Summary The inter-species exchange of metabolites plays a key role in the spatio-temporal dynamics of microbial communities. This raises the question whether ecosystem-level behavior of structured communities can be predicted using genome-scale models of metabolism for multiple organisms. We developed a modeling framework that integrates dynamic flux balance analysis with diffusion on a lattice, and applied it to engineered consortia. First, we predicted, and experimentally confirmed, the species-ratio to which a 2-species mutualistic consortium converges, and the equilibrium composition of a newly engineered 3-member community. We next identified a specific spatial arrangement of colonies, which gives rise to what we term the “eclipse dilemma”: does a competitor placed between a colony and its cross-feeding partner benefit or hurt growth of the original colony? Our experimentally validated finding, that the net outcome is beneficial, highlights the complex nature of metabolic interactions in microbial communities, while at the same time demonstrating their predictability.

Wolbachia are maternally inherited bacteria that commonly spread through host populations by causing cytoplasmic incompatibility, often expressed as reduced egg hatch when uninfected females mate with infected males. Infected females are frequently less fecund as a consequence of Wolbachia infection. However, theory predicts that because of maternal transmission, these “parasites” will tend to evolve towards a more mutualistic association with their hosts. Drosophila simulans in California provided the classic case of a Wolbachia infection spreading in nature. Cytoplasmic incompatibility allowed the infection to spread through individual populations within a few years and from southern to northern California (more than 700 km) within a decade, despite reducing the fecundity of infected females by 15%–20% under laboratory conditions. Here we show that the Wolbachia in California D. simulans have changed over the last 20 y so that infected females now exhibit an average 10% fecundity advantage over uninfected females in the laboratory. Our data suggest smaller but qualitatively similar changes in relative fecundity in nature and demonstrate that fecundity-increasing Wolbachia variants are currently polymorphic in natural populations.

(1) there is preexisting reciprocation or feedback for cooperation, and (2) reciprocation is preferentially received by cooperative genotypes. I used a two species system involving Salmonella enterica ser. Typhimurium and an Escherichia coli mutant unable to synthesize an essential amino acid. In lactose media Salmonella consumes metabolic waste from E. coli, thus creating a mechanism of reciprocation for cooperation. Growth in a spatially structured environment assured that the benefits of cooperation were preferentially received by cooperative genotypes. Salmonella evolved to aid E. coli by excreting a costly amino acid, however this novel cooperation disappeared if the waste consumption or spatial structure were removed. This study builds on previous work to demonstrate an experimental origin of interspecific cooperation, and to test the factors necessary for such interactions to arise. K E Y W O R D S : Consortia, cross-feeding, E. coli, Salmonella, spatial structure.

Despite broad scientific interest in harnessing the power of Earth's microbiomes, knowledge gaps hinder their efficient use for addressing urgent societal and environmental challenges. We argue that structuring research and technology developments around a design-build-test-learn (DBTL) cycle will advance microbiome engineering and spur new discoveries on the basic scientific principles governing microbiome function. In this Review, we present key elements of an iterative DBTL cycle for microbiome engineering, focusing on generalizable approaches, including top-down and bottom-up design processes, synthetic and self-assembled construction methods, and emerging tools to analyze microbiome function. These approaches can be used to NRMICRO-19-067V3 2 harness microbiomes for broad applications related to medicine, agriculture, energy, and the environment. We also discuss key challenges and opportunities of each approach and synthesize them into best practice guidelines for engineering microbiomes. We anticipate that adoption of a DBTL framework will rapidly advance microbiome-based biotechnologies aimed at improving human and animal health, agriculture, and enabling the bioeconomy.

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Ecological opportunities promote population divergence into coexisting lineages. However, the genetic mechanisms that enable new lineages to exploit these opportunities are poorly understood except in cases of single mutations. We examined how two Escherichia coli lineages diverged from their common ancestor at the outset of a long-term coexistence. By sequencing genomes and reconstructing the genetic history of one lineage, we showed that three mutations together were sufficient to produce the frequency-dependent fitness effects that allowed this lineage to invade and stably coexist with the other. These mutations all affected regulatory genes and collectively caused substantial metabolic changes. Moreover, the particular derived alleles were critical for the initial divergence and invasion, indicating that the establishment of this polymorphism depended on specific epistatic interactions.

Evolution by natural selection is fundamentally shaped by the fitness landscapes in which it occurs. Yet fitness landscapes are vast and complex, and thus we know relatively little about the long-range constraints they impose on evolutionary dynamics. Here, we exhaustively survey the structural landscapes of RNA molecules of lengths 12 to 18 nucleotides, and develop a network model to describe the relationship between sequence and structure. We find that phenotype abundance—the number of genotypes producing a particular phenotype—varies in a predictable manner and critically influences evolutionary dynamics. A study of naturally occurring functional RNA molecules using a new structural statistic suggests that these molecules are biased toward abundant phenotypes. This supports an “ascent of the abundant” hypothesis, in which evolution yields abundant phenotypes even when they are not the most fit.

By consuming and producing environmental resources, organisms inevitably change their habitat. The consequences of such environmental modifications can be detrimental or beneficial not only to the focal organism but also to other organisms sharing the same environment. Social evolution theory has been very influential in studying how social interactions mediated by public goods or bads evolve by emphasising the role of spatial structure. The environmental dimensions driving these interactions, however, are typically abstracted away. Here we propose a new, environmentally-mediated taxonomy of social behaviours where organisms are categorised by their production or consumption of environmental factors that help or harm others in the environment. We discuss microbial examples of our classification and highlight the importance of environmental intermediates more generally.