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ARS Home » Plains Area » Clay Center, Nebraska » U.S. Meat Animal Research Center » Meat Safety and Quality » Research » Publications at this Location » Publication #419714

Research Project: Identification, Genomic Characterization, and Metabolic Modeling of Foodborne Pathogens in the Meat Production Continuum

Location: Meat Safety and Quality

Title: A novel approach for detecting Salmonella enterica strains frequently attributed to human illness - development and validation of the highly pathogenic Salmonella (HPS) multiplex PCR assay

Author
item Harhay, Dayna
item Brader, Kerry
item Katz, Tatum
item Harhay, Gregory
item Bono, James
item Bosilevac, Joseph
item Wheeler, Tommy

Submitted to: Frontiers in Microbiology
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 12/16/2024
Publication Date: 1/7/2025
Citation: Harhay, D.M., Brader, K.D., Katz, T.S., Harhay, G.P., Bono, J.L., Bosilevac, J.M., Wheeler, T.L. 2025. A novel approach for detecting Salmonella enterica strains frequently attributed to human illness - development and validation of the highly pathogenic Salmonella (HPS) multiplex PCR assay. Frontiers in Microbiology. 15. Article 1504621. https://doi.org/10.3389/fmicb.2024.1504621.
DOI: https://doi.org/10.3389/fmicb.2024.1504621

Interpretive Summary: Salmonella enterica is a leading cause of foodborne illnesses and a global concern for human health. While there are over 2,600 different types of Salmonella, human illness data suggests that certain Salmonella (Salmonella of concern (SoC)) are better at causing disease than others. To improve food safety, there is a need to develop an assay to rapidly detect SoC and distinguish them from Salmonella that are less pathogenic. To address this need we compared genome sequences of more pathogenic Salmonella to those less pathogenic and identified eight genes that could be used to identify more pathogenic versions of Salmonella. An assay was developed to detect the presence of these 8 genes and Salmonella having five or more of the genes were designated Highly Pathogenic Salmonella (HPS). The assay was tested on 1,303 Salmonella from meat and poultry samples and demonstrated to be very accurate at identifying SoC. These data lay the groundwork for development of a rapid, commercial assay for detecting HPS, which will improve human health by reducing exposure to more pathogenic versions of Salmonella.

Technical Abstract: Introduction: Non-typhoidal Salmonella enterica (NTS) are leading bacterial agents of foodborne illnesses and a global concern for human health. While there are over 2,600 different serovars of NTS, epidemiological data suggests that certain serovars are better at causing disease than others, resulting in the majority of reported human illnesses in the United States. To improve food safety, there is a need to rapidly detect these more pathogenic serovars to facilitate their removal from the food supply. Methods: Addressing this need, we conducted a comparative analysis of 23 closed Salmonella genomic sequences of five serotypes. The analysis pinpointed eight genes (sseK2, sseK3, gtgA/gogA, avrA, lpfB, SspH2, spvD, and invA) that in combination, identify 7 of the 10 leading Salmonella serovars attributed to human illnesses in the US each year (i.e., Serovars of Concern or SoC). A multiplex PCR assay was developed to detect the presence of these genes, with strains amplifying five or more targets designated Highly Pathogenic Salmonella, or HPS. The utility of the resulting HPS assay for identifying SoC was examined in silico, using BLAST to determine the distribution of gene targets among closed Salmonella genome sequences in GenBank (n'='2,192 representing 148 serotypes) and by assaying 1,303 Salmonella (69 serotypes), isolated from FSIS regulatory samples. Results and discussion: Comparison of serotypes identified by the assay as HPS, with those identified as SoC, produced an Area Under the Curve (AUC) of 92.2% with a specificity of 96% and a positive predictive value of 97.4%, indicating the HPS assay has strong ability to identify SoC. The data presented lay the groundwork for development of rapid commercial assays for the detection of SoC.