Distribution of Antimicrobial Resistance Genes Across Salmonella enterica Isolates from Animal and Nonanimal Foods

• Published in: Journal of food protection 2020-02, Vol.83 (2), p.295-304
• Main Authors: Pettengill, J B, Tate, H, Gensheimer, K, Hsu, C H, Ihrie, J, Markon, A O, McDERMOTT, P F, Zhao, S, Strain, E, Bazaco, M C
• Format: Article
• Language: English
• Subjects: Agriculture; Aminoglycosides; Animals; Antibiotics; Antiinfectives and antibacterials; Antimicrobial agents; Antimicrobial resistance; Beef; Commodities; Disease; Drug resistance; Food; Food processing; Food safety; Food sources; Food supply; Foodborne diseases; Genes; Genomes; Health surveillance; Infections; Metadata; Nuts; Pathogens; Pork; Public health; Risk assessment; Salmonella; Seeds; Sulfonamides
• ISSN: 0362-028X; 1944-9097; 1944-9097
• DOI: 10.4315/0362-028X.JFP-19-310

Antimicrobial-resistant bacteria are a major public health problem. Of particular importance in the context of food safety is the prevalence of antimicrobial resistance (AMR) genes within nontyphoidal Salmonella, which is a leading bacterial cause of foodborne disease. We determined the prevalence of AMR genes across a very large number of Salmonella genomes (n = 25,647) collected from isolates from 16 common food sources. The average percentage of isolates from nonanimal foods, such as fruit, nuts and seeds, and vegetables, harboring at least one AMR gene was only marginally lower (72%) than that observed in isolates from animal foods such as beef, chicken, turkey, and pork (74%). This high prevalence of AMR genes was primarily driven by the high prevalence of aminoglycoside resistance genes in nearly all food isolates; genes for resistance to tetracycline and sulfonamide also were highly prevalent. However, evaluation of the number of genes per isolate revealed that the prevalence of AMR genes was higher in animal food isolates than in nonanimal food isolates (P = 0.018). A random forest analysis provided evidence that within a given serovar, resistance gene profiles differed according to isolate food source. AMR gene profiles could be used to correctly predict the food of origin for 71% of the isolates, but success differed according to serovar. This information can help inform AMR risk assessments of food commodities and refine processes for targeting interventions to limit the spread of AMR through the food supply.