CN115060557A - Method for analyzing relationship between microbiota-gut-brain axis signals and zebra fish neurobehavioral - Google Patents
Method for analyzing relationship between microbiota-gut-brain axis signals and zebra fish neurobehavioral Download PDFInfo
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Abstract
The invention provides a method for analyzing a relation between a microbiota-gut-brain axis signal and zebra fish neurobehavioral, and relates to the technical field of biological information analysis. The method comprises the steps of constructing a mental disease zebra fish model through antibiotic induction, analyzing microbial community structure change, species composition, intergroup difference significance and species difference of intestinal tissues of the mental disease zebra fish model to obtain intestinal microbial data, and screening metabonomics and lipidomics biomarkers of the brain tissues of the mental disease zebra fish through non-targeted metabonomics and/or non-targeted lipidomics analysis of the brain tissues of the zebra fish; and further analyzing the relationship between the microbiota-intestinal-brain axis signals and the neural behaviors of the zebra fish. The method can efficiently obtain the microbiota information between the mental disease zebra fish model and the normal control and metabonomics and lipidomics information, and provides an accurate and comprehensive analysis idea for the research of intestinal microbiota and neurobehavioral diseases.
Description
Technical Field
The invention relates to the technical field of biological information analysis, in particular to a method for analyzing a relation between a microbiota-gut-brain axis signal and zebra fish neurobehavioral information based on multi-component theory.
Background
The microbiota-Gut-Brain Axis (MGBA) is composed primarily of The Gut microbiota located in The lumen of The intestine, Gut cells (including intestinal cells, Enteroendocrine cells (EEC), goblet cells), and neurons and glial cells in The central nervous system. Gut microbiota utilizes a variety of communication channels to influence brain physiology, cognition and behavior. The most prominent of these approaches include: (1) direct mediation between the brain stem and the gut through the vagus nerve; (2) mediated by metabolites and cytokines produced by members of the gut microbiota; (3) metabolites and cytokines released by immune cells and their activated gut cells. Neurophysiologic and behavioral processes affected by the state of the gut microbiota include neurogenesis, synaptic plasticity, neurotransmitter signaling, neuronal morphology, neuroinflammation, neurodevelopment, and neurochemistry of the hippocampus, amygdala, prefrontal cortex, and hypothalamus. Gut microbiota dysregulation is associated with neurobehavioral disorders such as neurodevelopmental disorders (Autism Spectrum disorders, ASD) and schizophrenia), neurodegenerative disorders (Alzheimer's disease, AD), Parkinson's Disease (PD) and Multiple Sclerosis (MS), and mood disorders (depression and anxiety).
In recent years, more and more research has been directed to associating the microbial population with the structure and function of the nervous system, and to the discovery and elucidation of the role played by metabolites produced and/or induced by microorganisms in the cognitive abilities and psychological effects on the host in the brain. Currently, most of these studies are focused on mammalian models due to mammalian-human relationships. However, microbial-gut-brain axis studies using multigroup technology approaches on simpler neurogenetic model organisms (zebrafish, drosophila melanogaster and caenorhabditis elegans) have also evolved.
The zebra fish has the characteristics of fast in-vitro development, high breeding yield, good optical transparency and the like, and meanwhile, the zebra fish has a series of behaviours similar to human beings, including social interaction, cognition, sleeping, stress, anxiety and the like, so that the zebra fish becomes a main dominant model organism for exploring the interaction mechanism of a microbial population and a host nervous system.
In view of the above, the invention provides a method for analyzing the relationship between microbiota-gut-brain axis signals and zebra fish neurobehavioral relations based on multiple groups of theories.
Disclosure of Invention
The invention aims to provide a method for analyzing the relation between microbiota-gut-brain axis signals and zebra fish neurobehavioral characteristics based on multiple groups of theories. The invention is based on multi-group chemical information for analysis, and particularly establishes a method for analyzing the influence of microbial community-intestine-brain axis signal molecules on the behavior of zebra fish in a multi-layer and multi-angle manner by combining change data of intestinal microbial spectrums of intestinal tissues and non-targeted metabonomics and/or non-targeted lipidomics information of brain tissues.
The technical scheme provided by the invention is as follows:
the invention provides a method for analyzing the relation between microbiota-gut-brain axis signals and zebra fish neurobehavioral characteristics based on multiple groups of theories, which is characterized by comprising the following steps:
(a) constructing a zebra fish model with mental diseases through antibiotic induction;
(b) collecting brain tissues and intestinal tissues of zebra fish;
(c) evaluating the mental disease zebra fish model through histopathological section analysis, transmission electron microscope ultrastructure analysis and nerve disease related gene analysis;
(d) analyzing the microbial community structure change, species composition, inter-group difference significance and species difference of the intestinal tissues of the mental disease zebra fish model to obtain intestinal microbial data;
(e) screening out a metabonomic and/or lipidomic biomarker of the zebra fish brain tissue with mental diseases by carrying out non-targeted metabonomic and/or non-targeted lipidomic analysis on the zebra fish brain tissue;
(f) analyzing the relationship between the microbiota-gut-brain axis signals and the neurobehavioral of zebrafish by the gut microbial data and the metabolomic and/or lipidomic biomarkers.
In the invention, the normal adult zebra fish is subjected to antibiotic induction, so that the zebra fish has behavior characteristics of certain mental disease types, and a zebra fish model for acquiring the mental disease is established.
In the present invention, adult wild-type AB zebrafish of 3 months of age are typically selected for antibiotic induction and exposure.
In one embodiment, in the step (a), the mental disease zebrafish model is constructed by ciprofloxacin induction of adult zebrafish, and the mental disease type of the zebrafish is determined by animal behavior test;
preferably, constructing the mental disease zebra fish model comprises exposing the adult zebra fish to water containing ciprofloxacin at a concentration of 100-1000 μ g/L for 28 days for domestication.
In one embodiment, the type of mental illness of said zebrafish is determined by animal behavioral testing. For example, the behaviors of zebra fish caused by anxiety, such as thigmotaxis (preference of fish tank edge/corner), immobility or motion instability (sudden rapid swimming accompanied by high-speed continuous turning), reduction of swimming distance and the like, can be used for measuring the anxiety degree of the zebra fish and evaluating the establishment of an anxiety disease model.
Further, one or more characteristics selected from the group consisting of: increased anxiety-like behavior, increased degree of anxiety, increased depressive-like behavior, increased degree of depression, and the like. The mental disease model may include one or more mental diseases, such as anxiety or depression or a combination of both.
In one embodiment, the adult zebrafish are cultured under conditions of water temperature of 27.5 ± 2 ℃, 14h/10h of light and dark cycle;
further, more than 50% v/v of the exposure fluid was replaced every 24 hours during the exposure period, and all exposure fluid was replaced every 14 days.
In a specific embodiment, female zebrafish are first kept in clear water for 7 days, then exposed to high and low concentrations of ciprofloxacin, and a control group is established. Specifically, the low concentration may be 100. mu.g/L, and the high concentration may be 1000. mu.g/L. And during the exposure period, 50% of the exposure liquid is replaced every 24 hours, 200 mu L of the exposure liquid is collected to measure the actual exposure concentration, all the exposure liquid is replaced every 14 days, female fishes in the exposure liquid and male fishes bred in clear water are placed in clear water to lay eggs once, after 28 days of exposure, the female fishes and the male fishes are dissected into fishes, brain tissues and intestinal tissues are collected, and the fishes are immediately placed at-80 ℃ for freezing storage after being treated by liquid nitrogen.
In one embodiment, in said step (c), said histopathological section analysis comprises HE staining and Nissl staining of brain tissue of zebrafish to analyze the number, morphology and health status of neurons and glial cells in brain tissue, and HE staining of intestinal tissue to analyze the integrity of intestinal villi and the number of intestinal epithelial cells in intestinal tissue;
the transmission electron microscope ultrastructure analysis comprises observation of subcellular structures of neurons and analysis of health states of double-layer nuclear membranes, synapses, mitochondria and myelin sheaths of the neurons; preferably, observation is performed under an electron microscope field of view with a magnification of 10000, 20000, and 30000;
the neurological disease-related gene analysis includes analyzing expression levels of: a gene ache associated with acetylcholinesterase activity; genes associated with dopamine levels Th1, dat, Nr4a2b, bdnf; serotonin receptor-associated genes Th2, Htr1aa, Htr1ab, Htr5a, Htr1b and Htr2 a; genes Syn2a, mbp, shha, alpha 1-tubulin, gfap, Elavl3, Gap43, nestin, manf related to the development of the central nervous system of zebrafish; the gene chrn alpha 7 related to nicotinic cholinergic receptor alpha 7.
In one embodiment, the expression level of the gene is analyzed by real-time fluorescent quantitative PCR technique.
In one embodiment, in step (d), the alteration in the intestinal microflora structure is analyzed by 16s amplicon sequencing of zebrafish intestinal tissue; species composition information is obtained through single sample Alpha diversity analysis and different sample Beta diversity analysis; analyzing whether the community structure difference among groups is obvious or not by a Weighted _ uniform or Unweighted _ uniform distance in an Adonis or Anosim analysis method; biomarker species with significant differences between groups at the phylum or genus classification level were obtained by LEfSe and T-test tests.
In one embodiment, more than 5 zebra fish intestinal tissue samples are used as a sample for analysis, and the total weight of the sample is about 100-120 mg.
In one embodiment, the 16s amplicon is amplified by genomic DNA extraction and PCR on the sample, and the purified PCR product is then library-constructed and subjected to machine sequencing analysis.
In one embodiment, the obtained microbiological information is subjected to species composition analysis, including primarily single sample Alpha diversity analysis and different sample Beta diversity analysis. The abundance and diversity of species in a sample are reflected by Alpha diversity index, and the Beta diversity index reflects the difference degree of microbial community structures between samples by combining a dimensionality reduction map such as multivariate statistical method Principal Component Analysis (PCA), Principal coordinate Analysis (PCoA) or Non-quantitative Multi-Dimensional calibration (NMDS).
In one embodiment, the colony structure differences between groups are analyzed by Weighted _ uniform or Unweighted _ uniform distance in Adonis or Anosim analysis methods for significance.
In one embodiment, the obtained microbiological information is analyzed for species variability, consisting essentially of LefSe (LDA Effect size) and T-test tests to identify Biomarker species with significant differences between groups at the phylogenetic or genus classification level (p value < 0.05).
Furthermore, in some embodiments, the invention further comprises functional prediction of the obtained 16S sequencing data of the microorganism based on the KEGG, KO database.
In one embodiment, step (e) comprises performing chromatographic mass spectrometry after pretreating the zebra fish brain tissue.
In one embodiment, more than 5 zebra fish brain tissue samples are used as a sample for analysis, and the total weight of the sample is about 40-50 mg.
In one embodiment, the zebra fish brain tissue is added with a mixed solution of methanol and water, the mixture is subjected to ultrasonic crushing and centrifugation, the supernatant and the bottom solid are collected, the supernatant is subjected to nitrogen drying and methanol and water redissolving, the supernatant is subjected to centrifugation again, the supernatant is collected for non-targeted metabonomic chromatography mass spectrometry, and a Q-exact Orbitrap mass spectrometer is used for collecting data.
In one embodiment, a dichloromethane/methanol mixture is added to the bottom solid, ultrasonication and centrifugation are performed, the supernatant is collected, the supernatant is dried by nitrogen and redissolved by methanol and water, centrifugation is performed again, the supernatant is collected for non-targeted lipidomics chromatography mass spectrometry, and data are collected by using a SYNAPT XS high resolution mass spectrometer.
In one embodiment, the volume ratio of methanol to water in the mixed solution of methanol and water is 1: 1.
In one embodiment, the conditions for ultrasonication are 5s for sonication, 10s apart, and 120 cycles.
In one embodiment, the conditions of centrifugation after ultrasonication are 15300rpm at 4 ℃ for 10 min.
In one embodiment, the centrifugation after reconstitution is performed at 10000rpm at normal temperature for 10 min.
In one embodiment, the chromatographic conditions for non-targeted metabolomic chromatography mass spectrometry are gradient elution with Waters Xbridge c182.1x100mm, 3.5 μm column, acetonitrile-water (5: 5, V/V) +10mM ammonium acetate as mobile phase a and acetonitrile-water (95: 5, V/V) +10mM ammonium acetate as mobile phase B. The flow rate is 200 muL/min; the column temperature was 40 ℃, the sample injection tray temperature was 4 ℃, and the sample injection amount was 5 μ L.
In one embodiment, the chromatographic conditions for non-targeted lipidomic chromatography mass spectrometry are gradient elution with ACQUITY UPLC CSH c182.1x 100mm,1.7 μm column, acetonitrile-water (6: 4, V/V) +10mM ammonium acetate as mobile phase a and isopropanol-acetonitrile (9: 1, V/V) +10mM ammonium acetate as mobile phase B. The flow rate is 400 muL/min; the column temperature was 55 ℃ and the amount of sample was 2. mu.L.
In one embodiment, the mass spectrometry conditions of the non-targeted metabolomics chromatography mass spectrometry are that ESI is used as an ion source, Full scanning is carried out in a positive and negative ion scanning mode, the spraying voltage is 4.00KV, the capillary temperature is 320 ℃, the scanning mode is Full MS (70000Resolution) -dd/MS2(17500 Resolution; collision energy is 30eV), and the scanning range is 50-1200 m/z.
In one embodiment, the mass spectrometry conditions for non-targeted lipidomic chromatography mass spectrometry are mass spectrometry with ion Mobility TOF (Mobility TOF), Resolution (Resolution), MS E In order to adopt an acquisition mode and ESI as an ion source, full scanning is carried out in a positive ion scanning mode and a negative ion scanning mode, wherein the spraying voltage in the positive ion scanning mode and the spraying voltage in the negative ion scanning mode are respectively 2.0KV and 1.0KV, the cone voltage is 30V, the degassing voltage is 550 ℃, the desolventizing gas flow is 900L/Hr, and the scanning range of the ion source temperature of 120 ℃ is 50-1200 m/z.
Compared with the traditional high-resolution mass spectrometer for analyzing the non-targeted lipidomics workflow, the SYNAPT XS high-resolution mass spectrum supports the ion mobility technology, in the ion mobility experiment, the ion mobility experiment allows the measurement of the ion collision cross-sectional area (CCS) related to the chemical structure and three-dimensional conformation of ions besides accurate ion mass, increases the reliability of the identification result of the non-targeted lipidomics lipid, and is beneficial to determining the name of the ions or researching the structure of the ions, thereby reducing the interference and improving the signal to noise ratio (S: N).
In the invention, the method also comprises the step of mixing the supernatants of the analysis samples of the non-targeted metabonomics and the non-targeted lipid respectively in equal quantity for preparing the quality control sample.
In one embodiment, the method further comprises the steps of carrying out peak alignment, peak extraction, noise reduction and normalization on the collected data by using Compound Discover and Progenetics QI software, and screening the differential metabolites after obtaining a raw data matrix. The method comprises the steps of respectively importing the obtained raw data files of the non-targeted metabonomics and the non-targeted lipidomics into Compound discover3.3 software and Progenetics QI software to carry out data preprocessing such as peak alignment, peak extraction, noise reduction, normalization processing and the like, identifying a Compound, carrying out multivariate data statistical analysis and screening differential metabolites.
In one embodiment, the method further comprises performing a metabolic pathway enrichment analysis on the obtained differential metabolites. The metabolic pathway enrichment analysis is mainly based on the built-in database Metabolika of Compound discover 3.0 and MetabioAnalyst online software of KEGG metabolic pathway database to analyze and determine potential biomarkers and related metabolic pathways.
Compared with the prior art, the technical scheme of the invention has the beneficial effects that:
the invention provides a method for analyzing the relationship between intestinal microbiota and neurobehavioral diseases based on multigroup chemical integration, which is a brand-new analysis and research method combining histopathology, electron microscope scanning, real-time fluorescence quantitative PCR technology, 16s amplicon sequencing, non-targeted metabonomics and non-targeted lipidomics;
most of the research experiment designs in the prior art are unreasonable, the reliability of the generated results is low, and the invention provides an accurate and comprehensive analysis idea for the research of intestinal microbiota and neurobehavioral diseases; in the prior art, most researches on behavioral abnormalities caused by changes of single strains in intestinal microorganisms of zebra fish can analyze the relationship between overall signal changes of intestinal microbial spectrums (the composition and changes of the whole microbial community) and neurobehaviors;
the invention relates to a more comprehensive analysis method for researching the influence of the bacterial intestinal microbiota on the microbe-intestinal tract-brain axis signal and the Central Nervous System (CNS) diseases, which can provide a theoretical basis for the microbe treatment strategy of the neurobehavioral diseases.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and other drawings can be obtained by those skilled in the art without creative efforts.
FIG. 1 shows the results of a novel water jar test provided in example 1 of the present invention;
FIG. 2 is a photograph of pathological sections stained by HE of brain tissues of a control group and a high concentration model group in example 1 of the present invention;
FIG. 3 is a Nissl-stained pathological section of brain tissue of a control group and a high concentration model group in example 1 of the present invention;
FIG. 4 is a view of HE-stained pathological sections of intestinal tissues of a control group and a high concentration model group in example 1 of the present invention;
FIG. 5 is a transmission electron microscopy micrograph of brain tissue of a control group and a high concentration model group in example 1 of the present invention;
FIG. 6 is a heat map of the expression of genes associated with mental disorders in a control group, a low-concentration model group and a high-concentration model group in example 1 of the present invention;
FIG. 7 is a graph showing the relative abundance of microbial communities at the phylum taxonomic level in the control group, the low-concentration model group and the high-concentration model group in example 1 of the present invention;
FIG. 8 is a total ion flow graph of the control brain tissue non-targeted lipidomics of example 1 of the present invention;
FIG. 9 is a brain tissue non-targeted metabolomics Principal Component Analysis (PCA) score plot of example 1 of the present invention.
FIG. 10 is a diagram showing analysis of metabolic pathways of non-targeted lipidomics in brain tissue in example 1 of the present invention.
Detailed Description
The technical solutions of the present invention will be described clearly and completely with reference to the following embodiments, and it should be understood that the described embodiments are some, but not all, embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Examples
1. Method for constructing zebra fish model for mental diseases
Selecting 3-month-old adult wild AB zebra fish, and performing antibiotic exposure under the culture conditions that the culture water temperature is 27.5 +/-2 ℃ and the illumination and dark cycle is 14h/10 h.
Before a formal exposure experiment is carried out, female zebra fish to be exposed is placed in clear water for domestication for 7 days, a control group, a low-concentration (100 mu g/L) and high-concentration (1000 mu g/L) ciprofloxacin exposure group is arranged, 50% of exposure liquid is changed every 24 hours during exposure, 200 mu L of exposure liquid is collected to measure the actual exposure concentration, all exposure liquid is changed every 7 days, female fish in the exposure liquid and male fish fed in the clear water are placed in the clear water to lay eggs once, after 28 days of exposure, the female zebra fish and the male fish are dissected to collect brain tissues and intestinal tissues, and after 5 minutes of liquid nitrogen treatment, the female zebra fish are immediately placed at-80 ℃ for freezing storage.
A novel water tank experiment is adopted for evaluating the influence of external factors on the behavioral activities of the zebra fish. The experimental device is a circular glass container with the diameter of 12.5cm, the glass container is equally divided into a central area and an edge area through a concentric circle division method, generally speaking, the preference of zebra fish to the outer edge of the space is related to anxiety behavior, and the reduction of exploration behavior is related to the lack of interest of depression model. The swimming behavior of the zebra fish within 5min is recorded, and the acquired zebra fish track graph and the hotspot graph are shown in figure 1. The results show that the zebrafish in the exposed group exhibited depressive and anxiety behavior, as reflected by a reduced trajectory of movement and preference for the outer margins of space, compared to the control group.
2. Evaluation of zebra fish model for mental diseases through histopathological section, transmission electron microscope ultrastructure and gene analysis related to neurological diseases
The histopathological section analysis method mainly comprises the steps of analyzing the number, the morphology and the health state of neurons and glial cells in brain tissue after HE staining and Nissl staining of the brain tissue as shown in figures 2 and 3. The analysis result shows that the number of the neurons and the glial cells in the control group is reduced, and the shape is changed. Meanwhile, the integrity of intestinal villi and the number of intestinal epithelial cells in the intestinal tissue after HE staining the intestinal tissue are analyzed as shown in fig. 4. The results of the analysis indicated that the integrity of the intestinal villi was lost and the intestinal goblet cells were reduced.
The content of the transmission electron microscope ultrastructure analysis mainly comprises observing the subcellular structure of the neuron under an electron microscope visual field with the magnification of 10000, 20000 and 30000, and analyzing the health state of the double nuclear membrane, myelinated nerve fiber, mitochondria and myelin sheath of the neuron as shown in figure 5.
The 22 related genes for evaluating the mental disease zebra fish model specifically comprise: a gene ache associated with acetylcholinesterase activity; genes associated with dopamine levels Th1, dat, Nr4a2b, bdnf; serotonin receptor-associated genes Th2, Htr1aa, Htr1ab, Htr5a, Htr1b and Htr2 a; genes Syn2a, mbp, shha, alpha 1-tubulin, gfap, Elavl3, Gap43, nestin, manf associated with the development of the Central Nervous System (CNS) of zebrafish; the gene chrn alpha 7 related to the nicotinic cholinergic receptor alpha 7 is shown in figure 6, compared with a control group, the dopamine neurotransmitter and the receptor expression thereof are both remarkably reduced (P <0.01), the acetylcholine, the serotonin and the gamma-aminobutyric acid neurotransmitter and the receptor expression thereof are all remarkably up-regulated (P <0.05), and the gene expression related to the neurodevelopment is all remarkably reduced.
Method for analyzing intestinal microflora structure of model group by 3.16s amplicon sequencing
Firstly, extracting genome DNA (deoxyribonucleic acid) and performing PCR (polymerase chain reaction) amplification on zebra fish intestinal samples (5 intestinal tissue samples are one sample, and the amount of the sample is about 100-120 mg), and then constructing a library of PCR products subjected to sample mixing and purification treatment and performing machine sequencing analysis.
The main content and method of the intestinal flora data analysis are as follows: first, species composition analysis mainly included single sample Alpha diversity analysis and different sample Beta diversity analysis. The abundance and diversity of species in a sample are reflected by the Alpha diversity index, the Beta diversity index is combined with Principal coordinate Analysis (PCoA) of a multivariate statistical method to reflect the difference degree of microbial community structures among samples as shown in figure 7, and compared with a control group, the abundance and diversity of the exposed group microbial community are obviously reduced, which indicates that the resistance stability of an organism is reduced.
In addition, whether the colony structure difference among groups is significant was analyzed by Unweighted _ unifrac distance in the Anosim analysis method. Meanwhile, species difference analysis found out Biomarker species (p value <0.05) having significant differences between groups at the phylum or genus classification level mainly by lefse (lda Effect size) and T-test, and those having significant differences between groups at the genus classification level mainly were acetobacter (cetobacillus), Plesiomonas (Plesiomonas), Lactococcus (Lactococcus), and the like.
4. Method for pretreating zebra fish brain tissue sample
Thawing brain tissue samples (5 brain tissue samples are one sample, about 40-50 mg), adding 1.5mL of methanol/water (1:1, V/V) mixed extract pre-cooled, performing ultrasonic disruption on the sample mixture (working conditions are 5s of ultrasound, interval is 10s, circulation is performed for 120 times), centrifuging at 15300rpm and 4 ℃ for 10min, and collecting the centrifuged supernatant and the centrifuged bottom solid. And (3) blowing the centrifuged supernatant to be dry on a nitrogen blowing instrument at 45 ℃, re-dissolving the supernatant in 120 mu L of methanol/water (1:1, V/V) re-solution, whirling the solution until the supernatant is completely re-dissolved, centrifuging the solution at 10000rpm at normal temperature for 10min, and sucking the supernatant and putting the supernatant into a Q-active Orbitrap mass spectrometer for non-targeted metabonomics data acquisition.
Adding 1.6mL of pre-cooled dichloromethane/methanol (3:1, V/V) mixed extract into the collected centrifuged bottom solid, carrying out ultrasonic disruption on the sample mixture (the working condition is ultrasonic for 5s, the interval is 10s, the circulation is carried out for 120 times), placing the sample mixture into 15300rpm, centrifuging the sample mixture for 10min at 4 ℃, collecting supernatant, carrying out nitrogen blowing on the supernatant to dryness in a 45 ℃ nitrogen blowing instrument, redissolving the supernatant in 120 mu L of methanol/water (1:1, V/V) composite solution, carrying out vortex to complete redissolution, placing the supernatant into 10000rpm, centrifuging the supernatant for 10min at normal temperature, and sucking the supernatant and placing the supernatant into a SYNAPT XS high-resolution mass spectrometer for non-targeted lipidomics data acquisition as shown in figure 7.
And respectively and equivalently mixing the supernatants of the analysis samples of the non-target metabonomics and the non-target lipid for preparing the quality control sample.
5. Zebra fish brain tissue sample collection method
When a Q-exact Orbitrap mass spectrometer collects non-targeted metabonomics data, ESI is taken as an ion source in a mass spectrum condition, full scanning is carried out in a positive and negative ion scanning mode, the scanning range is 50-1200m/z, mobile phase A is acetonitrile-water (5: 5, V/V) +10mM ammonium acetate and mobile phase B is acetonitrile-water (95: 5, V/V) +10mM ammonium acetate in a liquid phase condition, gradient elution is carried out, and the sample injection amount is 5 mu L;
when non-targeted lipidomics data are acquired on a SYNAPT XS high-Resolution mass spectrometer, the mass spectrum condition takes an ion Mobility flight mass spectrum (Mobility TOF) and a Resolution (Resolution) as an acquisition mode, ESI as an ion source, full scanning is carried out in a positive and negative ion scanning mode, the scanning range is 50-1200m/z, the liquid phase condition carries out gradient elution by taking mobile phase A as acetonitrile-water (6: 4, V/V) +10mM ammonium acetate and mobile phase B as isopropanol-acetonitrile (9: 1, V/V) +10mM ammonium acetate, and the sample introduction amount is 2 muL.
6. Non-targeted metabonomics and lipidomics data analysis method
Analyzing and processing the acquired non-targeted metabonomics and lipidomics data, and specifically, importing the acquired non-targeted metabonomics and non-targeted lipidomics original raw data files into Compound Discover3.3 software and Progenetics QI software for data preprocessing such as peak alignment, peak extraction, noise reduction, normalization and the like, performing metabolite identification from mz cluster with database and HMDB database by Compound Discover3.3 software, identifying lipid compounds according to waters QI with lipid library and Lipidmaps matching, and the identified data matrix is imported into MetabioAnalyst software for PCA principal component analysis as shown in FIG. 9, the differential metabolite is screened by taking (P <0.05 and VIP)1 as a screening condition, the enrichment analysis of the metabolic pathway is mainly based on Metabioanalyst online software KEGG metabolic pathway database and is shown in figure 10, and the result shows that the main enrichment pathway of the differential metabolite is amino acid metabolism and fatty acid metabolism. The main pathways for differential lipid compound enrichment are sphingomyelin metabolism and glycerophospholipid metabolism.
Finally, it should be noted that: the above embodiments are only used to illustrate the technical solution of the present invention, and not to limit the same; while the invention has been described in detail and with reference to the foregoing embodiments, it will be understood by those skilled in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some or all of the technical features may be equivalently replaced; and the modifications or the substitutions do not make the essence of the corresponding technical solutions depart from the scope of the technical solutions of the embodiments of the present invention.
Claims (10)
1. A method for analyzing the relationship between microbiota-gut-brain axis signals and zebrafish neurobehavioral characteristics based on multiple groups of theories, comprising:
(a) constructing a zebra fish model with mental diseases through antibiotic induction;
(b) collecting brain tissue and intestinal tract tissue of zebra fish;
(c) evaluating the mental disease zebra fish model through histopathological section analysis, transmission electron microscope ultrastructure analysis and nerve disease related gene analysis;
(d) analyzing the microbial community structure change, species composition, inter-group difference significance and species difference of the intestinal tissues of the mental disease zebra fish model to obtain intestinal microbial data;
(e) screening out a metabonomic and/or lipidomic biomarker of the zebra fish brain tissue with mental diseases by carrying out non-targeted metabonomic and/or non-targeted lipidomic analysis on the zebra fish brain tissue;
(f) analyzing the relationship between the microbiota-gut-brain axis signals and the neurobehavioral of zebrafish by the gut microbial data and the metabolomic and/or lipidomic biomarkers.
2. The method according to claim 1, wherein in the step (a), the mental disease zebrafish model is constructed by ciprofloxacin induction of adult zebrafish, and the mental disease type of the zebrafish is determined by animal behavior test;
preferably, constructing the mental disease zebra fish model comprises exposing the adult zebra fish to water containing ciprofloxacin to the concentration of 100-1000 mug/L for over 28 days.
3. The method according to claim 2, wherein the adult zebrafish is cultured under conditions of water temperature of 27.5 ± 2 ℃, 14h/10h of light and dark cycle;
further, more than 50% of the exposure fluid volume was replaced every 24 hours during the exposure period, and all exposure fluid was replaced every 7 days.
4. The method according to claim 1, wherein in the step (c), the histopathological section analysis comprises HE staining and Nissl staining of the brain tissue of zebrafish to analyze the number, morphology and health status of neurons and glial cells in the brain tissue, and HE staining of the intestinal tissue to analyze the integrity of intestinal villi and the number of intestinal epithelial cells in the intestinal tissue;
the transmission electron microscope ultrastructure analysis comprises observation of subcellular structures of neurons and analysis of health states of double-layer nuclear membranes, synapses, mitochondria and myelin sheaths of the neurons;
the neurological disease-related gene analysis includes analyzing expression levels of: a gene ache associated with acetylcholinesterase activity; genes associated with dopamine levels Th1, dat, Nr4a2b, bdnf; serotonin receptor-associated genes Th2, Htr1aa, Htr1ab, Htr5a, Htr1b and Htr2 a; genes Syn2a, mbp, shha, alpha 1-tubulin, gfap, Elavl3, Gap43, nestin, manf related to the development of the central nervous system of zebrafish; the gene chrn alpha 7 related to nicotinic cholinergic receptor alpha 7.
5. The method according to claim 1, wherein in step (d), the change in the intestinal microflora structure is analyzed by 16s amplicon sequencing of zebrafish intestinal tissue; species composition information is obtained through single sample Alpha diversity analysis and different sample Beta diversity analysis; analyzing whether the community structure difference among groups is obvious or not by a Weighted _ uniform or Unweighted _ uniform distance in an Adonis or Anosim analysis method; biomarker species with significant differences between groups at the phylum or genus classification level were obtained by LEfSe and T-test tests.
6. The method of claim 1, wherein step (e) comprises performing chromatographic mass spectrometry after pretreating the zebrafish brain tissue.
7. The method of claim 6, wherein the zebra fish brain tissue is added with a mixture of methanol and water, ultrasonically crushed and centrifuged, the supernatant and bottom solids are collected, the supernatant is dried by nitrogen, and re-dissolved by methanol and water, then centrifuged again, the supernatant is collected for non-targeted metabonomic mass spectrometry, and a Q-active Orbitrap mass spectrometer is used for data acquisition.
8. The method of claim 7, wherein the bottom solids are added with a dichloromethane/methanol mixture, sonicated and centrifuged, the supernatant is collected, the supernatant is dried with nitrogen, reconstituted with methanol and water, centrifuged again, the supernatant is collected for non-targeted lipidomic mass spectrometry, and data are collected using a SYNAPT XS high resolution mass spectrometer.
9. The method according to claim 7 or 8, wherein the method further comprises performing peak alignment, peak extraction, noise reduction and normalization on the collected data by using Compound discovery and Progenetics QI software, and screening the differential metabolites after obtaining the original data matrix.
10. The method of claim 9, further comprising performing a metabolic pathway enrichment analysis on the obtained differential metabolites.
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| CN116908159A (en) * | 2023-08-23 | 2023-10-20 | 中国农业科学院农业质量标准与检测技术研究所 | Method for evaluating neuroendocrine influence of chemical substances on zebra fish |
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