The interspecies exchange of metabolites plays a key role in the spatiotemporal dynamics of microbial communities. This raises the question of whether ecosystem-level behavior of structured communities can be predicted using genome-scale metabolic models for multiple organisms. We developed a modeling framework that integrates dynamic flux balance analysis with diffusion on a lattice and applied it to engineered communities. First, we predicted and experimentally confirmed the species ratio to which a two-species mutualistic consortium converges and the equilibrium composition of a newly engineered three-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.

Evolutionary adaptation to a constant environment is often accompanied by specialization and a reduction of fitness in other environments. We assayed the ability of the Lenski Escherichia coli populations to grow on a range of carbon sources after 50,000 generations of adaptation on glucose. Using direct measurements of growth rates, we demonstrated that declines in performance were much less widespread than suggested by previous results from Biolog assays of cellular respiration. Surprisingly, there were many performance increases on a variety of substrates. In addition to the now famous example of citrate, we observed several other novel gains of function for organic acids that the ancestral strain only marginally utilized. Quantitative growth data also showed that strains with a higher mutation rate exhibited significantly more declines, suggesting that most metabolic erosion was driven by mutation accumulation and not by physiological tradeoffs. These reductions in growth by mutator strains were ameliorated by growth at lower temperature, consistent with the hypothesis that this metabolic erosion is largely caused by destabilizing mutations to the associated enzymes. We further hypothesized that reductions in growth rate would be greatest for substrates used most differently from glucose, and we used flux balance analysis to formulate this question quantitatively. To our surprise, we found no significant relationship between decreases in growth and dissimilarity to glucose metabolism. Taken as a whole, these data suggest that in a single resource environment, specialization does not mainly result as an inevitable consequence of adaptive tradeoffs, but rather due to the gradual accumulation of disabling mutations in unused portions of the genome. Adaptation to a single constant environment is commonly expected to result in decreased performance in alternative conditions, or specialization. It has been proposed that, rather than occurring through the neutral accumulation of mutations in unused alternative pathways, this happens because loss of these pathways enhances fitness in the constant environment via “tradeoffs.” We examined growth rates across a variety of nutrients for 12 independent lineages of Escherichia coli that had evolved in the laboratory for decades in a glucose-containing medium. Surprisingly, after 20,000 generations there were actually widespread improvements in the use of alternative nutrients, rather than the expected declines. After 50,000 generations, however, we find that this trend reversed for those populations that evolved a much higher mutation rate. This indicates that high mutation rate, and not adaptive tradeoffs per se (as had been previously proposed), is the primary driver of specialization. These results caution against general assumptions about the importance of adaptive tradeoffs during evolution, and emphasize the key role that newly evolved changes in mutation rate can play in promoting niche specialization.

How do adapting populations navigate the tensions between the costs of gene expression and the benefits of gene products to optimize the levels of many genes at once? Here we combined independently-arising beneficial mutations that altered enzyme levels in the central metabolism of Methylobacterium extorquens to uncover the fitness landscape defined by gene expression levels. We found strong antagonism and sign epistasis between these beneficial mutations. Mutations with the largest individual benefit interacted the most antagonistically with other mutations, a trend we also uncovered through analyses of datasets from other model systems. However, these beneficial mutations interacted multiplicatively (i.e., no epistasis) at the level of enzyme expression. By generating a model that predicts fitness from enzyme levels we could explain the observed sign epistasis as a result of overshooting the optimum defined by a balance between enzyme catalysis benefits and fitness costs. Knowledge of the phenotypic landscape also illuminated that, although the fitness peak was phenotypically far from the ancestral state, it was not genetically distant. Single beneficial mutations jumped straight toward the global optimum rather than being constrained to change the expression phenotypes in the correlated fashion expected by the genetic architecture. Given that adaptation in nature often results from optimizing gene expression, these conclusions can be widely applicable to other organisms and selective conditions. Poor interactions between individually beneficial alleles affecting gene expression may thus compromise the benefit of sex during adaptation and promote genetic differentiation. The pace and outcome of a series of adaptive steps in an evolving lineage depends upon how well different beneficial mutations stack on top of each other. We found that independent beneficial mutations that affected gene expression for a metabolic pathway did not work well together, and were often jointly deleterious. The most beneficial mutations interacted the most poorly with others, which was a trend we found common in other biological systems. Through generating a model that accounted for enzymatic benefits and expression costs, we uncovered that this antagonism was caused by a phenotype to fitness mapping that had an intermediate peak. This allowed us to predict the fitness effect of double mutants and to uncover that the single winning mutations tended to move straight to the peak in a single step. These findings demonstrate the importance of considering the phenotypic changes that cause nonlinear interactions between mutations upon fitness, and thus influence how populations evolve.

Significance: Organisms frequently exchange costly resources with other species. Theory suggests that this paradoxical cooperation between species might have its origins in waste consumption. When a species benefits from the waste of another, the recipient can evolve to aid the waste producer. The waste producer could then be selected to provide costly resources in return. We previously demonstrated the first step of this theorized process: Salmonella enterica evolved to secrete a costly amino acid to increase access to a byproduct generated by Escherichia coli . Here, we provide demonstration of a waste producer switching to costly cooperation. E. coli repeatedly evolved novel secretion of sugar to feed S. enterica . The results validate long-standing theory about the evolutionary origins of costly mutualism.

Contrary to previous understanding, recent evidence indicates that synonymous codon changes may sometimes face strong selection. However, it remains difficult to generalize the nature, strength, and mechanism(s) of such selection. Previously, we showed that synonymous variants of a key enzyme-coding gene (fae) of Methylobacterium extorquens AM1 decreased enzyme production and reduced fitness dramatically. We now show that during laboratory evolution, these variants rapidly regained fitness via parallel yet variant-specific, highly beneficial point mutations in the N-terminal region of fae. These mutations (including four synonymous mutations) had weak but consistently positive impacts on transcript levels, enzyme production, or enzyme activity. However, none of the proposed mechanisms (including internal ribosome pause sites or mRNA structure) predicted the fitness impact of evolved or additional, engineered point mutations. This study shows that synonymous mutations can be fixed through strong positive selection, but the mechanism for their benefit varies depending on the local sequence context.

Horizontal gene transfer plays a crucial role in microbial evolution. While much is known about the mechanisms that determine whether physical DNA can be transferred into a new host, the factors determining the utility of the transferred genes are less clear. We have explored this issue using dichloromethane consumption in Methylobacterium strains. Methylobacterium extorquens DM4 expresses a dichloromethane dehalogenase (DcmA) that has been acquired through horizontal gene transfer and allows the strain to grow on dichloromethane as the sole carbon and energy source. We transferred the dcmA gene into six Methylobacterium strains that include both close and distant evolutionary relatives. The transconjugants varied in their ability to grow on dichloromethane, but their fitness on dichloromethane did not correlate with the phylogeny of the parental strains or with any single tested physiological factor. This work highlights an important limiting factor in horizontal gene transfer, namely, the capacity of the recipient strain to accommodate the stress and metabolic disruption resulting from the acquisition of a new enzyme or pathway. Understanding these limitations may help to rationalize historical examples of horizontal transfer and aid deliberate genetic transfers in biotechnology for metabolic engineering.