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Clonality and Micro-Diversity of a Nationwide Spreading Genotype of Mycobacterium tuberculosis in Japan

Mycobacterium tuberculosis transmission routes can be estimated from genotypic analysis of clinical isolates from patients. In Japan, still a middle-incidence country of TB, a unique genotype strain designated as ‘M-strain’ has been isolated nationwide recently. To ascertain the history of the wide...

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Detalles Bibliográficos
Autores principales: Wada, Takayuki, Iwamoto, Tomotada, Tamaru, Aki, Seto, Junji, Ahiko, Tadayuki, Yamamoto, Kaori, Hase, Atushi, Maeda, Shinji, Yamamoto, Taro
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4348518/
https://www.ncbi.nlm.nih.gov/pubmed/25734518
http://dx.doi.org/10.1371/journal.pone.0118495
Descripción
Sumario:Mycobacterium tuberculosis transmission routes can be estimated from genotypic analysis of clinical isolates from patients. In Japan, still a middle-incidence country of TB, a unique genotype strain designated as ‘M-strain’ has been isolated nationwide recently. To ascertain the history of the wide spread of the strain, 10 clinical isolates from different areas were subjected to genome-wide analysis based on deep sequencers. Results show that all isolates possessed common mutations to those of referential strains. The greatest number of accumulated single nucleotide variants (SNVs) from the oldest coalescence was 13 nucleotides, indicating high clonality of these isolates. When an SNV common to the isolates was used as a surrogate marker of the clone, authentic clonal isolates with variation in a reliable subset of variable number of tandem repeat (VNTR) genotyping method can be selected successfully from clinical isolates populations of M. tuberculosis. When the authentic clones can also be assigned to sub-clonal groups by SNVs derived from the genomic comparison, they are classifiable into three sub-clonal groups with a bias of geographical origins. Feedback from genomic analysis of clinical isolates of M. tuberculosis to genotypic markers will be an efficient strategy for the big data in various settings for public health actions against TB.