Abstract
Salmonella enterica is a highly diverse group of organisms with over 2,500 serovars described to date. However, not all serovars are pathogenic to humans and animals. Many serovars typically cause self-limiting gastrointestinal infections, but certain host-adapted serovars, as well as those expressing specialized virulence factors (e.g., Vi capsule) have an increased potential to cause bacteremia and trigger systemic responses, necessitating immediate medical attention. Timely identification of Salmonella at the serovar level is, therefore, critical for informing risk assessments, guiding clinical decision-making and implementing effective strategies to prevent and control both environmental contamination and clinical infections. Yet, access to Salmonella serotyping services remains limited and unevenly distributed worldwide, causing substantial delays in responses to contamination and outbreaks, particularly in remote communities and under-resourced settings, Nanopore sequencing has emerged as a highly portable platform with a relatively low cost of entry that renders it an ideal technology to enable the widespread decentralization of Salmonella serotyping by sequencing. Here, we introduce a robust and accurate end-to-end laboratory workflow that utilizes long-read nanopore sequencing to generate Salmonella whole genome sequencing (WGS) data at a quality and depth sufficient for Salmonella risk assessment in routine diagnostic settings We validated our workflow against a panel of 16 serovars comprising 80 environmental isolates sampled from Canadian poultry farms, yielding 100% accuracy in serovar prediction. We showed that our workflow can obtain serotyping results and identify genetic risk factors within 24 h of bacterial isolation-a significant improvement over the typical 3 weeks turnaround in Canada. We additionally demonstrated the added benefits of WGS by annotating the draft genome assemblies generated from our laboratory workflow to identify virulence factors and antimicrobial resistance (AMR) determinants, leading to our discovery of previously uncharacterized genetic signatures putatively associated with Salmonella adaptation to avian environments, such as aerobactin biosynthesis genes. The genomic analyses presented herein have been packaged as an open-source, user-friendly sequence analysis pipeline that facilitates standardized, reproducible, scalable and portable analysis of Salmonella surface antigen markers and genetic risk factors associated with pathogenicity and AMR. Our protocol provides a comprehensive toolkit that empowers regional and local laboratories to independently conduct Salmonella risk assessments at scale-an essential step toward establishing real-time genomic surveillance and equitable access to contemporary diagnostic technologies.