176 results about "Metabolome" patented technology

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 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 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 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.

The invention provides a prawn disease-oriented intestinal tract key metabolite design method and device, and relates to the technical field of strategy optimizing.The prawn disease-oriented intestinal tract key metabolite design method comprises the steps that prawn intestinal tract metabolite data are obtained, a random forest model distinguishes prawn health conditions through intestinal tract metabolite, and indication intestinal tract metabolite for distinguishing the health conditions is determined; the importance of the distinguishing metabolites is quantified through an MDA algorithm, and the most important distinguishing metabolite combination is screened; and distinguishing the metabolite and converting the metabolite concentration into a weighted undirected network, obtaining the feature vector centrality of each metabolite in the molecular ecological network, and determining a key metabolite. According to the invention, the random forest and the molecular ecological network are combined to identify key metabolites in a disease state, and the relative importance of each variable to a classification result is quantified. Meanwhile, the proportion of each key metabolite is determined by tracing back to healthy prawn intestinal tracts, and diseases are prevented and controlled symptomatically by compensating the combination of the inhibited key metabolite in the disease prawns.

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.

A pharmaceutical composition, a food composition, and a cosmetic composition for preventing or treating alopecia, and their uses are disclosed. The compositions contain, as an active ingredient, an Akkermansia sp. strain, vesicles of the strain, a proteome and metabolome of the strain, a culture of the strain, a lysate of the strain, an extract of the strain, an extract of the culture, or an extract of the lysate. The compositions for preventing or treating alopecia are safe for the human body, have no side effects, and have excellent effects of combating alopecia and promoting hair growth.

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.