Whole genome sequencing analysis of multiple Salmonella serovars provides insights into phylogenetic relatedness, antimicrobial resistance, and virulence markers across humans, food animals and agriculture environmental sources

Abstract

Background: Salmonella enterica is a significant foodborne pathogen, which can be transmitted via several distinct routes, and reports on acquisition of antimicrobial resistance (AMR) are increasing. To better understand the association between human Salmonella clinical isolates and the potential environmental/animal reservoirs, whole genome sequencing (WGS) was used to investigate the epidemiology and AMR patterns within Salmonella isolates from two adjacent US states. Results: WGS data of 200 S. enterica isolates recovered from human (n = 44), swine (n = 32), poultry (n = 22), and farm environment (n = 102) were used for in silico prediction of serovar, distribution of virulence genes, and phylogenetically clustered using core genome single nucleotide polymorphism (SNP) and feature frequency profiling (FFP). Furthermore, AMR was studied both by genotypic prediction using five curated AMR databases, and compared to phenotypic AMR using broth microdilution. Core genome SNP-based and FFP-based phylogenetic trees showed consistent clustering of isolates into the respective serovars, and suggested clustering of isolates based on the source of isolation. The overall correlation of phenotypic and genotypic AMR was 87.61% and 97.13% for sensitivity and specificity, respectively. AMR and virulence genes clustered with the Salmonella serovars, while there were also associations between the presence of virulence genes in both animal/environmental isolates and human clinical samples. Conclusions: WGS is a helpful tool for Salmonella phylogenetic analysis, AMR and virulence gene predictions. The clinical isolates clustered closely with animal and environmental isolates, suggesting that animals and environment are potential sources for dissemination of AMR and virulence genes between Salmonella serovars.