Using genomics to trace Salmonella transmission and antimicrobial resistance (AMR) in the poultry and swine food chains in the Philippines

<p>Salmonellosis, caused by Salmonella spp., is among the most commonly reported foodborne diseases globally, and has a high health and economic burden in both animals and humans. Salmonella enterica is a primary cause of cases and outbreaks of diarrhoea worldwide, including in the Philippines. While numerous potential methods of transmission exist, commercial chicken and pig meat have been recognised as crucial food vehicles for S. enterica. The forecasted increase in consumption and utilisation of swine and poultry products in the Philippines in the next 10 years to over 3 million metric tonnes per annum, increases the likelihood for exposure to the bacterium. Previous studies from our Philippine team have shown that S. enterica is circulating in the chicken and pig food chains in Metropolitan Manila, and is a likely major and increasing cause of food poisoning. Notably, treatment options for salmonellosis are decreasing as the bacteria increase in their resistance to antimicrobial drugs. Due to frequent use of antibiotics, chickens and pigs are now realized as potential risks in disseminating drug-resistant S. enterica, with multi-drug resistant (MDR) strains now reported to be present in the Philippines. For this study, we propose to compare at the genetic level of past and present samples of S. enterica across live animal and processed meat domains in the chicken and pig food chains in Metropolitan Manilla. We will perform whole genome sequencing (WGS) of historical and prospectively collected S. enterica bacteria isolated from these samples. WGS technology has become a rapid and affordable tool that is revolutionising the fields of genetics, microbiology, and ecology, as well as public health surveillance and response, including animal health. WGS analysis has enabled new and often unpredicted routes to disease by defining resistance genotypes and their historical generation, predicting resistance phenotypes and identifying similar isolate genomes that are partof a transmission chains. The resulting genomic variation will increase our understanding of transmission and drug resistance to permit more effective interventions. These genomic data will be correlated with laboratory determined virulence and drug resistance outcomes and other collected meta data to enable an important contribution in disease control and prevention</p>