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

Authors :
Kathryn E. Holt
Andrew J. Page
Silvia Argimón
Florian Marks
Jacqueline A. Keane
Khalil Abudahab
Anthony Underwood
Corin A. Yeats
Vanessa K. Wong
Se Eun Park
Richard Goater
David M. Aanensen
Satheesh Nair
Zoe A. Dyson
Leonor Sánchez-Busó
Gordon Dougan
SD Baker
Benjamin Taylor
Argimón, Silvia [0000-0002-2884-3857]
Goater, Richard J. [0000-0001-9954-841X]
Taylor, Benjamin [0000-0002-9105-7760]
Sánchez-Busó, Leonor [0000-0002-4162-0228]
Dyson, Zoe A. [0000-0002-8887-3492]
Nair, Satheesh [0000-0002-7297-1485]
Park, Se Eun [0000-0002-1632-3045]
Marks, Florian [0000-0002-6043-7170]
Apollo - University of Cambridge Repository
Goater, Richard J [0000-0001-9954-841X]
Dyson, Zoe A [0000-0002-8887-3492]
Source :
Nature Communications, Nature Communications, Vol 12, Iss 1, Pp 1-12 (2021)
Publication Year :
2021

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.<br />Whole genome sequencing data are increasingly becoming routinely available but generating actionable insights is challenging. Here, the authors describe Pathogenwatch, a web tool for genomic surveillance of S. Typhi, and demonstrate its use for antimicrobial resistance assignment and strain risk assessment.

Details

ISSN :
20411723
Database :
OpenAIRE
Journal :
Nature Communications
Accession number :
edsair.doi.dedup.....0e814064f51e88d4489bf635f55d96bc
Full Text :
https://doi.org/10.1038/s41467-021-23091-2