Synthetic biology with its engineering approach, has the potential to transform the ways by which we analyze and manipulate living systems. In the present project, we aim at developing a new class of synthetic gene circuits the fine tuning of which relies on the affinity competition between active and inactive forms of a transcription factor. Modeling, helped by an in silico evolutionary approach, will be used to determine molecular parameters and network topologies required for a given functionality. Circuits will be assembled accordingly and their expression measured in mammalian cells to confirm the expected response or to refine the model. Using this methodology, we plan to build multi-inputs circuits with tunable response function, as well as new bistable and oscillatory circuits. The new investigated class of circuits will also be extended to multi-cellular networks exhibiting symmetry breaking or oscillating patterns. This fundamental project bridging modelling and experimental validation will promote the development of advanced targeting circuits with potential applications in diagnosis, gene therapy and complex tissue engineering.
SynNet Development of a new class of synthetic biology networks based on protein/protein interactions
Résumé
Mots clés
- Biosystems modellingCell-state targetingGenetic oscillatorsSynthetic gene networkTissue patterning
Partenaires du projet
INP
Vincent HAKIM
(UMR8023) Paris, France
INC
Mathieu Morel
Laboratoire PASTEUR
(UMR8640) France