CellPath

How do cells transition from one identity to another? Are these transitions progressive, or rather sharp? How do transition states compare between natural and induced reprogramming? Addressing these challenging questions requires comprehensive descriptions of cell states, and their mapping to cell fate. Here we propose to examine transition states during neuronal direct reprogramming in the transcriptomic space. We will use 2 in vivo integrated, physiological models, each one with their unique advantages. Since the cellular lineage of all cells is known in C. elegans, it allows us to interrogate natural direct reprogramming at the unique cell level with direct mapping of individual states to cell fate. This unmatched ability to isolate the same defined cell from all animals also bypasses the inherent heterogeneity associated with multiple identical cells purified from a tissue. Such heterogeneity adds noise to the cellular trajectories reconstituted from single cell omics and precludes a clear picture of the transition states between 2 identities. Finally, with its fast development the worm allows to follow the process minute per minute and pre-screen actionable targets to improve reprogramming strategies. In addition, we will use an in vivo TF-based induced neuronal reprogramming system, in an integrated epilepsy mice model. This will allow us not only to assess the reprogramming trajectory but also its ability to generate functional neurons. By comparing reprogramming trajectories in these 2 systems we will highlight shared principles and identify candidates factors to improve direct reprogramming. To this aim, we will develop novel full-length RNA-seq approaches, and use high-end computational pipelines in order to model gene regulation, with a particular focus on the architecture of transcription factors networks underlining the observed cellular transitions. Ultimately, we will assess in vivo which critical network nodes allow us to manipulate cell identity.