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

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.

Examination of the microbiota of normal cow milk using MinION nanopore sequencing.

The aim of this study was to evaluate the microbiota of normal milk in dairy cows and their relationship with host factors, such as the age of the cow (Age), somatic cell counts in milk (SCCs), and days in milk (DIM). We investigated 48 milk samples from 22 cows with no systemic or local clinical signs using MinION nanopore sequencing for a 16S rRNA gene amplicon. Bacterial richness was positively correlated with the DIM (P=0.