A method and system for evaluating microplastic neurotoxicity based on dia mass spectrometry technology

Abstract

This invention relates to the field of chemical and biological detection technology, and provides a method and system for assessing the neurotoxicity of microplastics based on DIA mass spectrometry. The method includes the following steps: constructing an animal model using the microplastic to be assessed and conducting behavioral experiments; obtaining whole hippocampal proteins from the animal model and performing enzymatic digestion to obtain a peptide mixture; acquiring mass spectrometry data of the peptide mixture using a data-independent acquisition mode; performing qualitative and quantitative analysis on the mass spectrometry data to screen differentially expressed proteins; performing bioinformatics analysis on the differentially expressed proteins; and combining the bioinformatics analysis results with the behavioral experiment results to assess the neurotoxicity of microplastics. This invention combines bioinformatics and behavioral analysis to systematically assess the impact of exposure to microplastics such as polytetrafluoroethylene (PTFE) on the neurological function of animals, providing a comprehensive mechanistic explanation and effective assessment method for the neurotoxicity of microplastics.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of chemical biological detection, and particularly relates to a method and system for evaluating microplastic neurotoxicity based on DIA mass spectrometry. BACKGROUND

[0002] Microplastics (MPs) are plastic fibers, particles or films with a particle size of less than 5 mm, and have become a new type of pollutant that pervades the global ecosystem. MPs enter the body through various pathways such as respiration, diet and contact, and are bioaccumulated and transmitted through the food chain. Polytetrafluoroethylene (PTFE) is a common plastic material widely used in daily life such as non-stick pan coatings and food packaging. PTFE-MPs and smaller nanoplastics (NPs) have invaded human blood vessels, liver, kidneys and reproductive systems, causing damage to normal physiological functions of organs, including inflammatory response, endocrine disruption and DNA damage.

[0003] Currently, research on microplastics has focused on their distribution in the environment, ecological risks and effects on the digestive system, but the toxic effects on the nervous system, especially the central nervous system of higher mammals, and the molecular mechanisms have not been fully studied. Traditional neurotoxicity evaluation relies on behavioral experiments and histopathological observation, which are effective but difficult to reveal the specific toxic action mechanisms at the molecular level, and lack high sensitivity and predictability. SUMMARY

[0004] The purpose of the present application is to provide a method for evaluating the neurotoxicity of microplastics based on DIA mass spectrometry, which aims to solve the above technical problems.

[0005] The present application is implemented as follows: a method for evaluating the neurotoxicity of microplastics based on DIA mass spectrometry, comprising the following steps:

[0006] Using the microplastics to be evaluated, an animal model is constructed, and a behavioral experiment is performed;

[0007] The hippocampus proteins of the animal model are obtained and subjected to enzymatic digestion to obtain a peptide mixture;

[0008] The peptide mixture is subjected to mass spectrometry data acquisition using a data-independent acquisition mode;

[0009] The mass spectrometry data are subjected to qualitative and quantitative analysis to screen differential expression proteins;

[0010] The differential expression proteins are subjected to bioinformatics analysis;

[0011] The bioinformatics analysis result is combined with the behavior experiment result to evaluate the neurotoxicity of the microplastic.

[0012] Further, the behavior experiment is a Morris water maze behavior experiment.

[0013] Further, the enzymolysis method is a filter membrane assisted proteolysis method.

[0014] Further, the mass spectrum data is liquid chromatography-tandem mass spectrum data.

[0015] Further, the step of acquiring mass spectrum data of the peptide mixture by using a data-independent acquisition mode specifically comprises:

[0016] The peptide mixture is analyzed by using a data-dependent acquisition mode to obtain the retention time, parent ion and fragment ion information of the peptide, so as to construct a universal library of the hippocampus.

[0017] Based on the universal library of the hippocampus, data acquisition of the data-independent acquisition mode is performed on all the peptide mixtures to obtain mass spectrum data.

[0018] Further, the step of qualitatively and quantitatively analyzing the mass spectrum data and screening the differentially expressed proteins specifically comprises:

[0019] The mass spectrum data is compared with a pre-established spectrum library to complete qualitative identification of the peptides and proteins, and relative quantitative analysis is performed to obtain proteomic data.

[0020] The proteomic data is statistically analyzed, and the differential fold and significance level are combined to screen out differentially expressed proteins.

[0021] Further, the bioinformatics analysis includes GO enrichment analysis and KEGG pathway analysis; the GO enrichment analysis enriches the functions of the differentially expressed proteins from three aspects of biological processes, cell components and molecular functions; the KEGG pathway analysis performs pathway annotation and enrichment analysis by mapping the differentially expressed proteins into a KEGG database to identify key signal pathways affected by the microplastic.

[0022] Further, the microplastic includes polytetrafluoroethylene microplastic.

[0023] Another object of the present application is to provide a system for evaluating the neurotoxicity of microplastic based on DIA mass spectrum technology, which is used to implement the above method and comprises:

[0024] A behavior experiment module is used to perform a behavior experiment on an animal model constructed by using the microplastic to be evaluated.

[0025] A mass spectrometry data acquisition module is configured to acquire mass spectrometry data of a peptide mixture in a data-independent acquisition mode, wherein the peptide mixture is obtained by enzymatic digestion of hippocampal whole proteins of an animal model;

[0026] A mass spectrometry data analysis module is configured to perform qualitative and quantitative analysis on the mass spectrometry data and screen differential expression proteins;

[0027] A bioinformatics analysis module is configured to perform bioinformatics analysis on the differential expression proteins;

[0028] A neurotoxicity evaluation module is configured to combine the bioinformatics analysis results and the behavioral experiment results to evaluate the neurotoxicity of the microplastics.

[0029] The method for evaluating the neurotoxicity of microplastics based on the DIA mass spectrometry technology provided by the application combines bioinformatics analysis and behavioral experiment analysis to systematically evaluate the influence degree of polytetrafluoroethylene and other microplastics on the nerve function damage of animals, and provides a comprehensive mechanism explanation and effective evaluation method for the neurotoxicity of microplastics.

[0030] 1. High sensitivity and systematicness: the DIA mass spectrometry technology can synchronously and accurately quantitatively analyze thousands of proteins in hippocampal tissues without bias, overcomes the low flux of the traditional targeted method and the poor repeatability of the DDA method, and can find subtle and early protein expression changes.

[0031] 2. Mechanism depth: not only differential expression proteins are screened, but also GO and KEGG and other system bioinformatics analysis are performed to convert the discrete protein list into biological meaningful pathways and functional networks, so that the neurotoxicity mechanism of microplastics is explained from multiple levels of molecular function, cell component and biological process.

[0032] 3. Multi-dimensional verification: bioinformatics analysis and behavioral experiment are innovatively combined, the bioinformatics analysis results reveal the potential mechanism from the molecular level, and the behavioral experiment provides functional phenotype evidence from the whole animal level, and the two are mutually verified, so that the conclusion is more comprehensive and reliable.

[0033] 4. Wide application prospect: the method established by the application is not only suitable for evaluating PTFE-MPs, but also can provide a standardized and efficient technical route for the neurotoxicity evaluation of other types of microplastics or environmental pollutants. The identified key differential expression proteins can be used as potential neurotoxicity biomarkers for environmental monitoring and health risk assessment. BRIEF DESCRIPTION OF DRAWINGS

[0034] Figure 1A flowchart of the method for evaluating microplastic neurotoxicity based on DIA mass spectrometry technology provided by the embodiments of the present application.

[0035] Figure 2 A mouse water maze positioning navigation map; in the figure, Control is the control group, and MPs is the PTFE-MPs exposure group; A, mouse positioning direction trajectory map; B, escape latency; C, movement distance; D, effective movement time; E, effective movement distance.

[0036] Figure 3 A space exploration behavior trajectory map; in the figure, Control is the control group, and MPs is the PTFE-MPs exposure group; A, mouse space exploration trajectory map; B, times of crossing platform; C, escape platform detention time; D, effective movement time; E, effective movement distance.

[0037] Figure 4 Differential expression protein results of the PTFE-MPs exposure group relative to the control group; wherein blue is down-regulated, and red is up-regulated.

[0038] Figure 5 A mouse hippocampus differential expression protein volcano plot of the PTFE-MPs exposure group relative to the control group; wherein the abscissa is the logarithmic transformation of Fold Change (FC, combined difference multiple), and the ordinate is the negative logarithmic transformation of p-value (p-value, significance level). Each point represents a protein, wherein a red point is a significantly highly expressed protein, a darker color indicates a higher up-regulation multiple, a blue point is a significantly lowly expressed protein, a darker color indicates a higher down-regulation multiple, and a gray point is a non-differential expression protein. p

[0039] Figure 6 A clustering heat map of differential expression proteins in the PTFE-MPs exposure group and the control group; the redder the color, the higher the relative expression, and the bluer the color, the lower the relative expression.

[0040] Figure 7 A bubble chart of differential expression proteins of the PTFE-MPs exposure group relative to the control group.

[0041] ​Figure 8 BP (Biological Process, biological process) term function enrichment chart of differential proteins.

[0042] Figure 9 MF (Molecular Function, molecular function) term function enrichment chart of differential proteins.

[0043] Figure 10 CC (Cellular Component, cellular component) term function enrichment chart of differential proteins.

[0044] Figure 11 KEGG pathway enrichment bar chart of differential expression proteins.

[0045] Figure 12 KEGG pathway bubble chart of differential expression proteins.

[0046] Figure 13 Dendrogram of the relationship between differential expression proteins and pathways; from left to right in the figure, differential expression proteins (red up-regulation, blue down-regulation), pathways, second-level classification of pathways, and top-level classification of pathways. DETAILED DESCRIPTION

[0047] In order to make the objects, technical solutions and advantages of the present application clearer, further detailed description will be given below in combination with the drawings and examples. It should be understood that the specific examples described herein are only used to explain the present application, and are not used to limit the present application.

[0048] Proteomics technology can reveal the changes in protein expression of organisms under specific stimulation in a panoramic manner, and is a powerful tool for discovering toxic biomarkers and elucidating molecular mechanisms. The data-independent acquisition (DIA) technology combines the advantages and characteristics of traditional proteomics "shotgun method" and mass spectrometry absolute quantification "gold standard" selected reaction monitoring / multiple reaction monitoring technology. In addition, the DIA technology has the advantages of panoramic scanning and data traceability. The present application uses DIA quantitative proteomics technology to identify the effects of microplastics on the differential expression proteins of mouse hippocampus, and provides strong technical support for revealing the mechanism of microplastic neurotoxicity.

[0049] The present application aims to provide a high-efficiency, accurate and repeatable method for identifying the effects of microplastic exposure on the protein expression of mouse hippocampus based on proteomics technology. The method can systematically identify the significant differential expression proteins of mice caused by microplastic exposure by optimizing the sample processing procedure, improving the mass spectrometry analysis parameters and developing bioinformatics analysis algorithms, and provides technical support and molecular targets for in-depth study of the mechanism of microplastic neurotoxicity through behavioral verification.

[0050] As Figure 1 shown in the figure, in one embodiment of the present application, a method for evaluating the neurotoxicity of microplastics based on DIA mass spectrometry technology is provided, comprising the following steps:

[0051] S100, using the microplastics to be evaluated, constructing an animal model and performing a behavioral experiment;

[0052] S200, obtaining hippocampal whole proteins of the animal model and performing enzymolysis to obtain a peptide mixture;

[0053] S300, performing mass spectrometry data acquisition on the peptide mixture in a data-independent acquisition (DIA) mode;

[0054] S400, performing qualitative and quantitative analysis on the mass spectrometry data and screening differential expression proteins;

[0055] S500, performing bioinformatics analysis on the differential expression proteins;

[0056] S600, combining the bioinformatics analysis results with the behavioral experiment results to evaluate the neurotoxicity of the microplastics.

[0057] In the embodiment of the present application, the microplastics include polytetrafluoroethylene microplastics (PTFE-MPs), but are not limited thereto. The method can reveal that PTFE-MPs exposure induces upregulation or downregulation of hippocampal protein expression, causes damage to the learning and memory ability of animals, and leads to neurological dysfunction.

[0058] In actual application, the construction method of the animal model is as follows: C59L / 6 male mice (4-6 weeks) are administered with 3 μm PTFE-MPs at 1 mg / day by gavage for 4 weeks; the controlled conditions for constructing the animal model are as follows: stable temperature of 22±1℃, relative humidity of 55±5%, and light / dark cycle of 12h.

[0059] In addition, the behavioral experiment is a Morris water maze behavioral experiment, which includes a positioning cruise and a spatial exploration experiment to test the cognitive dysfunction of mice caused by microplastics.

[0060] In a preferred embodiment of the present application, the enzymolysis method is a filter-aided protein enzymolysis (FASP) method; the obtained hippocampal whole proteins are enzymolyzed into a peptide mixture by FASP, and desalting, quantification and other pretreatments are performed.

[0061] In a preferred embodiment of the present application, the mass spectrometry data is liquid chromatography-tandem mass spectrometry (LC-MS / MS) data.

[0062] In a preferred embodiment of the present application, the step of performing mass spectrometry data acquisition on the peptide mixture using a data-independent acquisition mode specifically comprises:

[0063] Part of the peptide mixture is analyzed using a data-dependent acquisition (DDA) mode to obtain the retention time, parent ion m / z and fragment ion information of the peptide, so as to construct a universal library of hippocampus;

[0064] Based on the universal library of hippocampus, data acquisition on all peptide mixtures is performed using a data-independent acquisition mode to obtain mass spectrometry data.

[0065] In a preferred embodiment of the present application, the step of performing qualitative and quantitative analysis on the mass spectrometry data to screen differentially expressed proteins specifically comprises:

[0066] Using existing professional software (such as Spectronaut, DIA-NN, OpenSWATH, etc.), the mass spectrometry data is compared with the pre-established spectral library to complete the qualitative identification of the peptide and protein, and relative quantitative analysis is performed to obtain proteomic data;

[0067] Statistical analysis (such as t-test, variance analysis, etc.) is performed on the proteomic data, combined with the difference fold (Fold Change, FC) and significance level (p-value), to screen out differentially expressed proteins (Differentially Expressed Proteins, DEPs) that are significantly up-regulated and down-regulated between the PTFE-MPs exposure group and the control group, for example, according to the expression difference fold greater than 1.5 times and the significance level p value less than 0.05 to screen differentially expressed proteins. p

[0068] In a preferred embodiment of the present application, the bioinformatics analysis includes GO enrichment analysis and KEGG pathway analysis; the GO enrichment analysis enriches the functions of differentially expressed proteins from three aspects of biological processes, cellular components and molecular functions; the KEGG pathway analysis performs pathway annotation and enrichment analysis by mapping differentially expressed proteins into the KEGG database to identify key signaling pathways affected by microplastics.

[0069] In another embodiment of the present application, a system for evaluating the neurotoxicity of microplastics based on DIA mass spectrometry technology is also provided, which is used to implement the above method and comprises:

[0070] A behavior experiment module for performing a behavior experiment on an animal model constructed using the microplastics to be evaluated;

[0071] ​a mass spectrometry data acquisition module, configured to acquire mass spectrometry data of the peptide mixture in a data-independent acquisition mode, wherein the peptide mixture is obtained by enzymatic digestion of hippocampus total proteins of the animal model;

[0072] a mass spectrometry data analysis module, configured to perform qualitative and quantitative analysis on the mass spectrometry data, and screen the differentially expressed proteins;

[0073] a bioinformatics analysis module, configured to perform bioinformatics analysis on the differentially expressed proteins;

[0074] a neurotoxicity evaluation module, configured to combine the bioinformatics analysis result and the behavioral experiment result, and evaluate the neurotoxicity of the microplastics.

[0075] It should be noted that the above modules can be implemented in the form of a computer program, which can be run on a computer device, and the computer program composed of the modules can be stored in the memory of the computer device to enable the processor to execute the steps of the above method.

[0076] The following examples are illustratively described with respect to the evaluation of the neurotoxicity of PTFE-MPs, but are not limited thereto. The method provided in the embodiments of the present application can be applied to the neurotoxicity evaluation of other types of microplastics or environmental pollutants.

[0077] Example 1: Animal experiment, sample preparation and protease digestion

[0078] 1. Establishment of animal model: The mouse experiment was performed in accordance with the Guide for the Care and Use of Laboratory Animals published by the European Commission. C57BL / 6 male mice (4-6 weeks) were purchased from VITROLIFE Biotechnology Co., Ltd. and randomly divided into a control group (Control) and a PTFE-MPs exposure group (10 mice in each group). The mice were raised at a temperature of 22±1℃ and a humidity of 55±5%, with a 12 h light / dark cycle. All animals had free access to water and food. The control group was administered 95% saline by gavage for 5 weeks, and the exposure group was administered saline for 1 week, followed by 1 mg / day of 3 μm PTFE-MPs suspension for the last 4 weeks. At the same time, behavioral experiments were performed in the last week.

[0079] 2、Morris water maze behavior experiment: The positioning cruise experiment uses a water maze round pool with a diameter of 1200 mm and a depth of 60 cm. The experimental platform (diameter 65 mm) is placed 1 cm away from the water surface in the N quadrant. All mice are trained to find the hidden platform and receive 4 experiments per day for 6 consecutive days. In each experiment, the mice are released from different starting points and allowed to search for the platform for 1 minute. If the mouse does not find the platform within 60 seconds, it will be guided to the platform and allowed to stay on the platform for 10 seconds. On the seventh day, a probe test was conducted to examine the spatial memory of the mice. The mice were released from a new position different from the training day and allowed to swim for 60 seconds without the platform.

[0080] In the positioning cruise experiment (as shown in Figure 2 , compared with the control group of mice, the PTFE-MP exposure group of mice mainly relied on the edge, took longer to find the platform, and needed longer escape latency, with a total movement distance of 16000 mm, but the movement time in the effective area and the movement distance in the effective area were shorter, about 3 times smaller (P<0.05), indicating that the exposure group of mice had memory impairment. The learning and memory ability of mice was further evaluated by spatial exploration test, and the results are shown in Figure 3 , compared with the control group, the number of times the mice in the exposure group crossed the platform, the movement distance, the residence time, and the escape platform retention time in the effective area were significantly reduced (P<0.05), indicating that the mice in the exposure group had memory impairment. The results of the behavior experiment showed that PTFE-MPs can cause memory impairment and memory decline in mice.

[0081] 3、Sample preparation: After the behavior experiment, the mice were fed for one night, then killed by cervical dislocation the next day, and the hippocampal tissue was quickly separated, frozen in liquid nitrogen for 5 minutes, and stored at -80°C for long-term preservation. After grinding in liquid nitrogen, an appropriate amount of SDT lysis buffer was added to each sample, transferred to an EP tube, then boiled in a water bath for 3 minutes, ultrasonicated for 2 minutes, centrifuged at 4°C, 16000g for 20 minutes, and the supernatant was taken for protein quantification using the BCA method.

[0082] 4. Protein digestion: Dithiothreitol (DTT) was added to 100 mM in each sample, and boiled in water bath for 5 min, and then cooled to room temperature. 200 μL urea buffer (UA buffer) was added and mixed, and then transferred to 10 KD ultrafiltration centrifuge tube, and centrifuged at 12000 g for 15 min. 200 μL UA buffer was added and centrifuged at 12000 g for 15 min, and the filtrate was discarded. 100 μL iodoacetamide (IAM) was added, and oscillated at 600 rpm for 1 min, and then placed in dark at room temperature for 30 min, and centrifuged at 12000 g for 10 min. 100 μL UA buffer was added, and centrifuged at 12000 g for 10 min for 2 times. 100 μL NH4HCO3 buffer was added, and centrifuged at 14000 g for 10 min for 2 times. 40 μL trypsin buffer was added, and oscillated at 600 rpm for 1 min, and then placed at 37 °C for 16-18 h. A new collection tube was used, and centrifuged at 12000 g for 10 min, and the filtrate was collected, and then an appropriate amount of 0.1% trifluoroacetic acid (TFA) solution was added. The digested peptides were desalted by C18 Cartridge, and vacuum freeze-dried. After drying, the digested peptides were re-dissolved with 0.1% formic acid (FA), and the peptide concentration was determined for LC-MS analysis.

[0083] Example 2: DIA mass spectrometry data acquisition and data retrieval

[0084] Mass spectrometry data collection: An appropriate amount of peptide segments of each sample was taken for chromatographic separation using a Vanquish Neo UHPLC system, operated Neo UHPLC chromatographic system (Thermo Scientific). The buffer was 0.1% formic acid aqueous solution, and the B liquid was 0.1% formic acid acetonitrile aqueous solution (acetonitrile was 80%). The chromatographic column was equilibrated with 96% A liquid. After the sample was injected into the Trap Column (PepMap Neo 5μm C18 300μm X 5 mm, Thermo Scientific), it was subjected to gradient separation by the chromatographic analysis column (μPAC Neo High Throughput column, Thermo Scientific). The liquid phase gradient was set as follows: 0 min-0.1 min, B liquid linear gradient from 4%-6%; 0.1 min-1.1 min, B liquid linear gradient from 6%-12%; 1.1 min-4.3 min, B liquid linear gradient from 12%-22.5%; 4.3 min-6.1 min, B liquid linear gradient from 22.5%-45%; 6.1 min-8 min, B liquid maintained at 99%. After the separation of the peptide segments, Orbitrap Astral mass spectrometer (Thermo Scientific) was used for DIA (data-independent acquisition) mass spectrometry analysis. The analysis time was 8 min, the electrospray voltage was 2.2 kV, the detection mode was positive ion, the parent ion scanning range was 380-980 m / z, the first mass spectrometry resolution was 240000, the AGC target was 500%, the first maximum IT was 3 ms. The second mass spectrometry resolution was 80000, the AGC target was 500%, the second maximum IT was 3 ms, the RF-lens was 40%, the MS2 Activation Type was HCD, the Isolation window was 2 Th, the normalized collision energy was 25%, and the cycle time was 0.6.

[0085] Data retrieval: All mass spectrometry data were combined by software DIA-NN, and database retrieval and protein DIA quantitative analysis of DIA mass spectrometry data were completed.

[0086] Among them, the database is uniprot-Mus musculus

[10090] -87417-20240701.fasta, which is from the website https: / / www.uniprot.org / taxonomy / 10090.

[0087] Example 3: Data analysis and bioinformatics analysis

[0088] The method for evaluating the PTFE-MPs exposure-induced differential expression proteins in the hippocampus region in the embodiments of the present application is as follows:

[0089] (1) Differential expression protein screening: in the significance difference analysis of proteins, the T test (Student t test) combined with the method of change fold (Fold change, FC, the ratio of the average expression values between two groups) is used by default to screen out the significantly differentially expressed proteins (usually P < 0.05, FC ≥ 1.5 or ≤ 1 / 1.5), if there is no repeated sample group, it is not considered p As shown in Figure 4 , compared with the control group, there are 167 up-regulated proteins and 59 down-regulated proteins in the PTFE-MPs exposure group, and a total of 226 significantly differentially expressed proteins. The volcano plot Figure 5 more clearly shows the changes of the differentially expressed proteins.

[0090] (2) Cluster analysis of differentially expressed proteins: cluster analysis is a commonly used exploratory data analysis method, and the purpose is to group and classify data on the basis of similarity. The closer the cluster branches, the higher the expression pattern similarity, and the farther the cluster branches, the lower the expression pattern similarity. The clustering algorithm classifies both the sample and the variable dimensions. The clustering result of the sample can test the expression stability of the target protein in the sample group; the clustering of the target protein, the proteins with similar expression patterns may have similar functions or participate in the same biological pathway, or be in the adjacent regulatory position in the pathway.

[0091] As shown in Figure 6 , the analysis of the first 50 differentially expressed proteins shows that 41 proteins are up-regulated and 9 proteins are down-regulated due to microplastic exposure.

[0092] (3) GO (The Gene Ontology knowledgebase) enrichment analysis: the GO database describes genes and gene products from three aspects (Term): biological process (Biological Process, BP), molecular function (Molecular Function, MF) and cellular component (Cellular Component, CC). These three terms are the first level (level 1) of GO annotation, and each branch will be divided into more specific terms, level 2, level 3, etc. Further screening of statistically significant terms. The enrichment analysis result is represented by p value, less than 0.05 is a significant functional enrichment, and the smaller the value, the more significant the functional enrichment.

[0093] KEGG pathway analysis: KEGG database (Kyoto Encyclopedia of Genes and Genomes) is used to understand the advanced functions and uses of cells, organisms and ecosystems from the molecular level information, especially from the large-scale molecular data sets generated from genome sequencing and other high-throughput experimental techniques. In organisms, proteins do not exercise their functions independently, but different proteins coordinate with each other to complete a series of biochemical reactions to exercise their biological functions. Therefore, KEGG pathway analysis is the most direct and necessary way to more systematically and comprehensively understand the biological processes of cells, the occurrence mechanism of diseases, the mechanism of drug action, etc., which will help us to understand the functions of proteins and the relationships between proteins.

[0094] Differentially expressed protein enrichment bubble chart (as shown in Figure 7 ) and GO enrichment analysis, enrichment analysis from biological processes, molecular functions, and cellular components, as shown in Figure 8 , Figure 9 , Figure 10 In biological processes, differentially expressed proteins are mainly enriched in potassium ion transport, potassium ion transmembrane transport and potassium ion transport regulation; in terms of molecular function, they are mainly enriched in cation antiporter activity and potassium ion antiporter activity; from the cell component, the significantly differentially expressed proteins are enriched in the intrinsic components and constituent parts of the membrane, and the RDNA heterochromatin. The top 20 GO terms of differentially expressed protein enrichment significance are mainly enriched in myocardial cell adrenergic signaling, cardiac muscle contraction, and adhesion linkage. The enrichment analysis of KEGG on the differentially expressed proteins in the mouse hippocampus is shown in Figure 11 and Figure 12 , and the main differentially expressed proteins enriched in the adrenergic signaling in myocardial cells, myocardial contraction, and tight linkage pathway are Myl2, Cacng3, Cacng4, and Atf2.

[0095] The relationship between differentially expressed proteins and pathways is shown in Figure 13 After PTFE-MPs exposure, Myl2, Cacng3, and Cacng4 were significantly up-regulated, and Atf2 was significantly down-regulated, thereby activating the adrenergic signaling in myocardial cells, myocardial contraction, and adhesion linkage pathway, which may further trigger the neuroinflammation, oxidative stress, abnormal secretion of neurotransmitters, and apoptosis of brain tissue cells in mice, causing cognitive impairment in mice.

[0096] In summary, by integrating DIA proteomics, bioinformatics and behavioral analysis, the embodiment of the present application successfully identified that PTFE-MPs exposure can cause significant changes in the hippocampus proteome of mice, which are related to synaptic function and neurodegenerative disease-related pathways, and confirmed the cognitive dysfunction caused by behavior. The present application provides a comprehensive mechanism explanation and effective evaluation method for the neurotoxicity of PTFE-MPs.

[0097] The above embodiments only express several embodiments of the present application, which are described in detail and in detail, but cannot be understood as limiting the scope of the patent range of the present application. It should be noted that for ordinary skilled persons in the art, without departing from the concept of the present application, a number of modifications and improvements can be made, which belong to the protection scope of the present application. Therefore, the protection scope of the patent of the present application should be subject to the appended claims.

Claims

1. A method for assessing the neurotoxicity of microplastics based on DIA mass spectrometry technology, characterized in that, The method comprises the following steps: constructing an animal model by using microplastics to be evaluated and performing a behavior experiment; obtaining hippocampal whole proteins of the animal model and performing enzymolysis to obtain a peptide mixture; performing mass spectrum data acquisition on the peptide mixture by using a data-independent acquisition mode; performing qualitative and quantitative analysis on the mass spectrum data, and screening differential expression proteins; performing bioinformatics analysis on the differential expression proteins; combining the bioinformatics analysis result with the behavior experiment result to evaluate the neurotoxicity of the microplastics; the step of performing mass spectrum data acquisition on the peptide mixture by using the data-independent acquisition mode specifically comprises: performing analysis on part of the peptide mixture by using a data-dependent acquisition mode to obtain retention time, parent ion and fragment ion information of the peptide, so as to construct a general library of the hippocampus; performing data acquisition on all the peptide mixtures by using the data-independent acquisition mode based on the general library of the hippocampus to obtain mass spectrum data; the bioinformatics analysis comprises GO enrichment analysis and KEGG pathway analysis; the GO enrichment analysis enriches functions of the differential expression proteins from three aspects of biological processes, cell components and molecular functions; the KEGG pathway analysis identifies key signal pathways affected by the microplastics by mapping the differential expression proteins into a KEGG database to perform pathway annotation and enrichment analysis; and the differential expression proteins are Myl2, Cacng3, Cacng4 and Atf2.

2. The method for assessing the neurotoxicity of microplastics based on DIA mass spectrometry technology according to claim 1, characterized in that, the behavior experiment is a Morris water maze behavior experiment.

3. The method for assessing the neurotoxicity of microplastics based on DIA mass spectrometry technology according to claim 1, wherein, the enzymolysis method is a filter membrane-assisted protease enzymolysis method.

4. The method for assessing the neurotoxicity of microplastics based on DIA mass spectrometry technology according to claim 1, wherein, the mass spectrum data is liquid chromatography-tandem mass spectrum data.

5. The method for assessing the neurotoxicity of microplastics based on DIA mass spectrometry technology according to claim 1, wherein, the step of performing qualitative and quantitative analysis on the mass spectrum data to screen the differential expression proteins specifically comprises: comparing the mass spectrum data with a previously established spectral library to complete qualitative identification of the peptide and the protein, and to perform relative quantitative analysis to obtain proteomic data; performing statistical analysis on the proteomic data, combining with a differential fold and a significance level to screen out the differential expression proteins.

6. The method for assessing the neurotoxicity of microplastics based on DIA mass spectrometry technology according to claim 1, wherein, the microplastics comprise polytetrafluoroethylene microplastics.

7. A system for assessing the neurotoxicity of microplastics based on DIA mass spectrometry techniques for implementing the method of any one of claims 1-6, characterized in that, The method comprises the following steps: a behavior experiment module for performing a behavior experiment on an animal model constructed by using microplastics to be evaluated; a mass spectrum data acquisition module for performing mass spectrum data acquisition on a peptide mixture by using a data-independent acquisition mode; the peptide mixture is obtained by performing enzymolysis on hippocampal whole proteins of the animal model; a mass spectrum data analysis module for performing qualitative and quantitative analysis on the mass spectrum data to screen differential expression proteins; a bioinformatics analysis module for performing bioinformatics analysis on the differential expression proteins; a neurotoxicity evaluation module for combining a bioinformatics analysis result with a behavior experiment result to evaluate the neurotoxicity of the microplastics.

Images