Modelling bacterial flagellar growth

Abstract

The growth of bacterial flagellar filaments is a self-assembly process where flagellin molecules are transported through the narrow core of the flagellum and are added at the distal end. To model this situation, we generalize a growth process based on the TASEP model by allowing particles to move both forward and backward on the lattice. The bias in the forward and backward jump rates determines the lattice tip speed, which we analyze and also compare to simulations. For positive bias, the system is in a non-equilibrium steady state and exhibits boundary-induced phase transitions. The tip speed is constant. In the no-bias case we find that the length of the lattice grows as $N(t)\propto \sqrt{t}$, whereas for negative drift $N(t)\propto \ln t$. The latter result agrees with experimental data of bacterial flagellar growth.

6 pages, 7 figures

References in corpus (4)

• Phase Coexistence in Driven One Dimensional Transport
• A model of hyphal tip growth involving microtubule-based transport
• A dynamically extending exclusion process
• Dynamic Boundaries in Asymmetric Exclusion Processes

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