Combining engineering and evolution to create novel metabolic mutualisms between species

Limitation by a shared mutualist promotes coexistence of multiple competing partners

Although mutualisms are often studied as simple pairwise interactions, they typically involve complex networks of interacting species. How multiple mutualistic partners that provide the same service and compete for resources are maintained in mutualistic networks is an open question. We use a model bacterial community in which multiple 'partner strains' of Escherichia coli compete for a carbon source and exchange resources with a 'shared mutualist' strain of Salmonella enterica. In laboratory experiments, competing E. coli strains readily coexist in the presence of S. enterica, despite differences in their competitive abilities. We use ecological modeling to demonstrate that a shared mutualist can create temporary resource niche partitioning by limiting growth rates, even if yield is set by a resource external to a mutualism. This mechanism can extend to maintain multiple competing partner species. Our results improve our understanding of complex mutualistic communities and aid efforts to design stable microbial communities.

Synthetic Symbiosis under Environmental Disturbances

The power of synthetic biology is immense. Will it, however, be able to withstand the environmental pressures once released in the wild. As new technologies aim to do precisely the same, we use a much simpler model to test mathematically the effect of a changing environment on a synthetic biological system. We assume that the system is successful if it maintains proportions close to what we observe in the laboratory. Extreme deviations from the expected equilibrium are possible as the environment changes. Our study provides the conditions and the designer specifications which may need to be incorporated in the synthetic systems if we want such “ecoblocs” to survive in the wild.

By virtue of complex ecologies, the behavior of mutualisms is challenging to study and nearly impossible to predict. However, laboratory engineered mutualistic systems facilitate a better understanding of their bare essentials. On the basis of an abstract theoretical model and a modifiable experimental yeast system, we explore the environmental limits of self-organized cooperation based on the production and use of specific metabolites. We develop and test the assumptions and stability of the theoretical model by leveraging the simplicity of an artificial yeast system as a simple model of mutualism. We examine how one-off, recurring, and permanent changes to an ecological niche affect a cooperative interaction and change the population composition of an engineered mutualistic system. Moreover, we explore how the cellular burden of cooperating influences the stability of mutualism and how environmental changes shape this stability. Our results highlight the fragility of mutualisms and suggest interventions, including those that rely on the use of synthetic biology.

IMPORTANCE The power of synthetic biology is immense. Will it, however, be able to withstand the environmental pressures once released in the wild. As new technologies aim to do precisely the same, we use a much simpler model to test mathematically the effect of a changing environment on a synthetic biological system. We assume that the system is successful if it maintains proportions close to what we observe in the laboratory. Extreme deviations from the expected equilibrium are possible as the environment changes. Our study provides the conditions and the designer specifications which may need to be incorporated in the synthetic systems if we want such “ecoblocs” to survive in the wild.

Parallel Mutations Result in a Wide Range of Cooperation and Community Consequences in a Two-Species Bacterial Consortium

Multi-species microbial communities play a critical role in human health, industry, and waste remediation. Recently, the evolution of synthetic consortia in the laboratory has enabled adaptation to be addressed in the context of interacting species. Using an engineered bacterial consortium, we repeatedly evolved cooperative genotypes and examined both the predictability of evolution and the phenotypes that determine community dynamics. Eight Salmonella enterica serovar Typhimurium strains evolved methionine excretion sufficient to support growth of an Escherichia coli methionine auxotroph, from whom they required excreted growth substrates. Non-synonymous mutations in metA, encoding homoserine trans-succinylase (HTS), were detected in each evolved S. enterica methionine cooperator and were shown to be necessary for cooperative consortia growth. Molecular modeling was used to predict that most of the non-synonymous mutations slightly increase the binding affinity for HTS homodimer formation. Despite this genetic parallelism and trend of increasing protein binding stability, these metA alleles gave rise to a wide range of phenotypic diversity in terms of individual versus group benefit. The cooperators with the highest methionine excretion permitted nearly two-fold faster consortia growth and supported the highest fraction of E. coli, yet also had the slowest individual growth rates compared to less cooperative strains. Thus, although the genetic basis of adaptation was quite similar across independent origins of cooperative phenotypes, quantitative measurements of metabolite production were required to predict either the individual-level growth consequences or how these propagate to community-level behavior.

Adding biotic complexity alters the metabolic benefits of mutualism

Mutualism is ubiquitous in nature and plays an integral role in most communities. To predict the eco-evolutionary dynamics of mutualism it is critical to extend classic pair-wise analysis to include additional species. We investigated the effect of adding a third species to a pair-wise mutualism in a spatially structured environment. We tested the hypotheses that selection for costly excretions in a focal population (i) decreases when an exploiter is added (ii) increases when a third mutualist is added relative to the pair-wise scenario. We assayed the selection acting on Salmonella enterica when it exchanges methionine for carbon in an obligate mutualism with an auxotrophic Escherichia coli. A third bacterium, Methylobacterium extorquens, was then added and acted either as an exploiter of the carbon or third obligate mutualist depending on the nitrogen source. In the tripartite mutualism M. extorquens provided nitrogen to the other species. Contrary to our expectations, adding an exploiter increased selection for methionine excretion in S. enterica. Conversely, selection for cooperation was lower in the tripartite mutualism relative to the pair-wise system. Genome-scale metabolic models helped identify the mechanisms underlying these changes in selection. Our results highlight the utility of connecting metabolic mechanisms and eco-evolutionary dynamics.

Species interactions differ in their genetic robustness

Conflict and cooperation between bacterial species drive the composition and function of microbial communities. Stability of these emergent properties will be influenced by the degree to which species' interactions are robust to genetic perturbations. We use genome-scale metabolic modeling to computationally analyze the impact of genetic changes when Escherichia coli and Salmonella enterica compete, or cooperate. We systematically knocked out in silico each reaction in the metabolic network of E. coli to construct all 2583 mutant stoichiometric models. Then, using a recently developed multi-scale computational framework, we simulated the growth of each mutant E. coli in the presence of S. enterica. The type of interaction between species was set by modulating the initial metabolites present in the environment. We found that the community was most robust to genetic perturbations when the organisms were cooperating. Species ratios were more stable in the cooperative community, and community biomass had equal variance in the two contexts. Additionally, the number of mutations that have a substantial effect is lower when the species cooperate than when they are competing. In contrast, when mutations were added to the S. enterica network the system was more robust when the bacteria were competing. These results highlight the utility of connecting metabolic mechanisms and studies of ecological stability. Cooperation and conflict alter the connection between genetic changes and properties that emerge at higher levels of biological organization.