Assessment of an extraction protocol to detect the major mastitis-causing pathogens in bovine milk.

Despite all efforts to control its spread, mastitis remains the most costly disease for dairy farmers worldwide. One key component of better control of this disease is identification of the causative bacterial agent during udder infections in cows. Mastitis is complex, however, given the diversity of pathogens that must be identified. Development of a rapid and efficient bacterial species identification tool is thus necessary. This study was conducted to demonstrate the feasibility of bacterial DNA extraction for the automated molecular detection of major mastitis-causing pathogens directly in milk samples to complement traditional microbiological identification. Extraction and detection procedures were designed and optimized to achieve detection in a respectable time frame, at a reasonable cost, and with a high throughput capacity. The following species were identified: Staphylococcus aureus, Escherichia coli, Streptococcus uberis, Streptococcus agalactiae, Streptococcus dysgalactiae, and Klebsiella spp. (including Klebsiella oxytoca and Klebsiella pneumoniae). The detection procedure includes specific genomic DNA amplification by multiplex PCR for each species, separation by capillary electrophoresis, and laser-assisted automated detection. The specificity of the primers was assessed with a panel of bacteria representing mastitis-negative control species. The extraction protocol comprised multiple steps, starting with centrifugation for fat removal, followed by heating in the presence of a cation exchange resin to trap divalent ions. The analytical sensitivity was 100 cfu/mL for milk samples spiked with Staph. aureus, Strep. dysgalactiae, and E. coli, with a tendency for K. pneumoniae. The detection limit was 500 cfu/mL for Strep. uberis and Strep. agalactiae. The overall diagnostic sensitivity (95.4%) and specificity (97.3%) were determined in a double-blind randomized assay by processing 172 clinical milk samples with microbiological characterization as the gold standard. When the physical nature of the milk samples was too altered, DNA purification with a magnetic bead-based system was used. Of the apparent false-positive samples, 5 were identified by specific microbiological analysis as true-positive Staph. aureus co-infections, with further confirmation by ribosomal 16S sequencing. The proposed methodology could, therefore, become an interesting tool for automated PCR detection of major mastitis pathogens in dairy cattle.