Intitulé du projet
Spatial dynamics of prion diseases in the central nervous system
Nature du financement
ANR
État du projet
Accepté
Année de soumission
2026
Programme / appel + année
ANR JCJC 2026
Equipe(s) impliquée(s) dans le projet
BioSys
Dynenvie
StatInfOmics
Coordinateur·trice (nom et prénom)
Mezache Mathieu
Rôle de MaIAGE dans le projet
Coordinateur.trice
Nom(s) du(des) participant(s) - MaIAGE
M. Mezache (responsable), K. Adamczyk, G. Kon Kam King
Nom(s) du(des) partenaire(s) (nom, labo et localisation) - Hors MaIAGE
F. Hubert, P. Pudlo Aix-Marseille Université, A. Igel, H. Rezaei VIM Inrae
Date de début du projet
Date de fin du projet
Résumé
The PrionSpace project aims to study the multiscale mechanisms governing prion dissemination and its impact on neuronal network function. The central scientific questions addressed in this project are: (1) How do antagonistic catalytic mechanisms that govern prion assembly at a molecular level translate into strain-specific spatial dissemination patterns within brain tissue ? (2) How do tissue anisotropy, neuronal activity, and stress responses regulate prion replication dynamics ? (3) How do these physical and biochemical processes lead to functional degradation of the neural network ?
To answer these questions, PrionSpace integrates mathematical modeling, statistical inference, and experimental validation. It will develop a multi-scale modelling framework coupling growth–fragmentation kinetics with reaction–diffusion equations in order to describe prion dissemination in neural tissue. Simulation-Based Inference (SBI) methods will be designed to infer key parameters from experimental data and quantify uncertainties. Finally, electrophysiological data from prion-infected organotypic slices will be used to link aggregate distribution to network-level dysfunction.
To answer these questions, PrionSpace integrates mathematical modeling, statistical inference, and experimental validation. It will develop a multi-scale modelling framework coupling growth–fragmentation kinetics with reaction–diffusion equations in order to describe prion dissemination in neural tissue. Simulation-Based Inference (SBI) methods will be designed to infer key parameters from experimental data and quantify uncertainties. Finally, electrophysiological data from prion-infected organotypic slices will be used to link aggregate distribution to network-level dysfunction.
Champ thématique du contrat (MathNum)
Grand objectif concerné - principal - (MathNum)
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