Analysis of differences in the rumen microbiome and metabolic function in prepartum dairy cows with different body condition scores

Abstract

Background: The rumen is a crucial digestive organ for dairy cows. The rumen microbiota assists in the digestion of plant feed through microbe-mediated fermentation, during which the plant feed is transformed into nutrients for the cow's use. Variations in the composition and function of the rumen microbiome affect the energy utilization efficiency of dairy cows, which is one of the reasons for the varying body condition scores (BCSs). This study focused on prepartum Holstein dairy cows to analyze differences in rumen microbiota and metabolites among cows with different BCSs. Twelve prepartum dairy cows were divided into two groups, low BCS (LBCS, BCS = 2.75, n = 6) and high BCS (HBCS, BCS = 3.5, n = 6), to explore differences in microbial composition and metabolites.

Results: In the HBCS group, the genera within the phylum Firmicutes exhibited stronger correlations and greater abundances. Phyla such as Firmicutes, Patescibacteria, Acidobacteriota, Euryarchaeota, and Desulfobacterota, in addition to most of their constituent microbial groups, were significantly more abundant in the HBCS group than in the LBCS group. At the genus level, the abundances of Anaerovibrio, Veillonellaceae_UCG_001, Ruminococcus_gauvreauii_group, Blautia, Eubacterium, Prevotellaceae_YAB2003_group, Schwartzia, and Halomonas significantly increased in the HBCS group. The citrate cycle, involved in carbohydrate metabolism, exhibited a significant enrichment trend, with a notable increase in the abundance of its key substrate, citrate, in the HBCS group. This increase was significantly positively correlated with the differential bacterial genera.

Conclusion: In this study, prepartum dairy cows with higher BCS exhibited greater abundance of Firmicutes. This study provides theoretical support for microbiological research on dairy cows with different BCSs and suggests that regulating the rumen microbiome could help maintain prepartum dairy cows within an optimal BCS range.

Keywords: Body Condition Score; Prepartum Dairy Cows; Rumen Metabolomics; Rumen Microbiome.

Fig. 1

Workflow of the integrated rumen 16S rRNA gene sequencing and metabolomics approaches

Fig. 2

The difference in the rumen microbiome between cows with low (LBCS) and high (HBCS) body condition scores according to 16S rRNA gene sequencing data. A Changes in alpha diversity at the OTU level. B Changes in beta diversity at the OTU level. The P value was tested with PERMANOVA. C Community biplot analysis at the phylum and genus levels. D Genus co-occurrence network between LBCS and HBCS based on Spearman correlation analysis. Each node represents a bacterial genus; the node size represents the relative abundance of each genus per group. The line refers to the Spearman coefficient. Red and blue lines represent positive and negative interactions between nodes, respectively

Fig. 3

The difference in the rumen microbiota between cows with low (LBCS) and high (HBCS) body condition scores according to 16S rRNA gene sequencing data. A Cladogram of significantly different rumen microbiota between LBCS and HBCS. Significant differences were tested by linear discriminant analysis effect size analysis, with linear discriminant analysis (LDA) scores > 2 and a P value < 0.05. B Abundance of significantly different bacterial genera between LBCS and HBCS. Significant differences were tested by linear discriminant analysis effect size analysis, with linear discriminant analysis (LDA) scores > 2 and a P value < 0.05

Fig. 4

Metabolic pathway enrichment analysis of differential rumen metabolites between cows with low (LBCS) and high body condition scores. A partial least squares-discriminant analysis of the rumen metabolome between LBCS and HBCS cows. B Volcano map of metabolites identified in the faecal metabolome. C Pathway enrichment analysis of metabolites

Fig. 5

Correlation analysis of the significantly differential microbes and metabolites. Spearman correlations between the significantly differential microbiota and metabolites. *Represents a correlation P value < 0.05, **P value < 0.01. Red and blue represent positive and negative correlations, respectively