Droplet Digital Polymerase Chain Reaction Assay for Quantifying Salmonella in Meat Samples

TL;DR

This paper introduces a fast and accurate ddPCR method for measuring Salmonella in meat, offering a better alternative to traditional methods.

Contribution

A novel ddPCR assay using invA for rapid and sensitive Salmonella quantification in meat samples.

Findings

The ddPCR assay achieved a limit of quantification of 1.1 × 102 colony-forming units/mL.

ddPCR results showed strong correlation with plate count methods (R2 > 0.99).

Mathematical modeling confirmed high correlation (Pearson coefficient: 0.996) between ddPCR and plate counts.

Abstract

Salmonella, a major global foodborne pathogen, is a leading cause of salmonellosis. Quantitative detection of Salmonella provides a scientific basis for establishing microbiological criteria and conducting risk assessments. The plate count method remains the primary approach for bacterial quantification, whereas the most probable number (MPN) method is commonly used for detecting low levels of bacterial contamination. However, both methods are time-consuming and labor-intensive. Validated digital polymerase chain reaction (dPCR) techniques are emerging as promising alternatives because they enable rapid, absolute quantification with high specificity and sensitivity. Herein, we developed a novel droplet dPCR (ddPCR) assay for identifying and quantifying Salmonella using invA as the target. The assay demonstrated high specificity and sensitivity, with a limit of quantification of 1.1 × 102 colony-forming units/mL in meat samples. Furthermore, the log10 values obtained via ddPCR and plate counting exhibited a strong linear relationship (R2 > 0.99). Mathematical modeling of growth kinetics further confirmed a high correlation between plate count and ddPCR measurements (Pearson correlation coefficient: 0.996; calculated bias factor: 0.88). Collectively, these results indicate that ddPCR is a viable alternative to the MPN method and represents a powerful tool for the quantitative risk assessment of food safety.

Figures