65 results about "Non targeted metabolomics" patented technology

The invention discloses a screening method of mango pulp processing mode markers and an identification method of mango pulp processing modes, and relates to the technical field of analytical chemistry. According to the method, non-targeted metabonomics is combined with quasi-targeted metabonomics and targeted quantitative analysis, so that the characteristic markers capable of accurately distinguishing mango pulp in different processing modes are systematically screened and verified for the first time. The feature marker screened by the method can be used for constructing a discrimination model of the mango pulp processing mode, high-precision and high-reliability processing mode discrimination is realized based on the established multi-model fusion discrimination method, the discrimination efficiency and accuracy of the mango pulp processing mode are greatly improved, and the method is suitable for popularization and application. And a new technical means and theoretical basis are provided for product quality control and market supervision.

The invention discloses a method and a device for monitoring the stability of an anaerobic digestion system in real time. The method comprises the following steps: 1, carrying out non-targeted metabonomics analysis on the anaerobic digestion mVOCs category by adopting headspace solid-phase microextraction in combination with gas chromatography-high resolution mass spectrometry; 2, screening differential mVOCs markers based on principal component analysis and orthogonal partial least squares discriminant analysis; and 3, constructing a system stability real-time monitoring system by using an electronic nose sensor array, and when the difference mVOCs marker concentration deviates from a threshold value or difference categories are continuously accumulated, triggering early warning and recommending an optimization strategy by the system. The method and the device can monitor the state of the anaerobic reactor in real time, early warn the methane production inhibition risk in advance compared with traditional parameters (pH, volatile fatty acid and the like), improve the biogas yield and reduce the operation and maintenance cost, are suitable for intelligent management of anaerobic digestion scenes of kitchen garbage, municipal sludge, agricultural waste and the like, and can also be expanded to other anaerobic biological fermentation fields.

The invention discloses a method for analyzing component difference between Maotai-flavor yeast and yeast-making wheat by using non-targeted metabonomics. The method comprises the following steps: S1, pre-treating a sample; s2, detecting each sample by adopting the combination of an ultra-high performance liquid chromatograph and a quadrupole time-of-flight mass spectrometer; s3, acquiring original data, performing peak extraction, peak alignment and normalization by adopting metabonomics data analysis software, and evaluating the overall difference and intra-group variation among sample groups by adopting principal component analysis; constructing a grouping discrimination model through discriminant analysis of an orthogonal partial least square method; determining differential metabolites of the two groups of samples by taking variable projection importance (VIP) greater than 1 and statistical significance P less than 0.01 as a primary screening standard and combining a secondary screening standard that the difference multiple log2FC greater than 2 is up-regulated and the difference multiple log2FC less than-2 is down-regulated; s4, performing compound structure and category annotation on the screened differential metabolites through a metabolome database; and performing pathway enrichment analysis by adopting a statistical test method, and determining a core metabolic pathway enriched by the differential metabolites.

The invention discloses an application of astaxanthin in preparation of a regulator for improving the gentisic acid level. On the basis of non-targeted metabonomics analysis, it is found for the first time that in the SAP pathogenesis process, the level of a flora metabolite, namely gentisic acid (GA), in intestinal contents is remarkably reduced, and in-vivo gentisic acid level can be remarkably callback through astaxanthin intervention. Further research proves that exogenous supplement of gentisic acid can effectively simulate the protection effect of astaxanthin, including improvement of pancreatic tissue pathological damage, reduction of serum lipase and amylase activity, and inhibition of systemic inflammatory response (down-regulation of IL-1beta, IL-6 and TNF-alpha and up-regulation of IL-10). The invention not only discloses a new mechanism that astaxanthin plays a therapeutic role through an'intestinal flora-metabolite 'axis, but also determines that gentisic acid is used as a novel drug target for treating SAP, and constructs a new method for screening drugs for treating SAP according to the novel drug target.

The invention belongs to the technical field of compound analysis and identification, and discloses application of a metabonomics analysis technology to identification of lycium seed oil. According to the metabonomics analysis technology, the characteristic components of the lycium seed oil are identified through Log2 Fold Channel and VIP values, and the screening conditions for identifying the characteristic components of the lycium seed oil are | Log2 Fold Channel | > 1.5, and VIP < gt >; the method specifically comprises the steps of sample preparation, non-targeted metabonomics analysis, extraction and identification of characteristic peaks, similarity analysis, difference analysis and screening of differential markers. According to the method, a non-targeted metabonomics analysis method is adopted, various metabolic components in the lycium barbarum seed oil can be undiscriminately covered, the limitation that a traditional identification technology only aims at a few indexes is broken through, the unique characteristic components of the lycium barbarum seed oil can be accurately screened out, and the accuracy and specificity of an identification result are greatly improved.

The invention belongs to the technical field of drug detection, and particularly relates to a method for detecting lycium barbarum glycopeptide metabolites in rat plasma and tissues based on non-targeted metabonomics. According to the method, after rat lycium barbarum glycopeptides are administered through intragastric administration, blood, liver, intestine, lung and brain tissue samples after administration are collected. A UPLC-Q-TOF-MS (Ultra Performance Liquid Chromatography-Quadrupole Time of Flight Mass Spectrometry) analysis method is combined with a statistical analysis method comprising principal component analysis (PCA) and orthogonal-partial least squares discriminant analysis (OPLS-DA) to carry out in-vivo metabonomics analysis on the wolfberry glycopeptide. Then, based on a human metabolome database (HMDB), lycium barbarum glycopeptide differential metabolite is searched, so that the pharmacological action mechanism of the lycium barbarum glycopeptide is clarified from the perspective of metabolism, and a foundation is laid for deep research and development of the medicinal value of the lycium barbarum glycopeptide in future.

The invention discloses an excrement metabolism marker for predicting spontaneous premature delivery based on UHPLC-MS (Ultra High Performance Liquid Chromatography-Mass Spectrometry) and application, and belongs to the technical field of biological medicines. According to the premature pregnant woman excrement metabolite specific biomarker and the application thereof, the premature pregnant woman excrement metabolite specific biomarker is screened out through a non-targeted metabonomics technology, and the marker is 1-hydroxyl vitamine d2, Mirtazapine n-oxide, Tetraethene glycol or a combination of the 1-hydroxyl vitamine d2, the Mirtazapine n-oxide and the Tetraethene glycol. A premature delivery prediction model established by using the marker is high in sensitivity and good in specificity, and a reference basis is provided for early prediction and accurate prevention of spontaneous premature delivery.

The invention provides application of acetylcholine and 1-carboxyl-6-hydroxy-3, 4-dihydro-beta-carboline (the code in the attached drawing of the abstract is CHEMBL461889) in early pregnancy diagnosis, non-targeted metabonomics detection and analysis are carried out on the urine of pregnant and non-pregnant sows by virtue of a liquid chromatography-mass spectrometry technology; the two metabolic markers capable of being used for early pregnancy diagnosis of the sows are screened out by introducing two deep learning models for joint analysis, the AUC values of ROC curves of the two metabolic markers are 1, the accuracy is very high, and the pregnancy state of the sows can be accurately judged only 18 days after the sows are bred. The invention provides a novel effective sow early pregnancy diagnosis method for the pig breeding industry, and has important significance for reducing the breeding cost.

The invention provides an application of metabolites in sow vaginal secretion in early pregnancy diagnosis, and finds that three metabolic molecules can be used as markers for the early pregnancy diagnosis of sows for the first time on the basis of non-targeted metabonomics and machine learning conjoint analysis. According to the present invention, the metabolic markers are respectively INDOLEPROPIONIC ACID (indolepropionic acid), cis-Amonitate (cis-Amonitate) and 4-p-Coumaroylquinic acid (4-p-coumaroylquinic acid), the ROC curve AUC values of the metabolic markers are respectively 0.88, 0.92 and 0.77, and the metabolic markers have excellent diagnosis performance during the combination diagnosis. The pregnancy diagnosis is carried out by adopting the vaginal secretions of the sows 18 days after hybridization, the effective pregnancy diagnosis time is advanced by 5-8 days on the basis of a wave diagnosis method, and the method has important significance for reducing cost and increasing ultrasonic efficiency in live pig feeding.

The invention relates to the technical field of food identification, in particular to a method for identifying sheep milk and milk based on metabonomics, and aims to solve the industrial pain point that cheap milk is doped into current high-end sheep milk products and is difficult to detect through conventional physicochemical indexes, and the problems that existing protein, DNA and other identification methods are insufficient in sensitivity, complex in operation and the like. According to the invention, a non-targeted metabonomics analysis strategy is innovatively adopted. The saliency difference metabolites between the sheep milk and the milk are systematically screened from the omics level, and rapid, high-sensitivity and high-specificity identification on the authenticity of the sheep milk and whether the sheep milk is mixed with the milk is realized. According to the invention, a key technical basis and a material core are provided for developing corresponding detection products and market supervision methods.

The invention relates to the technical field of health assessment, in particular to a dynamic metabolism difference modeling method for a premature infant and a full-term infant, a marker and application, and the method comprises the following steps: obtaining a data set; the data set comprises neonatal plasma samples of a to-be-detected group and a control group; preprocessing the plasma sample in the data set; carrying out non-targeted metabonomics detection on the pretreated plasma sample by adopting ultra-high performance liquid chromatography-time-of-flight mass spectrometry to obtain mass spectrometry original data; preprocessing the mass spectrum original data, performing multivariate statistical analysis on the preprocessed mass spectrum data, and constructing a plasma metabolite discrimination model; and based on the plasma metabolite discrimination model, evaluating the metabolic disorder degree and health risk of the premature infant. According to the method, the metabolic disorder degree and the health risk of the premature infant are evaluated by constructing the plasma metabolite judgment model and based on the differential metabolite characteristics in the plasma metabolite judgment model, and the early screening of the health condition of the premature infant is realized.

The invention provides a metabolic marker combination for identifying okra related species, an identification method and application of the metabolic marker combination, and belongs to the technical field of drug detection. The identification method provided by the invention comprises the following steps: carrying out non-targeted metabonomics detection on dry powder samples of Abelmoschus manihot (L.) Medik., Abelmoschus moschus (L.) Meduli, Abelmoschus sagittifolius (L.) Merr. And Abelmoschus esculentus (L.) Moench by adopting ultra-high performance liquid chromatography-tandem mass spectrometry (UPLC-MS / MS), so as to obtain metabolite data, and carrying out quantitative analysis on the metabolite data, so as to obtain a sample of the Abelmoschus manihot (L.) Meduli, the sample of the Abelmoschus moschus (L.) Merr. And carrying out mass spectrum qualitative and quantitative analysis on metabolite data, and screening out common differential metabolites among the four plants as characteristic metabolites to realize variety identification of okra related species. The method can effectively distinguish okra species with similar morphologies, and has application value in traditional Chinese medicinal material original identification, germplasm resource screening and variety purity detection in a seedling raising stage.

The application discloses a metabolic marker for distinguishing metabolic syndrome and simple obesity and application thereof. The marker comprises eight metabolites, i.e. glycocholic acid, lithocholic acid, linoleic acid, valine, leucine, alanine, serine and glycine. The application performs non-targeted metabolomics analysis on serum of metabolic syndrome and simple obesity patients by liquid chromatography mass spectrometry, finds eight metabolites with significant difference between the two, and finds that the eight metabolic markers have high AUC when used for diagnosing and distinguishing metabolic syndrome patients or simple obesity patients alone or in combination.

The application belongs to the technical field of biological medicine, and discloses application of NP in preparation of a preparation for regulating metabolism of the intestines of senile type 2 diabetes. The NP is formed by hydrogen bond combination of a peptide from soft-shelled turtle eggs with naringenin in a mass ratio of 100:1, and the mass of the peptide is less than 3 kDa; the preparation is used for regulating phenotype-related metabolic modules and intestinal micro-ecological-related metabolic modules, remodeling the intestinal metabolic regulation network taking differential metabolites as a bridge, and thus systemically improving metabolic disorders related to senile type 2 diabetes. It is found that NP intervention can obviously correct abnormal total metabolic profiles of feces of senile type 2 diabetes mice, and make the disease type metabolic profile shift to a new steady state of intervention type. Non-targeted metabolomics analysis by LC-MS / MS shows that the overall metabolic profile of the high-dose NP group is closer to that of the classic hypoglycemic drug metformin group, indicating that NP has a significant metabolic remodeling capacity.

The invention discloses an application of intestinal flora metabolite salicylic acid as a predictive marker of Escherichia coli calf diarrhea. The obviously up-regulated metabolite salicylic acid is screened out from the diarrhea calf feces through a non-targeted metabonomics technology, and in a group of new independent samples, it is verified through an ELISA test that the salicylic acid concentration of the diarrhea calf feces is obviously higher than that of a healthy group. ROC curve analysis shows that the area under curve (AUC) of SA for predicting escherichia coli calf diarrhea is 0.8148, and the method has good prediction capability. The invention provides a non-invasive, cheap, rapid and high-specificity prediction method, can be used for early warning and auxiliary diagnosis of Escherichia coli calf diarrhea, and has important significance for guiding clinical precise medication and reducing the death rate of calves.

The invention relates to the technical field of food detection, and particularly discloses a method for identifying Luzhou-flavor liquor, which comprises the following steps: acquiring a plurality of different types of Luzhou-flavor liquor samples as a training set; carrying out non-targeted metabonomics analysis on the training set samples by adopting ultra-high performance liquid chromatography-tandem mass spectrometry, detecting non-volatile compounds in the training set samples, and obtaining composition and relative content data of the training set samples; based on the training set sample information and the non-volatile compound detection result, establishing a qualitative identification model of the Luzhou-flavor liquor by using an orthogonal partial least square discriminant analysis method; and performing non-targeted metabonomics analysis on a to-be-detected Luzhou-flavor liquor sample, and inputting obtained data into the qualitative identification model of the Luzhou-flavor liquor to obtain category information of the Luzhou-flavor liquor. According to the method provided by the invention, the established qualitative identification model of the Luzhou-flavor liquor based on different alcoholic strengths, producing areas and brands is reliable and good in predictability, and a new method can be provided for the qualitative identification of the Luzhou-flavor liquor.

The invention belongs to the technical field of biomedicine, and particularly relates to a method for detecting potential biomarkers of myocardial of an HFpEF mouse based on non-targeted metabonomics, which comprises the following steps: constructing an HFpEF mouse model by combining high fat diet with L-NAME, setting a conventional feeding control group, monitoring myocardial glucose metabolism through longitudinal [18F] FDG PET / CT, collecting myocardial tissues, and performing non-targeted metabonomics detection. And screening differential metabolites through Foldchange greater than or equal to 1.2 or less than or equal to 0.83 and p less than 0.05, and carrying out correlation analysis on the differential metabolites and [18F] FDG SUVmean to obtain 25 potential biomarkers. According to the method, the steps are clear and repeatable, the marker is directly related to myocardial energy metabolism, the diagnosis specificity is improved, and a support is provided for HFpEF targeted therapy research and development and molecular mechanism research.

The invention relates to the technical field of biomedicine, in particular to a group of key biomarkers for predicting endometrial receptivity, including specific microbial strains and metabolites, and a prediction model containing the markers. The method comprises the following steps: collecting a uterine cavity lavage fluid sample, carrying out 16S rRNA gene sequencing and non-targeted metabonomics analysis, and screening out eight key microbial strains and eight key metabolites; based on the markers, the following diagnostic models are constructed: a model only based on eight microbial strains; a model based on only eight metabolites; a combined microorganism and metabolite model; and a clinical data model is further combined. According to the method, a microbiome and metabolome multi-omics conjoint analysis strategy is adopted, strict screening is carried out in combination with LASSO regression, SVM-RFE and other machine learning algorithms, and the obtained biomarker is high in specificity. The constructed model, especially a combined model, shows high prediction precision and good calibration degree through verification of various curves.

The application discloses a kind of based on metabolic pathway analysis's Iresine heratensis fermentation quality regulation method, it is related to food biotechnology field, including, the sample of different varieties Iresine heratensis is obtained, carries out non-targeted metabolomics analysis, obtains metabolite spectrum data;The metabolite spectrum data carries out difference analysis, constructs key difference metabolite dataset;Metabolic pathway enrichment analysis is carried out to the key difference metabolite dataset, determines core metabolic pathway;Regulate the process parameter in Iresine heratensis fermentation process, obtain the fermentation product after regulation;The quality of the fermentation product after regulation is verified, feedback optimization the process parameter, form closed loop quality regulation method;The application is determined core metabolic pathway by constructing key difference metabolite dataset and enrichment analysis, realizes from traditional experience type fermentation process optimization to the change of accurate regulation based on metabolic mechanism, solves the problem that fermentation quality in prior art is greatly blind, target is not clear.

This invention discloses metabolic markers for the early auxiliary diagnosis of colorectal cancer in the field of biomedical technology and their applications. The development and utilization of such metabolic markers will provide technical support for the early auxiliary diagnosis of colorectal cancer. Using a non-targeted metabolomics detection method, this invention screened and verified the application value of 10 colorectal cancer metabolites in differentiating colorectal cancer patients from healthy controls, and the application value of 7 metabolites in differentiating precancerous lesions from healthy controls, which can significantly improve the level of early diagnosis of colorectal cancer.

The invention relates to the technical field of reproduction and metabolism, and discloses a plasma marker identification method for fetal intrauterine growth restriction, which comprises the following steps: firstly, designing nested case contrast research: taking the fetal intrauterine growth restriction (FGR) as a case group, pairing according to 1: 1 of pregnant mother blood sampling gestational week, neonatal gestational age and sex tendency index, and selecting a contrast group as a child suitable for gestational age; establishing an inclusion and exclusion standard of the research object; and then determining the sample size. According to the plasma marker identification method for the limited intrauterine growth of the fetus, on the basis of a non-targeted metabonomics screening mode, an FGR-related maternal plasma small molecule metabolite network is analyzed, a novel biomarker is found, and a new thought is provided for early screening of the FGR; the marker has high sensitivity and specificity in FGR identification, the research result provides a powerful molecular biology basis for early identification and intervention of FGR, and mother and infant health and social prosperous development are promoted.

The invention relates to the technical field of agricultural microorganisms and fermentation engineering, and discloses a method for evaluating the growth promoting effect of saline-alkaline tolerant growth-promoting compound bacteria on soybeans, which comprises the following steps: preparing Klebsiella GF2 and pseudomonas GF7 through fermentation, compounding to form a GFM compound bacteria system, setting a saline-alkaline gradient pot experiment, combining rhizosphere inoculation and critical period supplementary application, and carrying out saline-alkaline tolerant growth-promoting compound bacteria on soybeans to obtain the saline-alkaline tolerant growth-promoting compound bacteria. The system monitors growth indexes of soybeans in the whole growth period and calculates comprehensive growth promoting indexes; high-throughput sequencing, fluorescence in situ hybridization and non-targeted metabonomics technologies are integrated, and a rhizosphere microbial community structure, functional bacterium colonization and a soil key metabolic pathway are analyzed; finally, multi-source data are coupled through multivariate statistics, the growth promoting contribution of the fungicide is quantified, and the stability of the cross-stress level of the fungicide is evaluated. A standardized evaluation system which is clear in mechanism and can be quantitatively compared is constructed, the blank of systematic evaluation of microbial agents in the saline-alkali environment is filled, and a key tool and theoretical support are provided for efficient strain screening and saline-alkali soil bioremediation technology popularization.

The invention belongs to the technical field of biological medicine, and particularly discloses a construction method of a metabolite screening platform for regulating and controlling a T cell killing function, tumor cells expressing OVA and CD8 + T cells are co-cultured, and the co-culture is combined with a non-targeted metabonomics technology to form the metabolite screening platform for regulating and controlling the T cell killing function. The metabolite screening platform for regulating and controlling the killing function of the T cells is based on an in-vitro killing model which is clear in antigen, high in specificity and good in repeatability; the model and a high-sensitivity metabolite detection technology can be integrated; key metabolites which change remarkably in the tumor killing process of the T cells can be screened systematically without deviation; a metabolic pathway or a specific molecule which can be used as a biomarker for predicting the curative effect and can also be used as an intervention target to enhance the T cell function can be identified.

The invention discloses an anthocyanin non-target metabonomics detection method based on LC-HRMS (Liquid Chromatography-High Resolution Mass Spectrometry), which comprises the following steps: respectively extracting effective components from samples, and detecting by adopting an ultra-high performance liquid chromatography-mass spectrometry combined method after extraction, the obtained original data is detected, the established anthocyanin database is used for screening, difference analysis is completed, and P value is screened out; 0.05 and VIPgt; 1 is taken as an anthocyanin differential metabolite. Based on a non-targeted metabonomics method, 34 anthocyanidin substances are identified by UPLC-MSMS, then the anthocyanidin differential metabolites are obtained by an OPLS-DA method, and an important basis can be provided for a molecular mechanism of anthocyanidin formation.

The present invention provides a fecal biomarker combination for the early diagnosis of Sjogren's syndrome. The method is as follows: collect fecal specimens of the research subjects; collect fecal metabolites; use UPLC / Q-TOFMS technology to collect non-targeted metabolomics data of fecal metabolites to obtain a metabolic map; use XCMS to preprocess the metabolic map data; perform multivariate analysis to screen for differential metabolites and identify them in combination with relevant databases, retain endogenous differential metabolites, and further screen the endogenous differential metabolites using R language and establish a prediction model for verification to determine the biomarker combination for differentiating SS patients from healthy controls. Based on the metabolomics analysis of the feces of SS patients and healthy controls by UPLC / Q-TOFMS, a fecal biomarker combination for the early diagnosis or prevention of Sjogren's syndrome is obtained, which has high sensitivity and specificity, good predictability, and can be used for the early diagnosis of SS.

This invention belongs to the fields of bioinformatics and medical testing technology, specifically relating to a combination of biomarkers related to the postoperative prognosis of colorectal cancer and their application and prediction system. This invention, through 16S rRNA gene sequencing of tumor mucosal samples from colorectal cancer patients, combined with long-term postoperative follow-up data and screening, found that *Peptostreptococcus*, *Fusobacterium*, *Bacteroides*, *Porphyromonas*, and *Prevotella* are closely related to postoperative recurrence of colorectal cancer, with an AUC of 0.81 for assessing postoperative recurrence. Based on this, this invention conducts non-targeted metabolomics analysis, finding that combining alanine glutamate, putrescine, arginine, histidine, and sebacic acid with the above microbial biomarkers can improve the AUC to 0.91, significantly enhancing accuracy, specificity, and precision. This enables prognostic stratification of recurrence-free survival in colorectal cancer patients, demonstrating higher predictive efficacy and stability.

The invention discloses a liver metabolism composition for dairy cow subclinical ketosis risk assessment and application of the liver metabolism composition. The composition comprises at least two of metabolites of LysoPE (18: 2), Gpcho (16: 1 / 18: 1), cis-9-hexadecenoic acid and the like, preferably LysoPE (18: 2) and Gpcho (16: 1 / 18: 1). According to the present invention, the LC-MS non-targeting metabonomics technology finds that the expression of the composition in the liver of the cow with the subclinical ketosis is significantly abnormal, and the composition is enriched in key pathways such as glycerophospholipid metabolism; the invention also provides a kit containing the marker combination and a non-diagnostic purpose detection method thereof. The composition can be used for preparing a kit for assisting in distinguishing the subclinical ketosis risk, or can be used as a biomarker for drug screening, provides an earlier and specific solution for solving the problem that the existing serum BHBA detection window period is lagged, and has important significance for healthy breeding of dairy cows.

The application belongs to the field of biomedical technology, and aims to solve the problems of lack of metabolic typing characteristics in the current ESCC molecular typing method, lack of esophageal squamous cell carcinoma molecular typing method based on proteomics and metabolomics, and provides an esophageal squamous carcinoma ESCC molecular typing marker based on DIA proteomics and non-targeted metabolomics and its application. The marker is a combination of 4 proteins and 2 metabolites, the 4 proteins are: hexokinase 3 (HK3), Sec1 family domain protein 1 (SCFD1), septin 5 (SEPTIN5), and signal sequence receptor alpha subunit (SSR1); the 2 metabolites are creatine and 2-deoxy-D-glucose (2'DG). The application fills the gap of the molecular typing method based on proteomics and metabolomics in the field of esophageal squamous carcinoma research, and the proposed molecular typing model can be used as a method for diagnosis, treatment and prognosis evaluation of esophageal squamous carcinoma patients.

The invention belongs to the technical field of metabonomics, and particularly relates to a detection method of rheum tanguticum tissue specific metabolites and a comprehensive development and utilization method of rheum tanguticum, the detection method comprises the following steps: grinding roots, stems, leaves and seeds of rheum tanguticum to obtain powder samples of each tissue; mixing the powder sample with the extracting solution, extracting by adopting an ultrasonic-assisted method, and standing, centrifuging and filtering the obtained extract to obtain supernate; and carrying out liquid chromatography-tandem mass spectrometry analysis on the supernate, collecting data, and screening differential metabolites in combination with multivariate statistics and metabolic pathway enrichment analysis. According to the invention, a non-targeted metabonomics technology is adopted, composition differences of metabolites in various tissues of rheum tanguticum are systematically analyzed, and tissue-specific marker metabolites are screened out. The tissue distribution rule of the secondary metabolite on the metabolome level is disclosed, and a scientific basis is provided for medicine part selection, non-medicine tissue utilization, molecular breeding and the like.

The invention discloses a method for detecting metabolite containing phosphate radicals, which is characterized in that a mass spectrum label with stable and characteristic chlorine isotope distribution is introduced through a chlorination reagent derivatization strategy, so that a derivatization product can be subjected to rapid and high-specificity preliminary identification based on primary mass spectrum data. By combining with an automatic data mining program specially developed for this purpose, high-throughput and accurate screening and locking of potential phosphate radical-containing metabolites from massive and complex non-targeted metabonomics original data are realized, and the data analysis efficiency and reliability are greatly improved. The method is successfully applied to analysis of actual biological samples such as cholestasis disease models, efficient identification and accurate quantification of various key metabolites such as nucleotide and sugar phosphoric acid are achieved, disturbance of related metabolic pathways is disclosed, and a powerful innovative analysis tool is provided for disease mechanism research and biomarker discovery.