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Dissecting whole-genome sequencing-based online tools for predicting resistance in Mycobacterium tuberculosis: can we use them for clinical decision guidance?

2018-03-27Journal article Restricted access
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dc.contributor.authorMacedo, Rita
dc.contributor.authorNunes, Alexandra
dc.contributor.authorPortugal, Isabel
dc.contributor.authorDuarte, Sílvia
dc.contributor.authorVieira, Luís
dc.contributor.authorGomes, João Paulo
dc.date.accessioned2019-03-20T17:49:09Z
dc.date.available2019-03-20T17:49:09Z
dc.date.issued2018-03-27
dc.description.abstractWhole-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.pt_PT
dc.description.sponsorshipThis work was supported by Centre for Toxicogenomics and Human Health (ToxOmics, ref. UID/BIM/00009/2013) and GenomePT (ref.POCI-01-0145-FEDER-022184) from Fundação para a Ciência e Tecnologia, Portugal.pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.citationTuberculosis (Edinb). 2018 May;110:44-51. doi: 10.1016/j.tube.2018.03.009. Epub 2018 Mar 27pt_PT
dc.identifier.doi10.1016/j.tube.2018.03.009pt_PT
dc.identifier.issn1472-9792
dc.identifier.urihttp://hdl.handle.net/10400.18/6253
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.publisherElsevierpt_PT
dc.relation.publisherversionhttps://www.sciencedirect.com/science/article/pii/S1472979218300672?via%3Dihubpt_PT
dc.subjectWhole-genome Sequencingpt_PT
dc.subjectMultidrug-resistant Tuberculosispt_PT
dc.subjectTB Profilerpt_PT
dc.subjectMykrobe Predictorpt_PT
dc.subjectPhyResSEpt_PT
dc.subjectTGS-TBpt_PT
dc.subjectInfecções Respiratóriaspt_PT
dc.titleDissecting whole-genome sequencing-based online tools for predicting resistance in Mycobacterium tuberculosis: can we use them for clinical decision guidance?pt_PT
dc.typejournal article
dspace.entity.typePublication
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/5876/UID%2FBIM%2F00009%2F2013/PT
oaire.citation.endPage51pt_PT
oaire.citation.startPage44pt_PT
oaire.citation.titleTuberculosis (Edinb)pt_PT
oaire.citation.volume110pt_PT
oaire.fundingStream5876
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.nameFundação para a Ciência e a Tecnologia
rcaap.rightsembargoedAccesspt_PT
rcaap.typearticlept_PT
relation.isProjectOfPublicatione9cc9728-4f09-4e3a-b30d-53d4429986fb
relation.isProjectOfPublication.latestForDiscoverye9cc9728-4f09-4e3a-b30d-53d4429986fb

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