Next Generation Sequencing for the Detection of Foodborne Microbial Pathogens

Next generation sequencing (NGS) has become a central tool for pathogen detection since the introduction of the first NGS platform over a decade ago. NGS has enabled the routine whole genome sequencing (WGS) of bacterial isolates from clinical, suspect contaminated, and environmental samples. Vast databases, replete with invaluable metadata regarding time and geographic location of collection, are rapidly changing the landscape of disease surveillance, detection, and response. Few isolates are exactly alike at the genomic level and the utilization of WGS data for the high-resolution discrimination of differences has made NGS an indispensable technology for the typing and detection of pathogenic microbes. Bulk sequencing of Salmonella enterica isolates, an important and highly prevalent foodborne pathogen, has served as the prototype for how NGS technology and data can be integrated into and inform preventative public health efforts through rapid, accurate linkage between environmental and clinical samples, and alert to practices that may increase the likelihood of an outbreak. The increasing accessibility of NGS platforms to researchers in all fields of biology has led to substantial growth in the depth and diversity of publicly available nucleotide sequence databases. In turn this availability has opened new avenues for the exploration of how widespread important virulence factors are and how they affect pathogenesis. Direct bioinformatics-driven analysis of genome assemblies resulting from WGS studies provide new opportunities to characterize horizontally mobile virulence factors and a range of genomic features, important for understanding pathogenesis for both known and emerging pathogens. Our goals for this chapter are to inform investigators of the basics behind NGS, how data are produced and how they can be utilized to inform the detection and study of pathogen(s) of interest. Further we describe how the investigator can leverage a priori knowledge of that pathogen to influence the experimental design and how to maximize the usefulness of NGS data. In the context of WGS of cultured bacterial isolates, we provide an overview of how NGS platform selection influences the type of sequence data produced. Using two important foodborne bacterial pathogens that have little else in common, Salmonella enterica and Clostridium botulinum, we illustrate the already wide range of detection applications enabled by WGS data and discuss how NGS is revolutionizing disease detection, surveillance, and response.