As a leading cause of foodborne illness, hospitalization, and death in the U.S., Salmonella has a significant public health and economic impact. The pathogen's estimated economic burden in 2013 alone was $3.67 billion1. Although recent regulatory initiatives aim to reduce salmonellosis by 25% by 20302, gaps in current detection and mitigation strategies remain evident, particularly in aligning processing plant surveillance with public health outcomes3 .
Frozen ready-to-cook poultry products, which have been implicated in multiple Salmonella outbreaks, are a significant concern for public health. In response, the Food Safety and Inspection Service (FSIS) classified Salmonella as an adulterant in these products. Currently, FSIS Microbiology Laboratory Guidebook (MLG) 4.15 focuses solely on determining the prevalence of Salmonella in poultry products4. Under this guideline, collected samples are enriched for 18-24 h and then screened using the Molecular Detection System (MDS), which identifies the presence or absence of Salmonella but does not offer insight into the level of contamination. While this approach is valuable for detecting the presence of pathogens, it fails to provide quantitative information that could help food processors assess contamination risks more accurately and take targeted corrective actions.
In this study, we developed a method to augment detection from prevalence to quantification of microbial pathogens. It was designed for seamless integration into existing processes to detect Salmonella in poultry products with minimal disruption to current FSIS protocols. Instead of simply enriching the bulk sample, the method begins by washing the poultry products using media consistent with current FSIS methods. The rinse is then distributed into the first column of a 48-deep well block. Serial dilutions are performed across the remaining five columns, and the block is incubated for 18-24 h, aligning with the MLG 4.15 protocol. After incubation, the wells are tested for Salmonella, and the results are used to calculate the most probable number (MPN)5,6. This approach allows for quantification of contamination within the same time frame as the current FSIS process, making it a practical option for both industry and regulatory use. Figure 1 depicts a block diagram summarizing the modified MPN assay. The figure includes photographs taken at specific steps, the 48-well block utilized for dilution and growth of replicates, and the three techniques used as benchmarks to assess the most probable number of Salmonella present in ground chicken. In the first phase of this study, we utilized irradiated ground chicken to minimize the impact of background microflora and uncertainty of measurements relative to verified inoculum before applying the protocol to non-irradiated chicken samples.