Frontiers in Animal Science (Jan 2024)
Duplex droplet digital PCR detection of Streptococcus uberis and Streptococcus dysgalactiae, major etiological agents of bovine mastitis
Abstract
Bovine mastitis is one of the most important diseases affecting dairy cattle worldwide, resulting in significant economic losses due to high costs mainly associated with decreased production, antimicrobial treatment, and early culling of animals. The genus Streptococcus is among the primary bacterial pathogens causing bovine mastitis worldwide. The correct and timely diagnosis of mastitis is critical for the dairy industry, not only from the point of view of milk hygiene but also for economic, public health, and animal welfare reasons. Herein, we developed a diagnostic test of bovine intramammary infection employing a duplex droplet digital PCR (dddPCR) to detect and quantify Streptococcus uberis and Streptococcus dysgalactiae in milk, which outperforms the gold standard culture-based technique and the endpoint PCR. Indeed the detection limit for cultures and mock samples for dddPCR was a hundred times lower than the endpoint PCR. Additionally, the CFU/mL estimated based on the number of copies/uL obtained through dddPCR exhibited a strong correlation with the observed CFU/mL from the culture (r^2 > 0.99, p-value < 0.001), indicating that dddPCR provides a dependable estimate of this parameter. Moreover, the sensitivity of endpoint PCR, determined from artificial samples, was 40% for S. uberis and 55.4% for S. dysgalactiae meanwhile, the sensitivity of dddPCR was 80% and 100% for S. uberis and S. dysgalactiae, respectively, while the specificity was 100% for both techniques and pathogens. In conclusion, we propose a robust and reliable technique standardized for detecting and quantifying two of the most important bacteria that cause bovine mastitis. This dddPCR method may be particularly suitable to detect pathogens in milk samples with low bacterial loads or intermittently shedding and should be further tested with a larger sample size in future research.
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