Quantitative analysis of ruminal methanogenic microbial populations in beef cattle divergent in phenotypic residual feed intake (RFI) offered contrasting diets

peer-reviewedBackground Methane (CH4) emissions in cattle are an undesirable end product of rumen methanogenic fermentative activity as they are associated not only with negative environmental impacts but also with reduced host feed efficiency. The aim of this study was to quantify total and specific rumen microbial methanogenic populations in beef cattle divergently selected for residual feed intake (RFI) while offered (i) a low energy high forage (HF) diet followed by (ii) a high energy low forage (LF) diet. Ruminal fluid was collected from 14 high (H) and 14 low (L) RFI animals across both dietary periods. Quantitative real time PCR (qRT-PCR) analysis was conducted to quantify the abundance of total and specific rumen methanogenic microbes. Spearman correlation analysis was used to investigate the association between the relative abundance of methanogens and animal performance, rumen fermentation variables and diet digestibility. Results Abundance of methanogens, did not differ between RFI phenotypes. However, relative abundance of total and specific methanogen species was affected (P < 0.05) by diet type, with greater abundance observed while animals were offered the LF compared to the HF diet. Conclusions These findings suggest that differences in abundance of specific rumen methanogen species may not contribute to variation in CH4 emissions between efficient and inefficient animals, however dietary manipulation can influence the abundance of total and specific methanogen species.Funding for the development and main work of this research was provided under the National Development Plan, through the Research Stimulus Fund, administered by the Department of Agriculture, Fisheries & Food, Ireland RSF 05 224

Rumen methanogenic genotypes differ in abundance according to host residual feed intake phenotype and diet type

Methane is an undesirable end product of rumen fermentative activity because of associated environmental impacts and reduced host feed efficiency. Our study characterized the rumen microbial methanogenic community in beef cattle divergently selected for phenotypic residual feed intake (RFI) while offered a high-forage (HF) diet followed by a low-forage (LF) diet. Rumen fluid was collected from 14 high-RFI (HRFI) and 14 low-RFI (LRFI) animals at the end of both dietary periods. 16S rRNA gene clone libraries were used, and methanogen-specific tag-encoded pyrosequencing was carried out on the samples. We found that Methanobrevibacter spp. are the dominant methanogens in the rumen, with Methanobrevibacter smithii being the most abundant species. Differences in the abundance of Methanobrevibacter smithii and Methanosphaera stadtmanae genotypes were detected in the rumen of animals offered the LF compared to the HF diet while the abundance of Methanobrevibacter smithii genotypes was different between HRFI and LRFI animals irrespective of diet. Our results demonstrate that while a core group of methanogen operational taxonomic units (OTUs) exist across diet and phenotype, significant differences were observed in the distribution of genotypes within those OTUs. These changes in genotype abundance may contribute to the observed differences in methane emissions between efficient and inefficient animals

Divergent functional isoforms drive niche specialisation for nutrient acquisition and use in rumen microbiome

Many microbes in complex competitive environments share genes for acquiring and utilising nutrients, questioning whether niche specialisation exists and if so, how it is maintained. We investigated the genomic signatures of niche specialisation in the rumen microbiome, a highly competitive, anaerobic environment, with limited nutrient availability determined by the biomass consumed by the host. We generated individual metagenomic libraries from 14 cows fed an ad libitum diet of grass silage and calculated functional isoform diversity for each microbial gene identified. The animal replicates were used to calculate confidence intervals to test for differences in diversity of functional isoforms between microbes that may drive niche specialisation. We identified 153 genes with significant differences in functional isoform diversity between the two most abundant bacterial genera in the rumen (Prevotella and Clostridium). We found Prevotella possesses a more diverse range of isoforms capable of degrading hemicellulose, whereas Clostridium for cellulose. Furthermore, significant differences were observed in key metabolic processes indicating that isoform diversity plays an important role in maintaining their niche specialisation. The methods presented represent a novel approach for untangling complex interactions between microorganisms in natural environments and have resulted in an expanded catalogue of gene targets central to rumen cellulosic biomass degradation

Synthetic Sequencing Standards : A Guide to Database Choice for Rumen Microbiota Amplicon Sequencing Analysis

Our understanding of complex microbial communities, such as those residing in the rumen, has drastically advanced through the use of high throughput sequencing (HTS) technologies. Indeed, with the use of barcoded amplicon sequencing, it is now cost effective and computationally feasible to identify individual rumen microbial genera associated with ruminant livestock nutrition, genetics, performance and greenhouse gas production. However, across all disciplines of microbial ecology, there is currently little reporting of the use of internal controls for validating HTS results. Furthermore, there is little consensus of the most appropriate reference database for analyzing rumen microbiota amplicon sequencing data. Therefore, in this study, a synthetic rumen-specific sequencing standard was used to assess the effects of database choice on results obtained from rumen microbial amplicon sequencing. Four DADA2 reference training sets (RDP, SILVA, GTDB, and RefSeq + RDP) were compared to assess their ability to correctly classify sequences included in the rumen-specific sequencing standard. In addition, two thresholds of phylogenetic bootstrapping, 50 and 80, were applied to investigate the effect of increasing stringency. Sequence classification differences were apparent amongst the databases. For example the classification of Clostridium differed between all databases, thus highlighting the need for a consistent approach to nomenclature amongst different reference databases. It is hoped the effect of database on taxonomic classification observed in this study, will encourage research groups across various microbial disciplines to develop and routinely use their own microbiome-specific reference standard to validate analysis pipelines and database choice.</p