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The human genome, the genetic blueprint that every cell in our body follows, encodes approximately 20,000 genes. Through complex regulation of these genes, each cell is able to play the role it needs within our body. Synthetic biology, an emerging field in biology, seeks to expand on this blueprint and create cells with novel functions. The aim of this thesis is to provide methods that expands our ability to engineer and control multicellular systems by detecting and rewriting the cell state.
We first develop a method that enables the creation of a synthetic cell state to control morphogenesis. Using inducible expression of recombinases, we show this approach can induce a cell to commit to one of two mutually exclusive cell states. By regulating the expression of recombinases, we are able to control the distribution of cell states within an initially monoclonal and homogenous population of cells. We use the induction of a synthetic cell state to control morphogenesis by cell state-specific expression of homotypic cadherins which controls the cell’s adhesive properties. This enables us to create a large number of different shapes and control morphogenesis.
Secondly, we develop a library-based approach for cell state-specific gene regulation. We design a set of 6,107 Synthetic Promoters with Enhanced Cell-State Specificity (SPECS), and identify several SPECS with spatiotemporal specificity during the programmed differentiation of stem cells, as well as SPECS that are highly specific for breast cancer and glioblastoma stem-like cells.
Thirdly, we develop a method that allows detection of endogenous gene expression without modifying the endogenous gene itself. We show that placing a regulatory RNA downstream of a terminator allows for expression of the regulatory RNA, and demonstrate this method for miRNAs and gRNAs.
Together, this thesis develops methods to create synthetic cell states that can be used to control morphogenesis, and provides tools to detect endogenous cell states which can serve as inputs to control gene regulatory networks. |
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