ArticleEmerging microbes & infections2017
A quantitative and efficient approach to select MIRU-VNTR loci based on accumulation of the percentage differences of strains for discriminating divergent Mycobacterium tuberculosis sublineages.
Article in Emerging microbes & infections, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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7 citing papers in PubMed.
- The shortcut of mycobacterial interspersed repetitive unit-variable number tandem repeat typing forFrontiers in microbiology · 2022Article
- Molecular epidemiology of clinical Mycobacterium tuberculosis complex isolates in South Omo, Southern Ethiopia.BMC infectious diseases · 2020Article
- Enhancing the differentiation of specific genotypes in Mycobacterium tuberculosis population.Scientific reports · 2019Article
- Introducing the Best Six Loci in Mycobacterial Interspersed Repetitive Unit-Variable-Number Tandem Repeat (MIRU-VNTR) Typing forReports of biochemistry & molecular biology · 2019Article
- Characterization of Mycobacterium tuberculosis strains in Beijing, China: drug susceptibility phenotypes and Beijing genotype family transmission.BMC infectious diseases · 2018Article
- Have compensatory mutations facilitated the current epidemic of multidrug-resistant tuberculosis?Emerging microbes & infections · 2018Article
- Clustering and recent transmission ofInfection and drug resistance · 2018Article
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13 authors.
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Abstract
Although several optimal mycobacterial interspersed repetitive units-variable number tandem repeat (MIRU-VNTR) loci have been suggested for genotyping homogenous Mycobacterium tuberculosis, including the Beijing genotype, a more efficient and convenient selection strategy for identifying optimal VNTR loci is needed. Here 281 M. tuberculosis isolates were analyzed. Beijing genotype and non-Beijing genotypes were identified, as well as Beijing sublineages, according to single nucleotide polymorphisms. A total of 22 MIRU-VNTR loci were used for genotyping. To efficiently select optimal MIRU-VNTR loci, we established accumulations of percentage differences (APDs) between the strains among the different genotypes. In addition, we constructed a minimum spanning tree for clustering analysis of the VNTR profiles. Our findings showed that eight MIRU-VNTR loci displayed disparities in h values of ≥0.2 between the Beijing genotype and non-Beijing genotype isolates. To efficiently discriminate Beijing and non-Beijing genotypes, an optimal VNTR set was established by adding loci with APDs ranging from 87.2% to 58.8%, resulting in the construction of a nine-locus set. We also found that QUB11a is a powerful locus for separating ST10s (including ST10, STF and STCH1) and ST22s (including ST22 and ST8) strains, whereas a combination of QUB11a, QUB4156, QUB18, Mtub21 and QUB26 could efficiently discriminate Beijing sublineages. Our findings suggested that two nine-locus sets were not only efficient for distinguishing the Beijing genotype from non-Beijing genotype strains, but were also suitable for sublineage genotyping with different discriminatory powers. These results indicate that APD represents a quantitative and efficient approach for selecting MIRU-VNTR loci to discriminate between divergent M. tuberculosis sublineages.
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