International Journal of Mycobacteriology (Jan 2019)

A multilocus sequence typing scheme for Mycobacterium abscessus complex (MAB-multilocus sequence typing) using whole-genome sequencing data

  • Michelle Wuzinski,
  • Aneta K Bak,
  • Aaron Petkau,
  • Walter H B. Demczuk,
  • Hafid Soualhine,
  • Meenu Kaushal Sharma

DOI
https://doi.org/10.4103/ijmy.ijmy_106_19
Journal volume & issue
Vol. 8, no. 3
pp. 273 – 280

Abstract

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Background:Mycobacterium abscessus is a rapid growing nontuberculous mycobacteria (NTM) and a clinically significant pathogen capable of causing variable infections in humans that are difficult to treat and may require months of therapy/surgical interventions. Like other NTMs, M. abscessus can be associated with outbreaks leading to complex investigations and treatment of affected cases. Typing schemes for bacterial pathogens provide numerous applications; including identifying chain of transmission and tracking genomic evolution, are lacking or limited for many NTMs including M. abscessus. Methods: We extended the existing scheme from PubMLST using whole-genome data for M. abscessus by extracting data for 15 genetic regions within the M. abscessus genome. A total of 168 whole genomes and 11 gene sequences were used to build this scheme (MAB-multilocus sequence typing [MLST]). Results: All seven genes from the PubMLST scheme, namely argH, cya, gnd, murC, pta, purH, and rpoB, were expanded by 10, 14, 13, 10, 13, 10, and 9 alleles, respectively. Another eight novel genes were added including hsp 65, erm(41), arr, rrs, rrl, gyrA, gyrB, and recA with 16, 16, 25, 7, 32, 35, 29, and 15 alleles, respectively, with 85 unique sequence types identified among all isolates. Conclusion: MAB-MLST can provide identification of M. abscessus complex to the subspecies level based on three genes and can provide antimicrobial resistance susceptibility prediction based on results from seven genes. MAB-MLST generated a total of 85 STs, resulting in subtyping of 90 additional isolates that could not be genotyped using PubMLST and yielding results comparable to whole-genome sequencing (WGS). Implementation of a Galaxy-based data analysis tool, MAB-MLST, that simplifies the WGS data and yet maintains a high discriminatory index that can aid in deciphering an outbreak has vast applicability for routine diagnostics.

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