title: A Comparative Analysis of the Lyve-SET Phylogenomics Pipeline for Genomic Epidemiology of Foodborne Pathogens.
abstract: Modern epidemiology of foodborne bacterial pathogens in industrialized countries relies increasingly on whole genome sequencing (WGS) techniques. As opposed to profiling techniques such as pulsed-field gel electrophoresis, WGS requires a variety of computational methods. Since 2013, United States agencies responsible for food safety including the CDC, FDA, and USDA, have been performing whole-genome sequencing (WGS) on allListeria monocytogenesfound in clinical, food, and environmental samples. Each year, more genomes of other foodborne pathogens such asEscherichia coli, Campylobacter jejuni, andSalmonella entericaare being sequenced. Comparing thousands of genomes across an entire species requires a fast method with coarse resolution; however, capturing the fine details of highly related isolates requires a computationally heavy and sophisticated algorithm. MostL. monocytogenesinvestigations employing WGS depend on being able to identify an outbreak clade whose inter-genomic distances are less than an empirically determined threshold. When the difference between a few single nucleotide polymorphisms (SNPs) can help distinguish between genomes that are likely outbreak-associated and those that are less likely to be associated, we require a fine-resolution method. To achieve this level of resolution, we have developed Lyve-SET, a high-quality SNP pipeline. We evaluated Lyve-SET by retrospectively investigating 12 outbreak data sets along with four other SNP pipelines that have been used in outbreak investigation or similar scenarios. To compare these pipelines, several distance and phylogeny-based comparison methods were applied, which collectively showed that multiple pipelines were able to identify most outbreak clusters and strains. Currently in the US PulseNet system, whole genome multi-locus sequence typing (wgMLST) is the preferred primary method for foodborne WGS cluster detection and outbreak investigation due to its ability to name standardized genomic profiles, its central database, and its ability to be run in a graphical user interface. However, creating a functional wgMLST scheme requires extended up-front development and subject-matter expertise. When a scheme does not exist or when the highest resolution is needed, SNP analysis is used. Using threeListeriaoutbreak data sets, we demonstrated the concordance between Lyve-SET SNP typing and wgMLST.Availability: Lyve-SET can be found at https://github.com/lskatz/Lyve-SET.
authors.affiliation: Enteric Diseases Laboratory Branch, Centers for Disease Control and PreventionAtlanta, GA, USA; Center for Food Safety, College of Agricultural and Environmental Sciences, University of GeorgiaGriffin, GA, USA.
authors.forename: Lee S
authors.initials: LS
authors.lastname: Katz
authors.affiliation: Enteric Diseases Laboratory Branch, Centers for Disease Control and PreventionAtlanta, GA, USA; Oak Ridge Institute for Science and Education, Oak Ridge Associated UniversitiesOak Ridge, TN, USA.
authors.forename: Taylor
authors.initials: T
authors.lastname: Griswold
authors.affiliation: Enteric Diseases Laboratory Branch, Centers for Disease Control and PreventionAtlanta, GA, USA; IHRC, Inc.Atlanta, GA, USA.
authors.forename: Amanda J
authors.initials: AJ
authors.lastname: Williams-Newkirk
authors.affiliation: Enteric Diseases Laboratory Branch, Centers for Disease Control and PreventionAtlanta, GA, USA; IHRC, Inc.Atlanta, GA, USA.
authors.forename: Darlene
authors.initials: D
authors.lastname: Wagner
authors.affiliation: National Microbiology Laboratory, Public Health Agency of Canada Winnipeg, MB, Canada.
authors.forename: Aaron
authors.initials: A
authors.lastname: Petkau
authors.affiliation: National Microbiology Laboratory, Public Health Agency of Canada Winnipeg, MB, Canada.
authors.forename: Cameron
authors.initials: C
authors.lastname: Sieffert
authors.affiliation: National Microbiology Laboratory, Public Health Agency of Canada Winnipeg, MB, Canada.
authors.forename: Gary
authors.initials: G
authors.lastname: Van Domselaar
authors.affiliation: Center for Food Safety, College of Agricultural and Environmental Sciences, University of Georgia Griffin, GA, USA.
authors.forename: Xiangyu
authors.initials: X
authors.lastname: Deng
authors.affiliation: Enteric Diseases Laboratory Branch, Centers for Disease Control and Prevention Atlanta, GA, USA.
authors.forename: Heather A
authors.initials: HA
authors.lastname: Carleton
keywords: SNP pipeline; bacterial pathogen; foodborne; genomic epidemiology; outbreak; wgMLST