Phylogenomic Pipeline Validation for Foodborne Pathogen Disease Surveillance

Abstract

Foodborne pathogen surveillance in the United States is transitioning from strain identification using restriction digest technology (pulsed-field gel electrophoresis [PFGE]) to shotgun sequencing of the entire genome (whole-genome sequencing [WGS]). WGS requires a new suite of analysis tools, some of which have long histories in academia but are new to the field of public health and regulatory decision making. Although the general workflow is fairly standard for collecting and analyzing WGS data for disease surveillance, there are a number of differences in how the data are collected and analyzed across public health agencies, both nationally and internationally. This impedes collaborative public health efforts, so national and international efforts are underway to enable direct comparison of these different analysis methods. Ultimately, the harmonization efforts will allow the (mutually trusted and understood) production and analysis of WGS data by labs and agencies worldwide, thus improving outbreak response capabilities globally. This review provides a historical perspective on the use of WGS for pathogen tracking and summarizes the efforts underway to ensure the major steps in phylogenomic pipelines used for pathogen disease surveillance can be readily validated. The tools for doing this will ensure that the results produced are sound, reproducible, and comparable across different analytic approaches.

Keywords: Listeria; Salmonella; WGS; bioinformatic pipeline; foodborne pathogen; outbreak; phylogeny; validation.

FIG 1

NGS phylogenomic workflow for molecular disease surveillance, with critical validation points listed within each module.

FIG 2

Technical view of the two main types of analysis pipelines implemented for foodborne pathogen surveillance. First, DNA is isolated from the bacteria. Then, it is sequenced using a short-read NGS technology. The short reads can be analyzed in two different ways, each with the same goal of uncovering variants across the genome for use in the final clustering step. For the SNP-based approach, short reads from each isolate are mapped to a reference genome (draft or complete assembly), SNPs are called and filtered, filtered SNPs are written to a FASTA formatted SNP matrix, and then a phylogenetic clustering analysis is performed using that matrix as its input file. For the wgMLST- or cgMLST-based approach, short reads from each isolate are mapped against a species-specific allele database, an allele assignment is made for each gene and added to a FASTA-formated allele matrix, and then a phylogenetic clustering analysis is performed using that matrix as its input file.