A primary aim of microbial ecology is to determine patterns and drivers of community distribution, interaction, and assembly amidst complexity and uncertainty. Microbial community composition has been shown to change across gradients of environment, geographic distance, salinity, temperature, oxygen, nutrients, pH, day length, and biotic factors 1-6 . These patterns have been identified mostly by focusing on one sample type and region at a time, with insights extra polated across environments and geography to produce generalized principles. To assess how microbes are distributed across environments globally-or whether microbial community dynamics follow funda mental ecological 'laws' at a planetary scale-requires either a massive monolithic cross environment survey or a practical methodology for coordinating many independent surveys. New studies of microbial environments are rapidly accumulating; however, our ability to extract meaningful information from across datasets is outstripped by the rate of data generation. Previous meta analyses have suggested robust gen eral trends in community composition, including the importance of salinity 1 and animal association 2 . These findings, although derived from relatively small and uncontrolled sample sets, support the util ity of meta analysis to reveal basic patterns of microbial diversity and suggest that a scalable and accessible analytical framework is needed.The Earth Microbiome Project (EMP, http://www.earthmicrobiome. org) was founded in 2010 to sample the Earth's microbial communities at an unprecedented scale in order to advance our understanding of the organizing biogeographic principles that govern microbial commu nity structure 7,8 . We recognized that open and collaborative science, including scientific crowdsourcing and standardized methods 8 , would help to reduce technical variation among individual studies, which can overwhelm biological variation and make general trends difficult to detect 9 . Comprising around 100 studies, over half of which have yielded peer reviewed publications (Supplementary Table 1), the EMP has now dwarfed by 100 fold the sampling and sequencing depth of earlier meta analysis efforts 1,2 ; concurrently, powerful analysis tools have been developed, opening a new and larger window into the distri bution of microbial diversity on Earth. In establishing a scalable frame work to catalogue microbiota globally, we provide both a resource for the exploration of myriad questions and a starting point for the guided acquisition of new data to answer them. As an example of using this Our growing awareness of the microbial world's importance and diversity contrasts starkly with our limited understanding of its fundamental structure. Despite recent advances in DNA sequencing, a lack of standardized protocols and common analytical frameworks impedes comparisons among studies, hindering the development of global inferences about microbial life on Earth. Here we present a meta-analysis of microbial community samples collected by hundreds of r...

Summary The bacteria that colonize humans and our built environments have the potential to influence our health. Microbial communities associated with seven families and their homes over six weeks were assessed, including three families that moved home. Microbial communities differed significantly among homes, and the home microbiome was largely sourced from humans. The microbiota in each home were identifiable by family. Network analysis identified humans as the primary bacterial vector, and a Bayesian method significantly matched individuals to their dwellings. Draft genomes of potential human pathogens were observed on a kitchen counter could be matched to the hands of occupants. Following a house move, the microbial community in the new house rapidly converged on the microbial community of the occupants’ former house, suggesting rapid colonization by the family’s microbiota.

Cultivation-independent surveys of microbial diversity have revealed many bacterial phyla that lack cultured representatives. These lineages, referred to as candidate phyla, have been detected across many environments. Here, we deeply sequenced microbial communities from acetate-stimulated aquifer sediment to recover the complete and essentially complete genomes of single representatives of the candidate phyla SR1, WWE3, TM7, and OD1. All four of these genomes are very small, 0.7 to 1.2 Mbp, and have large inventories of novel proteins. Additionally, all lack identifiable biosynthetic pathways for several key metabolites. The SR1 genome uses the UGA codon to encode glycine, and the same codon is very rare in the OD1 genome, suggesting that the OD1 organism could also transition to alternate coding. Interestingly, the relative abundance of the members of SR1 increased with the appearance of sulfide in groundwater, a pattern mirrored by a member of the phylum Tenericutes. All four genomes encode type IV pili, which may be involved in interorganism interaction. On the basis of these results and other recently published research, metabolic dependence on other organisms may be widely distributed across multiple bacterial candidate phyla.

The microorganisms that inhabit hospitals may significantly influence patient recovery rates and outcomes (REFs). To develop a community level understating of how microorganisms colonize and move through the hospital environment, we mapped microbial dynamics between hospital surfaces, air and water to patients and staff over the course of one year as a new hospital became operational. Immediately following the introduction of staff and patients, the hospital microbiome became dominated by human skin-associated bacteria. Human skin samples had the lowest microbial diversity, while the greatest diversity was found on surfaces interacting with outdoor environments. The microbiota of patient room surfaces, especially bedrails, consistently resembled the skin microbial community of the current patient, with degree of similarity significantly correlated to higher humidity and lower temperatures. Microbial similarity between staff members showed a significant seasonal trend being greatest in late summer/early fall correlating with increased humidity.

Viruses represent the most abundant life forms on the planet. Recent experimental and computational improvements have led to a dramatic increase in the number of viral genome sequences identified primarily from metagenomic samples. As a result of the expanding catalog of metagenomic viral sequences, there exists a need for a comprehensive computational platform integrating all these sequences with associated metadata and analytical tools. Here we present IMG/VR (https://img.jgi.doe.gov/vr/), the largest publicly available database of 3908 isolate reference DNA viruses with 264 413 computationally identified viral contigs from >6000 ecologically diverse metagenomic samples. Approximately half of the viral contigs are grouped into genetically distinct quasi-species clusters. Microbial hosts are predicted for 20 000 viral sequences, revealing nine microbial phyla previously unreported to be infected by viruses. Viral sequences can be queried using a variety of associated metadata, including habitat type and geographic location of the samples, or taxonomic classification according to hallmark viral genes. IMG/VR has a user-friendly interface that allows users to interrogate all integrated data and interact by comparing with external sequences, thus serving as an essential resource in the viral genomics community.

The “Candidatus Synechococcus spongiarum” group includes different clades of cyanobacteria with high 16S rRNA sequence identity (~99%) and is the most abundant and widespread cyanobacterial symbiont of marine sponges. The first draft genome of a “Ca. Synechococcus spongiarum” group member was recently published, providing evidence of genome reduction by loss of genes involved in several nonessential functions. However, “Ca. Synechococcus spongiarum” includes a variety of clades that may differ widely in genomic repertoire and consequently in physiology and symbiotic function. Here, we present three additional draft genomes of “Ca. Synechococcus spongiarum,” each from a different clade. By comparing all four symbiont genomes to those of free-living cyanobacteria, we revealed general adaptations to life inside sponges and specific adaptations of each phylotype. Symbiont genomes shared about half of their total number of coding genes. Common traits of “Ca. Synechococcus spongiarum” members were a high abundance of DNA modification and recombination genes and a reduction in genes involved in inorganic ion transport and metabolism, cell wall biogenesis, and signal transduction mechanisms. Moreover, these symbionts were characterized by a reduced number of antioxidant enzymes and low-weight peptides of photosystem II compared to their free-living relatives. Variability within the “Ca. Synechococcus spongiarum” group was mostly related to immune system features, potential for siderophore-mediated iron transport, and dependency on methionine from external sources. The common absence of genes involved in synthesis of residues, typical of the O antigen of free-living Synechococcus species, suggests a novel mechanism utilized by these symbionts to avoid sponge predation and phage attack.

Fermentation-based metabolism is an important ecosystem function often associated with environments rich in organic carbon, such as wetlands, sewage sludge and the mammalian gut. The diversity of microorganisms and pathways involved in carbon and hydrogen cycling in sediments and aquifers and the impacts of these processes on other biogeochemical cycles remain poorly understood. Here we used metagenomics and proteomics to characterize microbial communities sampled from an aquifer adjacent to the Colorado River at Rifle, CO, USA, and document interlinked microbial roles in geochemical cycling. The organic carbon content in the aquifer was elevated via acetate amendment of the groundwater occurring over 2 successive years. Samples were collected at three time points, with the objective of extensive genome recovery to enable metabolic reconstruction of the community. Fermentative community members include organisms from a new phylum, Melainabacteria, most closely related to Cyanobacteria, phylogenetically novel members of the Chloroflexi and Bacteroidales, as well as candidate phyla genomes (OD1, BD1-5, SR1, WWE3, ACD58, TM6, PER and OP11). These organisms have the capacity to produce hydrogen, acetate, formate, ethanol, butyrate and lactate, activities supported by proteomic data. The diversity and expression of hydrogenases suggests the importance of hydrogen metabolism in the subsurface. Our proteogenomic data further indicate the consumption of fermentation intermediates by Proteobacteria can be coupled to nitrate, sulfate and iron reduction. Thus, fermentation carried out by previously unknown members of sediment microbial communities may be an important driver of nitrogen, hydrogen, sulfur, carbon and iron cycling.

In microbial ecology, a fundamental question relates to how community diversity and composition change in response to perturbation. Most studies have had limited ability to deeply sample community structure (e.g. Sanger-sequenced 16S rRNA libraries), or have had limited taxonomic resolution (e.g. studies based on 16S rRNA hypervariable region sequencing). Here, we combine the higher taxonomic resolution of near-full-length 16S rRNA gene amplicons with the economics and sensitivity of short-read sequencing to assay the abundance and identity of organisms that represent as little as 0.01% of sediment bacterial communities. We used a new version of EMIRGE optimized for large data size to reconstruct near-full-length 16S rRNA genes from amplicons sheared and sequenced with Illumina technology. The approach allowed us to differentiate the community composition among samples acquired before perturbation, after acetate amendment shifted the predominant metabolism to iron reduction, and once sulfate reduction began. Results were highly reproducible across technical replicates, and identified specific taxa that responded to the perturbation. All samples contain very high alpha diversity and abundant organisms from phyla without cultivated representatives. Surprisingly, at the time points measured, there was no strong loss of evenness, despite the selective pressure of acetate amendment and change in the terminal electron accepting process. However, community membership was altered significantly. The method allows for sensitive, accurate profiling of the “long tail” of low abundance organisms that exist in many microbial communities, and can resolve population dynamics in response to environmental change.