TY - JOUR
T1 - Dissecting whole-genome sequencing-based online tools for predicting resistance in Mycobacterium tuberculosis
T2 - can we use them for clinical decision guidance?
AU - Macedo, Rita
AU - Nunes, Alexandra
AU - Portugal, Isabel
AU - Duarte, Sílvia
AU - Vieira, Luís
AU - Gomes, João Paulo
N1 - Publisher Copyright:
© 2018 Elsevier Ltd
PY - 2018/5
Y1 - 2018/5
N2 - 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.
AB - 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.
KW - Multidrug-resistant tuberculosis
KW - Mykrobe predictor
KW - PhyResSE
KW - TB profiler
KW - TGS-TB
KW - Whole-genome sequencing
UR - http://www.scopus.com/inward/record.url?scp=85044567113&partnerID=8YFLogxK
U2 - 10.1016/j.tube.2018.03.009
DO - 10.1016/j.tube.2018.03.009
M3 - Article
C2 - 29779772
AN - SCOPUS:85044567113
SN - 1472-9792
VL - 110
SP - 44
EP - 51
JO - Tuberculosis
JF - Tuberculosis
ER -