GHTM

Global Health and Tropical Medicine

  • GHTM
    • Vision
    • Mission
    • Governance
    • Scientific Advisory Board
  • News
    • Outreach
    • Events
      • GHTM Sessions
      • Workshops
    • Articles
    • Jobs
  • Research
    • Cross-cutting issues
      • Global Pathogen Dispersion and Population Mobility
      • Drug Discovery and Drug Resistance
      • Diagnostics
      • Public Health Information
      • Fair Research Partnerships
    • Research Groups
      • PPS – Population health, policies and services
      • THOP – TB, HIV and opportunistic diseases and pathogens
      • VBD – Vector borne diseases and pathogens
      • IHC – Individual health care
    • Research in numbers
      • 2020
      • 2019
      • 2018
      • 2017
    • Projects
      • Ongoing Projects
    • Members
      • Population health, policies and services
        • PPS PhD members
        • PPS non PhD members
      • TB, HIV and opportunistic diseases and pathogens
        • THOP PhD members
        • THOP non PhD members
      • Vector-borne diseases and pathogens
        • VBD PhD members
        • VBD non PhD members
      • Individual Health Care
        • IHC PhD members
        • IHC non PhD members
      • Technical / administrative support
  • Publications
  • Education
    • Master Theses
    • PhD Theses
  • Services
Home / Publicações / Integrating informatics tools and portable sequencing technology for rapid detection of resistance to anti-tuberculous drugs

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

  • Autores: Phelan JE, O’Sullivan DM, Machado D, Ramos J, Oppong YEA, Campino L, McNerney R, Hibberd ML, Viveiros M, Huggett JF, Clark TG
  • Ano de Publicação: 2019
  • Journal: Genome Medicine
  • Link: https://genomemedicine.biomedcentral.com/articles/10.1186/s13073-019-0650-x
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.

Share this:

  • Click to share on Facebook (Opens in new window)
  • Click to share on Twitter (Opens in new window)
  • Click to share on LinkedIn (Opens in new window)
  • Click to share on Pinterest (Opens in new window)
  • Click to share on WhatsApp (Opens in new window)
  • Click to print (Opens in new window)

Events

PhD student from GHTM attended the India|EMBO Lecture Course

Ronise Silva, a PhD student under the Tropical Diseases and Global Health program at the Institute … [Read More...]

Registration for “Python applied to Biomedical Sciences” course is open!

GHTM informs that registration for the introduction course on Python programming language is … [Read More...]

BIOTROP, the biobank of GHTM-IHMT-NOVA, represented at the inauguration of the European headquarters of MIRRI-ERIC

  The Coordinator of the Biotropical Resources biobank (BIOTROP), Ana Paula Arez, and the … [Read More...]

Ciara O’Sullivan visited GHTM-IHMT and strengthened international relationship

  As part of the RESMALDETECT Exploratory Project, the GHTM-IHMT received a visit from Ciara … [Read More...]

Call for PhD Studentships

The Institute of Hygiene and Tropical Medicine (IHMT), Universidade Nova de Lisboa (NOVA), through … [Read More...]

IHMT | GHTM – APPLICATIONS ARE OPEN!

IHMT | GHTM - Applications are open for three research vacancies:   One position - PhD … [Read More...]

About GHTM

GHTM is a R&D Center that brings together researchers from IHMT with a track record in Tropical Medicine and International/Global Health. It aims at strengthening Portugal's role as a leading partner in the development and implementation of a global health research agenda. Our evidence-based interventions contribute to the promotion of equity in health and to improve the health of populations.

Contacts

Rua da Junqueira, 100
1349-008 Lisboa
Portugal
+351 213 652 600
+351 213 632 105

  • Facebook
  • YouTube

Subscribe Newsletter

  • How to get to GHTM/IHMT
  • GHTM Sessions
  • Research Groups
  • Cross-cutting issues
© Copyright 2023 IHMT-UNL Todos os Direitos Reservados.
  • Universidade Nova de Lisboa
  • Fundação para a Ciência e a Tecnologia

    Project UID/Multi/04413/2013