Variation in Antimicrobial Resistance in Sporadic and Outbreak-related Salmonella enterica Serovar Typhimurium

The prevalence of different antimicrobial resistance profiles and variants of the Salmonella genomic island 1 (SGI1) was reported for Salmonella enterica serovar Typhimurium DT104 strains isolated from patients in Denmark. Variation in antimicrobial resistance and corresponding changes of SGI1 were shown among isolates from a foodborne outbreak

DNA microarray analysis of Salmonella serotype Typhimurium strains causing different symptoms of disease

<p>Abstract</p> <p>Background</p> <p><it>Salmonella enterica </it>subsp. <it>enterica </it>is one of the leading food-borne pathogens in the USA and European countries. Outcome of human <it>Salmonella </it>serotype Typhimurium infections ranges from mild self-limiting diarrhoea to severe diarrhoea that requires hospitalization. Increased knowledge of the mechanisms that are responsible for causing infection and especially the severity of infection is of high interest.</p> <p>Results</p> <p>Strains were selected from patients with mild infections (n = 9) and patients with severe infections (n = 9) and clinical data allowed us to correct for known underlying diseases. Additionally, outbreak isolates (n = 3) were selected. Strains were analyzed on a DNA-DNA microarray for presence or absence of 281 genes covering marker groups of genes related to pathogenicity, phages, antimicrobial resistance, fimbriae, mobility, serotype and metabolism. Strains showed highly similar profiles when comparing virulence associated genes, but differences between strains were detected in the prophage marker group. The <it>Salmonella </it>virulence plasmid was present in 72% of the strains, but presence or absence of the virulence plasmid did not correspond to disease symptoms. A dendrogram clustered strains into four groups. Clustering confirmed DT104 as being a clonal phagetype. Clustering of the remaining strains was mainly correlated to presence or absence of the virulence plasmid and mobile elements such as transposons. Each of the four clusters in the tree represented an almost equal amount of strains causing severe or mild symptoms of infection.</p> <p>Conclusions</p> <p>We investigated clinical significance of known virulence factors of <it>Salmonella </it>serotype Typhimurium strains causing different disease symptoms, and conclude that the few detected differences in <it>Salmonella </it>serotype Typhimurium do not affect outcome of human disease.</p

Genome sequencing reveals diversification of virulence factor content and possible host adaptation in distinct subpopulations of Salmonella enterica

<p>Abstract</p> <p>Background</p> <p>Divergence of bacterial populations into distinct subpopulations is often the result of ecological isolation. While some studies have suggested the existence of <it>Salmonella enterica </it>subsp. <it>enterica </it>subclades, evidence for these subdivisions has been ambiguous. Here we used a comparative genomics approach to define the population structure of <it>Salmonella enterica </it>subsp. <it>enterica</it>, and identify clade-specific genes that may be the result of ecological specialization.</p> <p>Results</p> <p>Multi-locus sequence analysis (MLSA) and single nucleotide polymorphisms (SNPs) data for 16 newly sequenced and 30 publicly available genomes showed an unambiguous subdivision of <it>S. enterica </it>subsp. <it>enterica </it>into at least two subpopulations, which we refer to as clade A and clade B. Clade B strains contain several clade-specific genes or operons, including a β-glucuronidase operon, a S-fimbrial operon, and cell surface related genes, which strongly suggests niche specialization of this subpopulation. An additional set of 123 isolates was assigned to clades A and B by using qPCR assays targeting subpopulation-specific SNPs and genes of interest. Among 98 serovars examined, approximately 20% belonged to clade B. All clade B isolates contained two pathogenicity related genomic islands, SPI-18 and a cytolethal distending toxin islet; a combination of these two islands was previously thought to be exclusive to serovars Typhi and Paratyphi A. Presence of β-glucuronidase in clade B isolates specifically suggests an adaptation of this clade to the vertebrate gastrointestinal environment.</p> <p>Conclusions</p> <p><it>S. enterica </it>subsp. <it>enterica </it>consists of at least two subpopulations that differ specifically in genes involved in host and tissue tropism, utilization of host specific carbon and nitrogen sources and are therefore likely to differ in ecology and transmission characteristics.</p

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 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