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ACTIPOP

Actin polymers in the cellular cortex: a population dynamics approach

Project leaders: Amandine Véber (MAP5, CNRS & Paris Cité U.) and François Robin (IBPS, Inserm & Sorbonne U.)

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Project funded by the French National Research Agency (ANR)

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Objectives

  • Model and understand, qualitatively and quantitatively, the dynamics of cortical actin seen as one (or several) population(s) of individuals competing for the capture of free monomers and interacting with various accessory proteins.

  • Important elements to integrate: stochasticity of the components of this dynamic; spatial structuring of actin; environment fluctuating in time and space.

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This project furthers the PhD work of Anne Van Gorp-Lanvin (defended in 2022) “Multi-scale modelling of the intra-cellular actin dynamics” in several research directions. This PhD was co-supervised by A. Véber and F. Robin.

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Main directions of the project

  • Use pre-existing models and code to understand the assembly of actin polymer networks modulated by Arp-2/3 proteins on the one hand, and by formins on the other hand.

  • Explore the short- and long-range impact of the spatial structure of actin networks on their local and global dynamics.

  • Build new models that are amenable to mathematical analysis and incorporate the key elements of the individual growth-fragmentation dynamics and a fine description of the interactions between polymers in their fluctuating and/or inhomogeneous environment.

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Project members

  • Amandine Véber (MAP5, UPCité), project leader on the maths side - mathematical modelling and analysis

  • François Robin (IBPS, Sorbonne U.), project leader on the biology side - theorical and experimental approaches in developmental biology

  • Flora Llense (IBPS, Sorbonne U.), genetics and fluorescence microscopy

  • Teresa Ferraro (IBPS, Sorbonne U.), single molecule microscopy

  • Lea Popovic (Concordia University, Montréal), mathematical modelling and analysis

  • Sébastien Billes (March-August 2024, Sorbonne U. PhD programme student), bioinformatics and programming

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References

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