Journal of Global Antimicrobial Resistance (Sep 2020)

Detection of a novel mutation in the rpoB gene in a multidrug resistant Mycobacterium tuberculosis isolate using whole genome next generation sequencing

  • Nilma Hirani,
  • Ameeta Joshi,
  • Siddharth Anand,
  • Abhay Chowdhary,
  • Karthik Ganesan,
  • Meenal Agarwal,
  • Nikhil Phadke

Journal volume & issue
Vol. 22
pp. 270 – 274

Abstract

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Background: Mycobacterium tuberculosis (Mtb) drug resistance is a global concern. Moreover, multiple drug resistant (MDR), extensively drug resistant (XDR), and totally drug resistant (TDR) Mtb cases are on the rise in developing countries like India. Most of these cases are identified only 3–6 months after initiation of treatment owing to incomplete/failed clinical response and incomplete information from phenotypic drug resistance assays and/or targeted Mtb mutation analysis. Here, we report the development of an in-house whole genome sequencing (WGS) assay and bioinformatics pipeline that helped resolve the phenotype-genotype discrepancy in a clinical isolate. Methodology and results: A sample from a suspected drug resistant Mtb case tested by line probe assay (LPA) showed the absence of both the mutant and wild type alleles for an rpoB gene mutation site. An in-house next generation sequencing (NGS) assay was used for WGS of this isolate. Bioinformatics analysis revealed that the isolate harboured a novel insertional mutation in the 81-bp hotspot region of the rpoB gene and a S315T mutation in the katG gene, which could explain resistance to rifampicin and isoniazid, respectively. These results correlated with the clinical diagnosis, LPA, solid culture drug susceptibility testing, and pyrosequencing carried out on the sample. The WGS data also provided information regarding the isolate’s lineage and indicated an absence of known mutations conferring resistance to other antitubercular drugs. Conclusion: WGS is a highly sensitive, specific, and unbiased approach for identification of all possible drug resistance-conferring mutations, which can help clinicians make more informed treatment-related decisions.

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