CN112505207A - Biological metabonomics analysis method for screening antioxidant active substances - Google Patents
Biological metabonomics analysis method for screening antioxidant active substances Download PDFInfo
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Abstract
The invention discloses a biometabonomic analysis method for screening antioxidant active substances, and belongs to the technical field of metabonomic analysis. Metabolite detection analysis was performed on caenorhabditis elegans samples by using GC-TOF/MS techniques. ChromaTOF software and MS DIAL software perform data conversion, calibration of data baselines, peak alignment, identification, peak area calculation, etc., and normalize peak areas. And performing multivariate statistical analysis on five groups of caenorhabditis elegans samples of a normal control group, a model group and 3 anthocyanin pretreatment groups, and screening biological metabolites with obvious differences. Through screening and investigation, 15, 8, 9 and 14 different metabolites with an antioxidation mechanism are respectively obtained from the model group and the 3 groups of anthocyanin pretreatment groups, recognition and high-throughput analysis of the antioxidation mechanism are realized by utilizing callback changes of abundance of the different metabolites, and a metabolite path is visualized.
Description
Technical Field
The invention relates to a biometabomic analysis method for screening antioxidant active substances, belonging to the technical field of metabonomic analysis.
Background
Anthocyanins are natural pigments in flavonoids, and are widely applied to the fields of foods, cosmetics, biomedicines and the like. The plant has 6 common anthocyanins, and the blueberry has 5 anthocyanins including cyanidin, malvidin, petunidin, paeoniflorin, and delphinidin. Anthocyanins are also common ingredients in human diet, and have various functional effects such as antioxidation, anti-aging, anti-inflammation and the like, so that the anthocyanins are widely applied to the fields of food and medical treatment. Numerous research results indicate that the antioxidant activity of anthocyanins is related to their chemical structure and even to the glycosidic form. However, the conventional studies on the antioxidant effect of anthocyanins are mostly based on the results of in vitro evaluation methods. Due to the complexity of the whole organism, the in vitro results do not directly reflect the in vivo effects of anthocyanins and do not provide direct guidance. Therefore, there is a need to establish a platform or biological model that can effectively assess the function of active compounds, providing true efficacy of antioxidants in vivo.
The traditional in vivo antioxidant evaluation usually takes a mouse or a rat as a model, has long test period, high cost and large individual difference influence, and is not suitable for batch preliminary screening of antioxidant active compounds. In patent application CN201710381294, SD rat is used as animal model, ellagic acid is used as antioxidant, and the lavage is continued for 8 weeks, and weekly urine sample is taken for metabolite detection by liquid chromatography mass spectrometry. The method provides a new idea based on the biological metabolism level for drug screening and evaluation. However, the rat is used as a model, large errors are easy to occur due to individual differences, the continuous gavage period is as long as 8 weeks, the test period is long, the drug dosage required to be consumed is large, the overall investment cost is high, and the high-throughput drug activity preliminary screening is not suitable. In addition, the sample is rat urine, and the analysis level of metabolites of the rat urine is difficult to explain the overall biological effect of the drug in the body; although the metabolites for liquid quality detection are abundant, the corresponding metabolite library still needs to be perfected.
Disclosure of Invention
In order to solve the technical problems of high cost, long period, poor systematicness and the like existing in screening of antioxidant active compounds and evaluation of action mechanisms of mammals, the invention provides a method for evaluating the antioxidant effect of active compounds by taking caenorhabditis elegans as an antioxidant model. The caenorhabditis elegans is easy to grow in a laboratory, low in test cost, short in life cycle, small in size, suitable for large-scale and high-flux drug screening, has a clear cell map, and is an ideal model for resisting aging, oxidation and neurodegenerative diseases. Therefore, an antioxidant and anti-aging evaluation model can be established by using caenorhabditis elegans to solve the defects of the mammal test. In addition, many mammals have stress responses preserved in nematode, and show 60% -80% gene homology with human, which has high predictive value for mammalian results. The antioxidant signaling network in nematodes is well understood, which helps to utilize nematodes as a model organism for antioxidant evaluation.
The first object of the present invention is to provide a biometabomic analysis method for screening antioxidant active substances, which uses caenorhabditis elegans as an antioxidant animal model, comprising the steps of:
(1) grouping experiments: the normal control group, the model group and the 3 anthocyanin pretreatment groups are divided into 5 groups;
(2) c, caenorhabditis elegans culture: plating the wild type caenorhabditis elegans with Escherichia coli, synchronizing egg collection in the egg laying period, and eluting with buffer solution when the plate is cultured to L2 stage, collecting and counting the density of caenorhabditis elegans;
(3) and (3) induction treatment: uniformly adding caenorhabditis elegans of L2 stage into a 6-hole plate according to a certain density, simultaneously providing OP50 food, respectively adding 3 kinds of anthocyanin into an anthocyanin pretreatment group, adding a solvent with the same volume into a model group and a control group for incubation, then adding an oxidative stress inducer into the model group and the anthocyanin pretreatment group, and continuing incubation;
(4) collecting samples: collecting the polypide sample into a centrifuge tube for further processing after the step (3) is finished;
(5) sample preparation: extracting, enriching and derivatizing the collected sample, and then waiting for machine analysis;
(6) metabolite detection assay: detecting by GC-TOF/MS to obtain a metabolic spectrum, and identifying metabolites and screening differential metabolites by adopting metabonomics related software and a statistical method;
(7) metabolic pathway analysis: and constructing a corresponding metabolic signal path and analyzing by adopting a metabonomics related database and a software program.
In one embodiment of the present invention, the 3 anthocyanins in step (1) and step (3) are cyanidin, delphinidin, and malvidin-3-arabinoside, respectively.
In one embodiment of the present invention, the model group in step (1) and the oxidative stress inducing agent in step (2) are each a paraquat solution with a molar concentration of 0.2-0.9 mM.
In one embodiment of the present invention, the agar plate in step (2) is a caenorhabditis elegans culture-dedicated NGM plate; the buffer solution is M9 phosphate buffer solution,
in one embodiment of the present invention, the density of the insect body used in the experiment in step (2) and step (3) is 2000-3000 pieces/mL.
In one embodiment of the present invention, 1mL of solution containing nematodes is added to each well in step (3), and the final volume of each well is 2.0 mL; the concentration of OP50 provided was 200 mg/mL. The solvent is sterile water.
In one embodiment of the present invention, the incubation time after adding anthocyanin in step (3) is 36-72h, and the incubation time after adding inducer is 12-36 h.
In one embodiment of the invention, during the process of collecting the larvae in the step (4), the larvae are washed 3 times with M9 buffer, OP50 is washed off as much as possible, and the C.elegans is quenched with a pre-cooled aqueous solution of methanol at a volume ratio of 3:2 at-20 ℃.
In one embodiment of the invention, the extraction in the step (5) is an ultrasonic-assisted tissue trituration mode, the extraction solvent is an aqueous solution of acetonitrile to isopropanol with a volume ratio of 3:3:2 precooled at-20 ℃, and the extraction process is a low-temperature environment; centrifuging at 12000 r/min for 2min, collecting supernatant, and repeatedly extracting for 3 times. And carrying out vacuum freeze-drying and concentration on the extracting solution, then carrying out derivatization treatment, and transferring the sample to a chromatographic sample injection vial for computer analysis after derivatization.
In one embodiment of the present invention, the GC-TOF/MS conditions in step (6) are: DB-5 chromatographic column (30m × 250 μm,0.25 μm), helium as carrier gas, flow rate of column passing 20mL/min, and sample introduction volume of 1.0 μ L; the temperatures of the sample inlet, the ion source interface and the ion source are respectively 280 ℃, 280 ℃ and 250 ℃; temperature programming conditions: the initial column temperature is 70 deg.C and maintained for 1min, and then the temperature is raised to 280 deg.C at 6 deg.C/min and maintained for 5 min. The mass spectrum scanning range is 50-600m/z, the scanning speed is 20 times/s, and the solvent delay time is set to be 6 min.
In an embodiment of the present invention, the specific method for processing mass spectrum data in step (6) is: data conversion, peak extraction, data baseline calibration, peak alignment, deconvolution, metabolite identification, peak area calculation, etc. are performed using ChromaTOF software and MS DIAL software, and peak areas are normalized. The peak identification parameters are set as: the number of scanning times of each peak is 20, the minimum peak height is 10000 amplitudes, and the background peak intensity of the mass spectrum for deconvolution is 5000 amplitudes; the metabolite identification setting parameters are as follows: the retention time error was 0.5min, the m/z error was 0.5Da, and the retention time error for mass spectral similarity greater than 70% peak alignment was set to 0.075 min. The peak area of each sample metabolite was normalized using a SERRF normalization method based on Quality Control (QC) samples.
In one embodiment of the present invention, the specific method for multivariate statistical analysis and differential metabolite screening in step (6) comprises: the normalized data obtained above were subjected to Principal Component Analysis (PCA) with unsupervised pattern recognition, partial least squares (PLS-DA) with supervised pattern recognition and discriminant analysis (OPLS-DA) with orthogonal partial least squares by running R software, and the metabolite differences among the groups of samples were compared by means of a score plot to evaluate the model quality. Further, the t-test results (p-value <0.05) were used as candidate variables for differential metabolites, i.e. biomarkers, according to the significance projection parameters (VIP >1.0) obtained from the OPLS-DA model.
In one embodiment of the present invention, the specific method for constructing and analyzing the metabolic pathway described in step (7) is as follows: and searching and matching the normalized data by adopting a PubChem and KEGG database baseline. Then, the converted numerical value (FC), the t-test result, the KEGG code and the metabolite name are integrated, and the cytoscape3.7.2 software is used for visualizing the metabolic pathway and drawing a metabolic signal network map. Further, the differential metabolites are mainly distributed in the TCA cycle, energy metabolism, amino acid metabolism, lipid metabolism, and neurotransmitter synthesis. Anthocyanin pre-protection can reverse metabolic disorders caused by paraquat-induced oxidative stress to different degrees.
The invention has the beneficial effects that:
the invention provides a method for evaluating the antioxidant activity of anthocyanin in vivo by taking caenorhabditis elegans as a model, which can be used for researching the influence of oxidative stress change in vivo on the physiological and biochemical metabolic processes of organisms. The caenorhabditis elegans is utilized to establish an antioxidant and anti-aging evaluation model, so that the defects that mammals such as rats, mice and the like are used as models, the test period is long, the cost is high, local sampling can be realized only due to large volume, the sample preparation is complex, and high-throughput screening and activity evaluation of antioxidant compounds are difficult to carry out are overcome, and screening and evaluation of potential antioxidant active compounds from the biological whole metabolic level are truly realized. The nematode model biological model is stable and repeatable, and can be used as an in vivo active oxygen level imbalance animal model for mechanism research of metabolic disorder caused by in vivo oxidative stress imbalance and screening of antioxidant active compounds.
The invention is based on GC-TOF/MS detection technology and metabonomics analysis method, obtains different treatment groups and marker metabolites related to oxidative stress influence and antioxidant stress regulation and control by multiple screening methods, and provides a characteristic fingerprint related to in vivo antioxidant. Many core metabolic pathways are conserved from caenorhabditis elegans to human beings, and the utilization of caenorhabditis elegans as a biological model to evaluate the antioxidant action mechanism of an active compound as a whole is a reliable strategy and can provide research and application demonstration for the preliminary screening of the antioxidant active compound and the elucidation of the metabolic influence mechanism.
Drawings
FIG. 1 PCA score plots for C.elegans samples from the control, model and 3 anthocyanin pre-treatment groups;
FIG. 2 is a graph of the OPLS-DA scores of C.elegans samples in the control group (Con) compared with the model group (PQ, FIG. 2A) and the cyanidin pretreatment group (Cya, FIG. 2B), delphinidin pretreatment group (Del, FIG. 2C), malvidin-3-arabinoside pretreatment group (Mal-3-ara, FIG. 2D), respectively;
FIG. 3 clustering heatmap of control (Con), and model (PQ) and cyanidin pretreatment (Cya), delphinidin pretreatment (Del), malvidin-3-arabinoside pretreatment (Mal-3-ara) based on 20 metabolites that are metabolically different;
FIG. 4 is a graph showing the relative pathway of metabolic changes in C.elegans samples compared between the control group (Con) and the model group (PQ, FIG. 4A) and cyanidin pretreatment group (Cya, FIG. 4B), delphinidin pretreatment group (Del, FIG. 4C), malvidin-3-arabinoside pretreatment group (Mal-3-ara, FIG. 4D), respectively;
FIG. 5 is a graph of the metabolite network signaling pathway reflecting metabolic changes in C.elegans samples compared to model group (PQ, FIG. 5A) and cyanidin pretreatment group (Cya, FIG. 5B), delphinidin pretreatment group (Del, FIG. 5C), malvidin-3-arabinoside pretreatment group (Mal-3-ara, FIG. 5D), respectively.
Detailed Description
The following description of the preferred embodiments of the present invention is provided for the purpose of better illustrating the invention and is not intended to limit the invention thereto.
Example 1:
(1) grouping experiments: the normal control group, the model group and the 3 anthocyanin pretreatment groups comprise 5 groups of cyanidin, delphinidin and malvidin-3-arabinoside, and 7 levels are designed in each group.
(2) C, caenorhabditis elegans culture: wild type caenorhabditis elegans is cultured by adopting a normal NGM plate coated with Escherichia coli OP50, egg collection and synchronization are carried out in the egg laying period, when the plate is cultured to the L2 period, the worm bodies are eluted and collected from the plate by using M9 phosphate buffer solution, and the density of the caenorhabditis elegans is adjusted to be 2500-.
(3) And (3) induction treatment: the caenorhabditis elegans of L2 stage was added into 6-well plate at the above density of 1 mL/well, OP50 was provided as food at a final concentration of 200mg/mL, the above 3 kinds of anthocyanin were added to the anthocyanin pretreatment group at a final concentration of 50. mu.M (in sterile water), the induction group and the control group were added with the same volume of sterile water, and incubated for 48 h. Then adding an oxidative stress inducer, namely paraquat solution with the molar concentration of 0.3mM, into the model group and the anthocyanin pretreatment group, and continuing to incubate for 24 h.
(4) Collecting samples: after the induction treatment was completed, each well of caenorhabditis elegans was transferred to a 2mL centrifuge tube, left to stand for 5min, the supernatant solution was removed and washed 3 times with M9 buffer, OP50 was washed off as much as possible, and the caenorhabditis elegans was quenched with a-20 ℃ pre-cooled aqueous solution of methanol to water at a volume ratio of 3: 2. The quenching solution was removed after centrifugation at 1000 rpm at 4 ℃. The sample is stored at-20 ℃ or the metabolite of the sample is directly extracted.
(5) Sample preparation: the metabolite extraction adopts an ultrasonic-assisted tissue trituration mode, the extraction solvent is an acetonitrile-isopropanol-water solution with a volume ratio of 3:3:2 precooled at-20 ℃, and the extraction process is carried out in a low-temperature environment (ice bath or 4 ℃). Centrifuging at 12000 r/min for 2min, collecting supernatant, and repeatedly extracting for 3 times. Meanwhile, the quantity of Quality Control (QC) samples is calculated according to the quantity of the samples, QC samples are prepared, and fatty acid standard substances (C8-C24) with the concentration of 1mg/mL are added into the QC samples to control the quality of sample processing. And carrying out vacuum freeze-drying and concentration on the extracting solution, then carrying out derivatization treatment, and transferring a sample to a chromatographic sample injection vial for computer analysis after derivatization.
(6) Metabolite detection assay: and (3) obtaining a metabolic spectrum by GC-TOF/MS detection, and identifying metabolites and screening differential metabolites by adopting metabonomics related software and a statistical method. The conditions of GC-TOF/MS were: DB-5 chromatographic column (30m × 250 μm,0.25 μm), helium as carrier gas, flow rate of column passing 20mL/min, and sample introduction volume of 1.0 μ L; the temperatures of the sample inlet, the ion source interface and the ion source are respectively 280 ℃, 280 ℃ and 250 ℃; temperature programming conditions: the initial column temperature is 70 deg.C and maintained for 1min, and then the temperature is raised to 280 deg.C at 6 deg.C/min and maintained for 5 min. The mass spectrum scanning range is 50-600m/z, the scanning speed is 20 times/s, and the solvent delay time is set to be 6 min.
The specific method for processing mass spectrum data comprises the following steps: data conversion, peak extraction, data baseline calibration, peak alignment, deconvolution, metabolite identification, peak area calculation, etc. are performed using ChromaTOF software and MS DIAL software, and peak areas are normalized. The peak identification parameters are set as: the number of scanning times of each peak is 20, the minimum peak height is 10000 amplitudes, and the background peak intensity of the mass spectrum for deconvolution is 5000 amplitudes; the metabolite identification setting parameters are as follows: the retention time error was 0.5min, the m/z error was 0.5Da, and the retention time error for mass spectral similarity greater than 70% peak alignment was set to 0.075 min. The peak area of each sample metabolite was normalized using a SERRF normalization method based on Quality Control (QC) samples.
The specific method for multivariate statistical analysis and differential metabolite screening comprises the following steps: the normalized data obtained above were subjected to Principal Component Analysis (PCA) with unsupervised pattern recognition, partial least squares (PLS-DA) with supervised pattern recognition and discriminant analysis (OPLS-DA) with orthogonal partial least squares by running R software, and the metabolite differences among the groups of samples were compared by means of a score plot to evaluate the model quality. Further, the t-test results (p-value <0.05) were taken as candidate variables for differential metabolites, i.e. biomarkers, according to the variable weight values obtained for the OPLS-DA model (VIP > 1.0).
(7) Metabolic pathway analysis: and the normalized data is searched and matched by adopting a PubChem and KEGG database baseline. Then, the converted numerical value (FC), the t-test result, the KEGG code and the metabolite name are integrated, and the cytoscape3.7.2 software is used for visualizing the metabolic pathway and drawing a metabolic signal network map. Further, the differential metabolites are mainly distributed in the TCA cycle, energy metabolism, amino acid metabolism, lipid metabolism, and neurotransmitter synthesis. Anthocyanin pre-protection can reverse metabolic disorders caused by paraquat-induced oxidative stress to different degrees.
184 metabolites were co-detected by GC-TOF/MS analysis, using software and mass spectrometry libraries to identify and peak area quantify the C.elegans metabolites. And performing multivariate analysis comparison on the metabolic changes of the control group, the model group and the anthocyanin pretreatment group. The metabolite spectrum of caenorhabditis elegans is analyzed through unsupervised PCA analysis and supervised OPLS-DA analysis, and the reliability of the model is verified. The PCA results are shown in FIG. 1, wherein 48% of the total viscosity variation of the first two principal components of the five groups is obtained, and the sample points of the control group and the model group are completely separated, which indicates that the paraquat-induced oxidative stress model is successfully constructed. The distances between the 3 anthocyanin pretreatment groups and the control group and the model group are different, which shows that different anthocyanin pretreatment interventions even call back the metabolic changes caused by oxidative stress.
Complete separation between the control and model groups was also observed in figure 2 by performing OPLS-DA analysis on the data, indicating that there was a very significant difference in the metabolic profile between the two groups. The reliability of the OPLS-DA model is further verified by adopting a replacement test in OPLS-DA, and compared with a control group, parameters obtained by the model group, the cyanidin pretreatment group, the delphinidin pretreatment group and the malvidin-3-arabinoside pretreatment group are R2X which is 0.431, 0.363, 0.183 and 0.369 respectively; R2Y ═ 0.993,0.940, 0.931, 0.960; q2 is 0.978, 0.905, 0.759 and 0.925, which shows that the established OPLS-DA model has better fitting effect.
To more clearly show which metabolite changes produced differences in the principal components of the model, the top 20 significantly different metabolites were visualized using Hierachic Pearson clustering heatmap analysis. As shown in fig. 3, most metabolites were significantly down-regulated in the model group treated with oxidative stress induction. In the anthocyanin pretreatment group, the metabolite abundance of the delphinidin pretreatment group is the closest to that of the control group, which shows that the delphinidin can more effectively reverse the disturbance of paraquat-induced oxidative stress on caenorhabditis elegans metabolism. This is consistent with the results for PCA, OPLS-DA. By combining 3 analysis indexes, the fact that paraquat induction causes in-vivo metabolic disorder of caenorhabditis elegans can be obtained, the effect is mainly shown in the down-regulation of metabolite levels, and anthocyanin pretreatment can be reversed to different degrees.
Differential metabolite identification and metabolite pathway enrichment analysis
According to VIP & gt 1 obtained by OPLS-DA and a t test value meeting the 95% level, differences of metabolite detection abundance are evaluated by combining an FC value, 15, 8, 9 and 14 significant metabolites are respectively obtained by a model group, a cyanidin pretreatment group, an delphinidin pretreatment group and a malvidin-3-arabinoside pretreatment group, and the results are shown in Table 1. Compared with the control group, 11 metabolites of the total significant metabolites of the model group are in a descending trend, only 4 metabolites are in an ascending trend, and the metabolic disorders are in callback to different degrees under the protection of anthocyanin. Other metabolites with obvious difference are also found in the cyanidin pretreatment group (1 metabolite), the delphinidin pretreatment group (7 metabolites) and the malvidin-3-arabinoside pretreatment group (3 metabolites), which indicates that anthocyanin not only participates in the regulation of the metabolic pathway influenced by paraquat induction, but also responds to other metabolic processes.
TABLE 1 summary of differential metabolites
Note: Δ indicates that the VIP value obtained by OPLS-DA is greater than 1; a represents a statistical difference p <0.05 compared to the control group; b represents a statistical difference p <0.01 compared to the control group.
The metabolite pathways were enriched using MetaboAnalyst and the results are shown in figure 4. When caenorhabditis elegans is under oxidative stress conditions, the metabolite effects of the model group are significantly increased from the viewpoint of aging and oxidative stress, and are mainly related to several metabolic pathways. These pathways include the tricarboxylic acid (TCA) cycle, glutamine and glutamate metabolism, glycerophospholipid metabolism, pyruvate metabolism, cysteine and methionine metabolism, arginine and proline metabolism, alanine, aspartic acid and glutamic acid metabolism, glycerophospholipid metabolism, and glutathione metabolism (fig. 4A). These pathways are involved in the metabolism of energy, amino acids and lipids. Of the three anthocyanin pretreatment groups, cyanidin and malvidin-3-arabinoside pretreatment groups were involved in similar metabolic processes (fig. 4B and 4D). Changes in alanine metabolism, pantothenate and CoA biosynthesis, pyrimidine metabolism, and fatty acid degradation were also found in these two groups. In addition, pretreatment of delphinidin significantly reversed the metabolic disorders caused by paraquat, and multiple metabolic processes were restored to levels similar to those of the control group; in addition, 9 biosynthetic and metabolic processes were enriched (fig. 4C). These results also indicate that anthocyanins can protect caenorhabditis elegans from metabolic disturbances caused by oxidative stress.
Metabolic network pathway analysis
To analyze the interactions between metabolites, metabolic network pathways that were subject to oxidative stress and intervention by three anthocyanins were analyzed using the MetaMapp network software, and a visualized metabolic network pathway map was generated using CytoScape (fig. 5). The diameter of the dots in the graph correlates to the FC value and the p value of the t-test. The model group was treated with paraquat significantly affecting many metabolic processes of caenorhabditis elegans. Metabolites such as tyrosine, cystathionine, citrulline, pipecolic acid, palmitic acid, valine, eicosapentaenoic acid, fructose-6-phosphate, phosphoenolpyruvate, glutathione and linoleic acid (p <0.01) were significantly reduced in abundance relative to the control, while cholesterol (FC value 14.1), stearic acid (FC value 5.5), homoserine (FC value 22.7), uracil (FC value 50.6), thymine (32.9), glycerol (FC value 5.3) (p <0.01) were significantly increased (fig. 5A). Cyanidin, delphinidin and malvidin-3-arabinoside treatment reversed paraquat-induced metabolic changes to varying degrees (fig. 5B-D). The metabolite abundance of the delphinidin pretreatment group after paraquat induction is the closest to that of the control group, which shows that the delphinidin can effectively reverse metabolic disorder caused by paraquat and maintain the normal metabolic dynamics of caenorhabditis elegans. The metabolic network pathway analysis well explains the antioxidation action mechanism of anthocyanin under the oxidative stress of caenorhabditis elegans induced by paraquat.
Comparative example 1:
reference is made to the procedure of example 1, with the difference that the concentration of the oxidative stress inducer paraquat is 0.2mM, the nematode body density is 3000 nematodes/mL, the incubation time for anthocyanin intervention is 48h and the inducer treatment time is 36 h.
Comparative example 2:
the method of example 1 was referenced except that the oxidative stress inducer paraquat concentration was 0.9mM, nematode body density was 2000 nematodes/mL, incubation time for anthocyanin intervention was 72h, and inducer treatment time was 12 h.
The extracted samples obtained in the above examples and comparative examples were subjected to GC-MS detection and data analysis under the same conditions, and the results were obtained by examining the peak shape of the spectrum, the matching degree of the search results, the amount and quantification of the final metabolites, and the like in many ways: the quantity of metabolites, the abundance of substances and the construction effect of an oxidative stress model obtained under the parameter conditions in the examples are all superior to those of the comparative examples.
Although the present invention has been described with reference to the preferred embodiments, it should be understood that various changes and modifications can be made therein by those skilled in the art without departing from the spirit and scope of the invention as defined in the appended claims.
Claims (10)
1. A method for screening an antioxidant active substance, which is characterized by using caenorhabditis elegans as an antioxidant animal model, comprising the steps of:
(1) grouping experiments: the normal control group, the model group and the 3 anthocyanin pretreatment groups are divided into 5 groups;
(2) c, caenorhabditis elegans culture: plating the wild type caenorhabditis elegans with Escherichia coli, synchronizing egg collection in the egg laying period, and eluting with buffer solution when the plate is cultured to L2 stage, collecting and counting the density of caenorhabditis elegans;
(3) and (3) induction treatment: uniformly adding caenorhabditis elegans of L2 stage into a 6-hole plate according to a certain density, simultaneously providing OP50 food, respectively adding 3 kinds of anthocyanin into an anthocyanin pretreatment group, adding a solvent with the same volume into a model group and a control group for incubation, then adding an oxidative stress inducer into the model group and the anthocyanin pretreatment group, and continuing incubation;
(4) collecting samples: collecting the polypide sample into a centrifuge tube for further processing after the step (3) is finished;
(5) sample preparation: extracting, enriching and derivatizing the collected sample, and then waiting for machine analysis;
(6) metabolite detection assay: detecting by GC-TOF/MS to obtain a metabolic spectrum, and identifying metabolites and screening differential metabolites by adopting metabonomics related software and a statistical method;
(7) metabolic pathway analysis: and constructing a corresponding metabolic signal path and analyzing by adopting a metabonomics related database and a software program.
2. The method of claim 1, wherein the 3 anthocyanins of step (1) and step (3) are cyanidin, delphinidin, malvidin-3-arabinoside, respectively.
3. The method according to claim 1 or 2, wherein the model group of step (1) and the oxidative stress-inducing agent of step (2) are each a paraquat solution having a molar concentration of 0.1 to 0.5 mM.
4. The method as claimed in any one of claims 1 to 3, wherein the density of the insect bodies used in the experiments in step (2) and step (3) is 2000-3000 strips/mL.
5. The method according to any one of claims 1 to 4, wherein the incubation time after the addition of anthocyanin in step (3) is 36 to 72 hours, and the incubation time after the addition of inducer is 12 to 36 hours.
6. The method according to any one of claims 1 to 5, wherein the extraction in the step (5) is an ultrasonic-assisted tissue trituration method, the extraction solvent is an acetonitrile/isopropanol/water solution with a volume ratio of 3:3:2 pre-cooled at-20 ℃, and the extraction process is a low-temperature environment.
7. The method as claimed in any one of claims 1 to 6, wherein the GC-TOF/MS conditions in step (6) are: DB-5 chromatographic column (30m × 250 μm,0.25 μm), helium as carrier gas, flow rate of column passing 20mL/min, and sample introduction volume of 1.0 μ L; the temperatures of the sample inlet, the ion source interface and the ion source are respectively 280 ℃, 280 ℃ and 250 ℃; temperature programming conditions: keeping the initial column temperature at 70 deg.C for 1min, heating to 280 deg.C at 6 deg.C/min, and keeping for 5 min; the mass spectrum scanning range is 50-600m/z, the scanning speed is 20 times/s, and the solvent delay time is set to be 6 min.
8. The method according to any one of claims 1 to 7, wherein the mass spectrometry data processing in step (6) is specifically: performing data conversion, peak extraction, data baseline calibration, peak alignment, deconvolution, metabolite identification, peak area calculation and the like by using ChromaTOF software and MSDIAL software, and normalizing the peak areas; the peak identification parameters are set as: the number of scanning times of each peak is 20, the minimum peak height is 10000 amplitudes, and the background peak intensity of the mass spectrum for deconvolution is 5000 amplitudes; the metabolite identification setting parameters are as follows: the retention time error is 0.5min, the m/z error is 0.5Da, and the retention time error of the mass spectrum similarity which is more than 70 percent of peak alignment is set as 0.075 min; the peak area of each sample metabolite was normalized using a SERRF normalization method based on Quality Control (QC) samples.
9. The method according to any one of claims 1 to 8, wherein the multivariate statistical analysis and differential metabolite screening of step (6) is performed by: running the normalized data by using R software to perform Principal Component Analysis (PCA) of unsupervised pattern recognition, partial least squares (PLS-DA) of supervised pattern recognition and orthogonal partial least squares discriminant analysis (OPLS-DA) discriminant analysis, and comparing metabolite differences among groups of sample groups through a score map to evaluate the quality of the model; further, the t-test results (p-value <0.05) were used as candidate variables for differential metabolites, i.e. biomarkers, according to the significance projection parameters (VIP >1.0) obtained from the OPLS-DA model.
10. The method according to any one of claims 1 to 9, wherein the metabolic pathway is constructed and analyzed in step (7) by the following specific method: searching and matching the normalized data by adopting a PubChem and KEGG database baseline; then integrating the converted numerical value (FC), the t-test result, the KEGG code and the metabolite name, visualizing the metabolic pathway by using cytoscape3.7.2 software, and drawing a metabolic signal network diagram; further, differential metabolites are mainly distributed in the TCA cycle, energy metabolism, amino acid metabolism, lipid metabolism, and neurotransmitter synthesis; anthocyanin pre-protection can reverse metabolic disorders caused by paraquat-induced oxidative stress to different degrees.
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