Global population structure and genotyping framework for genomic surveillance of the major dysentery pathogen, Shigella sonnei
dc.contributor.author | Hawkey, Jane | |
dc.contributor.author | Paranagama, Kalani | |
dc.contributor.author | Baker, Kate | |
dc.contributor.author | Bengtsson, Rebecca J. | |
dc.contributor.author | Weill, François-Xavier | |
dc.contributor.author | Thomson, Nicholas R. | |
dc.contributor.author | Baker, Stephen | |
dc.contributor.author | Cerdeira, Louise | |
dc.contributor.author | Iqbal, Zamin | |
dc.contributor.author | Hunt, Martin | |
dc.contributor.author | Ingle, Danielle | |
dc.date.accessioned | 2024-01-23T00:10:38Z | |
dc.date.available | 2024-01-23T00:10:38Z | |
dc.date.issued | 2021 | |
dc.date.updated | 2022-10-02T07:17:57Z | |
dc.description.abstract | Shigella sonnei is the most common agent of shigellosis in high-income countries, and causes a significant disease burden in low- and middle-income countries. Antimicrobial resistance is increasingly common in all settings. Whole genome sequencing (WGS) is increasingly utilised for S. sonnei outbreak investigation and surveillance, but comparison of data between studies and labs is challenging. Here, we present a genomic framework and genotyping scheme for S. sonnei to efficiently identify genotype and resistance determinants from WGS data. The scheme is implemented in the software package Mykrobe and tested on thousands of genomes. Applying this approach to analyse >4,000 S. sonnei isolates sequenced in public health labs in three countries identified several common genotypes associated with increased rates of ciprofloxacin resistance and azithromycin resistance, confirming intercontinental spread of highly-resistant S. sonnei clones and demonstrating the genomic framework can facilitate monitoring the spread of resistant clones, including those that have recently emerged, at local and global scales. | en_AU |
dc.format.mimetype | application/pdf | en_AU |
dc.identifier.issn | 2041-1723 | en_AU |
dc.identifier.uri | http://hdl.handle.net/1885/311751 | |
dc.language.iso | en_AU | en_AU |
dc.provenance | This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. | en_AU |
dc.publisher | Macmillan Publishers Ltd | en_AU |
dc.relation | http://purl.org/au-research/grants/nhmrc/APP1174555 | en_AU |
dc.rights | © 2021 The authors | en_AU |
dc.rights.license | Creative Commons Attribution licence | en_AU |
dc.rights.uri | http://creativecommons.org/licenses/by/4.0/ | en_AU |
dc.source | Nature Communications | en_AU |
dc.title | Global population structure and genotyping framework for genomic surveillance of the major dysentery pathogen, Shigella sonnei | en_AU |
dc.type | Journal article | en_AU |
dcterms.accessRights | Open Access | en_AU |
local.bibliographicCitation.issue | 1 | en_AU |
local.contributor.affiliation | Hawkey, Jane, Monash University | en_AU |
local.contributor.affiliation | Paranagama, Kalani, Monash University | en_AU |
local.contributor.affiliation | Baker, Kate, University of Liverpool | en_AU |
local.contributor.affiliation | Bengtsson, Rebecca J. , University of Liverpool | en_AU |
local.contributor.affiliation | Weill, François-Xavier, Institut Pasteur | en_AU |
local.contributor.affiliation | Thomson, Nicholas R., The Wellcome Trust Sanger Institute | en_AU |
local.contributor.affiliation | Baker, Stephen, Cambridge Institute of Therapeutic Immunology & Infectious Disease | en_AU |
local.contributor.affiliation | Cerdeira, Louise, Monash University | en_AU |
local.contributor.affiliation | Iqbal, Zamin, European Bioinformatics Institute | en_AU |
local.contributor.affiliation | Hunt, Martin, European Bioinformatics Institute | en_AU |
local.contributor.affiliation | Ingle, Danielle, College of Health and Medicine, ANU | en_AU |
local.contributor.authoremail | u4123675@anu.edu.au | en_AU |
local.contributor.authoruid | Ingle, Danielle, u4123675 | en_AU |
local.description.notes | Imported from ARIES | en_AU |
local.identifier.absfor | 420200 - Epidemiology | en_AU |
local.identifier.ariespublication | a383154xPUB19166 | en_AU |
local.identifier.citationvolume | 12 | en_AU |
local.identifier.doi | 10.1038/s41467-021-22700-4 | en_AU |
local.identifier.scopusID | 2-s2.0-85105772110 | |
local.identifier.thomsonID | WOS:000658723900032 | |
local.identifier.uidSubmittedBy | a383154 | en_AU |
local.publisher.url | https://www.nature.com/ | en_AU |
local.type.status | Published Version | en_AU |
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