of biological samples including plasma samples, liver tissue samples, plant tissue samples, etc.

[0070] Specifically, the processing steps of plasma samples, taking mouse plasma samples as an example, include: transferring 50 μL of sample into a 2 mL centrifuge tube; adding 200 μL of pre-cooled methanol:acetonitrile (1:1, v / v), v / v is the volume ratio, and vortexing for 30 seconds; freezing in a -20°C refrigerator for 30 minutes; centrifuging at 12,000 rpm and 4°C for 10 minutes, taking 200 μL of the supernatant and concentrating it to dryness in a vacuum; adding 100 μL of 50% methanol (containing 5 ppm 2-chlorophenylalanine) for re-dissolution, and vortexing for 30 seconds; centrifuging at 12,000 rpm and 4°C for 10 minutes, taking the supernatant and filtering it through a 0.22 μm filter membrane, and adding the filtrate into the detection bottle for LC-MS analysis.

[0071] Specifically, the processing steps of liver tissue samples, taking mouse liver tissue samples as an example, include: weighing 50 mg of sample into a 2 mL centrifuge tube; adding 200 μL of pre-cooled water, adding 2 steel beads, putting into a high-throughput tissue grinder, 55 Hz, grinding for 60 s, repeating this step once; adding 800 μL of methanol:acetonitrile (1:1, v / v); putting into an ultrasonic cleaner for ultrasonication for 30 min; putting into a -20°C refrigerator for freezing for 30 min; centrifuging at 12,000 rpm and 4°C for 10 min, taking 800 μL of supernatant, and concentrating to dryness in vacuo; adding 150 μL of 50% methanol (containing 5 ppm 2-chlorophenylalanine) for re-dissolution, vortexing for 30 s; centrifuging at 12,000 rpm and 4°C for 10 min, taking the supernatant and filtering through a 0.22 μm filter membrane, and adding the filtrate into the detection bottle for LC-MS analysis.

[0072] Specifically, the processing steps of plant tissue samples, taking Arabidopsis tissue samples as an example, include: weighing 100 mg of sample into a 2 mL centrifuge tube; adding 500 μL of pre-cooled methanol: acetonitrile: water (2:2:1, v / v / v, containing 5 ppm 2-chlorophenylalanine), adding 2 steel beads, and vortexing for 30 s; placing in a high-throughput tissue grinder, 55 Hz, grinding for 60 s, repeating this step once; placing in an ultrasonic cleaner for 10 min; placing in a -20°C refrigerator for freezing for 30 min; centrifuging at 12,000 rpm and 4°C for 10 min, taking the supernatant and filtering it through a 0.22 μm filter membrane, and adding the filtrate to the detection bottle for LC-MS analysis.

[0073] Specifically, the biological sample processing method in step S10 can perform preliminary processing on the biological sample, and can filter out residual impurities, so as to facilitate the subsequent liquid chromatography separation of the biological sample in step S20 and the mass spectrometry analysis of the biological sample in step S30. In addition, the biological sample processing method in step S10 is suitable for processing including but not limited to the above three different types of biological samples.

[0074] Step S20: The pool sample obtained after processing the biological sample is subjected to liquid chromatography separation, wherein the liquid chromatography separation uses an ACQUITY UPLC HSS T3 column (100Å, 1.8 µm, 2.1 mm × 100 mm), a flow rate of 0.4 mL / min, a column temperature of 40°C, an automatic sampler of 8°C, and an injection volume of 2 μL. The ACQUITY UPLC HSS T3 column is a liquid chromatography column, which is generally used for high performance liquid chromatography separation.

[0075] Specifically, the parameter 100Å is a representation of the pore size of the packing material of the chromatographic column. Ångström (angstrom) is a unit of length used to represent atomic-level dimensions. 100Å means that the pore size of the packing material is 100 angstroms.

[0076] Specifically, the parameter 1.8 µm is the diameter of the filler particles, expressed in micrometers, indicating that the filler particles are 1.8 micrometers in size. This small particle size helps improve separation efficiency and resolution.

[0077] Specifically, the parameter 2.1 mm × 100 mm is the inner diameter and length of the chromatographic column. 2.1 mm means that the inner diameter of the chromatographic column is 2.1 mm, and 100 mm means that the length of the chromatographic column is 100 mm. The combination of the inner diameter and length determines the separation ability and analysis speed of the chromatographic column.

[0078] Specifically, the flow rate of 0.4 mL / min is an important parameter in liquid chromatography, which indicates the speed at which the solution flows in the chromatographic column. 0.4 mL / min means that the flow rate is 0.4 milliliters per minute, which is the rate at which the solvent passes through the chromatographic column. The choice of flow rate will affect the separation efficiency, resolution, and analysis time.

[0079] Specifically, a column temperature of 40°C refers to the temperature setting of the chromatographic column, indicating that the temperature of the chromatographic column is 40 degrees Celsius. Controlling the column temperature can affect the selectivity, resolution, and peak shape of the separation.

[0080] Specifically, the automatic sampler 8°C means that the temperature of the automatic sampler is set to 8 degrees Celsius. Maintaining the sampler at a lower temperature helps to maintain the stability of the sample and prevent the sample from being degraded or volatilized during the injection process.

[0081] Specifically, the injection volume of 2 μL refers to the amount of sample introduced into the chromatographic system in liquid chromatography separation. The injection volume of 2 μL means that the injection volume is 2 microliters (μL), that is, the amount of sample introduced into the chromatographic system each time is 2 microliters. Accurate control of the injection volume is crucial to the accuracy and repeatability of the analysis.

[0082] After step S20, different compounds in the biological sample can be effectively separated so that they appear separately in the detector, thereby achieving quantitative or qualitative analysis of each component.

[0083] Step S30: After liquid chromatography separation, the pool sample is subjected to mass spectrometry analysis using a ThermoOrbitrap Exploris 120 mass spectrometer.

[0084] Specifically, the Thermo Orbitrap Exploris 120 mass spectrometer performs DDA mass spectrometry data acquisition in positive and negative ion modes on the biological sample after processing in step S20, respectively. A HESI source is used, a spray voltage of 3.5 kV / -3.0 kV, a sheath gas of 40 arb, an auxiliary gas of 15 arb, a capillary temperature of 325°C, an auxiliary gas temperature of 300°C, a primary resolution of 60,000, a scanning range of 100-1000 m / z, an AGC Target Standard, a Max IT of 100 ms, the top 4 ions in response are screened for secondary fragmentation, a dynamic exclusion time of 8 s, a secondary resolution of 15,000, and an HCD collision energy of 30%.

[0085] Step S40: After the mass spectrometry analysis is completed, the AIE-MS automatic exclusion method is used to identify and exclude interference signals in the mass spectrometry data, and secondary mass spectrometry data is acquired by iterative acquisition.

[0086] Specifically, AIE-MS (Automated iterative exclusion - Mass Spectrometry) is a mass spectrometry acquisition method that can significantly increase the amount of effective secondary mass spectrometry data, thereby improving the depth of metabolite identification. Its basic principle is to automatically identify background ions and MS1 ions of the secondary mass spectra that have been collected with relatively high abundance based on the secondary and corresponding primary mass spectrometry data collected by conventional DDA, and generate a list of MS1 and corresponding RT collected by secondary exclusion. In the subsequent secondary acquisition of samples, the secondary mass spectra of the parent ions in the list are no longer collected, and it is iterated 4-5 times in sequence to achieve the purpose of increasing the amount of secondary mass spectrometry collected for the parent ions and improving the depth of metabolite identification.

[0087] Specifically, the AIE-MS automatic exclusion method process in step S40 is as follows: Figure 2 As shown, including:

[0088] S401: Setting the mass range and abundance threshold of ion signals in mass spectrometry data;

[0089] S402: Identify and exclude ion signals within the mass range of set mass spectrum data and not higher than the abundance threshold, and obtain secondary mass spectrum data.

[0090] Specifically, the mass range of mass spectrometry data is often used to exclude ion signals whose masses are not within the specified range to avoid low mass or noise interfering with data analysis; the abundance threshold is used to determine which ion signals have an abundance higher than the set threshold, and these ion signals will be retained for further analysis.

[0091] Specifically, the AIE-MS automatic exclusion method used needs to obtain an automatic exclusion list by the AIE-MS mass spectrum acquisition method. The AIE-MS mass spectrum acquisition method used has the following process: Figure 3 As shown, including:

[0092] S4011: Select ion data in the clean and non-mixed peak segment according to the total ion chromatogram of the background ions of the Blank sample;

[0093] S4012: Selecting ion information of the ion data;

[0094] S4013: Screen out the ions that simultaneously appear in all Blank samples with the selected ion information as Blank sample background ions;

[0095] S4014: Extracting MS2 information in the pool sample using MSConvert software based on the background exclusion ions obtained;

[0096] S4015: Generate an AIE-MS automatic exclusion list based on the extracted MS2 information;

[0097] S4016: Setting the mass range and abundance threshold of the ion signal in the mass spectrometry data according to the obtained AIE-MS automatic exclusion list.

[0098] Specifically, an iterative exclusion method is used to identify and exclude ion signals within a set mass range and not higher than an abundance threshold, and ion signals in set mass spectrometry data are iteratively excluded at set time intervals, with the set number of iterations being 4-5 times.

[0099] Specifically, the process of the iterative exclusion method is to first acquire mass spectrum data of sample 1, and then automatically give an exclusion list based on sample 1 through the AIE-MS mass spectrum acquisition method;

[0100] The obtained exclusion list is input into the acquisition parameters of sample 2, mass spectrum data is acquired, and then a new exclusion list is automatically given based on sample 2 by the AIE-MS mass spectrum acquisition method;

[0101] The obtained exclusion list is input into the acquisition parameters of sample 3, mass spectrometry data is acquired, and then a new exclusion list is automatically given based on sample 3 through the AIE-MS mass spectrometry acquisition method, which is iterated 4-5 times in sequence.

[0102] After step S40, a large amount of mass spectrometry data can be effectively processed, noise and irrelevant ion signals can be filtered out, and high-quality and meaningful ion signals can be retained for subsequent analysis and interpretation. The automatic exclusion method helps to improve the accuracy, reliability and interpretability of the data, thereby supporting more effective mass spectrometry experiments and data interpretation.

[0103] Specifically, in step S4011, the background ion source of the Blank sample is the 3-shot Blank sample loaded onto the machine before the formal pooling. The selected clean segment usually represents the area without the target compound signal, which can be used to identify and extract the background ion signal, such as selecting the 0-10 minute segment.

[0104] Specifically, in step S4012, the ion information of the top 200 ion data in the selected segment is selected;

[0105] Specifically, in step S4013, the ion information of the first 200 ion data of the three blank samples is screened, and the ion information mz (Mass to charge ratio, m / z) that appears simultaneously in the three blank samples is screened out as background exclusion ions.

[0106] Specifically, in step S4014, MS2 information refers to the information of fragment ions obtained by collision induced dissociation or other fragmentation techniques of ions. Extracting MS2 information of the extracted Blank sample background ions can help understand the structure and properties of these ions, which is helpful for subsequent exclusion and identification processes.

[0107] Specifically, in step S4015, the qualitative analysis of metabolites is highly dependent on the effective number of MS2 information collected. When searching multiple samples, qualitative analysis can be achieved if effective MS2 is collected in any sample. In theory, the MSMS (Tandem Mass Spectrometry) information collected from each sample has no overlap or crossover, which can achieve maximum effective MS2 collection. Based on this basic theory, a code block was written in R language to automatically generate exclusion list information for the next sample collection based on the MS2 information in the previous sample, so as to maximize the MSMS information collection.

[0108] Specifically, the AIE-MS acquisition method mainly increases the number of effective MSMS acquisitions to increase the number of metabolite identifications. Therefore, the two most critical indicators for evaluating the AIE-MS acquisition method and the conventional DDA acquisition method are: MS2 acquisition amount and metabolite identification amount. Figure 7 It can be seen that the AIE-MS acquisition method can significantly improve the MS2 acquisition and metabolite identification of plasma tissues; Figure 8 It can be seen that the AIE-MS acquisition method can significantly increase the amount of MS2 collected in liver tissue and improve the amount of metabolite identification; Fig. 9 It can be seen that the AIE-MS acquisition method can significantly increase the MS2 acquisition amount of plant tissues and improve the metabolite identification amount.

[0109] Specifically, according to the CD3.3 software search library information, the collected MSMS information was extracted, as shown in Table 1, pos represents positive ion mode, neg represents negative ion mode, pos-AIE represents AIE-MS acquisition method in positive ion mode, neg-AIE represents AIE-MS acquisition method in negative ion mode, AIE acquisition method-all represents the combination of positive and negative ion modes of AIE-MS acquisition method, pos-conventional DDA method represents DDA acquisition method in positive ion mode, neg-conventional DDA method represents DDA acquisition method in negative ion mode, conventional DDA method-all represents the combination of positive and negative ion modes of DDA acquisition method. In different sample types, the MS2 and identification numbers obtained by AIE-MS acquisition method are improved, but the improvement rates of different types of samples are different, and the differences are even large. The most significant improvement was in plasma samples, where the MS2 collection volume and metabolite identification volume increased by 61.49% and 36.76% respectively; Arabidopsis tissue samples increased by 36.13% and 21.67% respectively; and mouse liver tissue increased by 48.41% and 16.67% respectively.

[0110] Table 1 MS2 and identification quantity information of two acquisition methods for different sample types

[0111]

[0112] In summary, AIE-MS significantly improves the amount of MS2 collected, especially in plasma samples, where the improvement reaches 61.49%. The amount of metabolite identification is also significantly improved, but there are large differences between different sample types, and the improvement effect on animal tissues is relatively weak. Among them, the overall improvement effect of plasma is the most obvious, which may be due to the presence of rich and high-abundance lipid compounds in plasma samples. The AIE-MS collection method can better improve the detection of low-abundance compounds, especially the detection of compounds affected by blood lipids. Therefore, the AIE-MS collection method may be more suitable for the analysis of samples affected by high-abundance substances, such as serum plasma and other samples, and can more significantly improve the identification of compounds. It has great potential in improving the identification throughput of LC-MS metabolomics and improving data quality.

[0113] In addition, the present invention also proposes a mass spectrometry acquisition device, please refer to Figure 5 , the mass spectrum acquisition device comprises:

[0114] Sample pre-processing module: used for processing biological samples to be processed;

[0115] Sample separation module: used for liquid chromatography separation of processed biological samples;

[0116] Mass spectrometry analysis module: used for mass spectrometry analysis of biological samples after liquid chromatography separation;

[0117] Automatic exclusion module: used to identify and exclude interference signals in mass spectrometry data using the AIE-MS automatic exclusion method after mass spectrometry analysis is completed, and to iteratively acquire secondary mass spectrometry data;

[0118] Wherein, the liquid chromatography separation uses an ACQUITY UPLC HST3 chromatographic column, and the mass spectrometry analysis uses a Thermo Orbitrap Exploris 120 mass spectrometer;

[0119] Among them, the automatic exclusion module also includes:

[0120] Data setting submodule: used to set the mass range and abundance threshold of ion signals in mass spectrometry data;

[0121] Identification and exclusion submodule: used to identify and exclude ion signals within the mass range of the set mass spectrometry data and not higher than the abundance threshold, and obtain secondary mass spectrometry data;

[0122] The data setting submodule sets the mass range and abundance threshold of the ion signal in the mass spectrometry data, which is set by the automatic exclusion list obtained by the AIE-MS mass spectrometry acquisition method, including:

[0123] Ion data selection sub-module: used to select clean, non-mixed peak ion data in the segment based on the total ion chromatogram of the background ions of the Blank sample;

[0124] Ion information selection sub-module: used for selecting ion information of the ion data;

[0125] Background ion selection sub-module: used to screen out ions that simultaneously appear in all Blank samples with the selected ion information as Blank sample background ions;

[0126] Information extraction sub-module: used to extract MS2 information in the pool sample using MSConvert software based on the obtained background exclusion ions;

[0127] Automatic exclusion list generation sub-module: used to generate AIE-MS automatic exclusion list based on the extracted MS2 information;

[0128] Data determination sub-module: used to determine the mass range and abundance threshold of ion signals in mass spectrometry data based on the obtained AIE-MS automatic exclusion list;

[0129] Wherein, the Blank sample is a blank sample, and the pool sample is a biological sample.

[0130] The mass spectrometry acquisition device provided by the present application adopts the mass spectrometry acquisition method in the above embodiment, which can solve the technical problem of mass spectrometry acquisition. Compared with the prior art, the beneficial effects of the mass spectrometry acquisition device provided by the present application are the same as the beneficial effects of the mass spectrometry acquisition method provided by the above embodiment, and other technical features in the mass spectrometry acquisition device are the same as the features disclosed in the above embodiment method, which will not be repeated here.

[0131] The present application provides a mass spectrometry acquisition device, which includes: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the mass spectrometry acquisition method in the above-mentioned embodiment one.

[0132] Reference below Figure 6, which shows a schematic diagram of the structure of a mass spectrometry acquisition device suitable for implementing the embodiments of the present application. The mass spectrometry acquisition device in the embodiments of the present application may include but is not limited to mobile terminals such as mobile phones, laptop computers, digital broadcast receivers, PDAs (Personal Digital Assistants), PADs (Portable Application Descriptions), PMPs (Portable Media Players), etc., and fixed terminals such as digital TVs, desktop computers, etc. Figure 6 The mass spectrometry acquisition device shown is merely an example and should not bring any limitation to the functions and scope of use of the embodiments of the present application.

[0133] Figure 6 The mass spectrometry acquisition device shown may include a processing device 1001 (e.g., a central processing unit, a graphics processor, etc.), which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM: Read Only Memory) 1002 or a program loaded from a storage device 1003 to a random access memory (RAM: Random Access Memory) 1004. In RAM1004, various programs and data required for the operation of the mass spectrometry acquisition device are also stored. The processing device 1001, ROM1002, and RAM1004 are connected to each other through a bus 1005. An input / output (I / O) interface 1006 is also connected to the bus. Generally, the following systems can be connected to the I / O interface 1006: an input device 1007 including, for example, a touch screen, a touch pad, a keyboard, a mouse, an image sensor, a microphone, an accelerometer, a gyroscope, etc.; an output device 1008 including, for example, a liquid crystal display (LCD: Liquid Crystal Display), a speaker, a vibrator, etc.; a storage device 1003 including, for example, a magnetic tape, a hard disk, etc.; and a communication device 1009. The communication device 1009 can allow the mass spectrometry acquisition device to communicate with other devices wirelessly or by wire to exchange data. Although the figure shows a mass spectrometry acquisition device with various systems, it should be understood that it is not required to implement or have all the systems shown. More or fewer systems can be implemented or have alternatively.

[0134] In particular, according to the embodiments disclosed in the present application, the process described above with reference to the flowchart can be implemented as a computer software program. For example, the embodiments disclosed in the present application include a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program includes a program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network through a communication device, or installed from a storage device 1003, or installed from a ROM 1002. When the computer program is executed by the processing device 1001, the above-mentioned functions defined in the method of the embodiment disclosed in the present application are executed.

[0135] The mass spectrometry acquisition device provided by the present application adopts the mass spectrometry acquisition method in the above embodiment, which can solve the technical problem of mass spectrometry acquisition. Compared with the prior art, the beneficial effects of the mass spectrometry acquisition device provided by the present application are the same as the beneficial effects of the mass spectrometry acquisition method provided by the above embodiment, and the other technical features in the mass spectrometry acquisition device are the same as the features disclosed in the method of the previous embodiment, which will not be repeated here.

[0136] The various parts disclosed in this application can be implemented by hardware, software, firmware or a combination thereof. In the description of the above embodiments, specific features, structures, materials or characteristics can be combined in any one or more embodiments or examples in a suitable manner.

[0137] The present application also provides a computer program product, including a computer program, which implements the steps of the mass spectrometry acquisition method as described above when executed by a processor.

[0138] The computer program product provided in this application can solve the technical problems of the mass spectrometry acquisition method. Compared with the prior art, the beneficial effects of the computer program product provided in this application are the same as the beneficial effects of the mass spectrometry acquisition method provided in the above embodiment, which will not be repeated here.

[0139] The above descriptions are only some embodiments of the present application, and are not intended to limit the patent scope of the present application. All equivalent structural changes made using the contents of the present application specification and drawings under the technical concept of the present application, or direct / indirect applications in other related technical fields are included in the patent protection scope of the present application.

Claims

1. A mass spectrometry acquisition method, characterized in that: The method comprises the following steps: S10: Perform biological sample processing on the provided plasma sample; S20: performing liquid chromatography separation on the processed plasma sample; S30: After liquid chromatography separation, the plasma samples were subjected to mass spectrometry analysis; S40: After the mass spectrometry analysis is completed, the AIE-MS automatic exclusion method is used to identify and exclude interference signals in the mass spectrometry data, and secondary mass spectrometry data is acquired iteratively; Wherein, the liquid chromatography separation uses an ACQUITY UPLC HSS T3 chromatographic column, and the mass spectrometry analysis uses a ThermoOrbitrap Exploris 120 mass spectrometer; Wherein, the S40 specifically includes: S401: Setting the mass range and abundance threshold of ion signals in mass spectrometry data; S402: Identify and exclude ion signals within the mass range of set mass spectrum data and not higher than the abundance threshold, and obtain secondary mass spectrum data; The mass range and abundance threshold of the ion signal in the mass spectrum data are set in S401 by the automatic exclusion list obtained by the AIE-MS mass spectrum acquisition method, and the AIE-MS mass spectrum acquisition method includes: S4011: Select ion data in the clean and non-mixed peak segment according to the total ion chromatogram of the background ions of the Blank sample; S4012: Selecting ion information of the ion data; S4013: Screen out the ions that simultaneously appear in all Blank samples with the selected ion information as Blank sample background ions; S4014: Extracting MS2 information in the pool sample using MSConvert software based on the background exclusion ions obtained; S4015: Generate an AIE-MS automatic exclusion list based on the extracted MS2 information; S4016: determining a mass range and an abundance threshold of ion signals in the mass spectrometry data according to the obtained AIE-MS automatic exclusion list; Wherein, the Blank sample is a blank sample, and the pool sample is a plasma sample.

2. A mass spectrometry acquisition method according to claim 1, characterized in that: The identification and exclusion of ion signals within the mass range of the set mass spectrum data and not higher than the abundance threshold adopts an iterative exclusion method to iteratively exclude ion signals in the set mass spectrum data at set time intervals.

3. A mass spectrometry acquisition method according to claim 1, characterized in that: The biological sample processing step in S10 includes: Using an organic solvent to precipitate proteins from a provided biological sample, and centrifuging to obtain a supernatant; The supernatant obtained by centrifugation is concentrated under vacuum; The supernatant after vacuum concentration is reconstituted and concentrated using a reconstitution solution; Filter the reconstituted and concentrated supernatant to remove residual impurities; Wherein, the organic solvent is a mixture of methanol and acetonitrile, and the reconstituted solution is methanol.

4. A mass spectrometry acquisition device, characterized in that: Sample pre-processing module: used for biological sample processing of plasma samples to be processed; Sample separation module: used for liquid chromatography separation of processed plasma samples; Mass spectrometry analysis module: used to perform mass spectrometry analysis on plasma samples after liquid chromatography separation; Automatic exclusion module: used to identify and exclude interference signals in mass spectrometry data using the AIE-MS automatic exclusion method after mass spectrometry analysis is completed, and to iteratively acquire secondary mass spectrometry data; Wherein, the liquid chromatography separation uses an ACQUITY UPLC HST3 chromatographic column, and the mass spectrometry analysis uses a Thermo Orbitrap Exploris 120 mass spectrometer; Among them, the automatic exclusion module also includes: Data setting submodule: used to set the mass range and abundance threshold of ion signals in mass spectrometry data; Identification and exclusion submodule: used to identify and exclude ion signals within the mass range of the set mass spectrometry data and not higher than the abundance threshold, and obtain secondary mass spectrometry data; The data setting submodule sets the mass range and abundance threshold of the ion signal in the mass spectrometry data, which is set by the automatic exclusion list obtained by the AIE-MS mass spectrometry acquisition method, including: Ion data selection sub-module: used to select clean, non-contaminated peak ion data in the segment based on the total ion chromatogram of the background ions of the Blank sample; Ion information selection sub-module: used for selecting ion information of the ion data; Background ion selection sub-module: used to screen out ions that simultaneously appear in all Blank samples as Blank sample background ions; Information extraction sub-module: used to extract MS2 information in the pool sample using MSConvert software based on the obtained background exclusion ions; Automatic exclusion list generation sub-module: used to generate AIE-MS automatic exclusion list based on the extracted MS2 information; Data determination sub-module: used to determine the mass range and abundance threshold of ion signals in mass spectrometry data based on the obtained AIE-MS automatic exclusion list; Wherein, the Blank sample is a blank sample, and the pool sample is a plasma sample.

5. A mass spectrometry acquisition device, characterized in that: The mass spectrometry acquisition device comprises: A memory, a processor, and a mass spectrometry acquisition program stored in the memory and executable on the processor, wherein the mass spectrometry acquisition program implements the mass spectrometry acquisition method according to any one of claims 1 to 3 when executed by the processor.

6. A computer program product, characterized in that The computer program product comprises a mass spectrometry acquisition program, and when the mass spectrometry acquisition program is executed by a processor, the mass spectrometry acquisition method according to any one of claims 1 to 3 is implemented.

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