Preparation method and device of gene probe, probe and kit

Abstract

The embodiment of the invention discloses a preparation method and device of a gene probe, the probe and a kit, and the preparation method of the gene probe comprises the following steps: determining at least one microorganism corresponding to a target disease; analyzing the gene sequence of the at least one microorganism to determine a target gene sequence of the at least one microorganism; and preparing a gene probe corresponding to the target disease based on the target gene sequence of the at least one microorganism.

Description

Technical Field

[0001] The embodiments of the present application relate to the field of bioinformatics, and are related to but not limited to a method and device for preparing a gene probe, a probe, and a kit. Background Art

[0002] Chronic obstructive pulmonary disease (COPD) is a common, preventable and treatable clinical disease characterized by persistent respiratory symptoms and airflow limitation. It is usually caused by airway and / or alveolar abnormalities caused by significant exposure to toxic particles or gases and the patient's own lung hypoplasia. Major complications affect the morbidity and mortality.

[0003] Currently, the discovery of COPD is still based on clinician experience, bacterial culture or next-generation sequencing methods, but the experimental costs are high and require a lot of time and financial resources. Summary of the invention

[0004] In view of this, the embodiments of the present application provide a method and device for preparing a gene probe, a probe and a kit.

[0005] The technical solution of the embodiment of the present application is implemented as follows:

[0006] In a first aspect, an embodiment of the present application provides a method for preparing a gene probe, the method comprising:

[0007] Identify at least one microorganism corresponding to the target disease;

[0008] Analyzing the gene sequence of the at least one microorganism to determine the target gene sequence of the at least one microorganism;

[0009] Based on the target gene sequence of the at least one microorganism, a gene probe corresponding to the target disease is prepared.

[0010] In some embodiments, the analyzing the gene sequence of the at least one microorganism to determine the target gene sequence of the at least one microorganism comprises: analyzing the gene sequence of the at least one microorganism to obtain a reference sequence; using the reference sequence to construct a phylogenetic tree of the at least one microorganism; and determining the target gene sequence of the at least one microorganism based on the phylogenetic tree.

[0011] In some embodiments, the analyzing the gene sequence of the at least one microorganism to obtain a reference sequence includes: obtaining multiple genome sequences of a first microorganism among the at least one microorganism; performing statistics on the sequences at the same sites in the multiple genome sequences to obtain statistical results; and determining the reference sequence corresponding to the first microorganism based on the statistical results.

[0012] In some embodiments, determining the target gene sequence of the at least one microorganism based on the phylogenetic tree includes: determining multiple first gene sequences of the at least one microorganism based on the phylogenetic tree; wherein the first gene sequence is used to characterize the sequence information of the strain of the at least one microorganism; performing sequence consistency comparison on the multiple first gene sequences to obtain a comparison result; and determining the target gene sequence of the at least one microorganism based on the comparison result.

[0013] In some embodiments, the determining of multiple first gene sequences of the at least one microorganism based on the phylogenetic tree includes: determining, based on the phylogenetic tree, first gene sequences corresponding to different strains of the at least one microorganism, to obtain multiple first gene sequences; correspondingly, performing sequence consistency comparison on the multiple first gene sequences to obtain comparison results includes: performing sequence consistency comparison on the first gene sequences corresponding to the different strains of microorganisms, to obtain comparison results.

[0014] In some embodiments, determining the target gene sequence of the at least one microorganism based on the comparison result includes: determining at least one second gene sequence based on the comparison result; wherein the second gene sequence is used to characterize the common gene sequence of the at least one microorganism; performing a conservation analysis on the at least one second gene sequence to obtain an analysis result; and based on the analysis result, screening out the target gene sequence of the at least one microorganism from the at least one second gene sequence.

[0015] In some embodiments, screening out the target gene sequence of at least one microorganism from the at least one second gene sequence based on the analysis result includes: determining the candidate gene sequence segment of each second gene sequence in the at least one second gene sequence based on the analysis result; inputting the candidate gene sequence segment of each second gene sequence into a pre-trained neural network model to obtain the proportion of different categories of amino acids in the candidate gene sequence segment of each second gene sequence; and screening out the target gene sequence segment of at least one microorganism from the candidate gene sequence segments based on the proportion of different categories of amino acids in the candidate gene sequence segment of each second gene sequence.

[0016] In some embodiments, the preparation of the gene probe corresponding to the target disease based on the target gene sequence of the at least one microorganism includes: preparing a plurality of first gene probes using the target gene sequence as a template; screening the plurality of first gene probes to obtain at least one second gene probe; and determining the at least one second gene probe as the gene probe corresponding to the target disease.

[0017] In some embodiments, the method also includes: determining the target target sequence corresponding to the target disease; correspondingly, screening the multiple first gene probes to obtain at least one second gene probe includes at least one of the following: determining the degree of binding free energy between each first gene probe in the multiple first gene probes and the target target sequence; based on the degree of binding free energy, determining at least one second gene probe from the multiple first gene probes; determining the secondary structure of each first gene probe in the multiple first gene probes; based on the secondary structure of each first gene probe, determining at least one second gene probe from the multiple first gene probes; determining the root mean square deviation between each first gene probe in the multiple first gene probes and the target gene probe; determining the degree of molecular structure change of each first gene probe based on the root mean square deviation; based on the degree of molecular structure change of each first gene probe, determining at least one second gene probe from the multiple first gene probes.

[0018] In a second aspect, an embodiment of the present application provides a device for preparing a gene probe, the device comprising:

[0019] a determination unit, used to determine at least one microorganism corresponding to the target disease;

[0020] an analysis unit, configured to analyze the gene sequence of the at least one microorganism to determine a target gene sequence of the at least one microorganism;

[0021] A preparation unit is used to prepare a gene probe corresponding to the target disease based on the target gene sequence of the at least one microorganism.

[0022] In a third aspect, an embodiment of the present application provides a gene probe, which is prepared by the above method.

[0023] In a fourth aspect, an embodiment of the present application provides a kit comprising the above-mentioned gene probe.

[0024] The embodiments of the present application provide a method and device for preparing a gene probe, a probe and a kit, which determine at least one microorganism corresponding to a target disease; analyze the gene sequence of the at least one microorganism to determine the target gene sequence of the at least one microorganism; and prepare a gene probe corresponding to the target disease based on the target gene sequence of the at least one microorganism. In this way, a gene probe can be prepared for a specific gene part of a pathogenic microorganism, so that after a specific binding experiment is performed, the designed probe specifically binds to the target target sequence to form a double chain. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] Figure 1The following is a schematic diagram of the implementation process of the method for preparing the gene probe of the present application example. Figure 1 ;

[0026] Figure 2 The following is a schematic diagram of the implementation process of the method for preparing the gene probe of the present application example. Figure 2 ;

[0027] Figure 3 The following is a schematic diagram of the implementation process of the method for preparing the gene probe of the present application example. Figure 3 ;

[0028] Figure 4 A flowchart of the method for designing a COPD pathogenic microorganism-specific probe according to an embodiment of the present application;

[0029] Figure 5 This is a schematic diagram of the structure of the gene probe preparation device of the present application embodiment;

[0030] Figure 6 A hardware entity schematic diagram of an electronic device according to an embodiment of the present application. DETAILED DESCRIPTION

[0031] The technical solution of the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all of the embodiments. Based on the embodiments of the present application, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present application.

[0032] In the following description, reference is made to “some embodiments”, which describe a subset of all possible embodiments, but it will be understood that “some embodiments” may be the same subset or different subsets of all possible embodiments and may be combined with each other without conflict.

[0033] In the subsequent description, the suffixes such as "module", "component" or "unit" used to represent elements are only used to facilitate the description of the present application, and have no specific meanings. Therefore, "module", "component" or "unit" can be used in a mixed manner.

[0034] It should be pointed out that the terms "first\second\third" involved in the embodiments of the present application are merely used to distinguish similar objects and do not represent a specific ordering of the objects. It can be understood that "first\second\third" can be interchanged in a specific order or sequence where permitted, so that the embodiments of the present application described here can be implemented in an order other than that illustrated or described here.

[0035] Based on this, an embodiment of the present application provides a method for preparing a gene probe, and the functions implemented by the method can be implemented by calling a program code by a processor in an electronic device. Of course, the program code can be stored in a storage medium of the electronic device. Figure 1 The following is a schematic diagram of the implementation process of the method for preparing the gene probe of the present application example. Figure 1 ,like Figure 1 As shown, the method includes:

[0036] Step S101, determining at least one microorganism corresponding to the target disease;

[0037] Here, the electronic device may be various types of devices with information processing capabilities, such as biological instruments, navigators, smart phones, tablet computers, wearable devices, laptop computers, servers or server clusters, etc.

[0038] In the examples of the present application, the target disease may be any disease, such as COPD (Chronic Obstructive Pulmonary Disease). That is, the types of target diseases are not limited in the examples of the present application, as long as a gene probe for the disease can be prepared by the method in the examples of the present application.

[0039] For example, assuming that the target disease can be chronic obstructive pulmonary disease, we can cooperate with clinical experts to obtain sputum collection from patients with clear clinical diagnosis at the early stage of the disease, extract DNA (DeoxyriboNucleic Acid, deoxyribonucleic acid), remove human DNA, retain microbial DNA, and obtain metagenomic DNA. Then, use FastQC, BWA, Kraken2 and other software to perform bioinformatics analysis on the metagenomic DNA, and obtain "species" and "strain" information by comparing with the microbial genome reference sequence of NCBI (National Center for Biotechnology Information, a scientific research information database), and then organize the classification data of microorganisms, and analyze the relative abundance of each microbial species. Further, by comparing different microbial genome sequences, remove the sequences of normal human respiratory microorganisms, and obtain metagenomic sequences related to the onset of chronic obstructive pulmonary disease. Finally, obtain original microbial sequencing data of chronic obstructive pulmonary disease patients that cause disease attacks.

[0040] More precisely, we can search and read relevant literature for more extensive analysis and confirmation. We can download and analyze the metagenomic data of COPD in the GEO database of NCBI to obtain more microbial data of COPD. Combining our own clinical data analysis, as well as information from public data and literature reports, we obtained the pathogenic microorganisms most related to the early onset of COPD through meta-analysis. These pathogenic microorganisms are Candida albicans, Streptococcus pneumoniae, and Klebsiella pneumoniae. These three pathogenic microorganisms are the three microorganisms corresponding to the target disease COPD.

[0041] Step S102, analyzing the gene sequence of the at least one microorganism to determine the target gene sequence of the at least one microorganism;

[0042] Here, a conservative and specific gene sequence can be determined through multiple alignment, literature analysis, etc., and the conservative and specific gene sequence is the target gene sequence.

[0043] In the embodiment of the present application, the gene sequence of the at least one microorganism can be analyzed to determine a specific sequence (i.e., a target gene sequence) that is evolutionarily conservative, functionally critical, and effective at the "species" level and can be distinguished from other pathogenic microorganisms. At the same time, the specific sequence also has good advantages in terms of overall affinity and stability for bases formed by complementary pairing of DNA bases, and the specific sequence can effectively avoid the formation of secondary structures such as "hairpin" structures by the probe sequence itself.

[0044] Step S103: preparing a gene probe corresponding to the target disease based on the target gene sequence of the at least one microorganism.

[0045] For example, the software primer5.0 can be used to prepare its specific probe using the determined target gene sequence as a template. During preparation, the probe length can be set to about 25bp (base pairs), the GC (base G and C, i.e., guanine and cytosine) content can be set to 30%-80%, and the Tm (melting temperature) value can be set to 68-70°C (degrees Celsius). At the same time, the dimer structure is evaluated, and then the primer probe hairpin structure is evaluated. Then, the specificity of the gene probe is analyzed using Blast (Basic Local Alignment Search Tool, a biomacromolecule sequence alignment search tool) to determine that the sequence corresponding to this gene probe has the highest alignment with the target gene sequence of at least one microorganism.

[0046] Here, through the gene probe preparation method in the above steps S101 to S103, a gene probe can be prepared for the specific gene part of the pathogenic microorganism, so that after a specific binding experiment, the designed probe specifically binds to the target sequence to form a double strand.

[0047] Based on the above embodiments, the present application further provides a method for preparing a gene probe, which is applied to electronic equipment. Figure 2 The following is a schematic diagram of the implementation process of the method for preparing the gene probe of the present application example. Figure 2 ,like Figure 2 As shown, the method includes:

[0048] Step S201, determining at least one microorganism corresponding to the target disease;

[0049] Here, the target disease may include one pathogenic microorganism, or may include two or more pathogenic microorganisms.

[0050] Step S202, analyzing the gene sequence of the at least one microorganism to obtain a reference sequence;

[0051] In the present application, if it is determined that the target disease corresponds to multiple pathogenic microorganisms, the gene sequences of the multiple pathogenic microorganisms are analyzed to obtain a reference sequence. The reference sequence is an identical sequence that appears in each genome sequence (i.e., a common sequence).

[0052] Step S203, constructing a phylogenetic tree of the at least one microorganism using the reference sequence;

[0053] Here, the phylogenetic tree is also called an evolutionary tree, which is a tree that shows the evolutionary relationship between species that are believed to have a common ancestor. It is a method of classifying kinship branches. In the tree, each node represents the most recent common ancestor of its branches, and the length of the line between the nodes corresponds to the evolutionary distance (such as the estimated evolutionary time).

[0054] In the embodiment of the present application, the full gene sequence of at least one microorganism corresponding to the target disease can be downloaded through NCBI. Because each microorganism has multiple genome sequences corresponding to the same name, all these sequences are downloaded, and the sequence with the most occurrences at each site is selected as a reference to obtain a reference sequence. Based on the downloaded annotation information of each reference sequence, a phylogenetic tree is constructed through sequence features to determine the information of the pathogenic microorganism on the "species" and "strains", as well as the evolutionary relationship between different "strains" of the same microorganism with the sequence.

[0055] For example, pathogenic microorganisms associated with COPD can be selected by the following selection methods: first, based on the microorganisms in clinical data, the scope of selected microorganisms is narrowed; that is, the "species" and "strains" that are consistent with the clinical data are directly determined and the sequence is used as the object of the next probe design; second, the sequence of the "strain" that is consistent with the microorganisms associated with COPD reported in clinical literature and GEO public data is used as the second priority sequence for the next probe design; third, through the construction of a phylogenetic tree, the sequence of the most representative "strain" in evolution is determined as the next probe design; fourth, the "strain" with the richest sequence in the public database is selected as the representative sequence for the next probe design.

[0056] Step S204, determining the target gene sequence of the at least one microorganism based on the phylogenetic tree;

[0057] In the embodiment of the present application, the target gene sequence of at least one pathogenic microorganism can be obtained based on the phylogenetic tree constructed in step S203. That is, the phylogenetic tree is analyzed to screen specific key microorganisms and determine the specific evolutionary conserved sequences of these microorganisms, so as to be accurate to the "species" level.

[0058] Step S205: preparing a gene probe corresponding to the target disease based on the target gene sequence of the at least one microorganism.

[0059] Here, through the method for preparing the gene probe in the above steps S201 to S205, a phylogenetic tree can be constructed for pathogenic microorganisms, and then the gene sequences of specific key microorganisms can be screened, so that probes can be prepared based on the screened gene sequences.

[0060] Based on the above embodiments, the present application further provides a method for preparing a gene probe, which is applied to an electronic device and includes:

[0061] Step S211, determining at least one microorganism corresponding to the target disease;

[0062] Step S212, obtaining multiple genome sequences of a first microorganism in the at least one microorganism;

[0063] For example, there are three microorganisms that cause COPD, namely Candida albicans, Streptococcus pneumoniae and Klebsiella pneumoniae, and multiple genome sequences of the three microorganisms are obtained respectively.

[0064] Step S213, performing statistics on the sequences at the same site in the multiple genome sequences to obtain statistical results;

[0065] Here, because there are multiple genome sequences corresponding to the same name for each microorganism, all these sequences can be downloaded, and the sequences at the same site can be counted to obtain statistical results. Then, based on the statistical results, the sequence with the most occurrences at each site is selected as a reference to obtain a reference sequence. In other words, the reference sequence is a segment of the same sequence that appears in each genome sequence (i.e., a common sequence fragment).

[0066] Step S214: determining a reference sequence corresponding to the first microorganism based on the statistical results;

[0067] Here, for each of the at least one microorganism, the method in step S212 to step S214 may be used to determine its corresponding reference sequence (common sequence fragment).

[0068] Step S215, constructing a phylogenetic tree of the at least one microorganism using the reference sequence;

[0069] Step S216, determining the target gene sequence of the at least one microorganism based on the phylogenetic tree;

[0070] Step S217: preparing a gene probe corresponding to the target disease based on the target gene sequence of the at least one microorganism.

[0071] Based on the above embodiments, the present application further provides a method for preparing a gene probe, which is applied to an electronic device and includes:

[0072] Step S221, determining at least one microorganism corresponding to the target disease;

[0073] Step S222, analyzing the gene sequence of the at least one microorganism to obtain a reference sequence;

[0074] Step S223, constructing a phylogenetic tree of the at least one microorganism using the reference sequence;

[0075] Step S224: determining a plurality of first gene sequences of the at least one microorganism based on the phylogenetic tree; wherein the first gene sequences are used to characterize sequence information of the strain of the at least one microorganism;

[0076] Here, the phylogenetic tree may be analyzed to obtain the sequence information of the “species” and “strain” of the at least one microorganism, ie, the first gene sequence.

[0077] Step S225, performing sequence consistency comparison on the plurality of first gene sequences to obtain a comparison result;

[0078] Step S226, determining the target gene sequence of the at least one microorganism according to the comparison result;

[0079] Here, after obtaining the sequence information of the "species" and "strain" of the at least one microorganism, the sequence information of the "species" and "strain" of the at least one microorganism can be compared for sequence consistency, and based on the comparison results, the target gene sequence of the at least one microorganism corresponding to the target disease can be determined.

[0080] Step S227: preparing a gene probe corresponding to the target disease based on the target gene sequence of the at least one microorganism.

[0081] In some embodiments, the step S224, determining a plurality of first gene sequences of the at least one microorganism based on the phylogenetic tree, comprises:

[0082] Based on the phylogenetic tree, determining first gene sequences corresponding to different strains of the at least one microorganism, respectively, to obtain a plurality of first gene sequences;

[0083] Correspondingly, the step S225 performs sequence consistency comparison on the plurality of first gene sequences to obtain a comparison result, including:

[0084] The first gene sequences corresponding to the different strains of microorganisms are compared for sequence consistency to obtain a comparison result.

[0085] Here, since the same microorganism may have different strains, the embodiment of the present application performs sequence consistency comparison on the first gene sequences corresponding to different strains of microorganisms, so that the designed probe can successfully match all strains of this species.

[0086] Based on the above embodiments, the present application further provides a method for preparing a gene probe, which is applied to an electronic device and includes:

[0087] Step S231, determining at least one microorganism corresponding to the target disease;

[0088] Step S232, analyzing the gene sequence of the at least one microorganism to obtain a reference sequence;

[0089] Step S233, constructing a phylogenetic tree of the at least one microorganism using the reference sequence;

[0090] Step S234: determining a plurality of first gene sequences of the at least one microorganism based on the phylogenetic tree; wherein the first gene sequences are used to characterize sequence information of the strain of the at least one microorganism;

[0091] Step S235, performing sequence consistency comparison on the plurality of first gene sequences to obtain a comparison result;

[0092] Step S236: determining at least one second gene sequence according to the comparison result; wherein the second gene sequence is used to characterize a common gene sequence of the at least one microorganism;

[0093] Here, a plurality of first gene sequences may be compared for sequence consistency to obtain key characteristic information thereof, and the key characteristic information is the second gene sequence.

[0094] For example, multiple sequences of different strains can be compared and analyzed, a global comparison can be constructed and scored, and the consensus sequence with the highest score can be obtained as the candidate probe sequence (i.e., the first gene sequence). Among them, the sequences can be compared with each other, 10 mismatches are allowed in each 1kb sequence, 1 point is given for consistent base comparison, 1 point is given for mismatch penalty, 3 points for insertion and deletion penalty, and multiple sequences (e.g., n) are compared. The total score of the final n sequences after comparison is the sum of the scores of the comparison results. The comparison method with the highest score is the optimal global comparison method, and the consensus sequence obtained by this method is the common sequence of the target disease-related microorganism (i.e., the second gene sequence).

[0095] Step S237, performing conservation analysis on the at least one second gene sequence to obtain an analysis result;

[0096] Step S238, based on the analysis result, screening out the target gene sequence of the at least one microorganism from the at least one second gene sequence;

[0097] For example, after obtaining the common sequence of target disease-related microorganisms, sequence conservation analysis can be performed, such as using a script program to edit, annotate, and analyze multiple sequences. In some embodiments, a conservation analysis module can be used. First, the file output after alignment is imported into the program, and the region with the smallest sequence change is selected by comparing the sequences of different "strains". Then, the ratio of actual bases to randomly expected bases is introduced, and the conservation of the sequence is predicted in combination with its function and the conservation of the protein structure of the coding sequence, and the most conservative region is selected as the conservative structural domain. Then, the target gene sequence is obtained based on the conservative structural domain.

[0098] Here, for each of the at least one microorganism, the method in step S236 to step S238 may be used to determine the corresponding target gene sequence.

[0099] Step S239: preparing a gene probe corresponding to the target disease based on the target gene sequence of the at least one microorganism.

[0100] In some embodiments, the step S238, screening out the target gene sequence of the at least one microorganism from the at least one second gene sequence based on the analysis result, comprises:

[0101] Step S2381, determining a candidate gene sequence segment of each second gene sequence in the at least one second gene sequence based on the analysis result;

[0102] Here, based on the analysis results, the conservation of the sequence can be predicted, and the most conserved region can be selected as the conserved domain, which is the candidate gene sequence segment of the second gene sequence.

[0103] Step S2382, inputting the candidate gene sequence segment of each second gene sequence into a pre-trained neural network model to obtain the proportion of different types of amino acids in the candidate gene sequence segment of each second gene sequence;

[0104] Here, it is necessary to consider that the sequences of different parts of amino acids in pathogenic microorganisms are different, and they also correspond to different secondary structures. Different secondary structures have different types of medication and methods of medication during treatment. Because the purpose of designing probes in the embodiments of this application is to discover pathogenic microorganisms and use medication, it is necessary to select a suitable secondary structure that matches existing drugs. Therefore, the neural network model can be used to obtain the proportion of different types of amino acids in the sequence segment, and then screen them.

[0105] Step S2383: based on the proportion of different types of amino acids in the candidate gene sequence segments of each second gene sequence, screen out the target gene sequence segment of the at least one microorganism from the candidate gene sequence segments.

[0106] Based on the above embodiments, the present application further provides a method for preparing a gene probe, which is applied to electronic equipment. Figure 3 The following is a schematic diagram of the implementation process of the method for preparing the gene probe of the present application example. Figure 3 ,like Figure 3 As shown, the method includes:

[0107] Step S301, determining at least one microorganism corresponding to the target disease;

[0108] Step S302, analyzing the gene sequence of the at least one microorganism to determine the target gene sequence of the at least one microorganism;

[0109] Step S303, using the target gene sequence as a template, preparing a plurality of first gene probes;

[0110] For example, the software Primer 5.0 can be used to design a specific probe using the target gene sequence as a template, and the prepared specific probe is the first gene probe.

[0111] Step S304, screening the plurality of first gene probes to obtain at least one second gene probe;

[0112] In the embodiments of the present application, a variety of methods (for example, thermodynamic methods and molecular dynamics simulations, etc.) can be used to evaluate the optimal length, optimal sequence composition, optimal GC content, optimal end design, etc. of the first gene probe, thereby screening multiple first gene probes and screening out at least one second gene probe.

[0113] Step S305: determine the at least one second gene probe as the gene probe corresponding to the target disease.

[0114] Here, through the probe preparation method in the above steps S301 to S305, a gene probe can be prepared for the specific gene part of the pathogenic microorganism of the target disease, and a specific probe sequence with a specific length can be obtained.

[0115] In some embodiments, the method further comprises: determining a target sequence corresponding to the target disease;

[0116] Correspondingly, the step S304, screening the plurality of first gene probes to obtain at least one second gene probe, includes at least one of the following:

[0117] The first method is to determine the degree of binding free energy between each of the plurality of first gene probes and the target sequence; based on the degree of binding free energy, determine at least one second gene probe from the plurality of first gene probes;

[0118] For example, the free energy of hybridization between the first gene probe and the target sequence is calculated using the thermodynamic integration method and the free energy perturbation method, mainly by calculating the free energy change between the two substrates (probe and target DNA) and then the free energy change between the complex (probe and target DNA). Based on the free energy change, at least one second gene probe is determined from multiple first gene probes.

[0119] The second method is to determine the secondary structure of each of the plurality of first gene probes; and based on the secondary structure of each of the first gene probes, determine at least one second gene probe from the plurality of first gene probes;

[0120] For example, the spatial structure of the first gene probe DNA is used as the initial structure of the molecular dynamics simulation, and then a series of processes are performed to obtain the most stable state of the first gene probe DNA, determine the secondary structure of the first gene probe DNA, exclude probes that form obvious secondary structures such as "hairpins", and obtain the second gene probe. In this way, the possible secondary structures of the sequence composition and its most stable state can be analyzed, and the best probe sequence can be found by excluding the case of obvious "hairpin" secondary structures.

[0121] The third method is to determine the root mean square deviation between each of the multiple first gene probes and the target gene probe; determine the degree of change in the molecular structure of each of the first gene probes based on the root mean square deviation; and determine at least one second gene probe from the multiple first gene probes based on the degree of change in the molecular structure of each of the first gene probes.

[0122] For example, the deviation statistics of the first gene probe conformation and the target conformation are performed, and the simulation result configuration is translated and rotated to make it overlap or partially overlap with the target configuration as much as possible, and then the difference between the coordinates of each atom and the target configuration is calculated. The value is the average square root of the square of the difference, which indicates the degree of change in the molecular structure and then screens out the second gene probe. In this way, the inevitable secondary hairpin structure can be analyzed and the optimal sequence result can be selected.

[0123] Studies have shown that microbial infection is an important cause of the aggravation of chronic obstructive pulmonary disease. Therefore, changes in microorganisms can be used as biomarkers to provide early warnings for clinical treatment. Therefore, based on the aforementioned embodiments, the embodiments of the present application further provide a method for preparing a gene probe, which is a method for designing a specific probe for COPD pathogenic microorganisms, including: designing a detection probe, designing a characteristic conservative sequence for COPD-causing pathogenic microorganisms; analyzing and obtaining specific evolutionary conservative sequences according to the screened COPD-causing pathogenic microorganisms; and then designing a probe sequence of a specific length according to the thermodynamic optimal scheme, and selecting a hybridization probe with similar properties such as annealing temperature. A single-stranded probe is synthesized by DNA synthesis technology as a specific detection probe for COPD disease. The above-mentioned probe is subjected to a specific binding experiment with the dehumanized DNA extracted from the sputum of the patient to be detected. The designed probe is specifically combined with the target target sequence to form a double strand, thereby detecting pathogenic microorganisms.

[0124] In other words, the current detection of COPD is still based on clinician experience, bacterial culture or second-generation sequencing methods. Relying on the experience of clinicians is often subjective, and young doctors lack relevant experience. Relying on bacterial culture usually requires at least a week of bacterial culture time, and many bacteria are difficult to culture, which seriously limits the timeliness of COPD detection and treatment. Although the second-generation sequencing technology represented by metagenomics can detect pathogenic microorganisms, its experimental cost is high and it costs a lot. At the same time, it requires samples to be sent to central laboratories or third-party testing centers, and requires a dedicated team and computing resources for analysis, and it also takes several days to obtain results.

[0125] The embodiment of the present application proposes a method for designing a specific probe for COPD pathogenic microorganisms, including: selection of pathogenic microorganisms, determination of evolutionary conserved sequences, thermodynamic probe design, and molecular dynamics model optimization. This method can achieve early detection of COPD patients. The key lies in how to accurately select the key pathogenic microorganisms of COPD, and how to find specific sequences that are evolutionarily conservative, functionally critical, and effective at the "species" level for the selected pathogenic microorganisms, which can be distinguished from other pathogenic microorganisms. At the same time, the overall affinity and stability of the bases formed by complementary pairing of DNA bases, and the effective avoidance of the formation of secondary structures such as "hairpin" structures by the probe sequence itself. In addition, within the experimental temperature range, a stable double-stranded structure must be formed with the complementary chain of the target microbial DNA. For this purpose, thermodynamic methods and molecular dynamics simulation methods are developed to effectively evaluate the optimal length, optimal sequence composition, optimal GC (Guanylate Cyclase, guanylate cyclase) content, and optimal end design of the probe sequence. Finally, in the design of multiple sets of probes, it is necessary to comprehensively consider the range of conditions for the hybridization reactions of multiple sets of probes, and select the simplest probe combination by "voting" according to the overlap range of the optimal annealing temperature.

[0126] Below, the method for designing a pathogen-specific probe for COPD in the embodiment of the present application is described in detail:

[0127] First, selection of pathogenic microorganisms in the early stage of COPD;

[0128] (1) Through cooperation with clinical experts, we collected sputum from COPD patients with a clear clinical diagnosis at the early stage of the disease, extracted DNA, removed human DNA, retained microbial DNA, and obtained metagenomic DNA. Further metagenomic sequencing was performed. Bioinformatics analysis of the second-generation sequencing data was performed using FastQC, BWA, kraken2 and other software. By comparing with the microbial genome reference sequence of NCBI, the information of "species" and "strain" was obtained. Then, the classification data of microorganisms was sorted, and the relative abundance of each microbial species was analyzed. Further, by comparing the microbial genome sequences of different patients, the sequences of normal human respiratory microorganisms were removed to obtain metagenomic sequences related to the onset of COPD. Finally, we obtained first-hand original microbial sequencing data of COPD patients that caused disease attacks.

[0129] (2) Conduct a more extensive analysis and confirmation of COPD by searching and reading relevant literature on PubMed. Download and analyze the metagenomic data of COPD in the GEO database of NCBI to obtain more COPD microbial data. Combined with the analysis of our own clinical data, public data, and information reported in the literature, through meta-analysis, we obtained the pathogenic microorganisms most related to the early onset of COPD, namely Candida Albicans (Candida albicans), Streptococcus Pneumoniae (Streptococcus pneumoniae), and Klebsiella Pneumonia (Klebsiella pneumoniae).

[0130] Second, determine the key characteristic sequences of microorganisms;

[0131] (1) Download the complete gene sequences of the three microorganisms through NCBI. Because there are multiple genome sequences corresponding to the same name for each microorganism, all these sequences are downloaded. Select the sequence with the most occurrences at each site as a reference to obtain a reference sequence. According to the downloaded annotation information of each sequence, a phylogenetic tree is constructed by sequence characteristics. By constructing a phylogenetic tree, the information of the microorganism in "species" and "strains" and the evolutionary relationship between different "strains" of the same microorganism with the sequence can be determined. The embodiment of the present application selects pathogenic microorganisms related to COPD through the following selection method: First, the scope of selected microorganisms is narrowed down through the microorganisms in its own clinical data. If the "species" and "strains" are consistent with the first-hand data, the sequence is directly determined and used as the object of the next probe design; secondly, the sequence of the "strain" consistent with the microorganisms related to COPD reported in clinical literature and GEO public data is used as the second preferred sequence for the next probe design; thirdly, through the construction of a phylogenetic tree, the most representative "strain" sequence in evolution is determined as the next probe design; fourthly, the "strain" with the most abundant sequence in the public database is selected as the representative sequence for the next probe design.

[0132] (2) The sequence information of the "species" and "strains" of COPD-related microorganisms obtained in the previous step is further analyzed to obtain its key characteristic information. The specific steps are as follows: Through the written program, multiple sequence alignment analyses are performed, a global alignment is constructed, and scoring is performed to obtain the highest-scoring consensus sequence as the probe candidate sequence. The sequences can be aligned with each other, allowing 10 mismatches in each 1kb sequence, 1 point for consistent base alignment, 1 point for mismatch penalty, 3 points for insertion and deletion penalty, and multiple sequences (for example, n sequences). The final total score after alignment of the n sequences is the sum of the scores of the alignment results. The alignment method with the highest score is the optimal global alignment method. The consensus sequence obtained by this method is the common sequence of the COPD-related microorganism, and the alignment result is output in the fasta format file.

[0133] (3) After obtaining the common sequence of the COPD-related microorganisms, further sequence conservation analysis is performed, and the script program is used to edit, annotate, and analyze multiple sequences. The embodiment of the present application uses a conservation analysis module, firstly imports the fasta file output after alignment into the program, compares the sequences of different "strains", selects the region with the smallest sequence change, introduces the ratio of actual bases to randomly expected bases, combines its function and the conservation of the protein structure of the coding sequence, predicts the conservation of its sequence, and selects the most conserved region as the conserved domain.

[0134] (4) For the candidate protein coding sequence regions, machine learning technology was applied to secondary structure prediction. Two feed-forward neural networks were combined to analyze the output obtained from PSI-BLAST (position-specific iterative-BLAST) and divide the amino acids in the sequence into four groups: hydrophobic, polar, small non-polar, and aromatic compounds.

[0135] (5) Furthermore, when selecting probe sequences, the genome sequences of other microorganisms unrelated to COPD obtained by clinical metagenomic sequencing are compared, and these sequences are compared with the candidate sequences to ensure that the overall sequence difference between the candidate sequences and these sequences unrelated to COPD is greater than 50%. This facilitates the subsequent discovery of target microorganisms and the distinction of unrelated microorganisms in hybridization sequencing.

[0136] Third, prepare gene probes;

[0137] (1) Use the software primer5.0 to design a specific probe using this specific sequence as a template. When designing, pay attention to the probe length, which should be around 25 bp, the GC content should be 30%-80%, and the Tm value should be 68-70°C. At the same time, evaluate the dimer structure, then evaluate the primer probe hairpin structure, and then use Blast to analyze the specificity to determine that this selected sequence has the highest alignment with the target microbial sequence.

[0138] (2) Molecular dynamics simulation optimization scheme;

[0139] The spatial structure of the probe DNA is used as the initial structure of the molecular dynamics simulation. First, the prepared initial structure is placed in the force field, and then the SPC (simple point charge) water model is used to simulate the hybridization environment. The distance between the initial structure and the set boundary box is set to 10A in each dimension. Then, the local high energy is optimized, atomic collisions are removed, and the system energy is minimized. Subsequently, the NPT system is used to keep the temperature, pressure and number of atoms unchanged. The Nose-Hoover constant temperature calculation method is used to adjust the temperature of the equilibrium system to 300K, the pressure is set to 1atm, and a 50ns molecular dynamics simulation is performed. A snapshot of the trajectory is saved every 40ps, and 1250 frames are collected. The most stable state of the probe DNA is obtained to determine the secondary structure of the DNA probe. Probes that form obvious secondary structures such as "hairpins" are excluded to ensure that the probe itself does not form a complex secondary structure.

[0140] (3) RMSD (root-mean-square deviation) analysis;

[0141] Root mean square deviation analysis is the deviation statistics of the resulting DNA probe conformation and the target conformation. RMSD calculation is mainly performed by translating and rotating the simulation result configuration so that it overlaps or partially overlaps with the target configuration (generally the initial structure) as much as possible, and then calculating the difference between the coordinates of each atom and the target configuration, and its value is the average square root of the square of the difference. RMSD is the sum of all atomic deviations between the conformation and the target conformation calculated at a certain moment. Each frame has an RMSD, so it is an important basis for measuring whether the system is stable. The calculation of RMSD is based on the molecular dynamics simulation trajectory and is calculated by the Desmond module. It is the deviation statistics of the conformation generated during the dynamics simulation process and the target conformation, which is used to indicate the degree of change in the molecular structure. In the embodiment of the present application, the first frame is set as the reference structure to calculate the RMSD of the protein backbone, and the calculation formula is as follows:

[0142]

[0143] Where i is the total number of atoms analyzed, m i is the mass of the ith atom, X i and Y i represents the coordinate vector of the target atom i in the same coordinate system as the coordinate vector of atom i in the reference structure, and M is the total mass.

[0144] (4) Calculation of binding free energy of hybridization between probe DNA and target DNA;

[0145] Using the LIE method and the calculation method based on the empirical equation, the embodiment of the present application uses the thermodynamic integration method and the free energy perturbation method to calculate the free energy calculation method of the hybridization of the designed probe and the target DNA. Mainly through two calculations, the free energy change between the two substrates (probe and target DNA) is first calculated, and then the free energy change between the complex (probe and target DNA) is calculated. The LIE method and the MM / PBSA method are free energy prediction methods based on molecular dynamics sampling. The theoretical basis of linear interaction energy (Linear Interaction Energy, LIE) comes from the linear response approximation (Linear Response Approximation) theory in non-equilibrium statistical physics, which decomposes the free energy into polar and non-polar contributions. The embodiment of the present application adopts kinetic sampling to decompose the energy into electrostatic interaction energy, solvation energy, van der Waals interaction energy and entropy change caused by conformational changes in a vacuum state, and analyzes the molecular dynamics trajectory by using Prime MM-GBSA to predict the binding free energy (△G) between the hybrid double strands of the probe DNA and the target DNA based on molecular dynamics. bind). The method used in the embodiment of the present application mainly utilizes the MM-PBSA / GBSA method. The formula for calculating the binding free energy of MM / GBSA is as follows:

[0146] △G bind =G complex -G protein -G ligand

[0147] Among them, △G bind is the binding free energy, G complex , G protein , G ligand are the free energies of complex K, probe DNA and target DNA respectively. MM +△G GB +△G nonpolar -T △S The equation used to estimate the energy, ∆E MM is the gas phase interaction energy between the probe DNA and the target DNA, expressed as △G GB and △G nonpolar The polar and nonpolar components of the desolvation free energy, T △S is the change in conformational entropy upon ligand binding.

[0148] Use the program to calculate MM / GBSA:

[0149] $SCHRODINGER / run thermal_MM / GBSA.py-j xxx-step_size 125yyy-out.cms;

[0150] Where xxx is the name of the output file, yyy-out.cms is the name of the input file (the result of molecular dynamics), and -step_size 125 means that samples are collected every 125 frames.

[0151] The optimal probe sequence that can bind to the target DNA is obtained through calculation.

[0152] Fourth, experimental results;

[0153] Based on the three microorganisms of patients with chronic obstructive pulmonary disease, a total of 7 specific genes (as shown in Table 1) were selected in this embodiment of the application. Specific probes were designed using this specific sequence as a template using primer5.0, and reverse Blast was performed to exclude specific genes psA, ply, Spn9802, and Spn9828, and finally the probes were determined (as shown in Table 2).

[0154] microorganism Specific gene Streptococcus Pneumoniae psA, lytA, ply, Spn9802, Spn9828 Candida Albicans ITS2 Klebsiella Pneumoniae CelB

[0155] Table 1 Specific gene information of three microorganisms related to COPD

[0156]

[0157]

[0158] Table 2 Determination of specific probes for some microorganisms

[0159] Figure 4 The flowchart of the method for designing a COPD pathogen-specific probe in the embodiment of the present application is as follows: Figure 4 As shown, the method includes:

[0160] Step S401, screening microorganisms;

[0161] Here, microorganism screening is mainly carried out through clinical experience, own clinical data, microbial evolution, conservative genome analysis, etc.

[0162] Step S402, searching for specific genes;

[0163] Here, conserved and specific sequences are determined through multiple alignments, literature analysis, etc.

[0164] Step S403: designing a probe.

[0165] Here, probes were designed and their specificity was tested by various methods.

[0166] That is, the embodiments of the present application propose the following main contents:

[0167] ①, Probe design, the present application embodiment develops a set of detection probe design methods for early-stage COPD patients. The method is based on clinical experience, own clinical data, microbial evolution, conservative and characteristic genome sequence selection, phylogenetic tree analysis, screening specific key microorganisms, and determining the specific evolutionary conservative sequences of these microorganisms, accurate to the "species" level.

[0168] ② Use the software primer5.0 to design specific probes using the microorganism-specific sequence as a template, and then use Blast to analyze the specificity to determine that this selected sequence has the highest degree of alignment with the target microorganism sequence.

[0169] ③. Use thermodynamic methods, molecular dynamics simulation and other methods to calculate the optimal probe sequence that can bind to the target DNA.

[0170] ④. The present application example provides for the first time a specific probe sequence for early detection of COPD. Three microorganisms are Candida Albicans (Albicans), Streptococcus Pneumoniae (Streptococcus pneumoniae) and Klebsiella Pneumoniae (Klebsiella pneumoniae). A total of 3 specific genes are selected, namely Streptococcus Pneunoniae (lytA), Candida Albicans (ITS2), Klebsiella Pneumoniae (CelB), a total of 15 sequences, and the detailed information of the sequences is shown in Table 2.

[0171] Thus, the technical solution in the embodiment of the present application has the following advantages:

[0172] ① First, obtain pathogenic microorganisms related to COPD through own clinical data, literature meta-analysis, and public data.

[0173] ②. Use microbial evolution, conservation and characteristic genome sequence selection and phylogenetic tree analysis to screen specific key microorganisms and design probes based on the specific evolutionary conserved sequences of these microorganisms.

[0174] ③. Then, through methods and steps such as molecular dynamics simulation, specificity is obtained, and the optimal solution is used to design a probe sequence of a specific length, and hybridization probes with similar properties such as annealing temperature are selected.

[0175] Furthermore, the technical solutions in the embodiments of the present application can be applied to the following scenarios:

[0176] Gene sequencing is the gateway to precision medicine and a powerful tool for public health. Compared with traditional bacterial culture methods, metagenomic technology has significant advantages in the detection of pathogenic microorganisms, such as fast speed and high accuracy, and has been increasingly widely used in clinical testing. The method described in this scheme is used to detect pathogenic microorganisms in patients with respiratory diseases and has good clinical application prospects. In particular, the three pathogenic microorganisms described in this scheme are common pathogenic microorganisms of a variety of respiratory diseases. The specific probe sequences of these three pathogenic microorganisms are crucial for disease discovery and treatment and have great commercial value.

[0177] Therefore, a project can be developed, the core goal of which is to combine the latest research progress in biotechnology and information technology, create a 5G-enabled third-generation solid-state nanopore agile online gene sequencing process and solution, and verify the research results with the detection of chronic obstructive pulmonary disease (COPD) pathogens as the application scenario. At present, solid-state nanopore sequencing has challenges such as low signal-to-noise ratio and too fast speed when biological molecules pass through, making direct sequencing difficult. The industry generally adopts a target pathogen detection method based on hybridization sequencing, and the core of this method is to design a specific probe sequence for a specific target pathogen, synthesize the probe and perform a hybridization reaction, that is, to form a double-stranded DNA corresponding to the pathogen, and collect a higher signal-to-noise ratio signal through the nanopore for analysis. Therefore, the specific probe design method and the corresponding design results proposed in the scheme in the embodiment of this application can be used as the main input for the next step of detection.

[0178] Based on the above embodiments, the present application provides a gene probe, which is prepared by the above gene probe preparation method, so that the gene probe can be used to accurately detect specific pathogenic microorganisms.

[0179] Based on the above embodiments, the present application provides a kit, which comprises the gene probe prepared as above, so that the kit can be used to accurately detect specific pathogenic microorganisms.

[0180] In some embodiments, the kit may further comprise primers for amplifying a base sequence having a region that hybridizes with the gene probe.

[0181] Based on the foregoing embodiments, the embodiments of the present application provide a device for preparing a gene probe, which includes the various units included, the various modules included in the units, and the various components included in the modules, which can be implemented by a processor in an electronic device; of course, it can also be implemented by a specific logic circuit; in the implementation process, the processor can be a CPU (Central Processing Unit), an MPU (Microprocessor Unit), a DSP (Digital Signal Processing) or an FPGA (Field Programmable Gate Array), etc.

[0182] Figure 5 FIG. 1 is a schematic diagram of the composition structure of the gene probe preparation device of the present application embodiment. Figure 5 As shown, the device 500 includes:

[0183] A determination unit 501 is used to determine at least one microorganism corresponding to a target disease;

[0184] An analysis unit 502 is used to analyze the gene sequence of the at least one microorganism to determine the target gene sequence of the at least one microorganism;

[0185] The preparation unit 503 is used to prepare a gene probe corresponding to the target disease based on the target gene sequence of the at least one microorganism.

[0186] In some embodiments, the analysis unit 502 includes:

[0187] An analysis module, used to analyze the gene sequence of the at least one microorganism to obtain a reference sequence;

[0188] A construction module for constructing a phylogenetic tree of the at least one microorganism using the reference sequence;

[0189] A determination module is used to determine the target gene sequence of the at least one microorganism based on the phylogenetic tree.

[0190] In some embodiments, the analysis module comprises:

[0191] an analysis submodule, for obtaining a plurality of genome sequences of a first microorganism among the at least one microorganism;

[0192] The analysis submodule is further used to perform statistics on the sequences at the same site in the multiple genome sequences to obtain statistical results;

[0193] The analysis submodule is further used to determine a reference sequence corresponding to the first microorganism based on the statistical results.

[0194] In some embodiments, the determining module includes:

[0195] A first determining component is used to determine a plurality of first gene sequences of the at least one microorganism based on the phylogenetic tree; wherein the first gene sequences are used to characterize sequence information of the strain of the at least one microorganism;

[0196] A comparison component, used for comparing the sequence consistency of the plurality of first gene sequences to obtain a comparison result;

[0197] The second determining component is used to determine the target gene sequence of the at least one microorganism according to the comparison result.

[0198] In some embodiments, the first determining component includes:

[0199] A first determination subcomponent is used to determine first gene sequences corresponding to different strains of microorganisms in the at least one microorganism based on the phylogenetic tree to obtain a plurality of first gene sequences;

[0200] Correspondingly, the comparison component includes:

[0201] The comparison subcomponent is used to compare the first gene sequences corresponding to the different strains of microorganisms for sequence consistency to obtain a comparison result.

[0202] In some embodiments, the second determining component includes:

[0203] A second determination subcomponent is used to determine at least one second gene sequence according to the comparison result; wherein the second gene sequence is used to characterize a common gene sequence of the at least one microorganism;

[0204] The second determining subcomponent is further used to perform conservation analysis on the at least one second gene sequence to obtain an analysis result;

[0205] The second determination subcomponent is further used to screen out the target gene sequence of the at least one microorganism from the at least one second gene sequence based on the analysis result.

[0206] In some embodiments, the second determining subcomponent includes:

[0207] a segment determination subcomponent, configured to determine a candidate gene sequence segment of each second gene sequence in the at least one second gene sequence based on the analysis result;

[0208] An input subcomponent, used to input the candidate gene sequence segment of each second gene sequence into a pre-trained neural network model to obtain the proportion of different categories of amino acids in the candidate gene sequence segment of each second gene sequence;

[0209] The screening subcomponent is used to screen out the target gene sequence segment of the at least one microorganism from the candidate gene sequence segments based on the proportion of different types of amino acids in the candidate gene sequence segments of each second gene sequence.

[0210] In some embodiments, the preparation unit 503 includes:

[0211] A preparation module, used to prepare a plurality of first gene probes using the target gene sequence as a template;

[0212] A screening module, used for screening the plurality of first gene probes to obtain at least one second gene probe;

[0213] The preparation module is further used to determine the at least one second gene probe as the gene probe corresponding to the target disease.

[0214] In some embodiments, the apparatus further comprises:

[0215] A target sequence determination unit, used to determine a target sequence corresponding to the target disease;

[0216] Correspondingly, the screening module includes at least one of the following:

[0217] A first screening submodule is used to determine the degree of binding free energy between each of the plurality of first gene probes and the target sequence; based on the degree of binding free energy, determine at least one second gene probe from the plurality of first gene probes;

[0218] A second screening submodule is used to determine the secondary structure of each of the plurality of first gene probes; based on the secondary structure of each of the first gene probes, determine at least one second gene probe from the plurality of first gene probes;

[0219] The third screening submodule is used to determine the root mean square deviation between each first gene probe in the multiple first gene probes and the target gene probe; determine the degree of molecular structure change of each first gene probe based on the root mean square deviation; and determine at least one second gene probe from the multiple first gene probes based on the degree of molecular structure change of each first gene probe.

[0220] The description of the above device embodiment is similar to the description of the above method embodiment, and has similar beneficial effects as the method embodiment. For technical details not disclosed in the device embodiment of the present application, please refer to the description of the method embodiment of the present application for understanding.

[0221] It should be noted that, in the embodiment of the present application, if the preparation method of the above-mentioned gene probe is implemented in the form of a software function module, and when it is sold or used as an independent product, it can also be stored in a computer-readable storage medium. Based on such an understanding, the technical solution of the embodiment of the present application is essentially or the part that contributes to the prior art can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including several instructions to enable an electronic device (which can be a personal computer, server, etc.) to execute all or part of the method described in each embodiment of the present application. And the aforementioned storage medium includes: various media that can store program codes such as U disk, mobile hard disk, ROM (Read Only Memory, read-only memory), magnetic disk or optical disk. In this way, the embodiment of the present application is not limited to any specific hardware and software combination.

[0222] Correspondingly, an embodiment of the present application provides an electronic device, including a memory and a processor, wherein the memory stores a computer program that can be run on the processor, and when the processor executes the program, the steps in the method for preparing a gene probe provided in the above embodiment are implemented.

[0223] Correspondingly, an embodiment of the present application provides a readable storage medium on which a computer program is stored. When the computer program is executed by a processor, the steps in the above-mentioned method for preparing a gene probe are implemented.

[0224] It should be noted here that the description of the above storage medium and device embodiments is similar to the description of the above method embodiments, and has similar beneficial effects as the method embodiments. For technical details not disclosed in the storage medium and device embodiments of this application, please refer to the description of the method embodiments of this application for understanding.

[0225] It should be noted that Figure 6 A hardware entity diagram of an electronic device according to an embodiment of the present application is shown in FIG. Figure 6 As shown, the hardware entity of the electronic device 600 includes: a processor 601, a communication interface 602 and a memory 603, wherein

[0226] The processor 601 generally controls the overall operation of the electronic device 600 .

[0227] The communication interface 602 may enable the electronic device 600 to communicate with other devices, servers, or platforms through a network.

[0228] The memory 603 is configured to store instructions and applications executable by the processor 601, and can also cache data to be processed or processed by the processor 601 and various modules in the electronic device 600 (for example, image data, audio data, voice communication data, and video communication data), which can be implemented through FLASH (flash memory) or RAM (Random Access Memory).

[0229] In the several embodiments provided in the present application, it should be understood that the disclosed devices and methods can be implemented in other ways. The device embodiments described above are only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation, such as: multiple units or components can be combined, or can be integrated into another system, or some features can be ignored or not executed. In addition, the coupling, direct coupling, or communication connection between the components shown or discussed can be through some interfaces, and the indirect coupling or communication connection of the devices or units can be electrical, mechanical or other forms.

[0230] The units described above 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 distributed on multiple network units; some or all of the units may be selected according to actual needs to achieve the purpose of the present embodiment.

[0231] In addition, all functional units in the embodiments of the present application can be integrated into one processing module, or each unit can be a separate unit, or two or more units can be integrated into one unit; the above integrated unit can be implemented in the form of hardware or in the form of hardware plus software functional units. A person of ordinary skill in the art can understand that all or part of the steps of implementing the above method embodiments can be completed by hardware related to program instructions, and the aforementioned program can be stored in a computer-readable storage medium, which, when executed, executes the steps of the above method embodiments; and the aforementioned storage medium includes: various media that can store program codes, such as mobile storage devices, ROM, RAM, disks or optical disks.

[0232] The methods disclosed in several method embodiments provided in this application can be arbitrarily combined without conflict to obtain new method embodiments.

[0233] The features disclosed in several product embodiments provided in this application can be arbitrarily combined without conflict to obtain new product embodiments.

[0234] The features disclosed in several method or device embodiments provided in this application can be arbitrarily combined without conflict to obtain new method embodiments or device embodiments.

[0235] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

Claims

1. A method for preparing a gene probe, characterized in that: The method comprises: Identify at least one microorganism corresponding to the target disease; Analyzing the gene sequence of the at least one microorganism to determine the target gene sequence of the at least one microorganism; Based on the target gene sequence of the at least one microorganism, a gene probe corresponding to the target disease is prepared.

2. The method according to claim 1, characterized in that The step of analyzing the gene sequence of the at least one microorganism to determine the target gene sequence of the at least one microorganism comprises: Analyzing the gene sequence of the at least one microorganism to obtain a reference sequence; constructing a phylogenetic tree of the at least one microorganism using the reference sequence; Based on the phylogenetic tree, a target gene sequence of the at least one microorganism is determined.

3. The method according to claim 2, characterized in that The step of analyzing the gene sequence of the at least one microorganism to obtain a reference sequence comprises: obtaining a plurality of genome sequences of a first microorganism among the at least one microorganism; Performing statistics on sequences at the same site in the multiple genome sequences to obtain statistical results; Based on the statistical results, a reference sequence corresponding to the first microorganism is determined.

4. The method according to claim 2, characterized in that: Determining the target gene sequence of at least one microorganism based on the phylogenetic tree comprises: Based on the phylogenetic tree, determining a plurality of first gene sequences of the at least one microorganism; wherein the first gene sequences are used to characterize sequence information of the strain of the at least one microorganism; Performing sequence consistency comparison on the multiple first gene sequences to obtain a comparison result; According to the comparison result, the target gene sequence of the at least one microorganism is determined.

5. The method according to claim 4, characterized in that Determining a plurality of first gene sequences of the at least one microorganism based on the phylogenetic tree comprises: Based on the phylogenetic tree, determining first gene sequences corresponding to different strains of the at least one microorganism, respectively, to obtain a plurality of first gene sequences; Correspondingly, performing sequence consistency comparison on the plurality of first gene sequences to obtain a comparison result includes: The first gene sequences corresponding to the different strains of microorganisms are compared for sequence consistency to obtain a comparison result.

6. The method according to claim 5, characterized in that Determining the target gene sequence of the at least one microorganism according to the comparison result comprises: Determine at least one second gene sequence according to the comparison result; wherein the second gene sequence is used to characterize the common gene sequence of the at least one microorganism; Performing a conservation analysis on the at least one second gene sequence to obtain an analysis result; Based on the analysis result, the target gene sequence of the at least one microorganism is screened out from the at least one second gene sequence.

7. The method according to claim 6, characterized in that The step of screening out the target gene sequence of the at least one microorganism from the at least one second gene sequence based on the analysis result comprises: Based on the analysis result, determining a candidate gene sequence segment of each second gene sequence in the at least one second gene sequence; Inputting the candidate gene sequence segment of each second gene sequence into a pre-trained neural network model to obtain the proportion of different types of amino acids in the candidate gene sequence segment of each second gene sequence; Based on the proportions of different types of amino acids in the candidate gene sequence segments of each second gene sequence, the target gene sequence segment of the at least one microorganism is screened out from the candidate gene sequence segments.

8. The method according to any one of claims 1 to 7, characterized in that: The method of preparing a gene probe corresponding to the target disease based on the target gene sequence of the at least one microorganism comprises: Using the target gene sequence as a template, preparing a plurality of first gene probes; Screening the plurality of first gene probes to obtain at least one second gene probe; The at least one second gene probe is determined as a gene probe corresponding to the target disease.

9. The method according to claim 8, characterized in that The method further comprises: Determining the target sequence corresponding to the target disease; Correspondingly, the screening of the plurality of first gene probes to obtain at least one second gene probe includes at least one of the following: Determine the degree of binding free energy between each of the plurality of first gene probes and the target sequence; determine at least one second gene probe from the plurality of first gene probes based on the degree of binding free energy; or Determine the secondary structure of each of the plurality of first gene probes; and determine at least one second gene probe from the plurality of first gene probes based on the secondary structure of each of the first gene probes; or Determine the root mean square deviation between each first gene probe and the target gene probe in the plurality of first gene probes; and determine the degree of molecular structure change of each first gene probe based on the root mean square deviation; and determine at least one second gene probe from the plurality of first gene probes based on the degree of molecular structure change of each first gene probe.

10. A gene probe preparation device, characterized in that: The device comprises: a determination unit, used to determine at least one microorganism corresponding to the target disease; an analysis unit, configured to analyze the gene sequence of the at least one microorganism to determine a target gene sequence of the at least one microorganism; A preparation unit is used to prepare a gene probe corresponding to the target disease based on the target gene sequence of the at least one microorganism.

11. A gene probe, characterized in that: The gene probe is prepared by the method according to any one of claims 1 to 9.

12. A kit, characterized in that: Comprising the gene probe according to claim 11.

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