Method, device, equipment, medium and program product for determining flora regulation and control effect

Abstract

The invention relates to a flora regulation and control effect determination method, device and equipment, a medium and a program product. The method comprises the following steps: determining a target intestinal flora from to-be-selected intestinal flora, determining a target traditional Chinese medicine component from to-be-selected traditional Chinese medicine components according to the target intestinal flora and to-be-selected traditional Chinese medicine components, and then constructing an in-vitro model for simulating a human intestinal physiological environment based on a human intestinal microbial ecosystem simulator SHIME. A control experiment is performed based on the in-vitro model, the target intestinal flora and the target traditional Chinese medicine components, so that the regulation effect of the target traditional Chinese medicine components on the target intestinal flora can be determined based on data of the control experiment, and a mechanism of regulating intestinal immunity by traditional Chinese medicine is deeply disclosed. Moreover, according to the embodiment of the invention, the human intestinal physiological environment is simulated based on SHIME, the in-vitro model closer to the real physiological state is provided, and the accuracy of the regulation effect obtained based on the in-vitro model is further improved.

Description

Technical Field

[0001] This application relates to the field of biomedical technologies, and particularly to a method, device, equipment, medium, and program product for determining the effect of microbiota regulation. Background Art

[0002] As the largest immune organ in the human body, the gut microbiota plays a crucial role in maintaining gut immune balance. Therefore, understanding which gut microbiota are involved in gut immune regulation and how to effectively regulate these gut microbiota with traditional Chinese medicine has great medical significance. Thus, how to evaluate the regulatory effect of traditional Chinese medicine components on gut microbiota has become an urgent problem to be solved in this field. Summary of the Invention

[0003] Based on this, in view of the above technical problems, it is necessary to provide a method, device, equipment, medium, and program product for determining the effect of microbiota regulation that can evaluate the regulatory effect of traditional Chinese medicine components on gut microbiota.

[0004] In a first aspect, this application provides a method for determining the effect of microbiota regulation. The method includes:

[0005] Determining target gut microbiota from candidate gut microbiota;

[0006] Determining target traditional Chinese medicine components from the candidate traditional Chinese medicine components according to the target gut microbiota and the candidate traditional Chinese medicine components;

[0007] Constructing an in vitro model for simulating the human gut physiological environment based on the human gut microbiota ecosystem simulator SHIME;

[0008] Conducting a control experiment based on the in vitro model, the target gut microbiota, and the target traditional Chinese medicine components to determine the regulatory effect of the target traditional Chinese medicine components on the target gut microbiota.

[0009] In one embodiment, the determining target gut microbiota from candidate gut microbiota includes:

[0010] Obtaining sequencing data of the candidate gut microbiota and index data of gut immune factors from multiple public databases;

[0011] Performing correlation analysis according to the sequencing data and the index data to construct a regulatory network; the regulatory network is used to characterize the interaction relationship between the candidate gut microbiota and the gut immune factors;

[0012] Determining the target gut microbiota from the candidate gut microbiota according to the regulatory network.

[0013] In one embodiment, the determining target traditional Chinese medicine components from the candidate traditional Chinese medicine components according to the target gut microbiota and the candidate traditional Chinese medicine components includes:

[0014] Perform molecular docking simulations on the candidate traditional Chinese medicine components and the target intestinal flora to obtain docking parameters;

[0015] Determine the target traditional Chinese medicine components from the candidate traditional Chinese medicine components according to the docking parameters.

[0016] In one embodiment, perform a control experiment based on the in vitro model, the target intestinal flora, and the target traditional Chinese medicine components to determine the regulatory effect of the target traditional Chinese medicine components on the target intestinal flora, including:

[0017] Determine the in vitro model as the first control group;

[0018] Add the target intestinal flora to the in vitro model to obtain a second control group;

[0019] Add the target intestinal flora and the target traditional Chinese medicine components to the in vitro model to obtain an experimental group;

[0020] Every first preset time interval, add an equal amount of culture medium to the first control group, the second control group, and the experimental group to conduct the control experiment and determine the regulatory effect of the target traditional Chinese medicine components on the target intestinal flora.

[0021] In one embodiment, every first preset time interval, add an equal amount of culture medium to the first control group, the second control group, and the experimental group to conduct the control experiment, including:

[0022] Every first preset time interval, add an equal amount of culture medium to the first control group, the second control group, and the experimental group;

[0023] Every second preset time interval, collect the monitoring data of the first control group, the second control group, and the experimental group; the monitoring data is used to determine the regulatory effect of the target traditional Chinese medicine components on the target intestinal flora.

[0024] In one embodiment, the culture medium includes at least one of culture solution, nutrients, and drug components, and the culture medium is used to simulate the process of human diet and drug intake.

[0025] In a second aspect, the present application also provides a device for determining the regulatory effect of intestinal flora. The device includes:

[0026] A first determination module for determining a target intestinal flora from candidate intestinal flora;

[0027] A second determination module for determining target traditional Chinese medicine components from the candidate traditional Chinese medicine components according to the target intestinal flora and the candidate traditional Chinese medicine components;

[0028] A building module for constructing an in vitro model for simulating the physiological environment of the human intestine based on the human intestinal microbiota ecosystem simulator SHIME;

[0029] A control experiment module for conducting a control experiment based on the in vitro model, the target intestinal microbiota, and the target traditional Chinese medicine ingredient to determine the regulatory effect of the target traditional Chinese medicine ingredient on the target intestinal microbiota.

[0030] In a third aspect, the present application also provides a computer device, including a memory and a processor. The memory stores a computer program, and when the processor executes the computer program, the steps of any of the above methods are implemented.

[0031] In a fourth aspect, the present application also provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the steps of any of the above methods are implemented.

[0032] In a fifth aspect, the present application also provides a computer program product, including a computer program. When the computer program is executed by a processor, the steps of any of the above methods are implemented.

[0033] The above method, device, equipment, medium, and program product for determining the regulatory effect of the microbiota can determine the target intestinal microbiota from the candidate intestinal microbiota, determine the target traditional Chinese medicine ingredient from the candidate traditional Chinese medicine ingredients according to the target intestinal microbiota and the candidate traditional Chinese medicine ingredients, then construct an in vitro model for simulating the physiological environment of the human intestine based on the human intestinal microbiota ecosystem simulator SHIME, and conduct a control experiment based on the in vitro model, the target intestinal microbiota, and the target traditional Chinese medicine ingredient. Thus, the regulatory effect of the target traditional Chinese medicine ingredient on the target intestinal microbiota can be determined based on the data of the control experiment, and the mechanism of traditional Chinese medicine regulating intestinal immunity is deeply revealed. Moreover, in the embodiments of the present application, an in vitro model closer to the real physiological state is provided based on SHIME simulating the physiological environment of the human intestine, thereby improving the accuracy of the regulatory effect obtained based on the in vitro model. Description of the Drawings

[0034] Figure 1 is an internal structure diagram of a computer device provided by an embodiment of the present application;

[0035] Figure 2 is a flowchart of a method for determining the regulatory effect of the microbiota provided by an embodiment of the present application;

[0036] Figure 3 is a flowchart of a method for determining the target intestinal microbiota provided by an embodiment of the present application;

[0037] Figure 4 is a flowchart of a method for determining the target traditional Chinese medicine ingredient provided by an embodiment of the present application;

[0038] Figure 5 It is a schematic flowchart of a method for determining the regulatory effect of a target traditional Chinese medicine component on target intestinal flora provided by an embodiment of the present application;

[0039] Figure 6 It is a schematic flowchart of a control experiment provided by an embodiment of the present application;

[0040] Figure 7 It is a schematic flowchart of a method for determining the regulatory effect of intestinal flora based on public data mining and SHIME platform provided by an embodiment of the present application;

[0041] Figure 8 It is a structural block diagram of a device for determining the regulatory effect of flora provided by an embodiment of the present application. Detailed implementation manners

[0042] In order to make the objectives, technical solutions and advantages of the present application clearer, the present application will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application, and are not used to limit the present application.

[0043] As the largest immune organ in the human body, intestinal flora plays a crucial role in maintaining intestinal immune balance. Therefore, understanding which intestinal flora is involved in intestinal immune regulation and how to effectively regulate these intestinal flora with traditional Chinese medicine has great medical significance. Therefore, how to evaluate the regulatory effect of traditional Chinese medicine components on intestinal flora has become an urgent problem to be solved in this field.

[0044] The method for determining the regulatory effect of flora provided by the embodiments of the present application can be applied to an application environment as Figure 1 shown. Figure 1 It is an internal structural diagram of a computer device provided by an embodiment of the present application. The computer device can be a server, and its internal structural diagram can be as Figure 1 shown. The computer device includes a processor, a memory and a network interface connected through a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The network interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, it realizes a method for determining the regulatory effect of flora.

[0045] Those skilled in the art can understand, Figure 1The structure shown is only a block diagram of some structures related to the solution of this application, and does not constitute a limitation on the computer device to which the solution of this application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine some components, or have different component arrangements.

[0046] In one embodiment, as Figure 2 shown, Figure 2 is a schematic flowchart of a method for determining the effect of gut microbiota regulation provided by an embodiment of this application. This method can be applied to Figure 1 the computer device in, and this method includes the following steps:

[0047] S201, determine the target gut microbiota from the candidate gut microbiota.

[0048] In one embodiment, 16S rRNA sequencing data of each candidate gut microbiota and index data of gut immune factors related to the candidate gut microbiota can be obtained from multiple public databases, and then based on the 16S rRNA sequencing data and the index data, the target gut microbiota that plays a key role in gut immune regulation can be determined from the candidate gut microbiota.

[0049] Among them, the public database can include, for example, the SRA (Sequence Read Archive) database, the ENA (European Nucleotide Archive) database, etc. The index data of gut immune factors can include, for example, the level of inflammatory factors, the number of immune cells, etc.

[0050] S202, determine the target traditional Chinese medicine ingredient from the candidate traditional Chinese medicine ingredients according to the target gut microbiota and the candidate traditional Chinese medicine ingredients.

[0051] In the embodiment of this application, the chemical composition information of the candidate traditional Chinese medicine ingredients can be obtained from multiple databases, and then the molecular docking software is used to perform molecular docking simulation on the candidate traditional Chinese medicine ingredients and the target gut microbiota according to the chemical composition information of the candidate traditional Chinese medicine ingredients to obtain docking parameters, so as to be able to determine the target traditional Chinese medicine ingredient that has a potential regulatory effect on the target gut microbiota from the candidate traditional Chinese medicine ingredients according to the docking parameters.

[0052] S203, construct an in vitro model for simulating the human gut physiological environment based on the human gut microbiota ecosystem simulator SHIME.

[0053] Exemplarily, parameters such as the temperature, pH value, and stirring speed of different reactors such as the stomach, small intestine, and colon can be preset, and the human gut microbiota ecosystem simulator (SHIME) constructs an in vitro model according to the preset parameters to simulate the human gut physiological environment through the in vitro model.

[0054] In one embodiment, when using the Simulator of the Human Intestinal Microbial Ecosystem (SHIME), the SHIME can be calibrated and its performance verified based on standard microbial communities and chemicals to improve the stability and reliability of the operation of the SHIME.

[0055] S204. Conduct a control experiment based on an in vitro model, a target intestinal flora, and a target traditional Chinese medicine ingredient to determine the regulatory effect of the target traditional Chinese medicine ingredient on the target intestinal flora.

[0056] In one embodiment, a control group and an experimental group can be set up based on an in vitro model, a target intestinal flora, and a target traditional Chinese medicine ingredient. Then, an equal amount of culture medium is regularly added to the reactors of the control group and the experimental group to simulate the process of human diet and drug intake. During the above control experiment, monitoring data can be regularly collected, and comparative analysis can be performed based on the monitoring data of the control group and the experimental group to determine the regulatory effect of the target traditional Chinese medicine ingredient on the target intestinal flora.

[0057] Optionally, the results of cell experiments can also be obtained, and then the regulatory effect obtained based on the in vitro model in this application can be verified by comparison based on the results of the cell experiments to further clarify the regulatory mechanism and effectiveness of the target traditional Chinese medicine ingredient on the target intestinal flora.

[0058] In the embodiments of the present application, by determining a target intestinal flora from candidate intestinal floras, determining a target traditional Chinese medicine ingredient from candidate traditional Chinese medicine ingredients according to the target intestinal flora and candidate traditional Chinese medicine ingredients, then constructing an in vitro model for simulating the human intestinal physiological environment based on the Simulator of the Human Intestinal Microbial Ecosystem SHIME, and conducting a control experiment based on the in vitro model, the target intestinal flora, and the target traditional Chinese medicine ingredient, it is possible to determine the regulatory effect of the target traditional Chinese medicine ingredient on the target intestinal flora based on the data of the control experiment, and deeply reveal the mechanism of traditional Chinese medicine in regulating intestinal immunity. Moreover, in the embodiments of the present application, based on SHIME to simulate the human intestinal physiological environment, an in vitro model closer to the real physiological state is provided, thereby improving the accuracy of the regulatory effect obtained based on the in vitro model.

[0059] Refer to Figure 3 , Figure 3 is a schematic flowchart of a method for determining a target intestinal flora provided by an embodiment of the present application. This embodiment relates to a possible implementation manner of how to determine a target intestinal flora from candidate intestinal floras. On the basis of the above embodiment, the above S201 includes the following steps:

[0060] S301. Obtain the sequencing data of candidate intestinal floras and the index data of intestinal immune factors from multiple public databases.

[0061] In one embodiment, the initial 16S rRNA sequencing data of each candidate gut microbiota and the initial index data of gut immune factors related to the candidate gut microbiota can be obtained from multiple public databases. Then, the initial sequencing data and the initial index data are respectively subjected to data cleaning and format conversion to obtain sequencing data and index data, so as to improve the accuracy and consistency of the sequencing data and the index data.

[0062] Among them, the public databases can include, for example, the SRA (Sequence Read Archive) database, the ENA (European Nucleotide Archive) database, etc. The index data of gut immune factors can include, for example, inflammatory factor levels, the number of immune cells, etc.

[0063] S302, perform correlation analysis based on the sequencing data and the index data to construct a regulatory network.

[0064] Among them, the regulatory network is used to characterize the interaction relationship between the candidate gut microbiota and gut immune factors.

[0065] Optionally, diversity analysis and species composition analysis can be performed on the sequencing data of the candidate gut microbiota based on bioinformatics analysis tools, and then the sequencing data and the index data are correlated based on principal component analysis (PCA) and redundancy analysis (PDA) to screen out the gut microbiota characteristics significantly related to gut immunity, so as to obtain the correlation analysis result. A regulatory network is constructed based on the correlation analysis result to intuitively reflect the interaction relationship between the candidate gut microbiota and gut immune factors through the regulatory network.

[0066] Exemplarily, the above bioinformatics analysis tools can include, for example, QIIME2 (Quantitative Insights Into Microbial Ecology 2), relevant packages in the R language, etc. The gut microbiota characteristics significantly related to gut immunity can include, for example, specific patterns of changes in the abundance of microbiota, activation of microbiota functional pathways, etc.

[0067] S303, determine the target gut microbiota from the candidate gut microbiota according to the regulatory network.

[0068] In one embodiment, the regulatory network can be analyzed based on network topology analysis method to determine the target gut microbiota from the candidate gut microbiota.

[0069] Exemplarily, the importance degree of each candidate gut microbiota node can be quantified based on the regulatory network, and then an importance degree threshold is set, and the candidate gut microbiota corresponding to the importance degree greater than the importance degree threshold is determined as the target gut microbiota.

[0070] In the embodiments of the present application, sequencing data of candidate gut microbiota and index data of gut immune factors are obtained from multiple public databases, and correlation analysis is performed based on the sequencing data and the index data to construct a regulatory network for characterizing the interaction relationship between the candidate gut microbiota and the gut immune factors. According to the regulatory network, target gut microbiota are determined from the candidate gut microbiota, so that more comprehensive sequencing data and index data can be obtained from multiple public databases, providing a more solid data basis for subsequent research, overcoming the problem of limited data sources in traditional research, and being able to more intuitively and deeply reflect the interaction relationship between the candidate gut microbiota and the gut immune factors based on the regulatory network, improving the accuracy of the selected target gut microbiota.

[0071] Referring to Figure 4 , Figure 4 FIG. Figure 4 is a schematic flowchart of a method for determining a target traditional Chinese medicine ingredient provided by an embodiment of the present application. What this embodiment relates to is a possible implementation manner of how to determine target traditional Chinese medicine ingredients from candidate traditional Chinese medicine ingredients according to target gut microbiota and candidate traditional Chinese medicine ingredients. On the basis of the above embodiment, the above S202 includes the following steps:

[0072] S401, perform molecular docking simulation on the candidate traditional Chinese medicine ingredients and the target gut microbiota to obtain docking parameters.

[0073] In one embodiment, molecular docking simulation can be performed on the surface proteins or metabolic enzymes of the candidate traditional Chinese medicine ingredients and the target gut microbiota based on molecular docking software to obtain docking parameters.

[0074] Among them, the molecular docking software can include, for example, AutoDock Vina, etc. The docking parameters can include, for example, docking scores, binding affinities, etc.

[0075] S402, determine target traditional Chinese medicine ingredients from the candidate traditional Chinese medicine ingredients according to the docking parameters.

[0076] Exemplarily, a preset docking parameter range can be set, and the candidate traditional Chinese medicine ingredients corresponding to the docking parameters within the preset docking parameter range are determined as target traditional Chinese medicine ingredients.

[0077] Optionally, the target traditional Chinese medicine ingredients can be ranked according to their activities, and subsequent control experiments can be carried out in the order of the activity ranking.

[0078] In the embodiments of the present application, molecular docking simulation is performed on the candidate traditional Chinese medicine ingredients and the target gut microbiota to obtain docking parameters, and target traditional Chinese medicine ingredients are determined from the candidate traditional Chinese medicine ingredients according to the docking parameters, so as to systematically predict target traditional Chinese medicine ingredients that have potential regulatory effects on the target gut microbiota based on molecular docking technology, improving the pertinence of subsequent control experiments, reducing research costs, shortening the research cycle, and improving research efficiency.

[0079] Reference Figure 5 , Figure 5 is a schematic flowchart of a method for determining the regulatory effect of a target traditional Chinese medicine ingredient on a target intestinal flora provided by an embodiment of the present application. This implementation relates to a possible implementation manner of conducting a control experiment based on an in vitro model, a target intestinal flora, and a target traditional Chinese medicine ingredient to determine the regulatory effect of the target traditional Chinese medicine ingredient on the target intestinal flora. Based on the above embodiment, the above S204 includes the following steps:

[0080] S501, determine the in vitro model as the first control group.

[0081] S502, add the target intestinal flora to the in vitro model to obtain the second control group.

[0082] S503, add the target intestinal flora and the target traditional Chinese medicine ingredient to the in vitro model to obtain the experimental group.

[0083] Exemplarily, assuming that the target traditional Chinese medicine ingredient includes the chemical components of Paeonia lactiflora Pall., the in vitro model without adding any substances, that is, only containing the culture medium, can be determined as the first control group, then the in vitro model added with the target intestinal flora can be determined as the second control group, and the in vitro model added with the target intestinal flora and the chemical components of Paeonia lactiflora Pall. can be determined as the experimental group. And set multiple parallel reactors for each group.

[0084] S504, add an equal amount of culture medium to the first control group, the second control group, and the experimental group at every first preset time interval to conduct a control experiment and determine the regulatory effect of the target traditional Chinese medicine ingredient on the target intestinal flora.

[0085] Exemplarily, at every first preset time interval, an equal amount of culture medium can be added to the reactors of the first control group, the second control group, and the experimental group respectively to simulate the process of human diet and drug intake. During the control experiment, the monitoring data in each reactor can be collected at every second preset time, and then the monitoring data of the control group and the experimental group can be compared and analyzed to determine the regulatory effect of the target traditional Chinese medicine ingredient on the target intestinal flora.

[0086] In the embodiments of the present application, an in vitro model is determined as the first control group, the target intestinal flora is added to the in vitro model to obtain the second control group, and the target intestinal flora and the target traditional Chinese medicine components are added to the in vitro model to obtain the experimental group. Every first preset time interval, an equal amount of culture medium is added to the first control group, the second control group, and the experimental group to conduct a control experiment, so as to determine the regulatory effect of the target traditional Chinese medicine components on the target intestinal flora based on the data of the control experiment, and deeply reveal the mechanism of traditional Chinese medicine in regulating intestinal immunity. Moreover, in the embodiments of the present application, based on the SHIME to simulate the human intestinal physiological environment, an in vitro model closer to the real physiological state is provided, thereby improving the accuracy of the regulatory effect obtained based on the in vitro model.

[0087] Refer to Figure 6 , Figure 6 FIG. is a schematic flow chart of a control experiment provided by an embodiment of the present application. This embodiment relates to a possible implementation manner of how to add an equal amount of culture medium to the first control group, the second control group, and the experimental group every first preset time interval to conduct a control experiment. On the basis of the above embodiment, the above S503 includes the following steps:

[0088] S601, every first preset time interval, add an equal amount of culture medium to the first control group, the second control group, and the experimental group.

[0089] Exemplarily, the culture medium may include, for example, culture medium including culture solution, nutrients, drug components, etc., to simulate the process of human diet and drug intake by adding the culture medium.

[0090] S602, every second preset time interval, respectively collect the monitoring data of the first control group, the second control group, and the experimental group.

[0091] Among them, the monitoring data is used to determine the regulatory effect of the target traditional Chinese medicine components on the target intestinal flora.

[0092] Optionally, samples within the first control group, the second control group, and the experimental group can be collected every second preset time interval. Based on the high-throughput sequencing technology and the samples collected from each group, the dynamic change data of the intestinal flora composition and abundance within each group are respectively detected, and the content change data of intestinal metabolites (such as short-chain fatty acids, bile acids, etc.) within each group are detected using analytical instruments such as gas chromatography-mass spectrometry (GC-MS) and liquid chromatography-mass spectrometry (LC-MS). Then, the dynamic change data of the intestinal flora composition and abundance within each group, as well as the content change data of intestinal metabolites (such as short-chain fatty acids, bile acids, etc.) can be determined as the monitoring data.

[0093] In one embodiment, biostatistical methods such as analysis of variance and cluster analysis can be used to analyze the monitoring data, compare the differences between the experimental group and the first control group and the second control group, and evaluate the regulatory effect of the chemical components of Paeonia lactiflora on the target intestinal flora and the impact on intestinal immunity-related metabolites based on the differences.

[0094] In the embodiments of the present application, at every first preset time interval, an equal amount of culture medium is added to the first control group, the second control group, and the experimental group. At every second preset time interval, the monitoring data of the first control group, the second control group, and the experimental group are collected respectively, so that the regulatory effect of the target traditional Chinese medicine components on the target intestinal flora can be determined based on the monitoring data, and the mechanism of traditional Chinese medicine regulating intestinal immunity is deeply revealed. Moreover, in the embodiments of the present application, based on the SHIME to simulate the human intestinal physiological environment, an in vitro model closer to the real physiological state is provided, thereby improving the accuracy of the regulatory effect obtained based on the in vitro model.

[0095] Refer to Figure 7 , Figure 7 is a schematic flowchart of a method for determining the regulatory effect of intestinal flora based on public data mining and the SHIME platform provided by the embodiments of the present application. The method includes the following steps:

[0096] S701, Obtain the sequencing data of the candidate intestinal flora and the index data of intestinal immune factors from multiple public databases.

[0097] S702, Perform correlation analysis based on the sequencing data and the index data to construct a regulatory network.

[0098] S703, Determine the target intestinal flora from the candidate intestinal flora according to the regulatory network.

[0099] S704, Perform molecular docking simulation on the candidate traditional Chinese medicine components and the target intestinal flora to obtain docking parameters.

[0100] S705, Determine the target traditional Chinese medicine components from the candidate traditional Chinese medicine components according to the docking parameters.

[0101] S706, Construct an in vitro model for simulating the human intestinal physiological environment based on the human intestinal microbiome ecosystem simulator SHIME.

[0102] S707, At every first preset time interval, add an equal amount of culture medium to the first control group, the second control group, and the experimental group to conduct a control experiment.

[0103] S708, At every second preset time interval, collect the monitoring data of the first control group, the second control group, and the experimental group respectively.

[0104] S709. Determine the regulatory effect of the target traditional Chinese medicine component on the target intestinal flora according to the monitoring data.

[0105] It should be understood that although the steps in the flowcharts involved in the above-described embodiments are sequentially shown according to the indication of the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless there is a clear indication in this article, the execution of these steps has no strict order limit, and these steps can be executed in other orders. Moreover, at least a part of the steps in the flowcharts involved in the above-described embodiments may include multiple steps or multiple stages. These steps or stages are not necessarily executed at the same time, but can be executed at different times. The execution order of these steps or stages is not necessarily sequential, but can be executed alternately or alternately with at least a part of other steps or steps or stages in other steps.

[0106] Based on the same inventive concept, the embodiments of the present application also provide a device for determining the regulatory effect of the flora, which is used to implement the method for determining the regulatory effect of the flora involved above. The solution provided by this device to solve the problem is similar to the solution described in the above method. Therefore, the specific limitations in one or more embodiments of the device for determining the regulatory effect of the flora provided below can refer to the limitations on the method for determining the regulatory effect of the flora in the above text, and will not be repeated here.

[0107] In one embodiment, as Figure 8 shown, Figure 8 FIG. is a structural block diagram of a device for determining the regulatory effect of the flora provided by the embodiment of the present application. The device 800 includes:

[0108] The first determination module 801 is used to determine the target intestinal flora from the candidate intestinal flora.

[0109] The second determination module 802 is used to determine the target traditional Chinese medicine component from the candidate traditional Chinese medicine components according to the target intestinal flora and the candidate traditional Chinese medicine components.

[0110] The construction module 803 is used to construct an in vitro model for simulating the human intestinal physiological environment based on the human intestinal microbiota ecosystem simulator SHIME.

[0111] The control experiment module 804 is used to perform a control experiment based on the in vitro model, the target intestinal flora and the target traditional Chinese medicine component to determine the regulatory effect of the target traditional Chinese medicine component on the target intestinal flora.

[0112] In one of the embodiments, the first determination module 801 includes:

[0113] The acquisition unit is used to acquire the sequencing data of the candidate intestinal flora and the index data of the intestinal immune factors from multiple public databases.

[0114] A building unit is used to perform correlation analysis based on sequencing data and index data to construct a regulatory network; the regulatory network is used to characterize the interaction relationship between candidate gut microbiota and gut immune factors.

[0115] A first determination unit is used to determine target gut microbiota from candidate gut microbiota according to the regulatory network.

[0116] In one embodiment, the second determination module 802 includes:

[0117] A molecular docking unit is used to perform molecular docking simulation on candidate traditional Chinese medicine components and target gut microbiota to obtain docking parameters.

[0118] A second determination unit is used to determine target traditional Chinese medicine components from candidate traditional Chinese medicine components according to the docking parameters.

[0119] In one embodiment, the control experiment module 804 includes:

[0120] A third determination unit is used to determine the in vitro model as the first control group.

[0121] A fourth determination unit is used to add target gut microbiota to the in vitro model to obtain a second control group.

[0122] A fifth determination unit is used to add target gut microbiota and target traditional Chinese medicine components to the in vitro model to obtain an experimental group.

[0123] A control experiment unit is used to add an equal amount of culture medium to the first control group, the second control group, and the experimental group every first preset time interval to conduct a control experiment and determine the regulatory effect of the target traditional Chinese medicine component on the target gut microbiota.

[0124] In one embodiment, the control experiment unit is specifically used to add an equal amount of culture medium to the first control group, the second control group, and the experimental group every first preset time interval; collect monitoring data of the first control group, the second control group, and the experimental group every second preset time interval; the monitoring data is used to determine the regulatory effect of the target traditional Chinese medicine component on the target gut microbiota.

[0125] In one embodiment, the culture medium includes at least one of culture solution, nutrients, and drug components, and the culture medium is used to simulate the process of human diet and drug intake.

[0126] Each module in the above-mentioned device for determining the effect of flora regulation can be implemented in whole or in part by software, hardware, or a combination thereof. Each of the above modules can be embedded in or independent of the processor in a computer device in the form of hardware, or stored in the memory of the computer device in the form of software, so that the processor can call and execute the operations corresponding to each of the above modules.

[0127] In one embodiment, a computer device is provided, including a memory and a processor. A computer program is stored in the memory, and when the processor executes the computer program, the following steps are implemented:

[0128] Determine the target intestinal flora from the candidate intestinal flora;

[0129] According to the target intestinal flora and the candidate traditional Chinese medicine components, determine the target traditional Chinese medicine components from the candidate traditional Chinese medicine components;

[0130] Based on the in vitro human gut microbial ecosystem simulator SHIME, construct an in vitro model for simulating the human gut physiological environment;

[0131] Based on the in vitro model, the target intestinal flora, and the target traditional Chinese medicine components, conduct a control experiment to determine the regulatory effect of the target traditional Chinese medicine components on the target intestinal flora.

[0132] In one embodiment, when the processor executes the computer program, the following steps are further implemented:

[0133] Obtain the sequencing data of the candidate intestinal flora and the index data of intestinal immune factors from multiple public databases;

[0134] Conduct a correlation analysis based on the sequencing data and the index data to construct a regulatory network; the regulatory network is used to characterize the interaction relationship between the candidate intestinal flora and intestinal immune factors;

[0135] According to the regulatory network, determine the target intestinal flora from the candidate intestinal flora.

[0136] In one embodiment, when the processor executes the computer program, the following steps are further implemented:

[0137] Conduct a molecular docking simulation on the candidate traditional Chinese medicine components and the target intestinal flora to obtain docking parameters;

[0138] According to the docking parameters, determine the target traditional Chinese medicine components from the candidate traditional Chinese medicine components.

[0139] In one embodiment, when the processor executes the computer program, the following steps are further implemented:

[0140] Determine the in vitro model as the first control group;

[0141] Add the target intestinal flora to the in vitro model to obtain the second control group;

[0142] Add the target intestinal flora and the target traditional Chinese medicine components to the in vitro model to obtain an experimental group;

[0143] Add an equal amount of culture medium to the first control group, the second control group, and the experimental group at every first preset time interval to conduct a control experiment and determine the regulatory effect of the target traditional Chinese medicine components on the target intestinal flora.

[0144] In one embodiment, when the processor executes the computer program, the following steps are further implemented:

[0145] Add an equal amount of culture medium to the first control group, the second control group, and the experimental group at every first preset time interval;

[0146] Collect the monitoring data of the first control group, the second control group, and the experimental group at every second preset time interval; the monitoring data is used to determine the regulatory effect of the target traditional Chinese medicine components on the target intestinal flora.

[0147] In one embodiment, the culture medium includes at least one of culture solution, nutrients, and drug components, and the culture medium is used to simulate the human diet and drug intake process.

[0148] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the following steps are implemented:

[0149] Determine the target intestinal flora from the candidate intestinal flora;

[0150] Determine the target traditional Chinese medicine components from the candidate traditional Chinese medicine components according to the target intestinal flora and the candidate traditional Chinese medicine components;

[0151] Construct an in vitro model for simulating the human intestinal physiological environment based on the human intestinal microbiota ecosystem simulator SHIME;

[0152] Conduct a control experiment based on the in vitro model, the target intestinal flora, and the target traditional Chinese medicine components to determine the regulatory effect of the target traditional Chinese medicine components on the target intestinal flora.

[0153] In one embodiment, when the computer program is executed by the processor, the following steps are further implemented:

[0154] Obtain the sequencing data of the candidate intestinal flora and the index data of the intestinal immune factors from multiple public databases;

[0155] Conduct a correlation analysis based on the sequencing data and the index data to construct a regulatory network; the regulatory network is used to characterize the interaction relationship between the candidate intestinal flora and the intestinal immune factors;

[0156] Determine the target intestinal flora from the candidate intestinal flora according to the regulatory network.

[0157] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented:

[0158] Perform molecular docking simulation on the candidate traditional Chinese medicine components and the target intestinal flora to obtain docking parameters;

[0159] Determine the target traditional Chinese medicine components from the candidate traditional Chinese medicine components according to the docking parameters.

[0160] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented:

[0161] Determine the in vitro model as the first control group;

[0162] Add the target intestinal flora to the in vitro model to obtain the second control group;

[0163] Add the target intestinal flora and the target traditional Chinese medicine components to the in vitro model to obtain the experimental group;

[0164] Every first preset time interval, add an equal amount of culture medium to the first control group, the second control group, and the experimental group to conduct a control experiment and determine the regulatory effect of the target traditional Chinese medicine components on the target intestinal flora.

[0165] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented:

[0166] Every first preset time interval, add an equal amount of culture medium to the first control group, the second control group, and the experimental group;

[0167] Every second preset time interval, collect the monitoring data of the first control group, the second control group, and the experimental group respectively; the monitoring data is used to determine the regulatory effect of the target traditional Chinese medicine components on the target intestinal flora.

[0168] In one embodiment, the culture medium includes at least one of culture solution, nutrients, and drug components, and the culture medium is used to simulate the process of human diet and drug intake.

[0169] In one embodiment, a computer program product is provided, including a computer program, and when the computer program is executed by a processor, the following steps are implemented:

[0170] Determine the target intestinal flora from the candidate intestinal flora;

[0171] Determine the target traditional Chinese medicine components from the candidate traditional Chinese medicine components according to the target intestinal flora and the candidate traditional Chinese medicine components;

[0172] Based on the Simulator of the Human Intestinal Microbial Ecosystem (SHIME), construct an in vitro model for simulating the human intestinal physiological environment;

[0173] A control experiment is conducted based on an in vitro model, target gut microbiota, and target traditional Chinese medicine components to determine the regulatory effect of the target traditional Chinese medicine components on the target gut microbiota.

[0174] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented:

[0175] Obtain the sequencing data of candidate gut microbiota and the index data of gut immune factors from multiple public databases;

[0176] Perform correlation analysis based on the sequencing data and index data to construct a regulatory network; the regulatory network is used to characterize the interaction relationship between candidate gut microbiota and gut immune factors;

[0177] Determine the target gut microbiota from the candidate gut microbiota according to the regulatory network.

[0178] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented:

[0179] Perform molecular docking simulation on candidate traditional Chinese medicine components and the target gut microbiota to obtain docking parameters;

[0180] Determine the target traditional Chinese medicine components from the candidate traditional Chinese medicine components according to the docking parameters.

[0181] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented:

[0182] Determine the in vitro model as the first control group;

[0183] Add the target gut microbiota to the in vitro model to obtain the second control group;

[0184] Add the target gut microbiota and the target traditional Chinese medicine components to the in vitro model to obtain the experimental group;

[0185] Every first preset time interval, add an equal amount of culture medium to the first control group, the second control group, and the experimental group to conduct a control experiment and determine the regulatory effect of the target traditional Chinese medicine components on the target gut microbiota.

[0186] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented:

[0187] Every first preset time interval, add an equal amount of culture medium to the first control group, the second control group, and the experimental group;

[0188] Every second preset time interval, collect the monitoring data of the first control group, the second control group, and the experimental group respectively; the monitoring data is used to determine the regulatory effect of the target traditional Chinese medicine components on the target gut microbiota.

[0189] In one embodiment, the culture medium includes at least one of a culture solution, nutrients, and drug components, and the culture medium is used to simulate the process of human diet and drug intake.

[0190] Those of ordinary skill in the art can understand that all or part of the processes in the above-described embodiment methods can be completed by instructing relevant hardware through a computer program. The computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above various methods. Among them, any reference to a memory, database, or other medium used in the various embodiments provided in the present application can include at least one of non-volatile and volatile memories. Non-volatile memories can include read-only memory (ROM), magnetic tapes, floppy disks, flash memories, optical memories, high-density embedded non-volatile memories, resistive random access memories (ReRAMs), magnetoresistive random access memories (MRAMs), ferroelectric random access memories (FRAMs), phase change memories (PCMs), graphene memories, etc. Volatile memories can include random access memory (RAM) or external cache memories, etc. By way of illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM), etc. The databases involved in the various embodiments provided in the present application can include at least one of relational databases and non-relational databases. Non-relational databases can include distributed databases based on blockchain, etc., without limitation. The processors involved in the various embodiments provided in the present application can be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, data processing logics based on quantum computing, etc., without limitation.

[0191] The technical features of the above embodiments can be combined arbitrarily. For the sake of concise description, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, it should be considered as the scope recorded in this specification.

[0192] The above-described embodiments merely represent several implementation manners of the present application. The description thereof is relatively specific and detailed, but it should not be construed as a limitation to the patent scope of the present application. It should be noted that for those of ordinary skill in the art, without departing from the concept of the present application, several modifications and improvements can still be made, and these all fall within the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the appended claims.

Claims

1. A method for determining the effect of microbial flora regulation, characterized in that: The method comprises: Determine a target intestinal flora from among the intestinal flora to be selected; According to the target intestinal flora and the candidate Chinese medicine components, determining a target Chinese medicine component from the candidate Chinese medicine components; An in vitro model for simulating the physiological environment of the human intestine was built based on the human intestinal microbial ecosystem simulator SHIME; A control experiment is performed based on the in vitro model, the target intestinal flora and the target traditional Chinese medicine component to determine the regulatory effect of the target traditional Chinese medicine component on the target intestinal flora.

2. The method according to claim 1, characterized in that The step of determining a target intestinal flora from the intestinal flora to be selected comprises: Acquire the sequencing data of the intestinal flora to be selected and the index data of intestinal immune factors from multiple public databases; Performing association analysis based on the sequencing data and the indicator data to construct a regulatory network; the regulatory network is used to characterize the interaction relationship between the selected intestinal flora and the intestinal immune factor; According to the regulatory network, the target intestinal flora is determined from the candidate intestinal flora.

3. The method according to claim 1, characterized in that The step of determining a target Chinese medicinal ingredient from the Chinese medicinal ingredients to be selected according to the target intestinal flora and the Chinese medicinal ingredients to be selected comprises: Performing molecular docking simulation on the candidate Chinese medicine component and the target intestinal flora to obtain docking parameters; According to the docking parameters, the target Chinese medicinal ingredient is determined from the candidate Chinese medicinal ingredients.

4. The method according to any one of claims 1 to 3, characterized in that: The control experiment based on the in vitro model, the target intestinal flora and the target traditional Chinese medicine component is carried out to determine the regulatory effect of the target traditional Chinese medicine component on the target intestinal flora, including: determining the in vitro model as a first control group; Adding the target intestinal flora to the in vitro model to obtain a second control group; Adding the target intestinal flora and the target traditional Chinese medicine component to the in vitro model to obtain an experimental group; At intervals of a first preset time, an equal amount of culture medium is added to the first control group, the second control group, and the experimental group to conduct the control experiment and determine the regulatory effect of the target Chinese herbal ingredient on the target intestinal flora.

5. The method according to claim 4, characterized in that The step of adding an equal amount of culture medium to the first control group, the second control group, and the experimental group at intervals of a first preset time to perform the control experiment comprises: At intervals of the first preset time, adding an equal amount of culture medium to the first control group, the second control group, and the experimental group; At every second preset time interval, the monitoring data of the first control group, the second control group, and the experimental group are respectively collected; the monitoring data are used to determine the regulatory effect of the target traditional Chinese medicine ingredient on the target intestinal flora.

6. The method according to claim 5, characterized in that The culture medium comprises at least one of a culture solution, nutrients and drug components, and the culture medium is used to simulate the human diet and drug intake process.

7. A device for determining the effect of bacterial flora regulation, characterized in that: The device comprises: A first determination module is used to determine a target intestinal flora from among the intestinal flora to be selected; A second determination module is used to determine a target Chinese medicinal ingredient from the candidate Chinese medicinal ingredients according to the target intestinal flora and the candidate Chinese medicinal ingredients; Building modules for constructing in vitro models for simulating the physiological environment of the human intestine based on the human intestinal microbial ecosystem simulator SHIME; A control experiment module is used to conduct a control experiment based on the in vitro model, the target intestinal flora and the target traditional Chinese medicine ingredient to determine the regulatory effect of the target traditional Chinese medicine ingredient on the target intestinal flora.

8. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 6 are implemented.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

10. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

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