High resolution clustering of Salmonella enterica serovar Montevideo strains using a next-generation sequencing approach

Abstract

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.

Usefulness of High-Quality Core Genome Single-Nucleotide Variant Analysis for Subtyping the Highly Clonal and the Most Prevalent Salmonella enterica Serovar Heidelberg Clone in the Context of Outbreak Investigations

“…In other words, outbreaks attributed to food products that are not consumed locally (at a single restaurant or social event, for example) will go undetected, thus preventing strong laboratory evidence to link human cases to each other and to potential sources. Recent studies have demonstrated the strength of WGS subtyping of outbreaks using hqSNV analysis for several foodborne outbreaks or outbreaks attributed to other serovars of Salmonella (4,10,12,14,21), including the previously problematic clonal S. Enteritidis (13). This study yielded very strong laboratory evidence of genetic relatedness between epidemiologically related isolates where previous conventional laboratory evidence obtained by PFGE and phage type was weak at best.…”

“…The increasing readiness of WGS technology combined with the widely hypothesized and previously reported high concordance of WGSbased typing approaches with epidemiological data have resulted in the widespread adoption of WGS surveillance and outbreak response by global contemporaries responsible for public health and food safety, and this method is positioned to replace PFGEbased molecular epidemiology of foodborne pathogens (10,(12)(13)(14). This revolution in global disease surveillance has created the urgency for Canadian public health laboratories to apply WGS technology to routine public health activities.…”

Epidemiological significance of Salmonella enterica serovar Montevideo and the potential role of feed for their entry into the food chain

“…Next-generation sequencing (NGS) is a new technology producing dramatic advancement in molecular investigation of epidemics associated with contaminated food. The method enables investigation of genetic relatedness of clinical isolates, food-contaminating isolates and their environmental counterparts (Allard et al, 2012 (Gericke et al, 1988). The isolates from the feces of diseased infants manifested variable antimicrobial resistance (ranging from susceptible to multiple resistant).…”

“…Among the foodborne pathogens, Salmonella enterica is one of the most devastating pathogens (Gieraltowski et al, 2013). Salmonellosis is responsible for 11% all food related deaths (Allard et al, 2012), and the incidence of salmonellosis in the human population has not been decreasing during the past decade (Brendan et al, 2013). Manual for reporting on food-borne outbreaks (EFSA, 2015) recommends that severity of disease can be characterized by reporting the number of deaths and hospitalizations.…”

Genomic Analysis of Bacterial Outbreaks

“…(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;…”