Heterogeneous Diffusion in Living Cells

Abstract

In this thesis, to deal with a spatiotemporal heterogeneity in living cells, we develop a novel analysis technique, namely cluster analysis for single particle time-series, and apply the methodology to a single-particle tracking experiment in vivo. The experiment was performed to reveal the intracellular transport mechanism of purinosomes. A majority of purinosomes interact with both microtubule and mitochondria networks, showing subdiffusive mean squared displacement. But they can probabilistically be transported along microtubule branches in a ballistic manner. To understand the physical mechanism underlying the anti-correlation at short time scales, two models are suggested: fractional Brownian motion with diffusing diffusivity and Brownian motion in periodic potential field. The former explains the anti-correlation in terms of self-similar noise caused by the crowded network environment and the latter describes the colocalization phenomena as obstructed states arisen by uneven potential field. Meanwhile, a small portion of particles undergoing the ballistic motion show power-law probability density function of displacement and superdiffusive mean squared displacement. The dynamics is modeled by a 2-state continuous-time Markov chain in which subdiffusive and ballistic phases alternate. In addition, if we introduce angle persistence to the ballistic states, two point correlation function fits better to the experiment, which suggests the direction of the ballistic states has a positive temporal correlation at the short time regime.