Heuristic and Hierarchical-Based Population Mining of Salmonella enterica Lineage I Pan-Genomes as a Platform to Enhance Food Safety

The recent incorporation of bacterial whole-genome sequencing (WGS) into Public Health laboratories has enhanced foodborne outbreak detection and source attribution. As a result, large volumes of publicly available datasets can be used to study the biology of foodborne pathogen populations at an unprecedented scale. To demonstrate the application of a heuristic and agnostic hierarchical population structure guided pan-genome enrichment analysis (PANGEA), we used populations of S. enterica lineage I to achieve two main objectives: (i) show how hierarchical population inquiry at different scales of resolution can enhance ecological and epidemiological inquiries; and (ii) identify population-specific inferable traits that could provide selective advantages in food production environments. Publicly available WGS data were obtained from NCBI database for three serovars of Salmonella enterica subsp. enterica lineage I (S. Typhimurium, S. Newport, and S. Infantis). Using the hierarchical genotypic classifications (Serovar, BAPS1, ST, cgMLST), datasets from each of the three serovars showed varying degrees of clonal structuring. When the accessory genome (PANGEA) was mapped onto these hierarchical structures, accessory loci could be linked with specific genotypes. A large heavy-metal resistance mobile element was found in the Monophasic ST34 lineage of S. Typhimurium, and laboratory testing showed that Monophasic isolates have on average a higher degree of copper resistance than the Biphasic ones. In S. Newport, an extra sugE gene copy was found among most isolates of the ST45 lineage, and laboratory testing of multiple isolates confirmed that isolates of S. Newport ST45 were on average less sensitive to the disinfectant cetylpyridimium chloride than non-ST45 isolates. Lastly, data-mining of the accessory genomic content of S. Infantis revealed two cryptic Ecotypes with distinct accessory genomic content and distinct ecological patterns. Poultry appears to be the major reservoir for Ecotype 1, and temporal analysis further suggested a recent ecological succession, with Ecotype 2 apparently being displaced by Ecotype 1. Altogether, the use of a heuristic hierarchical-based population structure analysis that includes bacterial pan-genomes (core and accessory genomes) can (1) improve genomic resolution for mapping populations and accessing epidemiological patterns; and (2) define lineage-specific informative loci that may be associated with survival in the food chain.

Automated summary

Incorporating bacterial whole-genome sequencing into Public Health laboratories has improved foodborne outbreak detection and source attribution. Analysis on the populations of three serovars of Salmonella enterica subsp. enterica revealed insights on ecological and epidemiological patterns at different hierarchical scales, demonstrating the potential for using genomics in understanding pathogen populations. Additionally, identification of lineage-specific informative loci that may provide selective advantages in food production environments was achieved.