Evaluation of WGS-subtyping methods for epidemiological surveillance of foodborne salmonellosis (original) (raw)
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Applied and Environmental Microbiology, 2011
In this study, we report a whole-genome single nucleotide polymorphism (SNP)-based evolutionary approach to study the epidemiology of a multistate outbreak of Salmonella enterica subsp. enterica serovar Montevideo. This outbreak included 272 cases that occurred in 44 states between July 2009 and April 2010. A case-control study linked the consumption of salami made with contaminated black and red pepper to the outbreak. We sequenced, on the SOLiD System, 47 isolates with XbaI PFGE pattern JIXX01.0011, a common pulsed-field gel electrophoresis (PFGE) pattern associated with isolates from the outbreak. These isolates represented 20 isolates collected from human sources during the period of the outbreak and 27 control isolates collected from human, food, animal, and environmental sources before the outbreak. Based on 253 high-confidence SNPs, we were able to reconstruct a tip-dated molecular clock phylogeny of the isolates and to assign four human isolates to the actual outbreak. We developed an SNP typing assay to rapidly discriminate between outbreak-related cases and non-outbreak-related cases and tested this assay on an extended panel of 112 isolates. These results suggest that only a very small percentage of the human isolates with the outbreak PFGE pattern and obtained during the outbreak period could be attributed to the actual pepper-related outbreak (20%), while the majority (80%) of the putative cases represented background cases. This study demonstrates that next-generation-based SNP typing provides the resolution and accuracy needed for outbreak investigations of food-borne pathogens that cannot be distinguished by currently used subtyping methods.
Evaluation of Whole Genome Sequencing for Outbreak Detection of Salmonella enterica
PLoS ONE, 2014
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 reveling 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.
2020
Salmonella enterica serovar Enteritidis is a major cause of foodborne Salmonella infections and outbreaks in humans. Effective surveillance and timely outbreak detection are essential for public health control. Multilevel genome typing (MGT) with multiple levels of resolution has been previously demonstrated as a promising tool for this purpose. In this study, we developed MGT with nine levels for S. Enteritidis and characterised the genomic epidemiology of S. Enteritidis in detail. We examined 26,670 publicly available S. Enteritidis genome sequences from isolates spanning 101 years from 86 countries to reveal their spatial and temporal distributions. Using the lower resolution MGT levels, globally prevalent and regionally restricted sequence types (STs) were identified; avian associated MGT4-STs were found that were common in human cases in the USA were identified; temporal trends were observed in the UK with MGT5-STs from 2014 to 2018, revealing both long lived endemic STs and th...
Salmonella spp. - A Global Challenge [Working Title], 2021
Salmonella enterica serovar Enteritidis (or Salmonella Enteritidis, SE) is one of the oldest members of the genus Salmonella, based on the date of first description and has only gained prominence as a significant bacterial contaminant of food over the last three or four decades. Currently, SE is the most common Salmonella serovar causing foodborne illnesses. Control measures to alleviate human infections require that food isolates be characterized and this was until recently carried out using Pulsed-Field Gel Electrophoresis (PFGE) and phage typing as the main laboratory subtyping tools for use in demonstrating relatedness of isolates recovered from infected humans and the food source. The results provided by these analytical tools were presented with easy-to-understand and comprehensible nomenclature, however, the techniques were inherently poorly discriminatory, which is attributable to the clonality of SE. The tools have now given way to whole genome sequencing which provides a f...
Microorganisms
Over the last decade, Salmonella enterica serovar Schwarzengrund has become more prevalent in Asia, Europe, and the US with the simultaneous emergence of multidrug-resistant isolates. As these pathogens are responsible for many sporadic illnesses and chronic complications, as well as outbreaks over many countries, improved surveillance is urgently needed. For 20 years, pulsed-field gel electrophoresis (PFGE) has been the gold standard for determining bacterial relatedness by targeting genome-wide restriction enzyme polymorphisms. Despite its utility, recent studies have reported that PFGE results correlate poorly with that of closely related outbreak strains and clonally dominant endemic strains. Due to these concerns, alternative amplification-based molecular methods for bacterial strain typing have been developed, including clustered regular interspaced short palindromic repeats (CRISPR) and multilocus sequence typing (MLST). Furthermore, as the cost of sequencing continues to dec...
Food microbiology, 2018
Salmonella enterica serovar Heidelberg (S. Heidelberg) is one of the top serovars causing human salmonellosis. This serovar ranks second and third among serovars that cause human infections in Québec and Canada, respectively, and has been associated with severe infections. Traditional typing methods such as PFGE do not display adequate discrimination required to resolve outbreak investigations due to the low level of genetic diversity of isolates belonging to this serovar. This study evaluates the ability of four whole genome sequence (WGS)-based typing methods to differentiate among 145 S. Heidelberg strains involved in four distinct outbreak events and sporadic cases of salmonellosis that occurred in Québec between 2007 and 2016. Isolates from all outbreaks were indistinguishable by PFGE. The core genome single nucleotide variant (SNV), core genome multilocus sequence typing (MLST) and whole genome MLST approaches were highly discriminatory and separated outbreak strains into four...
Journal of clinical microbiology, 2015
Whole genome next generation sequencing (NGS) was used to retrospectively examine 57 isolates from five epidemiologically confirmed community outbreaks (designated as Outbreak 1 to Outbreak 5) caused by Salmonella enterica serovar Typhimurium (S. 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 to two single nucleotide polymorphisms (SNPs) with the exception of 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 the other four outbreaks were 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 modelled using known mutation rates to derive a cut-off value for the number of SN...
Foodborne Pathogens and Disease, 2007
Nontyphoid Salmonella is one of the main causes of bacterial gastroenteritis worldwide and is responsible for 65% of reported outbreaks of foodborne diseases in France. Serotyping is widely used for isolate preliminary identification, but it poorly discriminates strains. Rapid, efficient molecular subtyping tools have therefore been developed for the investigation of outbreaks. We evaluated the performance of the pulsed-field gel electrophoresis (PFGE) method for discrimination of 31 Salmonella serotypes frequently isolated in France. We set up a genomic database of Salmonella strains isolated from food, animals, the environment, and humans to improve the management of contamination and reactions to foodborne disease outbreaks. We studied 1128 isolates by PFGE, according to the standardized PulseNet protocol. We identified 452 PFGE patterns, 67.5% of which corresponded to a single isolate. The ability of this method to distinguish between isolates was estimated by calculating the Simpson index and the 95% confidence interval. Values obtained ranged between 0.33 (0.11-0.54) to 0.99 (0.96-1.00), depending on serotype. Epidemiological information about isolates was used for analyses of intra-and interserotype diversity results and for determining whether PFGE patterns were linked to the source of the isolate. Clustering analysis of the PFGE patterns obtained confirmed that serotype and PFGE genotype were closely linked. Some PFGE patterns were identified as major patterns, each of these patterns being found in at least 10 isolates. The database generated has already proved its effectiveness in epidemiological investigations in livestock production and foodborne outbreaks.