The ruminal microbiome associated with methane emissions from ruminant livestock

Contribution of Ruminal Fungi, Archaea, Protozoa, and Bacteria to the Methane Suppression Caused by Oilseed Supplemented Diets

Dietary lipids can suppress methane emission from ruminants, but effects are variable. Especially the role of bacteria, archaea, fungi and protozoa in mediating the lipid effects is unclear. In the present in vitro study, archaea, fungi and protozoa were selectively inhibited by specific agents. This was fully or almost fully successful for fungi and protozoa as well as archaeal activity as determined by the methyl-coenzyme M reductase alpha subunit gene. Five different microbial treatments were generated: rumen fluid being intact (I), without archaea (–A), without fungi (–F), without protozoa (–P) and with bacteria only (–AFP). A forage-concentrate diet given alone or supplemented with crushed full-fat oilseeds of either safflower (Carthamus tinctorius) or poppy (Papaver somniferum) or camelina (Camelina sativa) at 70 g oil kg⁻¹ diet dry matter was incubated. This added up to 20 treatments with six incubation runs per treatment. All oilseeds suppressed methane emission compared to the non-supplemented control. Compared to the non-supplemented control, –F decreased organic matter (OM) degradation, and short-chain fatty acid concentration was greater with camelina and safflower seeds. Methane suppression per OM digested in –F was greater with camelina seeds (−12 vs.−7% with I, P = 0.06), but smaller with poppy seeds (−4 vs. −8% with I, P = 0.03), and not affected with safflower seeds. With –P, camelina seeds decreased the acetate-to-propionate ratio and enhanced the methane suppression per gram dry matter (18 vs. 10% with I, P = 0.08). Hydrogen recovery was improved with –P in any oilseeds compared to non-supplemented control. No methane emission was detected with the –A and –AFP treatments. In conclusion, concerning methanogenesis, camelina seeds seem to exert effects only on archaea and bacteria. By contrast, with safflower and poppy seeds methane was obviously reduced mainly through the interaction with protozoa or archaea associated with protozoa. This demonstrated that the microbial groups differ in their contribution to the methane suppressing effect dependent on the source of lipid. These findings help to understand how lipid supplementation and microbial groups interact, and thus may assist in making this methane mitigation tool more efficient, but await confirmation in vivo.

Archaea Are Interactive Components of Complex Microbiomes

Recent findings have shaken our picture of the biology of the archaea and revealed novel traits beyond archaeal extremophily and supposed 'primitiveness'. The archaea constitute a considerable fraction of the Earth's ecosystems, and their potential to shape their surroundings by a profound interaction with their biotic and abiotic environment has been recognized. Moreover, archaea have been identified as a substantial component, or even as keystone species, in complex microbiomes - in the environment or accompanying a holobiont. Species of the Euryarchaeota (methanogens, halophiles) and Thaumarchaeota, in particular, have the capacity to coexist in plant, animal, and human microbiomes, where syntrophy allows them to thrive under energy-deficiency stress. Due to methodological limitations, the archaeome remains mysterious, and many questions with respect to potential pathogenicity, function, and structural interactions with their host and other microorganisms remain.

Indigenously associated methanogens intensified the metabolism in hydrogenosomes of anaerobic fungi with xylose as substrate

Anaerobic fungi are potent lignocellulose degraders, but have not yet been exploited in this capacity, largely owing to their poor metabolic characterization. In the current study, a time course of fermentation was conducted to study the effect of the co-cultured methanogens on xylose metabolism by anaerobic fungi. The fermentation end-products from anaerobic fungal monoculture were H₂ (6.7 ml), CO₂ (65.7 ml), formate (17.90 mM), acetate (9.00 mM), lactate (11.89 mM), ethanol, and malate after 96 h fermentation. Compared to the monoculture, the end-products of co-culture shifted to more CO₂ (71.8 ml) and acetate (15.20 mM), methane (14.9 ml), less lactate (5.28 mM), and hardly detectable formate and H₂ at the end of fermentation. After 48 h, accumulated formate was remarkably consumed by co-cultured methanogens, accompanied by significantly increased acetate, CO₂ and pH, and decreased lactate and malate. Xylose utilization, in both cultures, was similar during fermentation. However, the relative flux of carbon in hydrogenosomes in the co-culture was higher than that in the monoculture. In conclusion, the co-culture with methanogens enhanced "energy yields" of anaerobic fungi by removing the accumulated formate, decreased the metabolism in cytosol, for example, the lactate pathway, and increased the metabolism in hydrogenosomes, for example, the acetate pathway.

Application of meta-omics techniques to understand greenhouse gas emissions originating from ruminal metabolism

Methane emissions from ruminal fermentation contribute significantly to total anthropological greenhouse gas (GHG) emissions. New meta-omics technologies are beginning to revolutionise our understanding of the rumen microbial community structure, metabolic potential and metabolic activity. Here we explore these developments in relation to GHG emissions. Microbial rumen community analyses based on small subunit ribosomal RNA sequence analysis are not yet predictive of methane emissions from individual animals or treatments. Few metagenomics studies have been directly related to GHG emissions. In these studies, the main genes that differed in abundance between high and low methane emitters included archaeal genes involved in methanogenesis, with others that were not apparently related to methane metabolism. Unlike the taxonomic analysis up to now, the gene sets from metagenomes may have predictive value. Furthermore, metagenomic analysis predicts metabolic function better than only a taxonomic description, because different taxa share genes with the same function. Metatranscriptomics, the study of mRNA transcript abundance, should help to understand the dynamic of microbial activity rather than the gene abundance; to date, only one study has related the expression levels of methanogenic genes to methane emissions, where gene abundance failed to do so. Metaproteomics describes the proteins present in the ecosystem, and is therefore arguably a better indication of microbial metabolism. Both two-dimensional polyacrylamide gel electrophoresis and shotgun peptide sequencing methods have been used for ruminal analysis. In our unpublished studies, both methods showed an abundance of archaeal methanogenic enzymes, but neither was able to discriminate high and low emitters. Metabolomics can take several forms that appear to have predictive value for methane emissions; ruminal metabolites, milk fatty acid profiles, faecal long-chain alcohols and urinary metabolites have all shown promising results. Rumen microbial amino acid metabolism lies at the root of excessive nitrogen emissions from ruminants, yet only indirect inferences for nitrogen emissions can be drawn from meta-omics studies published so far. Annotation of meta-omics data depends on databases that are generally weak in rumen microbial entries. The Hungate 1000 project and Global Rumen Census initiatives are therefore essential to improve the interpretation of sequence/metabolic information.