Abstract
Background
Salmonella enterica
remains a leading cause of food-borne diseases worldwide. Serotype information is important in food safety and public health activities to reduce the burden of salmonellosis. In the current study, two methods were used to determine serotypes of 111 strains of
Salmonella
isolated from poultry feces in Burkina Faso. First,
Salmonella
Multiplex Assay for Rapid Typing (SMART) Polymerase Chain Reaction (PCR) was used to determine the serovars of the
S. enterica
isolates. Second, serovar prediction based on whole genome sequencing (WGS) data was performed using SeqSero 2.0.
Results
Among the 111
Salmonella
isolates, serotypes for 17 (15.31%) isolates were identified based on comparison to a panel of representative SMART codes previously determined for the 50 most common serovars in the United States. Forty-four (44) new SMART codes were developed for common and uncommon serotypes. A total of 105 (94.59%) isolates were serotyped using SeqSero 2.0 for serovar prediction based on WGS data.
Conclusion
We determined that SeqSero 2.0 was more comprehensive for identifying
Salmonella
serotypes from Burkina Faso than SMART PCR.