Subventions et des contributions :

Subvention ou bourse octroyée s'appliquant à plus d'un exercice financier. (2017-2018 à 2018-2019)

Each cell type in every tissue of the body has a unique identity associated with its particular function. Whether it is a stem cell, neuron, muscle or skin cell, its unique identity is 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 the epithelial-to-mesenchymal transition, or EMT.

EMT is a phenotypic switch where epithelial cells lose their defining characteristics and transition towards a mesenchymal state capable of migration and tissue invasion, and gaining a resemblance to stem cells. EMT is critical for many biological processes including embryo gastrulation, heart development, fibrosis, and wound healing. This transition between states is highly dynamic and is orchestrated by complex molecular networks thought to shift cells 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 TGFβ1, a factor well-established for its ability to induce the EMT. We will 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, exploring this process in epithelial cells from other tissues and in response to other EMT-inducing cues will allow us 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.