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Updated: Jan 29, 2026

Droplet Digital TRAP ddTRAP: Adaptation of the Telomere Repeat Amplification Protocol to Droplet Digital Polymerase Chain Reaction
Published on: May 3, 2019
Droplet Digital Polymerase Chain Reaction Assay for Quantifying Salmonella in Meat Samples.
Yingying Liang1, Yangtai Liu2, Xin Liu2
1Shanghai Municipal Center for Disease Control and Prevention, Shanghai 200336, China.
A new droplet digital PCR (ddPCR) assay accurately quantifies Salmonella in food. This rapid method offers a viable alternative to traditional techniques for food safety risk assessment.
Area of Science:
- Food Microbiology
- Molecular Diagnostics
- Food Safety Science
Background:
- Salmonella is a major foodborne pathogen causing salmonellosis globally.
- Accurate quantification of Salmonella is crucial for microbiological criteria and risk assessments.
- Traditional methods like plate count and most probable number (MPN) are time-consuming and labor-intensive.
Purpose of the Study:
- To develop and validate a novel droplet digital PCR (ddPCR) assay for the rapid and accurate quantification of Salmonella.
- To evaluate the performance of the ddPCR assay compared to conventional methods.
Main Methods:
- Development of a ddPCR assay targeting the invA gene of Salmonella.
- Validation of the assay's specificity, sensitivity, and limit of quantification in meat samples.
- Comparison of ddPCR results with traditional plate counting and mathematical modeling of growth kinetics.
Main Results:
- The ddPCR assay demonstrated high specificity and sensitivity.
- The limit of quantification was determined to be 1.1 × 10^2 colony-forming units/mL in meat samples.
- Strong linear correlation (R^2 > 0.99) was observed between ddPCR and plate count measurements, with a high correlation coefficient (0.996) in growth kinetics modeling.
Conclusions:
- Droplet digital PCR (ddPCR) is a viable and powerful alternative to the MPN method for Salmonella quantification.
- The developed ddPCR assay provides a rapid, specific, and sensitive tool for quantitative risk assessment in food safety.
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