JP6327473B2 - Method for identifying Mycobacterium tuberculosis strain and method for detecting gene mutation - Google Patents

Description

  The present invention relates to identification of Mycobacterium tuberculosis strains, identification / detection methods for gene mutations in Mycobacterium tuberculosis genome, and methods for producing consensus genome information of Mycobacterium tuberculosis used in these methods.

Tuberculosis is the infectious disease with the highest number of deaths per year in a single infection. The WHO estimates that about 10 million people are infected with tuberculosis annually and 2.5 million people die from the disease. In addition, the situation is getting worse, such as the emergence of multi-drug resistant tuberculosis strains of Mycobacterium tuberculosis. In the control of tuberculosis, rapid patient diagnosis and identification of the source of infection are important. M. tuberculosis strain typing has proven to be very useful for explosive epidemic research,
It is applied to solve various epidemiological problems.

  Currently, detection and identification of Mycobacterium tuberculosis is performed by culturing a sample collected from a patient and using the obtained culture, using VNTR, sporigotyping, or IS6110-RFLP. VNTR counts the number of repeats of each of a plurality of repeat regions present separately in the gene of Mycobacterium tuberculosis, and compares the number of each region to identify a strain.

  Sporigotyping analyzes a region containing a spacer sequence sandwiched between 36 bp direct repeats that are specifically present in the Mycobacterium tuberculosis genome. The number of spacer sequences varies from strain to strain (up to about 50) depending on the strain. After amplification of the same region by the PCR method, hybridization is performed using the spacer sequence. As a result, for example, a certain strain has spacers 1, 2, 3, and 5, and another strain has spacers 2 and 4.

  IS6110-RFLP detects a portion having approximately the same sequence present in about 10 at most in the Mycobacterium tuberculosis genome. After cutting the Mycobacterium tuberculosis genome with a restriction enzyme called PvuII, each fragment is separated by electrophoresis and subjected to Southern transfer to verify the sequence of IS6110. Since each strain has a different number of IS6110 and the length of the fragment containing them, it is used to identify the strain.

  However, such methods require a considerable amount of time for culturing, and the methods themselves are complicated. Moreover, since the gene sequence information of the Mycobacterium tuberculosis genome is not directly used, the identification accuracy is also a problem.

  On the other hand, as genome analysis progresses worldwide, the whole genome analysis has been completed also in Mycobacterium tuberculosis (see Non-Patent Document 1). Under such circumstances, it has also been proposed to amplify the entire gene of Mycobacterium tuberculosis using the PCR method and to prepare a DNA chip on which this PCR product is immobilized (Non-patent Document 2 and Non-patent Document 3). This is a method for detecting differences in the genome structure of M. tuberculosis using such a chip.

  For example, a method for identifying Mycobacterium tuberculosis using a probe-immobilized substrate using an oligonucleotide specific for Mycobacterium tuberculosis has been disclosed (Patent Document 1). In addition, inventions of typing methods using specific sequences for the identification of Mycobacterium tuberculosis have been disclosed (Patent Documents 2 and 3). With these methods, M. tuberculosis around the world can now be roughly classified into 10 strains.

Japanese Patent Application Laid-Open No. 2004-113196 "Typing DNA chip using Mycobacterium tuberculosis-specific gene group including many specific repetitive gene sequences and use thereof" Patent No. 3612552 “Detection and differentiation of Mycobacterium tuberculosis group bacteria by tandem mutation repeat sequence oligotyping” Patent No. 3134940 “Amplification and detection of Mycobacterium avium complex”

Nature, 393: 537-544, (1998). Science, 284: 1520-1523 (1999). Proc Natl Acad Sci USA, 98: 7534-7539, (2001)

  Therefore, the present invention provides a method for identifying and detecting a strain of Mycobacterium tuberculosis in a sample and a gene mutation from the gene sequence information of the Mycobacterium tuberculosis genome in the sample using the consensus genomic information of Mycobacterium tuberculosis, and the consensus genomic information. It is an object to provide a method of producing

  In order to solve the above-mentioned problems, a computerized method for identifying a strain of Mycobacterium tuberculosis in a sample according to the present invention comprises the following arrangement. That is, a method for identifying a Mycobacterium tuberculosis strain in a sample by a computer, the computer storing a genome information of the Mycobacterium tuberculosis in the sample inputted, and a consensus genome information of the Mycobacterium tuberculosis stored in the computer Alignment process for the gene sequence of a specific strain contained in the sample and the gene sequence of Mycobacterium tuberculosis in the sample, and the specific gene sequence in the genome information of Mycobacterium tuberculosis in the sample is the consensus genome of Mycobacterium tuberculosis A step of identifying a specific strain based on the type of strain corresponding to the specific gene sequence stored in advance by detecting a coincidence with the specific gene sequence included in the information, and a tubercle bacillus in the sample And a step of displaying the identification result of the strain. Here, the specific gene sequence in the genomic information of Mycobacterium tuberculosis in the sample may coincide with the specific gene sequence included in the consensus genomic information of Mycobacterium tuberculosis may be all or a partial match. In addition, the gene sequence that characterizes a certain strain is known when the specific gene sequence in the genomic information of Mycobacterium tuberculosis in the sample matches the specific gene sequence included in the consensus genomic information of Mycobacterium tuberculosis. It is also possible to use this information.

  Moreover, the method for identifying the strain and mutation of M. tuberculosis in a sample according to the present invention has the following configuration. That is, the step of storing the genome information of M. tuberculosis in the sample input by the computer, the gene sequence information of the specific strain contained in the consensus genome information of M. tuberculosis stored by the computer and the M. tuberculosis in the sample Alignment processing for gene sequence information and specific gene sequence in Mycobacterium tuberculosis genome information in the sample is detected in advance to match with the specific gene sequence included in the consensus genome information of Mycobacterium tuberculosis. A step of identifying a specific strain based on the type of strain corresponding to the specific gene sequence, and a gene sequence included in the M. tuberculosis consensus genome information corresponding to the identified strain as a reference gene sequence, The reference gene sequence is compared with the gene sequence of Mycobacterium tuberculosis in the sample, and the reference gene sequence A step of identifying the different genetic information as a gene mutation information, identification results of strains of Mycobacterium tuberculosis in a sample, and characterized by comprising the step of displaying the result of genetic mutation information.

  The consensus genome information of M. tuberculosis is M. tuberculosis H37Rv, M. tuberculosis KZN605, M. tuberculosis RGTB423, M. tuberculosis RGTB 327, M. tuberculosis Erdman, M. tuberculosis CTRI-2, M. tuberculosis CDC 1551, M. tuberculosis CCDC 5180, Mycobacterium tuberculosis CCDC5079, Mycobacterium tuberculosis KZN4207, Mycobacterium tuberculosis KZN1435, Mycobacterium tuberculosis F11, Mycobacterium tuberculosis H37Ra, Mycobacterium CIPT 140010059, Mycobacterium GM041182, Mycobacterium BCG str. Mexico, Mycobacterium BCG str. Moreau About partial or complete genome information of RDJ strain, related bacteria BCG str. Tokyo 172 strain, related bacteria BCG Pasteur 1173P2 The consensus genome information may include a common gene sequence region as a common gene sequence region and a gene sequence region different among strains as a gene sequence region unique to the strain. In addition, some of the Mycobacterium tuberculosis strains and related strains listed here may be altered or deleted.

  The correction of the inversion of the gene sequence in constructing the consensus genome information of M. tuberculosis is between gene sequences 932051 and 932052 of M. tuberculosis strain KZN605, between positions 3479594 and 3459595, and gene sequence 93.1985 of M. tuberculosis strain KZN1435. Between the 3 and 1986th, between the 3479865th and 3479866th, between the gene sequence 932007 and 932008, and between the 3475655th and 3476554th of the Mycobacterium tuberculosis strain KZN4207 There may be. The correction of the inversion of the gene sequence mentioned here may be carried out altogether or may be consensus genome information of Mycobacterium tuberculosis with one or more corrections. In addition, the correction of the gene sequence of the Mycobacterium tuberculosis genome may be performed not only by correcting the inversion but also by correcting metastasis as necessary.

  The consensus genome information of Mycobacterium tuberculosis may be gene sequence 1. In addition, one, two or more bases contained in the gene sequence of gene sequence 1 may be substituted, deleted or added as long as identification of Mycobacterium tuberculosis in the sample and gene mutation can be detected.

  The step of displaying the result of the gene mutation information may be capable of displaying information on the gene sequence region containing the gene mutation. When the M. tuberculosis strain in the sample is identified by the consensus genome of the present invention and compared with its gene sequence, if there is a mutation in the M. tuberculosis gene sequence in the sample, the mutation location is indicated and the mutation It may be possible to show information such as a name, a function, a specific number, or link information to detailed information related to a gene region containing.

  In addition, a method for identifying a drug-responsive mutant gene showing drug resistance or drug sensitivity of Mycobacterium tuberculosis in a sample using the computer of the present invention comprises the following arrangement. In the step of identifying gene information different from the reference gene sequence as gene mutation information, the gene mutation information is compared with drug response mutation gene information of Mycobacterium tuberculosis stored in the computer, and the gene mutation information is a specific drug response mutation gene. In the case of information, this is identified, and in the step of displaying the result of gene mutation information, the result of gene mutation information and drug response mutation gene information may be displayed. That is, when there is a mutation in the gene sequence of the Mycobacterium tuberculosis genome in the sample, if this is a genetic mutation involved in resistance or sensitivity to a specific drug, this is identified and displayed as a result. That is, if the gene sequence contained in the M. tuberculosis genome in the sample and the M. tuberculosis consensus genome are compared, and there is a mutation in the M. tuberculosis gene sequence in the sample, the gene mutation information and the computer are stored in advance. The drug response mutation gene information for each strain of Mycobacterium tuberculosis is compared, and the gene mutation is identified as drug response mutation gene information.

  A method for identifying a drug-responsive mutant gene showing drug resistance or drug sensitivity of Mycobacterium tuberculosis in a sample by the computer of the present invention may be configured as follows. That is, it is characterized by using consensus genome information of Mycobacterium tuberculosis containing a sequence having a drug-responsive mutant gene. By adding the gene sequence information of Mycobacterium tuberculosis strains having drug-responsive mutant genes to the Mycobacterium tuberculosis consensus genome of the present invention, the drug-responsive mutant strains of Mycobacterium tuberculosis can be directly compared with the gene sequence of Mycobacterium tuberculosis in the sample. Can be identified. That is, Mycobacterium tuberculosis strains can be classified and identified from the viewpoint of drug response mutation.

  In the production and production of M. tuberculosis consensus genome information, M. tuberculosis H37Rv, M. tuberculosis KZN605, M. tuberculosis RGTB423, M. tuberculosis RGTB 327, M. tuberculosis Erdman, M. tuberculosis CTRI-2, M. tuberculosis CDC1551 M. tuberculosis CCDC5180, M. tuberculosis CCDC5079, M. tuberculosis KZN4207, M. tuberculosis KZN1435, M. tuberculosis F11, M. tuberculosis H37Ra, M. tuberculosis CIPT 140010059, M. tuberculosis GM041182 Among the genome information of a part or all of the related bacteria BCG str. Moreau RDJ strain, related bacteria BCG str. Tokyo 172 strain, related bacteria BCG Pasteur 1173P2 strain, the inversion of each gene sequence is corrected or transferred, Regarding the gene sequences subjected to the alignment processing, the consensus genome information may include a common gene sequence region as a common gene sequence region and a gene sequence region different among strains as a unique gene sequence region of the strain. Moreover, the correction | amendment of the transfer of a gene sequence and the inversion mentioned here is good also as consensus genome information of M. tuberculosis by implementing all or one part.

  The above invention may be a computer system. That is, a tuberculosis sample information storage unit that stores information on the genome of Mycobacterium tuberculosis in the sample input by the computer, a consensus genome information storage unit in which the computer stores information on the Mycobacterium tuberculosis consensus, and a gene for Mycobacterium tuberculosis in the sample An alignment processing unit that performs alignment processing on the sequence and the gene sequence included in the M. tuberculosis consensus genome information, and the specific gene sequence in the M. tuberculosis genome information in the sample is a specific gene sequence included in the M. tuberculosis consensus genome information. A strain identification processing unit that identifies a specific strain based on the type of strain corresponding to the specific gene sequence stored in advance by detecting a match, and the specific strain identified by the strain identification processing unit Of specific strains contained in the Mycobacterium tuberculosis consensus genome information corresponding to A reference gene sequence identification processing unit for identifying a gene sequence, and a mutant gene information detection unit for comparing the reference gene sequence with a gene sequence of Mycobacterium tuberculosis in a sample to identify gene information different from the reference gene sequence And a computer system for identifying the Mycobacterium tuberculosis strain in the sample and the gene mutation thereof, comprising the identification result of the Mycobacterium tuberculosis strain in the sample and an information output unit for displaying gene mutation information. The inventions according to claims 1 to 8 may be computer system inventions.

  According to the method for identifying M. tuberculosis strains and mutations using the Mycobacterium tuberculosis consensus genome of the present invention, all strains of M. tuberculosis are identified, SNP level typing, and gene mutation detection based on the gene sequence information of M. tuberculosis in the sample. The resolution and analysis time of epidemiological analysis such as strain classification can be significantly improved.

Explanatory diagram showing inversions present in the Mycobacterium tuberculosis genome Explanatory diagram showing correction of inversion in the Mycobacterium tuberculosis genome (H37Rv vs Erdman Harr plot) Explanatory diagram showing the processing to correct the inversion present in the Mycobacterium tuberculosis genome (Harr plot of H37Rv vs KZN1405 (before correction)) Explanatory diagram showing the correction process of the inversion present in the Mycobacterium tuberculosis genome (Harr plot of H37Rv vs KZN 1405 (after correction)) Computer image showing part of the alignment of Mycobacterium tuberculosis on a genome-wide scale List of mutation positions by comparison with Mycobacterium tuberculosis consensus genome Phylogenetic diagram of Mycobacterium tuberculosis and related bacteria obtained using the Mycobacterium tuberculosis consensus genome (rootless phylogenetic tree) Phylogenetic diagram of Mycobacterium tuberculosis and related bacteria obtained using the Mycobacterium tuberculosis consensus genome (rootless phylogenetic tree) Systematic diagram of Mycobacterium tuberculosis and related bacteria obtained using M. tuberculosis H37Rv strain (rooted phylogenetic tree) Phylogenetic diagram of Mycobacterium tuberculosis and related bacteria obtained using the genome of all Mycobacterium tuberculosis strains (Rooted phylogenetic tree) The figure which shows the comparison result of VNTR pattern Figure showing comparison results of sporigotyping patterns Image of analysis software using Mycobacterium tuberculosis consensus genome Explanatory diagram identifying drug-responsive mutant gene information using the Mycobacterium tuberculosis consensus genome

  So far, typing methods have not been able to analyze strain differences due to insufficient resolution of strain identification. However, the present inventor is able to obtain genome-wide sequence information with the advent of next-generation sequencers, and in view of the fact that comparison at the whole genome level can be easily performed, existing whole genome information is registered. A virtual consensus genome sequence that incorporates all standard information on 13 strains of Mycobacterium tuberculosis and 6 medically important related strains was created and used to create a strain of Mycobacterium tuberculosis in the sample. The present inventors have obtained knowledge that gene mutations can be identified, and have reached the present invention. This method enables identification of all Mycobacterium tuberculosis strains, typing of SNP levels, and detection of gene mutations based on the gene sequence information of Mycobacterium tuberculosis in the sample. Can be improved.

  The present invention will be described below with reference to the drawings. Here, some experimental examples and examples are given, but the design of the embodiment of the present invention can be changed as appropriate without departing from the spirit of the present invention.

(Mycobacterium tuberculosis and related bacteria constituting the Mycobacterium tuberculosis consensus genome)
The construction of consensus genome information of Mycobacterium tuberculosis that is a component of the present invention will be described. Preparations were made for the gene sequences contained in the genomes of 13 strains of Mycobacterium tuberculosis, for which existing genome-wide information was registered, and 6 medically important related strains. Table 1 shows the Mycobacterium tuberculosis strains used for the construction of the Mycobacterium tuberculosis consensus genome in the present invention, and lists serial numbers, strain names and accession numbers from the left. Table 2 shows the M. tuberculosis related strains used for the construction of the M. tuberculosis consensus genome in the present invention, and lists the serial number, strain name and accession number from the left. Here, 6 medically important related strains are strains extracted from humans, which are similar to the Mycobacterium tuberculosis genome and are considered for the reason that they can be used to construct the Mycobacterium tuberculosis consensus genome. It is a selection.

(Inversion of gene sequence)
Next, the inversion of each gene sequence was corrected. Bacteria and viruses, such as Mycobacterium tuberculosis, that cause infectious diseases are prone to transfer and inversion in genomic genes. Here, the inversion refers to the case where a part of the chromosome is inverted 180 ° and fits in the same position. Metastasis refers to the case where a part of a chromosome moves out of its original position and moves to another position on the chromosome. The present inventor has found that M. tuberculosis has less inversion / metastasis, and by correcting all of this inversion, construction of a consensus genome of M. tuberculosis has been realized. By correcting inversion and metastasis, it is possible to increase the number of overlapping sequences in each gene sequence, and to construct an optimal consensus genome for identifying strains of Mycobacterium tuberculosis and detecting gene mutations.

A procedure for detecting an inversion in the gene sequence of the Mycobacterium tuberculosis genome will be described.
Homology is compared from the beginning of the genome for each unit of a certain number of nucleotides (called Window), and if the homology becomes extremely low, it is searched whether there is an alternative place elsewhere in the genome. Repeat that. Incidentally, the same applies to the search for gene sequence transfer. When comparing, the inversion is detected by searching for complementary sequences. By setting the parameters, even parts with low homology are detected, and these gene sequence inversions can be detected using general gene analysis software (http://asap.ahabs.wisc.edu/mauve/index.php). It can be implemented by using. However, visual confirmation is necessary to specify the exact base position of the inversion of the gene sequence.

  In the examples of the present invention, inversion detection was carried out for 3 strains of Mycobacterium tuberculosis KZN605 strain, Mycobacterium tuberculosis KZN1435 strain and Mycobacterium tuberculosis KZN4207 strain by the above-described detection procedure of gene sequence inversion. After that, alignment is performed to construct a consensus genome. The genome size of Mycobacterium tuberculosis was about 4.4 Mbp, but it was found that gene inversion occurred in these three strains in the vicinity of about 0.9 Mbp and 3.4 Mbp of the genome (FIG. 1). Among these, there are repeat sequences existing in several places in Mycobacterium tuberculosis called IS6110 at the site where the direction of the gene near 3.4 Mbp is switched. By comparing with a strain that did not, the forward metastasis position near 0.9 Mbp where the genome was replaced was searched. In this part, all three strains encode the same protein of unknown function that is annotated as hypothetical protein.

  FIG. 1 is a diagram called a genome rearrangement map (genome rearrangement map), in which two upper and lower genomes are arranged in the order of 5 ′-> 3 ′ from left to right. The part where the corresponding gene exists in each of the upper and lower sides is connected with a line. Since M. tuberculosis is highly similar, most parts are connected by line segments, so they are displayed as filled. The part that appears to be a triangle in the middle indicates that the corresponding part of the upper and lower genomes (near 3,400,000 bp) is inverted (inverted) from the part slightly 5 'to 1,000,000 bp. Corresponding to the inverted correction position, the vicinity of 1,000,000 to 3,400,000 is reversed.

  Next, after detecting the inversion of 3 strains of M. tuberculosis KZN605, M. tuberculosis KZN1435 and M. tuberculosis KZN4207, correction was performed by reversing the inverted gene sequence. Specifically, between gene sequences 932051 and 932052 of Mycobacterium tuberculosis KZN605, between 3479594 and 3459595, between gene sequences 931985 and 931986 of Mycobacterium tuberculosis KZN1435, between 3479865 and 3479866, The gene sequence between Mycobacterium tuberculosis KZN4207 gene sequence 932007 and 932008, and between 3475553 and 3476554, was inverted, and correction was performed by reversing it.

  The result of correcting the inversion of these M. tuberculosis genomes will be described using a Harr plot. FIG. 2 shows H37Rv vs Erdman (a), H37Rv vs KZN1405 (before correction) (b), and H37Rv vs KZN1405 (after correction) (c). The vertical axis of the graph is H37Rv, the horizontal axis is Erdman, KZN1405, each represents the position in the genome of Mycobacterium tuberculosis, the position of 0 is the 5 'end, each closer to 3' as the value increases, the largest The value is about 4.4 Mbp. As shown in FIG. 2a, when the line segment is connected from the lower left to the upper right, it indicates that the base sequences roughly match at each position. In FIG. 2b, it can be seen that a line segment extends from the upper left to the lower right in the central portion, and the portion is inverted between the two bacteria. FIG. 2c shows the same analysis performed after detecting this portion and correcting the inversion. As in FIG. 2a, the line segments are directed from the lower left to the upper right, thereby enabling alignment.

(Alignment process for M. tuberculosis consensus genome construction)
After correcting the inversion of the gene sequence of the Mycobacterium tuberculosis genome in this way, alignment processing was performed on the gene sequence of the Mycobacterium tuberculosis and its related bacteria (FIG. 3). Alignment process inputs two or more gene sequences to a computer and displays them on the computer screen from the 5 'side to the 3' side so that the common part of each gene sequence is maximized Calculation and rearrangement (alignment) processing is performed. If necessary, a gap may be made so that the common part of each gene sequence is maximized. There are already several known techniques for this processing method, and these are used in the present invention. FIG. 3 shows a computer image showing a part of the alignment process of Mycobacterium tuberculosis on a genome-wide scale.

  In the present invention, by correcting the inversion of the gene sequence of each Mycobacterium tuberculosis genome, it is possible to obtain many overlapping gene parts (specifically, about 95% overlapping parts) by the alignment process, The first tuberculosis consensus genome was constructed. On the other hand, if this inversion correction process is not performed, even if the alignment process is performed, the homology is only about 40%.

  The overlapping sequence portion thus obtained is extracted from the gene sequence information and used as a constituent element of the consensus genome of Mycobacterium tuberculosis. On the other hand, non-overlapping gene sequences are also used as components of the M. tuberculosis consensus genome as a gene sequence that characterizes M. tuberculosis. That is, it becomes an artificial gene sequence in which the overlapping part of the Mycobacterium tuberculosis genome and a plurality of non-overlapping gene sequences are linked, and a plurality of non-overlapping gene sequences are linked in comparison with the naturally occurring M. tuberculosis genome. Therefore, the amount of information becomes large. Specifically, the information amount of the Mycobacterium tuberculosis genome existing in nature is about 4.4 Mbp, whereas the information amount of the consensus genome of the present invention is about 4.9 Mbp.

(Genetic sequence of Mycobacterium tuberculosis consensus genome and its use)
SEQ ID NO: 1 is an example of the gene sequence of the consensus genome of the Mycobacterium tuberculosis genome in the present invention. The gene size is about 4.9 Mbp. The consensus genome of the Mycobacterium tuberculosis genome in the present invention can be expanded. For example, when new Mycobacterium tuberculosis strains or Mycobacterium tuberculosis related strains are discovered in the future, the genomic genes of these strains are reversed in the gene sequence. After correcting the position and metastasis, alignment processing can be performed to add to the consensus genome of the Mycobacterium tuberculosis genome of the present invention.

  In addition to identifying an unknown Mycobacterium tuberculosis strain in a sample, the Mycobacterium tuberculosis consensus genome constructed in the present invention can detect gene mutations in the genome of the strain. First, genome analysis of M. tuberculosis in this sample was performed (for example, illumina MiSeq, Genome Analyzer series, HiSeq series, Lifetechnologies ion proton, ion PGM, SoLid series, Roche GS series, PacBio PacBio Next-generation sequencer that adopts a new base sequence analysis method that is different from the base sequence analysis method based on the conventional Sanger method such as RS series, and gene sequence analysis by the conventional Sanger method) Enter the genome sequence information of the whole genome into a computer. Next, the gene sequence information of the M. tuberculosis consensus genome constructed in the present invention and alignment processing are performed. For this alignment process, commercially available computer software was used.

  The consensus genome is constructed by correcting the inversion in the gene sequence of the Mycobacterium tuberculosis genome, but if the gene sequence of the strain in the sample is aligned with the gene sequence of the Mycobacterium tuberculosis consensus genome, The correction of the position may reduce the coincidence rate of the gene sequence. Therefore, in the M. tuberculosis consensus genome, by adding specific information indicating that correction processing has been performed to the gene sequence corrected for inversion, the probability of matching is increased when aligning with the gene sequence of the strain in the sample. As described above, a gene sequence from which inversion correction is canceled may be generated so that inversion correction processing and unprocessed alignment processing can be performed.

  The Mycobacterium tuberculosis consensus genome of the present invention contains a gene sequence that characterizes the Mycobacterium tuberculosis and its related bacteria included in Tables 1 and 2, so that it is present in the sample by alignment with the Mycobacterium tuberculosis consensus genome. For unknown strains, strains can be identified. That is, there is a gene sequence that matches (including partial matches) the gene sequence of any of the gene sequences that characterize M. tuberculosis and related bacteria included in Tables 1 and 2 and the gene sequence of an unknown strain in the sample. By detecting this, the strain can be identified.

(Detection rate of Mycobacterium tuberculosis-corresponding sequences in the Mycobacterium tuberculosis consensus genome)
Table 3 shows the M. tuberculosis-corresponding sequence detection rate of the M. tuberculosis consensus genome of the present invention. The detection rate of M. tuberculosis-corresponding sequences indicates that the M. tuberculosis consensus genome of the present invention is a highly standardized M. tuberculosis genome. Using a sample containing a plurality of Mycobacterium tuberculosis strains as a sample, using the genome information of Mycobacterium tuberculosis H37Rv strain, which is a standard strain of Mycobacterium tuberculosis, and the Mycobacterium tuberculosis consensus genome of the present invention, a gene corresponding to Mycobacterium tuberculosis in the sample The detection rate of the sequence was measured. Using a sample of two types of heat-sterilized tuberculosis cultures, the gene was amplified with a gene amplification kit from NEB, and the gene purified with the gene purification kit from QIAGEN was sequenced using a gene analyzer MiSeq (Illumina). Was analyzed. The obtained gene sequence data is considered to virtually reflect the gene sequence of the entire genome, and the detection rate of the gene sequence corresponding to M. tuberculosis in the sample can be measured. As a result of gene sequence analysis, it was possible to obtain data of about 2 million bases in each of two types of tuberculosis culture specimens. The gene sequence information was mapped to the genome information of the Mycobacterium tuberculosis consensus genome and the Mycobacterium tuberculosis H37Rv strain of the present invention, respectively, and the detection rate of the gene sequence corresponding to Mycobacterium tuberculosis was measured. In any specimen, the Mycobacterium tuberculosis consensus genome of the present invention had a high detection rate and was shown to have standard genome information superior to that of the Mycobacterium tuberculosis H37Rv strain, which is a Mycobacterium tuberculosis standard strain.

(Identification of gene mutation using Mycobacterium tuberculosis consensus genome)
By utilizing the Mycobacterium tuberculosis consensus genome of the present invention, not only the strain in the sample can be identified, but also its gene mutation can be detected. As an example of the present invention, using a consensus genome of the Mycobacterium tuberculosis genome of SEQ ID NO: 1, a gene mutation of a Mycobacterium tuberculosis strain was identified in a sample of Mycobacterium tuberculosis. The entire gene sequence analysis of the Mycobacterium tuberculosis genome of the sample was performed, and the information was input into a computer, and a comparison process was performed with the Mycobacterium tuberculosis consensus genome of the present invention. In FIG. 4, the information regarding the gene mutation by the comparison with the M. tuberculosis consensus genome is displayed.

  FIG. 4 shows an alignment process of the M. tuberculosis consensus genome of the present invention and the gene sequence of M. tuberculosis in a sample to detect a gene mutation in the M. tuberculosis genome in the sample. From the left, the position of the mutation in the consensus sequence (a specific gene (base) and its position in the M. tuberculosis consensus genome), the base on the query side (the base in the gene sequence of the M. tuberculosis genome in the sample corresponding to this gene ( Missing mutations are displayed as dots)), the position of the mutation on the query side, the distance to the next mismatch, and the sequence name on the query side. In the query position, the position of the mutation that is displayed continuously with 1 TB indicates that there are consecutive mutations in the gene, and 3574 TB and 5393 TB are displayed because the mutations are dispersed. I understand that The query-side sequence name is KZN4207, indicating that the tuberculosis bacterium in the sample is identified as KZN4207.

(A systematic analysis of Mycobacterium tuberculosis using the Mycobacterium tuberculosis consensus genome)
The Example which carried out the systematic analysis of M. tuberculosis using the M. tuberculosis consensus genome of this invention is demonstrated. FIG. 5 shows a systematic diagram of M. tuberculosis and related bacteria obtained using the M. tuberculosis consensus genome of the present invention. The phylogenetic tree was created using Bayes' posterior probability method, which makes it possible to estimate when each strain diverged. The number "90.0", which is written in small with the horizontal bar, means "900 years". So far, phylogenetic analysis of strains has been performed by 16S rRNA nucleotide sequence and housekeeping gene polymorphism, and by tuberculosis by sporigotyping and VNTR, and recently by SNP concatenation using whole genome data. I came. However, these use only a part of the information of the whole genome, so the topology of the whole phylogenetic tree is correct even when the results seen in the bifurcation here are good. It was difficult to judge whether or not. On the other hand, since the entire genome-wide alignment is possible, the “ultimate phylogenetic tree” that truly reflects the entire genome information can be created.

  Next, the accuracy of the phylogenetic analysis of M. tuberculosis using the M. tuberculosis consensus genome of the present invention will be described. FIG. 6a is an example of phylogenetic analysis of Mycobacterium tuberculosis using the Mycobacterium tuberculosis consensus genome of the present invention, and FIG. 6b is an example of phylogenetic analysis of Mycobacterium tuberculosis using the Mycobacterium tuberculosis H37Rv strain, which is a standard strain of Mycobacterium tuberculosis. FIG. 6c is an example in which a phylogenetic analysis of M. tuberculosis was performed using the genomes of all M. tuberculosis strains (13 types of M. tuberculosis and its related bacteria used for the construction of the M. tuberculosis consensus genome of the present invention). 6a and 6c have almost the same lineage classification, but in FIG. 6b, the tubercle bacilli RGTB423 strain does not belong to any group and has different lineage diagrams. About 13 M. tuberculosis strains, it can be displayed as “MTB” to form one group (FIGS. 6a and 6c). That is, it was shown that the phylogenetic analysis of M. tuberculosis using the M. tuberculosis consensus genome of the present invention is superior in accuracy to that using the M. tuberculosis H37Rv strain, which is a M. tuberculosis standard strain. In addition, the difference which arose in the system | strain analysis is based on the SNP information detected in the comparison with M. tuberculosis RGTB423 strain with M. tuberculosis H37Rv strain. That is, since the Mycobacterium tuberculosis consensus genome of the present invention has a high degree of standardization, there is a high probability that a SNP unique to Mycobacterium tuberculosis RGTB423 is detected, but when compared with the Mycobacterium tuberculosis H37Rv strain, This is because the unique SNP of the Mycobacterium tuberculosis H37Rv strain itself is also detected. The number “300” in FIG. 6 means “300 years”. 5 and 6 both show the phylogenetic analysis of Mycobacterium tuberculosis. FIG. 5 is an unrooted phylogenetic tree, and FIG. 6 is a rooted phylogenetic tree.

(Long sequence polymorphism analysis and analysis of Mycobacterium tuberculosis strains using Mycobacterium tuberculosis consensus genome)
Next, a long sequence polymorphism analysis method and a virtual determination method using the M. tuberculosis consensus genome of the present invention were performed in order to analyze M. tuberculosis strains against 19 types of M. tuberculosis and related bacteria. In Table 4, the result of the system | strain determination by a long sequence polymorphism analysis method is shown for every strain. The long sequence polymorphism analysis method is a phylogenetic method different from spoligotyping and VNTR, and is a sequence that is missing only in certain strains in comparison with a representative tuberculosis strain called H37Rv and other strains of tuberculosis. (Proc Natl Acad Sci US A. 2006 Feb 21; 103 (8): 2869-73. Epub 2006 Feb
13.). This method has been applied to the analysis of the relationship between human evolution and M. tuberculosis symbiosis with humans (Nat Genet.
2013 Oct; 45 (10): 1176-82. Doi: 10.1038 / ng.2744. Epub 2013 Sep 1.). On the other hand, in the virtual determination method using the Mycobacterium tuberculosis consensus genome of the present invention, the phylogenetic method is based on the presence or absence of amplification of a specific region by PCR in three methods of spoligotyping method, VNTR method, and Long sequence polymorphism method. This was carried out by virtually determining the presence or absence of a sequence that was the target of amplification by PCR. As a result of analysis of M. tuberculosis strains by these two methods, the same results were obtained for 18 types of 19 types of M. tuberculosis and related strains. In the virtual determination method using the Mycobacterium tuberculosis consensus genome, it was “Strain 4”. This difference was determined to be “line 5” because part of the region indicating that it was not “line 5” was missing in the long sequence polymorphism analysis method. This example shows that there are exceptional strains in which the results of the conventional typing method do not match the properties of the original strain, and these can be proved by a virtual method without actual experimentation. I was able to show gender.

(Identification of Mycobacterium tuberculosis strains by Mycobacterium tuberculosis consensus genome using VNTR and sporigotyping)
Next, VNTR (variable number of tandem repeats) is investigated for M. tuberculosis in the sample, and it is investigated whether this data can be identified by mapping this data to the consensus genome of the present invention. (FIG. 7). VNTR is a repetitive sequence of several bases to several tens of bases whose presence in hundreds to thousands of places has been confirmed in the genome. The repetitive sequence polymorphism analysis is a method for typing M. tuberculosis by examining the copy number of repetitive sequences in minisatellite DNA existing on the M. tuberculosis genome. Since polymorphism is seen in the number of repetitions and the polymorphism is rich, it has been used for linkage analysis and the like as a useful polymorphic marker so far. FIG. 7 shows the result of examining VNTR for arbitrarily selected tuberculosis bacteria and mapping this data to the consensus genome of the present invention. By computer processing, the VNTR pattern of M. tuberculosis strains contained in the consensus genome that approximates the VNTR pattern of M. tuberculosis in the sample can be displayed and rearranged so that the two can be compared. The name of each VNTR is displayed at the top of each table, and the number of the VNTR is displayed below it. The middle part of the table displays the names of strains identified in the consensus genome of the present invention and VNTR data, and the lower part displays VNTR data of Mycobacterium tuberculosis in the sample. Points where these two data do not match are marked with a hatched box. By the comparative processing of VNTR using the consensus genome of the present invention, any strain of Mycobacterium tuberculosis can be identified.

  The sporigotyping method visualizes the spacer sequence between multiple direct repeats (DR) sequences present in the genomic DR region of the Mycobacterium tuberculosis group, and compares the presence or absence between strains to determine the genotype of Mycobacterium tuberculosis. It is a technique to analyze. In the DR region, there are multiple repeat sequences (Directrepeat: DR) consisting of 36 bp that are specifically detected only in the Mycobacterium tuberculosis group, and through a spacer sequence composed of 37-41 bp each of different base sequences. About 10-50 copies. The number of DRs contained in the DR region varies from strain to strain, and the spacer sequence between them also varies from strain to strain, so the strain genotype is determined by comparing the presence or absence of 43 spacer sequences between strains. . FIG. 8 shows the result of mapping the data to the consensus genome of the present invention by examining the sporigotyping for arbitrarily selected M. tuberculosis. By computer processing, it is possible to display the sporigotyping pattern of M. tuberculosis strains contained in the consensus genome that approximates the M. tuberculosis sporigotyping pattern in the sample, and rearrange them so that the two can be compared. it can.

The upper part of FIG. 8 displays the names of the respective data, and the lower part displays the sporgotyping pattern in the consensus genome of the present invention. The lower part displays the sporgotyping data of Mycobacterium tuberculosis in the sample. Yes. Points where these two data do not match are marked with a box. An arbitrary strain of Mycobacterium tuberculosis can be identified by a comparison process of sporigotyping using the consensus genome of the present invention. Distance is the number of different values (black or white) divided by the total number of values. What is SpolDB4 ST ST?
It is an abbreviation of type, and it numbers things that have a certain pattern of sporigotyping patterns. The black / white display of the pattern indicates the presence / absence of 43 specific gene regions, and the determination is performed by PCR and hybridization based on the presence / absence of 43 specific gene regions. 8, for example, if the first area is “present”, the first is black, and if the second area is “none”, the second is white.

  It was shown that the strain of M. tuberculosis can be identified by examining the VNTR pattern or the sporigotyping pattern of the M. tuberculosis genome in the sample and mapping it to the M. tuberculosis consensus genome of the present invention. That is, without obtaining information on the entire gene sequence of the Mycobacterium tuberculosis genome in the sample, if there is information on the VNTR pattern or sporigotyping pattern of Mycobacterium tuberculosis, which is a conventional method, the Mycobacterium tuberculosis consensus genome of the present invention is used. Thus, the strain can be identified.

  Therefore, as a modification of the present invention, a method for identifying a strain of M. tuberculosis in a sample by a computer, the computer storing a VNTR pattern or a sporigotyping pattern of M. tuberculosis in a sample input; A process of performing alignment processing on the VNTR pattern or sporigotyping pattern of a specific strain included in the consensus genome information of Mycobacterium tuberculosis stored in the computer, and the VNTR pattern or sporigotyping pattern of M. tuberculosis in the sample, and the sample The specific VNTR pattern or sporigotyping pattern in the genome information of Mycobacterium tuberculosis is consistent with the specific VNTR pattern or sporigotyping pattern contained in the consensus genomic information of Mycobacterium tuberculosis. Identifying process and sun Identification results of strain of Mycobacterium tuberculosis in Le may method of identifying strains of M. tuberculosis and a step of displaying.

(Computer system using Mycobacterium tuberculosis consensus genome)
A computer system using the M. tuberculosis consensus genome will be described. The computer system for identifying strains and mutations of M. tuberculosis in this sample is a M. tuberculosis sample information storage unit that stores the genome information of M. tuberculosis in the sample input by the computer, and the computer stores M. tuberculosis consensus genome information. A consensus genome information storage unit, an alignment processing unit that aligns a gene sequence included in the genome information of Mycobacterium tuberculosis in the sample and a gene sequence included in the Mycobacterium tuberculosis consensus genome information, and a specific gene of Mycobacterium tuberculosis in the sample Corresponds to the specific strain identified by the strain identification processing unit and the strain identification processing unit that identifies the specific strain by matching the specific gene sequence included in the consensus genome information of Mycobacterium tuberculosis Reference strains of specific strains included in the consensus genome information of Mycobacterium tuberculosis A mutant gene for identifying a gene information different from the reference gene sequence as a gene mutation information by comparing a reference gene sequence identification processing unit for identifying a child sequence with the reference gene sequence and a gene sequence of Mycobacterium tuberculosis in a sample. An information detection unit, and an information output unit for displaying the identification result of the M. tuberculosis strain in the sample and gene mutation information are provided. In addition, information such as the function and name of the gene at any gene sequence site such as a gene mutation site can be displayed. The computer system may be provided as analysis software. In addition, implementation is also possible so that systematic analysis of strains such as Mycobacterium tuberculosis in the sample can be performed.

(Virtual judgment of Beijing type, modern type, or ancestral type using Mycobacterium tuberculosis consensus genome)
Among the Mycobacterium tuberculosis, the Beijing-type strain that is particularly prevalent in Asia is said to be highly pathogenic, and among the Beijing-type, the modern type tends to be resistant to drugs (Nat Genet . 2013 Jul; 45 (7): 784 -90), the identification is important. Conventionally, Beijing type determination has been mainly performed by the sporigotyping method or PCR method, and classification into modern type and ancestral type has been performed by PCR method (for example, Genome Res. 2005 Oct; 15 (10): 1357-64). .). In this example, a virtual determination method using the M. tuberculosis consensus genome of the present invention was performed. Table 5 shows the results. In the Sporigotyping method, which is a Beijing type determination that has been used in the past, the CDC5079 and CCDC5180 strains are determined to be Beijing type, but in the virtual determination method using the Mycobacterium tuberculosis consensus genome of the present invention, Only CCDC5180 was determined to be Beijing and modern. By the way, similar results can be obtained in the PCR-based method. This is because the “specific site of the insertion sequence called IS6110” is stored in the Mycobacterium tuberculosis consensus genome of the present invention, and this sequence can be determined as an index, so that it can be determined accurately. There are multiple IS6110s in the genome of Mycobacterium tuberculosis, and subtype classification of Mycobacterium tuberculosis is possible based on their location and number. The insertion sequence of IS6110 is shown in gene sequence 2. The above results show that there are exceptional strains that do not match the judgment results of multiple typing methods, and that these can be proved by virtual methods without actual experimentation, indicating the usefulness of this method. did it.

(Identification of drug-responsive mutant genes using the Mycobacterium tuberculosis consensus genome)
In the drug resistance detection method, in the case of Mycobacterium tuberculosis, drug resistance is caused by a point mutation of a gene. Therefore, the presence or absence of drug resistance is determined by detecting a mutation in a gene that induces drug resistance. Specific examples of genes that induce drug resistance include rpoB, katG, mabA-inhA, embB, pncA, gryA, rpsL, and rrs genes, and these mutations are analyzed. For example, in katG, the presence or absence of a point mutation that changes the amino acid at position 232 from P to S (this residue is the base at position 2155418 in the standard strain H37Rv (the residue is changed from C to T)) Make a decision with. In the software of the present invention, drug resistance detection may be performed using information obtained by annotating residues contributing to each mutation using a consensus genome.

  For example, the drug-responsive mutation gene information of M. tuberculosis is stored in advance in a computer, the gene sequence of M. tuberculosis in a sample is compared with the consensus genome of the present invention, and the gene mutation information of M. tuberculosis in the sample is detected. If this matches the specific drug response mutant gene information, it may be identified. That is, there is a method of displaying the results of both gene mutation information and drug response mutation gene information in displaying the results of gene mutation information. The drug response mutation gene information includes the drug name, information about the drug, the sensitivity or resistance property to the drug, the name of the drug response mutation gene, gene sequence related information, and the like. On the other hand, the consensus genome information of Mycobacterium tuberculosis according to the present invention is constructed based on 13 types of Mycobacterium tuberculosis and related bacteria, and genome information of Mycobacterium tuberculosis including a sequence having a drug-responsive mutant gene is added thereto. Consensus genome information may also be constructed. In this case, the gene sequence information of M. tuberculosis in the sample can be directly compared with the gene sequence information of the drug-responsive mutant M. tuberculosis.

  FIG. 10 shows identification of drug response mutant gene information using the Mycobacterium tuberculosis consensus genome. From the left column, “species name” and “strain name” are displayed. EMB (ethambutol), FQ (fluoroquinolone), INH (isonicotinic acid hydrazide), PZA (pyrazinamide), RIF (rifampicin), STR (streptomycin sulfate) are the names of drugs, respectively, and the metabolism of the drug is The names of related genes are displayed. As one of the drug response mutation gene information, the sensitivity or resistance property to each drug is shown as “R” (resistance) and “S” (sensitivity) for each strain. This result indicates that information on drug-responsive mutant genes using the Mycobacterium tuberculosis consensus genome was obtained. Note that the sensitivity or resistance property to each drug differs for each strain because there is a mutation in a gene related to drug metabolism. In the present invention, the gene mutation information can also be displayed.

Claims (9)

A computerized method for identifying Mycobacterium tuberculosis strains in a sample,
(1) storing a genome information of Mycobacterium tuberculosis in a sample input by a computer;
(2) a step of performing an alignment process on the gene sequence of a specific strain included in the consensus genome information of M. tuberculosis stored in the computer, and the gene sequence of M. tuberculosis in the sample;
(3) identifying a specific strain by matching a specific gene sequence in the genomic information of Mycobacterium tuberculosis in the sample with a specific gene sequence included in the consensus genomic information of Mycobacterium tuberculosis;
(4) displaying the identification result of the strain of Mycobacterium tuberculosis in the sample;
Comprising
The consensus genome information of the Mycobacterium tuberculosis is Mycobacterium tuberculosis H37Rv strain, Mycobacterium tuberculosis KZN605 strain, Mycobacterium tuberculosis RGTB423 strain, Mycobacterium tuberculosis RGTB327 strain, Mycobacterium tuberculosis Erdman strain, Mycobacterium tuberculosis CTRI-2 strain, Mycobacterium tuberculosis CDC1551 strain, Mycobacterium tuberculosis CCDC5180 strain Mycobacterium tuberculosis CCDC5079 strain, Mycobacterium tuberculosis KZN4207 strain, Mycobacterium tuberculosis KZN1435 strain, Mycobacterium tuberculosis F11 strain, Mycobacterium tuberculosis H37Ra strain, related strain CIPT 140010059 strain, related strain GM041182 strain, related strain BCG str. Mexico strain, related strain BCG str. More than RDJ strain, related strain BCG str. Tokyo 172 strain, related strain BCG Pasteur 1173P2 partial or complete genome information, corrected for inversion or transposition of each gene sequence, aligned gene sequence The consensus genome information includes a common gene sequence region as a common gene sequence region and a gene sequence region different among strains as a unique gene sequence region of the strain, which is included in a computer sample. To identify strains of A computerized method for identifying Mycobacterium tuberculosis strains and mutations in a sample comprising:
(1) storing a genome information of Mycobacterium tuberculosis in a sample input by a computer;
(2) a step of performing an alignment process on the gene sequence of a specific strain included in the consensus genome information of M. tuberculosis stored in the computer, and the gene sequence of M. tuberculosis in the sample;
(3) identifying a specific strain by matching a specific gene sequence in the genomic information of Mycobacterium tuberculosis in the sample with a specific gene sequence included in the consensus genomic information of Mycobacterium tuberculosis;
(4) The gene sequence included in the Mycobacterium tuberculosis consensus genome information corresponding to the identified strain is used as a reference gene sequence, and the reference gene sequence and the gene sequence of M. tuberculosis in the sample are compared, and the reference gene sequence and Identifying different genetic information as genetic mutation information;
(5) a step of displaying the identification result of the Mycobacterium tuberculosis strain in the sample and the result of the gene mutation information;
Comprising
The consensus genome information of the Mycobacterium tuberculosis is Mycobacterium tuberculosis H37Rv strain, Mycobacterium tuberculosis KZN605 strain, Mycobacterium tuberculosis RGTB423 strain, Mycobacterium tuberculosis RGTB327 strain, Mycobacterium tuberculosis Erdman strain, Mycobacterium tuberculosis CTRI-2 strain, Mycobacterium tuberculosis CDC1551 strain, Mycobacterium tuberculosis CCDC5180 strain Mycobacterium tuberculosis CCDC5079 strain, Mycobacterium tuberculosis KZN4207 strain, Mycobacterium tuberculosis KZN1435 strain, Mycobacterium tuberculosis F11 strain, Mycobacterium tuberculosis H37Ra strain, related strain CIPT 140010059 strain, related strain GM041182 strain, related strain BCG str. Mexico strain, related strain BCG str. More than RDJ strain, related strain BCG str. Tokyo 172 strain, related strain BCG Pasteur 1173P2 partial or complete genome information, corrected for inversion or transposition of each gene sequence, aligned gene sequence The consensus genome information includes a common gene sequence region as a common gene sequence region and a gene sequence region different among strains as a unique gene sequence region of the strain, which is included in a computer sample. Of identifying strains of E. coli and gene mutations thereof.
Compensation of the inversion of the gene sequence in the construction of the consensus genome information of M. tuberculosis is between gene sequence 932051 and 932052 of M. tuberculosis strain KZN605, between gene 3479594 and 334595, gene sequence 93.1985 of M. tuberculosis strain KZN1435 And between 93 and 1986, between 3479865 and 3479866, between gene sequence 932007 and 932008 of Mycobacterium tuberculosis strain KZN4207, and part or all of the gene sequence between 3476553 and 3476554 The identification method by a computer according to claim 1 or 2, characterized by the above-mentioned. 4. The computer identification method according to claim 1, wherein the consensus genome information of Mycobacterium tuberculosis is gene sequence 1.   5. The computer identification method according to claim 2, 3 or 4, wherein in the step of displaying the result of the gene mutation information, information on the gene sequence region containing the gene mutation can also be displayed. In the step of identifying gene information different from the reference gene sequence as gene mutation information, the gene mutation information is compared with drug response mutation gene information of Mycobacterium tuberculosis stored in the computer, and the gene mutation information is a specific drug response mutation gene. If it is information, this is identified, and in the step of displaying the result of gene mutation information, the result of gene mutation information and drug-responsive mutation gene information is displayed. The identification method by a computer according to any one of 3, 4, and 5 . 6. The computer identification method according to any one of claims 2, 3, 4, and 5 , wherein consensus genome information of Mycobacterium tuberculosis containing a sequence having a drug-responsive mutant gene is used.   A method of producing consensus genome information of Mycobacterium tuberculosis, including Mycobacterium tuberculosis H37Rv strain, Mycobacterium tuberculosis KZN605 strain, Mycobacterium tuberculosis RGTB423 strain, Mycobacterium tuberculosis RGTB327 strain, Mycobacterium tuberculosis Erdman strain, Mycobacterium tuberculosis CTRI-2 strain, Mycobacterium tuberculosis CDC1551 strain Mycobacterium tuberculosis CCDC5180 strain, Mycobacterium tuberculosis CCDC5079 strain, Mycobacterium tuberculosis KZN 4207 strain, Mycobacterium tuberculosis KZN1435 strain, Mycobacterium tuberculosis F11 strain, Mycobacterium tuberculosis H37Ra strain, related strain CIPT 140010059 strain, related strain GM041182 strain, related strain BCG str. Mexico strain For some or all of the genome information of related BCG str. Moreau RDJ strain, related BCG str. Tokyo 172 strain, related BCG Pasteur 1173P2 strain, correct the inversion or transfer of each gene sequence. Characterized in that the consensus genome information includes a common gene sequence region as a common gene sequence region and a gene sequence region that differs between strains as a unique gene sequence region of the strain, in the consensus genome information. Consensus Method of producing a genome information. A computer system for identifying Mycobacterium tuberculosis strains and mutations in a sample,
(1) Mycobacterium tuberculosis sample information storage unit for storing genome information of Mycobacterium tuberculosis in a sample input by a computer;
(2) a consensus genome information storage unit in which a computer stores information on Mycobacterium tuberculosis consensus genome;
(3) an alignment processing unit that performs alignment processing on the gene sequence included in the genome information of M. tuberculosis in the sample and the gene sequence included in the M. tuberculosis consensus genome information;
(4) a strain identification processing unit for identifying a specific strain by matching a specific gene sequence of M. tuberculosis in a sample with a specific gene sequence included in the consensus genome information of M. tuberculosis;
(5) a reference gene sequence identification processing unit for identifying a reference gene sequence of a specific strain included in the M. tuberculosis consensus genome information corresponding to the specific strain identified by the strain identification processing unit;
(6) a mutant gene information detection unit that compares the reference gene sequence with a gene sequence of Mycobacterium tuberculosis in a sample and identifies gene information different from the reference gene sequence as gene mutation information;
(7) an information output unit displaying the identification result of the strain of Mycobacterium tuberculosis in the sample, and gene mutation information;
Comprising
The consensus genome information of the Mycobacterium tuberculosis is Mycobacterium tuberculosis H37Rv strain, Mycobacterium tuberculosis KZN605 strain, Mycobacterium tuberculosis RGTB423 strain, Mycobacterium tuberculosis RGTB327 strain, Mycobacterium tuberculosis Erdman strain, Mycobacterium tuberculosis CTRI-2 strain, Mycobacterium tuberculosis CDC1551 strain, Mycobacterium tuberculosis CCDC5180 strain Mycobacterium tuberculosis CCDC5079 strain, Mycobacterium tuberculosis KZN4207 strain, Mycobacterium tuberculosis KZN1435 strain, Mycobacterium tuberculosis F11 strain, Mycobacterium tuberculosis H37Ra strain, related strain CIPT 140010059 strain, related strain GM041182 strain, related strain BCG str. Mexico strain, related strain BCG str. More than RDJ strain, related strain BCG str. Tokyo 172 strain, related strain BCG Pasteur 1173P2 partial or complete genome information, corrected for inversion or transposition of each gene sequence, aligned gene sequence Tuberculosis in a sample characterized in that the consensus genome information includes a common gene sequence region as a common gene sequence region and a gene sequence region different between strains as a unique gene sequence region of the strain Fungus A computer system for identifying strains and their gene mutations.

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