Listeria monocytogenes (Lm) is a major human foodborne pathogen. Numerous Lm outbreaks have been reported worldwide and associated with a high case fatality rate, reinforcing the need for strongly coordinated surveillance and outbreak control. We developed a universally applicable genome-wide strain genotyping approach and investigated the population diversity of Lm using 1,696 isolates from diverse sources and geographical locations. We define, with unprecedented precision, the population structure of Lm, demonstrate the occurrence of international circulation of strains and reveal the extent of heterogeneity in virulence and stress resistance genomic features among clinical and food isolates. Using historical isolates, we show that the evolutionary rate of Lm from lineage I and lineage II is low (∼2.5 × 10 substitutions per site per year, as inferred from the core genome) and that major sublineages (corresponding to so-called 'epidemic clones') are estimated to be at least 50-150 years old. This work demonstrates the urgent need to monitor Lm strains at the global level and provides the unified approach needed for global harmonization of Lm genome-based typing and population biology.

Listeria monocytogenes (Lm) causes severe foodborne illness (listeriosis). Previous molecular subtyping methods, such as pulsed-field gel electrophoresis (PFGE), were critical in detecting outbreaks that led to food safety improvements and declining incidence, but PFGE provides limited genetic resolution. A multiagency collaboration began performing real-time, whole-genome sequencing (WGS) on all US Lm isolates from patients, food, and the environment in September 2013, posting sequencing data into a public repository. Compared with the year before the project began, WGS, combined with epidemiologic and product trace-back data, detected more listeriosis clusters and solved more outbreaks (2 outbreaks in pre-WGS year, 5 in WGS year 1, and 9 in year 2). Wholegenome multilocus sequence typing and single nucleotide polymorphism analyses provided equivalent phylogenetic relationships relevant to investigations; results were most useful when interpreted in context of epidemiological data. WGS has transformed listeriosis outbreak surveillance and is being implemented for other foodborne pathogens.

Shiga toxin-producing Escherichia coli (STEC) is an important foodborne pathogen capable of causing severe disease in humans. Rapid and accurate identification and characterization techniques are essential during outbreak investigations. Current methods for characterization of STEC are expensive and time-consuming. With the advent of rapid and cheap whole genome sequencing (WGS) benchtop sequencers, the potential exists to replace traditional workflows with WGS. The aim of this study was to validate tools to do reference identification and characterization from WGS for STEC in a single workflow within an easy to use commercially available software platform. Publically available serotype, virulence, and antimicrobial resistance databases were downloaded from the Center for Genomic Epidemiology (CGE) (www.genomicepidemiology.org) and integrated into a genotyping plug-in with in silico PCR tools to confirm some of the virulence genes detected from WGS data. Additionally, down sampling experiments on the WGS sequence data were performed to determine a threshold for sequence coverage needed to accurately predict serotype and virulence genes using the established workflow. The serotype database was tested on a total of 228 genomes and correctly predicted from WGS for 96.1% of O serogroups and 96.5% of H serogroups identified by conventional testing techniques. A total of 59 genomes were evaluated to determine the threshold of coverage to detect the different WGS targets, 40 were evaluated for serotype and virulence gene detection and 19 for the stx gene subtypes. For serotype, 95% of the O and 100% of the H serogroups were detected at > 40x and ≥ 30x coverage, respectively. For virulence targets and stx gene subtypes, nearly all genes were detected at > 40x, though some targets were 100% detectable from genomes with coverage ≥20x. The resistance detection tool was 97% concordant with phenotypic testing results. With isolates sequenced to > 40x coverage, the different databases accurately predicted serotype, virulence, and resistance from WGS data, providing a fast and cheaper alternative to conventional typing techniques.

Campylobacter jejuni is a leading cause of enteric bacterial illness in the United States. Traditional molecular subtyping methods, such as pulsed-field gel electrophoresis (PFGE) and 7-gene multilocus sequencing typing (MLST), provided limited resolution to adequately identify C. jejuni outbreaks and separate out sporadic isolates during outbreak investigations. Whole genome sequencing (WGS) has emerged as a powerful tool for C. jejuni outbreak detection. In this investigation, 45 human and 11 puppy isolates obtained during a 2016-2018 outbreak linked to pet store puppies were sequenced. Core genome multilocus sequence typing (cgMLST) and high-quality single nucleotide polymorphism (hqSNP) analysis of the sequence data separated the isolates into the same two clades containing minor within clade differences; however, cgMLST analysis does not require selection of an appropriate reference genome making this method preferable to hqSNP analysis for Campylobacter surveillance and cluster detection. The isolates were classified as ST2109—a rarely seen MLST sequence type. PFGE was performed on 38 human and 10 puppy isolates; PFGE patterns did not reliably predict clustering by cgMLST analysis. Genetic detection of antimicrobial resistance determinants predicted that all outbreak-associated isolates would be resistant to six drug classes. Traditional antimicrobial susceptibility testing (AST) confirmed a high correlation between genotypic and phenotypic antimicrobial resistance determinations. WGS analysis linked C. jejuni isolates in humans and pet store puppies even when canine exposure information was unknown, aiding the epidemiological investigation during this outbreak. WGS data were also used to quickly identify the highly drug-resistant profile of these outbreak-associated C. jejuni isolates.

We used a two-step whole genome sequencing analysis for resolving two concurrent outbreaks in two neonatal services in Belgium, caused by exfoliative toxin A-encoding-gene-positive (eta+) methicillin-susceptible Staphylococcus aureus with an otherwise sporadic spa-type t209 (ST-109). Outbreak A involved 19 neonates and one healthcare worker in a Brussels hospital from May 2011 to October 2013. After a first episode interrupted by decolonization procedures applied over 7 months, the outbreak resumed concomitantly with the onset of outbreak B in a hospital in Asse, comprising 11 neonates and one healthcare worker from mid-2012 to January 2013. Pan-genome multilocus sequence typing, defined on the basis of 42 core and accessory reference genomes, and single-nucleotide polymorphisms mapped on an outbreak-specific de novo assembly were used to compare 28 available outbreak isolates and 19 eta+/spa-type t209 isolates identified by routine or nationwide surveillance. Pan-genome multilocus sequence typing showed that the outbreaks were caused by independent clones not closely related to any of the surveillance isolates. Isolates from only ten cases with overlapping stays in outbreak A, including four pairs of twins, showed no or only a single nucleotide polymorphism variation, indicating limited sequential transmission. Detection of larger genomic variation, even from the start of the outbreak, pointed to sporadic seeding from a pre-existing exogenous source, which persisted throughout the whole course of outbreak A. Whole genome sequencing analysis can provide unique fine-tuned insights into transmission pathways of complex outbreaks even at their inception, which, with timely use, could valuably guide efforts for early source identification.