Scientific Reports (May 2022)

Characterisation of drug-resistant Mycobacterium tuberculosis mutations and transmission in Pakistan

  • Gary Napier,
  • Anwar Sheed Khan,
  • Abdul Jabbar,
  • Muhammad Tahir Khan,
  • Sajid Ali,
  • Muhammad Qasim,
  • Noor Mohammad,
  • Rumina Hasan,
  • Zahra Hasan,
  • Susana Campino,
  • Sajjad Ahmad,
  • Baharullah Khattak,
  • Simon J. Waddell,
  • Taj Ali Khan,
  • Jody E. Phelan,
  • Taane G. Clark

DOI
https://doi.org/10.1038/s41598-022-11795-4
Journal volume & issue
Vol. 12, no. 1
pp. 1 – 10

Abstract

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Abstract Tuberculosis, caused by Mycobacterium tuberculosis, is a high-burden disease in Pakistan, with multi-drug (MDR) and extensive-drug (XDR) resistance, complicating infection control. Whole genome sequencing (WGS) of M. tuberculosis is being used to infer lineages (strain-types), drug resistance mutations, and transmission patterns—all informing infection control and clinical decision making. Here we analyse WGS data on 535 M. tuberculosis isolates sourced across Pakistan between years 2003 and 2020, to understand the circulating strain-types and mutations related to 12 anti-TB drugs, as well as identify transmission clusters. Most isolates belonged to lineage 3 (n = 397; 74.2%) strain-types, and were MDR (n = 328; 61.3%) and (pre-)XDR (n = 113; 21.1%). By inferring close genomic relatedness between isolates (< 10-SNPs difference), there was evidence of M. tuberculosis transmission, with 55 clusters formed consisting of a total of 169 isolates. Three clusters consist of M. tuberculosis that are similar to isolates found outside of Pakistan. A genome-wide association analysis comparing ‘transmitted’ and ‘non-transmitted’ isolate groups, revealed the nusG gene as most significantly associated with a potential transmissible phenotype (P = 5.8 × 10–10). Overall, our study provides important insights into M. tuberculosis genetic diversity and transmission in Pakistan, including providing information on circulating drug resistance mutations for monitoring activities and clinical decision making.