102 results about "Metabolome" patented technology

The invention belongs to the technical field of biosynthesis of plant secondary metabolites, and particularly relates to a key gene for biosynthesis of large-fruit hawthorn flavonoid compounds and a screening method and application of the key gene. Through combined analysis of metabolome and transcriptome, a key gene combination containing seven structural genes and three transcription factor genes is screened out; the expression of the genes is remarkably positively correlated with the accumulation of a target flavone metabolite [6]-gingerol, and the genes are core factors for regulating and controlling the synthesis of the flavonoid compounds of the big-fruit hawthorns through experimental verification. According to the invention, the key gene for regulating and controlling the synthesis of flavone substances such as [6]-gingerol in the big hawthorn fruit is systematically identified for the first time, and a target spot is provided for analyzing a quality formation mechanism from a molecular level; the gene can be used for molecular marker-assisted breeding so as to cultivate a new variety of large-fruit hawthorn with high flavone content, and also can provide gene resources and technical support for the development of functional food and health care products.

The invention provides a single strain metabolism characteristic chromatogram database of oral key microorganisms in a high-glucose microenvironment and a construction method and application thereof, and belongs to the technical field of oral microbiology. The method comprises the following steps: simulating an intraoral high-glucose microenvironment in vitro; the method comprises the following steps: carrying out standardized single-strain culture on oral key microorganisms, carrying out whole-spectrum metabolism detection (non-targeted liquid chromatography-mass spectrometry (LC-MS) and non-targeted gas chromatography-mass spectrometry (GC-MS) on culture supernatant, and identifying and analyzing metabolism to construct a single-strain metabolism characteristic spectrum database of the oral key microorganisms in a high-glucose microenvironment. The database can be used for source attribution and cross validation of in-vivo metabolome results, and assists in screening key metabolites and key pathways related to high glucose. According to the method, the reliability of metabolite source judgment is improved, the directional influence of high glucose on the flora metabolism function is revealed, the method is standardized, and resources are platformized.

The invention relates to the technical field of medicines, and discloses an application of combination of bufalin and heme in preparation of a cancer treatment medicine. According to the invention, by means of an active metabonomics means, a key active metabolite-heme is locked through exogenous library screening and endogenous analysis, and the drug effect of bufalin is regulated by means of the active metabolite. Through verification, it is found that heme can cooperate with the synergistic drug effect in various cancer cell lines, and a new technical normal form based on an active metabolome for improving the drug effect of bufalin is provided. The pharmaceutical composition can improve the apoptosis induction ability of bufalin to different cancer cells, and provides powerful guiding significance for developing a novel treatment scheme in clinical medicine.

This invention provides a combination of metabolic biomarkers for T-staging assessment of colorectal cancer, comprising four groups of metabolite combinations specifically distinguishing different T stages of colorectal cancer, each group containing 10 endogenous small molecule metabolites. This invention also provides detection methods and applications for the above-mentioned metabolic biomarker combinations. Furthermore, this invention provides a method for T-staging colorectal cancer for non-diagnostic and therapeutic purposes, as well as a combination of metabolic biomarkers related to the evolution of T-staging and tumor invasion depth in colorectal cancer. The advantages of this invention are: by combining iEESI-MS detection with multivariate statistics and machine learning, specific metabolic biomarkers related to T-staging of colorectal cancer are screened, a T-staging discrimination model is constructed, and objective, accurate, and rapid assessment of T-staging of colorectal cancer is achieved, providing molecular support for preoperative individualized treatment.

The amount of certain metabolomic markers from the lipid metabolism can be used for the highly specific and sensitive in-vitro diagnosis of ADHD.

The invention relates to the technical field of organelle separation, and provides a method for rapid purification of peroxisome and oxidation regulation analysis of ultra-long chain fatty acid. The method comprises the following steps: introducing a nucleic acid sequence for coding a fusion protein into a target cell to obtain a cell material, the fusion protein comprising a truncated sequence derived from a peroxisome membrane protein and a tag sequence for affinity purification; taking the cell material as a sample, and separating the peroxisome with the fusion protein from the cell by utilizing an affinity ligand on the basis of a high affinity binding principle. Therefore, according to the method disclosed by the invention, the peroxisome can be rapidly and efficiently enriched, and the whole purification process can be completed within 30 minutes, so that the experimental period is greatly shortened; core protein components of target organelles can be efficiently reserved, and the metabolic activity of peroxisome can be maintained through a complete membrane structure and an internal environment; meanwhile, the same purified sample can synchronously support proteome and metabolome analysis, and direct association of'protein-metabolism 'data is realized.

The application discloses a method for screening garlic fructan adversity response key enzyme genes and metabolites based on transcriptome and metabolome, and the method can better analyze the relationship between genes and metabolites by jointly analyzing the fructan-related differentially expressed genes measured by the transcriptome and the fructan-related metabolism substances with obvious metabolism changes measured by the metabolome, and constructing a gene-metabolite network interaction diagram.

The application discloses a digital image coding method based on metabolomics mass spectrum data. The method groups the mass-to-charge ratios in a preset mass range in the obtained first liquid chromatography-tandem mass spectrometry data according to preset division conditions; generates a full metabolome profile image according to the first mass-to-charge ratios and the first scan indexes in each group after grouping, and cuts and stacks the image to obtain a first multi-channel image; and screens a first target block based on the pooling signal intensity and the image entropy corresponding to the first multi-channel image, and the second multi-channel image stacked by the first target block is used to train a deep learning model for classifying biological samples. Thus, the metabolomics mass spectrum data can be converted into an image thereof through the digital image coding mode, the image can accurately retain the mass spectrum structure of the mass spectrum data of the metabolite species and level in the analytical metabolomics, and the deep learning model trained thereby can comprehensively reflect the original state of the metabolomics in LC-MS.

The present application relates to the field of crop genetic breeding and molecular biology, and particularly relates to a highland barley beta-glucan screening index system and a major gene positioning method, which comprises the following steps: firstly, a three-dimensional coupling screening system of genetic stability, functional activity and agronomic adaptability is constructed, the index combination weight is determined by using an entropy weight method and an analytic hierarchy process, and an AMMI model is combined to correct the environmental effect and calculate the comprehensive score of the germplasm; secondly, a recombinant inbred line and a natural germplasm double positioning population is constructed, and near-infrared spectroscopy is combined with a Transformer model to quickly obtain phenotype data; thirdly, a candidate major effective segment is obtained through double population joint positioning, a major effective gene is screened out by combining a transcriptome and a metabolome co-expression network, and a functional molecular marker is developed. The present application realizes accurate evaluation of highland barley germplasm and accurate positioning of major effective genes, and the phenotype detection is efficient and lossless, the molecular marker selection is accurate, and the present application can also be applied to other cereal crops.

The invention discloses a microneedle patch for in-vivo space-time omics analysis and a preparation method and application thereof, and belongs to the technical field of gene detection. Comprising the following steps: performing high-density modification on the surface of the microneedle for molecular binding; preparing a micro-needle base grinding tool for constructing a micro-needle patch; connecting the universal primer probe and the capture primer probe to the bar code probe; the microneedle patch captures to-be-detected molecules in a living body in situ; a probe complementary with the strand displacement region is added, polymeric strand displacement is carried out, and the obtained product can be used for constructing a sequencing library to realize spatial omics analysis of a living sample; the microneedle after strand displacement can be coupled with the bar code probe again to realize reuse of the microneedle for a new round of reaction. According to the method, the analysis of the spatial group in the living body sample is realized at extremely low cost, the operation is simple, the application field is wide, and the method can be used for detecting genomes, transcriptomes, proteomes, epigenomes, metabolomes and the like.

The invention relates to the technical field of biological information, and particularly discloses a multi-omics genome combined genetic assessment method and device. According to the method, multi-source data such as a genome, a transcriptome, a proteome, a metabolome, a microbiome and a high-throughput phenotype are integrated by constructing a multi-omics fusion similar matrix, an adaptive dichotomy is adopted to optimize omics weights, a grid search and cross validation system is introduced, and global optimal estimation of parameters is achieved. Verification of the method on livestock and poultry breeding and plant breeding data shows that the prediction accuracy of complex characters can be remarkably improved, and particularly, the prediction precision in low heritability characters is remarkably improved. The invention further provides a corresponding device which comprises a data acquisition module, a matrix construction module, a parameter optimization module and a breeding value calculation module, comprehensive utilization of multi-omics information can be efficiently achieved, and the accuracy and calculation efficiency of breeding value estimation are improved.

The application belongs to the technical field of molecular biology, and particularly relates to metabolic markers for distinguishing hypertrophic cardiomyopathy and left ventricular hypertrophy and application. The application analyzes the metabolome of hypertrophic cardiomyopathy (HCM) patients, left ventricular hypertrophy (LVH) patients caused by non-hypertrophic cardiomyopathy and healthy people, finds that carnitine C16:2, carnitine C14:0, carnitine C16:0, carnitine C18:0 and carnitine C18:1 are differentially expressed in HCM patients and LVH patients, pyridoxine phosphate, ito acid, adenosine monophosphate, adenosine diphosphate and adenosine triphosphate are differentially expressed in HCM patients and healthy people, lysine base, methyl glutamic acid, acetyl proline, malate semialdehyde and citramalate are differentially expressed in LVH patients and healthy people, and ROC curve analysis shows excellent prediction effect, strong specificity and high sensitivity.

The application discloses a kind of based on multi-omics deep learning colorectal cancer liver metastasis detection method and system, comprising: extracting the feature gene group with CRC transfer-metabolic dual function, and construct CRC transfer risk prediction model foundation, based on analysis CRC transfer risk probability to screen the molecular marker with CRC transfer nature and CRLM specific characteristics as initial candidate biomarker;Meanwhile, from the metabolome to obtain the differential expression metabolite corresponding to CRLM patient sample and LCRC patient sample metabolome, and the enrichment pathway analysis of transcriptome and metabolome is combined to construct CRLM multi-layer core metabolic network, for the screening core biomarker of colorectal cancer liver metastasis accurate detection in accordance with, entire method can effectively screen the biomarker for detecting colorectal cancer liver metastasis.

The application provides a tea plant gene and a method for regulating theanine accumulation in a tea plant CsSSCD1 The application belongs to the technical field of plant molecular biology. CsSSCD1 The base sequence of the gene is shown as SEQ ID No. 1. The application verifies the negative regulation of the gene by using VIGS technology and transient overexpression technology. In addition, through targeted amino acid metabolome analysis, it is found that CsSSCD1 The expression inhibition weakens the synthesis of tyrosine, the expression of the key enzyme AAAT of aromatic amino acid synthesis is inhibited, the accumulation of glutamic acid is reduced but not significant, and the accumulation of glutamine is significantly reduced, finally the degradation of theanine is blocked and the synthesis is increased. It is firstly proposed that the tyrosine degradation pathway may regulate the accumulation of theanine through metabolic pathway interaction and substrate competition mechanism, and on this basis, the key gene of the pathway is identified and functionally verified CsSSCD1 The gene is negatively correlated with theanine metabolism.

The invention relates to a method for screening and identifying metabolites and florae with a human immune regulation effect, which comprises the following steps: (1) establishing immune system humanized mice with multiple intestinal types, and analyzing the change of the florae, the metabolites and the immune system through intestinal flora sequencing, serum metabolome sequencing, flow cytometry and transcriptome sequencing; (2) determining the correlation and sequence between flora related metabolites and the change of the immune system through bioinformatics analysis; and (3) confirming the regulation and control relationship between the candidate metabolites and the immune subgroups in the step (2) through biological experiments. By means of the screening method, the chemical small molecule metabolites for regulating and controlling the human immune cells in the normal physiological state can be screened on a large scale, and the chemical small molecule metabolites can be developed into immunotherapy drugs or used as cell therapy drug culture system components. The screened propionic acid can promote cytotoxicity of T cells and CAR-T and secretion of related cytokines in the aspect of function regulation of the T cells, and the metabolite 2-hydroxybutyric acid is highly positively correlated with the Treg cells and can promote generation and functions of the Treg cells.

The invention discloses a colorectal cancer liver metastasis detection method and system based on multi-omics deep learning, and the method comprises the steps: extracting a characteristic gene group with CRC metastasis-metabolism dual functions, and on the basis of constructing a CRC metastasis risk prediction model, screening molecular markers with CRC metastasis general and CRLM specific characteristics based on the analysis of CRC metastasis risk probability, the biomarker is used as an initial candidate biomarker; meanwhile, a CRLM patient sample and differential expression metabolites corresponding to an LCRC patient sample metabolome are obtained from a metabolome, and a CRLM multilayer core metabolic network is constructed in combination with enrichment pathway analysis of a transcriptome and the metabolome, so that core biomarkers are screened for accurate detection of colorectal cancer liver metastasis; the whole method can effectively screen the biomarker beneficial to detection of colorectal cancer liver metastasis.

The invention provides a multi-omics fusion phenotype prediction method and system based on a potential space of an auto-encoder, and belongs to the technical field of biological information and machine learning, and the method comprises the steps: carrying out the preprocessing of multi-source omics data, such as genotype, metabolome and hyperspectrum, and splicing the data into a high-dimensional matrix; carrying out unsupervised training on the matrix by using an auto-encoder, carrying out nonlinear compression on the matrix to a uniform low-dimensional potential space, and generating fusion features; constructing supervised learning models such as XGBoost and the like to predict agronomic characters by taking the fusion features as input; and by calculating the genetic advantage and fusion gain of the target character, recommending an optimal omics use strategy according to a preset decision rule. According to the method, heterogeneous multi-omics data are effectively integrated through the auto-encoder, noise is filtered out, a cross-omics nonlinear relation is mined, and the prediction precision of a complex character is remarkably improved. Meanwhile, the provided quantitative decision framework provides a scientific basis for efficient configuration of omics resources in breeding practice, and predictive performance and cost control are both considered.

The invention provides a method, a system, equipment and a medium for constructing a yeast high-temperature tolerance prediction model, and belongs to the field of microbial breeding, and the method comprises the following steps: determining a tolerance label based on a maximum specific growth rate, an ethanol yield and a final ethanol concentration, and obtaining transcriptome data and metabolome data of a saccharomyces cerevisiae strain, the metabolome data comprises the synthesis rate of the trehalose, and the synthesis rate of the trehalose is determined according to the net synthesis amount of the trehalose in the heat shock time of the saccharomyces cerevisiae strain; constructing feature vectors according to the transcriptome data and the metabolome data; and inputting the feature vectors into the model to determine a predicted tolerance score, and performing hyper-parameter optimization on the model according to the tolerance tag and the tolerance score of the saccharomyces cerevisiae strain in the training set to obtain a yeast high-temperature tolerance prediction model. According to the method, the built-in powerful nonlinear learning ability of the model is utilized, the complex mapping relation between the multi-omics characteristics and the high-temperature tolerance is mined, and the accuracy and reliability during model prediction are guaranteed.

The invention discloses a method for enhancing pine wood nematode disease resistance of larch through jasmonic acid signal mediated flavonoid biosynthesis. The method comprises the following steps that 1, the larch is inoculated with pine wood nematode; 2, performing high-throughput omics sequencing sampling and data analysis; 3, treating larch seedlings with methyl jasmonate; 4, the inhibition effect of the kaempferol and the citrus aurantium on the pine wood nematodes is obtained. According to the method, larch is taken as a research object, a disease stress system is constructed by artificially inoculating pine wood nematodes, leaf / stem tissues at different time points after infection are selected, and sequential multiomics analysis is carried out by combining transcriptome sequencing and a wide targeting metabolome technology; the theoretical basis and method for improving the pine wood nematode disease resistance of larch by regulating and controlling the biosynthesis of kaempferol and citrus aurantium through a jasmonic acid signal way are defined.

Disclosed herein are compositions (e.g., pharmaceutical compositions, nutraceutical compositions) and methods useful for, inter alia, modulating levels of certain chorismate metabolites in a subject (e.g., in the gut of a subject). Modulation of levels of certain chorismate metabolites in a subject (e.g., levels of the chorismate metabolites in the gut) may have beneficial effects, prophylactic, and / or therapeutic effects for the subject, for example, in enhancing cognitive function or treating one or more signs or symptoms of a neurological disorder.

The invention provides research on a mechanism for regulating red bayberry fruit anthocyanin synthesis through optical signals and application of the mechanism. By treating Dongkui waxberries with different light-transmitting bags, the quality characteristics of mature fruits are analyzed, and comprehensive analysis is performed in combination with transcriptome and metabolome. The result shows that the bagging in the young fruit period significantly reduces the fruit quality, the black light-proof bag inhibits the fruit color change and anthocyanin synthesis, and the bagging influence in the color change period is small. Metabolome and transcriptome analysis shows that differential metabolites are enriched in anthocyanin synthesis and flavonoid metabolic pathways, related differential metabolites are identified, and core regulation transcription factors HY5 and DF1 participate in the photoregulation anthocyanin accumulation process. According to the invention, an optical signal regulation and control mechanism is defined, related factors and metabolites are identified, and a basis is provided for quality improvement and cultivation technology optimization of waxberries.

The present application belongs to the technical field of bioinformatics, and specifically relates to a chronic atrophic gastritis biomarker screening method and system based on a multi-modal differential network. The present application comprises: preprocessing metabolome data and microbiome data, respectively constructing intra-modal interaction graphs and inter-modal interaction graphs, and obtaining a multi-modal differential network by making a difference between the interaction graphs under different clinical groupings; based on the constructed differential network, a multi-level difference evaluation index is constructed: CDI is calculated at the node level to quantify the network topology and biological function differences of the biomarkers; at the structure level, a group specificity index GSI is defined to characterize the group specificity of the differential network structure; the feature ranking results obtained by CDI and GSI are fused and screened to obtain a biomarker set for atrophic gastritis classification prediction. The present application improves the effectiveness of biomarker screening under the condition of small sample and high dimension, and provides support for subsequent targeted cultivation of candidate colonies and metabolites and development of potential intervention target points.

The invention belongs to the field of biochemistry, and relates to a myocardial infarction risk assessment system, a kit and an instrument. The myocardial infarction risk assessment system obtains the content of a thiol metabolite combination in a biological sample of a subject, and outputs a risk score based on a preset myocardial infarction risk assessment model according to the content of the thiol metabolite combination. The method comprises the following steps of: presetting AUCgt of a myocardial infarction risk assessment model in a training set and two groups of external verification sets; 0.8, Plt; and the kit has good sensitivity, specificity and reliability. A myocardial infarction risk assessment system and a kit developed on the basis of the model can realize early screening, auxiliary diagnosis, illness monitoring and drug curative effect assessment of myocardial infarction on a conventional liquid chromatography-tandem mass spectrometry platform, and a new technical approach is provided for metabolic molecule typing and risk stratification of myocardial infarction.

This invention discloses a lactic acid bacterium and its application, belonging to the field of microbial fermentation technology. The lactic acid bacterium is *Lactobacillus plantarum* (Lactobacillus plantarum). Lactiplantibacillus plantarum FYcg1, with preservation number CGMCC No. 33190, is a strain that produces high levels of acid, is resistant to acid, salt, and bile salts, and exhibits a nitrite degradation rate exceeding 99%. It also shows significant inhibitory effects on Escherichia coli and Staphylococcus aureus. This invention optimizes the preparation method of a direct-inoculation starter culture, using skim milk powder, sucrose, and trehalose as a composite protective agent. The starter culture is prepared through specific centrifugation, pre-freezing, and vacuum freeze-drying, resulting in a high survival rate of live bacteria and good storage stability. When used for fruit and vegetable fermentation, it can rapidly lower pH, increase total acid content, and optimize flavor and metabolite composition, effectively solving problems such as long natural fermentation cycles, uneven quality, and poor safety. It is suitable for the industrialized and standardized production of pickled bamboo shoots.

The invention further provides a cancer prediction system based on metabonomics mass spectrum data parameterization. The cancer prediction system comprises a sample collection module used for collecting detection samples, a mass spectrum detection module used for conducting mass spectrum scanning, a mass spectrum data processing module and a data classification module. The mass spectrum data processing module is used for performing signal selective addition on the mass spectrum signals, and fitting and classifying the added mass spectrum signals to obtain metabolite pathway characteristics of a detection sample; and the data classification module adopts a machine learning algorithm to construct a prediction model according to the metabolite pathway characteristics to obtain a final prediction result. The prediction system can improve the prediction accuracy, and solves the problem that the accuracy is low when serum metabolome is used for predicting cancers.

The invention belongs to the technical field of single-cell metabolome analysis, and particularly relates to a single-cell metabolome analysis method and system with a motility rate sensing function, and the method comprises the steps: obtaining metabolism spectrum data of a plurality of single cells through a single-cell mass spectrum platform, and forming an initial single-cell metabolism matrix; the initial single cell metabolism matrix comprises a plurality of single cell samples and corresponding metabolite ion strength characteristics; inputting single cell survival rate labels provided by an external survival rate judgment module into the analysis process, wherein the survival rate labels are in one-to-one correspondence with corresponding single cells of the initial metabolism matrix; performing subset division on the initial metabolism matrix according to the motility rate label input in the step 2; reconstructing a living cell metabolism matrix and a dead cell metabolism matrix in groups, performing data processing and analysis operation on the living cell metabolism matrix and the dead cell metabolism matrix, and outputting an analysis result with better biological interpretation based on motility rate correction.

The invention provides application of a TaPAL8 gene in positive regulation of phenolic acid content of wheat, and belongs to the technical field of gene engineering. Wide targeted metabolome detection is carried out on wheat whole growth period materials by utilizing an HPLC-MS / MS technology, specific accumulation of various phenolic acids in stalks is highly related to expression of multiple phenylpropane pathway genes, one gene is annotated as phenylalanine ammonialyase, the gene number is TraesCS6D01G212200, and the gene is named as TaPAL8. According to the embodiment of the invention, the gene TaPAL8 is transformed into a wheat variety Fielder to obtain a transformed plant with overexpression TaPAL8, and in the overexpression mutant, the content of various acyl modified quinic acid substances in stalks and grouted grains is remarkably increased.

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 invention belongs to the technical field of cell viability on-line discrimination, and particularly relates to a mass spectrum-based cell viability measurement method and a mass spectrum-based cell viability measurement system. The invention provides a label-free endogenous metabolite-based cell viability measurement scheme and a label-free endogenous metabolite-based cell viability measurement system, aiming at the defects that the prior art depends on an exogenous label and cannot be synchronously carried out on line with single cell mass spectrometry. The method comprises the following steps: acquiring continuous single cell metabolome data through single cell electrospray ionization mass spectrometry, identifying a single cell event and a time window by taking ubiquitous membrane lipid as a first characteristic ion, extracting an endogenous metabolite reflecting cell activity in the window as a second characteristic ion, and calculating a signal-to-noise ratio; generating an activity label according to a preset threshold value and counting the cell viability of the group, wherein the system correspondingly comprises a data acquisition module, an event identification module, a marker extraction module, a threshold value judgment module and a viability counting module. According to the invention, synchronous, on-line and label-free accurate measurement of the cell viability in single cell metabonomics analysis is realized, and exogenous interference and data deviation are effectively avoided.

The invention belongs to the technical field of food processing and quality safety control, and particularly relates to a specific metabolic marker combination for identifying a drying mode of high-calcium vegetable ox ear powder and application of the specific metabolic marker combination. The metabolic marker composition is prepared from 12 kinds of metabolites, namely, larch sibirica flavone, 9-Methyl-arylchromenone, larch resinol, docosapentaenoic acid, gibberellin A7, methyl-arylpyranone, docosapentaenoyl glycerophosphorylcholine, Cratoxyborenone E, heptanol, prenylflavonoids, pteridin-6-carboxylic acid and Garcimangosone B. The invention further discloses a preparation method of the metabolic marker composition. The metabolic marker combination provided by the invention can be used for carrying out production process traceability and authenticity identification on the high-calcium vegetable ox ear powder, and can be used as a basis for evaluating a product drying process quality standard and monitoring the consistency of a drying process.