Using a multi-omics approach to explore potential associations with rumen content and serum of cows with different milk production levels based on genomic predicted transmitting ability for milk and phenotypic milk production.

This study aims to compare rumen microbiome and metabolites between second lactation dairy cows in the 75th percentile (n = 12; 57.2 ± 5.08 kg/d) of production according to genomic predicted transmitting ability for milk (GPTAM) and their counterparts in the 25th percentile (n = 12; 47.2 ± 8.61 kg/d). It was hypothesized that the metagenome and metabolome would differ between production levels. Cows were matched by days in milk (DIM), sire, occurrence of disease, and days open in previous lactation. For an additional comparison, the cows were also divided by phenotype into high (n = 6; 61.3 ± 2.8 kg/d), medium (n = 10; 55 ± 1.2 kg/d), and low (n = 8; 41.9 ± 5.6 kg/d) based on their milk production. Samples were collected 65 ± 14 DIM. Rumen content was collected using an oro-gastric tube and serum samples were collected from the coccygeal vessels. High-resolution liquid chromatography-mass spectrometry (LC-MS) was used for rumen and serum metabolite profiling. Shotgun metagenomics was used for rumen microbiome profiling. Microbiome sample richness and diversity were used to determine alpha and Bray-Curtis dissimilarity index was used to estimate beta diversity. Differences in metabolites were determined using t-tests or ANOVA. Pearson correlations were used to consider associations between serum metabolites and milk production. There was no evidence of a difference in rumen metabolites or microbial communities by GPTAM or phenotype. Cows in the phenotypic low group had greater serum acetate to propionate ratio and acetate proportion compared to the cows in the phenotypic medium group. Likewise, serum propionate proportion was greater in the medium compared to the low phenotypic group. Serum acetate, butyrate, and propionate concentrations had a weak positive correlation with milk production. When investigating associations between rumen environment and milk production, future studies must consider the impact of the ruminal epithelium absorption and post-absorption processes in relation to milk production.

Microbiome network traits in the rumen predict average daily gain in beef cattle under different backgrounding systems.

BACKGROUND: Backgrounding (BKG), the stage between weaning and finishing, significantly impacts feedlot performance in beef cattle; however, the contributions of the rumen microbiome to this growth stage remain unexplored. A longitudinal study was designed to assess how BKG affects rumen bacterial communities and average daily gain (ADG) in beef cattle. At weaning, 38 calves were randomly assigned to three BKG systems for 55 days (d): a high roughage diet within a dry lot (DL, n = 13); annual cover crop within a strip plot (CC, n = 13); and perennial pasture vegetation within rotational paddocks (PP, n = 12), as before weaning. After BKG, all calves were placed in a feedlot for 142 d and finished with a high energy ration. Calves were weighed periodically from weaning to finishing to determine ADG. Rumen bacterial communities were profiled by collecting fluid samples via oral probe and sequencing the V4 region of the 16S rRNA bacterial gene, at weaning, during BKG and finishing. RESULTS: Rumen bacterial communities diverged drastically among calves once they were placed in each BKG system, including sharp decreases in alpha diversity for CC and DL calves only (P < 0.001). During BKG, DL calves showed a substantial increase of Proteobacteria (Succinivibrionaceae family) (P < 0.001), which also corresponded with greater ADG (P < 0.05). At the finishing stage, Proteobacteria bloomed for all calves, with no previous alpha or beta diversity differences being retained between groups. However, at finishing, PP calves showed a compensatory ADG, particularly greater than that in calves coming from DL BKG (P = 0.02). Microbiome network traits such as lower average shortest path length, and increased neighbor connectivity, degree, number and strength of bacterial interactions between rumen bacteria better predicted ADG during BKG and finishing than variation in specific taxonomic profiles. CONCLUSIONS: Bacterial co-abundance interactions, as measured by network theory approaches, better predicted growth performance in beef cattle during BKG and finishing, than the abundance of specific taxa. These findings underscore the importance of early post weaning stages as potential targets for feeding interventions that can enhance metabolic interactions between rumen bacteria, to increase productive performance in beef cattle.

Monitoring and Improving the Metabolic Health of Dairy Cows during the Transition Period.

The peripartum period of a dairy cow is characterized by several physiological and behavioral changes in response to a rapid increase in nutrient demands, to support the final stages of fetal growth and the production of colostrum and milk. Traditionally, the transition period is defined as the period 3 weeks before and 3 weeks after parturition. However, several researchers have argued that the transition period begins at the time of dry-off (~60-50 days prior to calving) and extends beyond the first month post-calving in high producing dairy cows. Independent of the definition used, adequate adaptation to the physiological demands of this period is paramount for a successful lactation. Nonetheless, not all cows are successful in transitioning from late gestation to early lactation, leading to approximately one third of dairy cows having at least one clinical disease (metabolic and/or infectious) and more than half of the cows having at least one subclinical case of disease within the first 90 days of lactation. Thus, monitoring dairy cows during this period is essential to detect early disease signs, diagnose clinical and subclinical diseases, and initiate targeted health management to avoid health and production impairment. In this review, we discuss different strategies to monitor dairy cows to detected unintended disruptions in performance and management strategies that can be implemented to improve the metabolic health and performance of dairy cows during the transition period.

Effects of the Administration of a Non-specific Immune Stimulant Around Transportation on Health and Performance of Jersey and Jersey-Cross Heifer Calves During the Rearing Period: Randomized Clinical Trial.

Our objective was to evaluate the effects of a non-specific immune stimulant (IS) administered around transportation on health scores (HS), average daily gain (ADG), disease treatment and mortality of Jersey and Jersey-cross calves during the rearing period. Newborn calves (4 d ± 1) were randomly allocated to receive either 1 mL of saline (CON; n = 438), 1 mL of IS before transport (BTIS; n = 431), or 1 mL of IS immediately after transport (ATIS; n = 436). Calves were health scored weekly for 3 weeks after transport. The data were analyzed using multivariable linear mixed models and multivariable logistic regression models. Kaplan-Meier survival analysis was performed for time to event analysis. Treatment, birth weight, breed, site of birth, serum total solids, dam parity, season of enrollment, and metaphylaxis were offered to models. Differences in respiratory and fecal HS, and ADG between treatment groups were not statistically significant. A total of 196 (15.0%) calves were treated at least once for any disease and 52 calves were treated multiple times. The proportion of calves treated for respiratory disease and/or diarrhea were 14.4, 14.4, and 16.2% for BTIS, ATIS and CON groups, respectively. Although the differences in the likelihood of treatment for both respiratory disease and/or diarrhea during the first 9 weeks of life was not statistically different between groups, we observed that more calves in the control group received disease treatments around 15 days of age compared with calves that received IS. The likelihood of treatment for respiratory diseases alone during the first 30 days of life was smaller in the calves that received IS before transportation when compared to the control group. Only 18 (1.4%) calves died within the study period. The calf mortality likelihood was not statistically different between study groups; however, fewer calves in the IS groups died when compared to CON. In conclusion, the use of IS around transportation did not influence weekly HS, ADG, and the number of disease treatments during the rearing period, but administering IS before transportation resulted in fewer treatments of respiratory diseases during the first 30 days post-transport and marginally lower mortality rates during the rearing period.