32 results about "Non targeted metabolomics" patented technology

The invention discloses a GC-MS-based plant non-targeted metabolomics sample pretreatment method. The method comprises the steps of 1) mixing up a plant sample, an internal standard substance and a hydrophilic organic solvent, wherein the hydrophilic organic solvent is pre-cooled to be -20 to 4 DEG C; cooling the obtained mixture to be -80 to -10 DEG C, grinding, crushing and conducting the supersonic extraction in the ice-water bath; 2) then respectively adding a lipophilic organic solvent and water, uniformly mixing up, conducting the supersonic extraction in the ice-water bath, conducting the high-speed centrifugation at the temperature of 0 to 16 DEG C, obtaining the aqueous phase and evaporating; 3) adding an oximation reagent, and conducting the oximation reaction at the temperature of 30 to 45 DEG C; 4) finally adding a derivatization reagent and n-hexane, and conducting the derivatization reaction at the temperature of 60 to 80 DEG C. According to the technical scheme of the invention, based on the above pretreatment method, the primary metabolites of a plant sample can be fully extracted, so that the abundant metabolite spectrum data information can be obtained. Meanwhile, both the change of metabolites during the extraction process, and the pollution of liposoluble substances to a gas chromatographic column can be avoided as much as possible. Therefore, the better sample reproducibility is realized.

The invention discloses a method for screening and characterizing a metabolite-protein interaction system based on metabolomics and a structural mass spectrometric technique; a heterologously expressed tagged target protein is immobilized through an affinity immobilization method, then, the target protein is incubated with a metabolite extract, and finally, after being separated, denatured and eluted, the target protein-metabolite complex is subjected to non-targeted metabolomics analysis, and the complex is compared with a control group (an affinity vector without immobilized protein) so as to screen a metabolite with potential interaction with the target protein. Afterwards, the potential interaction system is directly verified using structural mass spectrometry. The binding method enables high-throughput screening of metabolites with potential interaction with the target protein, and also, direct characterization of the structural mass spectrometry can be used to screen out false positive interaction results that are probably introduced during indirect characterization. The method is a reliable high-throughput research tool for protein-metabolite interactions.

The invention discloses a disease prediction method and system based on medical big data. The method comprises the following steps: importing mass spectrum data of mainstream mass spectrum instrumentmanufacturers, and completing the conversion from original mass spectrum data of the manufacturers to a general data format; realizing automatic labeling and qualitative analysis of endogenous compounds in the mass spectrum through a metabolite compound database according to the spectrum information of the endogenous metabolites of the individual human body and a compound search matching algorithm; wherein the loading is used for effectively managing huge and complex human body metabonomics samples and carrying out data mining and modeling, and the loaded data types mainly comprise targeted and non-targeted metabonomics mass spectrum original data and labeling results; performing standardized cleaning, compound alignment and qualitative and quantitative analysis on complex multi-sample data, and performing correction by adopting a multi-class algorithm; and adopting a machine learning model training set algorithm with different types of mass spectrum data processing characteristics tocomplete the whole process of training, publishing and maintaining the user disease prediction model.

The invention relates to a blood metabolite marker for diagnosing multiple myeloma, and application. Untargeted metabolomics detection are firstly performed on a healthy donor (HD), and the marrow andperipheral blood sample of a primary-care patient of multiple myeloma (mm) to screen out 5 metabolites that have significant differences in marrows and peripheral blood samples, wherein the 5 metabolites are respectively L_Proline, L_Aspartic acid, L_Cystine, Stearic acid, and Palmitic acid. The analysis result of the ROC curve shows that the 5 different metabolites as a whole can more accuratelydiagnose MM. Targeted metabolomics detection further confirmed that the metabolome composed of these 5 metabolites is an ideal MM diagnostic method. The invention can accurately diagnose MM and is ofgreat significance for promoting the diagnosis of MM in basic research and clinical treatment.

The invention provides a method for identifying 25 or less pseudo-ginseng and 80 or less pseudo-ginseng based on non-targeted metabonomics, and belongs to the field of analysis and detection of traditional Chinese medicinal materials, the method comprises the following steps: S1, extracting a pseudo-ginseng metabolite by using a methanol solution as a solvent to obtain a test sample; S2, carrying out non-targeted component determination on the pseudo-ginseng metabolite extracting solution by adopting a UHPLC LTQ Oribitrap MS (Ultra High Performance Liquid Chromatography LTQ Oribitrap Mass Spectrometry) combined technology to obtain original data; S3, performing preprocessing and multivariate statistical analysis on the original data in sequence; and S4, screening differential metabolites by taking the variable importance projection index as a screening index. According to the method, the differential metabolites of the pseudo-ginseng of different specifications are screened on the basis of integral analysis of the pseudo-ginseng, the UHPLC LTQ Oribitrap MS technology is combined with non-targeted metabonomics and principal component analysis, the method can be used for accurately distinguishing the pseudo-ginseng of different commodity specifications, and a theoretical basis is provided for specification standards of medicinal material commodities in the pseudo-ginseng market.

The invention discloses a method for detecting imatinib metabolite in plasma of GIST patients based on non-targeted metabonomics, which comprises the following steps: collecting peripheral venous blood of a plurality of GIST patients who do not take IM or take IM regularly for a long time, processing the peripheral venous blood, performing non-targeted detection on a sample to be detected by adopting a UPLC-QTOF / MS (Ultra Performance Liquid Chromatography-Quadrature Time of Flight / Mass Spectrometry) combined technology to obtain original data of the metabolite in the plasma, performing unsupervised principal component analysis (PCA), orthogonal partial least squares discriminant analysis (OPLS-DA), Student's t-test and difference multiple analysis (FoldChange) on original data, searching differential metabolites, and searching a database to qualitatively determine the GIST metabolic marker. Technical support is provided for effective treatment of GIST patients suitable for IM treatment, and a foundation can be laid for effectiveness, pertinence, noninvasive screening and marker characterization of drug treatment after confirmation of digestive tract tumors.

The invention discloses a GC-MS-based plant non-targeted metabolomics sample pretreatment method. The method comprises the steps of 1) mixing up a plant sample, an internal standard substance and a hydrophilic organic solvent, wherein the hydrophilic organic solvent is pre-cooled to be -20 to 4 DEG C; cooling the obtained mixture to be -80 to -10 DEG C, grinding, crushing and conducting the supersonic extraction in the ice-water bath; 2) then respectively adding a lipophilic organic solvent and water, uniformly mixing up, conducting the supersonic extraction in the ice-water bath, conducting the high-speed centrifugation at the temperature of 0 to 16 DEG C, obtaining the aqueous phase and evaporating; 3) adding an oximation reagent, and conducting the oximation reaction at the temperature of 30 to 45 DEG C; 4) finally adding a derivatization reagent and n-hexane, and conducting the derivatization reaction at the temperature of 60 to 80 DEG C. According to the technical scheme of the invention, based on the above pretreatment method, the primary metabolites of a plant sample can be fully extracted, so that the abundant metabolite spectrum data information can be obtained. Meanwhile, both the change of metabolites during the extraction process, and the pollution of liposoluble substances to a gas chromatographic column can be avoided as much as possible. Therefore, the better sample reproducibility is realized.

The invention discloses a method for screening a prostate cancer PSA diagnosis gray region serum marker. The method comprises the following steps of S10, collecting a sample; S20, carrying out metabonomics pretreatment; S30, arranging a to-be-tested sample analysis operation sequence; S40, carrying out a non-targeted metabonomics experiment; S50, qualitatively detecting the original data of metabolites; S60, screening differential metabolites among the samples to be detected; S70, carrying out metabolic pathway analysis; S80, screening serum metabolites, and determining candidate diagnostic markers; and S90, determining a diagnostic marker. The invention provides a biomarker which is efficient, minimally invasive and capable of accurately screening prostatic cancer and distinguishing prostatic hyperplasia, so that the procedure for detecting the prostatic cancer is simplified, and complications caused by rectal ultrasound guided prostatic biopsy diagnosis are avoided.

The invention relates to a hydroxyl metabolite derivatization method and a non-targeted metabonomics efficient analysis method. The hydroxyl metabolite derivatization method comprises the steps that 1, hydroxyl metabolite extraction is conducted on a sample to be detected through a first solvent, then drying is conducted to remove the first solvent, and a dried sample is obtained; and 2, the dried sample is mixed with a second solvent to dissolve the dried sample, then 4-dimethylaminopyridine and dansyl chloride are added, the solution and the added substances are well mixed, and heating is performed for incubation; and after incubation is completed, sodium hydroxide is added, then heating is conducted for incubation, finally formic acid is added, and a derivatizated sample is obtained. According to the non-targeted metabonomics efficient analysis method, 12C labeling and 13C labeling are synchronously carried out by adopting the derivatization method, so that the metabolite detection sensitivity is improved, more metabolite can be detected at the same time, and the metabolite coverage rate is higher; and the detected metabolite is a peak pair, so that the influence caused by instrument drift and matrix is reduced, and the quantification is more accurate.

The invention relates to the field of nano material preparation and metabonomics analysis, in particular to a metabonomics analysis method of a multi-dimensional MXene nano material. The metabonomics analysis method provided by the invention comprises the following steps: (1) carrying out DESI-MSI scanning on a biological sample to obtain DESI-MSI detection results of water-soluble metabolites and fat-soluble metabolites; the biological sample being collected from an animal model given with a multi-dimensional MXene nanomaterial; wherein the DESI-MSI detection conditions comprise that in a positive mode, the voltage is 5-6 kV; in the negative mode, the voltage being -4.5 to -5 kV; the spatial resolution being 50 to 80 [mu] m; the solvent spray being a 90-95% v / v methanol aqueous solution containing 0.1-0.5% v / v formic acid; and (2) carrying out space metabonomics analysis on the DESI-MSI detection result. In addition, the metabonomics analysis method disclosed by the invention can also comprise the step of carrying out non-targeted metabonomics detection and analysis on the cells co-cultured by the multi-dimensional MXene nano material. The method provides a basis for evaluating a multi-dimensional MXene nano material synthesis technology and biological response characteristic evaluation, and has a wide application prospect.

The invention discloses a method for evaluating a toxicity effect mechanism, and relates to the field of cytotoxicity evaluation methods. The method includes the following steps: after a biological sample is exposed to poison, screening out differential metabolites and differential genes through metabolomics detection and analysis and transcriptomics detection and analysis, and constructing a metabolic network composed of the differential metabolites and the differential genes through spearman correlation coefficient analysis to evaluate the toxic effect mechanism; the metabonomics detection and analysis comprises the following steps: performing non-targeted metabonomics detection and analysis to obtain differential metabolites of the biological sample after being exposed to the poison, and screening out a metabolic pathway having the highest correlation with the differential metabolites; and performing targeted metabonomics detection analysis on the basis of the non-targeted metabonomics differential metabolites to obtain the determined differential metabolites and related metabolic pathways.

The invention belongs to the technical field of oolong tea identification, and relates to application of a metabonomics analysis technology to identification of Danxiang Dancong tea. In the metabonomics analysis technology, characteristic components of the Danxiang Dancong tea are identified through Log2 Fold Change, adj.p and VIP values, and the screening conditions are |Log2 Fold Change|>1.5, adj.p<0.01, and VIP is greater than 1. The metabonomics analysis technology is utilized to establish a comprehensive and unambiguous non-targeted metabonomics analysis method of the duck's droppings, metabolic component analysis can be performed on different varieties of tea leaves, and characteristic components of the duck's droppings can be accurately found out; the metabonomics analysis method of the characteristic components of the Danxiangxiang Dancong tea is established on the basis of the chemical components of the tea leaves, and the characteristic markers of the Danxiangxiang beneficial to true and false identification, geographical traceability, high-quality variety screening, flavor regulation and the like of the Danxiangxiang are screened from big data in combination with chemometrics analysis.

The invention relates to the field of liquid chromatography / mass spectrometry detection and particularly relates to different coffee extraction method characteristic markers and a screening method andapplication thereof. The method comprises: 1) carrying out grouping according to an extraction method of a coffee sample to obtain standard samples, 2) performing liquid chromatography-mass spectrometry analysis on each group of the standard samples, 3) performing statistical analysis on the obtained data to obtain different substances in the standard samples in each group, and 4) characterizingthe structures of the different substances. The screening method is simple, fast, accurate and stable. The ultra-high performance liquid chromatography tandem quadrupole / time-of-flight high-resolutionmass spectrometry-based non-targeted metabolomics technology is used for identification of coffee. The method has great significance for strengthening the research on the identification of coffee brewing methods, exploring the change of coffee components in the brewing process, improving the quality of coffee and ensuring the health of consumers.

The invention relates to a method for identifying the variety of honey by use of a non-target metabonomics technology. The method is characterized in that through a simple sample pre-treatment process, then lots of high-resolution mass spectrometric data are acquired through an ultra-high performance liquid chromatography-quadrupole / electrostatic field orbitrap high-resolution mass spectrometry method, interference caused by deviation and variation in experimental data through background deduction, chromatographic peak extraction, normalization, data conversion and data scaling, and after that, a real feature marker capable of distinguishing the variety of honey can be discovered and confirmed through principal component analysis, t-checkout, volcano plots and variable importance projection drawings. When the feature marker is utilized to identify the quality of honey, the identification results are objective and accurate. The method is used for not only source-tracing identification of the variety of honey but also variety source tracing and origin tracing identification of other agricultural products.

The present disclosure discloses a marker for screening and distinguishing NFC apple juice based on non-targeted metabolomics and use thereof, relating to the technical field of distinguishing of juice. The marker for distinguishing NFC apple juice disclosed in the present disclosure is selected from the following molecules: gallocatechin, catechin, taxifolin, p-hydroxybenzaldehyde, 5-methoxysalicylic acid, azelaic acid, caffeic acid, chlorogenic acid, epicatechin, eriodictyol, ferulic acid, isoquercitrin, naringenin, n-fructosyl isoleucine, p-coumaraldehyde, p-coumaric acid, phloretin, phlorizin, procyanidin B1, quercetin-3-O-galactoside and rutin. The above markers may be used for distinguishing the NFC apple juice and the FC apple juice, and have relatively high accuracy.

The invention discloses a fish gill metabonomics sample pretreatment optimization method, and relates to the technical field of metabonomics. The optimization method comprises the following steps: 1, preparing instruments and reagents; 2, UPLC-Q-TOF / MS data acquisition and analysis: acquisition and preparation of a sample, carrying out UPLC-Q-TOF / MS analysis, and performing data processing and statistical analysis. According to the invention, a UPLC-Q-TOF / MS technology is adopted, and a research object is a non-targeted metabonomics gill tissue sample. In the scheme, a liquid phase extraction and purification method involved in the pretreatment method is optimized and methodologically investigated, and analysis and discussion are carried out based on the coverage rate (the number of detected potential metabolites) and the stability (the RSD of the relative peak area and retention time of the metabolites); meanwhile, methodological investigation is carried out by utilizing a QC sample, and finally, the UPLC-Q-TOF / MS non-targeted metabonomics sample pretreatment method suitable for the gill tissues is established.

The invention belongs to the technical field of biological analysis, and particularly relates to a liquid chromatogram compound retention time database calibration method based on SCAC-RI. The methodcomprises the following steps: establishing an initial compound retention time database; calculating a compound retention index; and establishing a correction retention time database under a new method by taking SCAC as an index. According to the method, the situation that the database is unavailable due to retention time deviation caused by chromatographic condition change is improved to a greatextent, so that migration of the retention time database among different methods becomes possible, and adverse effects of unstable factors of other liquid phase systems on the retention time in an experiment can be eliminated so as to greatly improve the matching degree with a database during compound identification. The method is suitable for the field of non-targeted metabonomics and other chemical analysis in which a universal and flexible retention time database needs to be established to qualitatively analyze complex multi-component samples.

The invention discloses application of proline and alanine in prevention and treatment of wheat scab. The method comprises the following steps: firstly, based on a non-targeted metabonomics technology, screening resistance-related differential metabolites in a gibberellic disease-resistant wheat variety in an electric ion full scanning mode, and carrying out metabolic pathway enrichment analysis to find that an amino acid pathway is related to gibberellic disease resistance; and identifying proline and alanine in the amino acid pathway as fusarium head blight resistance related metabolites through a targeted metabonomics technology. According to the method, proline and alanine are treated before inoculation of in-vitro leaves and ears of wheat, so that the wheat can be effectively protected and treated, and the method is of great significance to prevention and treatment of wheat scab.

The invention relates to a derivatization method of carboxyl metabolites and a non-targeted metabonomics efficient analysis method. The derivatization method of the carboxyl metabolites comprises the steps of: step 1, enabling a sample to be detected to be subjected to carboxyl metabolite extraction through a first solvent, then performing drying, removing the first solvent, and obtaining a dried sample; step 2, mixing the dry sample with a second solvent to dissolve the dry sample, then adding triethanolamine and 2-bromo-1-(4-dimethylaminophenyl) ethanone, uniformly mixing, and then heating for incubation; after incubation is completed, adding triglycine, then performing heating, performing incubation, and obtaining a derivatization sample. According to the non-targeted metabonomics efficient analysis method, 12C labeling and 13C labeling are synchronously carried out by adopting the derivatization method, so that the metabolite detection sensitivity is improved, more metabolite can be detected at the same time, and the metabolite coverage rate is higher; and the detected metabolite is a peak pair, so that the influence caused by instrument drift and matrix is reduced, and the quantification is more accurate.

The invention relates to blood metabolite markers and applications for diagnosing multiple myeloma. First, through non-targeted metabolomics detection of bone marrow and peripheral blood samples from healthy donors (HD) and newly diagnosed patients with multiple myeloma (MM), five metabolites were screened out in bone marrow and peripheral blood. There are significant differences in blood, respectively L_Proline (proline), L_Aspartic acid (aspartic acid), L_Cystine (cystine), Stearic acid (stearic acid), Palmitic acid (palmitic acid). The results of ROC curve analysis showed that the five differential metabolites as a whole could diagnose MM more accurately. Targeted metabolomics detection further confirmed that the metabolite composed of 5 metabolites is an ideal method for MM diagnosis. The invention can accurately diagnose MM, and has great significance for promoting basic research, diagnosis and clinical treatment of MM.

The invention relates to a carbonyl metabolite derivatization method and a non-targeted metabonomics efficient analysis method.The carbonyl metabolite derivatization method comprises the steps of: 1, performing carbonyl metabolite extraction on a sample to be detected through a first solvent, then performing drying to remove the first solvent, and obtaining a dried sample; and 2, dissolving the dried sample, adding a pH adjusting reagent to adjust the pH value, adding dansylhydrazide, uniformly mixing, heating, incubating, cooling to terminate the reaction, drying to obtain a solid, and redissolving the solid to obtain a derivatized sample. According to the non-targeted metabonomics efficient analysis method, 12C labeling and 13C labeling are synchronously carried out by adopting the derivatization method, so that the metabolite detection sensitivity is improved, more metabolite can be detected at the same time, and the metabolite coverage rate is higher; and the detected metabolite is a peak pair, the influence caused by instrument drift and matrix is reduced, noise interference is eliminated, and quantification is more accurate.

The invention belongs to the technical field of oolong tea identification, and relates to the application of a metabolomics analysis technique to identify Yashixiang Dancong tea. In the metabolomics analysis technique, the Log 2 Fold Change, adj .p , VIP value to identify the characteristic components of Yashixiang Dancong tea, the screening condition is ∣Log 2 Fold Change∣>1.5, adj .p <0.01 and VIP>1. A comprehensive, non-discriminatory, non-targeted metabolomics analysis method for Yashixiang was established using metabolomics analysis technology, which can analyze the metabolic components of different varieties of tea and accurately find out the characteristic components of Yashixiang; Based on the chemical composition, a metabolomics analysis method for the characteristic components of Yashixiang Dancong tea was established. Combined with chemometric analysis, screening from big data is conducive to the identification of true and false, geographical traceability and high-quality variety screening of Yashixiang. Characteristic markers of duck feces aroma for applications such as flavor regulation and so on.

The invention relates to the technical field of food authenticity detection and identification, in particular to a metabolic marker combination for mutton origin traceability, a screening method and application. The metabolic marker combination for mutton origin traceability provided by the invention is obtained by combining metabonomics data and a chemometrics method, provides a scientific basis for mutton origin traceability research, authenticity identification and quality safety control, has strong universality, and is suitable for popularization and application. The mutton origin traceability detection method provided by the invention is simple, rapid, accurate and stable, and the non-targeted metabonomics technology based on the real-time direct analysis ion source and quadrupole-flight time high-resolution mass spectrum coupling technology is applied to the field of mutton origin traceability for the first time.

The invention discloses a method for screening myocardial ischemia resisting pharmacodynamic material basis of yang exhaustion treating decoction. The method comprises the following steps: 1, determining myocardial ischemia resisting endogenous metabolin of the yang exhaustion treating decoction and measuring the peak area; 2, determining in-vivo migration constituents in the yang exhaustion treating decoction and measuring the peak area; 3, performing correlation analysis on the peak area of the myocardial ischemia resisting endogenous metabolin of the yang exhaustion treating decoction and the peak area of the in-vivo migration constituents in the yang exhaustion treating decoction and screening out myocardial ischemia resisting pharmacodynamic material basis of the yang exhaustion treating decoction. The method disclosed by the invention is based on isoproterenol-induced rat myocardial ischemia model; an ultrahigh performance liquid chromatography-quadrupole rod-flight time mass spectrum non-targeted metabonomic technology and a targeted metabonomic technology based on an ultrahigh performance liquid chromatography-triple quadrupole rod mass spectrum are utilized to screen out 12 kinds of myocardial ischemia resisting pharmacodynamic material basis of the yang exhaustion treating decoction; thus, accuracy of the myocardial ischemia resisting pharmacodynamic material basis ofthe yang exhaustion treating decoction is improved, a screening period is shortened, and screening consumption cost is reduced.

The invention discloses application of serum myristic acid as an asthma diagnosis marker. According to the present invention, the non-target metabonomics of the serum of the experimental group is analyzed through the Q Exactive Orbitrap LC-MS, such that 12 asthma-related serum core metabolites such as myristic acid are found; wherein the serum myristic acid of an asthma patient is obviously higher than that of a healthy person, the difference has statistical significance, the serum myristic acid has relatively high sensitivity to asthma diagnosis, and the result is verified through a verification group. The serum myristic acid provided by the invention has relatively high sensitivity and specificity as an asthma diagnosis marker, and is simpler and more convenient, so that the serum myristic acid has a good application prospect in diagnosis of asthma.

The invention relates to the fields of nanomaterial preparation and metabolomics analysis, in particular to a metabolomics analysis method for Au-Pd / wtE.coli nanomaterials. The metabolomics analysis method provided by the present invention comprises the following steps: (1) performing DESI-MSI scanning on frozen sections of tissues or organs of animal models to obtain the DESI-MSI detection results of water-soluble metabolites and fat-soluble metabolites; The animal model described above is an animal model given Au-Pd / wtE.coli nanomaterials; wherein, the DESI-MSI detection conditions include: in positive mode, the voltage is 4.5-5kV; in negative mode, the voltage is -4.5-5kV; The spatial resolution is 50-100 μm; the solvent spray composition is 90-95% methanol aqueous solution; (2) spatial metabolomics analysis is performed on the DESI‑MSI detection results. In addition, the metabolomics analysis method of the present invention may also include non-targeted metabolomics detection and analysis of cells co-cultured with Au-Pd / wtE.coli nanomaterials. The invention provides a basis for evaluating Au-Pd / wtE.coli synthesis technology and biological response characteristic evaluation, and has broad application prospects.

The invention relates to a quality control method and device in metabolomics and a storage medium, which belong to the technical field of metabolomics analysis. The method comprises the steps that experimental samples are equivalently extracted and mixed to acquire quality control samples; the sample information of the quality control samples is acquired, wherein the sample information includes aprincipal component analysis chart, an experimental sample, the fluctuation trend chart of the quality control samples and / or the first principal component value of the quality control samples; basedon the sample information, abnormal samples in the quality control samples are filtered out to obtain the screened quality control samples; and the screened quality control samples are used for standardization correction. The problem of abnormalities in QC samples can be solved. The repeatability of QC samples is improved. The accuracy of data analysis results for non-targeted metabolomics is improved.