Does the rumen microbiome play a role in feed efficiency of beef cattle?1

2016 ◽  
Vol 94 (suppl_6) ◽  
pp. 44-48 ◽  
Author(s):  
F. Li ◽  
M. Zhou ◽  
K. Ominski ◽  
L. L. Guan
Microbiome ◽  
2019 ◽  
Vol 7 (1) ◽  
Author(s):  
Fuyong Li ◽  
Thomas C. A. Hitch ◽  
Yanhong Chen ◽  
Christopher J. Creevey ◽  
Le Luo Guan

2017 ◽  
Vol 83 (9) ◽  
Author(s):  
Fuyong Li ◽  
Le Luo Guan

ABSTRACT Exploring compositional and functional characteristics of the rumen microbiome can improve the understanding of its role in rumen function and cattle feed efficiency. In this study, we applied metatranscriptomics to characterize the active rumen microbiomes of beef cattle with different feed efficiencies (efficient, n = 10; inefficient, n = 10) using total RNA sequencing. Active bacterial and archaeal compositions were estimated based on 16S rRNAs, and active microbial metabolic functions including carbohydrate-active enzymes (CAZymes) were assessed based on mRNAs from the same metatranscriptomic data sets. In total, six bacterial phyla (Proteobacteria, Firmicutes, Bacteroidetes, Spirochaetes, Cyanobacteria, and Synergistetes), eight bacterial families (Succinivibrionaceae, Prevotellaceae, Ruminococcaceae, Lachnospiraceae, Veillonellaceae, Spirochaetaceae, Dethiosulfovibrionaceae, and Mogibacteriaceae), four archaeal clades (Methanomassiliicoccales, Methanobrevibacter ruminantium, Methanobrevibacter gottschalkii, and Methanosphaera), 112 metabolic pathways, and 126 CAZymes were identified as core components of the active rumen microbiome. As determined by comparative analysis, three bacterial families (Lachnospiraceae, Lactobacillaceae, and Veillonellaceae) tended to be more abundant in low-feed-efficiency (inefficient) animals (P < 0.10), and one archaeal taxon (Methanomassiliicoccales) tended to be more abundant in high-feed-efficiency (efficient) cattle (P < 0.10). Meanwhile, 32 microbial metabolic pathways and 12 CAZymes were differentially abundant (linear discriminant analysis score of >2 with a P value of <0.05) between two groups. Among them, 30 metabolic pathways and 11 CAZymes were more abundant in the rumen of inefficient cattle, while 2 metabolic pathways and 1 CAZyme were more abundant in efficient animals. These findings suggest that the rumen microbiomes of inefficient cattle have more diverse activities than those of efficient cattle, which may be related to the host feed efficiency variation. IMPORTANCE This study applied total RNA-based metatranscriptomics and showed the linkage between the active rumen microbiome and feed efficiency (residual feed intake) in beef cattle. The data generated from the current study provide fundamental information on active rumen microbiome at both compositional and functional levels, which serve as a foundation to study rumen function and its role in cattle feed efficiency. The findings that the active rumen microbiome may contribute to variations in feed efficiency of beef cattle highlight the possibility of enhancing nutrient utilization and improve cattle feed efficiency through modification of rumen microbial functions.


2020 ◽  
Vol 11 ◽  
Author(s):  
Marc D. Auffret ◽  
Robert D. Stewart ◽  
Richard J. Dewhurst ◽  
Carol-Anne Duthie ◽  
Mick Watson ◽  
...  

2017 ◽  
Vol 0 (0) ◽  
pp. 0
Author(s):  
V. M. Artegoitia ◽  
A. P. Foote ◽  
R. G. Tait ◽  
L. A. Kuehn ◽  
R. M. Lewis ◽  
...  

2019 ◽  
Vol 97 (5) ◽  
pp. 2181-2187
Author(s):  
Ahmed A Elolimy ◽  
Emad Abdel-Hamied ◽  
Liangyu Hu ◽  
Joshua C McCann ◽  
Daniel W Shike ◽  
...  

Abstract Residual feed intake (RFI) is a widely used measure of feed efficiency in cattle. Although the precise biologic mechanisms associated with improved feed efficiency are not well-known, most-efficient steers (i.e., with low RFI coefficient) downregulate abundance of proteins controlling protein degradation in skeletal muscle. Whether cellular mechanisms controlling protein turnover in ruminal tissue differ by RFI classification is unknown. The aim was to investigate associations between RFI and signaling through the mechanistic target of rapamycin (MTOR) and ubiquitin-proteasome pathways in ruminal epithelium. One hundred and forty-nine Red Angus cattle were allocated to 3 contemporary groups according to sex and herd origin. Animals were offered a finishing diet for 70 d to calculate the RFI coefficient for each. Within each group, the 2 most-efficient (n = 6) and least-efficient animals (n = 6) were selected. Compared with least-efficient animals, the most-efficient animals consumed less feed (P &lt; 0.05; 18.36 vs. 23.39 kg/d DMI). At day 70, plasma samples were collected for insulin concentration analysis. Ruminal epithelium was collected immediately after slaughter to determine abundance and phosphorylation status of 29 proteins associated with MTOR, ubiquitin-proteasome, insulin signaling, and glucose and amino acid transport. Among the proteins involved in cellular protein synthesis, most-efficient animals had lower (P ≤ 0.05) abundance of MTOR, p-MTOR, RPS6KB1, EIF2A, EEF2K, AKT1, and RPS6KB1, whereas MAPK3 tended (P = 0.07) to be lower. In contrast, abundance of p-EEF2K, p-EEF2K:EEF2K, and p-EIF2A:EIF2A in most-efficient animals was greater (P ≤ 0.05). Among proteins catalyzing steps required for protein degradation, the abundance of UBA1, NEDD4, and STUB1 was lower (P ≤ 0.05) and MDM2 tended (P = 0.06) to be lower in most-efficient cattle. Plasma insulin and ruminal epithelium insulin signaling proteins did not differ (P &gt; 0.05) between RFI groups. However, abundance of the insulin-responsive glucose transporter SLC2A4 and the amino acid transporters SLC1A3 and SLC1A5 also was lower (P ≤ 0.05) in most-efficient cattle. Overall, the data indicate that differences in signaling mechanisms controlling protein turnover and nutrient transport in ruminal epithelium are components of feed efficiency in beef cattle.


2020 ◽  
Vol 98 (Supplement_3) ◽  
pp. 220-220
Author(s):  
Bobwealth O Omontese ◽  
Ashok K Sharma ◽  
Jason Langlie ◽  
Joe Armstrong ◽  
Alfredo DiCostanzo ◽  
...  

Abstract Backgrounding (BKG) segment in beef production systems is characterized by utilization of different forages which affect growth performance and carcass characteristics. However, it is unclear how BKG systems impact rumen microbiome. We investigated rumen microbiome dynamics of beef calves under different BKG systems. At weaning, Angus and Angus x Simmental beef calves (n = 38) were stratified by age, weight, and sex in a completely randomized design into 1 of 3 BKG treatments for 55 d: 1) perennial pasture (PP; quackgrass, orchardgrass; smooth bromegrass, red clover, and alfalfa); 2) summer annual cover crop (CC; cereal oats, purple top turnips, hunter forage brassica, and graza forage radish); and 3) dry lot (DL; haylage, corn, and DDGS). After BKG, all calves were assigned to a high energy ration in a feedlot. Rumen sample was collected via esophageal tubing at weaning, BKG and feedlot. A total of 190 rumen fluid samples were used to sequence the hypervariable V4 region of the 16S rRNA bacterial gene on an Illumina MiSeq platform. The results showed that BKG systems largely influenced rumen bacterial communities. Specifically, microbiome composition and diversity were not different at weaning, diverged significantly during BKG (Shannon index, Bray Curtis distance metrics; P &lt; 0.001) and homogenized during feedlot. During the BKG segment, the bacterial genera Agrobacterium, Coprococcus, and Ruminococcus were dominant in CC whereas Fibrobacteraceae and Mycoplasmataceae was most dominant in DL. Moreover, rumen microbiome patterns of CC and DL calves showed increased plasticity in early stages of development but not during feedlot with PP showing fewer changes over time. These results indicate that BKG systems significantly modulate the rumen microbiome of beef cattle and, underscore the importance of early developmental stages as potential targets for feeding interventions that can impact the animal microbiome to enhance animal performance.


2017 ◽  
Vol 95 (suppl_2) ◽  
pp. 161-161 ◽  
Author(s):  
J. F. Taylor ◽  
J. E. Beever ◽  
J. E. Decker ◽  
H. C. Freetly ◽  
D. J. Garrick ◽  
...  

animal ◽  
2018 ◽  
Vol 12 ◽  
pp. s321-s335 ◽  
Author(s):  
G. Cantalapiedra-Hijar ◽  
M. Abo-Ismail ◽  
G.E. Carstens ◽  
L.L. Guan ◽  
R. Hegarty ◽  
...  

Sign in / Sign up

Export Citation Format

Share Document