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A global resource for genomic predictions of antimicrobial resistance and surveillance of Salmonella Typhi at pathogenwatch

Author

Listed:
  • Silvia Argimón

    (Wellcome Genome Campus)

  • Corin A. Yeats

    (University of Oxford)

  • Richard J. Goater

    (Wellcome Genome Campus
    Wellcome Genome Campus)

  • Khalil Abudahab

    (Wellcome Genome Campus)

  • Benjamin Taylor

    (University of Oxford)

  • Anthony Underwood

    (Wellcome Genome Campus)

  • Leonor Sánchez-Busó

    (University of Oxford
    Foundation for the Promotion of Health and Biomedical Research in the Valencian Community (FISABIO-Public Health))

  • Vanessa K. Wong

    (Cambridge Biomedical Campus)

  • Zoe A. Dyson

    (Cambridge Biomedical Campus
    London School of Hygiene and Tropical Medicine
    Monash University)

  • Satheesh Nair

    (Public Health England)

  • Se Eun Park

    (International Vaccine Institute)

  • Florian Marks

    (International Vaccine Institute)

  • Andrew J. Page

    (Wellcome Genome Campus
    Norwich Research Park)

  • Jacqueline A. Keane

    (Wellcome Genome Campus)

  • Stephen Baker

    (University of Cambridge)

  • Kathryn E. Holt

    (London School of Hygiene and Tropical Medicine
    Monash University)

  • Gordon Dougan

    (Cambridge Biomedical Campus)

  • David M. Aanensen

    (Wellcome Genome Campus
    University of Oxford)

Abstract

As whole-genome sequencing capacity becomes increasingly decentralized, there is a growing opportunity for collaboration and the sharing of surveillance data within and between countries to inform typhoid control policies. This vision requires free, community-driven tools that facilitate access to genomic data for public health on a global scale. Here we present the Pathogenwatch scheme for Salmonella enterica serovar Typhi (S. Typhi), a web application enabling the rapid identification of genomic markers of antimicrobial resistance (AMR) and contextualization with public genomic data. We show that the clustering of S. Typhi genomes in Pathogenwatch is comparable to established bioinformatics methods, and that genomic predictions of AMR are highly concordant with phenotypic susceptibility data. We demonstrate the public health utility of Pathogenwatch with examples selected from >4,300 public genomes available in the application. Pathogenwatch provides an intuitive entry point to monitor of the emergence and spread of S. Typhi high risk clones.

Suggested Citation

  • Silvia Argimón & Corin A. Yeats & Richard J. Goater & Khalil Abudahab & Benjamin Taylor & Anthony Underwood & Leonor Sánchez-Busó & Vanessa K. Wong & Zoe A. Dyson & Satheesh Nair & Se Eun Park & Flori, 2021. "A global resource for genomic predictions of antimicrobial resistance and surveillance of Salmonella Typhi at pathogenwatch," Nature Communications, Nature, vol. 12(1), pages 1-12, December.
  • Handle: RePEc:nat:natcom:v:12:y:2021:i:1:d:10.1038_s41467-021-23091-2
    DOI: 10.1038/s41467-021-23091-2
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