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,Selenomonasand members of theSuccinivibrionaceaefamily 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.

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.

Background: Dairy cows are susceptible to postpartum systemic oxidative stress (OS), which leads to significant production loss and metabolic disorders. The gut microbiota has been linked to host health and stress levels. However, to what extent the gut microbiota is associated with postpartum OS remains unknown. In this study, the contribution of the fecal microbiota to postpartum systemic OS and its underlying mechanisms were investigated by integrating 16S rRNA gene sequencing, metagenomics, and metabolomics in postpartum dairy cattle and by transplanting fecal microbiota from cattle to mice. Results: A strong link was found between fecal microbial composition and postpartum OS, with an explainability of 43.1%. A total of 17 significantly differential bacterial genera and 19 species were identified between cows with high (HOS) and low OS (LOS). Among them, 9 genera and 16 species showed significant negative correlations with OS, and Marasmitruncus and Ruminococcus_sp._CAG:724 had the strongest correlations. The microbial functional analysis showed that the fecal microbial metabolism of glutamine, glutamate, glycine, and cysteine involved in glutathione synthesis was lower in HOS cows. Moreover, 58 significantly different metabolites were identified between HOS and LOS cows, and of these metabolites, 19 were produced from microbiota or cometabolism of microbiota and host. Furthermore, these microbial metabolites were enriched in the metabolism of glutamine, glutamate, glycine, and cysteine. The mice gavaged with HOS fecal microbiota had significantly higher OS and lower plasma glutathione peroxidase and glutathione content than those orally administered saline or LOS fecal microbiota. Conclusions: Integrated results suggest that the fecal microbiota is responsible for OS and that lower glutathione production plays a causative role in HOS. These findings provide novel insights into the mechanisms of postpartum OS and potential regulatory strategies to alleviate OS in dairy cows.