scholarly journals Metatranscriptomic Profiling Reveals Linkages between the Active Rumen Microbiome and Feed Efficiency in Beef Cattle

2017 ◽  
Vol 83 (9) ◽  
Author(s):  
Fuyong Li ◽  
Le Luo Guan
Keyword(s):  
Beef Cattle ◽  
Feed Efficiency ◽  
Metabolic Pathways ◽  
Nutrient Utilization ◽  
Content Type ◽  
Linear Discriminant ◽  
Cattle Feed ◽  
Total Rna ◽  
Bacterial Phyla ◽  
Rumen Microbiome

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.

scholarly journals Identification of Microbial Genetic Capacities and Potential Mechanisms Within the Rumen Microbiome Explaining Differences in Beef Cattle Feed Efficiency

2020 ◽  
Vol 11 ◽  
Author(s):  
Marc D. Auffret ◽  
Robert D. Stewart ◽  
Richard J. Dewhurst ◽  
Carol-Anne Duthie ◽  
Mick Watson ◽  
...  
Keyword(s):  
Beef Cattle ◽  
Feed Efficiency ◽  
Cattle Feed ◽  
Rumen Microbiome

scholarly journals Comparative metagenomic and metatranscriptomic analyses reveal the breed effect on the rumen microbiome and its associations with feed efficiency in beef cattle

Microbiome ◽  
2019 ◽  
Vol 7 (1) ◽  
Author(s):  
Fuyong Li ◽  
Thomas C. A. Hitch ◽  
Yanhong Chen ◽  
Christopher J. Creevey ◽  
Le Luo Guan
Keyword(s):  
Beef Cattle ◽  
Feed Efficiency ◽  
Rumen Microbiome

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
Keyword(s):  
Beef Cattle ◽  
Feed Efficiency ◽  
Rumen Microbiome

scholarly journals Effect of Phenotypic Residual Feed Intake and Dietary Forage Content on the Rumen Microbial Community of Beef Cattle

2012 ◽  
Vol 78 (14) ◽  
pp. 4949-4958 ◽  
Author(s):  
Ciara A. Carberry ◽  
David A. Kenny ◽  
Sukkyan Han ◽  
Matthew S. McCabe ◽  
Sinead M. Waters
Keyword(s):  
Community Structure ◽  
Beef Cattle ◽  
Feed Intake ◽  
Feed Efficiency ◽  
Residual Feed Intake ◽  
High Energy ◽  
Production Costs ◽  
Fibrobacter Succinogenes ◽  
Content Type ◽  
Physiological Variables

ABSTRACTFeed-efficient animals have lower production costs and reduced environmental impact. Given that rumen microbial fermentation plays a pivotal role in host nutrition, the premise that rumen microbiota may contribute to host feed efficiency is gaining momentum. Since diet is a major factor in determining rumen community structure and fermentation patterns, we investigated the effect of divergence in phenotypic residual feed intake (RFI) on ruminal community structure of beef cattle across two contrasting diets. PCR-denaturing gradient gel electrophoresis (DGGE) and quantitative PCR (qPCR) were performed to profile the rumen bacterial population and to quantify the ruminal populations ofEntodiniumspp., protozoa,Fibrobacter succinogenes,Ruminococcus flavefaciens,Ruminococcus albus,Prevotella brevis, the genusPrevotella, and fungi in 14 low (efficient)- and 14 high (inefficient)-RFI animals offered a low-energy, high-forage diet, followed by a high-energy, low-forage diet. Canonical correspondence and Spearman correlation analyses were used to investigate associations between physiological variables and rumen microbial structure and specific microbial populations, respectively. The effect of RFI on bacterial profiles was influenced by diet, with the association between RFI group and PCR-DGGE profiles stronger for the higher forage diet. qPCR showed thatPrevotellaabundance was higher (P< 0.0001) in inefficient animals. A higher (P< 0.0001) abundance ofEntodiniumandPrevotellaspp. and a lower (P< 0.0001) abundance ofFibrobacter succinogeneswere observed when animals were offered the low-forage diet. Thus, differences in the ruminal microflora may contribute to host feed efficiency, although this effect may also be modulated by the diet offered.

scholarly journals In Vivo Assay Reveals Microbial OleA Thiolases Initiating Hydrocarbon and β-Lactone Biosynthesis

mBio ◽  
2020 ◽  
Vol 11 (2) ◽  
Author(s):  
Megan D. Smith ◽  
Serina L. Robinson ◽  
Mandkhai Molomjamts ◽  
Lawrence P. Wackett
Keyword(s):  
Metabolic Pathways ◽  
Xanthomonas Campestris ◽  
Membrane Lipids ◽  
Membrane Lipid ◽  
Limited Information ◽  
Content Type ◽  
Bacterial Phyla ◽  
Long Chain

ABSTRACT OleA, a member of the thiolase superfamily, is known to catalyze the Claisen condensation of long-chain acyl coenzyme A (acyl-CoA) substrates, initiating metabolic pathways in bacteria for the production of membrane lipids and β-lactone natural products. OleA homologs are found in diverse bacterial phyla, but to date, only one homodimeric OleA has been successfully purified to homogeneity and characterized in vitro. A major impediment for the identification of new OleA enzymes has been protein instability and time-consuming in vitro assays. Here, we developed a bioinformatic pipeline to identify OleA homologs and a new rapid assay to screen OleA enzyme activity in vivo and map their taxonomic diversity. The screen is based on the discovery that OleA displayed surprisingly high rates of p-nitrophenyl ester hydrolysis, an activity not shared by other thiolases, including FabH. The high rates allowed activity to be determined in vitro and with heterologously expressed OleA in vivo via the release of the yellow p-nitrophenol product. Seventy-four putative oleA genes identified in the genomes of diverse bacteria were heterologously expressed in Escherichia coli, and 25 showed activity with p-nitrophenyl esters. The OleA proteins tested were encoded in variable genomic contexts from seven different phyla and are predicted to function in distinct membrane lipid and β-lactone natural product metabolic pathways. This study highlights the diversity of unstudied OleA proteins and presents a rapid method for their identification and characterization. IMPORTANCE Microbially produced β-lactones are found in antibiotic, antitumor, and antiobesity drugs. Long-chain olefinic membrane hydrocarbons have potential utility as fuels and specialty chemicals. The metabolic pathway to both end products share bacterial enzymes denoted as OleA, OleC, and OleD that transform acyl-CoA cellular intermediates into β-lactones. Bacteria producing membrane hydrocarbons via the Ole pathway additionally express a β-lactone decarboxylase, OleB. Both β-lactone and olefin biosynthesis pathways are initiated by OleA enzymes that define the overall structure of the final product. There is currently very limited information on OleA enzymes apart from the single representative from Xanthomonas campestris. In this study, bioinformatic analysis identified hundreds of new, putative OleA proteins, 74 proteins were screened via a rapid whole-cell method, leading to the identification of 25 stably expressed OleA proteins representing seven bacteria phyla.

scholarly journals Development and comparison of RNA-sequencing pipelines for more accurate SNP identification: practical example of functional SNP detection associated with feed efficiency in Nellore beef cattle

BMC Genomics ◽  
2020 ◽  
Vol 21 (1) ◽  
Author(s):  
S. Lam ◽  
J. Zeidan ◽  
F. Miglior ◽  
A. Suárez-Vega ◽  
I. Gómez-Redondo ◽  
...  
Keyword(s):  
Beef Cattle ◽  
Candidate Genes ◽  
Rna Sequencing ◽  
Feed Efficiency ◽  
Metabolic Pathways ◽  
Functional Annotation ◽  
Read Depth ◽  
Economic Benefits ◽  
Rna Seq ◽  
Positional Candidate

Abstract Background Optimization of an RNA-Sequencing (RNA-Seq) pipeline is critical to maximize power and accuracy to identify genetic variants, including SNPs, which may serve as genetic markers to select for feed efficiency, leading to economic benefits for beef production. This study used RNA-Seq data (GEO Accession ID: PRJEB7696 and PRJEB15314) from muscle and liver tissue, respectively, from 12 Nellore beef steers selected from 585 steers with residual feed intake measures (RFI; n = 6 low-RFI, n = 6 high-RFI). Three RNA-Seq pipelines were compared including multi-sample calling from i) non-merged samples; ii) merged samples by RFI group, iii) merged samples by RFI and tissue group. The RNA-Seq reads were aligned against the UMD3.1 bovine reference genome (release 94) assembly using STAR aligner. Variants were called using BCFtools and variant effect prediction (VeP) and functional annotation (ToppGene) analyses were performed. Results On average, total reads detected for Approach i) non-merged samples for liver and muscle, were 18,362,086.3 and 35,645,898.7, respectively. For Approach ii), merging samples by RFI group, total reads detected for each merged group was 162,030,705, and for Approach iii), merging samples by RFI group and tissues, was 324,061,410, revealing the highest read depth for Approach iii). Additionally, Approach iii) merging samples by RFI group and tissues, revealed the highest read depth per variant coverage (572.59 ± 3993.11) and encompassed the majority of localized positional genes detected by each approach. This suggests Approach iii) had optimized detection power, read depth, and accuracy of SNP calling, therefore increasing confidence of variant detection and reducing false positive detection. Approach iii) was then used to detect unique SNPs fixed within low- (12,145) and high-RFI (14,663) groups. Functional annotation of SNPs revealed positional candidate genes, for each RFI group (2886 for low-RFI, 3075 for high-RFI), which were significantly (P < 0.05) associated with immune and metabolic pathways. Conclusion The most optimized RNA-Seq pipeline allowed for more accurate identification of SNPs, associated positional candidate genes, and significantly associated metabolic pathways in muscle and liver tissues, providing insight on the underlying genetic architecture of feed efficiency in beef cattle.

scholarly journals Application of Molecular Techniques to Better Understand the Roles of Rumen Microbiota in Cattle Feed Efficiency

Fine Focus ◽  
2016 ◽  
Vol 2 (2) ◽  
pp. 82-91
Author(s):  
Jun Hong Liu ◽  
Le Luo Guan
Keyword(s):  
Feed Intake ◽  
Feed Efficiency ◽  
High Throughput Sequencing ◽  
Negative Relationship ◽  
Live Weight ◽  
Molecular Techniques ◽  
Cattle Feed ◽  
Rumen Microbiota ◽  
Rumen Microbiome ◽  
New Findings

Feed efficiency, simply expressed as less feed inputs versus animal production outputs, can be measured in several ways, such as feed conversion ratio (FCR) and residual feed intake (RFI). FCR is a common measurement in beef cattle operations, and is the ratio of feed intake to live-weight gain. RFI is defined as the difference between actual and predicted feed intake after taking into account variability in maintenance and growth requirements. Rumen microbiota, which inludes bacteria, archaea, protozoa, and fungi, play an essential role in the digestion of lignocellulosic plant biomass, and can provide more than 70% of the host ruminants energy requirements via the production of volatile fatty acids (VFAs). Methane, a potent greenhouse gas (GHG), is produced in large quantities by the rumen microbiota, and is a known contributor to the global increase in GHG emissions. Studies have shown a negative relationship between methane emission and feed efficiency. Therefore, there is a need to study the feed efficiency from a rumen microbiome perspective and explore the probability of improving feed efficiency and hence reduce methane production in cattle by manipulating the rumen microbiome. The development of high-throughput sequencing technologies incuding metagenomics and metatranscriptomic analyses in the past decade has led to a sharp increase in understanding the rumen microbiota and associated function. As such, this mini-review will focus on the new findings during the last decade in cattle feed efficiency and the rumen microbiome.

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