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This multiagency report developed by the Interagency Collaboration for Genomics for Food and Feed Safety provides an overview of the use of and transition to whole genome sequencing (WGS) technology for detection and characterization of pathogens transmitted commonly by food and for identification of their sources. We describe foodborne pathogen analysis, investigation, and harmonization efforts among the following federal agencies: National Institutes of Health; Department of Health and Human Services, Centers for Disease Control and Prevention (CDC) and U.S. Food and Drug Administration (FDA); and the U.S. Department of Agriculture, Food Safety and Inspection Service, Agricultural Research Service, and Animal and Plant Health Inspection Service. We describe single nucleotide polymorphism, core-genome, and whole genome multilocus sequence typing data analysis methods as used in the PulseNet (CDC) and GenomeTrakr (FDA) networks, underscoring the complementary nature of the results for linking genetically related foodborne pathogens during outbreak investigations while allowing flexibility to meet the specific needs of Interagency Collaboration partners. We highlight how we apply WGS to pathogen characterization (virulence and antimicrobial resistance profiles) and source attribution efforts and increase transparency by making the sequences and other data publicly available through the National Center for Biotechnology Information. We also highlight the impact of current trends in the use of culture-independent diagnostic tests for human diagnostic testing on analytical approaches related to food safety and what is next for the use of WGS in the area of food safety.

Species and subspecies within the Salmonella genus have been defined for public health purposes by biochemical properties; however, reference laboratories have increasingly adopted sequence-based, and especially whole genome sequence (WGS), methods for surveillance and routine identification. This leads to potential disparities in subspecies definitions, routine typing, and the ability to detect novel subspecies. A large-scale analysis of WGS data from the routine sequencing of clinical isolates was employed to define and characterise Salmonella subspecies population structure, demonstrating that the Salmonella species and subspecies were genetically distinct, including those previously identified through phylogenetic approaches, namely: S. enterica subspecies londinensis (VII), subspecies brasiliensis (VIII), subspecies hibernicus (IX) and subspecies essexiensis (X). The analysis also identified an additional novel subspecies, reptilium (XI). Further, these analyses indicated that S. enterica subspecies arizonae (IIIa) isolates were divergent from the other S. enterica subspecies, which clustered together and, on the basis of ANI analysis, subspecies IIIa was sufficiently distinct to be classified as a separate species, S. arizonae. Multiple phylogenetic and statistical approaches generated congruent results, suggesting that the proposed species and subspecies structure was sufficiently biologically robust for routine application. Biochemical analyses demonstrated that not all subspecies were distinguishable by these means and that biochemical approaches did not capture the genomic diversity of the genus. We recommend the adoption of standardised genomic definitions of species and subspecies and a genome sequence-based approach to routine typing for the identification and definition of novel subspecies., Highlights • A large-scale analysis of genomic data demonstrate Salmonella species and subspecies are genetically distinct. • Biochemical analysis does not capture the genomic diversity of the Salmonella genus but routine species and subspecies identification can be achieved with rMLST • Average Nucleotide Identify (ANI) with a 95% criteria was suitable to distinguish species and 98% to distinguish subspecies. • Five novel S. enteric subspecies (VII-XI) type strains are defined. • Reclassification of S. arizonae as a separate species is recommended.