METABOLIC MODELING OF BIOFILM COMMUNITIES FOR BIOTECHNOLOGICAL APPLICATIONS

Interacting microbial consortia are of keen interest for developing new biotechnological applications. While most efforts to engineer microbial consortia have focused on well-mixed, planktonic systems, naturally occurring microorganisms usually exist in multispecies biofilms encapsulated in self-produced extracellular polymer matrix. Efficient, large-scale conversion of plant-derived feedstocks to useful commodity chemicals remains a substantial technological challenge with enormous potential for societal benefits. Engineered biofilm consortia have the potential to solve important biotechnological problems that have proved difficult for monoculture biofilms and planktonic consortia. Considerable experimental progress has been reported for engineering and characterizing biofilm consortia but the parallel development of computational tools for simulation, design and optimization of stable, robust and productive designed consortia has been lacking. In this work, I demonstrate how metabolic modeling can be used for in silico design and optimization of biofilm systems for various applications. The developed biofilm metabolic modeling framework combines genome-scale metabolic reconstructions of individual bacteria, species-specific uptake kinetics for supplied nutrients and crossfed metabolites, and reaction-diffusion equations for extracellular metabolites to generate spatially-resolved predictions of species and extracellular metabolites. The modeling approach was first applied to the design of two-strain biofilm communities to demonstrate the value of incorporating a secondary, acetate-consuming bacterium to detoxify the environment and relieve acetate-induced growth inhibition of a primary bacterium. The first system consisted of a wild-type Escherichia coli strain combined with a mutant E. coli strain engineered to eliminate glucose metabolism and allow aerobic acetate uptake. Coculture biofilm model results were consistent with measurements generated by my experimental collaborators for enhanced biomass accumulation compared to a wild-type E. coli monoculture biofilm. The second system was computationally designed to convert glucose to isobutanol, an important platform chemical used as an oxygenated gasoline component and as an industrial solvent. Coculture biofilms consisting of an E. coli strain engineered for microaerobic isobutanol synthesis and a wild-type Geobacter metallireducens strain for anaerobic acetate consumption were predicted to generate higher isobutanol titers than the E. coli monoculture biofilms. A key bottleneck to the development of productive and robust synthetic communities is the difficulty in identifying compatible microbial strains and favorable culture conditions. I also utilized the biofilm modeling framework to investigate four system design based on combining bacterial strains with complementary metabolic functions as alternatives for the conversion of cellobiose to isobutanol. Each alternative system design consisted of an anaerobic cellulolytic bacterium which degraded cellobiose to glucose, an aerobic E. coli strain engineered for glucose-to-isobutanol conversion, and an aerobic or anaerobic byproduct consumer for metabolizing growth-inhibiting organic acids such as acetate secreted by the other two strains. The simulations predicted different cellobiose-to-isobutanol conversion capabilities depending on the metabolic compatibility of the three bacteria. I also extended the modeling approach to study necro-mass catabolism in a two-strain biofilm system. Here, the two-strain consortium was designed to have a primary specialist, cellulolytic anaerobe Clostridium phytofermentans and secondary resource specialist, E. coli. The model provided qualitative agreement with experimentally observed behavior of species interactions and biomass enhancement due to mutualistic relationship between the species and necro-mass catabolism. Through this work I generated several general design principles and I believe that these principles will be widely applicable for the design of productive and robust synthetic biofilm communities that will be translatable to other bioconversion problems