BoLA-DQA2 haplotypes and resistance to bovine mastitis

Abstract

Mastitis is the most important production disease in dairy cattle in the world and accounts for around 70% of the economic losses of a dairy farm. Approaches to control mastitis include management practices, nutrition, vaccination, and molecular genetics. This study explored the variability of the Bovine Leukocyte Antigen DQA₂ (BoLA-DQA₂) gene, which belongs to a family of genes associated with the immune response. Also, novel methods to detect mastitis by using Artificial Neural Networks (ANN) were explored. Two different herds (Herd A: -223 suffix; Herd B: -289 suffix) were typed at exon two of the BoLA-DQA₂ gene using the polymerase chain reaction (PCR) and single stranded conformation polymorphism (SSCP). Four new alleles were found (G-223, D-223, A-289 and B-289, with GenBank accession numbers AF388177, AF388178, AY442304 and AY442305, respectively).

Comparison with related sequences revealed the existence of 13 non-silent mutations. These mutations resulted in amino acid changes in pockets one (LIM) and five (V/L) of the putative antigen-binding region. A detailed study was carried out in Herd B, where quarter milk samples of 111 cows were analysed on a weekly basis during a 14-week period after calving. Also, teat characteristics were recorded for analysis. ANN was used to categorise quarters into different four health categories (healthy, moderately ill, ill and severely ill) by using milk traits (somatic cell score (SCS), electrical resistance, protein % and fat %) and combining them into one single value, termed Composite Milk Index (CMI). There were significant CMI differences (p<0.001) between the health categories (healthy: 13.1 ± 0.5; moderately ill: 18.4 ± 0.1; ill: 25.3 ± 0.2; severely ill: 67.8 ± 6.5). No associations were found between teat characteristics in their ability to avoid infection. Bacteriological analysis of the milk samples revealed that around 93% of milk samples in the healthy category were bacteriologically negative, whilst it was 50% for the severely ill category. The most frequent bacteria isolated were the minor pathogens Corynebacterium bovis (45%) and coagulase-negative staphylococci (CNS) (43%). Frequencies for major pathogens were 6% (Streptococcus uberis), 2% (Staphylococcus aureus) and 3% (Streptococcus dysgalactaiae). Herd B cows that were not infected during the trial period showed SCS differences (p<0.05) when grouped by their BoLA-DQA₂ haplotype (AA-289: 0.73 ± 0.1; AB-289: 1.30 ± 0.2; BB-289: 1.21 ± 0.2). There were no significant associations between BoLA-DQA₂-289 haplotypes and proportion of quarters infected with either C. bovis or CNS sp. It is concluded that the AA-289 haplotype may serve as a marker for lower SCS. However, studies where animals are challenged with a specific mastitis pathogen must be carried out to find associations between BoLA-DQA₂ alleles and resistance to mastitis.