Biomechanical Regulation of Microbial Self-Organization in Confined Environments

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Title: Biomechanical regulation of microbial self-organization in confined environments Inside hosts, microbes grow under spatial constraints and frequently become so crowded that mechanical stresses influence their behavior. For example, within humans, microbes often form fine-structured aggregates in cavities on teeth, skin follicles, or crypt-like structures in the colon, which are increasingly recognized as an important factor influencing human health. Although new layers of mechanical regulation of collective microbial growth and motion have emerged in recent years, we know little about how such regulation influences the self- organization of microbial communities. The main challenges are to experimentally monitor and theoretically model the feedback between forces and growth at the same time and across multiple scales. The objective of the proposed research is to quantify and model the direct and indirect feedback between growth and mechanical forces in order to explain and predict the self-organization of dense cellular populations. To this end, the P.I. proposes microfluidic and lineage tracking experiments spanning cellular to community-level scales, as well as extrapolating simulations and theory. The proposed research leverages the intense dialog between theory and experiment cultivated in his laboratory to achieve a predictive understanding of self- organization in microbial populations in terms of the joint actions of individual cells. The P.I. has two specific aims. First, he will identify and characterize physiological adaptations that enable microbial populations to sustain large mechanical stresses and cell shape deformations. Understanding such direct feedback between forces and growth will illuminate the role of forces in the pathogenic invasion of hosts, which is a key step for virulence. Second, he will elucidate how dense microbial populations establish in tight micro-environments, how they fend off invaders, turn over and adapt. Answering these questions will inform strategies to promote or perturb a resilient microbial ecosystem in the gut or other crowded environments. The proposed work develops state-of-the-art microfluidic techniques that enable automated spatio-temporal tracking of cells and a novel strategy to track evolutionary processes, under defined mechanical boundary conditions. The simulations developed synthesize modern population genetic theory with feature-rich biophysical simulations and bridge the gap in spatio-temporal scales between laboratory experiments and natural populations. The planned novel microfluidic devices and computer simulations will be of broad utility to the biophysics community for the goal of dissecting collective properties of microbial populations. 1