The human gut harbors diverse microbes that play a fundamental role in the well-being of their host. The constituents of the microbiota—bacteria, viruses, and eukaryotes—have been shown to interact with one another and with the host immune system in ways that influence the development of disease. We review these interactions and suggest that a holistic approach to studying the microbiota that goes beyond characterization of community composition and encompasses dynamic interactions between all components of the microbiota and host tissue over time will be crucial for building predictive models for diagnosis and treatment of diseases linked to imbalances in our microbiota.

SILVA (from Latin silva, forest, http://www.arb-silva.de) is a comprehensive resource for up-to-date quality-controlled databases of aligned ribosomal RNA (rRNA) gene sequences from the Bacteria, Archaea and Eukaryota domains and supplementary online services. SILVA provides a manually curated taxonomy for all three domains of life, based on representative phylogenetic trees for the small- and large-subunit rRNA genes. This article describes the improvements the SILVA taxonomy has undergone in the last 3 years. Specifically we are focusing on the curation process, the various resources used for curation and the comparison of the SILVA taxonomy with Greengenes and RDP-II taxonomies. Our comparisons not only revealed a reasonable overlap between the taxa names, but also points to significant differences in both names and numbers of taxa between the three resources.

Microbial metabolism powers biogeochemical cycling in Earth's ecosystems. The taxonomic composition of microbial communities varies substantially between environments, but the ecological causes of this variation remain largely unknown. We analyzed taxonomic and functional community profiles to determine the factors that shape marine bacterial and archaeal communities across the global ocean. By classifying >30,000 marine microorganisms into metabolic functional groups, we were able to disentangle functional from taxonomic community variation. We find that environmental conditions strongly influence the distribution of functional groups in marine microbial communities by shaping metabolic niches, but only weakly influence taxonomic composition within individual functional groups. Hence, functional structure and composition within functional groups constitute complementary and roughly independent "axes of variation" shaped by markedly different processes.

This revision of the classification of eukaryotes, which updates that of Adl et al. (2005), retains an emphasis on the protists and incorporates changes since 2005 that have resolved nodes and branches in phylogenetic trees. Whereas the previous revision was successful in re-introducing name stability to the classification, this revision provides a classification for lineages that were then still unresolved. The supergroups have withstood phylogenetic hypothesis testing with some modifications, but despite some progress, problematic nodes at the base of the eukaryotic tree still remain to be statistically resolved. Looking forward, subsequent transformations to our understanding of the diversity of life will be from the discovery of novel lineages in previously under-sampled areas and from environmental genomic information.

Microbial communities often exhibit incredible taxonomic diversity, raising questions regarding the mechanisms enabling species coexistence and the role of this diversity in community functioning. On the one hand, many coexisting but taxonomically distinct microorganisms can encode the same energy-yielding metabolic functions, and this functional redundancy contrasts with the expectation that species should occupy distinct metabolic niches. On the other hand, the identity of taxa encoding each function can vary substantially across space or time with little effect on the function, and this taxonomic variability is frequently thought to result from ecological drift between equivalent organisms. Here, we synthesize the powerful paradigm emerging from these two patterns, connecting the roles of function, functional redundancy and taxonomy in microbial systems. We conclude that both patterns are unlikely to be the result of ecological drift, but are inevitable emergent properties of open microbial systems resulting mainly from biotic interactions and environmental and spatial processes.

Although macroscopic plants, animals, and fungi are the most familiar eukaryotes, the bulk of eukaryotic diversity is microbial. Elucidating the timing of diversification among the more than 70 lineages is key to understanding the evolution of eukaryotes. Here, we use taxon-rich multigene data combined with diverse fossils and a relaxed molecular clock framework to estimate the timing of the last common ancestor of extant eukaryotes and the divergence of major clades. Overall, these analyses suggest that the last common ancestor lived between 1866 and 1679 Ma, consistent with the earliest microfossils interpreted with confidence as eukaryotic. During this interval, the Earth's surface differed markedly from today; for example, the oceans were incompletely ventilated, with ferruginous and, after about 1800 Ma, sulfidic water masses commonly lying beneath moderately oxygenated surface waters. Our time estimates also indicate that the major clades of eukaryotes diverged before 1000 Ma, with most or all probably diverging before 1200 Ma. Fossils, however, suggest that diversity within major extant clades expanded later, beginning about 800 Ma, when the oceans began their transition to a more modern chemical state. In combination, paleontological and molecular approaches indicate that long stems preceded diversification in the major eukaryotic lineages.

Rapidly developing sequencing methods and analytical techniques are enhancing our ability to understand the human microbiome, and, indeed, how we define the microbiome and its constituents. In this review we highlight recent research that expands our ability to understand the human microbiome on different spatial and temporal scales, including daily timeseries datasets spanning months. Furthermore, we discuss emerging concepts related to defining operational taxonomic units, diversity indices, core versus transient microbiomes and the possibility of enterotypes. Additional advances in sequencing technology and in our understanding of the microbiome will provide exciting prospects for exploiting the microbiota for personalized medicine.

The human microbiome substantially affects many aspects of human physiology, including metabolism, drug interactions and numerous diseases. This realization, coupled with ever-improving nucleotide sequencing technology, has precipitated the collection of diverse data sets that profile the microbiome. In the past 2 years, studies have begun to include sufficient numbers of subjects to provide the power to associate these microbiome features with clinical states using advanced algorithms, increasing the use of microbiome studies both individually and collectively. Here we discuss tools and strategies for microbiome studies, from primer selection to bioinformatics analysis.