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. 2018 Dec 21;63(1):e01204-18.
doi: 10.1128/AAC.01204-18. Print 2019 Jan.

Whole-Genome Sequencing for Predicting Clarithromycin Resistance in Mycobacterium abscessus

Samuel Lipworth #  1   2 , Natasha Hough #  3 , Laura Leach  4 , Marcus Morgan  4 , Katie Jeffery  4 , Monique Andersson  4 , Esther Robinson  5 , E Grace Smith  5 , Derrick Crook  3   2 , Tim Peto  3   2 , Timothy Walker  3
Affiliations

Whole-Genome Sequencing for Predicting Clarithromycin Resistance in Mycobacterium abscessus

Samuel Lipworth et al. Antimicrob Agents Chemother. .

Abstract

Mycobacterium abscessus is emerging as an important pathogen in chronic lung diseases, with concern regarding patient-to-patient transmission. The recent introduction of routine whole-genome sequencing (WGS) as a replacement for existing reference techniques in England provides an opportunity to characterize the genetic determinants of resistance. We conducted a systematic review to catalogue all known resistance-determining mutations. This knowledge was used to construct a predictive algorithm based on mutations in the erm(41) and rrl genes which was tested on a collection of 203 sequentially acquired clinical isolates for which there were paired genotype/phenotype data. A search for novel resistance-determining mutations was conducted using a heuristic algorithm. The sensitivity of existing knowledge for predicting resistance in clarithromycin was 95% (95% confidence interval [CI], 89 to 98%), and the specificity was 66% (95% CI, 54 to 76%). The subspecies alone was a poor predictor of resistance to clarithromycin. Eight potential new resistance-conferring single nucleotide polymorphisms (SNPs) were identified. WGS demonstrated probable resistance-determining SNPs in regions that the NTM-DR line probe cannot detect. These mutations are potentially clinically important, as they all occurred in samples that were predicted to be inducibly resistant and for which a macrolide would therefore currently be indicated. We were unable to explain all resistance, raising the possibility of the involvement of other as yet unidentified genes.

Keywords: macrolides; nontuberculous mycobacteria; whole-genome sequencing.

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Figures

FIG 1
FIG 1
Decision algorithm for predicting drug resistance in M. abscessus based on the literature search, with the numbers of isolates meeting each predictive criterion shown. Numbers in parentheses represent the number resistant/the number sensitive. *, 4 isolates had intermediate susceptibility; pos, position.
FIG 2
FIG 2
Flow diagram showing the stages of the systematic literature search.
See this image and copyright information in PMC

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