Nonequilibrium statistical physics applied to biophysical cellular processes

Abstract

The methods of statistical physics are increasingly being employed in a range of interdisciplinary areas. In particular, aspects of complex biological processes have been elucidated by bringing the problems down to the level of simple interactions studied in a statistical sense. In nonequilibrium statistical physics, a one dimensional lattice model known as the totally asymmetric simple exclusion processes (TASEP) has become prominent as a tool for modelling various cellular transport processes. Indeed the context in which the TASEP was first introduced (MacDonald et. al., 1968) was to model ribosome motion along mRNA during protein synthesis. In this work I study a variation of the TASEP in which particles hop along a one dimensional lattice which extends as they reach the end. We introduce this model to describe the unique growth dynamics of filamentous fungi, whereby a narrow fungal filament extends purely from its tip region while being supplied with growth materials from behind the tip. We find that the steady state behaviour of our model reflects that of the TASEP, however there is an additional phase where a dynamic shock is present in the system. I show through Monte Carlo simulation and theoretical analysis that the qualitative behaviour of this model can be predicted with a simple mean-field approximation, while the details of the phase behaviour are accurate only in a refined approximation which takes into account some correlations. I also discuss a further refined mean-field approximation and give a heuristic argument for our results. Next I present an extension of the model which allows the particles to interact with a second lattice, on which they diffuse in either direction. A first order meanfield continuum approximation suggests that the steady states of this system will exhibit some novel behaviour. Through Monte Carlo simulation I discuss the qualitative changes that arise due to the on-off dynamics. Finally I study a model for a second biological phenomenon: the length fluctuations of microtubules. The model describes stochastic polymerisation events at the tip of a microtubule. Using a mean-field theory, we find a transition between regimes where the microtubule grows on average, and where the length remains finite. For low rates of polymerisation and depolymerisation, the transition is in good agreement with Monte Carlo simulation.