Abstract:
Bovine mastitis, defined as an inflammatory reaction of the cows’ mammary gland in response to a microbial infection, is the most prevalent and most costly disease that occur in dairy cattle worldwide. Despite the development of a range of therapeutics and control strategies, the negative impact of bovine mastitis on the dairy industry remains high. This fact can be chiefly attributed to the lack of effective diagnostic tools for detection of mastitis at an early stage. Therefore, this Masters project aimed to determine whether Mass Spectrometry based metabolomics is capable of discriminating between milk obtained from healthy and mastitic cows as proof-of-concept for future metabolomics-based biomarker discovery for bovine mastitis. These metabolite biomarkers are hoped to aid BayerNZ in the development of a diagnostic tool for early mastitis detection and possible determination of the causative agent. A total of 29 different metabolite markers both previously reported and unreported to be implicated in mastitis were detected from metabolomic analysis of milk through GCMS, appearing as early as 12 hours after induction of an intramammary infection by the mastitis pathogen Streptococcus uberis. Additionally, preliminary data generated from LCMS analysis indicated that milk metabolite profiles were distinct and distinguishable between healthy milk and mastitic milk. If implementation of these biomarkers in mastitis diagnostics are seriously considered, a large scale metabolomic experiment is recommended which would later require subsequent biomarker validation. Furthermore, there is great potential in applying metabolomic analysis on mastitis caused by other causative agents for discovery of pathogen specific markers of mastitis which would be of great commercial interest.
