An artificial intelligence approach of feature engineering and ensemble methods depicts the rumen microbiome contribution to feed efficiency in dairy cows.

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.

Evaluation of Recombinant Bovine Interleukin-8 (rbIL-8) as a Treatment for Chronic Intramammary Infection in Dairy Cows.

Mastitis is one of the main contributors to antimicrobial resistance in livestock, so alternative therapies are being investigated to address it. The present study assessed the capability of recombinant bovine interleukin-8 (rbIL-8) to improve neutrophil function in the mammary gland and resolve chronic high somatic cell count (SCC) in Holstein cows. Multiparous cows (n = 8) with more than 300,000 SCC per mL were allocated to one of two intramammary infusions: saline (10 mL of saline solution) or rbIL-8 (1.57 mg/mL of recombinant bovine IL-8 diluted in 9 mL of saline). In addition, there was an untreated control group (n = 2, SCC < 300,000 SCC/mL). Milk samples were collected post-treatment at 0, 4, 8, 12, 24, 48, and 144 h to quantify milk SCC, haptoglobin, and IgG concentrations. Neutrophil's phagocytosis in milk and blood was evaluated via flow cytometry at 0, 24, and 48 h. The log of SCC did not differ between the infused groups (p = 0.369). Neutrophils presented a similar log of cells with high fluorescence for propidium-iodide (PI) and dihydrorhodamine (DHR) in milk (p = 0.412) and blood samples (p = 0.766) in both infused groups. Intramammary infusion of 1.57 mg/mL of rbIL-8 did not improve neutrophils response and failed to resolve chronic high SCC.

Rumen and lower gut microbiomes relationship with feed efficiency and production traits throughout the lactation of Holstein dairy cows.

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 study's 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.

Effect of GnRH 7 Days Before Presynchronization With Simultaneous PGF2α and GnRH on Reproductive Outcomes in Holstein Dairy Cows.

We evaluated if an additional GnRH injection 7 days before pre-synchronization with simultaneous PGF2α and GnRH (PG+G) would improve responses to presynchronization, synchronization, and pregnancy per AI (P/AI). We hypothesized that administering GnRH 7 days before PG+G would increase ovulation and corpus luteum (CL) presence at the PG+G, improve response to OvSynch treatments and P/AI. Holstein cows were blocked by parity and randomly assigned to either a PG+G (Control, n = 205); or to GnRH followed 7 days later by PG+G (ExtG, n = 201). At enrollment, Control was left untreated, whereas ExtG received GnRH. Seven days after enrollment, Control and ExtG received PG+G followed by OvSynch 7 days later (GnRH, 7 days PGF2α, 56 h GnRH, 16 h timed AI). Ovarian dynamics were assessed using ultrasonography in a subset of cows (n = 53 for Control; and n = 50 for ExtG) at each treatment, except the 2nd GnRH of OvSynch. Pregnancy diagnosed at 32- and 67-days post AI. Ovulation at enrollment tended (P = 0.06) to be higher for ExtG, but ovulation was not different at PG+G (P = 0.41) and first GnRH of the OvSynch (P = 0.25). There was a tendency (P = 0.08) for ExtG to have larger CL than Control at PGF2α of the OvSynch. There were no differences in CL and follicle sizes in any other treatment point assessed. There were no differences (P = 0.12) in luteolysis between treatments after PG+G. Overall P/AI was similar between treatments on Day 32 (Control = 33.0% vs. ExtG = 34.6%, P = 0.75) and 67 (Control = 31.8% vs. ExtG = 32.5%, P = 0.29) post AI. There was a tendency for an interaction between treatment and parity (P = 0.09) for P/AI at day 67 post-AI. In multiparous cows, ExtG tended to have greater P/AI than Control, whereas, in primiparous cows Control tended to have greater P/AI than ExtG at day 67 post-AI. In conclusion, the effects of GnRH 7 days before PG+G presynchronization lead to positive and negative tendencies, respectively, in multiparous and primiparous cows for P/AI at day 67 post-AI and needs further investigation.