Reference phylogenies are crucial for providing a taxonomic framework for interpretation of marker gene and metagenomic surveys, which continue to reveal novel species at a remarkable rate. Greengenes is a dedicated full-length 16S rRNA gene database that provides users with a curated taxonomy based on de novo tree inference. We developed a ‘taxonomy to tree’ approach for transferring group names from an existing taxonomy to a tree topology, and used it to apply the Greengenes, National Center for Biotechnology Information (NCBI) and cyanoDB (Cyanobacteria only) taxonomies to a de novo tree comprising 408 315 sequences. We also incorporated explicit rank information provided by the NCBI taxonomy to group names (by prefixing rank designations) for better user orientation and classification consistency. The resulting merged taxonomy improved the classification of 75% of the sequences by one or more ranks relative to the original NCBI taxonomy with the most pronounced improvements occurring in under-classified environmental sequences. We also assessed candidate phyla (divisions) currently defined by NCBI and present recommendations for consolidation of 34 redundantly named groups. All intermediate results from the pipeline, which includes tree inference, jackknifing and transfer of a donor taxonomy to a recipient tree (tax2tree) are available for download. The improved Greengenes taxonomy should provide important infrastructure for a wide range of megasequencing projects studying ecosystems on scales ranging from our own bodies (the Human Microbiome Project) to the entire planet (the Earth Microbiome Project). The implementation of the software can be obtained from http://sourceforge.net/projects/tax2tree/.

The tree of life is one of the most important organizing principles in biology¹. Gene surveys suggest the existence of an enormous number of branches², but even an approximation of the full scale of the tree has remained elusive. Recent depictions of the tree of life have focused either on the nature of deep evolutionary relationships^3–5 or on the known, well-classified diversity of life with an emphasis on eukaryotes⁶. These approaches overlook the dramatic change in our understanding of life's diversity resulting from genomic sampling of previously unexamined environments. New methods to generate genome sequences illuminate the identity of organisms and their metabolic capacities, placing them in community and ecosystem contexts^7,8. Here, we use new genomic data from over 1,000 uncultivated and little known organisms, together with published sequences, to infer a dramatically expanded version of the tree of life, with Bacteria, Archaea and Eukarya included. The depiction is both a global overview and a snapshot of the diversity within each major lineage. The results reveal the dominance of bacterial diversification and underline the importance of organisms lacking isolated representatives, with substantial evolution concentrated in a major radiation of such organisms. This tree highlights major lineages currently underrepresented in biogeochemical models and identifies radiations that are probably important for future evolutionary analyses.

Microbial communities are critical to ecosystem function. A key objective of metagenomic studies is to analyse organism-specific metabolic pathways and reconstruct community interaction networks. This requires accurate assignment of assembled genome fragments to genomes. Existing binning methods often fail to reconstruct a reasonable number of genomes and report many bins of low quality and completeness. Furthermore, the performance of existing algorithms varies between samples and biotopes. Here, we present a dereplication, aggregation and scoring strategy, DAS Tool, that combines the strengths of a flexible set of established binning algorithms. DAS Tool applied to a constructed community generated more accurate bins than any automated method. Indeed, when applied to environmental and host-associated samples of different complexity, DAS Tool recovered substantially more near-complete genomes, including previously unreported lineages, than any single binning method alone. The ability to reconstruct many near-complete genomes from metagenomics data will greatly advance genome-centric analyses of ecosystems.

The subterranean world hosts up to one-fifth of all biomass, including microbial communities that drive transformations central to Earth’s biogeochemical cycles. However, little is known about how complex microbial communities in such environments are structured, and how inter-organism interactions shape ecosystem function. Here we apply terabase-scale cultivation-independent metagenomics to aquifer sediments and groundwater, and reconstruct 2,540 draft-quality, near-complete and complete strain-resolved genomes that represent the majority of known bacterial phyla as well as 47 newly discovered phylum-level lineages. Metabolic analyses spanning this vast phylogenetic diversity and representing up to 36% of organisms detected in the system are used to document the distribution of pathways in coexisting organisms. Consistent with prior findings indicating metabolic handoffs in simple consortia, we find that few organisms within the community can conduct multiple sequential redox transformations. As environmental conditions change, different assemblages of organisms are selected for, altering linkages among the major biogeochemical cycles.

Diving into Deep Water: The Deepwater Horizon oil spill in the Gulf of Mexico was one of the largest oil spills on record. Its setting at the bottom of the sea floor posed an unanticipated risk as substantial amounts of hydrocarbons leaked into the deepwater column. Three separate cruises identified and sampled deep underwater hydrocarbon plumes that existed in May and June, 2010—before the well head was ultimately sealed. Camilli et al. (p. 201 ; published online 19 August) used an automated underwater vehicle to assess the dimensions of a stabilized, diffuse underwater plume of oil that was 22 miles long and estimated the daily quantity of oil released from the well, based on the concentration and dimensions of the plume. Hazen et al. (p. 204 ; published online 26 August) also observed an underwater plume at the same depth and found that hydrocarbon-degrading bacteria were enriched in the plume and were breaking down some parts of the oil. Finally, Valentine et al. (p. 208 ; published online 16 September) found that natural gas, including propane and ethane, were also present in hydrocarbon plumes. These gases were broken down quickly by bacteria, but primed the system for biodegradation of larger hydrocarbons, including those comprising the leaking crude oil. Differences were observed in dissolved oxygen levels in the plumes (a proxy for bacterial respiration), which may reflect differences in the location of sampling or the aging of the plumes.

Using a metagenomic approach, three types of CRISPR–Cas systems have been discovered in uncultivated bacterial and archaeal hosts from a variety of different environments. Current CRISPR–Cas technology is based on systems identified from cultured bacteria, whereas the enzymes from the numerous prokaryotes that have not been cultured have remained unexplored. By using cultivation-independent genome-resolved metagenomics, Jillian Banfield, Jennifer Doudna and colleagues identify and then functionally characterize new CRISPR–Cas systems. These include the first reported Cas9 in the archaeal domain of life, which was thought to lack such systems, as well as compact CRISPR–CasX and CRISPR–CasY systems. Genomic exploration of environmental microbial communities gives access to unprecedented genome diversity with the potential to revolutionize microbe-based biotechnologies. CRISPR–Cas systems provide microbes with adaptive immunity by employing short DNA sequences, termed spacers, that guide Cas proteins to cleave foreign DNA1,2. Class 2 CRISPR–Cas systems are streamlined versions, in which a single RNA-bound Cas protein recognizes and cleaves target sequences3,4. The programmable nature of these minimal systems has enabled researchers to repurpose them into a versatile technology that is broadly revolutionizing biological and clinical research5. However, current CRISPR–Cas technologies are based solely on systems from isolated bacteria, leaving the vast majority of enzymes from organisms that have not been cultured untapped. Metagenomics, the sequencing of DNA extracted directly from natural microbial communities, provides access to the genetic material of a huge array of uncultivated organisms6,7. Here, using genome-resolved metagenomics, we identify a number of CRISPR–Cas systems, including the first reported Cas9 in the archaeal domain of life, to our knowledge. This divergent Cas9 protein was found in little-studied nanoarchaea as part of an active CRISPR–Cas system. In bacteria, we discovered two previously unknown systems, CRISPR–CasX and CRISPR–CasY, which are among the most compact systems yet discovered. Notably, all required functional components were identified by metagenomics, enabling validation of robust in vivo RNA-guided DNA interference activity in Escherichia coli. Interrogation of environmental microbial communities combined with in vivo experiments allows us to access an unprecedented diversity of genomes, the content of which will expand the repertoire of microbe-based biotechnologies.