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Whole genome sequencing is replacing traditional laboratory surveillance methods as the primary tool to track and characterize clusters and outbreaks of the foodborne and zoonotic pathogen Salmonella enterica (S. enterica). In this study, 438 S. enterica isolates representing 35 serovars and 13 broad vehicle categories from one hundred epidemiologically confirmed outbreaks were evaluated for genetic variation to develop epidemiologically relevant interpretation guidelines for Salmonella disease cluster detection. The Illumina sequences were analyzed by core genome multi-locus sequence typing (cgMLST) and screened for antimicrobial resistance (AR) determinants and plasmids. Ninety-three of the one hundred outbreaks exhibited a close allele range (less than 10 allele differences with a subset closer than 5). The remaining seven outbreaks showed increased variation, of which three were considered polyclonal. A total of 16 and 28 outbreaks, respectively, showed variations in the AR and plasmid profiles. The serovars Newport and I 4,[5],12:i:-, as well as the zoonotic and poultry product vehicles, were overrepresented among the outbreaks, showing increased variation. A close allele range in cgMLST profiles can be considered a reliable proxy for epidemiological relatedness for the vast majority of S. enterica outbreak investigations. Variations associated with mobile elements happen relatively frequently during outbreaks and could be reflective of changing selective pressures.

Background Whole genome sequencing (WGS) has gained increasing importance in responses to enteric bacterial outbreaks. Common analysis procedures for WGS, single nucleotide polymorphisms (SNPs) and genome assembly, are highly dependent upon WGS data quality. Methods Raw, unprocessed WGS reads from Escherichia coli, Salmonella enterica, and Shigella sonnei outbreak clusters were characterized for four quality metrics: PHRED score, read length, library insert size, and ambiguous nucleotide composition. PHRED scores were strongly correlated with improved SNPs analysis results in E. coli and S. enterica clusters. Results Assembly quality showed only moderate correlations with PHRED scores and library insert size, and then only for Salmonella. To improve SNP analyses and assemblies, we compared seven read-healing pipelines to improve these four quality metrics and to see how well they improved SNP analysis and genome assembly. The most effective read healing pipelines for SNPs analysis incorporated quality-based trimming, fixed-width trimming, or both. The Lyve-SET SNPs pipeline showed a more marked improvement than the CFSAN SNP Pipeline, but the latter performed better on raw, unhealed reads. For genome assembly, SPAdes enabled significant improvements in healed E. coli reads only, while Skesa yielded no significant improvements on healed reads. Conclusions PHRED scores will continue to be a crucial quality metric albeit not of equal impact across all types of analyses for all enteric bacteria. While trimming-based read healing performed well for SNPs analyses, different read healing approaches are likely needed for genome assembly or other, emerging WGS analysis methodologies.

Increasingly, routine surveillance and monitoring of foodborne pathogens using whole-genome sequencing is creating opportunities to study foodborne illness epidemiology beyond routine outbreak investigations and case–control studies. Using a global phylogeny of Salmonella enterica serotype Typhimurium, we found that major livestock sources of the pathogen in the United States can be predicted through whole-genome sequencing data. Relatively steady rates of sequence divergence in livestock lineages enabled the inference of their recent origins. Elevated accumulation of lineage-specific pseudogenes after divergence from generalist populations and possible metabolic acclimation in a representative swine isolate indicates possible emergence of host adaptation. We developed and retrospectively applied a machine learning Random Forest classifier for genomic source prediction of Salmonella Typhimurium that correctly attributed 7 of 8 major zoonotic outbreaks in the United States during 1998–2013. We further identified 50 key genetic features that were sufficient for robust livestock source prediction.

Enterotoxigenic Escherichia coli (ETEC) are an important cause of diarrhea globally, particularly among children under the age of five in developing countries. ETEC O6 is the most common ETEC serogroup, yet the genome wide population structure of isolates of this serogroup is yet to be determined. In this study, we have characterized 40 ETEC O6 isolates collected between 1975-2016 by whole genome sequencing (WGS) and by phenotypic antimicrobial susceptibility testing. To determine the relatedness of isolates, we evaluated two methods-whole genome high-quality single nucleotide polymorphism (whole genome-hqSNP) and core genome SNP analyses using Lyve-SET and Parsnp respectively. All isolates were tested for antimicrobial susceptibility using a panel of 14 antibiotics. ResFinder 2.1 and a custom quinolone resistance determinants workflow were used for resistance determinant detection. VirulenceFinder 1.5 was used for prediction of the virulence genes. Thirty-seven isolates clustered into three major clades (I, II, III) by whole genome-hqSNP and core genome SNP analyses, while three isolates included in the whole genome-hqSNP analysis only did not cluster with clades I-III by both analyses and formed a distantly related outgroup, designated clade IV. Median number of pairwise whole genome-hqSNPs in clonal ETEC O6 outbreaks ranged from 0 to 5. Of the 40 isolates tested for antimicrobial susceptibility, 18 isolates were pansusceptible. Twenty-two isolates were resistant to at least one antibiotic, nine of which were multidrug resistant. Phenotypic antimicrobial resistance (AR) correlated with AR determinants in 22 isolates. Thirty-two isolates harbored both enterotoxin virulence genes while the remaining 8 isolates had only one of the two virulence genes. In summary, whole genome-hqSNP and core genome SNP analyses from this study revealed similar evolutionary relationships and an overall diversity of ETEC O6 isolates independent of time of isolation. Less than 5 pairwise hqSNPs between ETEC O6 isolates is circumstantially indicative of an outbreak cluster. Findings from this study will be a basis for quicker outbreak detection and control by efficient subtyping by WGS.

Salmonella enterica serotype Enteritidis is one of the most commonly reported causes of human salmonellosis. Its low genetic diversity, measured by fingerprinting methods, has made subtyping a challenge. We used whole-genome sequencing to characterize 125 S. enterica Enteritidis and 3 S. enterica serotype Nitra strains. Single-nucleotide polymorphisms were filtered to identify 4,887 reliable loci that distinguished all isolates from each other. Our whole-genome single-nucleotide polymorphism typing approach was robust for S. enterica Enteritidis subtyping with combined data for different strains from 2 different sequencing platforms. Five major genetic lineages were recognized, which revealed possible patterns of geographic and epidemiologic distribution. Analyses on the population dynamics and evolutionary history estimated that major lineages emerged during the 17th–18th centuries and diversified during the 1920s and 1950s.

BACKGROUND: Shiga toxin-producing Escherichia coli (STEC) O157:H7 is the causal agent for more than 96,000 cases of diarrheal illness and 3,200 infection-attributable hospitalizations annually in the United States. MATERIALS AND METHODS: We defined a confirmed case as a compatible illness in a person with the outbreak strain during 10/07/2011-11/30/2011. Investigation included hypothesis generation, a case-control study utilizing geographically-matched controls, and a case series investigation. Environmental inspections and tracebacks were conducted. RESULTS: We identified 58 cases in 10 states; 67% were hospitalized and 6.4% developed hemolytic uremic syndrome. Any romaine consumption was significantly associated with illness (matched Odds Ratio (mOR) = 10.0, 95% Confidence Interval (CI) = 2.1-97.0). Grocery Store Chain A salad bar was significantly associated with illness (mOR = 18.9, 95% CI = 4.5-176.8). Two separate traceback investigations for romaine lettuce converged on Farm A. Case series results indicate that cases (64.9%) were more likely than the FoodNet population (47%) to eat romaine lettuce (p-value = 0.013); 61.3% of cases reported consuming romaine lettuce from the Grocery Store Chain A salad bar. CONCLUSIONS: This multistate outbreak of STEC O157:H7 infections was associated with consumption of romaine lettuce. Traceback analysis determined that a single common lot of romaine lettuce harvested from Farm A was used to supply Grocery Store Chain A and a university campus linked to a case with the outbreak strain. An investigation at Farm A did not identify the source of contamination. Improved ability to trace produce from the growing fields to the point of consumption will allow more timely prevention and control measures to be implemented.

Objectives. To investigate a shigellosis outbreak in Genesee County, Michigan (including the City of Flint), and Saginaw County, Michigan, in 2016 and address community concerns about the role of the Flint water system. Methods. We met frequently with community members to understand concerns and develop the investigation. We surveyed households affected by the outbreak, analyzed Shigella isolate data, examined the geospatial distribution of cases, and reviewed available water quality data. Results. We surveyed 83 households containing 158 cases; median age was 10 years. Index case-patients from 55 of 83 households (66%) reported contact with a person outside their household who wore diapers or who had diarrhea in the week before becoming ill; results were similar regardless of household drinking water source. Genomic diversity was not consistent with a point source. In Flint, no space-time clustering was identified, and average free chlorine residual values remained above recommended levels throughout the outbreak period. Conclusions. The outbreak was most likely caused by person-to-person contact and not by the Flint water system. Consistent community engagement was essential to the design and implementation of the investigation.