Ruminants have the remarkable ability to convert human-indigestible plant biomass into human-digestible food products, due to a complex microbiome residing in the rumen compartment of their upper digestive tract. Here we report the discovery that rumen microbiome components are tightly linked to cows' ability to extract energy from their feed, termed feed efficiency. Feed efficiency was measured in 146 milking cows and analyses of the taxonomic composition, gene content, microbial activity and metabolomic composition was performed on the rumen microbiomes from the 78 most extreme animals. Lower richness of microbiome gene content and taxa was tightly linked to higher feed efficiency. Microbiome genes and species accurately predicted the animals' feed efficiency phenotype. Specific enrichment of microbes and metabolic pathways in each of these microbiome groups resulted in better energy and carbon channeling to the animal, while lowering methane emissions to the atmosphere. This ecological and mechanistic understanding of the rumen microbiome could lead to an increase in available food resources and environmentally friendly livestock agriculture.

Microbial communities are essential to the function of virtually all ecosystems and eukaryotes, including humans. However, it is still a major challenge to identify microbial cells active under natural conditions in complex systems. In this study, we developed a new method to identify and sort active microbes on the single-cell level in complex samples using stable isotope probing with heavy water (D 2 O) combined with Raman microspectroscopy. Incorporation of D 2 O-derived D into the biomass of autotrophic and heterotrophic bacteria and archaea could be unambiguously detected via C-D signature peaks in single-cell Raman spectra, and the obtained labeling pattern was confirmed by nanoscaleresolution secondary ion MS. In fast-growing Escherichia coli cells, label detection was already possible after 20 min. For functional analyses of microbial communities, the detection of D incorporation from D 2 O in individual microbial cells via Raman microspectroscopy can be directly combined with FISH for the identification of active microbes. Applying this approach to mouse cecal microbiota revealed that the host-compound foragers Akkermansia muciniphila and Bacteroides acidifaciens exhibited distinctive response patterns to amendments of mucin and sugars. By Ramanbased cell sorting of active (deuterated) cells with optical tweezers and subsequent multiple displacement amplification and DNA sequencing, novel cecal microbes stimulated by mucin and/ or glucosamine were identified, demonstrating the potential of the nondestructive D 2 O-Raman approach for targeted sorting of microbial cells with defined functional properties for singlecell genomics.ecophysiology | single-cell microbiology | carbohydrate utilization | nitrifier | Raman microspectroscopy M icroorganisms play a vital role in many environments. They mediate global biogeochemical cycles, catalyze biotechnological processes, and contribute to health and disease in the human body. The in situ study of microbial activity in natural and engineered ecosystems is therefore of great interest. For this purpose, several elegant methods have been established that use either transcriptional or translational activity of community members (i.e., metatranscriptomics, metaproteomics) (1-3) or the incorporation of isotopically labeled substrates into biomolecules (4-10) to infer the ecophysiology of microbes in such systems. However, these bulk techniques do not offer sufficient spatial resolution to study microbial activities at the micrometer scale. Therefore, important information can be overlooked because microbial communities are frequently spatially structured (e.g., biofilms) (11) and contain populations with life cycles (12,13). Furthermore, even apparently identical cells in clonal populations can have strongly divergent activities (14).Consequently, microbial ecophysiology is ideally studied also at the level of the single cell, but only a restricted number of approaches exist for determining physiological properties of individual cells in a microbial community. For exa...

Ruminants sustain a long-lasting obligatory relationship with their rumen microbiome dating back 50 million years. In this unique host-microbiome relationship, the host’s ability to digest its feed is completely dependent on its coevolved microbiome. This extraordinary alliance raises questions regarding the dependent relationship between ruminants’ genetics and physiology and the rumen microbiome structure, composition, and metabolism. To elucidate this relationship, we examined the association of host genetics with the phylogenetic and functional composition of the rumen microbiome. We accomplished this by studying a population of 78 Holstein-Friesian dairy cows, using a combination of rumen microbiota data and other phenotypes from each animal with genotypic data from a subset of 47 animals. We identified 22 operational taxonomic units (OTUs) whose abundances were associated with rumen metabolic traits and host physiological traits and which showed measurable heritability. The abundance patterns of these microbes can explain high proportions of variance in rumen metabolism and many of the host physiological attributes such as its energy-harvesting efficiency. Interestingly, these OTUs shared higher phylogenetic similarity between themselves than expected by chance, suggesting occupation of a specific ecological niche within the rumen ecosystem. The findings presented here suggest that ruminant genetics and physiology are correlated with microbiome structure and that host genetics may shape the microbiome landscape by enriching for phylogenetically related taxa that may occupy a unique niche.

MotivationPlasmids and other mobile elements are central contributors to microbial evolution and genome innovation. Recently, they have been found to have important roles in antibiotic resistance and in affecting production of metabolites used in industrial and agricultural applications. However, their characterization through deep sequencing remains challenging, in spite of rapid drops in cost and throughput increases for sequencing. Here, we attempt to ameliorate this situation by introducing a new circular element assembly algorithm, leveraging assembly graphs provided by a conventional de novo assembler and alignments of paired-end reads to assemble cyclic sequences likely to be plasmids, phages and other circular elements.ResultsWe introduce Recycler, the first tool that can extract complete circular contigs from sequence data of isolate microbial genomes, plasmidome and metagenome sequence data. We show that Recycler greatly increases the number of true plasmids recovered relative to other approaches while remaining highly accurate. We demonstrate this trend via simulations of plasmidomes, comparisons of predictions with reference data for isolate samples, and assessments of annotation accuracy on metagenome data. In addition, we provide validation by DNA amplification of 77 plasmids predicted by Recycler from the different sequenced samples in which Recycler showed mean accuracy of 89% across all data types—isolate, microbiome and plasmidome.Availability and ImplementationRecycler is available at http://github.com/Shamir-Lab/RecyclerSupplementary information Supplementary data are available at Bioinformatics online.

Abstract:In this minireview, we examine horizontal gene transfer (HGT) events in the mammalian gastrointestinal tract and their role in the evolutionary adaptation of microorganisms to the gut environment. We explore the notion of the mammalian gut as a melting pot of genetic exchange, resulting in the large extent of HGT occurrence.