Effects of rumen-native microbial feed supplementation on milk yield, composition, and feed efficiency in lactating dairy cows.

The objective of this study was to evaluate the effects of two rumen-native microbial feed supplements (MFS) on milk production, milk composition, and feed efficiency. A total of 90 multiparous cows between 40 and 60 d in milk were enrolled in a randomized block design study. Within each block (baseline milk yield), cows were randomly assigned to: control (no microbial feed supplementation), MFS1 (0.33 g/kg total mixed ration [TMR] of an MFS containing a minimum of Clostridium beijerinckii at 2 × 106 CFU/g and Pichia kudriavzevii at 2 × 107 CFU/g), or MFS2 (0.33 g/kg TMR of a MFS containing a minimum of C. beijerinckii at 2 × 106 CFU/g, P. kudriavzevii at 2 × 107 CFU/g, Ruminococcus bovis at 2 × 107 CFU/g, and Butyrivibrio fibrisolvens at 2 × 107 CFU/g). Cows were housed in a single group and fed the study diets ad libitum for 270 d. Individual milk yield was recorded using electronic milk meters, and milk fat and protein were measured using optical in-line analyzers at each of two daily milkings. Treatment and treatment by time effects were assessed through multiple linear regression analyses. Treatment effects were observed for milk and energy-corrected milk (ECM) yields, milk fat and protein yields and concentrations, dry matter intake (DMI), and feed efficiency; those effects were conditional to time for milk yield, DMI, and feed efficiency. Overall, milk, ECM, fat, and protein yields were higher for MFS2 compared with control cows (+3.0, 3.7, 0.12, and 0.12 kg/d, respectively). Compared with MFS1, milk yield was higher and protein yield tended to be higher for MFS2 cows (+2.9 and 0.09 kg/d, respectively). In contrast, MFS1 cows produced 0.17 and 0.08 units of percentage per day more fat and protein than MFS2 cows, and 0.07 units of percentage per day more protein than control cows. Dry matter intake and feed efficiency were higher for MFS2 cows compared with MFS1 cows (+1.3 kg/d and 0.06, respectively), and feed efficiency was higher for MFS2 cows compared with control cows (+0.04). Where observed, treatment by time effects suggest that the effects of MFS2 were more evident as time progressed after supplementation was initiated. No effects of microbial supplementation were observed on body weight, body condition score, somatic cell count, or clinical mastitis case incidence. In conclusion, the supplementation of MFS2 effectively improved economically important outcomes such as milk yield, solids, and feed efficiency.

This study evaluates the effects of two rumen-native microbial feed supplements (MFS) on milk yield, composition, and feed efficiency in lactating dairy cows. Ninety multiparous Holstein cows between 40 and 60 d in milk were assigned to control (no microbial feed supplementation), MFS1 (Clostridium beijerinckii and Pichia kudriavzevii), or MFS2 (C. beijerinckii, P. kudriavzevii, Ruminococcus bovis, and Butyrivibrio fibrisolvens) total mixed ration supplementation. Overall, MFS2 cows had higher milk and milk component yields than control and MFS1, while MFS1 cows had higher milk component concentrations than control and MFS2. Feed efficiency was higher for MFS2 compared with control and MFS1 cows. Microbial feed supplementation improved economically important outcomes such as milk yield, solids, and feed efficiency.

Ruminal Protozoal Populations of Angus Steers Differing in Feed Efficiency.

Feed accounts for as much as 70% of beef production costs, and improvement of the efficiency with which animals convert feed to product has the potential to have substantial financial impact on the beef industry. The rumen microbiome plays a key role in determining feed efficiency; however, previous studies of rumen microbiota have not focused on protozoal communities despite the estimation that these organisms represent approximately 50% of rumen content biomass. Protozoal communities participate in the regulation of bacterial populations and nitrogen cycling-key aspects of microbiome dynamics. The present study focused on identifying potential associations of protozoal community profiles with feed efficiency. Weaned steers (n = 50) 7 months of age weighing approximately 260 kg were adapted to a growing ration and GrowSafe for 2 weeks prior to a 70-day feed efficiency trial. The GrowSafe system is a feeding system that monitors feed intake in real time. Body weights were collected on the first day and then every 7 days of the feed efficiency trial, and on the final day, approximately 50 mL of rumen content were collected via orogastric tubing and frozen at -80 °C. Body weight and feed intake were used to calculate residual feed intake (RFI) as a measure of feed efficiency, and steers were categorized as high (n = 14) or low (n = 10) RFI based on ±0.5 standard deviations about the mean RFI. Microbial DNA was extracted, and the eukaryotic component profiled by amplification and sequencing of 18S genes using degenerate primers that can amplify this locus across a range of protists. The taxonomy of protozoal sequences was assigned using QIIME 1.9 and analyzed using QIIME and SAS 9.4 with significance determined at α ≤ 0.05. Greater abundances of unassigned taxa were associated with high-RFI steers (p = 0.03), indicating a need for further study to identify component protozoal species. Differences were observed between low- and high-RFI steers in protozoal community phylogenetic diversity, including weighted beta-diversity (p = 0.04), Faith's phylogenetic diversity (p = 0.03), and observed Operational taxonomic unit (OTU) (p = 0.03). The unassigned taxa and differences in phylogenetic diversity of protozoal communities may contribute to divergences observed in feed efficiency phenotypes in beef steers.

Rumen fluid metabolomics of beef steers differing in feed efficiency.

INTRODUCTION: Beef is the most consumed red meat in the United States, and the US is the largest producer and consumer of beef cattle globally. Feed is one of the largest input costs for the beef cattle industry, accounting for 40-60% of the total input costs. Identifying methods for improving feed efficiency in beef cattle herds could result in decreased cost to both producers and consumers, as well as increased animal protein available for global consumption. METHODS: In this study, rumen fluid was collected from low- (n = 14) and high-RFI (n = 15) steers. Rumen fluid was filtered through a 0.22 µM syringe filter, extracted using 0.1% formic acid in acetonitrile:water:methanol (2:2:1) and injected into the Dionex UltiMate 3000 UHPLC system with an Exactive Plus Orbitrap MS. Peaks were identified using MAVEN and analyzed using MetaboAnalyst 4.0 and SAS. Significance was determined using an α ≤ 0.05. RESULTS: Eight metabolites were greater in low-RFI steers compared to high-RFI steers, including 3,4-dihydroxyphenylacetate, 4-pyridoxate, citraconate, hypoxanthine, succinate/methylmalonate, thymine, uracil, and xylose (P ≤ 0.05). These metabolites were predominantly involved in amino acid and lipid metabolism. CONCLUSIONS: Rumen fluid metabolomes differ in steers of varying feed efficiencies. These metabolites may be used as biomarkers of feed efficiency, and may provide insight as to factors contributing to differences in feed efficiency that may be exploited to improve feed efficiency in beef cattle herds.

Rumen Bacteria and Serum Metabolites Predictive of Feed Efficiency Phenotypes in Beef Cattle.

The rumen microbiome is critical to nutrient utilization and feed efficiency in cattle. Consequently, the objective of this study was to identify microbial and biochemical factors in Angus steers affecting divergences in feed efficiency using 16S amplicon sequencing and untargeted metabolomics. Based on calculated average residual feed intake (RFI), steers were divided into high- and low-RFI groups. Features were ranked in relation to RFI through supervised machine learning on microbial and metabolite compositions. Residual feed intake was associated with several features of the bacterial community in the rumen. Decreased bacterial α- (P = 0.03) and ß- diversity (P < 0.001) was associated with Low-RFI steers. RFI was associated with several serum metabolites. Low-RFI steers had greater abundances of pantothenate (P = 0.02) based on fold change (high/low RFI). Machine learning on RFI was predictive of both rumen bacterial composition and serum metabolomic signature (AUC ≥ 0.7). Log-ratio proportions of the bacterial classes Flavobacteriia over Fusobacteriia were enriched in low-RFI steers (F = 6.8, P = 0.01). Reductions in Fusobacteriia and/or greater proportions of pantothenate-producing bacteria, such as Flavobacteriia, may result in improved nutrient utilization in low-RFI steers. Flavobacteriia and Pantothenate may potentially serve as novel biomarkers to predict or evaluate feed efficiency in Angus steers.

Temporal Stability of the Ruminal Bacterial Communities in Beef Steers.

Nutritional studies involving ruminants have traditionally relied on relatively short transition or wash-out periods between dietary treatments, typically two to four weeks. However, little is known about adequate adaptation periods required to reach stabilization of the rumen microbiome that could provide more accurate results from nutritional studies in ruminants. This study determined the rumen bacterial communities and rumen environment parameters over ten weeks following transition from a forage-based to concentrate-based diet. Several α-diversity metrics, including observed OTUs and Simpson's Evenness fluctuated throughout the trial, but were typically either greatest (observed OTUs) or lowest (Simpson's) at week 5 of the trial contrasted from weeks 1 and 10 (P < 0.05). At week 4, several orders associated with the shift to the final bacterial community composition, including Pasteurellales, Aeromonadales, and Bacteroidales. At week 5, rumen pH was correlated with α-diversity (P = 0.005) and predictive of the rumen microbiome signature at week 10 (R2 = 0.48; P = 0.04). Rumen microbiome stability did not occur until approximately 9 weeks following adaptation to the diet and was associated with changes in specific bacterial populations and rumen environment. The results of this study suggest that adaptation and wash-out periods must be re-evaluated in order to accommodate necessary rumen microbiome acclimation.