Development and Application of a Dual-Readout RPA-PfAgo System for Rapid Detection of Streptococcus agalactiae in Bovine Milk
Abstract
Streptococcus agalactiae is a major contagious pathogen of bovine mastitis and causes substantial economic losses in the dairy industry. In this study, a dual-readout RPA-PfAgo detection platform targeting the conserved cfb gene of S. agalactiae was established and optimized. Seven pairs of RPA primers were designed and screened to construct the Basic-RPA assay, and six guide DNAs (gDNAs) together with a specific probe were evaluated for PfAgo-assisted detection. Field validation was performed using 153 bovine milk samples collected from five dairy-farming regions in China, and assay performance was compared with bacteriological culture and a standardized quantitative PCR (qPCR) assay. The Basic-RPA assay achieved optimal amplification at 37 °C for 30 min, with a detection limit of 1 × 10−3 ng/µL and no cross-reactivity with non-target bacteria. The optimized RPA-PfAgo-RTF assay detected as few as 10 copies/µL, whereas the RPA-PfAgo-LFD assay detected 100 copies/µL, and both formats showed high analytical specificity. In field milk samples, bacteriological culture detected 21 positive samples, whereas standardized real-time PCR (qPCR), RPA-PfAgo-RTF, and RPA-PfAgo-LFD each detected 33 positive samples. When compared with bacteriological culture as a conventional comparator, all three molecular assays showed 100.00% positive agreement, 90.91% negative agreement, and a Kappa value of 0.733. In addition, RPA-PfAgo-RTF and RPA-PfAgo-LFD were completely concordant with the standardized qPCR assay across all 153 samples. These results indicate that the dual-readout RPA-PfAgo platform is a rapid and reliable molecular tool for detection of S. agalactiae in bovine milk.
Fields of Study & Subjects
Milk Quality and Mastitis in Dairy Cows
Neonatal and Maternal Infections
Infant Nutrition and Health
Publication details
- Journal / source
- Veterinary Sciences
- Publisher
- MDPI AG
- Volume
- 13
- Issue
- 6
- Pages
- 561–561
- Publication date
- 6 June 2026
- Language
- EN