Search

Abstract Background As the global population continues to grow, competition for resources between humans and livestock has been intensifying. Increasing milk protein production and improving feed efficiency are becoming increasingly important to meet the demand for high-quality dairy protein. In a previous study, we found that milk protein yield in dairy cows was associated with the rumen microbiome. The objective of this study was to elucidate the potential microbial features that underpins feed efficiency in dairy cows using metagenomics, metatranscriptomics, and metabolomics. Results Comparison of metagenomic and metatranscriptomic data revealed that the latter was a better approach to uncover the associations between rumen microbial functions and host performance. Co-occurrence network analysis of the rumen microbiome revealed differential microbial interaction patterns between the animals with different feed efficiency, with high-efficiency animals having more and stronger associations than low-efficiency animals. In the rumen of high-efficiency animals, Selenomonas and members of the Succinivibrionaceae family positively interacted with each other, functioning as keystone members due to their essential ecological functions and active carbohydrate metabolic functions. At the metabolic level, analysis using random forest machine learning suggested that six ruminal metabolites (all derived from carbohydrates) could be used as metabolic markers that can potentially differentiate efficient and inefficient microbiomes, with an accuracy of prediction of 95.06%. Conclusions The results of the current study provided new insights into the new ruminal microbial features associated with feed efficiency in dairy cows, which may improve the ability to select animals for better performance in the dairy industry. The fundamental knowledge will also inform future interventions to improve feed efficiency in dairy cows. Video Abstract.

Abstract Background Dairy cows utilize human-inedible, low-value plant biomass to produce milk, a low-cost product with rich nutrients and high proteins. This process largely relies on rumen microbes that ferment lignocellulose and cellulose to produce volatile fatty acids (VFAs). The VFAs are absorbed and partly metabolized by the stratified squamous rumen epithelium, which is mediated by diverse cell types. Here, we applied a metagenomic binning approach to explore the individual microbes involved in fiber digestion and performed single-cell RNA sequencing on rumen epithelial cells to investigate the cell subtypes contributing to VFA absorption and metabolism. Results The 52 mid-lactating dairy cows in our study (parity = 2.62 ± 0.91) had milk yield of 33.10 ± 6.72 kg. We determined the fiber digestion and fermentation capacities of 186 bacterial genomes using metagenomic binning and identified specific bacterial genomes with strong cellulose/xylan/pectin degradation capabilities that were highly associated with the biosynthesis of VFAs. Furthermore, we constructed a rumen epithelial single-cell map consisting of 18 rumen epithelial cell subtypes based on the transcriptome of 20,728 individual epithelial cells. A systematic survey of the expression profiles of genes encoding candidates for VFA transporters revealed that IGFBP5 + cg-like spinous cells uniquely highly expressed SLC16A1 and SLC4A9, suggesting that this cell type may play important roles in VFA absorption. Potential cross-talk between the microbiome and host cells and their roles in modulating the expression of key genes in the key rumen epithelial cell subtypes were also identified. Conclusions We discovered the key individual microbial genomes and epithelial cell subtypes involved in fiber digestion, VFA uptake and metabolism, respectively, in the rumen. The integration of these data enables us to link microbial genomes and epithelial single cells to the trophic system. Video abstract

Abstract Background Recently, we reported that some dairy cows could produce high amounts of milk with high amounts of protein (defined as milk protein yield [MPY]) when a population was raised under the same nutritional and management condition, a potential new trait that can be used to increase high-quality milk production. It is unknown to what extent the rumen microbiome and its metabolites, as well as the host metabolism, contribute to MPY. Here, analysis of rumen metagenomics and metabolomics, together with serum metabolomics was performed to identify potential regulatory mechanisms of MPY at both the rumen microbiome and host levels. Results Metagenomics analysis revealed that several Prevotella species were significantly more abundant in the rumen of high-MPY cows, contributing to improved functions related to branched-chain amino acid biosynthesis. In addition, the rumen microbiome of high-MPY cows had lower relative abundances of organisms with methanogen and methanogenesis functions, suggesting that these cows may produce less methane. Metabolomics analysis revealed that the relative concentrations of rumen microbial metabolites (mainly amino acids, carboxylic acids, and fatty acids) and the absolute concentrations of volatile fatty acids were higher in the high-MPY cows. By associating the rumen microbiome with the rumen metabolome, we found that specific microbial taxa (mainly Prevotella species) were positively correlated with ruminal microbial metabolites, including the amino acids and carbohydrates involved in glutathione, phenylalanine, starch, sucrose, and galactose metabolism. To detect the interactions between the rumen microbiome and host metabolism, we associated the rumen microbiome with the host serum metabolome and found that Prevotella species may affect the host’s metabolism of amino acids (including glycine, serine, threonine, alanine, aspartate, glutamate, cysteine, and methionine). Further analysis using the linear mixed effect model estimated contributions to the variation in MPY based on different omics and revealed that the rumen microbial composition, functions, and metabolites, and the serum metabolites contributed 17.81, 21.56, 29.76, and 26.78%, respectively, to the host MPY. Conclusions These findings provide a fundamental understanding of how the microbiome-dependent and host-dependent mechanisms contribute to varied individualized performance in the milk production quality of dairy cows under the same management condition. This fundamental information is vital for the development of potential manipulation strategies to improve milk quality and production through precision feeding. Video Abstract