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

被引:70
作者
Argimon, Silvia [1 ]
Yeats, Corin A. [2 ]
Goater, Richard J. [1 ,10 ]
Abudahab, Khalil [1 ]
Taylor, Benjamin [2 ]
Underwood, Anthony [1 ]
Sanchez-Buso, Leonor [2 ,11 ]
Wong, Vanessa K. [3 ]
Dyson, Zoe A. [3 ,4 ,5 ]
Nair, Satheesh [6 ]
Park, Se Eun [7 ]
Marks, Florian [7 ]
Page, Andrew J. [8 ,12 ]
Keane, Jacqueline A. [8 ]
Baker, Stephen [9 ]
Holt, Kathryn E. [4 ,5 ]
Dougan, Gordon [3 ]
Aanensen, David M. [1 ,2 ]
机构
[1] Ctr Genom Pathogen Surveillance, Wellcome Genome Campus, Hinxton, Cambs, England
[2] Univ Oxford, Ctr Genom Pathogen Surveillance, Big Data Inst, Nuffield Dept Med, Oxford, Oxon, England
[3] Cambridge Univ Hosp NHS Fdn Trust, Addenbrookes Hosp, Cambridge Biomed Campus, Cambridge, England
[4] London Sch Hyg & Trop Med, London, England
[5] Monash Univ, Dept Infect Dis, Melbourne, Vic, Australia
[6] Publ Hlth England, Gastrointestinal Bacterial Reference Unit, London, England
[7] Int Vaccine Inst, Seoul, South Korea
[8] Wellcome Sanger Inst, Pathogen Informat, Wellcome Genome Campus, Hinxton, Cambs, England
[9] Univ Cambridge, Cambridge Inst Therapeut Immunol & Infect Dis, Dept Med, Cambridge, England
[10] Wellcome Sanger Inst, Wellcome Genome Campus, Hinxton, Cambs, England
[11] Fdn Promot Hlth & Biomed Res Valencian Community, FISABIO Publ Hlth, Genom & Hlth Area, Valencia, Spain
[12] Quadram Inst Biosci, Norwich Res Pk, Norfolk, VA USA
基金
英国生物技术与生命科学研究理事会; 欧盟地平线“2020”;
关键词
ENTERICA; SEQUENCE; ALGORITHM; TREES;
D O I
10.1038/s41467-021-23091-2
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
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. 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.
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页数:12
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