Why are some groups of bacteria more diverse than others? We hypothesize that the metabolic energy available to a bacterial functional group (a biogeochemical group or ‘guild’) has a role in such a group’s taxonomic diversity. We tested this hypothesis by looking at the metacommunity diversity of functional groups in multiple biomes. We observed a positive correlation between estimates of a functional group’s diversity and their metabolic energy yield. Moreover, the slope of that relationship was similar in all biomes. These findings could imply the existence of a universal mechanism controlling the diversity of all functional groups in all biomes in the same way. We consider a variety of possible explanations from the classical (environmental variation) to the ‘non-Darwinian’ (a drift barrier effect). Unfortunately, these explanations are not mutually exclusive, and a deeper understanding of the ultimate cause(s) of bacterial diversity will require us to determine if and how the key parameters in population genetics (effective population size, mutation rate, and selective gradients) vary between functional groups and with environmental conditions: this is a difficult task.

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Poor lipid degradation limits low-temperature anaerobic treatment of domestic wastewater even when psychrophiles are used. We combined metagenomics and metaproteomics to find lipolytic bacteria and their potential, and actual, cold-adapted extracellular lipases in anaerobic membrane bioreactors treating domestic wastewater at 4 and 15 °C. Of the 40 recovered putative lipolytic metagenome-assembled genomes (MAGs), only three (Chlorobium, Desulfobacter, and Mycolicibacterium) were common and abundant (relative abundance ≥ 1%) in all reactors. Notably, some MAGs that represented aerobic autotrophs contained lipases. Therefore, we hypothesised that the lipases we found are not always associated with exogenous lipid degradation and can have other roles such as polyhydroxyalkanoates (PHA) accumulation/degradation and interference with the outer membranes of other bacteria. Metaproteomics did not provide sufficient proteome coverage for relatively lower abundant proteins such as lipases though the expression of fadL genes, long-chain fatty acid transporters, was confirmed for four genera (Dechloromonas, Azoarcus, Aeromonas and Sulfurimonas), none of which were recovered as putative lipolytic MAGs. Metaproteomics also confirmed the presence of 15 relatively abundant (≥ 1%) genera in all reactors, of which at least 6 can potentially accumulate lipid/polyhydroxyalkanoates. For most putative lipolytic MAGs, there was no statistically significant correlation between the read abundance and reactor conditions such as temperature, phase (biofilm and bulk liquid), and feed type (treated by ultraviolet light or not). Results obtained by metagenomics and metaproteomics did not confirm each other and extracellular lipases and lipolytic bacteria were not easily identifiable in the anaerobic membrane reactors used in this study. Further work is required to identify the true lipid degraders in these systems.

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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.

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A multi-scale computational model was created for the formation of activated sludge floc structure. The model couples mass balances for substrates and biomass at reactor scale with an individual-based approach for the floc morphology, shape and microcolony development. Among the novel model processes included are the group attachment of micro-flocs to the core structure and the clustering of nitrifiers. Simulation results qualitatively describe the formation of globular colonies of ammonia and nitrite oxidizers in the extracellular polymeric substance produced by heterotrophic microorganisms, as also observed in fluorescence in situ hybridization images. These results are the first step towards a multi-scale model of the activated sludge wastewater treatment systems, which could also be extended to other engineered biological systems.@en