Traditional Chinese medicine meridian prescription system for analyzing extracellular vesicles based on multi-omics integration

Abstract

The invention provides a traditional Chinese medicine meridian prescription system based on multi-omics integration analysis of extracellular vesicles, and the system comprises a data collection module which is used for collecting biopsy sample information of different groups of individuals based on related experiments and literatures of traditional Chinese medicine meridian prescription treatment; the data processing module is used for obtaining and preprocessing extracellular vesicle data and intestinal flora data based on biopsy sample information; the multi-omics integration module is used for obtaining multi-omics integration data; the discovery and verification module is used for obtaining the potential menstrual prescription drug effect evaluation biomarker and performing experimental verification on the potential menstrual prescription drug effect evaluation biomarker to obtain a verification result; and the system biology application module is used for obtaining a regulatory mechanism of the extracellular vesicles in a biological system based on construction of a gene-protein-metabolite interaction network. The invention can comprehensively reveal the pharmacodynamic mechanism of the traditional Chinese medicine menstrual prescription, and provides strong technical support and application prospect for the modern, scientific and internationalized development of traditional Chinese medicines.

Description

Technical Field

[0001] The present invention belongs to the field of research and application technology of traditional Chinese medicine, and specifically relates to a traditional Chinese medicine prescription system based on multi-omics integrated analysis of extracellular vesicles. Background Art

[0002] Traditional Chinese medicine prescriptions are an important part of the inheritance and development of traditional Chinese medicine, with a long history and rich clinical experience. Classic prescriptions refer to those prescriptions that are recorded in ancient classics of traditional Chinese medicine and have been tested in long-term clinical practice, with significant efficacy and wide application. These prescriptions occupy an important position in the theoretical system of traditional Chinese medicine. Their characteristics are rigorous prescription composition, concise medicinal ingredients, and definite efficacy, that is, "common, simple, cheap, and effective", which embodies the essence of traditional Chinese medicine's syndrome differentiation and treatment. The use of classic prescriptions does have its unique advantages. If the syndrome can be accurately identified and the appropriate classic prescription is selected, it can often be effective quickly during the treatment process. The comprehensive results of the multi-component and multi-target effects of classic prescription drugs are closely related to the holistic concept of traditional Chinese medicine treatment and the principle of individualized treatment. The development of modern science and technology has provided new means and methods for the study of classic prescriptions, especially through high-throughput omics technology and system biology methods, which can more deeply explore the pharmacodynamic mechanism and action pathway of classic prescriptions.

[0003] Extracellular vesicles (EVs) have shown important application prospects in the study of various diseases. Due to their stability and widespread presence in biological fluids, EVs have become important diagnostic and therapeutic biomarker carriers in liquid biopsies. For example, exosomes have been widely studied in cancer, neurodegenerative diseases, and infectious diseases. By analyzing their molecular composition, the disease mechanisms are revealed and new diagnostic and therapeutic targets are discovered. Microvesicles show an important role in cardiovascular and metabolic diseases, and participate in intercellular communication and pathological processes by carrying specific proteins and RNA molecules. In addition, apoptotic bodies have unique applications in immune regulation and cell death research. They promote immune responses by displaying apoptotic antigens and have potential immunoregulatory effects. By analyzing the molecular composition of EVs, the occurrence and development mechanisms of diseases can be revealed, providing new diagnostic and therapeutic targets.

[0004] The application of multi-omics technology has provided new ideas and means for the research of traditional Chinese medicine. Through technologies such as genomics, transcriptomics, proteomics and metabolomics, the chemical composition and biological activity of traditional Chinese medicine can be comprehensively analyzed to reveal its mechanism of action at the molecular level.

[0005] There are many problems and shortcomings in the existing technology: 1) Data integration is difficult: The multi-omics data of traditional Chinese medicine includes genomics, transcriptomics, proteomics and metabolomics, etc. The data is complex and diverse. The existing technology lacks a systematic data integration platform, making it difficult to obtain, share and analyze cross-domain data. 2) Lack of innovation in research methods: The existing technology has limitations in the research methods and evaluation systems for studying the multi-component and multi-target effects of traditional Chinese medicine, making it difficult to fully reveal the pharmacodynamic mechanism of traditional Chinese medicine. 3) Insufficient standardization and quality control: The standardization and quality control of traditional Chinese medicine prescriptions have not been fully resolved, and the existing technology is still insufficient in ensuring the safety and effectiveness of its clinical application. 4) Limited data analysis technology: The existing technology has limited technical means for data analysis and interpretation, and lacks effective bioinformatics tools to process and analyze massive data, which affects the efficiency and accuracy of the research. Summary of the invention

[0006] In view of the shortcomings of the prior art, the present invention provides a TCM prescription system based on multi-omics integrated analysis of extracellular vesicles. Through the study of extracellular vesicles in TCM prescriptions, the molecular mechanism of the treatment process is revealed or potential biomarkers are identified.

[0007] To achieve the above object, the present invention provides the following solutions:

[0008] A TCM prescription system based on multi-omics integrated analysis of extracellular vesicles, including: data acquisition module, data processing module, multi-omics integration module, discovery verification module and systems biology application module;

[0009] The data collection module is used to collect biopsy sample information of individuals in different groups based on relevant experiments and literature on traditional Chinese medicine prescriptions;

[0010] The data processing module is used to obtain and pre-process the extracellular vesicle data and the intestinal flora data based on the biopsy sample information; wherein the extracellular vesicles include exosomes, microvesicles and apoptotic bodies;

[0011] The multi-omics integration module is used to obtain multi-omics data of different groups based on the pre-processed extracellular vesicle data and the intestinal flora data, and integrate the multi-omics data based on different bioinformatics methods to obtain multi-omics integrated data;

[0012] The discovery verification module is used to compare and screen the multi-omics integrated data of different groups to obtain potential biomarkers for evaluating the efficacy of traditional Chinese medicine prescriptions, and to experimentally verify the potential biomarkers for evaluating the efficacy of traditional Chinese medicine prescriptions to obtain verification results;

[0013] The systems biology application module is used to construct a gene-protein-metabolite interaction network based on systems biology, the potential classical prescription efficacy evaluation biomarkers and the verification results, and obtain the regulatory mechanism of extracellular vesicles in biological systems.

[0014] Preferably, the biopsy sample information includes liquid biopsy sample information and fecal biopsy sample information of individuals in different groups;

[0015] Among them, different groups of individuals include healthy normal group individuals, diseased group individuals and traditional Chinese medicine treatment group individuals; the liquid biopsy sample information includes blood data, urine data, cerebrospinal fluid data and saliva data.

[0016] Preferably, in the data processing module, data cleaning, missing value processing and standardization are performed on the extracellular vesicle data and the intestinal flora data.

[0017] Preferably, the multi-omics integration module comprises:

[0018] A genomics data acquisition unit, used to sequence DNA data of extracellular vesicles of different groups to obtain genomics data;

[0019] A transcriptomics data acquisition unit, used to reverse transcribe RNA data of extracellular vesicles of different groups to obtain transcriptomics data;

[0020] Proteomics data acquisition unit, used to extract protein data of extracellular vesicles of different groups and obtain proteomics data based on mass spectrometry technology;

[0021] Metabolomics data acquisition unit, used to obtain metabolomics data based on nuclear magnetic resonance and liquid chromatography-mass spectrometry technology;

[0022] A metagenomic data acquisition unit, used to obtain metagenomic data of different groups of intestinal flora based on high-throughput sequencing technology;

[0023] An integration unit is used to integrate the genomics data, the transcriptomics data, the proteomics data, the metabolomics data and the metagenomics data to obtain multi-omics integrated data.

[0024] Preferably, the discovery verification module includes:

[0025] The gene comparison unit is used to compare the genomic data of different groups to obtain the genome variation structure;

[0026] The transcription comparison unit is used to compare the transcriptomic data of different groups to obtain gene expression differences;

[0027] The protein comparison unit is used to compare the proteomics data of different groups to obtain protein expression differences;

[0028] The metabolic comparison unit is used to compare the metabolomics data of different groups and build metabolic pathway models based on the existing bioinformatics database to obtain metabolic flow differences;

[0029] The intestinal flora comparison unit is used to compare the metagenomic data of different groups to obtain the differences in flora composition;

[0030] A marker acquisition unit, for obtaining a potential biomarker for evaluating the efficacy of a traditional Chinese medicine prescription based on the genome variation structure, the gene expression difference, the protein expression difference, the metabolic flux difference, and the bacterial community composition difference;

[0031] The verification unit is used to perform experimental verification on the potential biomarker for evaluating the efficacy of traditional Chinese medicine prescriptions to obtain verification results.

[0032] Preferably, the systems biology application module comprises:

[0033] A network topology analysis unit, for analyzing the nodes and functional modules of the constructed network based on the potential classical prescription efficacy evaluation biomarkers and the verification results, and obtaining the biological functions of the key nodes and functional modules;

[0034] The functional enrichment analysis unit is used to perform gene ontology analysis and pathway enrichment analysis on the biological functions of the key nodes and each functional module to obtain a gene-protein-metabolite interaction network.

[0035] Preferably, the network topology analysis unit includes:

[0036] A node analysis subunit, for analyzing node degree distribution based on the potential classical prescription efficacy evaluation biomarkers and the verification results, and obtaining key nodes; wherein the key nodes include genes, proteins and metabolites;

[0037] The module analysis subunit is used to obtain the functions of the data acquisition module, the data processing module, the multi-omics integration module and the discovery and verification module based on the detection algorithm, and to analyze the biological functions within each functional module.

[0038] Preferably, the functional enrichment analysis unit comprises:

[0039] A gene ontology analysis subunit, used to perform gene ontology analysis on the key nodes and the biological functions of each functional module to identify the biological functions;

[0040] The pathway enrichment analysis subunit performs pathway enrichment analysis on the key nodes and each functional module to identify biological processes.

[0041] Compared with the prior art, the beneficial effects of the present invention are as follows: the system of the present invention is used for the modernization research of Chinese medicine prescriptions, analysis of drug efficacy mechanisms, discovery of diagnostic biomarkers and personalized medication guidance. By integrating various visual data such as genomics, transcriptomics, proteomics, metabolomics and metagenomics of intestinal flora, the system analyzes the mechanism of action of Chinese medicine prescriptions at the molecular level, thereby improving the clinical application effect and international promotion of Chinese medicine prescriptions. With the support of bioinformatics, systems biology and cloud computing technology, the present invention has constructed an efficient and intelligent cloud platform for Chinese medicine prescription research, which is widely used in specific technical fields such as basic research, clinical research, new drug development and personalized medicine of traditional Chinese medicine. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] In order to more clearly illustrate the technical solution of the present invention, the following briefly introduces the drawings required for use in the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative labor.

[0043] Figure 1 This is a schematic diagram of the structure of a cloud platform for traditional Chinese medicine prescriptions based on multi-omics integrated analysis of extracellular vesicles according to an embodiment of the present invention;

[0044] Figure 2 A schematic diagram of a protein-metabolite interaction network according to an embodiment of the present invention;

[0045] Figure 3 A schematic diagram of a protein interaction network according to an embodiment of the present invention;

[0046] Figure 4 This is a visualization diagram of active ingredient-target-pathway signals of Chinese medicine in an embodiment of the present invention;

[0047] Figure 5 This is a transcriptome-protein-metabolite correlation network diagram of an embodiment of the present invention. DETAILED DESCRIPTION

[0048] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0049] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the present invention is further described in detail below with reference to the accompanying drawings and specific embodiments.

[0050] Embodiment 1

[0051] like Figure 1 As shown, the TCM prescription system (cloud platform) based on multi-omics integrated analysis of extracellular vesicles includes: data acquisition module, data processing module, multi-omics integration module (multi-omics integration and analysis module), discovery and verification module (biomarker discovery and verification module for prescription efficacy evaluation) and system biology application module;

[0052] A data collection module is used to collect biopsy sample information of individuals in different groups based on relevant experiments and literature on traditional Chinese medicine prescriptions; a further implementation method is that the biopsy sample information includes liquid biopsy sample information and fecal biopsy sample information of individuals in different groups;

[0053] Among them, different groups of individuals include healthy normal group individuals, disease group individuals and traditional Chinese medicine treatment group individuals; liquid biopsy sample information includes blood data, urine data, cerebrospinal fluid data and saliva data. EVs are extracted from these biological fluids for multi-omics analysis.

[0054] Healthy Normal Group: Include healthy individuals as a control group for comparative analysis.

[0055] Disease group: includes patients with a specific disease and is used to study the molecular mechanisms associated with the disease.

[0056] The classical prescription treatment group includes patients who received classical prescription treatment of traditional Chinese medicine, and is used to study the therapeutic effects and molecular mechanisms of classical prescriptions.

[0057] A data processing module, used to obtain and pre-process extracellular vesicle data and intestinal flora data based on biopsy sample information; wherein the extracellular vesicles include exosomes, microvesicles and apoptotic bodies;

[0058] Exosomes: Small vesicles secreted by cells that are involved in intercellular communication.

[0059] Microvesicles: Larger vesicles formed by budding from the cell membrane.

[0060] Apoptotic bodies: small bodies formed by apoptotic cells that carry information related to cell apoptosis.

[0061] In this embodiment, extracellular vesicles (EVs) can be divided into subgroups such as exosomes, microvesicles and apoptotic bodies according to their size and origin. Each subgroup has important biological characteristics and functions. In the data processing module, the present invention will also collect EVs-related biological information data and classify them into exosomes, microvesicles and apoptotic bodies to ensure the breadth and comprehensiveness of the data.

[0062] A further implementation method is that, in the data processing module, data cleaning, missing value processing and standardization are performed on the extracellular vesicle data and the intestinal flora data.

[0063] The multi-omics integration module is used to obtain multi-omics data of different groups based on the pre-processed extracellular vesicle data and intestinal flora data, and integrate the multi-omics data based on different bioinformatics methods to obtain multi-omics integrated data;

[0064] Multi-omics analysis includes:

[0065] Genomics: The study of the structure, function, and variation of genomes.

[0066] Transcriptomics: studying the global picture and dynamic changes of gene expression.

[0067] Proteomics: The study of protein structure, function and interactions.

[0068] Metabolomics: the study of the composition and changes of metabolites.

[0069] Metagenomics: studying the composition and function of the intestinal microbiota.

[0070] In a further embodiment, the multi-omics integration module comprises:

[0071] The genomic data acquisition unit is used to sequence the DNA data of extracellular vesicles of different groups to obtain genomic data; specifically, genomic data is used to study the effects of traditional Chinese medicine on genome structure and gene mutations, and data is obtained through whole genome sequencing (WGS) and whole exome sequencing (WES). First, the DNA of extracellular vesicles of different groups is extracted to construct a sequencing library. The library is sequenced using technologies such as WGS or WES, and the adapters, low-quality bases, and repeated sequences are removed.

[0072] The transcriptomics data acquisition unit is used to reverse transcribe the RNA data of extracellular vesicles of different groups to obtain transcriptomics data; specifically, the transcriptomics data is used to analyze the regulatory effect of traditional Chinese medicine on gene expression, and the data is obtained through RNA sequencing (RNA-seq) technology. First, RNA is extracted from extracellular vesicle samples of different groups. RNA is converted into cDNA through reverse transcription.

[0073] The proteomics data acquisition unit is used to extract protein data from different groups of extracellular vesicles and obtain proteomics data based on mass spectrometry technology; specifically, proteomics data is used to study the effects of traditional Chinese medicine on protein expression and post-translational modification, and data is obtained through mass spectrometry (MS) technology. First, proteins are extracted from extracellular vesicle samples from different groups and digested into peptides using enzymes (such as trypsin). The mass spectrometry data is analyzed to determine the protein identity and modification status.

[0074] The metabolomics data acquisition unit is used to obtain metabolomics data based on nuclear magnetic resonance and liquid chromatography-mass spectrometry technology. Specifically, metabolomics data is used to analyze the regulatory effect of traditional Chinese medicine on metabolites. First, nuclear magnetic resonance (NMR) and liquid chromatography-mass spectrometry (LC-MS) technology are used to obtain data on extracellular vesicles of different groups. Based on databases such as KEGG or HMDB, metabolic pathway models are constructed to analyze changes in metabolic flow.

[0075] The metagenomic data acquisition unit is used to obtain metagenomic data of different groups of intestinal flora based on high-throughput sequencing technology; specifically, metagenomic analysis of intestinal flora: firstly, high-throughput sequencing technology (such as 16S-rRNA gene sequencing and metagenomic sequencing) is used to obtain metagenomic data of different groups of intestinal flora. Examples of the application of intestinal flora in the study of traditional Chinese medicine prescriptions: studying the interaction between intestinal flora and traditional Chinese medicine prescriptions, revealing the regulatory mechanism of traditional Chinese medicine on intestinal flora, and the role of flora in the efficacy of traditional Chinese medicine, providing a scientific basis for personalized medication.

[0076] The omics analysis methods in each of the above parts can obtain rich biological information.

[0077] The integration unit is used to integrate genomic data, transcriptomics data, proteomics data, metabolomics data and metagenomic data to obtain multi-omics integrated data.

[0078] The discovery and verification module is used to compare and screen the multi-omics integrated data of different groups to obtain potential biomarkers for the evaluation of the efficacy of classical prescriptions, and to experimentally verify the potential biomarkers for the evaluation of the efficacy of classical prescriptions to obtain verification results. Specifically, through multi-omics data and bioinformatics analysis, the normal group, patient group and classical prescription treatment group are compared and screened to obtain potential biomarkers for the evaluation of the efficacy of classical prescriptions, and integrated analysis is performed to further determine the significance and reliability of the markers.

[0079] A further implementation is that the discovery verification module includes:

[0080] The gene comparison unit is used to compare genomic data of different groups to obtain the genome variation structure; specifically, the sequence reads are aligned to the reference genome to determine the genome variation.

[0081] The transcription comparison unit is used to compare transcriptomic data of different groups to obtain gene expression differences; that is, to compare expression differences under different conditions and find potential biomarkers or regulatory mechanisms.

[0082] The protein comparison unit is used to compare the proteomics data of different groups to obtain protein expression differences; that is, to perform protein function annotation, network analysis and differential expression analysis.

[0083] The metabolic comparison unit is used to compare the metabolomics data of different groups and build metabolic pathway models based on the existing bioinformatics database to obtain metabolic flow differences;

[0084] The intestinal flora comparison unit is used to compare the metagenomic data of different groups to obtain the differences in flora composition; clean, assemble and annotate the intestinal flora data, and analyze the composition and function of the flora.

[0085] The marker acquisition unit is used to obtain potential biomarkers for evaluating the efficacy of traditional Chinese medicine prescriptions based on genomic variation structure, gene expression differences, protein expression differences, metabolic flow differences, and bacterial flora composition differences;

[0086] The verification unit is used to conduct experimental verification of potential biomarkers for evaluating the efficacy of traditional Chinese medicine prescriptions and obtain verification results.

[0087] In this example, potential biomarkers for evaluating the efficacy of traditional Chinese medicine prescriptions were verified through experiments, including qPCR, Western Blot, ELISA and other technologies, to ensure the specificity and sensitivity of the markers.

[0088] Specifically, use cell lines or animal models for experimental verification to confirm that the selected biomarkers are indeed related to the efficacy of the prescription under experimental conditions. Process samples and perform biomarker detection (such as qPCR, Western Blot, etc.). Analyze the experimental results to confirm whether the expression level of the biomarker is related to the efficacy. Study the role of EVs in traditional Chinese medicine prescriptions, discover and verify that molecules in EVs are used as biomarkers for evaluating the efficacy of prescriptions, and provide a scientific basis for the efficacy of traditional Chinese medicine and personalized medication.

[0089] The system biology application module is used to construct a gene-protein-metabolite interaction network based on system biology, potential traditional Chinese medicine efficacy evaluation biomarkers and verification results, and obtain the regulatory mechanism of extracellular vesicles in biological systems. The gene-protein-metabolite interaction network uses the coding relationship between genes and proteins to construct the association between genes and proteins. Figure 2 , Figure 3 shown. Figure 2 In the figure, red circles represent metabolites, green circles represent proteins, and the thickness of the line represents the strength of the correlation between metabolites and proteins. The thicker the line, the stronger the correlation.

[0090] In a further embodiment, the systems biology application module comprises:

[0091] The network topology analysis unit is used to analyze the nodes and functional modules of the constructed network based on the potential classical prescription efficacy evaluation biomarkers and verification results, and obtain the biological functions of the key nodes and functional modules;

[0092] The functional enrichment analysis unit is used to perform gene ontology analysis and pathway enrichment analysis on the biological functions of key nodes and each functional module to obtain the gene-protein-metabolite interaction network.

[0093] A further implementation is that the network topology analysis unit comprises:

[0094] The node analysis subunit is used to evaluate biomarkers and verify results based on potential traditional Chinese medicine prescriptions, analyze node degree distribution, and obtain key nodes; key nodes include genes, proteins, and metabolites;

[0095] The module analysis subunit is used to obtain the functions of the data acquisition module, data processing module, multi-omics integration module and discovery verification module based on the detection algorithm (such as MCL, Louvain), and analyze the biological functions within each functional module.

[0096] A further embodiment is that the functional enrichment analysis unit comprises:

[0097] Gene ontology (GO) analysis subunit, used to perform gene ontology analysis on key nodes and biological functions of each functional module to identify biological functions;

[0098] The pathway enrichment analysis subunit uses pathway databases such as KEGG and Reactome to perform pathway enrichment analysis on key nodes and functional modules to identify biological processes.

[0099] In this embodiment, the specific process of constructing the gene-protein phase-metabolite interaction network includes:

[0100] Data preprocessing: Multi-omics datasets were standardized and normalized, and random forests were used to interpolate missing values.

[0101] Data exploratory analysis: Principal component analysis (PCA) was performed on the preprocessed multi-omics dataset to identify patterns and trends in the data. Cluster analysis was used to explore similarities and differences between samples.

[0102] Model construction: Based on metabolomics, proteomics, transcriptomics, genomics and the combination of these omics (integrated data), the LASSO (least absolute shrinkage and selection operator) regression algorithm was used to predict individual EVs and obtain a prediction model.

[0103] Feature selection: The LASSO algorithm was used to deal with the multicollinearity problem and select important features (metabolites, proteins, and genes) in the prediction model, which have strong correlations with EVs.

[0104] Model evaluation: Use an independent test set to evaluate the accuracy, sensitivity, and specificity of the model to test the generalization ability of the model. Statistical indicators such as confusion matrix, ROC curve, and AUC value can be calculated.

[0105] Heterogeneity analysis: Heterogeneity analysis was performed by comparing the differences between actual EVs and EVs predicted by the prediction model.

[0106] Bioinformatics analysis: interpret the prediction results of the prediction model and convert the data into biological significance. Perform functional annotation and pathway analysis on the selected markers. Perform enrichment analysis using databases (such as KEGG, Reactome).

[0107] Knowledge base network construction and analysis: Integrate the analysis results into the knowledge base of systems biology to provide resources for further research and application. Figure 4 , Figure 5 As shown in the figure, construct the gene-protein-metabolite interaction network using network visualization tools such as Cytoscape, R packages such as igraph or circlize to create network graphs. Set the properties of nodes and edges, such as size, color, and shape, to represent different biological entities and the relationships between them. Add annotations to the network graph, such as gene name, protein function, and metabolite type. Apply network analysis tools to identify key hub molecules or modules.

[0108] In this example, the role of combining systems biology with multi-omics analysis of EVs:

[0109] 1) Application of systems biology methods in EVs analysis: Apply systems biology methods to construct and analyze gene-protein-metabolite interaction networks and reveal regulatory mechanisms in complex biological systems.

[0110] 2) Construction of gene-protein-metabolite interaction networks: Using systems biology tools and algorithms, gene-protein-metabolite interaction networks are constructed. By analyzing these networks, the regulatory mechanisms of EVs in different physiological and pathological states can be revealed, helping to discover key regulatory nodes and molecules.

[0111] 3) Analysis of EVs regulatory mechanisms in complex biological systems: Through multi-omics data and systems biology methods, analyze the regulatory mechanisms of EVs in complex biological systems. Focus on the role of EVs in intercellular communication, metabolic regulation, and disease occurrence and development, and provide new theoretical basis and research ideas.

[0112] Through the construction of this platform, we can systematically and comprehensively study the molecular mechanisms of traditional Chinese medicine prescriptions in the treatment process, discover new biomarkers and therapeutic targets, and improve the clinical application effect and international promotion of traditional Chinese medicine prescriptions. The system of the present invention has a wide range of applications:

[0113] 1) Basic research on traditional Chinese medicine: Use multi-omics technology to deeply study the pharmacological material basis and mechanism of action of traditional Chinese medicine prescriptions, and reveal their molecular mechanism in the treatment of diseases.

[0114] 2) Clinical research and application: Through the integrated analysis of multi-omics data, potential diagnostic biomarkers and therapeutic targets are discovered to guide clinicians in personalized medication and improve the clinical efficacy of traditional Chinese medicine prescriptions.

[0115] 3) New drug development: Utilize the platform’s data analysis and model prediction capabilities to screen and verify new drug molecules and combinations, and provide scientific basis and technical support for the development of new Chinese medicines.

[0116] 4) Personalized medicine: Combining the patient's multi-omics data, formulate personalized Chinese medicine treatment plans, achieve precision medicine, and improve the patient's treatment effect and quality of life.

[0117] 5) International promotion: Through the platform's scientific data and analysis results, we will promote the recognition and application of Chinese medicine prescriptions in the international medical community and promote the promotion and development of Chinese medicine on a global scale.

[0118] The embodiments described above are only descriptions of the preferred embodiments of the present invention and are not intended to limit the scope of the present invention. Without departing from the design spirit of the present invention, various modifications and improvements made to the technical solutions of the present invention by ordinary technicians in this field should all fall within the protection scope determined by the claims of the present invention.

Claims

1. A Chinese medicine prescription system based on multi-omics integrated analysis of extracellular vesicles, characterized by: include: Data acquisition module, data processing module, multi-omics integration module, discovery and verification module, and systems biology application module; The data collection module is used to collect biopsy sample information of individuals in different groups based on relevant experiments and literature on traditional Chinese medicine prescriptions; The data processing module is used to obtain and pre-process extracellular vesicle data and intestinal flora data based on the biopsy sample information; wherein the extracellular vesicles include exosomes, microvesicles and apoptotic bodies; The multi-omics integration module is used to obtain multi-omics data of different groups based on the pre-processed extracellular vesicle data and the intestinal flora data, and integrate the multi-omics data based on different bioinformatics methods to obtain multi-omics integrated data; The discovery verification module is used to compare and screen the multi-omics integrated data of different groups to obtain potential biomarkers for evaluating the efficacy of traditional Chinese medicine prescriptions, and to experimentally verify the potential biomarkers for evaluating the efficacy of traditional Chinese medicine prescriptions to obtain verification results; The systems biology application module is used to construct a gene-protein-metabolite interaction network based on systems biology, the potential classical prescription efficacy evaluation biomarkers and the verification results, and obtain the regulatory mechanism of extracellular vesicles in biological systems.

2. The TCM prescription system based on multi-omics integrated analysis of extracellular vesicles according to claim 1, characterized in that: The biopsy sample information includes liquid biopsy sample information and fecal biopsy sample information of individuals in different groups; Among them, different groups of individuals include healthy normal group individuals, diseased group individuals and traditional Chinese medicine treatment group individuals; the liquid biopsy sample information includes blood data, urine data, cerebrospinal fluid data and saliva data.

3. The TCM prescription system based on multi-omics integrated analysis of extracellular vesicles according to claim 2, characterized in that: In the data processing module, data cleaning, missing value processing and standardization are performed on the extracellular vesicle data and the intestinal flora data.

4. The TCM prescription system based on multi-omics integrated analysis of extracellular vesicles according to claim 2, characterized in that: The multi-omics integration module includes: A genomics data acquisition unit, used to sequence DNA data of extracellular vesicles of different groups to obtain genomics data; A transcriptomics data acquisition unit, used to reverse transcribe RNA data of extracellular vesicles of different groups to obtain transcriptomics data; Proteomics data acquisition unit, used to extract protein data of extracellular vesicles of different groups and obtain proteomics data based on mass spectrometry technology; Metabolomics data acquisition unit, used to obtain metabolomics data based on nuclear magnetic resonance and liquid chromatography-mass spectrometry technology; A metagenomic data acquisition unit, used to obtain metagenomic data of different groups of intestinal flora based on high-throughput sequencing technology; An integration unit is used to integrate the genomics data, the transcriptomics data, the proteomics data, the metabolomics data and the metagenomics data to obtain multi-omics integrated data.

5. The TCM prescription system based on multi-omics integrated analysis of extracellular vesicles according to claim 4, characterized in that: The discovery verification module includes: The gene comparison unit is used to compare the genomic data of different groups to obtain the genome variation structure; The transcription comparison unit is used to compare the transcriptomic data of different groups to obtain gene expression differences; The protein comparison unit is used to compare the proteomics data of different groups to obtain protein expression differences; The metabolic comparison unit is used to compare the metabolomics data of different groups and build metabolic pathway models based on the existing bioinformatics database to obtain metabolic flow differences; The intestinal flora comparison unit is used to compare the metagenomic data of different groups to obtain the differences in flora composition; A marker acquisition unit, for obtaining a potential biomarker for evaluating the efficacy of a traditional Chinese medicine prescription based on the genome variation structure, the gene expression difference, the protein expression difference, the metabolic flux difference, and the bacterial community composition difference; The verification unit is used to perform experimental verification on the potential biomarker for evaluating the efficacy of traditional Chinese medicine prescriptions to obtain verification results.

6. The TCM prescription system based on multi-omics integrated analysis of extracellular vesicles according to claim 5, characterized in that: The systems biology application module includes: A network topology analysis unit, for analyzing the nodes and functional modules of the constructed network based on the potential classical prescription efficacy evaluation biomarkers and the verification results, and obtaining the biological functions of the key nodes and functional modules; The functional enrichment analysis unit is used to perform gene ontology analysis and pathway enrichment analysis on the biological functions of the key nodes and each functional module to obtain a gene-protein-metabolite interaction network.

7. The TCM prescription system based on multi-omics integrated analysis of extracellular vesicles according to claim 6, characterized in that: The network topology analysis unit comprises: A node analysis subunit, for analyzing node degree distribution based on the potential classical prescription efficacy evaluation biomarkers and the verification results, and obtaining key nodes; wherein the key nodes include genes, proteins and metabolites; The module analysis subunit is used to obtain the functions of the data acquisition module, the data processing module, the multi-omics integration module and the discovery and verification module based on the detection algorithm, and to analyze the biological functions within each functional module.

8. The TCM prescription system based on multi-omics integrated analysis of extracellular vesicles according to claim 6, characterized in that: The functional enrichment analysis unit comprises: A gene ontology analysis subunit, used to perform gene ontology analysis on the key nodes and the biological functions of each functional module to identify the biological functions; The pathway enrichment analysis subunit performs pathway enrichment analysis on the key nodes and each functional module to identify biological processes.

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