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Comparisons of whole genome sequencing and phenotypic drug susceptibility testing for Mycobacterium tuberculosis causing MDR-TB and XDR-TB in Thailand.

ABSTRACT

Drug-resistant tuberculosis (TB) is a major public health problem. There is little information regarding genotypic-phenotypic association of anti-TB drugs, especially for second-line drugs. We compared phenotypic drug-susceptibility testing (DST) with predictions based on whole-genome sequence (WGS) data for 266 Mycobacterium tuberculosis (Mtb) isolates. Phenotypic DST used the standard proportional method. Clinical isolates of Mtb collected in Thailand during 1998-2013 comprised 51 drug sensitive, 6 mono-resistant, 2 multiple-resistant, 88 multi-drug resistant (MDR), 95 pre-extensively drug-resistant (pre-XDR) and 24 XDR strains. WGS analysis was performed using the computer programs PhyResSE and TB-Profiler. TB-Profiler had higher average concordance with phenotypic DST than did PhyResSE for both first-line (91.96% vs 91.4%) and second-line (79.67% vs 78.20%) anti-TB drugs. The average sensitivity for all anti-TB drugs was also higher (83.13% vs 72.08%) with slightly lower specificity (83.50% vs 86.68%). Regardless of the program used, isoniazid, rifampicin and amikacin had the highest concordance with phenotypic DST (96.2%, 93.5% and 95.6%, respectively). Ethambutol, ethionamide and fluoroquinolone group had the lowest concordance (87.34%, 81.44%, and 73.85% respectively). Concordance rates of ofloxacin (a second-generation fluoroquinolone), levofloxacin, moxifloxacin and gatifloxacin (third and fourth generation) were 91.79%, 76.62%, 72.64% and 57.35%, respectively. Discordance between phenotypic and WGS-based DSTs might be partly due to the choice of critical concentration and variable reproducibility of the phenotypic tests. It may also be due to limitations of the mutation databases (especially for the second-line drugs) and of the analysis program used. Mutations related to fluoroquinolone resistance, especially the later generations, need to be identified. Copyright © 2019. Published by Elsevier B.V.