Ruminants provide essential nutrition for billions of people worldwide. The rumen is a specialized stomach that is adapted to the breakdown of plant-derived complex polysaccharides. The genomes of the rumen microbiota encode thousands of enzymes adapted to digestion of the plant matter that dominates the ruminant diet. We assembled 4,941 rumen microbial metagenome-assembled genomes (MAGs) using approximately 6.5 terabases of short- and long-read sequence data from 283 ruminant cattle. We present a genome-resolved metagenomics workflow that enabled assembly of bacterial and archaeal genomes that were at least 80% complete. Of note, we obtained three single-contig, whole-chromosome assemblies of rumen bacteria, two of which represent previously unknown rumen species, assembled from long-read data. Using our rumen genome collection we predicted and annotated a large set of rumen proteins. Our set of rumen MAGs increases the rate of mapping of rumen metagenomic sequencing reads from 15% to 50–70%. These genomic and protein resources will enable a better understanding of the structure and functions of the rumen microbiota.

The cow rumen is adapted for the breakdown of plant material into energy and nutrients, a task largely performed by enzymes encoded by the rumen microbiome. Here we present 913 draft bacterial and archaeal genomes assembled from over 800 Gb of rumen metagenomic sequence data derived from 43 Scottish cattle, using both metagenomic binning and Hi-C-based proximity-guided assembly. Most of these genomes represent previously unsequenced strains and species. The draft genomes contain over 69,000 proteins predicted to be involved in carbohydrate metabolism, over 90% of which do not have a good match in public databases. Inclusion of the 913 genomes presented here improves metagenomic read classification by sevenfold against our own data, and by fivefold against other publicly available rumen datasets. Thus, our dataset substantially improves the coverage of rumen microbial genomes in the public databases and represents a valuable resource for biomass-degrading enzyme discovery and studies of the rumen microbiome.

Soils store at least twice as much carbon (C) as plant biomass 1 , and, each year, soil microbial respiration releases ~60 Pg of C to the atmosphere as carbon dioxide (CO 2 ) 2 .In the short term, soil microbial respiration increases exponentially with temperature 3 , and thus models predict that warming-induced increases in CO 2 release from soils could represent an important positive feedback to 21 st century climate change 4 . However, the magnitude of this feedback remains uncertain, not least because the adaptation of soil microbial communities to changing temperatures has the potential to either substantially decrease ('compensatory adaptation' 5-7 ) or substantially increase ('enhancing adaptation' 8,9 ) warming-induced C losses. By collecting contrasting soils along a climatic gradient from the Arctic to the Amazon, we undertook the first global analysis of the role microbial thermal adaptation plays in controlling rates of CO 2 release from soils. Here we show that, enhancing adaptation was between three and ten times more common than compensatory adaptation. Furthermore, the strongest enhancing responses were observed in soils with high C contents and from cold climates; enhancing thermal adaptation increased the temperature sensitivity of respiration in these soils by a factor of 1.4. This suggests that the substantial stores of C present in organic and high-latitude soils may be more vulnerable to climate warming than currently predicted. Text:Short-term experiments have demonstrated that the rate of microbial respiration in soil increases exponentially with temperature, and this general relationship has been used in parameterising soil C and Earth system models 4,10 . However, plant physiologists have demonstrated that short-term measurements are inadequate for representing the dynamic response of plant respiration to changes in temperature. In plants, thermal acclimation, defined as the "subsequent adjustment in the rate of respiration to compensate for an initial change in temperature" 11 greatly reduces the impact of temperature change on plant respiration in the medium-to long-term, with major consequences for modelling C-cycle feedbacks to climate change 12 . In soil there is growing evidence of the potential for a similar compensatory effect through microbial adaptation to temperature 13 ('compensatory adaptation': defined here to include the potential for physiological acclimation, adaptation within populations, and changes in microbial community size and structure). However, it is unclear if microbial community-level responses should always be compensatory. In fact, responses that enhance the direct and instantaneous effect of temperature changes on soil respiration ('enhancing adaptation') have also been observed 8,9,14 . To date there has been no large-scale evaluation of the role of microbial adaptation in controlling the temperature sensitivity of soil respiration. This lack of understanding adds considerable uncertainty to predictions of the magnitude and direction of carbon-cycle feedb...

BackgroundThe emergence and spread of antimicrobial resistance is the most urgent current threat to human and animal health. An improved understanding of the abundance of antimicrobial resistance genes and genes associated with microbial colonisation and pathogenicity in the animal gut will have a major role in reducing the contribution of animal production to this problem. Here, the influence of diet on the ruminal resistome and abundance of pathogenicity genes was assessed in ruminal digesta samples taken from 50 antibiotic-free beef cattle, comprising four cattle breeds receiving two diets containing different proportions of concentrate.ResultsTwo hundred and four genes associated with antimicrobial resistance (AMR), colonisation, communication or pathogenicity functions were identified from 4966 metagenomic genes using KEGG identification. Both the diversity and abundance of these genes were higher in concentrate-fed animals. Chloramphenicol and microcin resistance genes were dominant in samples from forage-fed animals (P < 0.001), while aminoglycoside and streptomycin resistances were enriched in concentrate-fed animals. The concentrate-based diet also increased the relative abundance of Proteobacteria, which includes many animal and zoonotic pathogens. A high ratio of Proteobacteria to (Firmicutes + Bacteroidetes) was confirmed as a good indicator for rumen dysbiosis, with eight cases all from concentrate-fed animals. Finally, network analysis demonstrated that the resistance/pathogenicity genes are potentially useful as biomarkers for health risk assessment of the ruminal microbiome.ConclusionsDiet has important effects on the complement of AMR genes in the rumen microbial community, with potential implications for human and animal health.Electronic supplementary materialThe online version of this article (10.1186/s40168-017-0378-z) contains supplementary material, which is available to authorized users.

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.