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

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, Florian Marks, Andrew J. Page, Jacqueline A. Keane, Stephen Baker, Kathryn E. Holt, Gordon Dougan and David M. Aanensen ()
Additional contact information
Silvia Argimón: Wellcome Genome Campus
Corin A. Yeats: University of Oxford
Richard J. Goater: Wellcome Genome Campus
Khalil Abudahab: Wellcome Genome Campus
Benjamin Taylor: University of Oxford
Anthony Underwood: Wellcome Genome Campus
Leonor Sánchez-Busó: University of Oxford
Vanessa K. Wong: Cambridge Biomedical Campus
Zoe A. Dyson: Cambridge Biomedical Campus
Satheesh Nair: Public Health England
Se Eun Park: International Vaccine Institute
Florian Marks: International Vaccine Institute
Andrew J. Page: Wellcome Genome Campus
Jacqueline A. Keane: Wellcome Genome Campus
Stephen Baker: University of Cambridge
Kathryn E. Holt: London School of Hygiene and Tropical Medicine
Gordon Dougan: Cambridge Biomedical Campus
David M. Aanensen: Wellcome Genome Campus

Nature Communications, 2021, vol. 12, issue 1, 1-12

Abstract: 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.

Date: 2021
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DOI: 10.1038/s41467-021-23091-2

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