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

Detalhes bibliográficos
Autor(a) principal: Macedo, Rita
Data de Publicação: 2018
Outros Autores: Nunes, Alexandra, Portugal, Isabel, Duarte, Sílvia, Vieira, Luís, Gomes, João Paulo
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10400.18/6253
Resumo: 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.
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spelling Dissecting whole-genome sequencing-based online tools for predicting resistance in Mycobacterium tuberculosis: can we use them for clinical decision guidance?Whole-genome SequencingMultidrug-resistant TuberculosisTB ProfilerMykrobe PredictorPhyResSETGS-TBInfecções RespiratóriasWhole-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.This 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.ElsevierRepositório Científico do Instituto Nacional de SaúdeMacedo, RitaNunes, AlexandraPortugal, IsabelDuarte, SílviaVieira, LuísGomes, João Paulo2019-03-20T17:49:09Z2018-03-272018-03-27T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10400.18/6253engTuberculosis (Edinb). 2018 May;110:44-51. doi: 10.1016/j.tube.2018.03.009. Epub 2018 Mar 271472-979210.1016/j.tube.2018.03.009info:eu-repo/semantics/embargoedAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-07-20T15:41:17Zoai:repositorio.insa.pt:10400.18/6253Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T18:40:52.773473Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse
dc.title.none.fl_str_mv Dissecting whole-genome sequencing-based online tools for predicting resistance in Mycobacterium tuberculosis: can we use them for clinical decision guidance?
title Dissecting whole-genome sequencing-based online tools for predicting resistance in Mycobacterium tuberculosis: can we use them for clinical decision guidance?
spellingShingle Dissecting whole-genome sequencing-based online tools for predicting resistance in Mycobacterium tuberculosis: can we use them for clinical decision guidance?
Macedo, Rita
Whole-genome Sequencing
Multidrug-resistant Tuberculosis
TB Profiler
Mykrobe Predictor
PhyResSE
TGS-TB
Infecções Respiratórias
title_short Dissecting whole-genome sequencing-based online tools for predicting resistance in Mycobacterium tuberculosis: can we use them for clinical decision guidance?
title_full Dissecting whole-genome sequencing-based online tools for predicting resistance in Mycobacterium tuberculosis: can we use them for clinical decision guidance?
title_fullStr Dissecting whole-genome sequencing-based online tools for predicting resistance in Mycobacterium tuberculosis: can we use them for clinical decision guidance?
title_full_unstemmed Dissecting whole-genome sequencing-based online tools for predicting resistance in Mycobacterium tuberculosis: can we use them for clinical decision guidance?
title_sort Dissecting whole-genome sequencing-based online tools for predicting resistance in Mycobacterium tuberculosis: can we use them for clinical decision guidance?
author Macedo, Rita
author_facet Macedo, Rita
Nunes, Alexandra
Portugal, Isabel
Duarte, Sílvia
Vieira, Luís
Gomes, João Paulo
author_role author
author2 Nunes, Alexandra
Portugal, Isabel
Duarte, Sílvia
Vieira, Luís
Gomes, João Paulo
author2_role author
author
author
author
author
dc.contributor.none.fl_str_mv Repositório Científico do Instituto Nacional de Saúde
dc.contributor.author.fl_str_mv Macedo, Rita
Nunes, Alexandra
Portugal, Isabel
Duarte, Sílvia
Vieira, Luís
Gomes, João Paulo
dc.subject.por.fl_str_mv Whole-genome Sequencing
Multidrug-resistant Tuberculosis
TB Profiler
Mykrobe Predictor
PhyResSE
TGS-TB
Infecções Respiratórias
topic Whole-genome Sequencing
Multidrug-resistant Tuberculosis
TB Profiler
Mykrobe Predictor
PhyResSE
TGS-TB
Infecções Respiratórias
description 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.
publishDate 2018
dc.date.none.fl_str_mv 2018-03-27
2018-03-27T00:00:00Z
2019-03-20T17:49:09Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
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dc.identifier.uri.fl_str_mv http://hdl.handle.net/10400.18/6253
url http://hdl.handle.net/10400.18/6253
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv Tuberculosis (Edinb). 2018 May;110:44-51. doi: 10.1016/j.tube.2018.03.009. Epub 2018 Mar 27
1472-9792
10.1016/j.tube.2018.03.009
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dc.publisher.none.fl_str_mv Elsevier
publisher.none.fl_str_mv Elsevier
dc.source.none.fl_str_mv reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
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