Abstract

Salmonella spp. is one of the major agents of foodborne disease worldwide, and its virulence genes are responsible for the main pathogenic mechanisms of this micro-organism. The whole-genome sequencing (WGS) of pathogens has become a lower-cost and more accessible genotyping tool providing many gene analysis possibilities. This study provided an in silico investigation of 129 virulence genes, including plasmidial and bacteriophage genes from Brazilian strains' public Salmonella genomes. The frequency analysis of the four most sequenced serovars and a temporal analysis over the past four decades was also performed. The NCBI sequence reads archive (SRA) database comprised 1077 Salmonella public whole-genome sequences of strains isolated in Brazil between 1968 and 2018. Among the 1077 genomes, 775 passed in Salmonella in silico Typing (SISTR) quality control, which also identified 41 different serovars in which the four most prevalent were S. Enteritidis, S. Typhimurium, S. Dublin, and S. Heidelberg. Among these, S. Heidelberg presented the most distinct virulence profile, besides presenting Yersinia High Pathogenicity Island (HPI), rare and first reported in Salmonella from Brazil. The genes mgtC, csgC, ssaI and ssaS were the most prevalent within the 775 genomes with more than 99% prevalence. On the other hand, the less frequent genes were astA, iucBCD, tptC and shdA, with less than 1% frequency. All of the plasmids and bacteriophages virulence genes presented a decreasing trend between the 2000s and 2010s decades, except for the phage gene grvA, which increased in this period. This study provides insights into Salmonella virulence genes distribution in Brazil using freely available bioinformatics tools. This approach could guide in vivo and in vitro studies besides being an interesting method for the investigation and surveillance of Salmonella virulence. Moreover, here we propose the genes mgtC, csgC, ssaI and ssaS as additional targets for PCR identification of Salmonella in Brazil due to their very high frequency in the studied genomes.

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