Abstract
Whole-genome sequencing (WGS) has the potential to accelerate drug-susceptibility testing (DST) to design appropriate regimens for drug-resistant tuberculosis (TB). Several recently developed automated software tools promise to standardize the analysis and interpretation of WGS data. We assessed five tools (CASTB, KvarQ, Mykrobe Predictor TB, PhyResSE, and TBProfiler) with regards to DST and phylogenetic lineage classification, which we compared with phenotypic DST, Sanger sequencing, and traditional typing results for a collection of 91 strains. The lineage classifications by the tools generally only differed in the resolution of the results. However, some strains could not be classified at all and one strain was misclassified. The sensitivities and specificities for isoniazid and rifampicin resistance of the tools were high, whereas the results for ethambutol, pyrazinamide, and streptomycin resistance were more variable. False-susceptible DST results were mainly due to missing mutations in the resistance catalogues that the respective tools employed for data interpretation. Notably, we also found cases of false-resistance because of the misclassification of polymorphisms as resistance mutations. In conclusion, the performance of current WGS analysis tools for DST is highly variable. Sustainable business models and a shared, high-quality catalogue of resistance mutations are needed to ensure the clinical utility of these tools.
Highlights
This situation is exacerbated by the fact that conventional, phenotypic drug-susceptibility testing (DST) can take weeks or months because of the slow growth rate of MTBC3
Paired-end fastq files have to be merged for KvarQ and Mykrobe Predictor TB, which may represent a challenge for some users
We performed the most comprehensive comparison of five software pipelines for the automated analysis and interpretation of whole-genome sequencing (WGS) data of Mycobacterium tuberculosis complex (MTBC) strains to date
Summary
This situation is exacerbated by the fact that conventional, phenotypic drug-susceptibility testing (DST) can take weeks or months because of the slow growth rate of MTBC3 Targeted genotypic assays, such as line probe assays or the Cepheid Xpert MTB/RIF, have been developed to provide DST results within hours or days[4]. These assays only target the most frequent resistance mutations for a limited number of drugs. Variants (i.e. SNPs, insertions or deletions) have to be identified accurately These variants have to be interpreted correctly Using a collection of 91 clinical strains with resistance mutations that were confirmed by classical Sanger sequencing, we set out to assess the performance and functionalities of these tools
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