Altered microbiota, antimicrobial resistance genes, and functional enzyme profiles in the rumen of yak calves fed with milk replacer

Abstract

Yaks, as ruminants inhabiting high-altitude environments, possess a distinct rumen microbiome and are resistant to extreme living conditions. This study investigated the microbiota, resistome, and functional gene profiles in the rumen of yaks fed milk or milk replacer (MR), providing insights into the regulation of the rumen microbiome and the intervention of antimicrobial resistance in yaks through dietary methods. The abundance of Prevotella members increased significantly in response to MR. Tetracycline resistance was the most predominant. The rumen of yaks contained multiple antimicrobial resistance genes (ARGs) originating from different bacteria, which could be driven by MR, and these ARGs displayed intricate and complex interactions. MR also induced changes in functional genes. The enzymes associated with fiber degradation and butyrate metabolism were activated and showed close correlations with Prevotella members and butyrate concentration. This study allows us to deeply understand the ruminal microbiome and ARGs of yaks and their relationship with rumen bacteria in response to different milk sources.

Keywords: metagenomics; microbiome; milk replacer; resistome; rumen; yak.

FIG 1

Microbial diversities and structure of rumen in yak claves. (A and B) The richness and Shannon index of the rumen microbiome in the CON and TRT groups. (C) The PCoA of the Bray-Curtis distances of the rumen microbiome between the CON and TRT groups. (D) The composition of the rumen microbiome at the gene level in the CON and TRT groups. (E) The identification of signature species in the CON and TRT groups using linear discriminant analysis effect size.

FIG 2

The rumen resistome structure and composition in the CON and TRT groups. (A and B) The richness and Shannon index of the rumen resistome in the CON and TRT groups. (C) PCoA of Bray-Curtis distances for the rumen resistome structure between the CON and TRT groups. (D) Relative abundance of ARGs by class of antibiotics per sample. (E) The composition of ARGs per sample.

FIG 3

The identification of signature ARGs in the CON and TRT groups and their interactions. (A) The signature ARGs in the CON and TRT groups by the LEfSe algorithm. (B) Network analysis of the interactions among ARGs. The nodes (resistance genes) were colored by the corresponding class of antibiotics, and the size of the node was determined by the connection degrees.

FIG 4

Rumen resistome is associated with its bacterial community. (A) Procrustes analysis of the association between the composition of the resistome and that of the bacterial community in the CON and TRT groups. (B) The proportion of whole ARGs annotated to the bacterial species. (C) The proportion of the top five most abundant ARGs annotated to the bacterial species.

FIG 5

The structure and abundance of CAZyme in the CON and TRT groups. (A) The richness and diversity of rumen CAZyme in the CON and TRT groups. (B) PCoA of Bray-Curtis distances for the rumen CAZyme structure between the CON and TRT groups. (C) The bar plots of CAZyme at the class level in the CON and TRT groups. (D) The chord diagram shows the distribution of the top 30 CAZymes in the CON and TRT groups.

FIG 6

MR affected the rumen fermentation and related metabolism in the rumen microbiome, according to metagenomic results. (A) The comparison of VFA and lactate concentrations in the CON and TRT groups. (B) Comparisons of the relative abundance of related KO genes using the Wilcoxon test. The red font indicated that enzyme genes were significantly enriched in the CON group. The blue font indicated that enzyme genes were significantly enriched in the TRT group. (C) The tertiary network of bacteria, functional genes, and VFAs. Red nodes represent the signature species in the TRT group. Blue nodes represent the signature species in the CON group. Orange and light blue nodes represent the increased and decreased enzymes in the TRT group, respectively. Green nodes represent the VFAs. Red lines represent the positive correlations, and blue lines represent the negative correlations.