ArticlePloS one2014
Evaluation of whole genome sequencing for outbreak detection of Salmonella enterica.
Article in PloS one, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 138 papers.
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Who cites it
138 citing papers in PubMed, 263 citations in OpenAlex.
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- Genomic insights into antibiotic-resistant non-typhoidal Salmonella isolates from outpatients in Minhang District in Shanghai.Communications medicine · 2025Article
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- Antimicrobial susceptibility and resistome ofThe veterinary quarterly · 2024Article
- Predominance of OXA-48 carbapenemase-producingBiomolecules & biomedicine · 2024Article
- Outbreak detection in Harar town and Kersa district, Ethiopia using phylogenetic analysis and source attribution.BMC infectious diseases · 2024Article
- Emerging Strategies against Non-TyphoidalCurrent issues in molecular biology · 2024Review
- Dual effects of a bacteriocin-producingHeliyon · 2024Article
- Identifying factors that influence the use of pathogen genomics in Australia and New Zealand: a protocol.Frontiers in public health · 2024Article
- Evolution of Plasmodium falciparum antimalarial drug resistance markers post-adoption of artemisinin-based combination therapies in Yaounde, Cameroon.International journal of infectious diseases : IJID : official publication of the International Society for Infectious Diseases · 2023Article
- Salmonella Typhi whole genome sequencing in Rwanda shows a diverse historical population with recent introduction of haplotype H58.PLoS neglected tropical diseases · 2023Article
- Oxford nanopore technologies-a valuable tool to generate whole-genome sequencing data forFrontiers in veterinary science · 2023Article
78 more citing papers are in PubMed but not listed here.
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Authors and funding
5 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
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.
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