A Rapid Detection Method for <i>Salmonella</i> Based on Real-Time Recombinase Polymerase Amplification in Food
This study developed a rapid detection method for <i>Salmonella</i> based on real-time recombinase polymerase amplification (real-time RPA). The method exhibited excellent specificity and could amplify target genes within 20 min at 39°C. It achieved a Limit of Detection (LOD<sub>50</sub>) of 47 CFU/mL. To evaluate detection performance, artificially contaminated food samples-including egg products, chocolate products, meat products, grain-based products, and soy products-were tested. Prior to real-time RPA detection, the samples underwent an enrichment step by shaking incubation at 36°C for 6 h. The real-time RPA method demonstrated consistent and robust performance across diverse food matrices, with relative LOD (RLOD) values below 2.5, satisfying the validation criteria outlined in GUOBIAO 4789.45 (GB 4789.45). A chi-square test conducted on bulk pork samples further confirmed no significant difference between the real-time RPA method and the GB 4789.4 standard method (<i>p</i> > 0.05). These findings highlight the potential of real-time RPA as a reliable and efficient alternative to GB 4789.4 for detecting <i>Salmonella</i>, enhancing food safety monitoring practices.
Authors
- Qingyao Li (ORCID: https://orcid.org/0000-0002-0440-0015)
- Long Li (ORCID: https://orcid.org/0000-0003-0523-3308)
- Liping Song (ORCID: https://orcid.org/0000-0002-0543-1489)
- Yiping Suo
- Zhikai Hu
- Dan Wang (ORCID: https://orcid.org/0000-0001-9239-7399)
- Qinglong Wang (ORCID: https://orcid.org/0000-0003-1883-812X)
- Yujia Zhao (ORCID: https://orcid.org/0000-0002-7186-1727)
- Hong Yin (ORCID: https://orcid.org/0000-0001-6404-7965)
- Chao Xing (ORCID: https://orcid.org/0000-0002-8184-0559)
- Yue Cao (ORCID: https://orcid.org/0000-0003-2632-2983)
Institutions
- Jiangsu Institute of Metrology (CN)
- China National Center for Food Safety Risk Assessment (CN)
- China National Centre for Food Safety Risk Assessment (CN)
Publication Details
- Journal
- Foodborne Pathogens and Disease
- Published
- 2025-09-23
- DOI
- https://doi.org/10.1177/15353141251380364
- Primary Topic
- Biosensors and Analytical Detection
- Type
- article
- Field-Weighted Citation Impact
- 0.00