Environmental microbiology is undergoing a dramatic revolution due to the increasing accumulation of biological information and contextual environmen

Marine microbial communities have been essential contributors to global biomass, nutrient cycling, and biodiversity since the early history of Earth, but so far their community distribution patterns remain unknown in most marine ecosystems. The synthesis of 9.6 million bacterial V6-rRNA amplicons for 509 samples that span the global ocean's surface to the deep-sea floor shows that pelagic and benthic communities greatly differ, at all taxonomic levels, and share <10% bacterial types defined at 3% sequence similarity level. Surface and deep water, coastal and open ocean, and anoxic and oxic ecosystems host distinct communities that reflect productivity, land influences and other environmental constraints such as oxygen availability. The high variability of bacterial community composition specific to vent and coastal ecosystems reflects the heterogeneity and dynamic nature of these habitats. Both pelagic and benthic bacterial community distributions correlate with surface water productivity, reflecting the coupling between both realms by particle export. Also, differences in physical mixing may play a fundamental role in the distribution patterns of marine bacteria, as benthic communities showed a higher dissimilarity with increasing distance than pelagic communities. This first synthesis of global bacterial distribution across different ecosystems of the World's oceans shows remarkable horizontal and vertical large-scale patterns in bacterial communities. This opens interesting perspectives for the definition of biogeographical biomes for bacteria of ocean waters and the seabed.

The bacterial species definition, despite its eminent practical significance for identification, diagnosis, quarantine and diversity surveys, remains a very difficult issue to advance. Genomics now offers novel insights into intra-species diversity and the potential for emergence of a more soundly based system. Although we share the excitement, we argue that it is premature for a universal change to the definition because current knowledge is based on too few phylogenetic groups and too few samples of natural populations. Our analysis of five important bacterial groups suggests, however, that more stringent standards for species may be justifiable when a solid understanding of gene content and ecological distinctiveness becomes available. Our analysis also reveals what is actually encompassed in a species according to the current standards, in terms of whole-genome sequence and gene-content diversity, and shows that this does not correspond to coherent clusters for the environmental Burkholderia and Shewanella genera examined. In contrast, the obligatory pathogens, which have a very restricted ecological niche, do exhibit clusters. Therefore, the idea of biologically meaningful clusters of diversity that applies to most eukaryotes may not be universally applicable in the microbial world, or if such clusters exist, they may be found at different levels of distinction.

The application of multivariate statistical analyses has become a consistent feature in microbial ecology. However, many microbial ecologists are still in the process of developing a deep understanding of these methods and appreciating their limitations. As a consequence, staying abreast of progress and debate in this arena poses an additional challenge to many microbial ecologists. To address these issues, we present the GUide to STatistical Analysis in Microbial Ecology (GUSTA ME): a dynamic, web-based resource providing accessible descriptions of numerous multivariate techniques relevant to microbial ecologists. A combination of interactive elements allows users to discover and navigate between methods relevant to their needs and examine how they have been used by others in the field. We have designed GUSTA ME to become a community-led and -curated service, which we hope will provide a common reference and forum to discuss and disseminate analytical techniques relevant to the microbial ecology community.

Spatial distance (SD) and environmental heterogeneity (EH) are currently thought to represent major factors shaping genetic variation and population abundance, but their relative importance is still poorly understood. Because EH varies at multiple spatial scales, so too are microbial variables expected to vary. The determination of SD × EH interactions at multiple scales is, however, not a trivial exercise, especially when one examines their effects on microbial abundance and genomic similarities. Here we assessed those interactions at all scales perceptible in a patchy environment composed of known plant species and of heterogeneous soil physical and chemical parameters. For free-living, soil-borne Burkholderia ambifaria , genomic similarities responded to most of the spatial scales that the experimental sampling scheme could reveal, despite limited dispersal of the individuals. Species abundance and community composition were, however, responding to much smaller scales more consistent with local responses to EH. Our results suggest that whole-genome similarities may reflect the simultaneous effects of both SD and EH in microbial populations, but the pure effects of each factor only contributed to <2% of the total genetic variation. The large amount of unexplained variation that remains after considering most environmental, spatial, and biological interactions is then posited to be the result of noise introduced by unmeasured environmental and spatial variability, sampling effects, and neutral ecological drift.

Little information is available regarding the landscape-scale distribution of microbial communities and its environmental determinants. However, a landscape perspective is needed to understand the relative importance of local and regional factors and land management for the microbial communities and the ecosystem services they provide. In the most comprehensive analysis of spatial patterns of microbial communities to date, we investigated the distribution of functional microbial communities involved in N-cycling and of the total bacterial and crenarchaeal communities over 107 sites in Burgundy, a 31 500 km² region of France, using a 16 × 16 km² sampling grid. At each sampling site, the abundance of total bacteria, crenarchaea, nitrate reducers, denitrifiers- and ammonia oxidizers were estimated by quantitative PCR and 42 soil physico-chemical properties were measured. The relative contributions of land use, spatial distance, climatic conditions, time, and soil physico-chemical properties to the spatial distribution of the different communities were analyzed by canonical variation partitioning. Our results indicate that 43–85% of the spatial variation in community abundances could be explained by the measured environmental parameters, with soil chemical properties (mostly pH) being the main driver. We found spatial autocorrelation up to 739 km and used geostatistical modelling to generate predictive maps of the distribution of microbial communities at the landscape scale. The present study highlights the potential of a spatially explicit approach for microbial ecology to identify the overarching factors driving the spatial heterogeneity of microbial communities even at the landscape scale.