Transcriptional and epigenetic determinants of the epithelial-mesenchymal transition

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Each cell type in every tissue of the body has a unique identity associated with its particular function. Whether the cell type is a stem cell or a neuron, muscle or skin cell, the unique identity of that cell is mainly established by the expression of a unique set of genes. For some cells, however, their identity has considerable flexibility (plasticity) that allows them to change their shape and behavior as they respond to environmental cues. These transitions are normally context-specific, but there is growing evidence for certain commonalities among different cell types undergoing similar changes. A notable example is called the epithelial-to-mesenchymal transition, or EMT. EMT is a phenotypic switch where epithelial cells lose defining characteristics, such as cell polarity and stable cell-to-cell junctions, and transition towards a mesenchymal state, capable of migration and tissue invasion. It is critical for many biological processes including embryo gastrulation, heart development, fibrosis, and wound healing. In addition to increasing a cell's capacity for migration, the molecular program driving the EMT can also activate a stem cell-like phenotype in differentiated epithelial cells. This transition between states is highly dynamic and is orchestrated by complex molecular networks. It is thought that cells undergoing an EMT transition through a continuous trajectory, travelling through intermediate states with varying characteristics and degrees of stability. Beyond hallmark molecular markers of the epithelial or mesenchymal state, relatively little is known about the defining features of these states or the transitions between them. The complexity of the EMT requires an extensive, in-depth analysis if we are to understand its transcriptional and epigenetic determinants, and their kinetics, which is our goal. We plan to start with a simple model system ovarian epithelial cells treated with TGFB1, a factor well-established for its ability to induce the EMT. We aim to explore the relationship between nucleosome organization and transcriptional output using high-throughput genomics, and loss-of-function approaches in both static and dynamic cellular models. In the long-term, by exploring this process in epithelial cells from other tissues and in response to other environmental cues, we hope to discern generalizable regulatory principles that will improve our understanding of how cell state is maintained, and how transitions between states occur. Made publicly accessible, the data will be a major resource for further data mining, to explore mechanisms involved in wound repair and other EMT-mediated cellular processes, to define specific pathways that contribute to the adult stem cell state, and to inform current mathematical models of partial or reversible EMT.