Salmonella enterica is a leading cause of bacterial foodborne and zoonotic illnesses in the United States. For this study, we applied four different whole genome sequencing (WGS)-based subtyping methods: high quality single-nucleotide polymorphism (hqSNP) analysis, whole genome multilocus sequence typing using either all loci [wgMLST (all loci)] and only chromosome-associated loci [wgMLST (chrom)], and core genome multilocus sequence typing (cgMLST) to a dataset of isolate sequences from 9 well-characterized Salmonella outbreaks. For each outbreak, we evaluated the genomic and epidemiologic concordance between hqSNP and allele-based methods. We first compared pairwise genomic differences using all four methods. We observed discrepancies in allele difference ranges when using wgMLST (all loci), likely caused by inflated genetic variation due to loci found on plasmids and/or other mobile genetic elements in the accessory genome. Therefore, we excluded wgMLST (all loci) results from any further comparisons in the study. Then, we created linear regression models and phylogenetic tanglegrams using the remaining three methods. K-means analysis using the silhouette method was applied to compare the ability of the three methods to partition outbreak and sporadic isolate sequences. Our results showed that pairwise hqSNP differences had high concordance with cgMLST and wgMLST (chrom) allele differences. The slopes of the regressions for hqSNP vs. allele pairwise differences were 0.58 (cgMLST) and 0.74 [wgMLST (chrom)], and the slope of the regression was 0.77 for cgMLST vs. wgMLST (chrom) pairwise differences. Tanglegrams showed high clustering concordance between methods using two statistical measures, the Baker’s gamma index (BGI) and cophenetic correlation coefficient (CCC), where 9/9 (100%) of outbreaks yielded BGI values ≥ 0.60 and CCCs were ≥ 0.97 across all nine outbreaks and all three methods. K-means analysis showed separation of outbreak and sporadic isolate groups with average silhouette widths ≥ 0.87 for outbreak groups and ≥ 0.16 for sporadic groups. This study demonstrates that Salmonella isolates clustered in concordance with epidemiologic data using three WGS-based subtyping methods and supports using cgMLST as the primary method for national surveillance of Salmonella outbreak clusters.

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.

The United States are one of the world’s leading consumers of melons. In 2020, the Food and Drug Administration (FDA), the Centers for Disease Control and Prevention (CDC), and state health and regulatory partners investigated an outbreak of Salmonella Newport infections linked to melons from southwest Indiana, resulting in 80 ill persons and 18 hospitalizations reported across 15 states. Epidemiologic and traceback data indicated melons as the vehicle for these infections, but the collinearity of melon varieties purchased and consumed together in combination with the traceback investigation that could not rule out either melon type, did not allow investigators to delineate whether the vehicle was cantaloupe alone or, both cantaloupe and watermelons. Analysis of traceback records for cantaloupe and/or watermelon exposures for 12 ill people indicated convergence on a grower in southwest Indiana which supplied cantaloupe to the nine of eleven points of service where ill people purchased cantaloupe; similar convergence was not observed for watermelon. While Salmonella isolates were recovered from environmental samples collected by FDA throughout the growing operation, they were not highly genetically related to the outbreak strain by whole genome sequencing analyses, i.e. greater than a 20 high quality single nucleotide polymorphisms difference. This outbreak illustrates the need for additional efforts to determine the source and extent of environmental contamination in the melon growing region of southwest Indiana and emphasizes the need for outreach and education efforts to help promote farm practices to reduce pathogen contamination of melons.

Shiga-toxin-producing E. coli (STEC) is a leading causing of bacterial foodborne and zoonotic illnesses in the USA. Whole-genome sequencing (WGS) is a powerful tool used in public health and microbiology for the detection, surveillance, and outbreak investigation of STEC. In this study, we applied three WGS-based subtyping methods, high quality single-nucleotide polymorphism (hqSNP) analysis, whole genome multi-locus sequence typing using chromosome-associated loci [wgMLST (chrom)], and core genome multi-locus sequence typing (cgMLST), to isolate sequences from 11 STEC outbreaks. For each outbreak, we evaluated the concordance between subtyping methods using pairwise genomic differences (number of SNPs or alleles), linear regression models, and tanglegrams. Pairwise genomic differences were highly concordant between methods for all but one outbreak, which was associated with international travel. The slopes of the regressions for hqSNP vs. allele differences were 0.432 (cgMLST) and 0.966 wgMLST (chrom); the slope was 1.914 for cgMLST vs. wgMLST (chrom) differences. Tanglegrams comprised of outbreak and sporadic sequences showed moderate clustering concordance between methods, where Baker’s Gamma Indices (BGIs) ranged between 0.35 and 0.99 and Cophenetic Correlation Coefficients (CCCs) were ≥0.88 across all outbreaks. The K-means analysis using the Silhouette method showed the clear separation of outbreak groups with average silhouette widths ≥0.87 across all methods. This study validates the use of cgMLST for the national surveillance of STEC illness clusters using the PulseNet 2.0 system and demonstrates that hqSNP or wgMLST can be used for further resolution.

In July 2017, a Shiga toxin-producing Escherichia coli (STEC) outbreak was reported among 18 individuals with exposure to untreated recreational water at a California lake. Ten cases were hospitalized and five (ages 1–5 years) developed hemolytic-uremic syndrome. An environmental investigation was conducted to confirm STEC transmission via the lake and determine the outbreak strain contamination source. Large-volume water and sediment samples were collected in August 2017 and July 2018 and tested for STEC and molecular microbial source tracking markers. The STEC O157:H7 outbreak strain was recovered from the suspected exposure location and from goose scat, and goose genetic material was detected in every 2017 environmental sample, confirming lake water as the transmission vehicle and implicating the lake’s resident Canada goose population in disseminating the pathogen. An unrelated STEC O157:H7 strain and ruminant fecal contamination were detected the following year, suggesting repeated STEC introductions to the lake environment. Subsequent large-scale outbreaks of the same highly virulent STEC O157:H7 strain were associated with romaine lettuce and ground beef, resulting in its designation as the reoccurring, emerging, or persisting (REP) strain REPEXH01. The severe illnesses associated with outbreaks of virulent pathogen strains like REPEXH01 are more likely to be detected. Conducting environmental investigations in response to these reoccurring outbreaks allows for the collection of incremental evidence about the patterns of transmission and sources of consequential pathogens and strains. Such information can provide critical insights for mitigation strategies to interrupt ongoing transmission and prevent future outbreaks.