Summary
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.
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.
Unfold all
/
Fold all
More information & hyperlinks
| Web resources: | https://cordis.europa.eu/project/id/101042634 |
| Start date: | 01-03-2023 |
| End date: | 29-02-2028 |
| Total budget - Public funding: | 1 500 000,00 Euro - 1 500 000,00 Euro |
Cordis data
Original description
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.
Status
SIGNEDCall topic
ERC-2021-STGUpdate Date
09-02-2023
Images
No images available.
Geographical location(s)
