Résumé
Mastitis is a multifactorial infection of the udder that can be caused by a multitude of pathogens with varying severity and prevalence. This common disease is responsible for over 70% of antibiotic usage in dairy farms. Limited information exists about the interactions between pathogens in mastitis infections. The aim of this study was to investigate the dynamics of pathogens and their statistical associations in the udder microbiota. We explored the impact of these dynamics on mastitis risk and looked for factors influencing these dynamics and the potential sources of the studied pathogens at farm level. To address these objectives, two independent four-month longitudinal studies were conducted on cows of six dairy farms in the Auvergne region of France. Milk and faeces were collected from 33 cows, along with environmental samples (bedding and milk filter). DNA in these samples was analysed, using a commercial qPCR kit (PathoProofTM) to detect and quantify 15 mastitis-causing pathogens. Somatic cells were also quantified in milk samples. The data were then processed using principal component analysis, Ward clustering methods, and discrete-time Markov chains to identify preferential associations between pathogens and transitions between pathogen profiles. Clustering analyses of milk quarter samples revealed distinct patterns of pathogen distribution associated with different somatic cell counts and cow recovery dynamics. Corynebacterium bovis, though generally considered a minor pathogen, and Streptococcus uberis, were pivotal in the definition of milk pathogen clusters, with the presence of the former driving more severe immune response during infections by the latter. We discuss these results in regard of the possible presence of microbiota profiles in the udder influencing pathogen development and mastitis sensibility.