Pubmed Record 31243332
Abstract Text
Farmed ruminants are the largest source of anthropogenic methane emissions globally. The methanogenic archaea responsible for these emissions use molecular hydrogen (H2), produced during bacterial and eukaryotic carbohydrate fermentation, as their primary energy source. In this work, we used comparative genomic, metatranscriptomic and co-culture-based approaches to gain a system-wide understanding of the organisms and pathways responsible for ruminal H2 metabolism. Two-thirds of sequenced rumen bacterial and archaeal genomes encode enzymes that catalyse H2 production or consumption, including 26 distinct hydrogenase subgroups. Metatranscriptomic analysis confirmed that these hydrogenases are differentially expressed in sheep rumen. Electron-bifurcating [FeFe]-hydrogenases from carbohydrate-fermenting Clostridia (e.g., Ruminococcus) accounted for half of all hydrogenase transcripts. Various H2 uptake pathways were also expressed, including methanogenesis (Methanobrevibacter), fumarate and nitrite reduction (Selenomonas), and acetogenesis (Blautia). Whereas methanogenesis-related transcripts predominated in high methane yield sheep, alternative uptake pathways were significantly upregulated in low methane yield sheep. Complementing these findings, we observed significant differential expression and activity of the hydrogenases of the hydrogenogenic cellulose fermenter Ruminococcus albus and the hydrogenotrophic fumarate reducer Wolinella succinogenes in co-culture compared with pure culture. We conclude that H2 metabolism is a more complex and widespread trait among rumen microorganisms than previously recognised. There is evidence that alternative hydrogenotrophs, including acetogenic and respiratory bacteria, can prosper in the rumen and effectively compete with methanogens for H2. These findings may help to inform ongoing strategies to mitigate methane emissions by increasing flux through alternative H2 uptake pathways, including through animal selection, dietary supplementation and methanogenesis inhibitors.
Pubmed Record 30066630
Abstract Text
De novo assembly of RNA-seq data allows the study of transcriptome in absence of a reference genome either if data is obtained from a single organism or from a mixed sample as in metatranscriptomics studies. Given the high number of sequences obtained from NGS approaches, a critical step in any analysis workflow is the assembly of reads to reconstruct transcripts thus reducing the complexity of the analysis. Despite many available tools show a good sensitivity, there is a high percentage of false positives due to the high number of assemblies considered and it is likely that the high frequency of false positive is underestimated by currently used benchmarks. The reconstruction of not existing transcripts may false the biological interpretation of results as - for example - may overestimate the identification of "novel" transcripts. Moreover, benchmarks performed are usually based on RNA-seq data from annotated genomes and assembled transcripts are compared to annotations and genomes to identify putative good and wrong reconstructions, but these tests alone may lead to accept a particular type of false positive as true, as better described below. Here we present a novel methodology of de novo assembly, implemented in a software named STAble (Short-reads Transcriptome Assembler). The novel concept of this assembler is that the whole reads are used to determine possible alignments instead of using smaller k-mers, with the aim of reducing the number of chimeras produced. Furthermore, we applied a new set of benchmarks based on simulated data to better define the performance of assembly method and carefully identifying true reconstructions. STAble was also used to build a prototype workflow to analyse metatranscriptomics data in connection to a steady state metabolic modelling algorithm. This algorithm was used to produce high quality metabolic interpretations of small gene expression sets obtained from already published RNA-seq data that we assembled with STAble. The presented results, albeit preliminary, clearly suggest that with this approach is possible to identify informative reactions not directly revealed by raw transcriptomic data.
Pubmed Record 27760570
Abstract Text
Enteric fermentation by farmed ruminant animals is a major source of methane and constitutes the second largest anthropogenic contributor to global warming. Reducing methane emissions from ruminants is needed to ensure sustainable animal production in the future. Methane yield varies naturally in sheep and is a heritable trait that can be used to select animals that yield less methane per unit of feed eaten. We previously demonstrated elevated expression of hydrogenotrophic methanogenesis pathway genes of methanogenic archaea in the rumens of high methane yield (HMY) sheep compared to their low methane yield (LMY) counterparts. Methane production in the rumen is strongly connected to microbial hydrogen production through fermentation processes. In this study, we investigate the contribution that rumen bacteria make to methane yield phenotypes in sheep. Using deep sequence metagenome and metatranscriptome datasets in combination with 16S rRNA gene amplicon sequencing from HMY and LMY sheep, we show enrichment of lactate-producing Sharpea spp. in LMY sheep bacterial communities. Increased gene and transcript abundances for sugar import and utilisation and production of lactate, propionate and butyrate were also observed in LMY animals. Sharpea azabuensis and Megasphaera spp. act as important drivers of lactate production and utilisation according to phylogenetic analysis and read mappings. Our findings show that the rumen microbiome in LMY animals supports a rapid heterofermentative growth, leading to lactate production. We postulate that lactate is subsequently metabolised mainly to butyrate in LMY animals, producing 2 mol of hydrogen and 0.5 mol of methane per mol hexose, which represents 24 % less than the 0.66 mol of methane formed from the 2.66 mol of hydrogen produced if hexose fermentation was directly to acetate and butyrate. These findings are consistent with the theory that a smaller rumen size with a higher turnover rate, where rapid heterofermentative growth would be an advantage, results in lower hydrogen production and lower methane formation. Together with previous methanogen gene expression data, this builds a strong concept of how animal traits and microbial communities shape the methane phenotype in sheep.
Pubmed Record 25909276
Abstract Text
Search of metagenomics sequence databases for homologs of virophage capsid proteins resulted in the discovery of a new family of virophages in the sheep rumen metagenome. The genomes of the rumen virophages (RVP) encode a typical virophage major capsid protein, ATPase and protease combined with a Polinton-type, protein primed family B DNA polymerase. The RVP genomes appear to be linear molecules, with terminal inverted repeats. Thus, the RVP seem to represent virophage-Polinton hybrids that are likely capable of formation of infectious virions. Virion proteins of mimiviruses were detected in the same metagenomes as the RVP suggesting that the virophages of the new family parasitize on giant viruses that infect protist inhabitants of the rumen.
Pubmed Record 24907284
Abstract Text
Ruminant livestock represent the single largest anthropogenic source of the potent greenhouse gas methane, which is generated by methanogenic archaea residing in ruminant digestive tracts. While differences between individual animals of the same breed in the amount of methane produced have been observed, the basis for this variation remains to be elucidated. To explore the mechanistic basis of this methane production, we measured methane yields from 22 sheep, which revealed that methane yields are a reproducible, quantitative trait. Deep metagenomic and metatranscriptomic sequencing demonstrated a similar abundance of methanogens and methanogenesis pathway genes in high and low methane emitters. However, transcription of methanogenesis pathway genes was substantially increased in sheep with high methane yields. These results identify a discrete set of rumen methanogens whose methanogenesis pathway transcription profiles correlate with methane yields and provide new targets for CH4 mitigation at the levels of microbiota composition and transcriptional regulation.
