BackgroundThe World Health Organization recommends universal drug susceptibility testing for Mycobacterium tuberculosis complex to guide treatment decisions and improve outcomes. We assessed whether DNA sequencing can accurately predict antibiotic susceptibility profiles for first-line anti-tuberculosis drugs. MethodsWhole-genome sequences and associated phenotypes to isoniazid, rifampicin, ethambutol and pyrazinamide were obtained for isolates from 16 countries across six continents. For each isolate, mutations associated with drug-resistance and drug-susceptibility were identified across nine genes, and individual phenotypes were predicted unless mutations of unknown association were also present. To identify how whole-genome sequencing might direct first-line drug therapy, complete susceptibility profiles were predicted. These were predicted to be pan-susceptible if predicted susceptible to isoniazid and to other drugs, or contained mutations of unknown association in genes affecting these other drugs. We simulated how negative predictive value changed with drug-resistance prevalence.Results10,209 isolates were analysed. The greatest proportion of phenotypes were predicted for rifampicin (9,660/10,130; (95.4%)) and the lowest for ethambutol (8,794/9,794; (89.8%)). Isoniazid, rifampicin, ethambutol and pyrazinamide resistance was correctly predicted with 97.1%, 97.5% 94.6% and 91.3% sensitivity, and susceptibility with 99.0%, 98.8%, 93.6% and 96.8% specificity, respectively. 5,250 (89.5%) drug profiles were correctly predicted for 5,865/7,516 (78.0%) isolates with complete phenotypic profiles. Among these, 3,952/4,037 (97.9%) predictions of pan-susceptibility were correct. The negative predictive value for 97.5% of simulated drug profiles exceeded 95% where the prevalence of drug-resistance was below 47.0%. ConclusionsPhenotypic testing for first-line drugs can be phased down in favour of DNA sequencing to guide anti- tuberculosis drug therapy.

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BackgroundWhole-genome sequencing is increasingly used in clinical diagnosis of tuberculosis and study of Mycobacterium tuberculosis complex (MTC). MTC consists of several genetically homogenous mycobacteria species which can cause tuberculosis in humans and animals. Regions of difference (RDs) are commonly regarded as gold standard genetic markers for MTC classification.ResultsWe develop RD-Analyzer, a tool that can accurately infer the species and lineage of MTC isolates from sequence reads based on the presence and absence of a set of 31 RDs. Applied on a publicly available diverse set of 377 sequenced MTC isolates from known major species and lineages, RD-Analyzer achieved an accuracy of 98.14 % (370/377) in species prediction and a concordance of 98.47 % (257/261) in Mycobacterium tuberculosis lineage prediction compared to predictions based on single nucleotide polymorphism markers. By comparing respective sequencing read depths on each genomic position between isolates of different sublineages, we were able to identify the known RD markers in different sublineages of Lineage 4 and provide support for six potential delineating markers having high sensitivities and specificities for sublineage prediction. An extended version of RD-Analyzer was thus developed to allow user-defined RDs for lineage prediction.ConclusionsRD-Analyzer is a useful and accurate tool for species, lineage and sublineage prediction using known RDs of MTC from sequence reads and is extendable to accepting user-defined RDs for analysis. RD-Analyzer is written in Python and is freely available at https://github.com/xiaeryu/RD-Analyzer.Electronic supplementary materialThe online version of this article (doi:10.1186/s12864-016-3213-1) contains supplementary material, which is available to authorized users.