Interchanging species of similar function: Under natural conditions, bacteria form mixed, interacting communities. Understanding how such communities assemble and stabilize is important in a range of contexts, from biotechnological applications to what happens in our guts. Goldford et al. sampled the microbial communities from soil and plants containing hundreds to thousands of sequence variants. The organisms were passaged after culture in low concentrations of single carbon sources and were cross-fed with each other's metabolites; then, the resulting communities were sequenced using 16S ribosomal RNA, and the outcomes were modeled mathematically. The mix of species that survived under steady conditions converged reproducibly to reflect the experimentally imposed conditions rather than the mix of species initially inoculated—although at coarse phylogenetic levels, taxonomic patterns persisted. Science , this issue p. 469

Understanding the link between community composition and function is a major challenge in microbial population biology, with implications for the management of natural microbiomes and the design of synthetic consortia. Specifically, it is poorly understood whether community functions can be quantitatively predicted from traits of species in monoculture. Inspired by the study of complex genetic interactions, we have examined how the amylolytic rate of combinatorial assemblages of six starch-degrading soil bacteria depend on the separate functional contributions from each species and their interactions. Filtering our results through the theory of biochemical kinetics, we show that this simple function is additive in the absence of interactions among community members. For about half of the combinatorially assembled consortia, the amylolytic function is dominated by pairwise and higher-order interactions. For the other half, the function is additive despite the presence of strong competitive interactions. We explain the mechanistic basis of these findings and propose a quantitative framework that allows us to separate the effect of behavioral and population dynamics interactions. Our results suggest that the functional robustness of a consortium to pairwise and higher-order interactions critically affects our ability to predict and bottom-up engineer ecosystem function in complex communities.

A major open question in microbial community ecology is whether we can predict how the components of a diet collectively determine the taxonomic composition of microbial communities. Motivated by this challenge, we investigate whether communities assembled in pairs of nutrients can be predicted from those assembled in every single nutrient alone. We find that although the null, naturally additive model generally predicts well the family-level community composition, there exist systematic deviations from the additive predictions that reflect generic patterns of nutrient dominance at the family level. Pairs of more-similar nutrients (e.g. two sugars) are on average more additive than pairs of more dissimilar nutrients (one sugar–one organic acid). Furthermore, sugar–acid communities are generally more similar to the sugar than the acid community, which may be explained by family-level asymmetries in nutrient benefits. Overall, our results suggest that regularities in how nutrients interact may help predict community responses to dietary changes.

Significance: In the microbial world, it is common for previously isolated communities to come in contact with one another. This phenomenon is known as community coalescence. Despite it being a key process in the assembly of microbial communities, little is known about the mechanisms that determine its outcomes. Here we present an experimental system that allowed us to study over 100 coalescence events between previously segregated microbiomes. Our results, predicted by a mathematical model, provide direct evidence of ecological coselection: the situation where members of a community recruit one another during coalescence. Our combined experimental and theoretical framework represents a powerful tool to predict the outcomes and interrogate the mechanisms of community coalescence.

Permeable vesicles containing the proto-ring anchoring ZipA protein shrink when FtsZ, the main cell division protein, polymerizes in the presence of GTP. Shrinkage, resembling the constriction of the cytoplasmic membrane, occurs at ZipA densities higher than those found in the cell and is modulated by the dynamics of the FtsZ polymer. In vivo, an excess of ZipA generates multilayered membrane inclusions within the cytoplasm and causes the loss of the membrane function as a permeability barrier. Overproduction of ZipA at levels that block septation is accompanied by the displacement of FtsZ and two additional division proteins, FtsA and FtsN, from potential septation sites to clusters that colocalize with ZipA near the membrane. The results show that elementary constriction events mediated by defined elements involved in cell division can be evidenced both in bacteria and in vesicles.

The yeast Snf1 kinase and its mammalian ortholog, AMP-activated protein kinase (AMPK), regulate responses to metabolic stress. Previous studies identified a glycogen-binding domain in the AMPK β1 subunit, and the sequence is conserved in the Snf1 kinase β subunits Gal83 and Sip2. Here we use genetic analysis to assess the role of this domain in vivo. Alteration of Gal83 at residues that are important for glycogen binding of AMPK β1 abolished glycogen binding in vitro and caused diverse phenotypes in vivo. Various Snf1/Gal83-dependent processes were upregulated, including glycogen accumulation, expression of RNAs encoding glycogen synthase, haploid invasive growth, the transcriptional activator function of Sip4, and activation of the carbon source-responsive promoter element. Moreover, the glycogen-binding domain mutations conferred transcriptional regulatory phenotypes even in the absence of glycogen, as determined by analysis of a mutant strain lacking glycogen synthase. Thus, mutation of the glycogen-binding domain of Gal83 positively affects Snf1/Gal83 kinase function by a mechanism that is independent of glycogen binding.