Deciphering signalling pathway dynamics during cell-fate commitment in stem cells

Description du projet

Perturbations des signaux extracellulaires et devenir des cellules souches

La différenciation cellulaire en cellules matures présentant une forme et une fonction spécialisées est guidée par des signaux extracellulaires spécifiques. Il s’agit d'un processus d’une grande complexité qui est régulé sur le plan spatio-temporel. Financé par le Conseil européen de la recherche, le projet i-SignalTrace cherche à prédire les voies de signalisation qui sont activées dans les cellules souches lorsque ces derniers sont soumis à différents signaux extracellulaires. Les chercheurs auront recours à la technologie d’édition génétique CRISPR/Cas9 pour lever le voile sur les mécanismes d’engagement du devenir cellulaire et comprendre l’influence d’un éventail de perturbations sur les cellules souches. Ces travaux devraient générer des connaissances fondamentales sur la biologie du développement et améliorer les protocoles de médecine régénérative des thérapies cellulaires.

Objectif

Understanding the identity and intensity of the specific extracellular signals that a cell experiences at different times during its differentiation is essential to develop advanced cellular therapies. However, uncovering the sequence of these signaling events, their intensities, timing, and relevance in development and disease is proving to be very challenging.

Here, I propose to build i-SignalTrace: a CRISPR/Cas9-based molecular recorder with the capacity to store both lineage information and signalling pathway activity for multiple signals over time in single cells. By performing kinetic experiments and mathematical modeling, I will use i-SignalTrace to extract the probability of signalling pathways to be activated in stem cells when subject to different extracellular signals and reconstruct the lineage tree of pathway activities during differentiation with single-cell resolution. In combination with single-cell RNA sequencing, i-SignalTrace will make it possible to characterize transition and intermediate states along differentiation trajectories, and quantify the integration between extracellular signals and autonomous programs of gene expression. These results will allow predicting the differentiation trajectories that stem cells follow when subject to external perturbations, and deciphering the role of heterogeneity in signalling pathway activity during cell-fate commitment.

Using i-SignalTrace, I will identify missing or redundant signalling pathways induced during in vitro differentiation protocols. Therefore, I expect that exploitation of i-SignalTrace will allow establishing new criteria to design protocols to differentiate stem cells on demand. As a proof-of-concept, I propose a framework to improve the functionality of monolayer-derived cardiomyocytes. Taken together, i- SignalTrace will find applications in both fundamental developmental biology and translational regenerative medicine, which will benefit a much wider scientific community.