Pre-stimulation of Precision-Cut bovine udder slices with zymosan before LPS exposure indicates indicators for trained immunity
Filor, V.; Myslinska, J.; Saliani, A.; Dalli, J.; Steinbach, S.; Olinga, P.; Baeumer, W.; Werling, D.
Show abstract
Mastitis in cattle poses a significant health challenge and results in substantial economic losses for the dairy industry. This study aimed to establish precision-cut bovine udder slices (PCBUS) as an in vitro model to explore the potential of stimulating trained immunity in the udder. The goal was to investigate whether this approach could influence the early pathophysiological processes of mastitis and pave the way for developing new therapeutic strategies for udder inflammation in future research. PCBUS remained viable in culture for up to two weeks. When stimulated with E. coli-derived lipopolysaccharide (LPS), zymosan (an inducer of trained immunity), or pre-incubated with zymosan followed by LPS stimulation, the slices exhibited distinct responses in terms of pro-inflammatory cytokine production and lipid mediator profiles. Additionally, cytokine production was influenced by the presence or absence of fetal calf serum (FCS), highlighting the potential limitations of FCS in in vitro studies. While the current experimental setup did not definitively confirm the induction of trained immunity in the bovine udder, it validated the utility of PCBUS as a robust in vitro model for studying bovine udder inflammation. This model offers a promising platform for developing innovative mastitis treatments, particularly given the growing concern over antimicrobial resistance. It also provides a valuable tool for advancing our understanding of immune responses in the bovine udder. By adapting the precision-cut tissue slice technique to bovine udders, this model enables extensive research into new therapeutic approaches and supports basic research efforts to characterize complex pathophysiological processes associated with mastitis.
Matching journals
The top 2 journals account for 50% of the predicted probability mass.