A Practical Bioinformatics Workflow for Routine Analysis of Bacterial WGS Data
dc.contributor.author | Atxaerandio Landa, Aitor | |
dc.contributor.author | Arrieta Gisasola, Ainhoa | |
dc.contributor.author | Laorden Muñoz, Lorena | |
dc.contributor.author | Bikandi Bikandi, Joseba | |
dc.contributor.author | Garaizar Candina, Javier | |
dc.contributor.author | Martínez Malaxetxebarria, Irati | |
dc.contributor.author | Martínez Ballesteros, Ilargi | |
dc.date.accessioned | 2023-01-11T15:21:56Z | |
dc.date.available | 2023-01-11T15:21:56Z | |
dc.date.issued | 2022-11-29 | |
dc.identifier.citation | Microorganisms 10(12) : (2022) // Article ID 2364 | es_ES |
dc.identifier.issn | 2076-2607 | |
dc.identifier.uri | http://hdl.handle.net/10810/59231 | |
dc.description.abstract | The use of whole-genome sequencing (WGS) for bacterial characterisation has increased substantially in the last decade. Its high throughput and decreasing cost have led to significant changes in outbreak investigations and surveillance of a wide variety of microbial pathogens. Despite the innumerable advantages of WGS, several drawbacks concerning data analysis and management, as well as a general lack of standardisation, hinder its integration in routine use. In this work, a bioinformatics workflow for (Illumina) WGS data is presented for bacterial characterisation including genome annotation, species identification, serotype prediction, antimicrobial resistance prediction, virulence-related genes and plasmid replicon detection, core-genome-based or single nucleotide polymorphism (SNP)-based phylogenetic clustering and sequence typing. Workflow was tested using a collection of 22 in-house sequences of Salmonella enterica isolates belonging to a local outbreak, coupled with a collection of 182 Salmonella genomes publicly available. No errors were reported during the execution period, and all genomes were analysed. The bioinformatics workflow can be tailored to other pathogens of interest and is freely available for academic and non-profit use as an uploadable file to the Galaxy platform | es_ES |
dc.description.sponsorship | A.A.-L. and A.A.-G. are recipients of predoctoral grants from the Basque Government and UPV/EHU, respectively. This research was funded by the Basque Government through grant PA20/03 and the University of the Basque Country UPV/EHU through grant GIU21/021. | es_ES |
dc.language.iso | eng | es_ES |
dc.publisher | MDPI | es_ES |
dc.rights | info:eu-repo/semantics/openAccess | es_ES |
dc.rights.uri | http://creativecommons.org/licenses/by/4.0/ | |
dc.subject | foodborne pathogens | es_ES |
dc.subject | whole-genome sequencing | es_ES |
dc.subject | bioinformatics workflow | es_ES |
dc.subject | Galaxy | es_ES |
dc.title | A Practical Bioinformatics Workflow for Routine Analysis of Bacterial WGS Data | es_ES |
dc.type | info:eu-repo/semantics/article | es_ES |
dc.date.updated | 2022-12-22T14:35:45Z | |
dc.rights.holder | © 2022 by the authors.Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/ 4.0/). | es_ES |
dc.relation.publisherversion | https://www.mdpi.com/2076-2607/10/12/2364 | es_ES |
dc.identifier.doi | 10.3390/microorganisms10122364 | |
dc.departamentoes | Inmunología, microbiología y parasitología | |
dc.departamentoeu | Immunologia, mikrobiologia eta parasitologia |
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Except where otherwise noted, this item's license is described as © 2022 by the authors.Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/ 4.0/).