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.

Vibrio cholerae, the causative agent of cholera, is a bacterium autochthonous to the aquatic environment, and a serious public health threat. V. cholerae serogroup O1 is responsible for the previous two cholera pandemics, in which classical and El Tor biotypes were dominant in the sixth and the current seventh pandemics, respectively. Cholera researchers continually face newly emerging and reemerging pathogenic clones carrying diverse combinations of phenotypic and genotypic properties, which significantly hampered control of the disease. To elucidate evolutionary mechanisms governing genetic diversity of pandemic V. cholerae, we compared the genome sequences of 23 V. cholerae strains isolated from a variety of sources over the past 98 years. The genome-based phylogeny revealed 12 distinct V. cholerae lineages, of which one comprises both O1 classical and El Tor biotypes. All seventh pandemic clones share nearly identical gene content. Using analogy to influenza virology, we define the transition from sixth to seventh pandemic strains as a ''shift'' between pathogenic clones belonging to the same O1 serogroup, but from significantly different phyletic lineages. In contrast, transition among clones during the present pandemic period is characterized as a ''drift'' between clones, differentiated mainly by varying composition of laterally transferred genomic islands, resulting in emergence of variants, exemplified by V. cholerae O139 and V. cholerae O1 El Tor hybrid clones. Based on the comparative genomics it is concluded that V. cholerae undergoes extensive genetic recombination via lateral gene transfer, and, therefore, genome assortment, not serogroup, should be used to define pathogenic V. cholerae clones.genomic islands ͉ cholera toxin prophage ͉ lateral gene transfer