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

Emerg Microbes Infect. 2017 Jul 26;6(7):e68. doi: 10.1038/emi.2017.58.

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.

MeSH terms

  • Bacterial Typing Techniques / methods*
  • Beijing
  • DNA, Bacterial
  • Genetic Variation
  • Genotype
  • Humans
  • Minisatellite Repeats / genetics*
  • Mycobacterium tuberculosis / classification*
  • Mycobacterium tuberculosis / genetics*
  • Polymorphism, Single Nucleotide
  • Repetitive Sequences, Nucleic Acid*
  • Tuberculosis / microbiology
  • Tuberculosis / transmission

Substances

  • DNA, Bacterial