CN112630363A - MXene biological response characteristic metabonomics analysis method - Google Patents
MXene biological response characteristic metabonomics analysis method Download PDFInfo
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- CN112630363A CN112630363A CN202011642229.7A CN202011642229A CN112630363A CN 112630363 A CN112630363 A CN 112630363A CN 202011642229 A CN202011642229 A CN 202011642229A CN 112630363 A CN112630363 A CN 112630363A
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- G01N30/02—Column chromatography
- G01N30/88—Integrated analysis systems specially adapted therefor, not covered by a single one of the groups G01N30/04 - G01N30/86
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Abstract
The invention belongs to the technical field of metabonomics analysis, and particularly relates to an MXene biological response characteristic metabonomics analysis method. In view of the above-mentioned difficulties in the prior art, the analysis method provided by the present invention comprises the following steps: (1) co-culturing MXene nanometer material and cells to obtain a biological sample to be analyzed; (2) extracting at least one of a non-targeted water-soluble metabolite sample, a non-targeted lipid-soluble metabolite sample, and a targeted water-soluble metabolite sample in a biological sample to be analyzed; (3) detecting a non-targeted water-soluble metabolite sample, and/or a non-targeted fat-soluble metabolite sample, by liquid chromatography-mass spectrometry, and/or detecting a targeted water-soluble metabolite sample by gas chromatography-mass spectrometry. The present invention also optimizes the treatment conditions, extraction conditions and detection conditions of the biological sample. The invention provides a new research method for the subsequent modification and clinical application research of MXene nano-materials, and the application prospect is wide.
Description
Technical Field
The invention belongs to the technical field of metabonomics analysis, and particularly relates to an MXene biological response characteristic metabonomics analysis method.
Background
Metabonomics, a classical detection and analysis technique with various characteristics and significant advantages, has attracted great attention of researchers at present due to its inherent correlation principle and practical application. The technology also shows excellent advantages in the fields of revealing in-vivo metabolic processes, life behaviors and the like, and meanwhile, research of further technical innovation and development based on modern metabonomics is continued for many years and has fruitful results. Metabolomics has been successfully implemented to detect and analyze the structure and content of thousands of small molecules (<1500Da) of metabolites, revealing their inherent association with organisms. Due to the advantages of phenotypic biocompatibility, high-throughput analysis process, low detection cost, rich information analysis result and the like of metabonomics, the metabonomics are widely used in various life systems such as microorganisms, cells, plants, mammals, environment and the like to investigate the metabolic change rule in the life body. Meanwhile, metabonomics also has a plurality of leading-edge and meaningful results in the research fields of toxicological evaluation, new drug development, clinical diagnosis, disease treatment, food safety, environmental chemistry and the like. Recent metabonomics-based correlation studies have mainly focused on the development of technological improvements and new research fields, which put higher demands on the development of the species and sensitivity of metabolite detection.
In order to achieve the aim, a novel metabonomics research platform combining modern analysis technology and chemometrics statistical software successfully realizes effective detection of metabolites and integration processing of subsequent data, and summarizes endogenous and heterologous metabolic processes according to obtained results. In the existing detection means, liquid chromatography-tandem mass spectrometry (LC-MS) and gas chromatography-mass spectrometry (GC-MS) are powerful tools for metabonomics research, have the advantages of high sensitivity, simple sample treatment, wide coverage, short time and the like, realize the simultaneous detection of thousands of metabolites and are widely utilized. Currently, an omics analysis platform based on LC-MS, GC-MS and data statistical software is widely used for non-targeted combined metabonomics research. The omics analysis platform will play an important role in the research and technical optimization of the internal change of future life bodies, and provide valuable theoretical and practical references for the practical application and technical improvement of the non-targeting combined metabonomics.
Two-dimensional flaky Ti3C2The (MXene) nanosheet attracts attention of researchers due to excellent physicochemical properties and ultrathin morphology. MXene has the characteristics of high conductivity, easy surface modification, good mechanical property and the like, so that MXene becomes a new star with great potential in various research fields. Recently, MXene has been increasingly used in various biomedical fields such as bionics, organ regeneration, bioimaging, antibacterial and photothermal therapy. In order to better apply MXene in the biomedical field, the intrinsic intervention process and molecular mechanism of an organism-MXene interaction system are generally researched according to the application scene of MXene. The problems to be studied include the effect of MXene on metabolic pathways in different biological systems (tissue cells are different) and under different conditions (such as temperature and amount of nanomaterial). In response to this problem, metabolomic analysis techniques are a very good choice.
However, in metabolomics research, one of the challenges is how to isolate various metabolites from a biological sample and perform efficient detection. In general, the chemical composition of the metabolites of an organism is complex and there are various interferences with impurities of various target compounds to be analyzed, thus specific methods are usually required for the processing and extraction of biological samples before LC-MS and GC-MS detection. And the detection conditions of LC-MS and GC-MS should also be designed according to the type and content of the target metabolite to be detected.
At present, the interaction between MXene and organisms is rarely known, and under the condition that the internal intervention process and molecular mechanism of an interaction system are still unclear, the treatment condition, extraction condition and detection condition of a biological sample in a metabonomics analysis method cannot be determined according to a target metabolite to be detected.
Disclosure of Invention
Aiming at the difficulties in the prior art, the invention provides a MXene biological response characteristic non-targeting combined metabonomics analysis method, which aims to: provides the optimized processing condition, extraction condition and detection condition of the biological sample, so that the method is suitable for the metabonomics research of MXene and organism interaction system. Provides a new research method for the subsequent modification and clinical application research of MXene nano-materials.
An MXene bioresponse characteristic metabonomics analysis method comprises the following steps:
(1) taking a biological sample to be analyzed after the biological sample reacts with the MXene nano material;
(2) extracting at least one of a non-targeted water-soluble metabolite sample, a non-targeted lipid-soluble metabolite sample, and a targeted water-soluble metabolite sample in a biological sample to be analyzed;
(3) detecting a non-targeted water-soluble metabolite sample and/or a non-targeted fat-soluble metabolite sample by liquid chromatography-mass spectrometry and/or detecting a targeted water-soluble metabolite sample by gas chromatography-mass spectrometry;
wherein, when the non-target water-soluble metabolite sample is detected, the metabolite sample is dissolved in water, and the chromatographic conditions are as follows: the mobile phase takes acetonitrile aqueous solution with volume fraction of 5-10% as phase A and acetonitrile aqueous solution with volume fraction of 90-95% as phase B; the chromatographic column adopts amido ethylene bridge hybrid particles as filler;
and/or, the non-targeted fat-soluble metabolite sample is dissolved in a dichloromethane/methanol mixed solution during detection, and the chromatographic conditions are as follows: the mobile phase takes acetonitrile water solution with volume fraction of 60-70% as phase A and acetonitrile solution with volume fraction of 90-95% isopropanol as phase B; the chromatographic column adopts C30 or C18 silica gel chromatographic column;
and/or, the targeted water-soluble metabolite sample is dissolved in methanol during detection, and the chromatographic conditions are as follows: the carrier gas is helium; the chromatographic column adopts polydimethylsiloxane particles as filler.
Preferably, in step (1), the cells are human vascular endothelial cells, liver cells or kidney cells;
and/or the biological sample to be analyzed is a biological sample co-cultured with the MXene nano material, the co-culture time is more than or equal to 12 hours, and the preferred co-culture time is 24-48 hours.
Preferably, in the step (2), the extraction method of the non-target water-soluble metabolite sample comprises the following steps: washing the biological sample to be analyzed by using a phosphate buffer solution, adding trypsin to obtain a cell suspension, separating by using methanol, taking a supernatant, and drying to obtain the biological sample;
and/or the extraction method of the non-target fat-soluble metabolite sample comprises the following steps: washing the biological sample to be analyzed by using a phosphate buffer solution, adding trypsin to obtain a cell suspension, separating by using methanol and methyl tert-butyl ether, taking a supernatant, and concentrating to obtain the biological sample;
and/or the extraction method of the target water-soluble metabolite sample comprises the following steps: taking a non-target water-soluble metabolite sample, redissolving, derivatizing, separating again, taking supernatant, and drying to obtain the target-free water-soluble metabolite.
Preferably, in the step (2), the extraction method of the non-target water-soluble metabolite sample comprises the following steps: washing the biological sample to be analyzed by using a phosphate buffer solution, adding 0.25 wt.% of trypsin solution, adding 1-2 ml/10000000 cells, preferably 1ml/10000000 cells to obtain a cell suspension, adding 75-80% by volume of methanol aqueous solution, preferably 80% by volume of methanol aqueous solution, carrying out ultrasonic treatment for 20-30min, preferably 30min, carrying out vortex oscillation for 20-30min, preferably 20min, centrifuging at 10000-13000 rpm for 5-10 min, preferably 13000rpm for 5min, taking a supernatant, and drying to obtain the biological sample to be analyzed;
and/or the extraction method of the non-target fat-soluble metabolite sample comprises the following steps: washing the biological sample to be analyzed with phosphate buffer, adding 0.25 wt.% trypsin solution in an amount of 1-2 ml-
10000000 cells, preferably 1ml/10000000 cells, to obtain a cell suspension, adding methanol, performing vortex oscillation for 5-10 min, preferably 5min, sequentially adding methyl tert-butyl ether and water, centrifuging at 10000-13000 rpm for 5-10 min, preferably 13000rpm for 5min, taking a supernatant, and concentrating to obtain the cell suspension;
and/or the extraction method of the target water-soluble metabolite sample comprises the following steps: taking a non-target water-soluble metabolite sample, redissolving with pyridine, derivatizing, centrifuging at 10000-13000 rpm for 5-10 min, preferably at 13000rpm for 5min, taking supernate, and drying to obtain the target compound.
Preferably, the derivatization process is: adding pyridine solution of methoxylamine hydrochloride, and incubating at 60-65 deg.C for 90-100min, preferably at 60 deg.C for 90 min; then adding N-methyl-N- (trimethylsilyl) trifluoroacetamide, and incubating at 60-65 deg.C for 20-30min, preferably at 60 deg.C for 30 min.
Preferably, the targeted water-soluble metabolite sample comprises at least one of the following characteristic metabolites: aconitic acid, 4-aminobutyric acid, citric acid, dihydroxyacetone phosphate, fumaric acid, glutamic acid, glycerol-1-phosphate, α -ketoglutaric acid, lactic acid, malic acid, 6-phosphogluconic acid, 3-phosphoglyceric acid, asparagine, aspartic acid, alanine, glutamine, glycine, isoleucine, leucine, proline, valine, arachidic acid, eicosapentaenoic acid, elaidic acid, heptadecanoic acid, linoleic acid, tetradecanoic acid, palmitic acid, pelargonic acid and stearic acid.
Preferably, in the step (3), the chromatographic conditions for detecting the non-target water-soluble metabolite sample are as follows: the mobile phase takes acetonitrile water solution with volume fraction of 5% as phase A and acetonitrile water solution with volume fraction of 95% as phase B;
and/or, the chromatographic conditions for the detection of the non-targeted water-soluble metabolite sample further comprise: the phase A also contains 5-10mM ammonium acetate and 0.1-0.5 wt.% acetic acid, preferably contains 5mM ammonium acetate and 0.1 wt.% acetic acid, and the phase B also contains 5-10mM ammonium acetate and 0.1-0.5 wt.% acetic acid, preferably contains 5mM ammonium acetate and 0.1 wt.% acetic acid;
and/or the mobile phase takes acetonitrile water solution with volume fraction of 60% as phase A and acetonitrile solution with volume fraction of 90% isopropanol as phase B;
and/or, the chromatographic conditions for the detection of the non-targeted lipid-soluble metabolite sample further comprise: the phase a also contains 10-15mM ammonium formate and 0.1-0.5 wt.% formic acid, preferably 10mM ammonium formate and 0.1 wt.% formic acid, and the phase B also contains 10-15mM ammonium formate and 0.1-0.5 wt.% formic acid, preferably 10mM ammonium formate and 0.1 wt.% formic acid.
Preferably, in step (3), the chromatographic conditions for detecting the non-target water-soluble metabolite sample further include: the elution gradient was:
and/or, the chromatographic conditions for the detection of the non-targeted lipid-soluble metabolite sample further comprise: the elution gradient was:
preferably, in step (3), the chromatographic conditions for detecting the non-target water-soluble metabolite sample further include: the flow rate of the mobile phase is 200-300 mu l/min, preferably 300 mu l/min, the temperature of the chromatographic column is 35-40 ℃, preferably 35 ℃, and the sample amount is 2-5 mu l, preferably 5 mu l;
and/or, the chromatographic conditions for the detection of the non-targeted lipid-soluble metabolite sample further comprise: the flow rate of the mobile phase is 200-260 mu l/min, preferably 260 mu l/min, the temperature of the chromatographic column is 40-45 ℃, preferably 45 ℃, and the sample amount is 2-5 mu l, preferably 2 mu l;
and/or, the chromatographic conditions for targeted detection of a sample of water-soluble metabolites further comprise: the temperature of the chromatographic column is 35-40 ℃, preferably 35 ℃, the sample injection amount is 2-5 mul, preferably 5 mul, the flow rate of the carrier gas is 0.5-1ml/min, preferably 0.5ml/min, and the temperature of the sample injector is 250 ℃ and 300 ℃, preferably 250 ℃;
and/or, in the step (3), the mass spectrum detection conditions for detecting the non-targeted water-soluble metabolite sample are as follows: the scanning mode is that positive and negative ions are scanned simultaneously, the temperature of the capillary is 350-;
and/or the mass spectrum detection conditions for detecting the non-targeted fat-soluble metabolite sample are as follows: the scanning mode is that positive and negative ions are scanned simultaneously, the temperature of the capillary is 320-350 ℃, the preferred temperature is 320 ℃, the preferred flow rate of the sheath gas is 40-45 units, the preferred unit is 45 units, the flow rate of the auxiliary gas is 8-10 units, the preferred unit is 8 units, and the spraying voltage is 3.5-4kV, the preferred unit is 3.5 kV;
and/or the mass spectrum detection conditions for the detection of the targeted water-soluble metabolite sample are as follows: full scan mode m/z50-600, impact ionization energy 70-80eV, preferably 70eV, and solvent retardation set at 5.9-6min, preferably 5.9 min.
Preferably, in the step (3), the result obtained by the liquid chromatography-mass spectrometry and/or the gas chromatography-mass spectrometry detection is used for the analysis of the metabolic pathway, and the analysis of the metabolic pathway comprises the following steps:
(4.1) analyzing and identifying metabolites of the results obtained by the liquid chromatography-mass spectrometry and/or gas chromatography-mass spectrometry detection based on an R language algorithm to obtain statistical results;
(4.2) after normalizing the statistical results, performing principal component analysis, partial least squares discriminant analysis or orthogonal partial least squares discriminant analysis to group the metabolites;
(4.3) MetaboAnalyst analysis was performed by R language to identify representative metabolic pathways.
In the detection method of the biological sample provided by the invention, the detection conditions of the non-target water-soluble metabolite sample, the non-target fat-soluble metabolite sample and the target water-soluble metabolite sample are respectively optimized, and the separation and detection of various characteristic metabolites in the biological sample can be met. The accuracy of detecting and identifying the metabolites is improved, and the accuracy of subsequent metabolic pathway analysis is further improved. By the method, the influence of MXene on the biological metabolism pathway in different biological systems and under different environmental conditions can be researched.
In addition, the non-targeted metabonomics in the invention mainly researches the influence degree of MXene on metabolites from a macroscopic view, and inspects the types and the quantity of different metabolites and metabolic pathways. The targeted metabonomics mainly analyzes a plurality of closely related metabolites and metabolic pathways from a microscopic angle, and summarizes the influence rule of MXene from a detailed angle. And the metabolites and metabolic pathways investigated by the targeted metabonomics can be selected based on the analysis result of the non-targeted metabonomics, so that the pertinence is stronger, and the meaningful and important biological information can be obtained more favorably.
In the selection of the detection method, the targeted detection needs to utilize the unique narrow time window of the gas chromatography, the retention time is stable, the operation is simple and convenient, and the like; the invention can effectively combine the advantages of wide compound type coverage range and high sensitivity of liquid chromatogram for non-targeted detection, so as to effectively carry out non-targeted and targeted metabonomics research and reveal the biological response characteristic of MXene.
The method has the advantages of convenient operation, low cost, environment-friendly materials, environmental friendliness and simple design, is suitable for laboratory research and outdoor test, and is convenient for real-time non-targeted combined metabonomics research on the biological response characteristics of the MXene nano-materials.
Obviously, many modifications, substitutions, and variations are possible in light of the above teachings of the invention, without departing from the basic technical spirit of the invention, as defined by the following claims.
The present invention will be described in further detail with reference to the following examples. This should not be understood as limiting the scope of the above-described subject matter of the present invention to the following examples. All the technologies realized based on the above contents of the present invention belong to the scope of the present invention.
Drawings
FIG. 1 is a schematic flow diagram of a non-targeted combined metabonomics analysis method of MXene bioresponse characteristics of the present invention;
wherein, 1 is MXene nanometer material, 2 and 6 are cell culture dishes, 3 and 7 are cell culture media, 4 is a non-target water-soluble metabolite sample or a non-target fat-soluble metabolite sample, 5 is non-target liquid chromatography-mass spectrometry, 8 is target water-soluble metabolite, 9 is target gas chromatography-mass spectrometry, and 10 is bioinformatics statistics and analysis.
FIG. 2 is a logic diagram of the MXene biological response characteristic non-targeting combined metabonomics analysis method applied.
FIG. 3 shows the effect of different concentrations of MXene nanomaterials (100ng/ml or 500ng/ml) in co-culture with HUVEC cells on the (a) target metabolites and (b-c) metabolic pathways of the cells in example 1 of the present invention.
Detailed Description
The technical solution of the present invention is further illustrated by the following specific examples. Unless otherwise specified, the experimental methods used are conventional ones, and the instruments, reagents and raw materials used are commercially available. In the examples, unless otherwise specified, the concentrations of the solution, the mixed solution, or the mixed gas are volume concentrations, and the proportions are volume proportions.
Example 1 non-targeting combined metabonomics analysis method of MXene nano-material biological response characteristics
MXene nano material: MXene (Ti)3C2) The nano-materials were purchased from Nanjing Xiancheng nano-materials science and technology Co.
The medium for co-culture was dmem (dulbecco Modified Eagle medium) medium containing 10% fetal bovine serum and 1% penicillin-streptomycin solution.
The specific steps of this embodiment are shown in fig. 1 and 2, and specifically as follows:
1. co-culture of MXene nano material and cell
Culture dishes seeded with HUVEC cells in 5% CO2In an incubator at 37 ℃. The medium was changed every two days to maintain the viability of the cells.
After the cells had grown to exponential growth, the HUVEC cells were washed with phosphate buffer, and then 1ml trypsin was added to obtain a cell suspension. 2ml of cell suspension (cell concentration 1X 10)5one/mL) were dispersed and seeded into each well of a 6-well plate. Then, 2 doses of MXene nanometer materials 1 are respectively added into the pore plate and uniformly mixed, so that the concentration of the MXene nanometer materials 1 in the pore plate is 100ng/ml and 500ng/ml respectively, and five pores are formed in each concentration. The petri dish after the sample application is co-cultured in an incubator for 48 h. Thus obtaining the biological sample to be analyzed.
2. Non-targeted metabolite sample extraction and detection
And (3) washing the biological sample to be analyzed obtained after the co-culture in the step (1) by using a phosphate buffer, and then adding 1ml of trypsin to obtain a cell suspension.
(1) Preparation of non-targeted water-soluble metabolite samples: 1/2 volumes of the cell suspension were taken and quenched for 30min by adding 1ml of pre-cooled 80% aqueous methanol. After this time, the cell suspension was sonicated in an ice bath for 30min and vortexed for 20min, then centrifuged (13000rpm) for 5min, after which the supernatant was transferred to a new tube and vacuum dried for 3 hours to obtain a sample of non-targeted water-soluble metabolite, which was stored for use.
Detection of non-targeted water-soluble metabolite samples: taking the non-targeted water-soluble metabolite, adding water for redissolving, centrifuging to remove precipitates, taking supernate for bottling, and detecting by liquid chromatography-mass spectrometry to obtain the original data of the liquid chromatography-mass spectrometry spectrogram of the non-targeted water-soluble metabolite.
Wherein, the liquid chromatogram setting conditions are as follows: the flow rate of the mobile phase was 300. mu.l/min, and the mobile phase consisted of (A) a 5% aqueous acetonitrile solution (containing 5mM ammonium acetate and 0.1% acetic acid) and (B) a 95% aqueous acetonitrile solution (containing 5mM ammonium acetate and 0.1% acetic acid), with the associated elution gradients shown in Table 1. The column was packed with amido ethylene bridge hybrid particles (2.1 mm. times.100 mm, 1.7 μm) at a temperature of 35 ℃. The amount of sample was 5. mu.l. The mass spectrum setting conditions are as follows: the mass spectrum consists of a heating electrospray ionization source (H-ESI) and an Orbitrap mass analyzer, the scanning mode is that positive ions and negative ions are scanned simultaneously, the temperature of a capillary is 350 ℃, the flow rate of sheath gas is 35 units, the flow rate of auxiliary gas is 10 units, and the spraying voltage is 3.5 kV.
TABLE 1 elution gradient in chromatographic analysis of non-target water-soluble metabolite samples
(2) Preparation of non-targeted lipid-soluble metabolite samples: the cell suspension was removed in the remaining 1/2 volumes by centrifugation, then 300. mu.l methanol was added, after vortexing for 5min, the system was mixed with 1ml methyl tert-butyl ether and gently shaken. Subsequently, 250. mu. l H was added2O, and shake slowly for 1 h. Then centrifuged (13000rpm) for 5min, and the mixture was centrifugedAnd transferring the clear liquid into a new test tube, treating the clear liquid for 30min by using nitrogen flow, concentrating the clear liquid to obtain the non-target fat-soluble metabolite, and storing the non-target fat-soluble metabolite for later use.
Detection of non-targeted lipid-soluble metabolite samples: taking the fat-soluble metabolite, adding methanol and dichloromethane for redissolving, and detecting in a liquid chromatography-mass spectrum to obtain original data of a liquid chromatography-mass spectrum of the fat-soluble metabolite.
Wherein, the liquid chromatogram setting conditions are as follows: the flow rate of the mobile phase was 260. mu.l/min, and the mobile phase consisted of (A) a 60% acetonitrile aqueous solution (containing 10mM ammonium formate and 0.1% formic acid) and (B) a 90% isopropanol acetonitrile solution (containing 10mM ammonium formate and 0.1% formic acid), with the relevant elution gradients shown in Table 2. The temperature of the C30 column (2.1 mm. times.150 mm, 2.6 μm) was set at 45 ℃. The amount of sample was 2. mu.l. The MS setting conditions are as follows: the MS consists of a heating electrospray ionization source (H-ESI) and an Orbitrap mass analyzer, the scanning mode is that positive ions and negative ions are scanned simultaneously, the temperature of a capillary tube is 320 ℃, the flow rate of sheath gas is 45 units, the flow rate of auxiliary gas is 8 units, and the spraying voltage is 3.5 kV.
TABLE 2 elution gradient in chromatography of non-targeted lipid samples
3. Targeted metabolite sample extraction and detection
Samples of non-targeted water soluble metabolites were taken, reconstituted with pyridine, mixed with 30. mu.l, 40mg/ml methoxylamine hydrochloride-pyridine at 60 ℃ and incubated for 90 min. Then, 70 μ l N-methyl-N- (trimethylsilyl) trifluoroacetamide was added at 60 ℃ and incubated for 30 min. After centrifugation (13000rpm, 10min, 25 ℃), the supernatant is taken and dried to obtain a target water-soluble metabolite sample, which is stored for later use.
Detection of targeted water-soluble metabolites: taking the targeted water-soluble metabolite, adding methanol for redissolving, centrifuging to remove precipitates, taking the supernatant, bottling, and detecting by gas chromatography-mass spectrometry to obtain the original data of the gas chromatography-mass spectrometry spectrogram of the targeted water-soluble metabolite.
Wherein, the gas chromatography setting conditions are as follows: the chromatographic column filler is polydimethylsiloxane particles, and the temperature of the chromatographic column is 35 ℃; the sample amount is 5 mul; the carrier gas is helium, and the flow rate of the carrier gas is 0.5 ml/min; the injector temperature was 250 ℃. The mass spectrometry conditions used were: the scanning mode of the mass spectrum was the full scan mode (m/z50-600), the impact ionization energy was 70eV, and the solvent delay was set at 5.9 min.
4. Bioinformatic statistical analysis
Data preprocessing: importing liquid chromatography-mass spectrometry spectrogram original data of non-targeted water-soluble metabolites into Progenesis QI software, importing liquid chromatography-mass spectrometry spectrogram original data of non-targeted fat-soluble metabolites into MS-DIAL software, importing gas chromatography-mass spectrometry spectrogram original data of targeted water-soluble metabolites into MassHunter software, and performing information extraction on the original data through baseline correction, denoising, smoothing, time window segmentation and multivariate curve analysis algorithms to obtain retention time and intensity of characteristic peaks of liquid chromatography-mass spectrometry and/or liquid chromatography-mass spectrometry spectrograms after MXene treatment.
And (3) identifying the metabolites of the processed liquid chromatography-mass spectrum and/or liquid chromatography-mass spectrum spectrogram based on a Human Metabolome Database (HMDB) by adopting an R language algorithm to obtain a statistical result.
Further missing value attribution processing is performed through a KNN algorithm and LOESS signal correction. Then, Principal Component Analysis (PCA), partial least squares discriminant analysis (PLS-DA) and orthogonal partial least squares discriminant analysis (OPLS-DA) were performed, and the influence characteristics of MXene on the cellular metabolomics were examined by comparing the respective metabolites.
Metabolic pathway analysis was achieved by the R language MetaboAnalyst to identify representative metabolic pathways of cells under MXene intervention.
The analysis result shows that MXene nanometer material is co-cultured with HUVEC cells, the concentration (100ng/ml or 500ng/ml) of MXene has the influence on the targeted metabolites and metabolic pathways of the cells, and the specific analysis experiment result is shown in FIG. 3:
as shown in fig. 3a, in the embodiment of the present invention, after 100ng/ml or 500ng/ml of MXene nanomaterial is co-cultured with HUVEC cells, the extracted targeted characteristic metabolites include amino acids, organic acids, fatty acids, and the like, which specifically include: aconitic acid, 4-aminobutyric acid, citric acid, dihydroxyacetone phosphate, fumaric acid, glutamic acid, 1-phosphoglycerol, alpha-ketoglutaric acid, lactic acid, malic acid, 6-phosphoglyceric acid, 3-phosphoglyceric acid, asparagine, aspartic acid, alanine, glutamine, glycine, isoleucine, leucine, proline, valine, arachidic acid, eicosapentaenoic acid, elaidic acid, heptadecanoic acid, linoleic acid, tetradecanoic acid, palmitic acid, pelargonic acid, stearic acid. Wherein a high concentration of 500ng/ml MXene had a greater effect on cell-targeted metabolites and a low concentration of 100ng/ml MXene had a lesser effect on cell-targeted metabolites than the blank (control, i.e., cells cultured and samples extracted and tested under the same conditions without MXene addition).
As can be seen from FIG. 3b, the low concentration of 100ng/ml MXene intervenes in the targeted metabolic pathways involved in HUVEC cells, mainly comprising nitrogen metabolism, glyoxylate and dicarboxylate metabolism, glutamine and glutamate metabolism, amino acid biosynthesis, arginine and proline metabolism, alanine, aspartate and glutamate metabolism, 2-oxocarboxylate metabolism. The differential metabolic pathways are relatively few and the individual metabolic pathways are less prone to change relative to the blank set.
As can be seen from FIG. 3c, a high concentration of 500ng/ml MXene intervenes in the targeted metabolic pathways involved in HUVEC cells, which mainly comprise valine, leucine and isoleucine metabolism, the tricarboxylic acid cycle, glyoxylate and dicarboxylate metabolism, glycerophospholipid metabolism, glycerolipid metabolism, fatty acid biosynthesis, glutamine and glutamate metabolism, unsaturated fatty acid biosynthesis, amino acid biosynthesis, arginine and proline metabolism, alanine, aspartate and glutamate metabolism, 2-oxocarboxylate metabolism. The number of different metabolic pathways is relatively large and the trend of each metabolic pathway is relatively large compared with that of the blank group.
The embodiments show that the processing conditions, the extraction conditions and the detection conditions provided by the method of the invention can effectively analyze the metabolome of the MXene nano material and organism interaction system. Compared with the traditional single metabonomics analysis technology, the combined metabonomics analysis method can comprehensively inspect the change rule and mechanism of metabonomics under MXene intervention from macroscopic and microscopic angles, gives consideration to comprehensiveness and specificity, can effectively disclose the influence principle of MXene on cell metabonomics, provides basis for evaluating the biological response characteristics of MXene, can be used for evaluating the influence of MXene on the metabolic pathways of the biological system under different biological systems and different environmental conditions, and has wide application prospect.
Claims (10)
1. An MXene bioresponse characteristic metabonomics analysis method is characterized by comprising the following steps:
(1) taking a biological sample to be analyzed after the biological sample reacts with the MXene nano material;
(2) extracting at least one of a non-targeted water-soluble metabolite sample, a non-targeted lipid-soluble metabolite sample, and a targeted water-soluble metabolite sample in a biological sample to be analyzed;
(3) detecting a non-targeted water-soluble metabolite sample and/or a non-targeted fat-soluble metabolite sample by liquid chromatography-mass spectrometry and/or detecting a targeted water-soluble metabolite sample by gas chromatography-mass spectrometry;
wherein, when the non-target water-soluble metabolite sample is detected, the metabolite sample is dissolved in water, and the chromatographic conditions are as follows: the mobile phase takes acetonitrile aqueous solution with volume fraction of 5-10% as phase A and acetonitrile aqueous solution with volume fraction of 90-95% as phase B; the chromatographic column adopts amido ethylene bridge hybrid particles as filler;
and/or, the non-targeted fat-soluble metabolite sample is dissolved in a dichloromethane/methanol mixed solution during detection, and the chromatographic conditions are as follows: the mobile phase takes acetonitrile water solution with volume fraction of 60-70% as phase A and acetonitrile solution with volume fraction of 90-95% isopropanol as phase B; the chromatographic column adopts C30 or C18 silica gel chromatographic column;
and/or, the targeted water-soluble metabolite sample is dissolved in methanol during detection, and the chromatographic conditions are as follows: the carrier gas is helium; the chromatographic column adopts polydimethylsiloxane particles as filler.
2. The analytical method of claim 1, wherein: in the step (1), the cells are human vascular endothelial cells, liver cells or kidney cells;
and/or the biological sample to be analyzed is a biological sample co-cultured with the MXene nano material, the co-culture time is more than or equal to 12 hours, and the preferred co-culture time is 24-48 hours.
3. The analytical method of claim 1, wherein: in the step (2), the extraction method of the non-target water-soluble metabolite sample comprises the following steps: washing the biological sample to be analyzed by using a phosphate buffer solution, adding trypsin to obtain a cell suspension, separating by using methanol, taking a supernatant, and drying to obtain the biological sample;
and/or the extraction method of the non-target fat-soluble metabolite sample comprises the following steps: washing the biological sample to be analyzed by using a phosphate buffer solution, adding trypsin to obtain a cell suspension, separating by using methanol and methyl tert-butyl ether, taking a supernatant, and concentrating to obtain the biological sample;
and/or the extraction method of the target water-soluble metabolite sample comprises the following steps: taking a non-target water-soluble metabolite sample, redissolving, derivatizing, separating again, taking supernatant, and drying to obtain the target-free water-soluble metabolite.
4. The analytical method of claim 3, wherein: in the step (2), the extraction method of the non-target water-soluble metabolite sample comprises the following steps: washing the biological sample to be analyzed by using a phosphate buffer solution, adding 0.25 wt.% of trypsin solution, adding 1-2 ml/10000000 cells, preferably 1ml/10000000 cells to obtain a cell suspension, adding 75-80% by volume of methanol aqueous solution, preferably 80% by volume of methanol aqueous solution, carrying out ultrasonic treatment for 20-30min, preferably 30min, carrying out vortex oscillation for 20-30min, preferably 20min, centrifuging at 10000-13000 rpm for 5-10 min, preferably 13000rpm for 5min, taking a supernatant, and drying to obtain the biological sample to be analyzed;
and/or the extraction method of the non-target fat-soluble metabolite sample comprises the following steps: washing the biological sample to be analyzed by using a phosphate buffer solution, adding 0.25 wt.% of trypsin solution, adding 1-2 ml/10000000 cells, preferably 1ml/10000000 cells, obtaining a cell suspension, adding methanol, performing vortex oscillation for 5-10 min, preferably 5min, sequentially adding methyl tert-butyl ether and water, performing centrifugation for 5-10 min at 10000-13000 rpm, preferably 5min at 13000rpm, taking a supernatant, and concentrating to obtain the biological sample;
and/or the extraction method of the target water-soluble metabolite sample comprises the following steps: taking a non-target water-soluble metabolite sample, redissolving with pyridine, derivatizing, centrifuging at 10000-13000 rpm for 5-10 min, preferably at 13000rpm for 5min, taking supernate, and drying to obtain the target compound.
5. The analytical method according to claim 3 or 4, wherein: the derivatization process comprises the following steps: adding pyridine solution of methoxylamine hydrochloride, and incubating at 60-65 deg.C for 90-100min, preferably at 60 deg.C for 90 min; then adding N-methyl-N- (trimethylsilyl) trifluoroacetamide, and incubating at 60-65 deg.C for 20-30min, preferably at 60 deg.C for 30 min.
6. The assay according to any one of claims 3 to 5, wherein: the targeted water-soluble metabolite sample comprises at least one of the following characteristic metabolites: aconitic acid, 4-aminobutyric acid, citric acid, dihydroxyacetone phosphate, fumaric acid, glutamic acid, glycerol-1-phosphate, α -ketoglutaric acid, lactic acid, malic acid, 6-phosphogluconic acid, 3-phosphoglyceric acid, asparagine, aspartic acid, alanine, glutamine, glycine, isoleucine, leucine, proline, valine, arachidic acid, eicosapentaenoic acid, elaidic acid, heptadecanoic acid, linoleic acid, tetradecanoic acid, palmitic acid, pelargonic acid and stearic acid.
7. The analytical method of claim 1, wherein: in the step (3), the chromatographic conditions for detecting the non-targeted water-soluble metabolite sample are as follows: the mobile phase takes acetonitrile water solution with volume fraction of 5% as phase A and acetonitrile water solution with volume fraction of 95% as phase B;
and/or, the chromatographic conditions for the detection of the non-targeted water-soluble metabolite sample further comprise: the phase A also contains 5-10mM ammonium acetate and 0.1-0.5 wt.% acetic acid, preferably contains 5mM ammonium acetate and 0.1 wt.% acetic acid, and the phase B also contains 5-10mM ammonium acetate and 0.1-0.5 wt.% acetic acid, preferably contains 5mM ammonium acetate and 0.1 wt.% acetic acid;
and/or the mobile phase takes acetonitrile water solution with volume fraction of 60% as phase A and acetonitrile solution with volume fraction of 90% isopropanol as phase B;
and/or, the chromatographic conditions for the detection of the non-targeted lipid-soluble metabolite sample further comprise: the phase a also contains 10-15mM ammonium formate and 0.1-0.5 wt.% formic acid, preferably 10mM ammonium formate and 0.1 wt.% formic acid, and the phase B also contains 10-15mM ammonium formate and 0.1-0.5 wt.% formic acid, preferably 10mM ammonium formate and 0.1 wt.% formic acid.
8. The analytical method according to claim 1 or 7, wherein: in step (3), the chromatographic conditions for detecting the non-targeted water-soluble metabolite sample further comprise: the elution gradient was:
and/or, the chromatographic conditions for the detection of the non-targeted lipid-soluble metabolite sample further comprise: the elution gradient was:
9. the analytical method of claim 1, wherein: in step (3), the chromatographic conditions for detecting the non-targeted water-soluble metabolite sample further comprise: the flow rate of the mobile phase is 200-300 mu l/min, preferably 300 mu l/min, the temperature of the chromatographic column is 35-40 ℃, preferably 35 ℃, and the sample amount is 2-5 mu l, preferably 5 mu l;
and/or, the chromatographic conditions for the detection of the non-targeted lipid-soluble metabolite sample further comprise: the flow rate of the mobile phase is 200-260 mu l/min, preferably 260 mu l/min, the temperature of the chromatographic column is 40-45 ℃, preferably 45 ℃, and the sample amount is 2-5 mu l, preferably 2 mu l;
and/or, the chromatographic conditions for targeted detection of a sample of water-soluble metabolites further comprise: the temperature of the chromatographic column is 35-40 ℃, preferably 35 ℃, the sample injection amount is 2-5 mul, preferably 5 mul, the flow rate of the carrier gas is 0.5-1ml/min, preferably 0.5ml/min, and the temperature of the sample injector is 250 ℃ and 300 ℃, preferably 250 ℃;
and/or, in the step (3), the mass spectrum detection conditions for detecting the non-targeted water-soluble metabolite sample are as follows: the scanning mode is that positive and negative ions are scanned simultaneously, the temperature of the capillary is 350-;
and/or the mass spectrum detection conditions for detecting the non-targeted fat-soluble metabolite sample are as follows: the scanning mode is that positive and negative ions are scanned simultaneously, the temperature of the capillary is 320-350 ℃, the preferred temperature is 320 ℃, the preferred flow rate of the sheath gas is 40-45 units, the preferred unit is 45 units, the flow rate of the auxiliary gas is 8-10 units, the preferred unit is 8 units, and the spraying voltage is 3.5-4kV, the preferred unit is 3.5 kV;
and/or the mass spectrum detection conditions for the detection of the targeted water-soluble metabolite sample are as follows: full scan mode m/z50-600, impact ionization energy 70-80eV, preferably 70eV, and solvent retardation set at 5.9-6min, preferably 5.9 min.
10. The analytical method of claim 1, wherein: in the step (3), the result obtained by the liquid chromatography-mass spectrometry and/or the gas chromatography-mass spectrometry detection is used for the analysis of the metabolic pathway, and the analysis of the metabolic pathway comprises the following steps:
(4.1) analyzing and identifying metabolites of the results obtained by the liquid chromatography-mass spectrometry and/or gas chromatography-mass spectrometry detection based on an R language algorithm to obtain statistical results;
(4.2) after normalizing the statistical results, performing principal component analysis, partial least squares discriminant analysis or orthogonal partial least squares discriminant analysis to group the metabolites;
(4.3) MetaboAnalyst analysis was performed by R language to identify representative metabolic pathways.
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