Age-specific composition of milk microbiota in Tibetan sheep and goats

Abstract

Abstract This study investigates the dynamic changes in milk nutritional composition and microbial communities in Tibetan sheep and goats during the first 56 days of lactation. Milk samples were systematically collected at five time points (D0, D7, D14, D28, D56) post-delivery. In Tibetan sheep, milk fat, protein, and casein contents were highest on D0, gradually decreased, and stabilized after D14, while lactose and galactose levels showed the opposite trend. Goat milk exhibited similar initial peaks, with significant changes particularly between D0, D7, D14, and D56. 16S rRNA gene sequencing revealed increasing microbial diversity in both species over the lactation period. Principal coordinates analysis identified distinct microbial clusters corresponding to early (D0–D7), transitional (D14–D28), and mature (D56) stages. Core phyla, including Proteobacteria, Firmicutes, Bacteroidetes, and Actinobacteria, dominated the milk microbiota, with significant temporal shifts. Core microbes like Lactobacillus, Leuconostoc, and Streptococcus were common in both species, with species-specific taxa observed (e.g., Pediococcus in sheep, Shewanella in goats). Furthermore, we observed a highly shared core microbiota in sheep and goat milk, including Lactobacillus, Leuconostoc, and Streptococcus. Spearman correlation analysis highlighted significant relationships between specific microbial genera and milk nutrients. For instance, Lactobacillus positively correlated with total solids, non-fat milk solids, protein, and casein, while Mannheimia negatively correlated with protein content. This study underscores the complex interplay between milk composition and microbial dynamics in Tibetan sheep and goats, informing strategies for livestock management and nutritional enhancement. Key points • The milk can be classified into three types based on the microbiota composition • The changes of milk microbiota are closely related to the variations in nutrition • Filter out microbiota with species specificity and age specificity in the milk