Understanding how microbes assemble into communities is a fundamental open question in biology, with applications to human health, environmental sustainability, and metabolic engineering. Although it is known that the competition and exchange of nutrients (i.e., metabolic interactions) shape microbial community structure and dynamics, the ability to reliably predict the metabolic interactions and their effect on microbial communities is still being studied. This dissertation investigates how metabolism and environment shape microbial communities through the use of mathematical models, based on linear programming (LP) and mixed integer linear programming (MILP) methods. The first system I studied is a synthetic microbial consortium composed of two species, Cellulomonas fimi and Yarrowia lipolytica, hypothesized to be able to jointly transform cellulose into biofuel precursors. I combined experimental data and flux balance analysis (FBA) to test our capacity to predict metabolic interactions between the two organisms, and explored a proof-of-concept method to monitor the growth dynamics of this coculture. I next explored the possibility of generalizing the design of synthetic communities through the implementation of a computational method that can design division of labor strategies. The algorithm finds consortia of engineered bacterial strains that can survive by exchanging with each other specific nutrients. By distributing functions, microbial consortia can perform tasks that are impossible for individual species to accomplish alone. In addition to highlighting the trade-off between metabolic self-reliance and mutualistic exchange, this approach suggests how division of labor may arise in Escherichia coli monocultures. While mechanistic models are helpful for studying metabolism in microbes and microbial communities, it is interesting to ask whether increasingly cheaper high-throughput phenotypic data, can help achieve similar goals. To address this question, I developed a computational approach to investigate the relationship between growth profiles and microbial species, based on the identification of growth conditions that can best represent the whole dataset. This approach can help engineer microbial communities by identifying microbes that are more likely to engage in cross-feeding, rather than competition, based on their phenotypic profiles. In general, this dissertation demonstrates how different types of metabolic modeling approaches, both mechanism-based and data-driven, can be used to predict metabolic interactions between members of microbial consortia, and to help engineer novel synthetic communities.

This thesis reports the development of BioMe, a co-culture microplate platform that enables high-throughput, real-time quantitative growth dynamics measurements of interacting microbial batch cultures. The primary BioMe components can be 3D-printed, allowing ease of fabrication and DIY accessibility in the microbiome community. A pairwise 3D-printed iteration of the BioMe device was used in diffusion and co-culture experiments. Genetically engineered Escherichia Coli lysine and isoleucine auxotroph strains were used to characterize the diffusion of amino acids across the porous membranes. Results demonstrated a nonlinear relationship between growth rate and pore size and also distinct diffusion behavior for lysine and isoleucine. Pairwise syntrophic co-culture experiments demonstrated synergistic but repressed interaction between these two paired auxotrophs. Investigation of the effect of varying initial amino acid conditions on growth dynamics demonstrated that small changes in initial media condition can consistently affect patterns of yield and growth rate of constituent microbial species. / 2020-08-30T00:00:00Z

Communities are defined as the ensemble of populations that interact with each other and with the environment in a specific time and location. Community ecology studies how communities assemble, what are the patterns of diversity, abundance, and composition of species, and the processes driving these patterns. It includes four basic mechanisms for the assembly of communities: dispersal, drift, selection, and speciation, with each mechanism influencing how the communities change in a different way. Dispersal, the movement of species from one geographical location to another, plays a major role in the recolonization of barren environments and the introduction of new species to established environments. Drift (i.e., random birth and death events within a community) could, theoretically, be negligible in bacterial communities where the high population densities are expected to buffer its effect. Conversely, horizontal gene transfer can be a strong selective force, as horizontally transferred genetic material is a source of functional traits that may provide selective advantages to the recipient cells, especially in environments where strong selection pressure occurs. In my Ph.D. thesis, I aim to examine these three contrasting mechanisms in controlled, simplified bacterial communities that are designed and studied through a synthetic ecology approach. I found that even at low dispersal rates, the species abundance of planktonic bacterial communities can be homogenized by migration. This homogenization can occur even when there are strong variable selection forces interacting in each environment. I also found strong evidence on the importance of stochasticity in communities. Drift can decrease the community similarity by up to 6.3%, and increases the probabilities that species become extinct, especially in the case of rare taxa. In contrast, I found that naturally competent bacteria are favored to uptake more DNA in communities that are highly productive and phylogenetically diverse. This pattern is explained by a potential higher availability of naked DNA for naturally competent bacteria, presumably because there are more cells and the predation systems are more effective. Altogether, our findings support the theory on the importance of stochastic forces and their interaction with deterministic forces on the shaping of microbial community assembly.

Microbes live in complex environments where competitive and cooperative interactions occur that dictate their success and the status of their environment. By furthering our understanding of the interactions between microbes, questions into the evolution of cooperation, disease virulence and biodiversity can be addressed. This will help develop strategies to overcome problems concerning disease, socioeconomics and conservation. We use an approach that combines evolutionary ecology theory with genetics and molecular biology to establish and develop model microbial ecological systems to examine feeding strategies, in what has been termed synthetic ecology. Using the model fungal plant pathogen system of rice blast disease, we generated less virulent gene deletion mutants to examine the sociality of feeding strategies during infection and test a nascent virulence reduction strategy based on competitive exclusion. We revealed that the success of the pathogen is unexpectedly enhanced in mixed strain infections containing the virulent wild-type strain with a less virulent gene deletion mutant of the metabolic enzyme invertase. Our finding is explained by interference between different social traits that occur during sucrose feeding. To test the generality of our result, gene deletion mutants of putative proteases were generated and characterised. We found that if virulence related genes acted ‘privately’, as predicted by social theory, the associated mutants would not make viable strains to use for this virulence reduction strategy by competitive exclusion. Our study then went on to study the fitness of digesting resources extracellularly, as many microbes do, given that this strategy is exposed to social exploitation by individuals who do not pay the metabolic costs. This was investigated by developing an experimental system with Saccharomyces cerevisiae. Though internalising digestion could suppress cheats, the relative fitness of opposing strategies was dependent upon the environmental and demographic conditions. Using this polymorphic system, the influence of competitors on the stability of cooperation, and the influence of cheats on the maintenance of diversity were assessed. To test the fitness of internal versus external digestion in a more natural setting, we generated an internally digesting strain of the rice blast fungus. In addition to suppressing cheats, the strain had enhanced fitness and virulence over the wild-type. We propose that this is caused by a shift in a trade-off between yield and rate. We show how a synthetic ecology approach can capture details of the biology underlying complex ecological processes, while having control over the factors that drive them, so that the underlying mechanisms can be teased apart.