Assèta Kagambèga1,2,3, Lari M Hiott4, David S Boyle5, Elizabeth A McMillan4, Poonam Sharma4, Sushim K Gupta4, Hazem Ramadan4,6, Sohyun Cho4, Shaheen B Humayoun4, Tiffanie A Woodley4, Nicolas Barro7, Charlene R Jackson4, Jonathan G Frye4. 1. Bacterial Epidemiology and Antimicrobial Resistance Research Unit, U.S. National Poultry Research Center, USDA, ARS, Athens, GA, USA. kagambega.asseta@gmail.com. 2. Laboratoire de Biologie Moléculaire, d'épidémiologie et de surveillance des bactéries et virus transmissibles par les aliments (LaBESTA)/Ecole Doctorale Sciences et Technologies (EDST)/Université Joseph KI-ZERBO, Ouagadougou, Burkina Faso. kagambega.asseta@gmail.com. 3. Institut des Sciences, Ministère des enseignement supérieur, de la recherche scientifique et de l'innovation, Ouagadougou, Burkina Faso. kagambega.asseta@gmail.com. 4. Bacterial Epidemiology and Antimicrobial Resistance Research Unit, U.S. National Poultry Research Center, USDA, ARS, Athens, GA, USA. 5. PATH, Suite 200, Seattle, WA, 98121, USA. 6. Hygiene and Zoonoses Department, Faculty of Veterinary medicine, Mansoura University, Mansoura, 35516, Egypt. 7. Laboratoire de Biologie Moléculaire, d'épidémiologie et de surveillance des bactéries et virus transmissibles par les aliments (LaBESTA)/Ecole Doctorale Sciences et Technologies (EDST)/Université Joseph KI-ZERBO, Ouagadougou, Burkina Faso.
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.
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.
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