Microorganism tracing method, multi-strain variation map construction method and equipment

Abstract

The embodiment of the invention provides a tracing method of microorganisms, and a construction method and equipment of a multi-strain variation map. The microbe tracing method comprises the following steps: acquiring a microbe strain to be analyzed and the species of the microbe strain; performing variation analysis on the microbial strain to obtain variation information of the current strain; determining existing strain variation information corresponding to a plurality of existing microbial strains under the species; based on the microbial strain, the current strain variation information, the plurality of existing microbial strains and the existing strain variation information, a multi-strain variation map is established, the multi-strain variation map comprises a plurality of nodes and edges located between two nodes, the nodes are used for identifying the microbial strain, and the edges are used for identifying the current strain. The edge is used for identifying the correlation degree of variation information between two or more than two different microbial strains under the same species; and determining traceability information of the microbial strains based on the multi-strain variation map.

Description

Technical Field

[0001] The present invention relates to the field of microbial technology, and in particular to a microbial traceability method, a method for constructing a multi-strain variation map, and equipment. Background Art

[0002] Microbial traceability refers to checking the transmission routes of microorganisms based on their mutation sites, strain types, and epidemiological survey data. Microorganisms are a general term for a class of organisms, which can include bacteria, viruses, fungi, etc., covering many types of beneficial and harmful organisms, and are widely involved in many fields such as food, medicine, industry and agriculture, environmental protection, and sports, and are closely related to humans.

[0003] At present, microbial traceability is often achieved through manual investigation. Specifically, users evaluate and determine the traceability of microorganisms by querying papers, academic articles, news reports, etc., or users can directly estimate the traceability of microorganisms by asking microbial carriers. However, the accuracy and efficiency of the above traceability operations are low, which is not conducive to large-scale promotion operations. Summary of the invention

[0004] The embodiments of the present invention provide a method for tracing the origin of microorganisms, a method and device for constructing a multi-strain variation map, which realize efficient and automatic tracing of the origin of microorganisms and can be promoted on a large scale.

[0005] In a first aspect, an embodiment of the present invention provides a method for tracing the origin of a microorganism, comprising:

[0006] Obtaining a microbial strain to be analyzed and the species of the microbial strain;

[0007] Performing variation analysis on the microbial strain to obtain variation information of the current strain;

[0008] Determine the existing strain variation information corresponding to each of the multiple existing microbial strains under the genus;

[0009] Based on the microbial strain, the current strain variation information, the multiple existing microbial strains and the existing strain variation information, a multi-strain variation map is established, wherein the multi-strain variation map includes multiple nodes and edges between two nodes, wherein the nodes are used to identify the microbial strains, and the edges are used to identify the correlation between the variation information of two or more different microbial strains under the same genus;

[0010] Based on the multi-strain variation map, the traceability information of the microbial strain is determined.

[0011] In a second aspect, an embodiment of the present invention provides a microorganism tracing device, comprising:

[0012] A first acquisition module is used to acquire the microbial strain to be analyzed and the species of the microbial strain;

[0013] A first processing module is used to perform variation analysis on the microbial strain to obtain variation information of the current strain;

[0014] A first determination module is used to determine existing strain variation information corresponding to each of a plurality of existing microbial strains under the genus;

[0015] The first processing module is further used to establish a multi-strain variation map based on the microbial strain, the current strain variation information, the multiple existing microbial strains and the existing strain variation information, wherein the multi-strain variation map includes multiple nodes and edges between two nodes, wherein the nodes are used to identify the microbial strains, and the edges are used to identify the correlation between the variation information of two or more different microbial strains under the same genus;

[0016] The first processing module is further used to determine the traceability information of the microbial strain based on the multi-strain variation map.

[0017] In a third aspect, an embodiment of the present invention provides an electronic device, comprising: a memory and a processor; wherein the memory is used to store one or more computer instructions, wherein the one or more computer instructions, when executed by the processor, implement the microbial traceability method in the above-mentioned first aspect.

[0018] In a fourth aspect, an embodiment of the present invention provides a computer storage medium for storing a computer program, wherein the computer program enables a computer to implement the method for tracing the origin of microorganisms in the first aspect when executed.

[0019] In a fifth aspect, an embodiment of the present invention provides a computer program product, comprising: a computer program, which, when executed by a processor of an electronic device, enables the processor to execute the steps in the microorganism tracing method in the above-mentioned first aspect.

[0020] In a sixth aspect, an embodiment of the present invention provides a method for constructing a multi-strain variation map of a microorganism, comprising:

[0021] Obtaining microbial strains and species of the microbial strains;

[0022] Determining current strain variation information of the microbial strain;

[0023] Determine the existing strain variation information corresponding to each of the multiple existing microbial strains under the genus;

[0024] Based on the microbial strain, the current strain variation information, the multiple existing microbial strains and the existing strain variation information, a multi-strain variation map is established, wherein the multi-strain variation map includes multiple nodes and edges between two nodes, wherein the nodes are used to identify the microbial strains, and the edges are used to identify the correlation between variation information between two or more different microbial strains of the same genus.

[0025] In a seventh aspect, an embodiment of the present invention provides a device for constructing a multi-strain variation map of a microorganism, comprising:

[0026] A second acquisition module is used to acquire microbial strains and species of the microbial strains;

[0027] A second determination module is used to determine the current strain variation information of the microbial strain;

[0028] The second determination module is further used to determine existing strain variation information corresponding to each of the multiple existing microbial strains under the genus;

[0029] The second processing module is used to establish a multi-strain variation map based on the microbial strain, the current strain variation information, the multiple existing microbial strains and the existing strain variation information, wherein the multi-strain variation map includes multiple nodes and edges between two nodes, wherein the nodes are used to identify the microbial strains, and the edges are used to identify the correlation between the variation information of two or more different microbial strains under the same genus.

[0030] In an eighth aspect, an embodiment of the present invention provides an electronic device, comprising: a memory, a processor; wherein the memory is used to store one or more computer instructions, wherein the one or more computer instructions, when executed by the processor, implement the method for constructing a multi-strain variation map of microorganisms in the sixth aspect above.

[0031] In a ninth aspect, an embodiment of the present invention provides a computer storage medium for storing a computer program, wherein the computer program, when executed by a computer, implements the method for constructing a multi-strain variation map of microorganisms in the sixth aspect.

[0032] In the tenth aspect, an embodiment of the present invention provides a computer program product, comprising: a computer program, which, when executed by a processor of an electronic device, enables the processor to execute the steps in the method for constructing a multi-strain variation map of microorganisms in the sixth aspect above.

[0033] The microbial traceability method, multi-strain variation map construction method and device provided in this embodiment obtain the microbial strain to be analyzed and the species of the microbial strain to obtain the current strain variation information; determine the existing strain variation information corresponding to each of the multiple existing microbial strains under the species; then establish a multi-strain variation map based on the microbial strain, the current strain variation information, the multiple existing microbial strains and the existing strain variation information, and then determine the traceability information of the microbial strain based on the multi-strain variation map, effectively realizing that the traceability operation can be automatically performed on the microorganism based on the multi-strain variation map, which not only ensures the efficiency and accuracy of obtaining the traceability information, but also enables large-scale promotion operations, which is conducive to improving the practicality of the method. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0035] Figure 1 A schematic diagram of a scenario of a method for tracing the origin of a microorganism provided by an embodiment of the present invention;

[0036] Figure 2 A schematic diagram of a process for tracing the origin of a microorganism provided in an embodiment of the present invention;

[0037] Figure 3 A schematic diagram of a multi-strain variation map provided in an embodiment of the present invention;

[0038] Figure 4 A schematic diagram of a process for determining the traceability information of the microbial strain based on the multi-strain variation map provided in an embodiment of the present invention;

[0039] Figure 5 A schematic diagram of a process for calculating a first similarity between the microbial strain and each existing microbial strain provided in an embodiment of the present invention;

[0040] Figure 6 A schematic diagram of the principle of a method for constructing a multi-strain variation map of a microorganism provided in an application example of the present invention;

[0041] Figure 7 A schematic diagram of a process for constructing a multi-strain variation map of a microorganism provided in an embodiment of the present invention;

[0042] Figure 8A schematic diagram of the structure of a microorganism tracing device provided in an embodiment of the present invention;

[0043] Fig. 9 For Figure 8 A schematic diagram of the structure of an electronic device corresponding to the microorganism tracing device provided in the illustrated embodiment;

[0044] Fig.10 A schematic diagram of the structure of a device for constructing a multi-strain variation map of microorganisms provided in an embodiment of the present invention;

[0045] Fig.11 For Fig.10 A schematic diagram of the structure of an electronic device corresponding to the device for constructing a multi-strain variation map of microorganisms provided in the illustrated embodiment. DETAILED DESCRIPTION

[0046] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are 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.

[0047] The terms used in the embodiments of the present invention are only for the purpose of describing specific embodiments, and are not intended to limit the present invention. The singular forms "a", "said" and "the" used in the embodiments of the present invention and the appended claims are also intended to include plural forms, unless the context clearly indicates other meanings, and "multiple" generally includes at least two, but does not exclude the inclusion of at least one.

[0048] It should be understood that the term "and / or" used in this article is only a description of the association relationship of associated objects, indicating that there can be three relationships. For example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone. In addition, the character " / " in this article generally indicates that the associated objects before and after are in an "or" relationship.

[0049] As used herein, the words "if" and "if" may be interpreted as "at the time of" or "when" or "in response to determining" or "in response to detecting", depending on the context. Similarly, the phrases "if it is determined" or "if (stated condition or event) is detected" may be interpreted as "when it is determined" or "in response to determining" or "when detecting (stated condition or event)" or "in response to detecting (stated condition or event)", depending on the context.

[0050] It should also be noted that the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a product or system including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such a product or system. In the absence of more restrictions, the elements defined by the sentence "comprises a ..." do not exclude the existence of other identical elements in the product or system including the elements.

[0051] In addition, the step sequence in the following method embodiments is only an example and not a strict limitation.

[0052] Definition of terms:

[0053] Mutation site: The location in the microbial genome where a mutation occurs compared to the reference genome, including point mutations, insertions, deletions, etc.

[0054] Strain: For the same type of microorganism, subtypes vary due to genome mutations, and each subtype is a new strain.

[0055] In order to facilitate understanding of the specific implementation process and implementation effect of the microbial traceability method, the construction method of the multi-strain variation map and the device in this embodiment, the relevant technologies are briefly described below:

[0056] In the field of microorganisms, the following eight categories of microorganisms are usually included: bacteria, viruses, fungi, actinomycetes, rickettsia, mycoplasma, chlamydia, spirochetes, etc. Since microorganisms cover many types of beneficial and harmful species, they are widely involved in many fields such as food, medicine, industry and agriculture, environmental protection, sports, etc., and are closely related to humans. Therefore, microbial traceability operations have become an important research direction in the field of microorganisms. Microbial traceability refers to checking the transmission routes of microorganisms based on the mutation sites and strain types of microorganisms and combined with epidemiological survey data.

[0057] At present, microbial traceability is often achieved through manual investigation. For example, users can evaluate and determine the traceability of microorganisms by querying papers, academic articles, news reports, etc., or users can directly estimate the traceability of microorganisms by asking microbial carriers.

[0058] However, the accuracy and efficiency of the above-mentioned traceability operations are low, which is not conducive to large-scale promotion operations.

[0059] In order to solve the above technical problems, this embodiment proposes a microbial traceability method, a method and equipment for constructing a multi-strain variation map, and reference is made to the attached Figure 1As shown, the execution subject of the above-mentioned microbial traceability method can be a traceability device of the microorganism, and the traceability device of the microorganism can be implemented as a local server or a server in the cloud. At this time, the traceability method of the microorganism can be executed in the cloud, and several computing nodes (cloud servers) can be deployed in the cloud, and each computing node has processing resources such as computing and storage. In the cloud, multiple computing nodes can be organized to provide a certain service. Of course, a computing node can also provide one or more services. The way to provide the service in the cloud can be to provide a service interface to the outside, and the user calls the service interface to use the corresponding service. The service interface includes forms such as software development kit (Software Development Kit, referred to as SDK), application programming interface (Application Programming Interface, referred to as API).

[0060] Specifically, the microorganism traceability device can be communicatively connected with a client or a requester. For the solution provided in the embodiment of the present invention, the cloud can provide a service interface of the microorganism traceability service. The user calls the microorganism traceability service interface through the client / requester to trigger a request to call the microorganism traceability service interface to the cloud. The cloud determines the computing node that responds to the request and uses the processing resources in the computing node to perform specific processing operations for microorganism traceability.

[0061] The client / requester can be any computing device with a certain data transmission capability. In specific implementation, the client / requester can be a mobile phone, a personal computer PC, a tablet computer, a setting application, etc. In addition, the basic structure of the client / requester may include: at least one processor. The number of processors depends on the configuration and type of the client / requester. The client / requester may also include a memory, which may be volatile, such as RAM, or non-volatile, such as read-only memory (ROM), flash memory, etc., or may include both types. The memory usually stores an operating system (OS), one or more applications, and may also store program data, etc. In addition to the processing unit and the memory, the client / requester also includes some basic configurations, such as a network card chip, an IO bus, a display component, and some peripheral devices, etc. Optionally, some peripheral devices may include, for example, a keyboard, a mouse, an input pen, a printer, etc. Other peripheral devices are well known in the art and will not be described in detail here. In some other examples, the client / requester may be implemented as a sample collection end for microorganisms. In specific implementation, the sample collection end may be any computing device with certain sample transmission and sample collection capabilities.

[0062] A microbial traceability device refers to a device that can provide microbial traceability services in a network virtual environment, and usually refers to a device that uses the network to perform information planning and microbial traceability operations. In terms of physical implementation, a microbial traceability device can be any device that can provide computing services, respond to microbial traceability requests, and perform processing, such as a cluster server, conventional server, cloud server, cloud host, virtual center, etc. The composition of a microbial traceability device mainly includes a processor, hard disk, memory, system bus, etc., which is similar to a general computer architecture.

[0063] In the above embodiment, the client can establish a network connection with the microorganism traceability device, and the network connection can be a wireless or wired network connection. If the client and the microorganism traceability device are connected by communication, the network standard of the mobile network can be any one of 2G (GSM), 2.5G (GPRS), 3G (WCDMA, TD-SCDMA, CDMA2000, UTMS), 4G (LTE), 4G+ (LTE+), WiMax, 5G, 6G, etc.

[0064] In an embodiment of the present application, the client can obtain the microbial strain to be analyzed, which may include a partial genomic base fragment or a full gene base sequence in the genomic data, wherein the microbial strain may be data obtained in advance by collecting set microorganisms and stored in a preset area. At this time, the client can obtain the microbial strain to be analyzed by accessing the preset area. In order to realize the traceability operation of the microorganism, the obtained microbial strain can be sent to the traceability device of the microorganism.

[0065] A microbial traceability device is used to obtain the microbial strain to be analyzed, and then the species of the microbial strain can be determined. Since different species can correspond to different multi-strain variation maps, in order to accurately trace the microbial strain, the multi-strain variation map corresponding to the species can be determined. Specifically, the microbial strain can be first subjected to variation analysis to obtain the current strain variation information; the existing strain variation information corresponding to each of the multiple existing microbial strains under the species is determined; and then a multi-strain variation map can be established based on the microbial strain, the current strain variation information, the multiple existing microbial strains, and the existing strain variation information. The multi-strain variation map may include multiple nodes and edges between two nodes, wherein the nodes are used to identify the microbial strains, and the edges are used to identify the correlation between the variation information of two or more microbial strains of the same genus. After obtaining the multi-strain variation map, the traceability information of the microbial strains can be determined based on the multi-strain variation map, which effectively realizes that the traceability operation can be automatically performed on the microorganisms based on the multi-strain variation map, which not only ensures the efficiency and accuracy of the traceability operation of the microorganisms, but also has a simple and reliable implementation method, and can be used for large-scale application operations, further improving the practicability of the method.

[0066] Some embodiments of the present invention are described in detail below in conjunction with the accompanying drawings. In the case where there is no conflict between the embodiments, the following embodiments and the features in the embodiments can be combined with each other. In addition, the step sequence in the following method embodiments is only an example and not a strict limitation.

[0067] Figure 2 A schematic diagram of a microbial traceability method provided in an embodiment of the present invention; see attached Figure 2 As shown, this embodiment provides a method for tracing the source of microorganisms. The executor of the method can be a tracing device for microorganisms. It can be understood that the tracing device for microorganisms can be implemented as software, or a combination of software and hardware. Specifically, when the tracing device for microorganisms is implemented as hardware, it can be various electronic devices that can perform tracing operations of microorganisms, including but not limited to tablet computers, personal computers PCs, servers, etc. When the tracing device for microorganisms is implemented as software, it can be installed in the electronic devices listed above. Based on the above-mentioned tracing device for microorganisms, the tracing method for microorganisms in this embodiment can include the following steps:

[0068] Step S201: Obtain the microbial strain to be analyzed and the species of the microbial strain.

[0069] Step S202: performing variation analysis on the microbial strain to obtain variation information of the current strain.

[0070] Step S203: determining existing strain variation information corresponding to each of the multiple existing microbial strains under the genus.

[0071] Step S204: Based on the microbial strain, the current strain variation information, the multiple existing microbial strains and the existing strain variation information, a multi-strain variation map is established, wherein the multi-strain variation map includes multiple nodes and edges between two nodes, wherein the nodes are used to identify the microbial strains, and the edges are used to identify the correlation between the variation information of two or more different microbial strains under the same genus.

[0072] Step S205: Determine the traceability information of the microbial strains based on the multi-strain variation map.

[0073] The specific implementation principles and effects of each of the above steps are described in detail below:

[0074] Step S201: Obtain the microbial strain to be analyzed and the species of the microbial strain.

[0075] Among them, microbial traceability can improve the safety and effectiveness of food safety, environmental testing, synthetic biology and other fields. It can not only determine the evolutionary relationship, kinship and transmission path of microorganisms, but also be applied to synthetic biology research, bioengineering, biopharmaceuticals and other fields. For example, in the field of biopharmaceuticals, the source and evolution of microorganisms used in the drug production process can be traced through synthetic microbial traceability technology, thereby ensuring the safety and effectiveness of the drug. Therefore, when the user has a need for microbial traceability, the microbial traceability device can obtain the microbial strain to be analyzed and the species of the microbial strain. The number of microbial strains obtained can be one or more. When the number of microbial strains obtained is multiple, the traceability operation can be performed on multiple microbial strains simultaneously, and the traceability information of multiple microbial strains can be obtained simultaneously; or, the traceability operation of the microorganism can be performed on multiple microbial strains in sequence, and the traceability information of multiple microbial strains can be obtained in sequence.

[0076] In some instances, the microbial strains and the species of the microbial strains can be obtained through a client or a preset device. In this case, obtaining the microbial strains to be analyzed and the species of the microbial strains may include: obtaining a client or a preset device that is communicatively connected to a microbial traceability device, wherein the microbial strains to be analyzed and the species of the microbial strains are stored in the client or the preset device; actively or passively obtaining the microbial strains to be analyzed and the species of the microbial strains through the client.

[0077] In other examples, the microbial strains and the species of the microbial strains can be obtained in different ways. For example, the microbial strains can be obtained through a client, and the species of the microbial strains can be obtained by analyzing and processing the microbial strains. In this case, obtaining the microbial strains to be analyzed and the species of the microbial strains can include: obtaining a client that is communicatively connected to a microbial traceability device, wherein the microbial strains to be analyzed are stored in the client; actively or passively obtaining the microbial strains to be analyzed through the client; and then analyzing and processing the microbial strains to obtain the species of the microbial strains.

[0078] In some other examples, the microbial strains and the species of the microbial strains can be obtained not only through the client, but also by analyzing and processing the same sample to be analyzed. In this case, obtaining the microbial strains to be analyzed and the species of the microbial strains can include: obtaining the sample to be analyzed; performing whole genome sequencing on the sample to be analyzed to obtain sequencing fragments and the species of the microbial strain; performing sequence splicing on the sequencing fragments to obtain the microbial strain, which includes the whole genome base sequence corresponding to the sample to be analyzed.

[0079] Specifically, in order to implement traceability operations on microorganisms, the traceability device of the microorganism can obtain the sample to be analyzed. In some instances, the sample to be analyzed can be stored in a preset area or preset device. At this time, the sample to be analyzed can be obtained by accessing the preset area or preset device; in other instances, the sample to be analyzed can be obtained through a preset sampling device. At this time, obtaining the sample to be analyzed may include: determining the preset sampling device located on the traceability device of the microorganism; performing a sample sampling operation through the preset sampling device to obtain the sample to be analyzed, which effectively ensures the accuracy and reliability of the acquisition of the sample to be analyzed.

[0080] After obtaining the sample to be analyzed, the whole genome sequencing operation can be performed on the sample to be analyzed, so as to obtain the sequencing fragments and the species of the microorganism, wherein the species is the basic unit of microbial classification, which is used to identify the different genetic characteristics of the microorganism, for example, the species of the microorganism may include at least one of the following: influenza virus, adenovirus, coronavirus, rotavirus, etc. Since the sequencing fragments obtained through the whole genome sequencing operation are often partial genome base sequences, in order to accurately trace the source of the microorganism, the sequencing fragments can be spliced ​​to obtain the microbial strain including the whole genome base sequence corresponding to the sample to be analyzed, which effectively ensures the accuracy and reliability of the acquisition of the microbial strain and the species of the microorganism.

[0081] Step S202: performing variation analysis on the microbial strain to obtain variation information of the current strain.

[0082] In order to accurately determine the traceability information of the microbial strain, after obtaining the microbial strain, the microbial strain can be first subjected to variation analysis. Specifically, the microbial strain can be subjected to variation analysis through the standard strain to determine the current strain variation information of the microbial strain. At this time, determining the current strain variation information of the microbial strain can include: obtaining the standard strain corresponding to the species; performing variation analysis on the microbial strain using the standard strain to obtain the current strain variation information.

[0083] Specifically, for any one species of microorganism, a standard strain corresponds to it, and different species of microorganisms correspond to different standard strains, wherein, for any one species, the corresponding standard strain may be the first strain that can be collected or detected in the current species. In order to understand and count the variation of different subtypes of microbial strains in the current species, it is necessary to calculate and compare the obtained microbial strains with the standard strains of the species to determine the variation of the current microbial strains. Therefore, for the microbial strains to be analyzed, in order to accurately understand the variation, the standard strains used for variation analysis of the microbial strains can be first determined based on the species of the microbial strains. In some examples, the standard strains of each species can be stored in at least one microbial database. After obtaining the species of the microorganism, it can be searched in each microbial database based on the species, so as to obtain the standard strains corresponding to the species.

[0084] After obtaining the standard strain, the standard strain can be used to perform variation analysis on the microbial strain, so as to obtain the variation information of the current strain, which may include at least one of the following: variation type, variation position, variation number, variation ratio, etc., wherein the variation type may include: point mutation, insertion, deletion, etc.

[0085] It can be understood that the results of the variation analysis may include two categories, namely, the results of the absence of variation analysis and the results of the presence of variation analysis. At this time, using the standard strain to perform variation analysis on the microbial strain, obtaining the current strain variation information may include: when the standard strain and the microbial strain are the same, determining the current strain variation information as the first type of information used to identify that there is no variation in the microbial strain, that is, the current microbial strain does not vary relative to the standard strain; when the standard strain and the microbial strain are different, determining the current strain variation information as the second type of information used to identify that there is variation in the microbial strain, that is, the current microbial strain has variation relative to the standard strain.

[0086] Step S203: determining existing strain variation information corresponding to each of the multiple existing microbial strains under the genus.

[0087] Among them, the existing microbial strains are strains that have been processed by variation analysis at a historical moment, and their related variation analysis situations can be stored in a preset microbial database. When it is necessary to establish a multi-strain variation map, the species corresponding to the existing microbial strains can be determined first, and then the preset microbial database can be accessed through the species and the identification information of the existing microbial strains, so as to quickly determine the existing strain variation information corresponding to each of the multiple existing microbial strains under the current species.

[0088] Step S204: Based on the microbial strain, the current strain variation information, the multiple existing microbial strains and the existing strain variation information, a multi-strain variation map is established, wherein the multi-strain variation map includes multiple nodes and edges between two nodes, wherein the nodes are used to identify the microbial strains, and the edges are used to identify the correlation between the variation information of two or more different microbial strains under the same genus.

[0089] After obtaining the current strain variation information of the microbial strain and the existing strain variation information corresponding to each of the multiple existing microbial strains, the microbial strain, the current strain variation information, the multiple existing microbial strains and the existing strain variation information can be analyzed and processed to establish a multi-strain variation map.

[0090] In some instances, a multi-strain variation map can be established using a preset map construction algorithm or a pre-trained machine learning model. In this case, establishing a multi-strain variation map based on the microbial strain, the current strain variation information, multiple existing microbial strains, and the existing strain variation information may include: determining a map construction algorithm or a pre-trained machine learning model; using the map construction algorithm or the machine learning model to process the microbial strain, the current strain variation information, multiple existing microbial strains, and the existing strain variation information to obtain a multi-strain variation map.

[0091] In other instances, a multi-strain variation map can be established not only by a preset map construction algorithm or a pre-trained machine learning model, but also by calculating the similarity between a microbial strain and an existing microbial strain and between any two existing microorganisms. In this case, based on the microbial strain, the current strain variation information, multiple existing microbial strains and the existing strain variation information, establishing a multi-strain variation map may include: calculating a first similarity between the microbial strain and each existing microbial strain, and a second similarity between any two existing microbial strains; and establishing a multi-strain variation map based on the first similarity, the second similarity, the current strain variation information and the existing strain variation information.

[0092] Since different species of microorganisms may correspond to different multi-strain variation maps, the multi-strain variation map includes multiple nodes and edges between two nodes, such as Figure 3 As shown, the multi-strain variation map includes: node a, node a1, node a2, node a3, node a4, node a5, node a6, node a7, node a8, node a9, node a10, node a11, etc., the above-mentioned different nodes a represent different microbial strains, for example: node a1 represents influenza A (H1N1) virus, node a2 represents influenza A (H2N2) virus, node a3 represents influenza A (H3N2) virus... and so on, that is, the nodes in the multi-strain variation map are used to identify microbial strains, different nodes are used to represent microbial strains of different subtypes, and the edges between the nodes are used to identify the correlation between variation information of two or more different microbial strains of the same genus, wherein the variation information includes at least one of the following: variation type, variation site, variation number, etc. In some examples, the length of the edge is negatively correlated with the similarity between the variation information of two or more different microbial strains, that is, when the similarity between the variation information is higher, the length of the edge is smaller; when the similarity between the variation information is lower, the length of the edge is larger.

[0093] Specifically, after obtaining the microbial strain and each existing microbial strain, the base sequence of the microbial strain and the base sequence of each existing microbial strain can be calculated to obtain the first similarity between the microbial strain and each existing microbial strain, wherein the number of first similarities is multiple, for example, the multiple first similarities can include: the first similarity between the microbial strain and the existing microbial strain a1, the first similarity between the microbial strain and the existing microbial strain a2, the first similarity between the microbial strain and the existing microbial strain a3, etc. Similarly, the base sequence between any two existing microbial strains can be simultaneously calculated to obtain the second similarity between any two existing microbial strains, wherein the number of second similarities is multiple, for example: the multiple second similarities can include: the second similarity between the existing microbial strain a1 and the existing microbial strain a2, the second similarity between the existing microbial strain a1 and the existing microbial strain a3, the second similarity between the existing microbial strain a2 and the existing microbial strain a3, etc.

[0094] Since the relative deployment position and distance between the microbial strain and each existing microbial strain are related to the first similarity and the second similarity, for example: the higher the first similarity between the microbial strain and the existing microbial strain, the closer the relative deployment position and relative distance between the microbial strain and the existing microbial strain; the higher the first similarity between the microbial strain and the existing microbial strain, the farther the relative deployment position and relative distance between the microbial strain and the existing microbial strain. Therefore, after obtaining the first similarity and the second similarity, the first similarity, the second similarity, the current strain variation information and the existing strain variation information can be analyzed and processed to establish a multi-strain variation map. Specifically, the first similarity, the second similarity, the current strain variation information and the existing strain variation information can be analyzed and processed according to the preset map establishment rules to determine the deployment position and correlation between the current microbial strain and each existing microbial strain, and then the multi-strain variation map can be stably established, which effectively ensures the accuracy and reliability of determining the multi-strain variation map.

[0095] Continue to refer to the attached Figure 3 As shown, for nodes a18 and a19, there are three types of edges between them and node a corresponding to the standard strain. Specifically, there is edge 2 between node a18 and node a19, edge 3 between node a and a18 and a19, and edge 1 between node 19 and node a, wherein edge 2 is used to identify the similarity between the microbial strains represented by node a18 and node a19 or the similarity between the microbial strain variation information. Specifically, the longer the length of edge 2, the less similar the microbial strains between node a18 and node a19 are, or the less similar the variation information of the microbial strains between node a18 and node a19 are, and vice versa.

[0096] Similarly, edge 3 is used to identify the similarity between the microbial strains represented by node a and nodes 18 and 19, or the similarity of the variation information of the microbial strains. The longer edge 3 is, the less similar the microbial strains represented by node a and nodes 18 and 19 are, or the variation information of the microbial strains between nodes a18 and 19 is less similar to the microbial strain represented by node a. Otherwise, they are more similar. Edge 1 is used to identify the similarity between the microorganism represented by node a19 and the microorganism represented by node a, or the similarity of the variation information of the microorganisms. The longer the length of edge 1 is, the less similar the microbial strains between node a and node a19 are, or the variation information of the microbial strains between node a and node a19 is less similar. Otherwise, they are more similar.

[0097] It should be noted that the similarity between edge 2 and edge 1 can be obtained by matching and calculating the base sequences corresponding to each node, and the similarity corresponding to edge 3 can be obtained by weighted summing the similarities between node a and the associated nodes (a18 and a19). Of course, those skilled in the art can also use other methods to obtain the above similarity, as long as they can stably characterize the association relationship between the nodes, which will not be repeated here.

[0098] Step S205: Determine the traceability information of the microbial strains based on the multi-strain variation map.

[0099] Since the multi-strain variation map information includes the variation information of multiple subtypes of microbial strains of the same species and the correlation between the variation information of different microbial strains, after obtaining the multi-strain variation map, the microbial strains can be traced based on the multi-strain variation map to determine the traceability information of the microbial strains, wherein the traceability information may include at least one of the following: source, transmission route, etc.

[0100] Specifically, this embodiment does not limit the method for implementing the traceability of microbial strains. In some instances, the traceability operation can be implemented through a pre-trained machine learning model or a neural network model. At this time, based on the multi-strain variation map, determining the traceability information of the microbial strain may include: obtaining a pre-trained machine learning model or a neural network model; inputting the multi-strain variation map and the microbial strain into the machine learning model or the neural network model, and obtaining the traceability information of the microbial strain output by the machine learning model or the neural network model, thereby effectively ensuring the accuracy and reliability of the traceability information of the microbial strain.

[0101] In some other examples, after determining the traceability information of the microbial strain, in order to improve the practicality of the method, the method in this embodiment may also include: generating health and prevention and control information corresponding to the microbial strain based on the traceability information; and / or, generating medication guidance information corresponding to the microbial strain based on the traceability information; and / or, performing drug resistance analysis on the microbial strain based on the traceability information to obtain drug resistance analysis results; and / or, conducting drug research and development on the microbial strain based on the traceability information to obtain drug research and development information.

[0102] Example 1: Since the traceability information includes the source location and transmission route information corresponding to the microbial strain, in order to prevent and control the microbial strain, after obtaining the traceability information, the traceability information can be analyzed and processed to generate health and medical prevention and control information corresponding to the microbial strain, wherein the health and medical prevention and control information may include at least one of the following: prevention and control measures for microbial strains, such as wearing masks, washing hands frequently, frequent ventilation, less gathering, etc., and then the spread of microbial strains can be prevented and controlled based on the health and medical prevention and control information, thereby reducing the risk of transmission of microbial strains and the harm caused.

[0103] Example 2: In addition, since the source and transmission path included in the traceability information can reflect the applicable environmental characteristics and transmission conditions of the microbial strain, in order to achieve effective and active treatment operations on the patients or hosts carried by the microbial strain, after obtaining the traceability information, the traceability information can be analyzed and processed to generate medication guidance information corresponding to the microbial strain, wherein the medication guidance information may include at least one of the following: oral administration method guidance, precautions, medication guidance for special populations, lifestyle adjustments, etc. The above-mentioned oral administration method guidance may include at least one of the following: taking before meals, taking after meals, etc., precautions may include at least one of the following: appropriate time for taking medicine, appropriate course of treatment, existing adverse reactions, medication guidance for special populations may include at least one of the following: whether it is applicable to elderly patients, pregnant women and lactating women; lifestyle adjustments may include at least one of the following: quitting smoking, limiting alcohol, eating a reasonable diet, regular exercise, etc. After obtaining the medication guidance information, the user can be guided to take the medicine based on the medication guidance information, thereby ensuring the treatment effect for the microbial strain and reducing the harm caused by the microbial strain to the user.

[0104] Example 3: In addition, the source place and transmission route included in the traceability information can reflect the applicable environmental characteristics and transmission conditions of the microbial strains. In order to effectively analyze the response degree of the microbial strains to various drugs, after obtaining the traceability information, the microbial strains can be subjected to drug resistance analysis based on the traceability information, so as to obtain the drug resistance analysis results, wherein the drug resistance analysis results may include: the drug resistance degree of the microbial strains to Class A drugs is 5.8%, the drug resistance degree of the microbial strains to Class B drugs is 11.3%, and the drug resistance degree of the microbial strains to Class C drugs is 70.21%. It can be seen from the above drug resistance analysis results that, for microbial strains, the therapeutic effects of Class A drugs and Class B drugs are higher than those of Class C drugs, and the therapeutic effect of Class A drugs is higher than that of Class B drugs; and then the treatment plan for the microbial strains can be determined based on the drug resistance analysis results to minimize the hazards and impacts brought by the microbial strains.

[0105] Example 4: Finally, the source location and transmission route included in the traceability information can reflect the applicable environmental characteristics and transmission conditions of the microbial strain. In order to effectively determine the corresponding symptomatic drugs for the microbial strain, after obtaining the traceability information, drug research and development can be carried out on the microbial strain based on the traceability information, so as to obtain drug research and development information, wherein the drug research and development information may include at least one of the following: drug name (including generic name, trade name, English name, Chinese pinyin, etc.), indication (listing the main applicable scope or disease type of the drug), dosage form (the form of the drug, such as tablets, capsules, injections, etc.), specification (drug dosage or content, such as the weight of each tablet, the capacity of each bottle of injection, etc.), research and development unit (the name of the institution conducting drug research and development), registration classification (drugs are classified according to the regulations of the national drug regulatory authorities), application matters (indicating whether the drug is in the stage of new drug application, supplementary application, generic drug application, etc.), applicant (the individual or unit that submits the drug development application), application date (the date of submission of the drug development application) and other information (such as the drug's research and development history, technology transfer status, clinical trial status, etc.), etc., and then the drug can be promoted based on the drug research and development information, which effectively improves the practicality of the method.

[0106] The microbial traceability method provided in this embodiment obtains the microbial strain to be analyzed and the species of the microbial strain, and determines the existing strain variation information corresponding to each of the multiple existing microbial strains under the species; then a multi-strain variation map is established based on the microbial strain, the current strain variation information, the multiple existing microbial strains and the existing strain variation information, and then the traceability information of the microbial strain is determined based on the multi-strain variation map, which effectively realizes that the traceability operation can be automatically performed on the microorganism based on the multi-strain variation map, which not only ensures the efficiency and accuracy of obtaining the traceability information, but also the implementation principle of the method is simple, reliable, easy to deploy and implement, and can be widely promoted and operated, further improving the practicality of the method.

[0107] Figure 4 A schematic diagram of a process for determining the traceability information of a microbial strain based on a multi-strain variation map provided in an embodiment of the present invention; based on the above embodiment, refer to the attached Figure 4 As shown, when performing a traceability operation on a microbial strain, the traceability operation of the microorganism can be realized not only based on a pre-trained machine learning model or a neural network model, but also based on an existing strain closest to the microbial strain. At this time, the traceability information of the microbial strain determined based on the multi-strain variation map in this embodiment may include:

[0108] Step S401: Based on the multi-strain variation map, determine a target existing strain that matches the microbial strain.

[0109] Among them, the multi-strain variation map includes multiple microbial strains belonging to the same species as the microbial strain, and the multiple microbial strains may include existing strains similar to the microbial strain and existing strains that are not similar to the microbial strain. Since the traceability information of similar microbial strains has a certain similarity or correlation, in order to accurately determine the traceability information of the microbial strain, a target existing strain that matches the microbial strain can be found in the multi-strain variation map. The target existing strain can be an existing strain that is closest to or most similar to the microbial strain in the multi-strain variation map, that is, the sequence similarity between the target existing strain and the microbial strain is higher than the sequence similarity between other existing strains and the microbial strain, that is, the genetic distance between the target existing strain and the microbial strain is closest.

[0110] From the above, it can be seen that the target existing strain can be obtained by calculating the sequence similarity between the existing strain and the microbial strain. Specifically, based on the multi-strain variation map, determining a target existing strain that matches the microbial strain can include: calculating the sequence similarity between the microbial strain and the existing strains in the multi-strain variation map; and then determining the existing strain with the maximum sequence similarity as the target existing strain that matches the microbial strain.

[0111] It should be noted that when the existing strains with the maximum sequence similarity are multiple different existing strains, one can be randomly selected from the multiple existing strains to be determined as the target existing strain, or one can be selected from the multiple existing strains as the target existing strain based on artificially configured rules or artificial experience, which can ensure the accuracy and reliability of determining the target existing strain.

[0112] In addition, the target existing strain can not only be determined by calculating the size of the sequence similarity, but also by analyzing and processing the multi-strain variation map through a machine learning model. At this time, based on the multi-strain variation map, determining a target existing strain that matches the microbial strain can include: obtaining a pre-trained machine learning model; inputting the multi-strain variation map and the microbial strain into the machine learning model, and obtaining the target existing strain that matches the microbial strain output by the machine learning model, thereby effectively ensuring the accuracy and reliability of the determination of the target existing strain.

[0113] Step S402: Based on the target existing strain, determine the traceability information of the microbial strain.

[0114] After obtaining the target existing strain, the target existing strain can be analyzed and processed to determine the traceability information of the microbial strain. In some instances, after obtaining the target existing strain, the existing traceability information of the target existing strain can be determined, and then the target existing strain and the corresponding existing traceability information can be determined as one of the traceability information of the microbial strain.

[0115] In other instances, since the target existing strain is only the closest strain to the microbial strain, it cannot fully and accurately reflect the variation of the current microbial strain, and the variation can directly affect the traceability information such as the transmission route and source of the microorganism. Therefore, in order to ensure the comprehensiveness and accuracy of the traceability information, the traceability information of the microorganism can be determined in combination with the variation of the microbial strain. At this time, based on the target existing strain, determining the traceability information of the microbial strain can include: determining the current strain variation information of the microbial strain; determining the differential variation site in the microbial strain based on the current strain variation information and the multi-strain variation map, wherein the differential variation site refers to a variation site in the current strain variation information that is different from the existing variation site in the multi-strain variation map; determining the traceability information of the microbial strain based on the differential variation site and the target existing strain.

[0116] Among them, in order to accurately determine the traceability information of the microbial strain, after obtaining the microbial strain, the microbial strain can be subjected to variation analysis. Specifically, the microbial strain can be subjected to variation analysis through the standard strain to determine the current strain variation information of the microbial strain. At this time, determining the current strain variation information of the microbial strain can include: obtaining the standard strain corresponding to the species; using the standard strain to perform variation analysis on the microbial strain to obtain the current strain variation information.

[0117] Specifically, for any one species of microorganism, a standard strain corresponds to it, and different species of microorganisms correspond to different standard strains, wherein, for any one species, the corresponding standard strain may be the first strain that can be collected or detected in the current species. In order to understand and count the variation of different subtypes of microbial strains in the current species, it is necessary to calculate and compare the obtained microbial strains with the standard strains of the species to determine the variation of the current microbial strains. Therefore, for the microbial strains to be analyzed, in order to accurately understand the variation, the standard strains used for variation analysis of the microbial strains can be first determined based on the species of the microbial strains. In some examples, the standard strains of each species can be stored in at least one microbial database. After obtaining the species of the microorganism, it can be searched in each microbial database based on the species, so as to obtain the standard strains corresponding to the species.

[0118] After obtaining the standard strain, the standard strain can be used to perform variation analysis on the microbial strain, so as to obtain the variation information of the current strain, which may include at least one of the following: variation type, variation position, variation number, variation ratio, etc., wherein the variation type may include: point mutation, insertion, deletion, etc.

[0119] It can be understood that the results of the variation analysis may include two categories, namely, the results of the absence of variation analysis and the results of the presence of variation analysis. At this time, using the standard strain to perform variation analysis on the microbial strain, obtaining the current strain variation information may include: when the standard strain and the microbial strain are the same, determining the current strain variation information as the first type of information used to identify that there is no variation in the microbial strain, that is, the current microbial strain does not vary relative to the standard strain; when the standard strain and the microbial strain are different, determining the current strain variation information as the second type of information used to identify that there is variation in the microbial strain, that is, the current microbial strain has variation relative to the standard strain.

[0120] When the current strain variation information indicates that there is no variation in the microbial strain, it means that the current microbial strain is not a new microbial strain, and there is no need to determine the differential variation sites in the microbial strain. When the current strain variation information indicates that there is variation in the microbial strain, it means that the current microbial strain is a new subtype of microbial strain, and the current strain variation information and multi-strain variation map can be analyzed and processed to determine the differential variation sites in the microbial strain, wherein the differential variation sites refer to variation sites that occur in the microbial strain and are different from the existing variation sites in the existing strains.

[0121] This embodiment does not limit the specific method for determining the differential mutation sites. In some instances, the differential mutation sites can be determined by analyzing and processing the current strain mutation information and the multi-strain mutation map through a pre-trained machine learning model. At this time, based on the current strain mutation information and the multi-strain mutation map, determining the differential mutation sites in the microbial strains can include: obtaining a pre-trained machine learning model, inputting the current strain mutation information and the multi-strain mutation map into the machine learning model, and obtaining the differential mutation sites in the microbial strains output by the machine learning model. It should be noted that when there are no differential mutation sites in the microbial strain, the machine learning model can output a null value or prompt information; when there are differential mutation sites in the microbial strain, the specific position information and base information of the differential mutation sites can be directly output, so as to ensure the accurate and reliable determination of the differential mutation sites.

[0122] In other instances, differential mutation sites can be determined not only by a pre-trained machine learning model, but also by analyzing and comparing with existing mutation sites appearing in existing strains. At this time, based on the current strain mutation information and the multi-strain mutation map, determining the differential mutation sites in the microbial strain can include: determining a set of existing mutation sites appearing in multiple existing strains based on the multi-strain mutation map; determining at least one current mutation site in the microbial strain based on the current strain mutation information; in the case where there is an existing mutation site identical to the current mutation site in the set of existing mutation sites, determining the current mutation site as a non-differential mutation site; in the case where there is no existing mutation site identical to the current mutation site in the set of existing mutation sites, determining the current mutation site as a differential mutation site.

[0123] Specifically, since the multi-strain variation topology includes relevant variation information of multiple existing strains, after obtaining the multi-strain variation map, the multi-strain variation map can be analyzed and processed to determine the set of existing variation sites appearing in multiple existing strains. It should be noted that any two specific sites or any two variation types in the existing variation site set are not repeated. When two or more identical variation sites are found in the existing variation site set, the two or more identical variation sites can be deduplicated. This can reduce the amount of effective data included in the existing variation site set, thereby helping to improve the efficiency of determining differential variation sites.

[0124] After obtaining the existing mutation site set, since the existing mutation site set includes multiple different existing mutation sites, such as site 32 (base A mutates to base T), site 65 (insertion of base G), site 108 (deletion of base C), etc., then at least one current mutation site in the microbial strain can be counted or determined based on the current strain mutation information, and then the existing mutation site set can be searched to see whether there is an existing mutation site that is the same as the current mutation site. When there is an existing mutation site that is the same as the current mutation site in the existing mutation site set, it means that the current mutation of the microbial strain is not a new mutation, but a mutation that has occurred in the existing microbial strain currently counted, and then the current mutation site can be determined as a non-differential mutation site. Correspondingly, when there is no existing mutation site that is the same as the current mutation site in the existing mutation site set, it means that the current mutation of the microbial strain is a new mutation, a mutation that has not occurred in the existing microbial strain, and then the current mutation site can be determined as a differential mutation site.

[0125] For example, the existing mutation site set includes multiple different existing mutation sites, such as site 32 (base A mutates to base T), site 65 (base G is inserted), and site 108 (base C is deleted). The current mutation sites may include site 65 (base G is inserted), site 108 (base C mutates to base A), and site 201 (base G mutates to base A). Since there is an existing mutation site identical to “site 65 (base G is inserted)” in the existing mutation site set, the above-mentioned “site 65 (base G is inserted)” can be determined as a non-differential mutation site, and there is no existing mutation site identical to “site 108 (base C mutates to base A)” and “site 201 (base G mutates to base A)” in the existing mutation site set, and the above-mentioned “site 108 (base C mutates to base A)” and “site 201 (base G mutates to base A)” can be determined as differential mutation sites, thereby effectively ensuring the accuracy and reliability of determining the differential mutation sites.

[0126] After the above steps, the differential mutation sites and the target existing strains corresponding to the microbial strains can be accurately obtained, and then the differential mutation sites and the target existing strains can be analyzed and processed to determine the traceability information of the microbial strains. In some examples, the differential mutation sites and the target existing strains can be directly determined as the traceability information of the microbial strains, or, in other examples, the traceability information can be determined in combination with the attribute information of the differential mutation sites. At this time, based on the differential mutation sites and the target existing strains, determining the traceability information of the microbial strains can include: obtaining the attribute information of the differential mutation sites, the attribute information includes at least one of the following: base type, mutation type, mutation ratio, wherein the attribute information can be determined by analyzing and comparing the differential mutation sites with the standard strains; and then the traceability information of the microbial strains can be determined based on the differential mutation sites, the attribute information and the target existing strains. Specifically, the differential mutation sites, the attribute information and the target existing strains can be directly determined as the traceability information of the microbial strains, which effectively ensures the accuracy and reliability of the determination of the traceability information.

[0127] In this embodiment, a target existing strain that matches the microbial strain is determined based on the multi-strain variation map, and then the traceability information of the microbial strain is determined based on the target existing strain. Specifically, the target existing strain can be directly determined as the traceability information of the microbial strain, or the traceability information can be determined in combination with the current strain variation information of the microbial strain. The user can select a method for determining the traceability information according to the specific application scenario or application requirement. This not only effectively ensures the accuracy and reliability of the determination of the traceability information, but also improves the flexibility of the method.

[0128] Figure 5A schematic diagram of a process for calculating the first similarity between the microbial strain and each existing microbial strain provided in an embodiment of the present invention; based on the above embodiment, refer to the attached Figure 5 As shown, this embodiment provides a technical solution for determining the first similarity between a microbial strain and an existing microbial strain by analyzing and comparing the base sequences of the microbial strain and the existing microbial strain. Specifically, in this embodiment, calculating the first similarity between the microbial strain and each existing microbial strain may include:

[0129] Step S501: obtaining the first base sequence of the microbial strain and the second base sequence of each existing microbial strain.

[0130] Since the construction of a multi-strain variation map is related to the similarity between a microbial strain and each existing microbial strain, as well as between multiple existing microorganisms, in order to accurately construct a multi-strain variation map, the first base sequence of the microbial strain and the second base sequence of each existing microbial strain can be obtained first. It should be noted that when the number of existing microbial strains is multiple, the number of second base sequences is also multiple, and the second base sequences corresponding to multiple different existing microbial strains are different.

[0131] Step S502: Compare the first base sequence with each second base sequence to obtain the number of mismatched bases, the number of inserted bases, and the number of deleted bases between the microbial strain and each existing microbial strain.

[0132] After obtaining the first base sequence and each second base sequence, the first base sequence and each second base sequence can be analyzed and compared, so as to obtain the number of mismatched bases, the number of inserted bases and the number of deleted bases between the microbial strain and each existing microbial strain. Specifically, the number of mismatched bases, the number of inserted bases and the number of deleted bases are all integers greater than or equal to 0. The number of mismatched bases can identify the number of point mutations present in the first base sequence relative to the second base sequence, the number of inserted bases can identify the number of bases present in the first base sequence that do not exist in the second base sequence, and the number of deleted bases can identify the number of bases present in the second base sequence that do not exist in the first base sequence.

[0133] For example, in the second base sequence A A GTCTGACCGGACAAGC, the first base sequence is A GGTCCTGACCGACATGC, by comparing the first base sequence and the second base sequence, it can be known that, relative to the above-mentioned second base sequence, the number of mismatched bases corresponding to the first base sequence is 2 (that is, the A at the 2nd position becomes G, and the A at the 3rd from the bottom becomes T), the number of inserted bases is 1 (C at the 6th position), and the number of deleted bases is 1 (between the 12th and 13th positions). This effectively achieves stable and reliable acquisition of the number of mismatched bases, the number of inserted bases, and the number of deleted bases.

[0134] Step S503: Determine a first similarity between the microbial strain and each existing microbial strain based on the number of mismatched bases, the number of inserted bases and the number of deleted bases.

[0135] Since the number of mismatched bases, the number of inserted bases and the number of deleted bases can reflect the degree of difference between the current microbial strain and each existing microbial strain from different angles, after obtaining the number of mismatched bases, the number of inserted bases and the number of deleted bases, the number of mismatched bases, the number of inserted bases and the number of deleted bases can be analyzed and processed to determine the first similarity between the microbial strain and each existing microbial strain.

[0136] In some instances, the first similarity can be determined by a pre-trained machine learning model. In this case, based on the number of mismatched bases, the number of inserted bases, and the number of deleted bases, determining the first similarity between the microbial strain and each existing microbial strain can include: obtaining a pre-trained machine learning model, inputting the number of mismatched bases, the number of inserted bases, and the number of deleted bases into the machine learning model, and obtaining the first similarity between the microbial strain output by the machine learning model and each existing microbial strain.

[0137] In other instances, the first similarity can be determined not only by a pre-trained machine learning model, but also by combining the total length of the sequence after statistical updating of the first base sequence. At this time, determining the first similarity between the microbial strain and each existing microbial strain based on the number of mismatched bases, the number of inserted bases, and the number of deleted bases can include: statistically updating the first base sequence based on the number of inserted bases and the number of deleted bases to obtain an updated first base sequence; determining the total sequence length of the updated first base sequence; determining the first similarity between the microbial strain and each existing microbial strain based on the number of mismatched bases, the number of inserted bases, the number of deleted bases, and the total sequence length.

[0138] Specifically, when calculating the first similarity between the microbial strain and each existing microbial strain, since the current microbial strain may have inserted bases or missing bases, in the case of inserted bases, a deletion operation needs to be performed on the specific inserted bases; in the case of missing bases, a base filling operation needs to be performed on the missing bases. After the above operations, the sequence length of the microbial strain may change.

[0139] From the above, it can be seen that the obtained number of inserted bases and the number of deleted bases can affect the sequence length of the first base sequence of the current microbial strain. In order to accurately analyze and process the current microbial strain, after obtaining the number of inserted bases and the number of deleted bases, the first base sequence can be statistically updated based on the number of inserted bases and the number of deleted bases. Specifically, the inserted bases in the first base sequence can be deleted based on the number of inserted bases, and the corresponding positions in the first base sequence can be added based on the number of deleted bases, so that the updated first base sequence can be obtained.

[0140] After obtaining the first base sequence, the number of bases in the first base sequence can be counted to determine the total sequence length of the updated first base sequence, and then the number of unmatched bases, the number of inserted bases, the number of deleted bases and the total sequence length can be analyzed and processed to determine the first similarity between the microbial strain and each existing microbial strain.

[0141] In some examples, the first similarity may be negatively correlated with the number of mismatched bases, the first similarity may be negatively correlated with the number of inserted bases, and the first similarity may be negatively correlated with the number of deleted bases.

[0142] In other examples, the first similarity can be determined by the following formula. In this case, based on the number of mismatched bases, the number of inserted bases, the number of deleted bases and the total length of the sequence, determining the first similarity between the microbial strain and each existing microbial strain may include: obtaining the sum of the number of mismatched bases, the number of inserted bases and the number of deleted bases; determining the difference between the total length of the sequence and the sum; and determining the ratio of the difference to the total length of the sequence as the first similarity between the microbial strain and the corresponding existing microbial strain.

[0143] Specifically, when the number of mismatched bases is M, the number of inserted bases is I, the number of deleted bases is D, and the total length of the sequence is N, the sum of the number of mismatched bases M, the number of inserted bases I, and the number of deleted bases D can be obtained first, that is, (M+I+D); then the difference between the total length of the sequence and the sum can be determined, and the difference can be expressed as N-(M+I+D) or (NMID). After obtaining the difference, the ratio between the difference and the total length of the sequence can be determined as the first similarity between the microbial strain and the existing microbial strain, that is, the first similarity This effectively ensures the accuracy and reliability of calculating the first similarity.

[0144] It should be noted that the specific implementation principle and implementation effect of calculating the second similarity between any two existing microbial strains are similar to the specific implementation principle and implementation effect of calculating the first similarity between a microbial strain and each existing microbial strain. For details, please refer to the above statements and will not be repeated here.

[0145] In this embodiment, by obtaining the first base sequence of the microbial strain and the second base sequence of each existing microbial strain, comparing the first base sequence with each second base sequence, the number of mismatched bases, the number of inserted bases and the number of deleted bases between the microbial strain and each existing microbial strain are obtained, and then the first similarity between the microbial strain and each existing microbial strain is determined based on the number of mismatched bases, the number of inserted bases and the number of deleted bases, thereby effectively achieving the ability to stably and accurately calculate the first similarity, and then the calculated first similarity can be used to construct a multi-strain variation map, thereby effectively ensuring the accuracy and reliability of establishing the multi-strain variation map.

[0146] For specific applications, refer to the attached Figure 6 As shown, this application embodiment provides a method for constructing a multi-strain variation map of microorganisms, which can quickly compare the microbial strains to be detected with the detected microbial strains, and construct a multi-strain variation map for microbial tracing and variation inference operations. Specifically, the method may include:

[0147] Step 1: Obtain the strain of the microorganism to be detected and the species of the strain to be detected.

[0148] Specifically, the whole genome sequencing operation can be performed on the microorganism to be detected, so as to obtain some microbial gene fragments and the species of the strain to be detected, and then the microbial gene fragments are sequenced to obtain the strain to be detected of the microorganism to be detected, which can be the whole gene base sequence corresponding to the microorganism to be detected.

[0149] Step 2: Compare the strain to be tested with the reference genome of the standard strain of its species, and calculate the variation detection information of the strain to be tested.

[0150] Specifically, a standard strain can be first obtained based on the species of the strain to be tested, and then the reference genome of the standard strain can be determined, and the strain to be tested and the reference genome can be calculated and compared, so as to obtain variation detection information of the strain to be tested, and the variation detection information can include at least one of the following: mutation type, mutation position (or called variation site), number of mutations and mutation ratio, wherein the mutation type can include at least one of the following: point mutation, insertion, deletion; the mutation position can refer to the base position corresponding to the mutation type.

[0151] In some other examples, after obtaining the variation detection information, not only can the variation detection information be used to construct a multi-strain variation map, but also the genotype can be calculated based on the variation detection information, so that the strain to be detected can be typed, that is, the subtype and position of the microorganism to be classified between the corresponding species can be quickly located. For example: when it is found that a strain to be detected has a high degree of similarity with a detected strain, the type determined by the strain to be detected can be determined to be the same as the type of the detected strain; or, when it is found that a strain to be detected is similar to and different from a detected strain, at this time, when the type of the detected strain is H2N2, the type of the strain to be detected can be determined as H3N2 according to the preset rules, thereby realizing the typing operation of the strain to be detected. After the typing operation of the strain to be detected, the strain to be detected can be added to the corresponding microbial database or the corresponding multi-strain variation map, which effectively ensures the data comprehensiveness of the microbial database or the multi-strain variation map.

[0152] Step 3: Extract the whole genome sequencing information of the remaining tested strains of the species to which the strain to be tested belongs that have undergone whole genome sequencing, and calculate the population variation of all tested strains.

[0153] Specifically, after obtaining the variation detection information of the current strain to be tested, the genome sequencing data of the remaining strains that have undergone whole genome sequencing operations can be determined. The genome sequencing data may include the gene sequences corresponding to each tested strain and the existing variation detection information. The above-mentioned variation detection information and the existing variation detection information can then be statistically analyzed to obtain the population variation situation.

[0154] Step 4: Calculate the first similarity between the strain to be detected and each detected strain, and the second similarity between any two existing microbial strains.

[0155] Step 5: Establish a multi-strain variation map based on the first similarity, the second similarity, the variation detection information of the strain to be detected, and the population variation of all detected strains.

[0156] Step 6: Based on the multi-strain variation map, trace the strain to be tested to obtain traceability information.

[0157] Specifically, the detected strain that is closest to the strain to be detected is determined in the multi-strain variation map. At the same time, based on the variation detection information and population variation of the strain to be detected, the differential variation sites in the strain to be detected can be determined, and the attribute information of the differential variation sites can be determined. The attribute information may include at least one of the following: base type, variation type, variation ratio, etc.; then, the traceability information is determined based on the attribute information of the differential variation sites and the detected strains. Specifically, the above data can be combined with epidemiology to perform traceability operations on the microorganisms, so as to accurately determine the traceability information of the microorganisms.

[0158] In some other examples, when a differential mutation site is found in the strain to be detected, the differential mutation site and the strain to be detected can be associated and stored in the microbial database as a new detected strain in the microbial database, thereby updating the data in the microbial database and making the data in the microbial database more comprehensive.

[0159] It should be noted that after obtaining the multi-strain variation map, it can be used not only for traceability operations, but also for health and medical prevention and control operations, drug resistance analysis operations, vaccine research and development operations, and guidance on medication operations, etc. This effectively improves the practicality and application scope of the multi-strain variation map.

[0160] The method for constructing a multi-strain variation map of microorganisms provided in the present application embodiment can quickly locate the subtype and position of the microorganism to be classified between corresponding species based on the variation detection information of the strain to be detected of the microorganism, that is, it can quickly and accurately establish a multi-strain variation map corresponding to the species of the microorganism, and then the established multi-strain variation map can be used to trace the microorganism, which can improve the efficiency of the traceability operation and can be promoted on a large scale, further improving the practicality of the method.

[0161] Figure 7 A schematic diagram of a method for constructing a multi-strain variation map of a microorganism provided in an embodiment of the present invention; see Attachment Figure 7As shown, this embodiment provides a method for constructing a multi-lineage variation map of microorganisms. The executor of the method can be a device for constructing a multi-lineage variation map of microorganisms. It can be understood that the device for constructing a multi-lineage variation map of microorganisms can be implemented as software, or a combination of software and hardware. Specifically, when the device for constructing a multi-lineage variation map of microorganisms is implemented as hardware, it can be various electronic devices with operations for constructing a multi-lineage variation map of microorganisms, including but not limited to tablet computers, personal computers PCs, servers, and the like. When the device for constructing a multi-lineage variation map of microorganisms is implemented as software, it can be installed in the electronic devices listed above. Based on the above-mentioned device for constructing a multi-lineage variation map of microorganisms, the method for constructing a multi-lineage variation map of microorganisms in this embodiment can include the following steps:

[0162] Step S701: Obtain microbial strains and species of the microbial strains.

[0163] Step S702: Determine the current strain variation information of the microbial strain.

[0164] Step S703: determining existing strain variation information corresponding to each of the multiple existing microbial strains under the genus.

[0165] Step S704: Based on the microbial strain, the current strain variation information, multiple existing microbial strains and the existing strain variation information, a multi-strain variation map is established, and the multi-strain variation map includes multiple nodes and edges between two nodes. The nodes are used to identify the microbial strains, and the edges are used to identify the correlation between the variation information of two or more different microbial strains under the same genus.

[0166] In some instances, establishing a multi-strain variation map based on a microbial strain, current strain variation information, multiple existing microbial strains, and existing strain variation information may include: calculating a first similarity between a microbial strain and each existing microbial strain, and a second similarity between any two existing microbial strains; and establishing a multi-strain variation map based on the first similarity, the second similarity, the current strain variation information, and the existing strain variation information.

[0167] In some instances, after establishing a multi-strain variation map, the method in this embodiment may further include: determining a target existing strain that matches the microbial strain based on the multi-strain variation map; and determining traceability information of the microbial strain based on the target existing strain.

[0168] Among them, the specific implementation process and implementation effect of the gene variation detection method in this embodiment are similar to the specific implementation process and implementation effect of the corresponding same steps in the above embodiments. For details, please refer to the above statements and will not be repeated here.

[0169] The method for constructing a multi-strain variation map of microorganisms provided in this embodiment obtains the microbial strain and the species of the microbial strain, determines the current strain variation information of the microbial strain, determines the existing strain variation information corresponding to each of the multiple existing microbial strains under the species, and then establishes a multi-strain variation map based on the microbial strain, the current strain variation information, the multiple existing microbial strains and the existing strain variation information, effectively ensuring the accuracy and reliability of the establishment of the multi-strain variation map, and then the multi-strain variation map can be used for traceability operations, further improving the practicality of the method.

[0170] Figure 8 A schematic diagram of a microbial traceability device according to an embodiment of the present invention; see attached Figure 8 As shown, this embodiment provides a microorganism tracing device, which can perform the above Figure 2 The microorganism tracing method shown in the figure, the microorganism tracing device may include: a first acquisition module 11, a first determination module 13 and a first processing module 12. Specifically,

[0171] A first acquisition module 11 is used to acquire the microbial strains to be analyzed and the species of the microbial strains;

[0172] The first processing module 12 is used to perform variation analysis on the microbial strain to obtain variation information of the current strain;

[0173] A first determination module 13 is used to determine existing strain variation information corresponding to each of a plurality of existing microbial strains under the genus;

[0174] The first processing module 12 is further used to establish a multi-strain variation map based on the microbial strain, the current strain variation information, the multiple existing microbial strains and the existing strain variation information, wherein the multi-strain variation map includes multiple nodes and edges between two nodes, wherein the nodes are used to identify the microbial strains, and the edges are used to identify the correlation between the variation information of two or more different microbial strains under the same genus;

[0175] The first processing module 12 is used to determine the traceability information of the microbial strains based on the multi-strain variation map.

[0176] In some instances, when the first processing module 12 determines the traceability information of the microbial strain based on the multi-strain variation map, the first processing module 12 is used to: determine a target existing strain that matches the microbial strain based on the multi-strain variation map; and determine the traceability information of the microbial strain based on the target existing strain.

[0177] In some instances, when the first processing module 12 determines the traceability information of a microbial strain based on an existing target strain, the first processing module 12 is used to: determine the current strain variation information of the microbial strain; determine the differential variation sites in the microbial strain based on the current strain variation information and a multi-strain variation map, wherein the differential variation sites refer to variation sites in the current strain variation information that are different from the existing variation sites in the multi-strain variation map; determine the traceability information of the microbial strain based on the differential variation sites and the existing target strain.

[0178] In some instances, when the first processing module 12 determines differential mutation sites in a microbial strain based on current strain mutation information and a multi-strain mutation map, the first processing module 12 is used to: determine a set of existing mutation sites appearing in multiple existing strains based on the multi-strain mutation map; determine at least one current mutation site in the microbial strain based on the current strain mutation information; determine the current mutation site as a non-differential mutation site when there is an existing mutation site identical to the current mutation site in the set of existing mutation sites; and determine the current mutation site as a differential mutation site when there is no existing mutation site identical to the current mutation site in the set of existing mutation sites.

[0179] In some instances, when the first processing module 12 determines the traceability information of the microbial strain based on the differential mutation site and the target existing strain, the first processing module 12 is used to: obtain attribute information of the differential mutation site, the attribute information including at least one of the following: base type, mutation type, mutation ratio; determine the traceability information of the microbial strain based on the differential mutation site, the attribute information and the target existing strain.

[0180] In some examples, when the first processing module 12 determines the current strain variation information of the microbial strain, the first processing module 12 is used to: obtain a standard strain corresponding to the species; perform variation analysis on the microbial strain using the standard strain to obtain the current strain variation information.

[0181] In some instances, when the first processing module 12 uses the standard strain to perform variation analysis on the microbial strain to obtain the variation information of the current strain, the first processing module 12 is used to: when the standard strain and the microbial strain are the same, determine the variation information of the current strain as the first type of information used to identify that there is no variation in the microbial strain; when the standard strain and the microbial strain are different, determine the variation information of the current strain as the second type of information used to identify that there is variation in the microbial strain.

[0182] In some instances, when the first acquisition module 11 acquires the microbial strain to be analyzed and the species of the microbial strain, the first acquisition module 11 is used to execute: acquiring the sample to be analyzed; performing whole genome sequencing on the sample to be analyzed to obtain sequencing fragments and the species of the microbial strain; performing sequence splicing on the sequencing fragments to acquire the microbial strain, which includes the whole genome base sequence corresponding to the sample to be analyzed.

[0183] In some instances, when the first determination module 13 establishes a multi-strain variation map based on the microbial strain, the current strain variation information, multiple existing microbial strains, and the existing strain variation information, the first determination module 13 is used to execute: calculating a first similarity between the microbial strain and each existing microbial strain, and a second similarity between any two existing microbial strains; and establishing a multi-strain variation map based on the first similarity, the second similarity, the current strain variation information, and the existing strain variation information.

[0184] In some instances, when the first determination module 13 calculates the first similarity between the microbial strain and each existing microbial strain, the first determination module 13 is used to execute: obtaining a first base sequence of the microbial strain and a second base sequence of each existing microbial strain; comparing the first base sequence with each second base sequence to obtain the number of mismatched bases, the number of inserted bases, and the number of deleted bases between the microbial strain and each existing microbial strain; and determining the first similarity between the microbial strain and each existing microbial strain based on the number of mismatched bases, the number of inserted bases, and the number of deleted bases.

[0185] In some instances, when the first determination module 13 determines the first similarity between the microbial strain and each existing microbial strain based on the number of mismatched bases, the number of inserted bases, and the number of deleted bases, the first determination module 13 is used to execute: statistically updating the first base sequence based on the number of inserted bases and the number of deleted bases to obtain an updated first base sequence; determining the total sequence length of the updated first base sequence; and determining the first similarity between the microbial strain and each existing microbial strain based on the number of mismatched bases, the number of inserted bases, the number of deleted bases, and the total sequence length.

[0186] In some examples, the first similarity is negatively correlated with the number of mismatched bases, the first similarity is negatively correlated with the number of inserted bases, and the first similarity is negatively correlated with the number of deleted bases.

[0187] In some instances, when the first determination module 13 determines the first similarity between the microbial strain and each existing microbial strain based on the number of mismatched bases, the number of inserted bases, the number of deleted bases and the total length of the sequence, the first determination module 13 is used to execute: obtaining the sum of the number of mismatched bases, the number of inserted bases and the number of deleted bases; determining the difference between the total length of the sequence and the sum; and determining the ratio of the difference to the total length of the sequence as the first similarity between the microbial strain and the corresponding existing microbial strain.

[0188] In some instances, after determining the traceability information of the microbial strain, the first processing module 12 in this embodiment is also used to execute: based on the traceability information, generate health and prevention information corresponding to the microbial strain; and / or, based on the traceability information, generate medication guidance information corresponding to the microbial strain; and / or, based on the traceability information, perform drug resistance analysis on the microbial strain to obtain drug resistance analysis results; and / or, based on the traceability information, perform drug research and development on the microbial strain to obtain drug research and development information.

[0189] Figure 8 The device shown can perform Figure 1-Figure 6 For the method of the embodiment shown in the figure, the part not described in detail in this embodiment can be referred to Figure 1-Figure 6 The implementation process and technical effects of this technical solution refer to Figure 1-Figure 6 The description in the illustrated embodiment will not be repeated here.

[0190] In one possible design, Figure 8 The structure of the microorganism tracing device shown in the figure can be realized as an electronic device, which can be a controller, a personal computer, a server, or other devices. Fig. 9 As shown, the electronic device may include: a first processor 21 and a first memory 22. The first memory 22 is used to store the corresponding electronic device to execute the above Figure 1-Figure 6 The program of the microorganism tracing method provided in the illustrated embodiment, the first processor 21 is configured to execute the program stored in the first memory 22 .

[0191] The program includes one or more computer instructions, wherein the one or more computer instructions can implement the following steps when executed by the first processor 21: obtaining the microbial strain to be analyzed and the species of the microbial strain; performing variation analysis on the microbial strain to obtain the variation information of the current strain; determining the existing strain variation information corresponding to each of the multiple existing microbial strains under the species; establishing a multi-strain variation map based on the microbial strain, the current strain variation information, the multiple existing microbial strains and the existing strain variation information, the multi-strain variation map including multiple nodes and edges between two nodes, the nodes are used to identify the microbial strains, and the edges are used to identify the correlation between the variation information of two or more different microbial strains under the same species; based on the multi-strain variation map, determining the traceability information of the microbial strain.

[0192] Furthermore, the first processor 21 is also used to execute the aforementioned Figure 1-Figure 6 All or part of the steps in the illustrated embodiments.

[0193] The structure of the electronic device may further include a first communication interface 23 for the electronic device to communicate with other devices or a communication network.

[0194] In addition, an embodiment of the present invention provides a computer storage medium for storing computer software instructions used by electronic devices, which includes instructions for executing the above Figure 1-Figure 6 The procedures involved in the method for tracing the origin of microorganisms in the illustrated embodiment.

[0195] In addition, an embodiment of the present invention provides a computer program product, including: a computer-readable storage medium storing computer instructions, when the computer instructions are executed by one or more processors, causing the one or more processors to execute the above Figure 1-Figure 6 The steps in the method for tracing the origin of microorganisms in the method embodiment are shown.

[0196] Fig.10 A schematic diagram of a device for constructing a multi-strain variation map of a microorganism provided in an embodiment of the present invention; see Attachment Figure 7 As shown, this embodiment provides a device for constructing a multi-strain variation map of microorganisms, and the traceability device of the microorganism can perform the above Figure 2 The microorganism tracing method shown in the figure, the microorganism tracing device may include: a second acquisition module 31, a second determination module 32 and a second processing module 33, specifically,

[0197] The second acquisition module 31 is used to acquire microbial strains and species of the microbial strains.

[0198] The second determination module 32 is used to determine the current strain variation information of the microbial strain.

[0199] The second determination module 32 is further used to determine the existing strain variation information corresponding to each of the multiple existing microbial strains under the species.

[0200] The second processing module 33 is used to establish a multi-strain variation map based on the microbial strain, the current strain variation information, multiple existing microbial strains and the existing strain variation information. The multi-strain variation map includes multiple nodes and edges between two nodes. The nodes are used to identify the microbial strains, and the edges are used to identify the correlation between the variation information of two or more different microbial strains under the same genus.

[0201] In some instances, when the second processing module 33 establishes a multi-strain variation map based on the microbial strain, the current strain variation information, multiple existing microbial strains, and the existing strain variation information, the second processing module 33 is used to: calculate a first similarity between the microbial strain and each existing microbial strain, and a second similarity between any two existing microbial strains; and establish a multi-strain variation map based on the first similarity, the second similarity, the current strain variation information, and the existing strain variation information.

[0202] In some instances, after establishing a multi-strain variation map, the second processing module 33 in this embodiment is also used to: determine a target existing strain that matches the microbial strain based on the multi-strain variation map; and determine the traceability information of the microbial strain based on the target existing strain.

[0203] Fig.10 The device shown can perform Figure 7 For the method of the embodiment shown in the figure, the part not described in detail in this embodiment can be referred to the embodiment of the present invention. Figure 7 The implementation process and technical effects of this technical solution are shown in the relevant description of the embodiment shown in FIG. Figure 7 The description in the illustrated embodiment will not be repeated here.

[0204] In one possible design, Fig.10 The structure of the device for constructing the multi-strain variation map of microorganisms shown in the figure can be realized as an electronic device, which can be a mobile phone, a tablet computer, a server, or other devices. Fig.11 As shown, the electronic device may include: a second processor 41 and a second memory 42. The second memory 42 is used to store the corresponding electronic device executing the above Figure 7 The program of the method for constructing a multi-strain variation map of microorganisms provided in the illustrated embodiment, the second processor 41 is configured to execute the program stored in the second memory 42 .

[0205] The program includes one or more computer instructions, wherein the one or more computer instructions can implement the following steps when executed by the second processor 41: obtaining a microbial strain and a species of the microbial strain; determining the current strain variation information of the microbial strain; determining the existing strain variation information corresponding to each of multiple existing microbial strains under the species; and establishing a multi-strain variation map based on the microbial strain, the current strain variation information, multiple existing microbial strains and the existing strain variation information, wherein the multi-strain variation map includes multiple nodes and edges between two nodes, wherein the nodes are used to identify the microbial strains, and the edges are used to identify the correlation between the variation information of two or more different microbial strains under the same species.

[0206] Furthermore, the second processor 41 is also used to execute the aforementioned Figure 7 All or part of the steps in the illustrated embodiments.

[0207] The structure of the electronic device may further include a second communication interface 43 for the electronic device to communicate with other devices or a communication network.

[0208] In addition, an embodiment of the present invention provides a computer storage medium for storing computer software instructions used by electronic devices, which includes instructions for executing the above Figure 7 The procedures involved in the method for constructing a multi-strain variation map of microorganisms in the method embodiment shown.

[0209] In addition, an embodiment of the present invention provides a computer program product, including: a computer-readable storage medium storing computer instructions, when the computer instructions are executed by one or more processors, causing the one or more processors to execute the above Figure 7 The steps in the method for constructing a multi-strain variation map of microorganisms in the method embodiment are shown.

[0210] The device embodiments described above are merely illustrative, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the scheme of this embodiment. Ordinary technicians in this field can understand and implement it without paying creative labor.

[0211] Through the description of the above embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by adding a necessary general hardware platform, and of course can also be implemented by combining hardware and software. Based on such an understanding, the above technical solution is essentially or the part that contributes to the prior art can be embodied in the form of a computer product, and the present invention can be in the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program codes.

[0212] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable device to produce a machine, so that the instructions executed by the processor of the computer or other programmable device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0213] These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable device to work in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture including an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0214] These computer program instructions may also be loaded onto a computer or other programmable device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for executing on the computer or other programmable device to implement the process. Figure 1 A process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0215] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0216] The memory may include non-permanent storage in a computer-readable medium, random access memory (RAM) and / or non-volatile memory in the form of read-only memory (ROM) or flash RAM. The memory is an example of a computer-readable medium.

[0217] Computer readable media include permanent and non-permanent, removable and non-removable media that can be implemented by any method or technology to store information. Information can be computer readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, compact disk read-only memory (CD-ROM), digital versatile disk (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device. As defined herein, computer readable media does not include temporary computer readable media (transitory media), such as modulated data signals and carrier waves.

[0218] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for tracing the origin of microorganisms, characterized in that: include: Obtaining a microbial strain to be analyzed and the species of the microbial strain; Performing variation analysis on the microbial strain to obtain variation information of the current strain; Determine the existing strain variation information corresponding to each of the multiple existing microbial strains under the genus; Based on the microbial strain, the current strain variation information, the multiple existing microbial strains and the existing strain variation information, a multi-strain variation map is established, wherein the multi-strain variation map includes multiple nodes and edges between two nodes, wherein the nodes are used to identify the microbial strains, and the edges are used to identify the correlation between the variation information of two or more different microbial strains under the same genus; Based on the multi-strain variation map, the traceability information of the microbial strain is determined.

2. The method according to claim 1, characterized in that Based on the multi-strain variation map, the traceability information of the microbial strain is determined, including: Based on the multi-strain variation map, determining a target existing strain that matches the microbial strain; Based on the target existing strain, the traceability information of the microbial strain is determined.

3. The method according to claim 2, characterized in that Based on the target existing strain, the traceability information of the microbial strain is determined, including: Determining current strain variation information of the microbial strain; Determine the differential mutation sites in the microbial strains based on the current strain mutation information and the multi-strain mutation map, wherein the differential mutation sites refer to mutation sites in the current strain mutation information that are different from existing mutation sites in the multi-strain mutation map; Based on the differential mutation sites and the target existing strains, the traceability information of the microbial strain is determined.

4. The method according to claim 3, characterized in that Determining differentially variable sites in the microbial strains based on the current strain variation information and the multi-strain variation map includes: Based on the multi-strain variation map, determining a set of existing variation sites appearing in the multiple existing strains; Determining at least one current variation site in the microbial strain based on the current strain variation information; If there is an existing variant site that is the same as the current variant site in the existing variant site set, determining the current variant site as a non-differential variant site; When there is no existing variation site identical to the current variation site in the existing variation site set, the current variation site is determined as a differential variation site.

5. The method according to claim 3, characterized in that: Based on the differentially variant sites and the target existing strains, the traceability information of the microbial strains is determined, including: Acquiring attribute information of the differentially variant site, wherein the attribute information includes at least one of the following: base type, mutation type, and mutation ratio; Based on the differential mutation sites, attribute information and the target existing strains, the traceability information of the microbial strain is determined.

6. The method according to claim 3, characterized in that: Determining the current strain variation information of the microbial strain, including: Obtaining a standard strain corresponding to the species; The standard strain is used to perform variation analysis on the microbial strain to obtain variation information of the current strain.

7. The method according to any one of claims 1 to 6, characterized in that: Obtaining the microbial strain to be analyzed and the species of the microbial strain, including: Obtaining samples to be analyzed; Performing whole genome sequencing on the sample to be analyzed to obtain sequencing fragments and the species of the microbial strain; The sequencing fragments are sequenced and spliced ​​to obtain the microbial strain, which includes the whole genome base sequence corresponding to the sample to be analyzed.

8. The method according to any one of claims 1 to 6, characterized in that: Based on the microbial strain, the current strain variation information, the multiple existing microbial strains and the existing strain variation information, the multi-strain variation map is established, including: Calculating a first similarity between the microbial strain and each existing microbial strain, and a second similarity between any two existing microbial strains; The multi-strain variation map is established based on the first similarity, the second similarity, the current strain variation information and the existing strain variation information.

9. The method according to claim 8, characterized in that Calculating a first similarity between the microbial strain and each existing microbial strain comprises: Obtaining the first base sequence of the microbial strain and the second base sequence of each existing microbial strain; Comparing the first base sequence with each second base sequence to obtain the number of mismatched bases, the number of inserted bases, and the number of deleted bases between the microbial strain and each existing microbial strain; Based on the number of mismatched bases, the number of inserted bases, and the number of deleted bases, a first similarity between the microbial strain and each existing microbial strain is determined.

10. The method according to claim 9, characterized in that Determining a first similarity between the microbial strain and each existing microbial strain based on the number of mismatched bases, the number of inserted bases, and the number of deleted bases includes: Performing statistical updates on the first base sequence based on the number of inserted bases and the number of deleted bases to obtain an updated first base sequence; Determining the total length of the updated first base sequence; Based on the number of mismatched bases, the number of inserted bases, the number of deleted bases and the total length of the sequence, a first similarity between the microbial strain and each existing microbial strain is determined.

11. The method according to claim 10, characterized in that The first similarity is negatively correlated with the number of mismatched bases, the first similarity is negatively correlated with the number of inserted bases, and the first similarity is negatively correlated with the number of deleted bases.

12. The method according to claim 10, characterized in that Determining a first similarity between the microbial strain and each existing microbial strain based on the number of mismatched bases, the number of inserted bases, the number of deleted bases and the total length of the sequence includes: Obtaining the sum of the number of mismatched bases, the number of inserted bases, and the number of deleted bases; Determining the difference between the total length of the sequence and the sum; The ratio between the difference and the total length of the sequence is determined as the first similarity between the microbial strain and the corresponding existing microbial strain.

13. A method for constructing a multi-strain variation map of microorganisms, characterized in that: include: Obtaining microbial strains and species of the microbial strains; Determining current strain variation information of the microbial strain; Determine the existing strain variation information corresponding to each of the multiple existing microbial strains under the genus; Based on the microbial strain, the current strain variation information, the multiple existing microbial strains and the existing strain variation information, a multi-strain variation map is established, wherein the multi-strain variation map includes multiple nodes and edges between two nodes, wherein the nodes are used to identify the microbial strains, and the edges are used to identify the correlation between variation information between two or more different microbial strains of the same genus.

14. The method according to claim 13, characterized in that Based on the microbial strain, the current strain variation information, the multiple existing microbial strains and the existing strain variation information, a multi-strain variation map is established, including: Calculating a first similarity between the microbial strain and each existing microbial strain, and a second similarity between any two existing microbial strains; The multi-strain variation map is established based on the first similarity, the second similarity, the current strain variation information and the existing strain variation information.

15. The method according to claim 13, characterized in that After establishing the multi-strain variation map, the method further comprises: Based on the multi-strain variation map, determining a target existing strain that matches the microbial strain; Based on the target existing strain, the traceability information of the microbial strain is determined.

16. An electronic device, characterized in that: include: A memory and a processor; wherein the memory is used to store one or more computer instructions, wherein the one or more computer instructions, when executed by the processor, implement the method of any one of claims 1 to 15.

17. A computer storage medium, characterized in that: Used to store a computer program, which enables a computer to implement the method of any one of claims 1 to 15 when executed by the computer.

18. A computer program product, characterized in that include: A computer program, when executed by a processor of an electronic device, causes the processor to execute the steps of any one of the methods of claims 1 to 15.

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