Sommaire:

Living cells rely heavily on cytoskeletal transport as an efficient way of delivering vesicles and biochemically active cargos within the cytoplasm for cell viability and function regulation. Non-equilibrium stochastic motion of molecular machines such as motor proteins on cytoskeletal filaments plays a fundamental role in intracellular and intercellular traffic and cytoplasm dynamical organization, whereas perturbations of these functions are known to lead to diseases.
Recent progresses in experimental techniques are giving access to a wealth of data down to the single-molecule level in-cellulo, and models are becoming increasingly important in order to interpret these data and understand general mechanisms.
One approach to obtain fundamental insights into collective mechanisms and provide predictions for experimental situations is to use non-equilibrium statistical mechanics transport models.
Building on our recent work on one of the most paradigmatic lattice gas models, the “Totally Asymmetric Simple Exclusion Process” (TASEP), we generalize TASEP on networks of increasing complexity: from complex junctions up to large random networks that better mimic the cytoskeleton complexity in cells.
We provide here a general theoretical framework supported by simulations, numerical and analytical results, to acquire a throughout understanding of collective stochastic transport of motor proteins on simple and complex topologies, with emergent properties, dependent on the network connectivity, which could be observed in experiments.
Last but not least, the understanding of non-linear transport processes on complex networks inspired by this study can provide hints of great interest also for fundamental and applied sciences not necessarily related to the biological realm.

Pour plus d'informations, merci de contacter Dorignac J.