The importance of microbial communities (MCs) cannot be overstated. MCs underpin the biogeochemical cycles of the earth's soil, oceans and the atmosphere, and perform ecosystem functions that impact plants, animals and humans. Yet our ability to predict and manage the function of these highly complex, dynamically changing communities is limited. Building predictive models that link MC composition to function is a key emerging challenge in microbial ecology. Here, we argue that addressing this challenge requires close coordination of experimental data collection and method development with mathematical model building. We discuss specific examples where model–experiment integration has already resulted in important insights into MC function and structure. We also highlight key research questions that still demand better integration of experiments and models. We argue that such integration is needed to achieve significant progress in our understanding of MC dynamics and function, and we make specific practical suggestions as to how this could be achieved.

Microorganisms in wastewater treatment plants (WWTPs) are essential for water purification to protect public and environmental health. However, their diversity and the factors that control it are poorly understood. Using a systematic global-sampling effort, we analyzed the 16S rRNA gene sequences from ~1,200 activated sludge samples taken from 269 WWTPs in 23 countries on 6 continents. Our analyses revealed that the global activated sludge bacterial communities contain ~1 billion bacterial phylotypes with a Poisson lognormal diversity distribution. Despite this high diversity, activated sludge has a small global core bacterial community (n = 28 OTUs) that is strongly linked to activated sludge performance. Meta-analyses with global datasets associate the activated sludge microbiomes most closely to freshwater populations. In contrast to macroorganism diversity, activated sludge bacterial communities show no latitudinal gradient. Furthermore, their spatial turnover is scale-dependent and appears to be largely driven by stochastic processes (dispersal, drift), although deterministic factors (temperature, organic input) also are important. Our findings enhance mechanistic understanding of the global diversity and biogeography of activated sludge bacterial communities within a theoretical ecology framework and have important implications for microbial ecology and wastewater treatment processes.

EBI metagenomics (http://www.ebi.ac.uk/metagenomics) provides a free to use platform for the analysis and archiving of sequence data derived from the microbial populations found in a particular environment. Over the past two years, EBI metagenomics has increased the number of datasets analysed 10-fold. In addition to increased throughput, the underlying analysis pipeline has been overhauled to include both new or updated tools and reference databases. Of particular note is a new workflow for taxonomic assignments that has been extended to include assignments based on both the large and small subunit RNA marker genes and to encompass all cellular micro-organisms. We also describe the addition of metagenomic assembly as a new analysis service. Our pilot studies have produced over 2400 assemblies from datasets in the public domain. From these assemblies, we have produced a searchable, non-redundant protein database of over 50 million sequences. To provide improved access to the data stored within the resource, we have developed a programmatic interface that provides access to the analysis results and associated sample metadata. Finally, we have integrated the results of a series of statistical analyses that provide estimations of diversity and sample comparisons.

Simple beaker experiments established that light damages fecal coliforms in waste stabilization ponds by an oxygen-mediated exogenous photosensitization. Wavelengths of up to 700 nm were able to damage bacteria. The ability of wavelengths of >425 nm to damage fecal coliforms was dependent on the presence of dissolved sensitizers. The sensitizers were ubiquitous in raw sewage, unaffected by sewage treatment, not derivatives of bacteriochlorophyll or chlorophyll, absorbed well in UV light, and had a slight yellowish color; they are therefore believed to be humic substances. The ability of light to damage fecal coliforms was highly sensitive to, and completely dependent on, oxygen. Scavengers of H202 and singlet oxygen could protect the bacteria from the effects of sunlight, but scavengers of hydroxyl radicals and superoxides could not. Light-mediated damage of fecal coliforms was highly sensitive to elevated pH values, which also enabled light with wavelengths of >425 nm (in the presence of the sensitizer) to damage the bacteria. We conclude that humic substances, pH, and dissolved oxygen are important variables in the process by which light damages microorganisms in this and other environments and that these variables should be considered in future research on, and models of, the effects of light.