WGS
How is whole genome sequencing (WGS) data being used?
Whole genome sequence (WGS) analysis can be used for high-resolution subtyping of foodborne pathogens, such as E. coli O157, Salmonella and Listeria monocytogenes. WGS analysis has been used by regulatory (e.g., FDA-CFSAN, USDA-FSIS) and public health (e.g., CDC) agencies in surveillance, traceback and outbreak investigations. By comparing the WGS data from various isolates of the same pathogen, agencies can assess how genetically related the isolates are and identify (i) clusters of genetically related clinical isolates (i.e., cluster detection), (ii) clusters of genetically related isolates obtained over a long period of time from a single facility (i.e., persistent/resident strains), and (iii) associations between clinical and environmental/food isolates (i.e., source detection).
Genetic relationship is assessed through two main methods: single nucleotide polymorphism (SNP) differences and core genome multi locus sequence typing (cgMLST) allelic differences. Although these two methods are based on WGS data and tend to provide similar results, each method requires specific bioinformatic tools and has its own advantages and disadvantages. FDA-CFSAN uses SNP differences to assess the genetic relationship of isolates while CDC used cgMLST allelic differences to assess the genetic relationship of isolates.
Public databases host the WGS data and associated metadata obtained by regulatory and public health agencies and provide tools that allow for visualization of the WGS analysis (e.g., NCBI Pathogen Detection: https://www.ncbi.nlm.nih.gov/pathogens/).