BackgroundNext-Generation Sequencing (NGS) is increasingly being used as a molecular epidemiologic tool for discerning ancestry and traceback of the most complicated, difficult to resolve bacterial pathogens. Making a linkage between possible food sources and clinical isolates requires distinguishing the suspected pathogen from an environmental background and placing the variation observed into the wider context of variation occurring within a serovar and among other closely related foodborne pathogens. Equally important is the need to validate these high resolution molecular tools for use in molecular epidemiologic traceback. Such efforts include the examination of strain cluster stability as well as the cumulative genetic effects of sub-culturing on these clusters. Numerous isolates of S. Montevideo were shot-gun sequenced including diverse lineage representatives as well as numerous replicate clones to determine how much variability is due to bias, sequencing error, and or the culturing of isolates. All new draft genomes were compared to 34 S. Montevideo isolates previously published during an NGS-based molecular epidemiological case study.ResultsIntraserovar lineages of S. Montevideo differ by thousands of SNPs, that are only slightly less than the number of SNPs observed between S. Montevideo and other distinct serovars. Much less variability was discovered within an individual S. Montevideo clade implicated in a recent foodborne outbreak as well as among individual NGS replicates. These findings were similar to previous reports documenting homopolymeric and deletion error rates with the Roche 454 GS Titanium technology. In no case, however, did variability associated with sequencing methods or sample preparations create inconsistencies with our current phylogenetic results or the subsequent molecular epidemiological evidence gleaned from these data.ConclusionsImplementation of a validated pipeline for NGS data acquisition and analysis provides highly reproducible results that are stable and predictable for molecular epidemiological applications. When draft genomes are collected at 15×-20× coverage and passed through a quality filter as part of a data analysis pipeline, including sub-passaged replicates defined by a few SNPs, they can be accurately placed in a phylogenetic context. This reproducibility applies to all levels within and between serovars of Salmonella suggesting that investigators using these methods can have confidence in their conclusions.

Facile laboratory tools are needed to augment identification in contamination events to trace the contamination back to the source (traceback) of Salmonella enterica subsp. enterica serovar Enteritidis (S. Enteritidis). Understanding the evolution and diversity within and among outbreak strains is the first step towards this goal. To this end, we collected 106 new S. Enteriditis isolates within S. Enteriditis Pulsed-Field Gel Electrophoresis (PFGE) pattern JEGX01.0004 and close relatives, and determined their genome sequences. Sources for these isolates spanned food, clinical and environmental farm sources collected during the 2010 S. Enteritidis shell egg outbreak in the United States along with closely related serovars, S. Dublin, S. Gallinarum biovar Pullorum and S. Gallinarum. Despite the highly homogeneous structure of this population, S. Enteritidis isolates examined in this study revealed thousands of SNP differences and numerous variable genes (n = 366). Twenty-one of these genes from the lineages leading to outbreak-associated samples had nonsynonymous (causing amino acid changes) changes and five genes are putatively involved in known Salmonella virulence pathways. While chromosome synteny and genome organization appeared to be stable among these isolates, genome size differences were observed due to variation in the presence or absence of several phages and plasmids, including phage RE-2010, phage P125109, plasmid pSEEE3072_19 (similar to pSENV), plasmid pOU1114 and two newly observed mobile plasmid elements pSEEE1729_15 and pSEEE0956_35. These differences produced modifications to the assembled bases for these draft genomes in the size range of approximately 4.6 to 4.8 mbp, with S. Dublin being larger (∼4.9 mbp) and S. Gallinarum smaller (4.55 mbp) when compared to S. Enteritidis. Finally, we identified variable S. Enteritidis genes associated with virulence pathways that may be useful markers for the development of rapid surveillance and typing methods, potentially aiding in traceback efforts during future outbreaks involving S. Enteritidis PFGE pattern JEGX01.0004.

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In 2014, the identification of stone fruits contaminated with Listeria monocytogenes led to the subsequent identification of a multistate outbreak. Simultaneous detection and enumeration of L. monocytogenes were performed on 105 fruits, each weighing 127 to 145 g, collected from 7 contaminated lots. The results showed that 53.3% of the fruits yielded L. monocytogenes (lower limit of detection, 5 CFU/fruit), and the levels ranged from 5 to 2,850 CFU/fruit, with a geometric mean of 11.3 CFU/fruit (0.1 CFU/g of fruit). Two serotypes, IVb-v1 and 1/2b, were identified by a combination of PCR- and antiserum-based serotyping among isolates from fruits and their packing environment; certain fruits contained a mixture of both serotypes. Single nucleotide polymorphism (SNP)-based whole-genome sequencing (WGS) analysis clustered isolates from two case-patients with the serotype IVb-v1 isolates and distinguished outbreak-associated isolates from pulsed-field gel electrophoresis (PFGE)-matched, but epidemiologically unrelated, clinical isolates. The outbreak-associated isolates differed by up to 42 SNPs. All but one serotype 1/2b isolate formed another WGS cluster and differed by up to 17 SNPs. Fully closed genomes of isolates from the stone fruits were used as references to maximize the resolution and to increase our confidence in prophage analysis. Putative prophages were conserved among isolates of each WGS cluster. All serotype IVb-v1 isolates belonged to singleton sequence type 382 (ST382); all but one serotype 1/2b isolate belonged to clonal complex 5.IMPORTANCE WGS proved to be an excellent tool to assist in the epidemiologic investigation of listeriosis outbreaks. The comparison at the genome level contributed to our understanding of the genetic diversity and variations among isolates involved in an outbreak or isolates associated with food and environmental samples from one facility. Fully closed genomes increased our confidence in the identification and comparison of accessory genomes. The diversity among the outbreak-associated isolates and the inclusion of PFGE-matched, but epidemiologically unrelated, isolates demonstrate the high resolution of WGS. The prevalence and enumeration data could contribute to our further understanding of the risk associated with Listeria monocytogenes contamination, especially among high-risk populations.

Salmonella Newport has ranked in the top three Salmonella serotypes associated with foodborne outbreaks from 1995 to 2011 in the United States. In the current study, we selected 26 S. Newport strains isolated from diverse sources and geographic locations and then conducted 454 shotgun pyrosequencing procedures to obtain 16–24 × coverage of high quality draft genomes for each strain. Comparative genomic analysis of 28 S. Newport strains (including 2 reference genomes) and 15 outgroup genomes identified more than 140,000 informative SNPs. A resulting phylogenetic tree consisted of four sublineages and indicated that S. Newport had a clear geographic structure. Strains from Asia were divergent from those from the Americas. Our findings demonstrated that analysis using whole genome sequencing data resulted in a more accurate picture of phylogeny compared to that using single genes or small sets of genes. We selected loci around the mutS gene of S. Newport to differentiate distinct lineages, including those between invH and mutS genes at the 3′ end of Salmonella Pathogenicity Island 1 (SPI-1), ste fimbrial operon, and Clustered, Regularly Interspaced, Short Palindromic Repeats (CRISPR) associated-proteins (cas). These genes in the outgroup genomes held high similarity with either S. Newport Lineage II or III at the same loci. S. Newport Lineages II and III have different evolutionary histories in this region and our data demonstrated genetic flow and homologous recombination events around mutS. The findings suggested that S. Newport Lineages II and III diverged early in the serotype evolution and have evolved largely independently. Moreover, we identified genes that could delineate sublineages within the phylogenetic tree and that could be used as potential biomarkers for trace-back investigations during outbreaks. Thus, whole genome sequencing data enabled us to better understand the genetic background of pathogenicity and evolutionary history of S. Newport and also provided additional markers for epidemiological response.