Synthetic gene sensors and effectors to redirect organoid development

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Project Summary Human induced pluripotent stem cell (hiPSC)-derived organoids hold great promise for tissue engineering and personalized drug screening, but obtaining the desired multicellular organization and function from these systems is usually performed in an ad hoc fashion without forward design specification. Recently, we reported successful liver bud formation containing stromal cells, vascular tube-like structures and hematopoiesis-like processes by synthetically inducing diversity in GATA6 expression from a single hiPSC population. This accomplishment suggests that expanding circuit logic operations to artificially control differentiation drivers at particular bifurcations in lineage specification could profoundly impact the complexity and functionality of organoids. In this project, we bring together mathematical modeling, machine learning, optimization, and innovative synthetic biology techniques to elucidate and design fundamental decision and communication rules for guiding cells into complex, heterogeneous tissues. Our overarching hypothesis is that appropriate timing and predictable stochastic control of the expression of intracellular and extracellular factors is critical for redirecting lineage choices in order to elicit desired multicellular organization from a population of differentiating cells. We will develop synthetic tools for sensing differentiation stages of iPSC-derived organoids and construct and characterize a stochastic commitment switch in an inducible reporter system. These tools will be integrated in synthetic gene circuits for engineering emergent multicellular organization through stochastic temporal control of developmental factors. The modular commitment switches developed in this project will be capable of exploring how the degree of subpopulation biasing of cell fate decisions and level of cell fate synchronization at bipotent differentiation stages impacts self-assembly and emergent multicellular organization of an organoid. Our aims - executed through a closed loop of computational and experimental investigations - will shed insight on how generalizable methods of controlled manipulation can elicit desired organoid-level emergent properties.