Links between the rumen microbiota, methane emissions and feed efficiency of finishing steers offered dietary lipid and nitrate supplementation

Understanding the Diversity and Roles of the Ruminal Microbiome

The importance of ruminal microbiota in ruminants is emphasized, not only as a special symbiotic relationship with ruminants but also as an interactive and dynamic ecosystem established by the metabolites of various rumen microorganisms. Rumen microbial community is essential for life maintenance and production as they help decompose and utilize fiber that is difficult to digest, supplying about 70% of the energy needed by the host and 60-85% of the amino acids that reach the small intestine. Bacteria are the most abundant in the rumen, but protozoa, which are relatively large, account for 40-50% of the total microorganisms. However, the composition of these ruminal microbiota is not conserved or constant throughout life and is greatly influenced by the host. It is known that the initial colonization of calves immediately after birth is mainly influenced by the mother, and later changes depending on various factors such as diet, age, gender and breed. The initial rumen microbial community contains aerobic and facultative anaerobic bacteria due to the presence of oxygen, but as age increases, a hypoxic environment is created inside the rumen, and anaerobic bacteria become dominant in the rumen microbial community. As calves grow, taxonomic diversity increases, especially as they begin to consume solid food. Understanding the factors affecting the rumen microbial community and their effects and changes can lead to the early development and stabilization of the microbial community through the control of rumen microorganisms, and is expected to ultimately help improve host productivity and efficiency.

Composition of the rumen archaeal community of growing camels fed different concentrate levels

Understanding the rumen fermentation and methanogenic community in camels fed intensively is critical for optimizing rumen fermentation, improving feed efficiency, and lowering methane emissions. Using Illumina MiSeq sequencing, quantitative real-time PCR, and high-performance liquid chromatography, this study evaluates the influence of different concentrate supplement levels in the diet on rumen fermentation as well as the diversity and structure of the rumen methanogenic community for growing dromedary camels. Twelve growing camels were divided into three groups and given three levels of concentrate supplement, 0.7% (C1), 1% (C2), and 1.3% (C3) based on their body weight. All animals were fed alfalfa hay ad libitum. The levels of total volatile fatty acid, rumen ammonia, and methanogen copy number were unaffected by the supplementation level. Increasing the concentrate supplement level increased the proportion of propionic acid while decreasing the proportion of acetic acid. Increasing the level of concentrate in the diet had no effect on alpha diversity metrics or beta diversity of rumen methanogens. Methanobrevibacter and Methanosphaera predominated the methanogenic community and were declined as concentrate supplement level increased. This study sheds new light on the effect of concentrate supplement level in growing camels' diet on rumen fermentation and methanogenic community, which could help in the development of a strategy that aimed to reduce methane emissions and enhance feed efficiency.

Applying assisted reproductive technology and reproductive management to reduce CO2-equivalent emission in dairy and beef cattle: a review

Methane emission from beef and dairy cattle combined contributes around 4.5-5.0% of total anthropogenic global methane. In addition to enteric methane (CH4) produced by the rumen, cattle production also contributes carbon dioxide (CO2) (feed), nitrous oxide (N2O) (feed production, manure) and other CH4 (manure) to the total greenhouse gas (GHG) budget of beef and dairy production systems. The relative contribution in standard dairy systems is typically enteric CH4 58%, feed 29% and manure 10%. Herds with low production efficiency can have an enteric CH4 contribution up to 90%. Digestibility of feed can impact CH4 emission intensity. Low fertility herds also have a greater enteric CH4 contribution. Animals with good feed conversion efficiency have a lower emission intensity of CH4/kg of meat or milk. Feed efficient heifers tend to be lean and have delayed puberty. Fertility is a major driver of profit in both beef and dairy cattle, and it is highly important to apply multi-trait selection when shifting herds towards improved efficiency and reduced CH4. Single nucleotide polymorphisms (SNPs) have been identified for feed efficiency in cattle and are used in genomic selection. SNPs can be utilized in artificial insemination and embryo transfer to increase the proportion of cattle that have the attributes of efficiency, fertility and reduced enteric CH4. Prepubertal heifers genomically selected for favourable traits can have oocytes recovered to produce IVF embryos. Reproductive technology is predicted to be increasingly adopted to reduce generation interval and accelerate the rate of genetic gain for efficiency, fertility and low CH4 in cattle. The relatively high contribution of cattle to anthropogenic global methane has focussed attention on strategies to reduce enteric CH4 without compromising efficiency and fertility. Assisted reproductive technology has an important role in achieving the goal of multiplying and distributing cattle that have good efficiency, fertility and low CH4.

Combining host and rumen metagenome profiling for selection in sheep: prediction of methane, feed efficiency, production, and health traits

BACKGROUND

Rumen microbes break down complex dietary carbohydrates into energy sources for the host and are increasingly shown to be a key aspect of animal performance. Host genotypes can be combined with microbial DNA sequencing to predict performance traits or traits related to environmental impact, such as enteric methane emissions. Metagenome profiles were generated from 3139 rumen samples, collected from 1200 dual purpose ewes, using restriction enzyme-reduced representation sequencing (RE-RRS). Phenotypes were available for methane (CH4) and carbon dioxide (CO2) emissions, the ratio of CH4 to CH4 plus CO2 (CH4Ratio), feed efficiency (residual feed intake: RFI), liveweight at the time of methane collection (LW), liveweight at 8 months (LW8), fleece weight at 12 months (FW12) and parasite resistance measured by faecal egg count (FEC1). We estimated the proportion of phenotypic variance explained by host genetics and the rumen microbiome, as well as prediction accuracies for each of these traits.

RESULTS

Incorporating metagenome profiles increased the variance explained and prediction accuracy compared to fitting only genomics for all traits except for CO2 emissions when animals were on a grass diet. Combining the metagenome profile with host genotype from lambs explained more than 70% of the variation in methane emissions and residual feed intake. Predictions were generally more accurate when incorporating metagenome profiles compared to genetics alone, even when considering profiles collected at different ages (lamb vs adult), or on different feeds (grass vs lucerne pellet). A reference-free approach to metagenome profiling performed better than metagenome profiles that were restricted to capturing genera from a reference database. We hypothesise that our reference-free approach is likely to outperform other reference-based approaches such as 16S rRNA gene sequencing for use in prediction of individual animal performance.

CONCLUSIONS

This paper shows the potential of using RE-RRS as a low-cost, high-throughput approach for generating metagenome profiles on thousands of animals for improved prediction of economically and environmentally important traits. A reference-free approach using a microbial relationship matrix from log₁₀ proportions of each tag normalized within cohort (i.e., the group of animals sampled at the same time) is recommended for future predictions using RE-RRS metagenome profiles.

Effects of Major Families of Modulators on Performances and Gastrointestinal Microbiota of Poultry, Pigs and Ruminants: A Systematic Approach

Considering the ban on the use of antibiotics as growth stimulators in the livestock industry, the use of microbiota modulators appears to be an alternative solution to improve animal performance. This review aims to describe the effect of different families of modulators on the gastrointestinal microbiota of poultry, pigs and ruminants and their consequences on host physiology. To this end, 65, 32 and 4 controlled trials or systematic reviews were selected from PubMed for poultry, pigs and ruminants, respectively. Microorganisms and their derivatives were the most studied modulator family in poultry, while in pigs, the micronutrient family was the most investigated. With only four controlled trials selected for ruminants, it was difficult to conclude on the modulators of interest for this species. For some modulators, most studies showed a beneficial effect on both the phenotype and the microbiota. This was the case for probiotics and plants in poultry and minerals and probiotics in pigs. These modulators seem to be a good way for improving animal performance.

Taxonomic and predicted functional signatures reveal linkages between the rumen microbiota and feed efficiency in dairy cattle raised in tropical areas

Ruminants digest plant biomass more efficiently than monogastric animals due to their symbiotic relationship with a complex microbiota residing in the rumen environment. What remains unclear is the relationship between the rumen microbial taxonomic and functional composition and feed efficiency (FE), especially in crossbred dairy cattle (Holstein x Gyr) raised under tropical conditions. In this study, we selected twenty-two F1 Holstein x Gyr heifers and grouped them according to their residual feed intake (RFI) ranking, high efficiency (HE) (n = 11) and low efficiency (LE) (n = 11), to investigate the effect of FE on the rumen microbial taxa and their functions. Rumen fluids were collected using a stomach tube apparatus and analyzed using amplicon sequencing targeting the 16S (bacteria and archaea) and 18S (protozoa) rRNA genes. Alpha-diversity and beta-diversity analysis revealed no significant difference in the rumen microbiota between the HE and LE animals. Multivariate analysis (sPLS-DA) showed a clear separation of two clusters in bacterial taxonomic profiles related to each FE group, but in archaeal and protozoal profiles, the clusters overlapped. The sPLS-DA also revealed a clear separation in functional profiles for bacteria, archaea, and protozoa between the HE and LE animals. Microbial taxa were differently related to HE (e.g., Howardella and Shuttleworthia) and LE animals (e.g., Eremoplastron and Methanobrevibacter), and predicted functions were significatively different for each FE group (e.g., K03395-signaling and cellular process was strongly related to HE animals, and K13643-genetic information processing was related to LE animals). This study demonstrates that differences in the rumen microbiome relative to FE ranking are not directly observed from diversity indices (Faith's Phylogenetic Diversity, Pielou's Evenness, Shannon's diversity, weighted UniFrac distance, Jaccard index, and Bray-Curtis dissimilarity), but from targeted identification of specific taxa and microbial functions characterizing each FE group. These results shed light on the role of rumen microbial taxonomic and functional profiles in crossbred Holstein × Gyr dairy cattle raised in tropical conditions, creating the possibility of using the microbial signature of the HE group as a biological tool for the development of biomarkers that improve FE in ruminants.

Global Warming and Dairy Cattle: How to Control and Reduce Methane Emission

Agriculture produces greenhouse gases. Methane is a result of manure degradation and microbial fermentation in the rumen. Reduced CH4 emissions will slow climate change and reduce greenhouse gas concentrations. This review compiled studies to evaluate the best ways to decrease methane emissions. Longer rumination times reduce methane emissions and milk methane. Other studies have not found this. Increasing propionate and reducing acetate and butyrate in the rumen can reduce hydrogen equivalents that would otherwise be transferred to methanogenesis. Diet can reduce methane emissions. Grain lowers rumen pH, increases propionate production, and decreases CH4 yield. Methane generation per unit of energy-corrected milk yield reduces with a higher-energy diet. Bioactive bromoform discovered in the red seaweed Asparagopsis taxiformis reduces livestock intestinal methane output by inhibiting its production. Essential oils, tannins, saponins, and flavonoids are anti-methanogenic. While it is true that plant extracts can assist in reducing methane emissions, it is crucial to remember to source and produce plants in a sustainable manner. Minimal lipid supplementation can reduce methane output by 20%, increasing energy density and animal productivity. Selecting low- CH4 cows may lower GHG emissions. These findings can lead to additional research to completely understand the impacts of methanogenesis suppression on rumen fermentation and post-absorptive metabolism, which could improve animal productivity and efficiency.

Enteric Methane Emission, Rumen Fermentation and Microbial Profiles of Meat-Master Lambs Supplemented with Barley Fodder Sprouts

This study evaluated the effects of barley sprout on the ruminal fermentation characteristics, enteric methane emission and microbiome profiles of meat-master lambs. Twelve uncastrated lambs aged 3 months were used. They were randomly assigned to three dietary treatments: Eragrostis curvula hay as a control diet (T1), grass hay plus 25% barley sprouts (T2) and grass hay plus 50% barley sprouts (T3). Animals were fed the diet for 61 days, including 10 days of adaptation. Four animals per treatment were used to collect methane and rumen fluid. Methane emission was recorded for nine consecutive days, from day 52 to 60, using a hand-held laser detector. Rumen fluid was collected on day 61 using an esophageal stomach tube for volatile fatty acid and DNA sequencing. The sprout supplementation had significant (p < 0.05) effects on methane emission and ruminal fermentation. Significant effects on rumen fermentation were observed with regards to ammonia–nitrogen (NH3-N), acetic acid and a tendency (p < 0.0536) to increase propionic acid. Barley sprouts reduced methane gas emission, ammonia–nitrogen and the enhanced body weight of the animals. The bacteria Bacteroidota and Firmicutes were predominant among the identified phyla. In addition, there was a shift in the relative abundance of phylum among the treatments. The principal coordinate analysis showed a clear difference in microbiome among animals in T1 and those in T2 and T3. The sprout supplementation improves feed utilization efficiency by the animals. In conclusion, barley sprouts may be strategically used as a climate-smart feed resource for ruminants.

Host Genome-Metagenome Analyses Using Combinatorial Network Methods Reveal Key Metagenomic and Host Genetic Features for Methane Emission and Feed Efficiency in Cattle

Cattle production is one of the key contributors to global warming due to methane emission, which is a by-product of converting feed stuff into milk and meat for human consumption. Rumen hosts numerous microbial communities that are involved in the digestive process, leading to notable amounts of methane emission. The key factors underlying differences in methane emission between individual animals are due to, among other factors, both specific enrichments of certain microbial communities and host genetic factors that influence the microbial abundances. The detection of such factors involves various biostatistical and bioinformatics methods. In this study, our main objective was to reanalyze a publicly available data set using our proprietary Synomics Insights platform that is based on novel combinatorial network and machine learning methods to detect key metagenomic and host genetic features for methane emission and residual feed intake (RFI) in dairy cattle. The other objective was to compare the results with publicly available standard tools, such as those found in the microbiome bioinformatics platform QIIME2 and classic GWAS analysis. The data set used was publicly available and comprised 1,016 dairy cows with 16S short read sequencing data from two dairy cow breeds: Holstein and Nordic Reds. Host genomic data consisted of both 50 k and 150 k SNP arrays. Although several traits were analyzed by the original authors, here, we considered only methane emission as key phenotype for associating microbial communities and host genetic factors. The Synomics Insights platform is based on combinatorial methods that can identify taxa that are differentially abundant between animals showing high or low methane emission or RFI. Focusing exclusively on enriched taxa, for methane emission, the study identified 26 order-level taxa that combinatorial networks reported as significantly enriched either in high or low emitters. Additionally, a Z-test on proportions found 21/26 (81%) of these taxa were differentially enriched between high and low emitters (p value <.05). In particular, the phylum of Proteobacteria and the order Desulfovibrionales were found enriched in high emitters while the order Veillonellales was found to be more abundant in low emitters as previously reported for cattle (Wallace et al., 2015). In comparison, using the publicly available tool ANCOM only the order Methanosarcinales could be identified as differentially abundant between the two groups. We also investigated a link between host genome and rumen microbiome by applying our Synomics Insights platform and comparing it with an industry standard GWAS method. This resulted in the identification of genetic determinants in cows that are associated with changes in heritable components of the rumen microbiome. Only four key SNPs were found by both our platform and GWAS, whereas the Synomics Insights platform identified 1,290 significant SNPs that were not found by GWAS. Gene Ontology (GO) analysis found transcription factor as the dominant biological function. We estimated heritability of a core 73 taxa from the original set of 150 core order-level taxonomies and showed that some species are medium to highly heritable (0.25–0.62), paving the way for selective breeding of animals with desirable core microbiome characteristics. We identified a set of 113 key SNPs associated with >90% of these core heritable taxonomies. Finally, we have characterized a small set (<10) of SNPs strongly associated with key heritable bacterial orders with known role in methanogenesis, such as Desulfobacterales and Methanobacteriales.

Dynamics of the ruminal microbial ecosystem, and inhibition of methanogenesis and propiogenesis in response to nitrate feeding to Holstein calves

It is known that nitrate inhibits ruminal methanogenesis, mainly through competition with hydrogenotrophic methanogens for available hydrogen (H₂) and also through toxic effects on the methanogens. However, there is limited knowledge about its effects on the others members of ruminal microbiota and their metabolites. In this study, we investigated the effects of dietary nitrate inclusion on enteric methane (CH₄) emission, temporal changes in ruminal microbiota, and fermentation in Holstein calves. Eighteen animals were maintained in individual pens for 45 d. Animals were randomly allocated to either a control (CTR) or nitrate (NIT, containing 15 g of calcium nitrate/kg dry matter) diets. Methane emissions were estimated using the sulfur hexafluoride (SF₆) tracer method. Ruminal microbiota changes and ruminal fermentation were evaluated at 0, 4, and 8 h post-feeding. In this study, feed dry matter intake (DMI) did not differ between dietary treatments (P > 0.05). Diets containing NIT reduced CH₄ emissions by 27% (g/d) and yield by 21% (g/kg DMI) compared to the CTR (P < 0.05). The pH values and total volatile fatty acids (VFA) concentration did not differ between dietary treatments (P > 0.05) but differed with time, and post-feeding (P < 0.05). Increases in the concentrations of ruminal ammonia nitrogen (NH₃–N) and acetate were observed, whereas propionate decreased at 4 h post-feeding with the NIT diet (P < 0.05). Feeding the NIT diet reduced the populations of total bacteria, total methanogens, Ruminococcus albus and Ruminococcus flavefaciens, and the abundance of Succiniclasticum, Coprococcus, Treponema, Shuttlewortia, Succinivibrio, Sharpea, Pseudobutyrivibrio, and Selenomona (P < 0.05); whereas, the population of total fungi, protozoa, Fibrobacter succinogenes, Atopobium and Erysipelotrichaceae L7A_E11 increased (P < 0.05). In conclusion, feeding nitrate reduces enteric CH₄ emissions and the methanogens population, whereas it decreases the propionate concentration and the abundance of bacteria involved in the succinate and acrylate pathways. Despite the altered fermentation profile and ruminal microbiota, DMI was not influenced by dietary nitrate. These findings suggest that nitrate has a predominantly direct effect on the reduction of methanogenesis and propionate synthesis.

Genome-Wide Identification of Reference Genes for Reverse-Transcription Quantitative PCR in Goat Rumen

Simple Summary

The rumen plays an essential role as a digestive organ and serves as the primary site of energy substrate absorption for the productive ruminants. Understanding gene expression profiles is necessary to explore the intrinsic regulatory mechanisms of rumen development in goats. The selection of suitable reference genes (RGs) was the primary assay before the real-time quantitative PCR (RT-qPCR). We identified sixteen genome-wide candidate RGs for normalization of gene expression assessments in goat rumen tissues. We demonstrate that the RGs selected (RPS4X and RPS6) were more stably expressed than the commonly used HKGs (ACTB and GAPDH) in goat rumen tissues, suggesting that the ribosomal protein gene family may be another source for the RG pool.

Abstract

As the largest chamber of the ruminant stomach, the rumen not only serves as the principal absorptive surface and nutrient transport pathway from the lumen into the animal, but also plays an important short-chain fatty acid (SCFA) metabolic role in addition to protective functions. Accurate characterization of the gene expression profiles of genes of interest is essential to the exploration of the intrinsic regulatory mechanisms of rumen development in goats. Thus, the selection of suitable reference genes (RGs) is an important prerequisite for real-time quantitative PCR (RT-qPCR). In the present study, 16 candidate RGs were identified from our previous transcriptome sequencing of caprine rumen tissues. The quantitative expressions of the candidate RGs were measured using the RT-qPCR method, and the expression stability of the RGs was assessed using the geNorm, NormFinder, and BestKeeper programs. GeNorm analysis showed that the M values were less than 0.5 for all the RGs except GAPT4, indicating that they were stably expressed in the rumen tissues throughout development. RPS4X and RPS6 were the two most stable RGs. Furthermore, the expressions of two randomly selected target genes (IGF1 and TOP2A), normalized by the selected most stable RGs (RPS4X and RPS6), were consistent with the results of RNA sequencing, while the use of GAPDH and ACTB as RGs resulted in altered profiles. Overall, RPS4X and RPS6 showed the highest expression stability and the lowest coefficients of variation, and could be used as the optimal reference combination for quantifying gene expression in rumen tissues via RT-qPCR analysis.

Effect of a Low-Methane Diet on Performance and Microbiome in Lactating Dairy Cows Accounting for Individual Pre-Trial Methane Emissions

This study examined the effects of partly replacing grass silage (GS) with maize silage (MS), with or without rapeseed oil (RSO) supplementation, on methane (CH₄) emissions, production performance, and rumen microbiome in the diets of lactating dairy cows. The effect of individual pre-trial CH₄-emitting characteristics on dietary emissions mitigation was also examined. Twenty Nordic Red cows at 71 ± 37.2 (mean ± SD) days in milk were assigned to a replicated 4 × 4 Latin square design with four dietary treatments (GS, GS supplemented with RSO, GS plus MS, GS plus MS supplemented with RSO) applied in a 2 × 2 factorial arrangement. Partial replacement of GS with MS decreased the intake of dry matter (DM) and nutrients, milk production, yield of milk components, and general nutrient digestibility. Supplementation with RSO decreased the intake of DM and nutrients, energy-corrected milk yield, composition and yield of milk fat and protein, and general digestibility of nutrients, except for crude protein. Individual cow pre-trial measurements of CH₄-emitting characteristics had a significant influence on gas emissions but did not alter the magnitude of CH₄ emissions. Dietary RSO decreased daily CH₄, yield, and intensity. It also increased the relative abundance of rumen Methanosphaera and Succinivibrionaceae and decreased that of Bifidobacteriaceae. There were no effects of dietary MS on CH₄ emissions in this study, but supplementation with 41 g RSO/kg of DM reduced daily CH₄ emissions from lactating dairy cows by 22.5%.

Assessing the relationship between the rumen microbiota and feed efficiency in Nellore steers

BACKGROUND

Ruminants rely upon a complex community of microbes in their rumen to convert host-indigestible feed into nutrients. However, little is known about the association between the rumen microbiota and feed efficiency traits in Nellore (Bos indicus) cattle, a breed of major economic importance to the global beef market. Here, we compare the composition of the bacterial, archaeal and fungal communities in the rumen of Nellore steers with high and low feed efficiency (FE) phenotypes, as measured by residual feed intake (RFI).

RESULTS

The Firmicutes to Bacteroidetes ratio was significantly higher (P < 0.05) in positive-RFI steers (p-RFI, low feed efficiency) than in negative-RFI (n-RFI, high feed efficiency) steers. The differences in bacterial composition from steers with high and low FE were mainly associated with members of the families Lachnospiraceae, Ruminococcaceae and Christensenellaceae, as well as the genus Prevotella. Archaeal community richness was lower (P < 0.05) in p-RFI than in n-RFI steers and the genus Methanobrevibacter was either increased or exclusive of p-RFI steers. The fungal genus Buwchfawromyces was more abundant in the rumen solid fraction of n-RFI steers (P < 0.05) and a highly abundant OTU belonging to the genus Piromyces was also increased in the rumen microbiota of high-efficiency steers. However, analysis of rumen fermentation variables and functional predictions indicated similar metabolic outputs for the microbiota of distinct FE groups.

CONCLUSIONS

Our results demonstrate that differences in the ruminal microbiota of high and low FE Nellore steers comprise specific taxa from the bacterial, archaeal and fungal communities. Biomarker OTUs belonging to the genus Piromyces were identified in animals showing high feed efficiency, whereas among archaea, Methanobrevibacter was associated with steers classified as p-RFI. The identification of specific RFI-associated microorganisms in Nellore steers could guide further studies targeting the isolation and functional characterization of rumen microbes potentially important for the energy-harvesting efficiency of ruminants.

Microbial Communities in Methane Cycle: Modern Molecular Methods Gain Insights into Their Global Ecology

The role of methane as a greenhouse gas in the concept of global climate changes is well known. Methanogens and methanotrophs are two microbial groups which contribute to the biogeochemical methane cycle in soil, so that the total emission of CH4 is the balance between its production and oxidation by microbial communities. Traditional identification techniques, such as selective enrichment and pure-culture isolation, have been used for a long time to study diversity of methanogens and methanotrophs. However, these techniques are characterized by significant limitations, since only a relatively small fraction of the microbial community could be cultured. Modern molecular methods for quantitative analysis of the microbial community such as real-time PCR (Polymerase chain reaction), DNA fingerprints and methods based on high-throughput sequencing together with different “omics” techniques overcome the limitations imposed by culture-dependent approaches and provide new insights into the diversity and ecology of microbial communities in the methane cycle. Here, we review available knowledge concerning the abundances, composition, and activity of methanogenic and methanotrophic communities in a wide range of natural and anthropogenic environments. We suggest that incorporation of microbial data could fill the existing microbiological gaps in methane flux modeling, and significantly increase the predictive power of models for different environments.

Replacing Barley and Soybean Meal With By-products, in a Pasture Based Diet, Alters Daily Methane Output and the Rumen Microbial Community in vitro Using the Rumen Simulation Technique (RUSITEC)

Plant based by-products (BP) produced from food and bioethanol industries are human inedible, but can be recycled into the global food chain by ruminant livestock. However, limited data is available on the methanogenesis potential associated with supplementing a solely BP formulated concentrate to a pastoral based diet. Therefore the objective of this in vitro study was to investigate the effects of BP inclusion rate (in a formulated concentrate) to a pasture based diet on dietary digestibility, rumen fermentation patterns, methane production and the prokaryotic microbial community composition. Diets consisted of perennial ryegrass and one of two supplementary concentrates, formulated to be isonitrogenous (16% CP) and isoenergetic (12.0 MJ/ME/kg), containing either 35% BP, barley and soybean meal (BP35) or 95% BP (BP95) offered on a 50:50 basis, however, starch, NDF and fat content varied. The BPs, included in equal proportions on a DM basis, were soyhulls, palm kernel expeller and maize dried distillers grains. The BP35 diet had greater (P < 0.05) digestibility of the chemical constituents DM, OM, CP, NDF, ADF. Greater total VFA production was seen in the BP35 diet (P < 0.05). Daily methane production (mmol/day; +22.7%) and methane output per unit of total organic matter digested (MPOMD; +20.8%) were greatest in the BP35 diet (P < 0.01). Dietary treatment influenced microbial composition (PERMANOVA; P = 0.023) with a greater relative abundance of Firmicutes (adj P < 0.01) observed in the BP35. The Firmicutes:Bacteroidetes ratio was significantly reduced in the BP95 diet (P < 0.01). The relative proportions of Proteobacteria (adj P < 0.01), Succinivibrionaceae (adj P < 0.03) and Succinivibrio (adj P = 0.053) increased in the BP95 diet. The abundance of Proteobacteria was found to be negatively associated with daily methane production (r_s, −0.71; P < 0.01) and MPOMD (r_s, −0.65; P < 0.01). Within Proteobacteria, the relationship of methane production was maintained with the mean abundance of Succinivibrio (r_s, −0.69; P < 0.01). The abundance of the Firmicutes phyla was found to be positively correlated with both daily methane production (r_s, 0.79; P < 0.001) and MPOMD (r_s, 0.75; P < 0.01). Based on in vitro rumen simulation data, supplementation of an exclusively BP formulated concentrate was shown to reduce daily methane output by promoting a favorable alteration to the rumen prokaryotic community.