255 results about "Metabolomics" patented technology

The invention relates to a method for acquiring a biomarker for assisting CRLM early diagnosis. The method comprises the following steps: acquiring sequencing data, clinical information and metabonomics characteristics of a CRC sample; evaluating and determining a plurality of differentiated machine learning models; performing classification according to the determined machine learning model, and constructing a CRLM biomarker prediction model; screening candidate biomarkers according to the prediction model; and verifying the candidate biomarker at least according to the tissue slice and the serum sample, and determining a final biomarker.

The embodiment of the invention discloses a sleep peptide and differential metabolite detection method for caenorhabditis elegans, belongs to the technical field of organism metabolism, and aims to research sleep-awakening key metabolite of caenorhabditis elegans and a regulation mechanism of the sleep-awakening key metabolite. According to the sleep peptide for caenorhabditis elegans, the sleep peptide is an F4 monomer as shown in SEQ ID NO: 1. Compared with the prior art, the sleep and awakening process of the caenorhabditis elegans under the intervention of the goat milk-derived sleep peptide is analyzed through a metabonomics technology, the key metabolite for regulating and controlling sleep and awakening is successfully screened out, and a core metabolic pathway related to the key metabolite is disclosed. The application also constructs a metabolite-pathway-target regulation framework, fills the blank of sleep research in the aspect of metabolic regulation, provides a scientific basis for a sleep intervention strategy based on metabolic regulation, and also lays a foundation for developing metabolic markers of sleep states in the future.

The invention relates to the technical field of plant breeding, and particularly discloses a metabonomics-based alfalfa stress resistance gene analysis function and a breeding method. The core of the method is that screening is carried out by combining a tissue culture technology with metabolic intervention; an alfalfa explant is inoculated into an induction culture medium containing a specific metabolic pathway regulator for metabolic intervention culture; then transferring the obtained callus to a verification culture medium containing the metabolism regulator and an abiotic adversity stress factor at the same time, and carrying out metabolism mark verification and screening; and finally regenerating the screened cell line into a complete plant. According to the method, metabolic pressure is actively applied to the cellular level, and dual verification screening is implemented, so that early-stage, efficient and accurate breeding of the stress-resistant alfalfa material is realized, and the technical problems of long period, low efficiency and insufficient utilization of metabolic information in traditional breeding are solved.

The invention discloses a pathogenic microorganism detection system based on nanopore sequencing and intelligent interpretation. The system comprises six modules including a biomolecule electric signal acquisition module and a pathogen characteristic sequence extraction module. Ion current change signals are collected through a nanopore chip array, a pathogen characteristic sequence is extracted through differential coding, a hypergraph topological structure self-adaption building module is used for building a pathogen relation model, a multi-dimensional heterogeneous pathogen parameter fusion analysis module integrates morphological parameters, metabonomics parameters and other multi-dimensional parameters, and the multi-dimensional heterogeneous pathogen parameter fusion analysis module is used for analyzing the multi-dimensional parameters. The optimized hypergraph neural network reasoning module realizes pathogen category prediction, and finally, the nanopore sequencing result intelligent interpretation output module generates a detection report containing pathogen categories, subtypes and risk levels. The system is combined with nanopore sequencing and an intelligent algorithm, pathogenic microorganism detection can be efficiently and accurately completed, the accuracy, reliability and efficiency of detection are greatly improved, and the requirement for rapid and accurate detection of pathogens in practical application is met.

The invention belongs to a mass spectrometry technology, and particularly provides a single cell metabonomics analysis method based on the mass spectrometry technology, which comprises the following steps: (A1) collecting population cell data including a plurality of average mass spectrograms of a plurality of population cells in a low-resolution mode and a high-resolution mode; (A2) constructing an SCSR-Unet super-division model by using the population cell data, and training, verifying and testing the model; a loss function CL is used in network construction; (A3) collecting single cell data, wherein the single cell data comprises an average mass spectrum of a plurality of single cells in a low-resolution mode and a high-resolution mode; and (A4) enabling the average mass spectrum data in the low-resolution mode to pass through an SCSR-Unet model to obtain high-resolution mass spectrum data of predicted absolute intensity, and synchronously preprocessing the high-resolution mass spectrum data and the mass spectrum data in the high-resolution mode for single-cell metabonomics analysis.

The invention belongs to the field of computational biology calculation, and particularly relates to a colorectal cancer metabolism information generality analysis method based on intrinsic learning. The method comprises the following steps: firstly, training a deep learning model, and identifying an intrinsic metabolite of the colorectal cancer from a high-resolution tumor space metabonomics data set of the colorectal cancer; secondly, introducing a distribution selection mechanism and an intrinsic learning method, and efficiently screening intrinsic metabolites highly related to colorectal cancer diagnosis and staging; then, inputting the intrinsic metabolites into the tumor prediction network to estimate the tumor condition; and finally, evaluating the effectiveness of the screened intrinsic metabolites through multi-task verification, including tumor diagnosis and T / N / M staging prediction of colorectal cancer. Experimental results show that the colorectal cancer screened based on the model is predicted, the AUC in tumor diagnosis and T / N / M staging prediction tasks exceeds 0.9, and the model has high clinical application value.

The invention belongs to the technical field of biology, and particularly relates to bacillus velezensis HALZ676 as well as application and a method of the bacillus velezensis HALZ676 to cowhide fermentative degradation, the bacillus velezensis HALZ676 is separated from preserved pig trotters, and by analyzing biological characteristics, whole genome and metabonomics differences of the bacillus velezensis HALZ676, the cowhide can be efficiently degraded, and the cowhide can be efficiently degraded. It is found that peptide components smaller than 3000 Da in cow leather degradation liquid obtained through fermentation of the strain HALZ676 account for 68% or above, and the cowhide degradation liquid has remarkable antioxidant capacity and antibacterial capacity; the cowhide fermentation liquor is mainly used for promoting conversion and enrichment of antioxidant, anti-inflammatory and anti-cancer metabolites through a linoleic acid metabolic pathway, so that the antioxidant, anti-inflammatory and anti-cancer capacities of the cowhide fermentation liquor are enhanced; the cowhide fermented by the strain HALZ676 can enrich functional active components, and a theoretical basis and a promising strategy are provided for high-valued production of processing byproducts of livestock and poultry skin fermented by probiotic bacillus with high yield of collagenase.

The invention discloses a metabonomics-based Citrus Huanglongbing marker combination and a screening method thereof, and relates to a method for screening biomarkers of an asymptomatic Citrus Huanglongbing sample, metabolite screened by the method is adopted to further construct a prediction model, and the prediction model is used for detecting Citrus Huanglongbing in asymptomatic leaves. The biomarker of the asymptomatic sample can be screened through the method, and the method is of great significance to improvement of diagnosis accuracy.

The invention belongs to the technical field of medical diagnosis, and provides an HIV (human immunodeficiency virus) combined non-alcoholic fatty liver diagnosis and prediction marker and application. The marker comprises 39 biomarkers in total, wherein the 39 biomarkers comprise two intestinal microorganisms of enterobacter and klebsiella and 37 plasma metabolites of diacylglycerol, lysophosphatidic acid and the like; by integrating microbiome and metabonomics, the multi-dimensional marker is screened and verified, so that the problems of lack of high specificity and sensitivity, difficulty in early disease screening and incapability of effective risk assessment of an HIV (Human Immunodeficiency Virus) combined NAFLD (Non-Amplified Fragment Leukemia) early diagnosis method caused by unknown pathogenesis in the prior art are solved; the marker combination is applicable to preparation of diagnostic kits, construction of disease prediction models and development of targeted therapy drugs, and a theoretical basis is provided for early discovery, risk early warning and advanced intervention of the HIV combined with the non-alcoholic fatty liver disease.

The invention relates to a preparation method and application of a gamma-PGA-rich feed additive for broiler chickens, and the technical scheme for solving the problems is as follows: screening bacillus licheniformis DY-0089 for high yield of gamma-PGA from fermented foods such as fermented soya beans, fermented bean curds and natto, inoculating the bacillus licheniformis DY-0089 on a solid fermentation culture medium, fermenting for 24-96 hours at 28-45 DEG C, drying in a drying oven at 55-70 DEG C, and crushing to obtain the gamma-PGA-rich feed additive for broiler chickens. And preparing the feed additive rich in gamma-PGA. Research finds that when 1% of the gamma-PGA-rich feed additive is fed to broilers, the immune function of the body can be enhanced, cecum microbiota can be improved, cecum metabonomics can be adjusted, then the growth performance and feed conversion rate of the broilers are improved, serum biochemical indexes, oxidation resistance, slaughter performance, pectoral muscle nutritional ingredients and the like of the broilers are basically not affected, and the feed additive is suitable for large-scale production. And a theoretical basis is provided for development and application of the gamma-PGA-rich feed additive in animal breeding, especially broiler breeding.

The invention discloses a specific metabolic marker combination for diagnosing ovarian cancer and application thereof, and belongs to the field of markers for detecting ovarian cancer. The invention discloses a specific metabolic marker combination for diagnosing ovarian cancer. The specific metabolic marker combination comprises phosphatidylcholine 36: 6, sphingomyelin d40: 2 and sphingomyelin d41: 2. According to the invention, a metabonomics technology is used to screen out a specific metabolism marker combination for diagnosing ovarian cancer, and the specific metabolism marker combination has high sensitivity in ovarian cancer diagnosis and has high diagnosis capability for ovarian cancer diagnosis. The specific metabolic marker combination also has high specificity in ovarian cancer diagnosis, but is not applicable to diagnosis of endometrial cancer and cervical cancer. In addition, the plasma sample acquisition mode has the advantages of non-invasiveness and convenience, and has a wide application prospect in the research of biomarkers.

The invention discloses a multi-layer heterogeneous network unicellular organism network inference method based on meta-path enhancement, which mainly comprises a gene regulation knowledge base enhanced multi-layer heterogeneous network construction module for integrating an external gene interaction network and multiple omics data such as scRNA-seq, scATAC-seq, ST and the like; constructing a single-cell multi-omics multilayer heterogeneous network containing cell-cell, cell-gene and gene-gene relationships, and fusing spatial constraints to consider cell positions and tissue structures; and the feature enhancement module based on the meta-path explores complex semantics of the network by designing a multi-hop meta-path mode, designs an adaptive multi-view learning framework and a multi-round enhancement mechanism, and optimizes feature representation by using cell-gene interaction and cross-modal attention fusion. The unicellular biological network can be effectively deduced, the deduction accuracy and biological interpretation are remarkably improved, the method plays an important role in understanding the cell biological process, developing and treating diseases and the like, has good expandability, and can further integrate multi-modal omics data such as proteomics and metabonomics.

The invention provides a biomarker composition based on plasma metabonomics and application of the biomarker composition in early diagnosis of nasal extrinsic N / KT cell lymphoma, and relates to the technical field of biomarkers. According to the present invention, for the first time, it is provided that the 2-Methylbutyl beta-D-glucose acid, the 4-(2, 3-dihydro-1, 4-benzodioxin-6-yl) glucose acid and the 4-(octyloxyl) glucose acid can be adopted as the biomarkers for distinguishing the chronic sinusitis patient from the nasal knot external N / KT cell lymphoma patient, and the application of the 2-Methylbutyl beta-D-glucose acid, the 4-(2, 3-dihydro-1, 4-benzodioxin-6-yl) glucose acid, the 4-(2, 3-dihydro-1, 4-benzodioxin-6-yl) glucose acid, the 4-(2, 3-dihydro-1, 4-benzodioxin-6-yl) glucose acid and the 4-( According to the invention, a single-factor prediction model / combined factor prediction model NKTCL early diagnosis model AUCgt is constructed by taking the three biomarkers as characteristics and combining a random forest algorithm; 0.9, sensitivity gt; the specificity is gt; and the kit has relatively high accuracy, sensitivity and specificity for diagnosing the N / KT cell lymphoma outside the nasal knots, and is high in disease diagnosis and prediction capability. According to the method, stepped improvement of diagnosis efficiency is directly achieved through the synergistic effect of the multi-dimensional plasma metabonomics markers and algorithm suitability optimization, and a new normal form with high precision and clinical feasibility is provided for early screening of tumors.

This invention relates to the field of cell detection equipment technology, specifically to a detection device for bladder cancer metabolomics biomarkers. The device includes an ELISA reader, a moving stage, and well plates housed within it. It also includes a defoamer mounted on the outer wall of the ELISA reader. The defoamer comprises a fixing part, a pair of transmission parts, and a striking part and an air blowing part disposed within the fixing part. This bladder cancer metabolomics biomarker detection device, through a mechanical linkage design between the moving stage and the defoamer, uses a gear-driven toothed plate to move a dial-driven bending plate up and down, causing a striking rod to strike the well plate. Combined with synchronous airflow from the air blowing part, a protrusion pushes a piston plate within a second groove, directing airflow from the nozzle. This achieves automated removal of air bubbles from the wells before ELISA reader detection. The dual defoaming effect of striking vibration and airflow impact eliminates optical interference, ensuring the accuracy of the detection values ​​and simplifying the detection process.

The application provides a colorectal cancer prediction system and application thereof, which utilizes a metabolomics method, analyzes metabolites with significant differences in urine of colorectal cancer patients and normal people, screens a series of biomarkers capable of early indicating colorectal cancer occurrence risk, and further screens a group of biomarkers to construct a colorectal cancer diagnosis model, so that the colorectal cancer diagnosis model can be used for conveniently, non-invasively and efficiently predicting whether an individual is suffering from colorectal cancer, and meets clinical requirements.

The invention provides a pulmonary nodule targeting food and medicine homologous composition based on metabonomics screening and application thereof. By analyzing a pulmonary nodule specific metabolic profile, active components, namely platycodin D, mogroside V, oyster active peptide and fermented cordycepin, which can cooperatively regulate and control an arachidonic acid inflammation pathway, a glutathione antioxidant pathway and a tricarboxylic acid cycle energy pathway are reversely screened out. Animal experiments prove that the composition can reduce the volume of pulmonary nodules by 58.3%, human body application shows that the nodules of 76.7% of subjects are reduced, and liver and kidney toxicity is avoided. The composition can be prepared into tablets, capsules and other dosage forms, can be used as functional food or adjuvant therapy drugs for high risk groups of pulmonary nodules, and realizes accurate nutrition intervention.

The invention belongs to the technical field of medicines, and particularly relates to application of BAY-069 in preparation of a medicine for treating rheumatoid arthritis. Through metabonomics research, the inventor finds that the metabolic enzyme BCAT2 is remarkably highly expressed in synovial tissues of an active-stage RA patient and is relatively low in expression in synovial tissues of a remission-stage RA patient. The high expression of the metabolic enzyme BCAT2 is closely related to synovitis and bone destruction. The BAY-069 as a BCAT2 inhibitor can significantly reduce the score of joint inflammation, reduce synovitis and bone destruction, and effectively reduce bone loss. The invention provides an innovative RA metabolism targeted treatment strategy which has high safety and strong targeting property.

The invention discloses a colorectal cancer diagnostic marker group based on expiration volatile organic compounds and application of the colorectal cancer diagnostic marker group. The colorectal cancer diagnostic marker group consists of six expiration volatile organic compounds, namely furfural, 2-methyl butane, valeric acid, methyl allyl sulfide, hexane and octanal. According to the method, expiration samples of 182 subjects are analyzed through TD-GC-MS / MS, machine learning is combined, the six expiration volatile organic compounds are screened out, the diagnosis AUC of the combination in a verification queue reaches 0.907, the accuracy rate is 0.806, and the combination is superior to a serum marker combination (AUC = 0.861). The invention further provides the BRS and a colorectal cancer noninvasive diagnosis and risk stratification system, and the BRS and the colorectal cancer noninvasive diagnosis and risk stratification system are used for achieving efficient prediction and risk stratification of the colorectal cancer. Compared with a traditional risk scoring model depending on clinical variables such as age, family history and lifestyle, the BRS provides unique metabonomics information, and the prediction accuracy is remarkably improved.

The present application relates to the field of medical diagnosis, and in particular to screening biomarkers for differential diagnosis of gestational diabetes mellitus by using metabolomics, and establishing a model for diagnosing whether a pregnant individual is diabetic based on the biomarkers. The present application provides biomarkers and a diagnostic model for differential diagnosis of gestational diabetes mellitus, which can be applied to early diagnosis or prediction of gestational diabetes mellitus, and is of great significance for prevention or treatment of gestational diabetes mellitus.

The invention discloses a diabetic retinopathy diagnosis and analysis platform based on double body fluids and a method for analyzing a biological fluid sample by using the diabetic retinopathy diagnosis and analysis platform, and relates to the field of biological diagnos.The diabetic retinopathy diagnosis and analysis platform comprises an acquisition and analysis module and a machine learning module, the acquisition and analysis module acquires mass spectrum data of a biological sample through a mass spectrum system for analysis, and the machine learning module analyzes and processes the acquired mass spectrum data of the biological sample, constructs a diabetic retinopathy biomarker panel, and analyzes the diabetic retinopathy biomarker panel to obtain the diabetic retinopathy biomarker. The invention also comprises a method for analyzing a biological fluid sample by using the analysis platform, the biological fluid sample comprises vitreous humor and plasma, and the nanoparticles are used as a matrix of the biological fluid sample for mass spectrum data acquisition. The invention provides a rapid, stable, reliable and high-sensitivity vitreous humor metabonomics detection method and system.

The invention relates to the technical field of medicines, and discloses a bifidobacterium longum strain GZBAI 01 and application thereof in degradation of benzoic acid and prevention or treatment of colorectal cancer. The strain is separated from faeces of healthy people, genomics identification is carried out, the metabolic profile of the strain is measured through metabonomics, the strain can convert benzoic acid with carcinogenic risk into protocatechuic acid with antitumor activity through unique metabolic capability, meanwhile, the function of regulatory T cells (Treg) in tumor drainage lymph nodes can be inhibited, differentiation of CD8 + T cells is promoted, and the tumor drainage lymph nodes can be inhibited. Therefore, the colorectal cancer is prevented through double ways of eliminating cancerogen and generating therapeutic agents. A colorectal cancer mouse model and a subcutaneous tumor mouse model verify that the strain can significantly reduce the number and volume of tumors, and shows a benzoic acid conversion effect superior to that of other strains in vivo and in vitro, and a new way is provided for prevention and treatment of colorectal cancer.

The application discloses a breath metabolomics disease knowledge graph construction method and device, and the method comprises the following steps: acquiring a disease gas data set; preprocessing the disease gas data set to obtain a disease gas pretreatment data set; processing the disease gas pretreatment data set to obtain a breath metabolomics disease knowledge graph. The application significantly improves the recognition accuracy of diseases and gas entities and their relationships, makes the correlation between breath VOCs and diseases more intuitively present, realizes efficient organization and management of data, and promotes in-depth development of breath VOCs and disease research.

This invention discloses a method for screening key neurotoxic substances in food raw materials and their products using a *C. elegans* model combined with metabolomics. Food samples are processed to prepare a stock solution, which is then used to cultivate *C. elegans*. The sample exhibiting the greatest neurotoxicity to the nematodes is identified by analyzing the number of *C. elegans* movements and neuronal fluorescence images. Subsequently, key neurotoxic substances in food are systematically screened using a combination of non-targeted liquid chromatography-tandem mass spectrometry (LC-MS / MS) and a metabolomics platform. This application establishes a novel method for screening neurotoxic substances by combining nematode activity with non-targeted LC-MS / MS determination and a non-targeted metabolic platform, clarifying key neurotoxic substances in food and providing a theoretical basis for food quality control and high-quality development.

The present application relates to the technical field of pharmaceutical analysis, and in particular to a combined analysis method for exploring the effect of Huangkui capsules on improving chronic kidney injury of tacrolimus based on metabolomics and proteomics. The combined analysis method of the present application explores how Huangkui capsules improve the mechanism of chronic kidney injury of tacrolimus from multiple dimensions, which is beneficial to in-depth analysis of the specific effects of Huangkui capsules at the molecular, cellular and tissue levels, reveals the key path and regulation mechanism of kidney protection, and can also provide a scientific basis for optimizing clinical application, further promoting the modernization of traditional Chinese medicine and its wide application in the treatment of kidney disease.

An IROA Matrix of metabolite compounds is disclosed. Each of whose compounds has a molecular weight of 2000 AMU or less, and is present as first and second isotopomers that are equally present at two predetermined isotopomeric balances, and contain 2 to 10% of a first isotope, and 90 to 98% of a second isotope, respectively. A reagent pair for transforming a natural abundance mass spectral analysis metabolite sample into an IROA sample is also disclosed and comprises two reactively identical reagents that constitute first and second isotopomers containing 2 to 10% of a first isotope, and 90 to 98% of a second isotope, respectively. Each of the reagent pair contains the same reactive group that reacts with and bonds to a functional group of one or more compounds present in a composition of biologically-produced metabolite compounds. Methods of making and using the above and related materials are also disclosed.

The present invention provides a novel integrated platform that enables the verification of manufacturing processes for complex natural products, as well as the standardization and evaluation of complex natural products. This platform allows for the "system-wide" characterization of complex mixtures contained in therapeutic and / or health-promoting products based on or composed of natural substances, without limiting the approach to reductionist chemical approaches targeting single markers. This is achieved through the integration of qualitative and quantitative fingerprint characterization data metabolomics and physical and biophysical activity data for the mixtures, thereby providing a product characterization that forms the basis for verifying manufacturing processes that can ensure the reproducibility of efficacy and safety across different batches of the product. The analytical platform described herein enables the assurance of a complex natural product as a whole, by considering all the characteristics of its quality and efficacy, through a multidimensional analytical approach, in order to ensure reproducibility regarding efficacy and safety.

The invention discloses an application of a benzophenone derivative as a bipolar matrix-assisted laser desorption ionization matrix in mass spectrometry detection. The benzophenone derivative matrix provided by the invention can effectively improve desorption ionization efficiency and reduce background interference, is compatible with a positive ion and negative ion bipolar detection mode, and solves the technical bottleneck of single polarity of a traditional matrix detection mode. The matrix has a wide-spectrum absorption characteristic in an ultraviolet region, can be adapted to laser wavelengths of various matrix-assisted laser desorption ionization mass spectrometers, and has a wide application prospect. Besides, when the matrix is used for lipid compound detection, lipid endogenous metabolite spectrum signals with high sensitivity and high coverage rate can be obtained in positive and negative ion modes, the matrix is expected to be widely used for metabonomics and clinical basic research, and key technical support is provided for high-sensitivity and bipolar imaging of small molecule compounds in complex biological samples.

This invention discloses a method for delaying leaf senescence in Paspalum notatum under salt stress. The method includes the following steps: plant material culture and salt stress treatment; H2O2 content determination; DAB staining; chlorophyll content and Fv / Fm value determination; lipidomics data determination and analysis; endogenous hormone level analysis; real-time quantitative PCR analysis of gene expression levels; and transcriptomics data analysis. This invention discovers that root-derived H2O2 in Paspalum notatum under salt-driven conditions delays leaf senescence by participating in the regulation of jasmonic acid. The role of root-derived H2O2 was studied using diphenylthioiodine (DPI), a specific inhibitor of NADPH oxidase. Furthermore, the influence of the presence or absence of root-derived H2O2 on the expression of genes related to jasmonic acid synthesis precursors was investigated at the gene expression level. Mass spectrometry-based omics technology and data analysis are the first key technologies for implementing this project. Lipidomics, as one of the most important branches of metabolomics, can perform qualitative and quantitative analysis at the level of individual lipid species.

The invention belongs to the technical field of biology, and relates to a gene related to synthesis of a sweet substance of lithocarpus litseifolius, which is used for resource evaluation and genetic background analysis of the sweet substance of lithocarpus litseifolius germplasm, metabonomics research of sweet substance difference, transcriptomics and biological information research of a sweet substance synthesis related enzyme gene and the like. A plurality of genes related to synthesis of the Lithocarpus litseifolius sweet substances are screened, the most important genes are Cluster-69084.4 (PGT1), and the most important genes further comprise Cluster-58209.2 (4CL), Cluster-68818.0 (CHI), Cluster-56317.2 (CHS) and the like. The related gene provided by the invention can be used for evaluating or breeding germplasm resources of Lithocarpus litseifolius, the Lithocarpus litseifolius can be developed into a novel natural sweetening agent, the source of the sweetening agent is widened, and the gene has very important theoretical significance and practical value.

The invention belongs to the technical field of microorganisms, and discloses an amorphophallus bulbifer southern blight infection influence analysis method based on metabonomics and microbiomics. Conjoint analysis shows that core florae (such as Streptomyces, Penicillium and Bauldia) are in significant positive correlation with phenylpropanoids and glutathione (succinic acid, coniferyl alcohol and glutamic acid), succinic acid is in positive correlation with Kribbella and Terrimonas, 2 ', 2' ', 2' ', 2' ', 2' ', 2' ', 2' ', 2' ', 2' ', 2' ', 2' ', 2' ', 2' ', 2' ', 2' ', 2' ', 2' ', 2' ', 2' ', 2' ', 2' ', 2' ', 2' ', the 3, 3 '-cycle CMP is negatively correlated with pathogen-related bacteria, which indicates that the metabolite regulates and controls the abundance of specific bacteria through positive / negative feedback so as to drive the microecological balance of rhizosphere, and a collaborative defense strategy that plants recruit beneficial microorganisms and inhibit pathogenic bacteria through metabolism reprogramming is disclosed.