ArticleJournal of clinical microbiology2015
Delineating community outbreaks of Salmonella enterica serovar Typhimurium by use of whole-genome sequencing: insights into genomic variability within an outbreak.
Article in Journal of clinical microbiology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 54 papers, 2 of them syntheses that pooled it.
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Who cites it
54 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Using molecular methods to delineate norovirus outbreaks: a systematic review.Archives of virology · 2024Pooled it
- Using molecular methods to delineate norovirus outbreaks: a systematic review.Archives of virology · 2024Pooled it
- Article
- Whole-genome sequencing and phylogenetic analysis ofMicrobiology spectrum · 2025Article
- Implementing whole genome sequencing for foodborne pathogen surveillance: insights and recommendations based on expert experiences.Frontiers in microbiology · 2025Article
- DODGE: automated point source bacterial outbreak detection using cumulative long term genomic surveillance.Bioinformatics (Oxford, England) · 2024Article
- Use of whole genome sequencing for surveillance and control of foodborne diseases:Frontiers in microbiology · 2024Review
- P-DOR, an easy-to-use pipeline to reconstruct bacterial outbreaks using genomics.Bioinformatics (Oxford, England) · 2023Article
- Economic and health impact modelling of a whole genome sequencing-led intervention strategy for bacterial healthcare-associated infections for England and for the USA.Microbial genomics · 2023Article
- Phylogenomic investigation of an outbreak of fluoroquinolone-resistantMicrobial genomics · 2023Article
- Persistent Salmonella enterica serovar Typhi sub-populations within host interrogated by whole genome sequencing and metagenomics.PloS one · 2023Article
- MGTdb: a web service and database for studying the global and local genomic epidemiology of bacterial pathogens.Database : the journal of biological databases and curation · 2022Article
- Enhancing genomics-based outbreak detection of endemicMicrobial genomics · 2021Article
- Genomic Characterization ofPathogens (Basel, Switzerland) · 2021Article
- Genetic changes are introduced by repeated exposure of Salmonella spiked in low water activity and high fat matrix to heat.Scientific reports · 2021Article
- Comparison of conventional molecular and whole-genome sequencing methods for subtyping Salmonella enterica serovar Enteritidis strains from Tunisia.European journal of clinical microbiology & infectious diseases : official publication of the European Society of Clinical Microbiology · 2021Article
- Article
- Genomic evidence of environmental and resident Salmonella Senftenberg and Montevideo contamination in the pistachio supply-chain.PloS one · 2021Article
- Cost-effectiveness analysis of whole-genome sequencing during an outbreak of carbapenem-resistantAntimicrobial stewardship & healthcare epidemiology : ASHE · 2021Article
- Salmonella enterica Serovar Hvittingfoss in Bar-Tailed Godwits (Limosa lapponica) from Roebuck Bay, Northwestern Australia.Applied and environmental microbiology · 2020Article
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6 authors.
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No grant is acknowledged in the PubMed record.
Abstract
Whole-genome next-generation sequencing (NGS) was used to retrospectively examine 57 isolates from five epidemiologically confirmed community outbreaks (numbered 1 to 5) caused by Salmonella enterica serovar Typhimurium phage type DT170. Most of the human and environmental isolates confirmed epidemiologically to be involved in the outbreaks were either genomically identical or differed by one or two single nucleotide polymorphisms (SNPs), with the exception of those in outbreak 1. The isolates from outbreak 1 differed by up to 12 SNPs, which suggests that the food source of the outbreak was contaminated with more than one strain while each of the other four outbreaks was caused by a single strain. In addition, NGS analysis ruled in isolates that were initially not considered to be linked with the outbreak, which increased the total outbreak size by 107%. The mutation process was modeled by using known mutation rates to derive a cutoff value for the number of SNP difference to determine whether or not a case was part of an outbreak. For an outbreak with less than 1 month of ex vivo/in vivo evolution time, the maximum number of SNP differences between isolates is two or four using the lowest or highest mutation rate, respectively. NGS of S. Typhimurium significantly increases the resolution of investigations of community outbreaks. It can also inform a more targeted public health response by providing important supplementary evidence that cases of disease are or are not associated with food-borne outbreaks of S. Typhimurium.
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