Integrating informatics tools and portable sequencing technology for rapid detection of resistance to anti-tuberculous drugs

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dc.contributor.authorPhelan, Jody E.
dc.contributor.authorO’Sullivan, Denise M
dc.contributor.authorMachado, Diana
dc.contributor.authorRamos, Jorge
dc.contributor.authorOppong, Yaa E A
dc.contributor.authorCampino, Susana
dc.contributor.authorO’Grady, Justin
dc.contributor.authorMcNerney, Ruth
dc.contributor.authorHibberd, Martin L.
dc.contributor.authorViveiros, Miguel
dc.contributor.authorHuggett, Jim F
dc.contributor.authorClark, Taane G
dc.date.accessioned2019-12-10T09:03:39Z
dc.date.available2019-12-10T09:03:39Z
dc.date.issued2019-06-24
dc.date.updated2019-06-30T03:25:43Z
dc.description.abstractAbstract Background Mycobacterium tuberculosis resistance to anti-tuberculosis drugs is a major threat to global public health. Whole genome sequencing (WGS) is rapidly gaining traction as a diagnostic tool for clinical tuberculosis settings. To support this informatically, previous work led to the development of the widely used TBProfiler webtool, which predicts resistance to 14 drugs from WGS data. However, for accurate and rapid high throughput of samples in clinical or epidemiological settings, there is a need for a stand-alone tool and the ability to analyse data across multiple WGS platforms, including Oxford Nanopore MinION. Results We present a new command line version of the TBProfiler webserver, which includes hetero-resistance calling and will facilitate the batch processing of samples. The TBProfiler database has been expanded to incorporate 178 new markers across 16 anti-tuberculosis drugs. The predictive performance of the mutation library has been assessed using > 17,000 clinical isolates with WGS and laboratory-based drug susceptibility testing (DST) data. An integrated MinION analysis pipeline was assessed by performing WGS on 34 replicates across 3 multi-drug resistant isolates with known resistance mutations. TBProfiler accuracy varied by individual drug. Assuming DST as the gold standard, sensitivities for detecting multi-drug-resistant TB (MDR-TB) and extensively drug-resistant TB (XDR-TB) were 94% (95%CI 93–95%) and 83% (95%CI 79–87%) with specificities of 98% (95%CI 98–99%) and 96% (95%CI 95–97%) respectively. Using MinION data, only one resistance mutation was missed by TBProfiler, involving an insertion in the tlyA gene coding for capreomycin resistance. When compared to alternative platforms (e.g. Mykrobe predictor TB, the CRyPTIC library), TBProfiler demonstrated superior predictive performance across first- and second-line drugs. Conclusions The new version of TBProfiler can rapidly and accurately predict anti-TB drug resistance profiles across large numbers of samples with WGS data. The computing architecture allows for the ability to modify the core bioinformatic pipelines and outputs, including the analysis of WGS data sourced from portable technologies. TBProfiler has the potential to be integrated into the point of care and WGS diagnostic environments, including in resource-poor settings.
dc.identifier.apacitationPhelan, Jody E., , Machado, D., Ramos, J., Oppong, Y. E. A., Campino, S., ... Clark, T. G. (2019). Integrating informatics tools and portable sequencing technology for rapid detection of resistance to anti-tuberculous drugs. http://hdl.handle.net/11427/30678en_ZA
dc.identifier.chicagocitationPhelan, Jody E., , Diana Machado, Jorge Ramos, Yaa E A Oppong, Susana Campino, , et al "Integrating informatics tools and portable sequencing technology for rapid detection of resistance to anti-tuberculous drugs." (2019) http://hdl.handle.net/11427/30678en_ZA
dc.identifier.citationGenome Medicine. 2019 Jun 24;11(1):41
dc.identifier.ris TY - Journal Article AU - Phelan, Jody E. AU - O’Sullivan, Denise M AU - Machado, Diana AU - Ramos, Jorge AU - Oppong, Yaa E A AU - Campino, Susana AU - O’Grady, Justin AU - McNerney, Ruth AU - Hibberd, Martin L. AU - Viveiros, Miguel AU - Huggett, Jim F AU - Clark, Taane G AB - Abstract Background Mycobacterium tuberculosis resistance to anti-tuberculosis drugs is a major threat to global public health. Whole genome sequencing (WGS) is rapidly gaining traction as a diagnostic tool for clinical tuberculosis settings. To support this informatically, previous work led to the development of the widely used TBProfiler webtool, which predicts resistance to 14 drugs from WGS data. However, for accurate and rapid high throughput of samples in clinical or epidemiological settings, there is a need for a stand-alone tool and the ability to analyse data across multiple WGS platforms, including Oxford Nanopore MinION. Results We present a new command line version of the TBProfiler webserver, which includes hetero-resistance calling and will facilitate the batch processing of samples. The TBProfiler database has been expanded to incorporate 178 new markers across 16 anti-tuberculosis drugs. The predictive performance of the mutation library has been assessed using > 17,000 clinical isolates with WGS and laboratory-based drug susceptibility testing (DST) data. An integrated MinION analysis pipeline was assessed by performing WGS on 34 replicates across 3 multi-drug resistant isolates with known resistance mutations. TBProfiler accuracy varied by individual drug. Assuming DST as the gold standard, sensitivities for detecting multi-drug-resistant TB (MDR-TB) and extensively drug-resistant TB (XDR-TB) were 94% (95%CI 93–95%) and 83% (95%CI 79–87%) with specificities of 98% (95%CI 98–99%) and 96% (95%CI 95–97%) respectively. Using MinION data, only one resistance mutation was missed by TBProfiler, involving an insertion in the tlyA gene coding for capreomycin resistance. When compared to alternative platforms (e.g. Mykrobe predictor TB, the CRyPTIC library), TBProfiler demonstrated superior predictive performance across first- and second-line drugs. Conclusions The new version of TBProfiler can rapidly and accurately predict anti-TB drug resistance profiles across large numbers of samples with WGS data. The computing architecture allows for the ability to modify the core bioinformatic pipelines and outputs, including the analysis of WGS data sourced from portable technologies. TBProfiler has the potential to be integrated into the point of care and WGS diagnostic environments, including in resource-poor settings. DA - 2019-06-24 DB - OpenUCT DP - University of Cape Town KW - Drug resistance KW - Tuberculosis KW - Diagnostics KW - Drug-susceptibility testing KW - MDR-TB KW - XDR-TB KW - WGS LK - https://open.uct.ac.za PY - 2019 T1 - Integrating informatics tools and portable sequencing technology for rapid detection of resistance to anti-tuberculous drugs TI - Integrating informatics tools and portable sequencing technology for rapid detection of resistance to anti-tuberculous drugs UR - http://hdl.handle.net/11427/30678 ER - en_ZA
dc.identifier.urihttps://doi.org/10.1186/s13073-019-0650-x
dc.identifier.urihttp://hdl.handle.net/11427/30678
dc.identifier.vancouvercitationPhelan Jody E, , Machado D, Ramos J, Oppong YEA, Campino S, et al. Integrating informatics tools and portable sequencing technology for rapid detection of resistance to anti-tuberculous drugs. 2019; http://hdl.handle.net/11427/30678.en_ZA
dc.language.rfc3066en
dc.rights.holderThe Author(s).
dc.subjectDrug resistance
dc.subjectTuberculosis
dc.subjectDiagnostics
dc.subjectDrug-susceptibility testing
dc.subjectMDR-TB
dc.subjectXDR-TB
dc.subjectWGS
dc.titleIntegrating informatics tools and portable sequencing technology for rapid detection of resistance to anti-tuberculous drugs
dc.typeJournal Article
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