Regression tree analysis of the relationship between the concentrations of antimicrobial components and the microbiota of normal milk from dairy cows

Abstract

The purpose of this study was to determine the concentrations of antimicrobial components (immunoglobulin A (IgA), lactoferrin (LF), lingual antimicrobial peptide (LAP), and S100A7) in normal milk and their relation to host factors (Age, somatic cell count (SCC), days in milk, richness, and alpha diversity of the milk microbiota) in dairy cows using multivariate regression tree analyses, and to clarify how the milk microbiota is related to the obtained results. Thirty normal milk samples were collected from a commercial dairy farm in June 2020. The thresholds that predicted the concentration of each antimicrobial component in milk were obtained by regression tree analysis, and the beta-diversity of the milk microbiota composition between groups divided according to each threshold was compared by an analysis of similarities test. The IgA and LF concentrations were mainly predicted by the SCC (177,500 and 70,000 cells/ml, respectively), and the LAP and S100A7 concentrations were predicted by Age (29.667 and 40.3 months, respectively). No relationship was observed between the concentration of IgA, LAP, or S100A7 and the milk microbiota composition between the groups divided by the threshold for prediction, but the milk microbiota composition was significantly different between the groups divided by the threshold for predicting the LF concentration.Our results indicated that the LF concentration in normal milk may be associated with the milk microbiota composition.