TIME RESOLVED BOVINE HOST RESPONSE TO VIRULENCE FACTORS, MAPPED IN MILK BY SELECTED REACTION MONITORING S.L. Bislev1, U. Kusebauch2, M.C. Codrea1, R. Moritz2, C.M. Røntved1, E. Bendixen1 1 Department of Animal Science, Faculty of Science and Technology, Aarhus University, Tjele, Denmark; 2 Institute for Systems Biology, Seattle, Washington, USA Mastitis is beyond doubt the largest health problem in modern milk production. Many different pathogens can cause infections in the mammary gland, and give rise to severe toll on animal welfare, economic gain as well as on excessive use of antibiotics in food production. Rapid diagnostic methods are still not available, and particularly pathogen-specific biomarkers would be highly valuable, as these may allow correct antibiotic treatment to be applied shortly after an udder infection has been observed. Moreover, with automatic milking systems and on-line surveillance technology becoming widely used in dairy farming it raises potentials for detecting sensitive diagnostic markers for mastitis directly during daily milking. However, sensitive biomarker analysis in milk is complicated by the interference from the relatively high abundance of major milk proteins. In this study, we present a sensitive selected reaction monitoring (SRM) proteomics approach, targeting proteins suggested to play key roles in the bovine host response to mastitis. 17 biomarker candidates related to inflammatory response and mastitis were selected. The 17 candidate proteins were quantified in milk samples from cows challenged with peptidoglycan (PGN) from the gram-positive bacteria Staphylococcus aureus and lipopolysaccharide (LPS) from the gram-negative bacteria Escherichia coli for 54 hours. This method allowed for the first time a thorough proteome analysis of the time-resolved response to gram-positive and gram-negative cell wall components. The results demonstrated that the extent of protein regulation is much larger after challenge with LPS than with PGN underpinning the growing evidence that gram-negative bacteria cause a far more acute host response than gram-positive bacteria. Furthermore, this SRM approach provides a strong tool for investigating these proteins in very large scale experiments, particularly with the scope to investigate whether these candidate biomarkers are suited for monitoring animal health in milk production.