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• W2795065364 abstract "Whole-genome sequencing (WGS)-based bioinformatics platforms for the rapid prediction of resistance will soon be implemented in the Tuberculosis (TB) laboratory, but their accuracy assessment still needs to be strengthened. Here, we fully-sequenced a total of 54 multidrug-resistant (MDR) and five susceptible TB strains and performed, for the first time, a simultaneous evaluation of the major four free online platforms (TB Profiler, PhyResSE, Mykrobe Predictor and TGS-TB). Overall, the sensitivity of resistance prediction ranged from 84.3% using Mykrobe predictor to 95.2% using TB profiler, while specificity was higher and homogeneous among platforms. TB profiler revealed the best performance robustness (sensitivity, specificity, PPV and NPV above 95%), followed by TGS-TB (all parameters above 90%). We also observed a few discrepancies between phenotype and genotype, where, in some cases, it was possible to pin-point some “candidate” mutations (e.g., in the rpsL promoter region) highlighting the need for their confirmation through mutagenesis assays and potential review of the anti-TB genetic databases. The rampant development of the bioinformatics algorithms and the tremendously reduced time-frame until the clinician may decide for a definitive and most effective treatment will certainly trigger the technological transition where WGS-based bioinformatics platforms could replace phenotypic drug susceptibility testing for TB." @default.
• W2795065364 created "2018-04-06" @default.
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• W2795065364 date "2018-05-01" @default.
• W2795065364 modified "2023-10-16" @default.
• W2795065364 title "Dissecting whole-genome sequencing-based online tools for predicting resistance in Mycobacterium tuberculosis : can we use them for clinical decision guidance?" @default.
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• W2795065364 doi "https://doi.org/10.1016/j.tube.2018.03.009" @default.
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• W2795065364 hasPublicationYear "2018" @default.
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