Fermentation of dietary nutrients in ruminants gastrointestinal (GI) tract is an essential mechanism utilized to meet daily energy requirements. Especially in lactating dairy cows, the GI microbiome plays a pivotal role in the breakdown of indigestible plant polysaccharides and supply most AAs, fatty acids, and gluconeogenic precursors for milk synthesis. Although the contribution of the rumen microbiome to production efficiency in dairy cows has been widely researched over the years, variations throughout the lactation and the lower gut microbiome contribution to these traits remain poorly characterized. Therefore, we investigated throughout lactation the relationship between the rumen and lower gut microbiomes with production efficiency traits in Holstein cows. We found that the microbiome from both locations has temporal stability throughout lactation, yet factors such as feed intake levels played a significant role in shaping microbiome diversity. The composition of the rumen microbiome was dependent on feed intake. In contrast, the lower gut microbiome was less dependent on feed intake and associated with a potentially enhanced ability to digest dietary nutrients. Therefore, milk production traits may be more correlated with microorganisms present in the lower gut than previously expected. The current studys findings advance our understanding of the temporal relationship of the rumen and lower gut microbiomes by enabling a broader overview of the gut microbiome and production efficiency towards more sustainable livestock production.

Genetic selection has remarkably helped U.S. dairy farms to decrease their carbon footprint by more than doubling milk production per cow over time. Despite the environmental and economic benefits of improved feed and milk production efficiency, there is a critical need to explore phenotypical variance for feed utilization to advance the long-term sustainability of dairy farms. Feed is a major expense in dairy operations, and their enteric fermentation is a major source of greenhouse gases in agriculture. The challenges to expanding the phenotypic database, especially for feed efficiency predictions, and the lack of understanding of its drivers limit its utilization. Herein, we leveraged an artificial intelligence approach with feature engineering and ensemble methods to explore the predictive power of the rumen microbiome for feed and milk production efficiency traits, as rumen microbes play a central role in physiological responses in dairy cows. The novel ensemble method allowed to further identify key microbes linked to the efficiency measures. We used a population of 454 genotyped Holstein cows in the U.S. and Canada with individually measured feed and milk production efficiency phenotypes. The study underscored that the rumen microbiome is a major driver of residual feed intake (RFI), the most robust feed efficiency measure evaluated in the study, accounting for 36% of its variation. Further analyses showed that several alpha-diversity metrics were lower in more feed-efficient cows. For RFI, [Ruminococcus] gauvreauii group was the only genus positively associated with an improved feed efficiency status while seven other taxa were associated with inefficiency. The study also highlights that the rumen microbiome is pivotal for the unexplained variance in milk fat and protein production efficiency. Estimation of the carbon footprint of these cows shows that selection for better RFI could reduce up to 5 kg of diet consumed per cow daily, potentially reducing up to 37.5% of CH4. These findings shed light that the integration of artificial intelligence approaches, microbiology, and ruminant nutrition can be a path to further advance our understanding of the rumen microbiome on nutrient requirements and lactation performance of dairy cows to support the long-term sustainability of the dairy community.