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Examining Self-directed Multicellular Organization and Morphogenesis of Human Induced Pluripotent Stem Cells

Abstract

Embryonic morphogenesis is a critical determinant of tissue generation and function, yet many of the mechanisms that regulate morphogenic processes remain elusive due to the complex and dynamic nature of multicellular interactions and the limited tools to manipulate these systems at single cell resolution. Similarly, morphogenesis of human induced pluripotent stem-cell (hiPSC) derived organoids proceeds largely through self-organized pattern formation that crudely mimics organogenesis. The ability to control specific morphogenic processes would greatly enhance our ability to create bona vide human tissue and organ structures; however, robustly directing organoid morphogenesis requires development of novel control approaches. The four studies described in this dissertation developed systems to study pattern emergence and lineage fate specifications in hiPSC 2D and 3D cultures. First, the effects of mechanical regulation on population emergence and lineage fate specification was interrogated by mosaic knockdown of two mechanical regulators associated with cortical tension and cell-cell adhesion: Rho-associated kinase-1 (ROCK1) and E-cadherin (CDH1). Mosaic knockdown induced symmetry breaking (a pre-requisite of morphogenesis), which resulted in differential patterns of cell sorting and multicellular organization without disrupting pluripotency state. These results describe the spatiotemporal dynamics of multicellular self-organization that occur with the emergence of heterotypic cell populations within pluripotency allowing for population segregation before lineage fate commitment. Second, using machine learning, experimental parameters were optimized to yield pre-specified spatial patterns before successful validation in vitro with hiPSCs. Furthermore, asymmetric pre-patterning of iPSCs differentially impacted initial germ layer specification within differentiating colonies. This study demonstrated demonstrate that parameter optimization achieved by automated machine learning could be used to efficiently predict and control hiPSC self-organization. Third, the regulation of CDH1 on organization and lineage fate was examined in 3D gastruloid cultures, where both microenvironment and CDH1 knockdown triggered the emergence of extra embryonic lineages. This study indicated that microenvironment is essential for specific lineage emergence in the early embryo. Fourth in the final study, population emergence was examined in neuronal organoid cultures that displayed axial extensions similar to neural tube formation and extension. Extending aggregates were dependent on the emergence of a neuromesodermal progenitor population alongside neuronal populations. This model of neural tube extension provides a platform to probe how disruption of population emergence affects morphological phenotypes. Overall, these studies provided avenues to elucidate the underlaying multicellular interactions that enable the development of complex patterning events within the developing human embryo on multiple scales and across multiple developmental periods.

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