Technical note: Comparison of biomarker and molecular biological methods for estimating methanogen abundance

Feed Intake, Methane Emissions, Milk Production and Rumen Methanogen Populations of Grazing Dairy Cows Supplemented with Various C 18 Fatty Acid Sources

Emissions of methane (CH4) from dairy production systems are environmentally detrimental and represent an energy cost to the cow. This study evaluated the effect of varying C18 fatty acid sources on CH4 emissions, milk production and rumen methanogen populations in grazing lactating dairy cows. Forty-five Holstein Friesian cows were randomly allocated to one of three treatments (n = 15). Cows were offered 15 kg dry matter (DM)/d of grazed pasture plus supplementary concentrates (4 kg DM/d) containing either stearic acid (SA), linseed oil (LO), or soy oil (SO). Cows offered LO and SO had lower pasture DM intake (DMI) than those offered SA (11.3, 11.5 vs. 12.6 kg/d). Cows offered LO and SO had higher milk yield (21.0, 21.3 vs. 19.7 kg/d) and milk protein yield (0.74, 0.73 vs. 0.67 kg/d) than those offered SA. Emissions of CH4 (245 vs. 293, 289 g/d, 12.4 vs. 15.7, 14.8 g/kg of milk and 165 vs. 207, 195 g/kg of milk solids) were lower for cows offered LO than those offered SA or SO. Methanobrevibacter ruminantium abundance was reduced in cows offered LO compared to SA. Offering supplementary concentrates containing LO can reduce enteric CH4 emissions from pasture fed dairy cows.

Identification, Comparison, and Validation of Robust Rumen Microbial Biomarkers for Methane Emissions Using Diverse Bos Taurus Breeds and Basal Diets

Previous shotgun metagenomic analyses of ruminal digesta identified some microbial information that might be useful as biomarkers to select cattle that emit less methane (CH4), which is a potent greenhouse gas. It is known that methane production (g/kgDMI) and to an extent the microbial community is heritable and therefore biomarkers can offer a method of selecting cattle for low methane emitting phenotypes. In this study a wider range of Bos Taurus cattle, varying in breed and diet, was investigated to determine microbial communities and genetic markers associated with high/low CH4 emissions. Digesta samples were taken from 50 beef cattle, comprising four cattle breeds, receiving two basal diets containing different proportions of concentrate and also including feed additives (nitrate or lipid), that may influence methane emissions. A combination of partial least square analysis and network analysis enabled the identification of the most significant and robust biomarkers of CH4 emissions (VIP > 0.8) across diets and breeds when comparing all potential biomarkers together. Genes associated with the hydrogenotrophic methanogenesis pathway converting carbon dioxide to methane, provided the dominant biomarkers of CH4 emissions and methanogens were the microbial populations most closely correlated with CH4 emissions and identified by metagenomics. Moreover, these genes grouped together as confirmed by network analysis for each independent experiment and when combined. Finally, the genes involved in the methane synthesis pathway explained a higher proportion of variation in CH4 emissions by PLS analysis compared to phylogenetic parameters or functional genes. These results confirmed the reproducibility of the analysis and the advantage to use these genes as robust biomarkers of CH4 emissions. Volatile fatty acid concentrations and ratios were significantly correlated with CH4, but these factors were not identified as robust enough for predictive purposes. Moreover, the methanotrophic Methylomonas genus was found to be negatively correlated with CH4. Finally, this study confirmed the importance of using robust and applicable biomarkers from the microbiome as a proxy of CH4 emissions across diverse production systems and environments.

Methane sources in arctic thermokarst lake sediments on the North Slope of Alaska

The permafrost on the North Slope of Alaska is densely populated by shallow lakes that result from thermokarst erosion. These lakes release methane (CH4 ) derived from a combination of ancient thermogenic pools and contemporary biogenic production. Despite the potential importance of CH4 as a greenhouse gas, the contribution of biogenic CH4 production in arctic thermokarst lakes in Alaska is not currently well understood. To further advance our knowledge of CH4 dynamics in these lakes, we focused our study on (i) the potential for microbial CH4 production in lake sediments, (ii) the role of sediment geochemistry in controlling biogenic CH4 production, and (iii) the temperature dependence of this process. Sediment cores were collected from one site in Siqlukaq Lake and two sites in Sukok Lake in late October to early November. Analyses of pore water geochemistry, sedimentary organic matter and lipid biomarkers, stable carbon isotopes, results from CH4 production experiments, and copy number of a methanogenic pathway-specific gene (mcrA) indicated the existence of different sources of CH4 in each of the lakes chosen for the study. Analysis of this integrated data set revealed that there is biological CH4 production in Siqlukaq at moderate levels, while the very low levels of CH4 detected in Sukok had a mixed origin, with little to no biological CH4 production. Furthermore, methanogenic archaea exhibited temperature-dependent use of in situ substrates for methanogenesis, and the amount of CH4 produced was directly related to the amount of labile organic matter in the sediments. This study constitutes an important first step in better understanding the actual contribution of biogenic CH4 from thermokarst lakes on the coastal plain of Alaska to the current CH4 budgets.

Microbial trophic interactions and mcrA gene expression in monitoring of anaerobic digesters

Anaerobic digestion (AD) is a biological process where different trophic groups of microorganisms break down biodegradable organic materials in the absence of oxygen. A wide range of AD technologies is being used to convert livestock manure, municipal and industrial wastewaters, and solid organic wastes into biogas. AD gains importance not only because of its relevance in waste treatment but also because of the recovery of carbon in the form of methane, which is a renewable energy and is used to generate electricity and heat. Despite the advances on the engineering and design of new bioreactors for AD, the microbiology component always poses challenges. Microbiology of AD processes is complicated as the efficiency of the process depends on the interactions of various trophic groups involved. Due to the complex interdependence of microbial activities for the functionality of the anaerobic bioreactors, the genetic expression of mcrA, which encodes a key enzyme in methane formation, is proposed as a parameter to monitor the process performance in real time. This review evaluates the current knowledge on microbial groups, their interactions, and their relationship to the performance of anaerobic biodigesters with a focus on using mcrA gene expression as a tool to monitor the process.

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

Background

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.