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MIRU-VNTR 15 loci capability in diagnosis of Beijing M. Tuberculosis strains in comparison with Real Time PCR.

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Beijing strain has great importance among Mycobacterium tuberculosis (MTB) genotypes due to their drug resistance and pathogenicity. Determination of MTB genotypes and comparison of MIRU-VNTR 15 loci and real-time PCR… Click to show full abstract

Beijing strain has great importance among Mycobacterium tuberculosis (MTB) genotypes due to their drug resistance and pathogenicity. Determination of MTB genotypes and comparison of MIRU-VNTR 15 loci and real-time PCR methods for Beijing family identification was the main objective in this study. This study was conducted on 92 confirmed MTB isolates, 31 and 61 of which previously were determined by real- time PCR as Beijing and non-Beijing, respectively. Allelic diversity, clustering rate, phylogenetic tree, clonal complexes and molecular genotypes of isolates were determined by MIRU-VNTR 15 loci on its online software. In addition MIRU-VNTR 15 loci were performed for 16 non-tuberculosis isolates. Concordance between MIRU-VNTR 15 loci and real Time PCR in determination of Beijing genotype was 95.6(89.2-98.8). 74 different pattern of MIRU-VNTR were detected in 92 MTB isolates. 69 patterns were unique and 5 clusters were determined. Largest clusters contain 11 and 6 members. The clustering rate was 19.56%. Among 15 loci, Mtub04 and MIRU10 have the highest and MIRU04 had the lowest discriminatory power. In non-Beijing isolates, New1 and Delhi/CAS with 25% and 16.3% were the most prevalent MTB genotypes. None of the non-Tuberculosis isolates had the complete MIRU-VNTR 15 loci pattern. The results of this study showed that MIRU-VNTR 15 loci, in addition to being able to differentiate MTB genotypes, can distinguish non-tuberculosis species from MTB strains, but for the exact differentiation of Beijing MTB genotypes, it may be necessary to increase the patterns known in MIRU-VNTR data base.

Keywords: miru vntr; real time; vntr; vntr loci; tuberculosis

Journal Title: Cellular and molecular biology
Year Published: 2019

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