Characterization of Foodborne Outbreaks of Salmonella enterica Serovar Enteritidis with Whole-Genome Sequencing Single Nucleotide Polymorphism-Based Analysis for Surveillance and Outbreak Detection

Abstract

b Salmonella enterica serovar Enteritidis is a significant cause of gastrointestinal illness in the United States; however, current molecular subtyping methods lack resolution for this highly clonal serovar. Advances in next-generation sequencing technologies have made it possible to examine whole-genome sequencing (WGS) as a potential molecular subtyping tool for outbreak detection and source trace back. Here, we conducted a retrospective analysis of S. Enteritidis isolates from seven epidemiologically confirmed foodborne outbreaks and sporadic isolates (not epidemiologically linked) to determine the utility of WGS to identify outbreaks. A collection of 55 epidemiologically characterized clinical and environmental S. Enteritidis isolates were sequenced. Single nucleotide polymorphism (SNP)-based cluster analysis of the S. Enteritidis genomes revealed well supported clades, with less than four-SNP pairwise diversity, that were concordant with epidemiologically defined outbreaks. Sporadic isolates were an average of 42.5 SNPs distant from the outbreak clusters. Isolates collected from the same patient over several weeks differed by only two SNPs. Our findings show that WGS provided greater resolution between outbreak, sporadic, and suspect isolates than the current gold standard subtyping method, pulsed-field gel electrophoresis (PFGE). Furthermore, results could be obtained in a time frame suitable for surveillance activities, supporting the use of WGS as an outbreak detection and characterization method for S. Enteritidis. Foodborne bacterial pathogen characterization, surveillance, and outbreak detection is an important function of the public health laboratory (1). Current practices involve time-and laborintensive phenotypic typing, including biochemical profiling, phage typing, serotyping, and antimicrobial susceptibility testing. In addition, a variety of species-specific molecular methods for advanced characterization are utilized, including pulsed-field gel electrophoresis (PFGE), multiple-locus variable number tandem repeat analysis (MLVA), and virulence gene typing (2). Often, it is necessary to combine results from multiple techniques to provide an adequate level of discrimination in order to identify outbreak clusters within routine clinical surveillance isolates.Salmonella is an important foodborne pathogen that is estimated to be responsible for approximately 1 million cases of illness and more than 450 deaths annually in the United States (3). Salmonella enterica serovar Enteritidis is responsible for 36% of Salmonella outbreaks in the United States, and in 1990, it replaced Salmonella enterica serovar Typhimurium as the most frequently reported serotype of Salmonella worldwide (4, 5). It is estimated that approximately 64% of S. Enteritidis clinical cases are attributable to contaminated eggs and 18% to poultry products (5, 6).There is limited genetic variation between the strains of S. Enteritidis, which reduces the utility of current subtyping methods (7-9). For example, PFGE, the gold standard s...

Salmonella Thompson outbreak associated with consumption of chicken shawarma and the usefulness of genome sequencing in the investigation

“…The other strains of S. Thompson analyzed had three or more nucleotide variations and the epidemiological information available regarding the cases with these exposures was different. Genome sequencing has proven to be effective in several outbreaks (19)(20)(21)(22)(23). The use of the whole genome sequencing technique provides additional powers of discrimination, beyond serotyping and PFGE, to delimit and investigate an outbreak (20)(21)(22)(23)(24)(25).…”

Foodborne bacteria in dairy products: Detection by molecular techniques

“…PFGE and MLVA often do not provide sufficient resolution to differentiate between outbreaks (Taylor et al, 2015). Recently, whole genome sequencing has offered that discriminatory power with the potential to enhance epidemiological investigations and elucidate transmission pathways (Phillips et al, 2016).…”

“…PFGE has been described as the gold standard for subtyping the genus and species to provide further discrimination among bacterial pathogens (Wuyts et al, 2013;Taylor et al, 2015;Adkins et al, 2016) and is used by the National Molecular Subtyping Network for Foodborne Disease Surveillance in United States (PulseNet) (Bopp et al, 2016). Initially, PFGE was used to type Escherichia coli O157:H7 and then was developed to enable typing of various important bacteria, such as Listeria monocytogenes, Vibrio parahaemolyticus and Salmonella (Liu et al, 2016).…”

Genomic Analysis of Bacterial Outbreaks

“…In light of the very large genome plasticity of many bacterial species, fixed compositions of the core and auxiliary genomes are almost impossible, which creates an additional problem for the stability of the scheme. Nevertheless, this approach has gained some popularity and cgMLST ("core genome MLST", a reduced version of wgMLST as described above) schemes are now available for several pathogens including S. aureus, Listeria monocytogenes, Enterococcus faecium (de Been et al, 2015), and S. enterica (Taylor et al, 2015), among others.…”

“…(Snitkin et al, 2012;Espedido et al, 2013;Onori et al, 2015) Legionella pneumophila 3.5 Illumina HiSeq 2x100 bp Illumina MiSeq 2x250 bp, 2x150bp SOLiD 5500XL SE 75bp (Reuter et al, 2013a;Reuter et al, 2013b;Sánchez-Busó et al, 2014;Bartley et al, 2016) Listeria monocytogenes 3 Roche 454 GS-FLX (Gilmour et al, 2010;Schmid et al, 2014;Kwong et al, 2016 (Holt et al, 2008;Lienau et al, 2011;Quick et al, 2015;Allard et al, 2013;Cao et al, 2013;Allard et al, 2012;Taylor et al, 2015;Bekal et al, 2016) Salmonella Typhimurium 4.7 Illumina GA II system (Okoro et al, 2012) Shigella sonnei 5.06 Illumina GAII PE 2x54 bp Illumina MiSeq Illumina HiSeq2000 (Holt et al, 2012;Holt et al, 2013;McDonnell et al, 2013) 32 (Harris et al, 2010;Eyre et al, 2012;McAdam et al, 2012;Young et al, 2012;Köser et al, 2012;Holden et al, 2013;Nübel et al, 2013;Harris et al, 2013;Price et al, 2014;Azarian et al, 2015;Paterson et al, 2015;Senn et al, 2016;Kinnevey et al, 2016;Reuter et al, 2016) Streptococcus pneumoniae 1. Hendriksen et al, 2011;Chin et al, 2011;…”