Evaluation of whole genome sequencing for outbreak detection of Salmonella enterica.

Salmonella enterica is a common cause of minor and large food borne outbreaks. To achieve successful and nearly 'real-time' monitoring and identification of outbreaks, reliable sub-typing is essential. Whole genome sequencing (WGS) shows great promises for using as a routine epidemiologica...

Descripción completa

Guardado en:

Detalles Bibliográficos
Autores principales:	Pimlapas Leekitcharoenphon, Eva M Nielsen, Rolf S Kaas, Ole Lund, Frank M Aarestrup
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2014
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/6a33e760dbe6444f802870cf6d1bd6b2
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

id	oai:doaj.org-article:6a33e760dbe6444f802870cf6d1bd6b2
record_format	dspace
spelling	oai:doaj.org-article:6a33e760dbe6444f802870cf6d1bd6b22021-11-18T08:33:54ZEvaluation of whole genome sequencing for outbreak detection of Salmonella enterica.1932-620310.1371/journal.pone.0087991https://doaj.org/article/6a33e760dbe6444f802870cf6d1bd6b22014-01-01T00:00:00Zhttps://www.ncbi.nlm.nih.gov/pmc/articles/pmid/24505344/pdf/?tool=EBIhttps://doaj.org/toc/1932-6203Salmonella enterica is a common cause of minor and large food borne outbreaks. To achieve successful and nearly 'real-time' monitoring and identification of outbreaks, reliable sub-typing is essential. Whole genome sequencing (WGS) shows great promises for using as a routine epidemiological typing tool. Here we evaluate WGS for typing of S. Typhimurium including different approaches for analyzing and comparing the data. A collection of 34 S. Typhimurium isolates was sequenced. This consisted of 18 isolates from six outbreaks and 16 epidemiologically unrelated background strains. In addition, 8 S. Enteritidis and 5 S. Derby were also sequenced and used for comparison. A number of different bioinformatics approaches were applied on the data; including pan-genome tree, k-mer tree, nucleotide difference tree and SNP tree. The outcome of each approach was evaluated in relation to the association of the isolates to specific outbreaks. The pan-genome tree clustered 65% of the S. Typhimurium isolates according to the pre-defined epidemiology, the k-mer tree 88%, the nucleotide difference tree 100% and the SNP tree 100% of the strains within S. Typhimurium. The resulting outcome of the four phylogenetic analyses were also compared to PFGE revealing that WGS typing achieved the greater performance than the traditional method. In conclusion, for S. Typhimurium, SNP analysis and nucleotide difference approach of WGS data seem to be the superior methods for epidemiological typing compared to other phylogenetic analytic approaches that may be used on WGS. These approaches were also superior to the more classical typing method, PFGE. Our study also indicates that WGS alone is insufficient to determine whether strains are related or un-related to outbreaks. This still requires the combination of epidemiological data and whole genome sequencing results.Pimlapas LeekitcharoenphonEva M NielsenRolf S KaasOle LundFrank M AarestrupPublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 9, Iss 2, p e87991 (2014)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Pimlapas Leekitcharoenphon Eva M Nielsen Rolf S Kaas Ole Lund Frank M Aarestrup Evaluation of whole genome sequencing for outbreak detection of Salmonella enterica.
description	Salmonella enterica is a common cause of minor and large food borne outbreaks. To achieve successful and nearly 'real-time' monitoring and identification of outbreaks, reliable sub-typing is essential. Whole genome sequencing (WGS) shows great promises for using as a routine epidemiological typing tool. Here we evaluate WGS for typing of S. Typhimurium including different approaches for analyzing and comparing the data. A collection of 34 S. Typhimurium isolates was sequenced. This consisted of 18 isolates from six outbreaks and 16 epidemiologically unrelated background strains. In addition, 8 S. Enteritidis and 5 S. Derby were also sequenced and used for comparison. A number of different bioinformatics approaches were applied on the data; including pan-genome tree, k-mer tree, nucleotide difference tree and SNP tree. The outcome of each approach was evaluated in relation to the association of the isolates to specific outbreaks. The pan-genome tree clustered 65% of the S. Typhimurium isolates according to the pre-defined epidemiology, the k-mer tree 88%, the nucleotide difference tree 100% and the SNP tree 100% of the strains within S. Typhimurium. The resulting outcome of the four phylogenetic analyses were also compared to PFGE revealing that WGS typing achieved the greater performance than the traditional method. In conclusion, for S. Typhimurium, SNP analysis and nucleotide difference approach of WGS data seem to be the superior methods for epidemiological typing compared to other phylogenetic analytic approaches that may be used on WGS. These approaches were also superior to the more classical typing method, PFGE. Our study also indicates that WGS alone is insufficient to determine whether strains are related or un-related to outbreaks. This still requires the combination of epidemiological data and whole genome sequencing results.
format	article
author	Pimlapas Leekitcharoenphon Eva M Nielsen Rolf S Kaas Ole Lund Frank M Aarestrup
author_facet	Pimlapas Leekitcharoenphon Eva M Nielsen Rolf S Kaas Ole Lund Frank M Aarestrup
author_sort	Pimlapas Leekitcharoenphon
title	Evaluation of whole genome sequencing for outbreak detection of Salmonella enterica.
title_short	Evaluation of whole genome sequencing for outbreak detection of Salmonella enterica.
title_full	Evaluation of whole genome sequencing for outbreak detection of Salmonella enterica.
title_fullStr	Evaluation of whole genome sequencing for outbreak detection of Salmonella enterica.
title_full_unstemmed	Evaluation of whole genome sequencing for outbreak detection of Salmonella enterica.
title_sort	evaluation of whole genome sequencing for outbreak detection of salmonella enterica.
publisher	Public Library of Science (PLoS)
publishDate	2014
url	https://doaj.org/article/6a33e760dbe6444f802870cf6d1bd6b2
work_keys_str_mv	AT pimlapasleekitcharoenphon evaluationofwholegenomesequencingforoutbreakdetectionofsalmonellaenterica AT evamnielsen evaluationofwholegenomesequencingforoutbreakdetectionofsalmonellaenterica AT rolfskaas evaluationofwholegenomesequencingforoutbreakdetectionofsalmonellaenterica AT olelund evaluationofwholegenomesequencingforoutbreakdetectionofsalmonellaenterica AT frankmaarestrup evaluationofwholegenomesequencingforoutbreakdetectionofsalmonellaenterica
_version_	1718421625849774080

Evaluation of whole genome sequencing for outbreak detection of Salmonella enterica.

Ejemplares similares