218 results about "Metabolome" patented technology

The invention relates to the technical field of biomarkers, in particular to a blood biomarker combination for prediction and auxiliary diagnosis of ovarian reserve hypofunction (DOR), a corresponding detection kit and application of the blood biomarker combination. According to the invention, the content change of the nicotinamide mononucleotide (NMN) and the metabolite combination thereof in serum or plasma is screened for the first time and can be used as a detection index for predicting the ovarian reserve function decline. Based on the biomarker combination, the invention further provides an in-vitro detection kit containing a related standard substance, an internal standard solution and an extracting solution, and a data analysis method combined with a random forest model, so that an individual with a normal ovarian reserve function and an individual with hypofunction can be accurately distinguished. The method is noninvasive, simple, convenient, high in sensitivity and suitable for early recognition and layered screening of clinical ovarian reserve hypofunction.

The invention relates to a method for identifying a disease microorganism-metabolite combined marker based on a host-flora co-metabolism model. The method comprises the following steps: processing microbiome data; setting diet constraint conditions; determining classification composition of intestinal microorganisms of each individual, mapping abundance of each microorganism to a human microorganism genome scale metabolism model, and constructing an individualized flora metabolism network model; carrying out metabolic flow simulation on the constructed flora metabolism network model; integrating the constructed flora metabolism network model with the host metabolism network model, and predicting the metabolic flow and metabolite change of the whole system; and establishing a disease classifier based on a random forest machine learning algorithm to identify the microorganism-metabolite combined marker. According to the method, the complex metabolic process between the human body and the intestinal flora is restored in a metabolic network modeling and metabolic flow simulation mode, the method has the non-invasive characteristic, the time and economic cost is remarkably reduced, and meanwhile, the method has a great advantage in accuracy.

The invention provides an IBS micro-ecological transplantation intelligent prediction method and system based on multi-omics driving, and relates to the technical field of biomedicine. The method comprises the following steps: establishing a multi-omics data fusion subsystem to collect metagenome, metabolome, host genome and clinical phenotype group data of a target patient; inputting the data into a flora-metabolite combined network analysis model to construct an interaction network and extracting features; generating an incidence matrix based on the features and the host genome data and calculating indexes; generating indexes through a dynamic response algorithm in combination with the clinical phenotypic data and the indexes; and outputting a curative effect prediction result by using a transfer learning framework combined with modeling. The system comprises a data acquisition module, a network analysis module, a correlation calculation module, a dynamic response module and a joint modeling module. According to the method, multiple omics data are integrated, the flora and host relation is accurately mined, intelligent prediction of the micro-ecological transplantation curative effect is achieved, powerful support is provided for IBS personalized treatment, and meanwhile data processing and safety guarantee measures are taken.

The invention relates to the technical field of power transmission line monitoring, and discloses a power transmission line real-time monitoring method and platform. The method comprises the following steps: establishing a multi-omics data fusion subsystem to collect metagenome, metabolome, host genome and clinical phenotype group data of a target patient; inputting the data into a flora-metabolite combined network analysis model to construct an interaction network and extracting features; generating an incidence matrix based on the features and the host genome data and calculating indexes; generating indexes through a dynamic response algorithm in combination with the clinical phenotypic data and the indexes; and outputting a curative effect prediction result by using a transfer learning framework combined with modeling. The system comprises a data acquisition module, a network analysis module, a correlation calculation module, a dynamic response module and a joint modeling module. According to the method, multiple omics data are integrated, the flora and host relation is accurately mined, intelligent prediction of the micro-ecological transplantation curative effect is achieved, powerful support is provided for IBS personalized treatment, and meanwhile data processing and safety guarantee measures are taken.

The invention discloses a method for screening and identifying a cucumber aphid-resistant gene as well as a screened gene and application thereof, and provides a brand-new method for screening and identifying the cucumber aphid-resistant gene, which is used for screening the cucumber aphid-resistant gene based on four omics technologies. The four types of omics comprise transcriptome, proteome, methylation group and metabolome before and after inoculation of aphids on cucumbers, and the cucumber aphid resistance regulation gene is screened through combined analysis, so that a new gene resource is provided for improving the aphid resistance of the cucumbers, and a new method and a new idea are provided for designing molecular genetic breeding. The CsPGD2 gene obtained through screening is an aphid resistance gene, the dynamic change of a metabolic substance 5-ribulose phosphate in a metabolome is consistent with that of a transcriptome gene CsPGD2, the aphid resistance function of the gene CsPGD2 is verified through VIGS, and the result proves that the gene CsPGD2 is an important regulation factor for the aphid resistance of cucumbers. The invention provides a new gene resource for improving the aphid resistance of cucumbers, and has a good application prospect.

The invention relates to the technical field of cotton alkali-resistant gene mining, and particularly discloses a method for jointly screening key genes responding to upland cotton alkali stress based on transcriptome and metabolome, which comprises the following steps: carrying out alkali stress treatment on upland cotton to obtain tissue samples at different time points; performing transcriptome sequencing and metabolome sequencing on the tissue sample to respectively obtain gene expression data and metabolite data; performing difference analysis on the gene expression data and the metabolite data to obtain DEGs and DAMs; carrying out conjoint analysis on the DEGs and the DAMs, and screening to obtain a key gene and a regulatory pathway which respond to alkali stress; analyzing the key gene and the regulatory pathway through a gene expression verification technology to obtain an expression mode; according to the invention, 15 candidate genes related to the alkali resistance of the upland cotton are screened through WGCNA, a theoretical basis is provided for deeply knowing the molecular mechanism of the alkali resistance of the upland cotton, and a new gene resource is provided for subsequent research.

The invention discloses a rapid diagnosis method for blueberry continuous cropping soil obstacle factors, and belongs to the technical field of soil environment analysis. Based on combined analysis of soil physical and chemical factors, metagenome and metabolome, pathogenic bacteria types and key metabolites significantly related to the blueberry continuous cropping obstacle are extracted, and a characteristic diagnostic index system is formed. The index system comprises main pathogenic bacteria types, typical harmful metabolites, key soil physical and chemical factors and appropriate or risk threshold ranges thereof, and provides a scientific basis for rapid identification of soil continuous cropping obstacles. Comparative analysis is carried out by establishing a standardized index library, rapid comparison of related indexes and standard indexes in a newly sampled soil sample is realized, and whether the soil has continuous cropping obstacle risks or not is judged in an auxiliary manner by integrating the deviation degree of physical and chemical factors and biological factors.

The invention discloses a component detection system for unmanned automatic production of an extracting solution, and relates to the technical field of automatic production and quality control. The system integrates a plurality of detection technologies, including infrared spectroscopic analysis, OD value detection, pH value monitoring and absorbance detection, so as to realize real-time monitoring and automatic production management of the components of the extracting solution. By establishing a standard product fingerprint spectrum database, the system can automatically compare real-time detection data with a standard spectrum, and immediately triggers an alarm or stops production once an abnormality is found, so that the stability of product quality and the high efficiency of a production process are ensured. The system not only improves the automation degree of a production line, but also predicts and optimizes bioactive components through a whole genome nutrition group analysis technology in combination with species genome, transcriptome data and metabolome information, realizes precise formula and efficient production, and provides powerful support for an unattended automatic production system.

The invention discloses a method for treating piglet damp-heat diarrhea through multi-omics combined analysis. According to the method, faeces metabonomics, intestinal transcriptomics and intestinal flora 16s analysis are adopted, transcriptome data, metabolome data and intestinal flora data are screened according to a prime difference standard, then transcriptomics of a model group and a control group, faeces metabonomics and intestinal flora are subjected to conjoint analysis, an intersection is taken, and the faeces metabonomics of the model group and the control group, the faeces metabonomics of the model group and the control group and the intestinal flora of the model group and the control group are subjected carrying out conjoint analysis on transcriptomics of the Model group and HQ-M, faeces metabonomics and intestinal flora, and then taking an intersection; the method comprises the following steps of: selecting a plurality of metabolites and florae from a plurality of intestinal florae, respectively obtaining intersections, screening related genes, searching gene FPKM expression quantity in transcriptomics, and screening corresponding metabolites and florae in metabonomics and intestinal florae to obtain a gene-flora-metabolite related network diagram. Multi-omics combined analysis shows that the piglet diarrhea due to damp-heat is mainly manifested by inflammation and glucose and lipid metabolism disorder.

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 relates to a method for screening drought-resistant tea germplasm and application. The method for screening the drought-resistant tea tree germplasm comprises the following steps: step 1, performing repeated drought treatment on a tea tree, and measuring phenotype, metabolome data and transcriptome data of a sample; 2, screening the differential metabolite from the metabolome data, wherein the expression mode of the differential metabolite is that the differential metabolite does not respond or has no significance in response when the differential metabolite is subjected to drought for the first time and has significant response after multiple times of repeated drought, and taking the differential metabolite as a memory metabolite; 3, screening and analyzing differential genes in the tea trees subjected to repeated drought treatment: screening memory key genes from the differential genes; and step 4, according to the transcriptional level of the memory key genes in the tea tree leaves, determining the key genes with high transcriptional level as the drought-resistant tea tree germplasm. The 9 memory key genes are verified, the result shows that the selected gene is consistent with the transcriptome sequencing result, and the gene has good sensitivity, specificity and accuracy in screening drought-resistant tea trees or improving the drought resistance of the tea trees.

The invention belongs to the technical field of biomarker detection, and relates to a biomarker, a kit and an application of the biomarker in early screening of severe cognitive impairment of schizophrenia, the biomarker is composed of a metabolite SM C20: 2 and a metabolite PC ae C36: 2, and compared with non-severe cognitive impairment (non-SCI) of schizophrenia, the biomarker has the advantages that the biomarker can be used for early screening of severe cognitive impairment of schizophrenia; the biomarker has an area of 0.685 under an ROC curve in a discovery severe cognitive impairment (SCI) sample and an area of 0.720 under an ROC curve in a verification set. The method can be used for early screening the cognitive severity of schizophrenia patients under the condition of no drug interference, and has good stability, repeatability, sensitivity and specificity. The kit has screening and typing functions when being used for detecting schizophrenia patients, can be used for identifying the schizophrenia patients and a healthy control group, and can also be used for distinguishing SCI (severe cognitive impairment) and non-SCI (non-severe cognitive impairment) groups to assist clinical personalized intervention.

The invention relates to the field of microorganisms, and discloses a process method for producing MK-7 by fermenting soybeans and vinegar residues with bacillus subtilis. Soybeans and vinegar residues are used as fermentation substrates, and bacillus subtilis natto is used for fermentation; and obtaining the MK-7 from the fermentation liquid. Furthermore, an optimal process for producing MK-7 by fermenting soybeans and vinegar residues with bacillus subtilis is determined through a single factor test, an optimization test and a response surface test, and product changes before and after fermentation are analyzed through a non-targeted metabolome. The method solves the problem that the production efficiency cannot meet the actual production requirement in the current MK-7 extraction.

The invention discloses a space transcriptome and space metabolome integration method based on deep learning. The method comprises the following steps: firstly, acquiring original space transcriptomics data and original space metabonomics data of a biological tissue, and performing data preprocessing to obtain a preprocessed biological tissue data set; then, aligning space metabonomics data in the preprocessed biological tissue data set to space transcriptomics data, unifying data resolution, obtaining corrected space metabonomics data, and updating the biological tissue data set; and finally, generating to-be-integrated sample data from the newest biological tissue data set, inputting the to-be-integrated sample data into the spatial multi-omics data integration model, and outputting final joint embedding by the model, so that cross-modal and cross-sample effective integration of the data can be realized. According to the method, the problems of form and resolution inconsistency and batch effect caused by technical difference of ST and SM data are solved, and high-precision and interpretable spatial multi-omics integration analysis is realized.

The invention belongs to the field of plant breeding, and provides a whole genome prediction method based on multi-omics integration. Comprising the steps of genome data acquisition, metabolome data acquisition, transcriptome data acquisition, phenotype data acquisition, data preprocessing, hybrid data speculation, training set and test set division, prediction model construction, prediction model training, linear regression model training and phenotype value prediction. According to the method, the genome-phenotype prediction model, the metabolome-phenotype prediction model, the transcriptome-phenotype prediction model and the linear regression model are constructed, and ten-fold cross validation is used for training the models, so that the multi-omics predictive power of the models is improved, and the rice hybrid phenotype prediction precision is improved.

The invention relates to the technical field of environmental toxicology, in particular to a construction method and application of micro-nano plastic combined toxicity (AOP) based on multi-omics integration, and the construction method comprises the following steps: respectively carrying out single exposure culture of multi-target risk substances by adopting human-derived hepatocyte HepaRG cells; determining a combined exposure dose; cell treatment and sample preparation; transcriptome analysis; analyzing metabolome; transcriptome and metabolome data are integrated, pathway cross analysis is carried out, a gene-metabolite interaction network is constructed, and a core regulation and control module is identified; and constructing an AOP framework: determining a molecular initial event, a key event and a harmful outcome of the AOP framework based on the integrated data, and importing an AOP-WIKI platform to generate a standardized AOP framework. According to the method, the limitation of a traditional single omics and fixed dose model is broken through, full-chain dynamic association from a molecular initial event to a harmful outcome is realized, and a scientific basis is provided for combined pollution risk assessment in the fields of environment and food.

The invention provides a tetrastigma hemsleyanum origin tracing method and device, and relates to the technical field of traditional Chinese medicine origin identification. The tetrastigma hemsleyanum origin tracing method provided by the invention comprises the following steps: acquiring metabolome data of tetrastigma hemsleyanum from different origins, and screening out differential metabolites; training a classification model by using the data of the differential metabolites, then classifying the metabolome data of the radix tetrastigme to be tested by using the trained classification model, and predicting the production place of the radix tetrastigme to be tested; different producing areas include Zhejiang, Fujian, Jiangxi, Yunnan, Guangxi and Chongqing. The method is high in prediction accuracy, an efficient and convenient identification method is provided for radix tetrastigme producing area traceability, the market safety of radix tetrastigme is guaranteed, and the legitimate rights and interests of consumers are maintained.

The invention discloses an intestinal flora function state analysis method and system based on multi-omics conjoint analysis, and relates to the technical field of data analysis and microorganisms, and the technical scheme is characterized in that metagenome sequencing data and metabolome detection data of host intestinal flora are acquired; an interaction network atlas containing nodes and edges is constructed, the nodes comprise metabolite nodes and flora function pathway nodes, the edges are correlation lines connecting metabolites and flora function pathways, and correlation weights of the correlation lines are determined; screening out key interaction nodes from the interaction network atlas; and quantitatively evaluating the functional state of the host intestinal flora based on the key interaction nodes. According to the method, the dynamic interaction network atlas is constructed by integrating the metagenome sequencing data and the metabolome detection data, space-time correlation modeling of the flora function pathway and the metabolite is realized for the first time, the technical defect that the view angle of single omics analysis is limited is overcome, and the systematicness and biological interpretability of functional state evaluation are remarkably improved.

The invention discloses application of lactobacillus rhamnosus to preparation of a product for improving and treating cognitive impairment. The invention discloses the new application of the rhamnosus cheese for the first time, and the rhamnosus cheese can improve or treat cognitive impairment related to aging by improving behavioral function change, brain inflammatory factors, oxidative stress activity and neurotransmitter level caused by aging of mice and regulating transcriptome, intestinal microbiome, metabolome and the like. The lactobacillus rhamnosus has a potential application prospect in the aspect of improving learning and memory ability impairment caused by senescence.

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.

The present application relates to a system for assessing the degree of senescence, which assesses the degree of senescence of a cell by calculating a score of a cell metabolome state by taking into account metabonomics data of the cell. The system is especially suitable for cosmetic efficacy evaluation, anti-aging drug screening and other scenes, can shorten the research and development period in practical application, and has significant industrial application value.

A method and system for analyzing and / or estimating a metabolite profile of a subject. A digital image of a sample of feces of the subject is received by one or more processors. The digital image and / or one or more features extracted from the digital image is provided as input to a trained machine learning model which is configured to output a classification based on said input digital image and / or one or more features extracted from the digital image. Data indicative of one or more properties of the metabolome of the subject based on the output image classification is determined by the one or more processors.

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 invention discloses a Ustilaginoidea virens inoculant, a preparation method and application of the Ustilaginoidea virens inoculant in Ustilaginoidea virens inoculation, and belongs to the technical field of agricultural microorganisms. According to the method, two-step shake-flask culture is combined with the steps of filtering, centrifuging and spore germination, so that the ustilaginoidea virens inoculum taking germinated spores (GC) as the core is prepared, and the problems of hypha aging, low spore activity, asynchronous infection and the like in the existing inoculation method are effectively solved. The inoculant has a tender hypha structure and strong infection activity, and the inoculation efficiency and the pathogenesis consistency are remarkably improved. When being used for preparing transcriptome samples, metabolome samples and other omics samples, the strain avoids non-specific immune interference caused by PAMPs released by broken hyphae, ensures synchronous infection process, and is real and reliable in immune response. The invention provides a stable and efficient inoculation system with a clean background for the research on the ustilaginoidea virens-rice interaction mechanism, and has a good application prospect.

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.