Dynamics in Crowded Environments: Is Non-Gaussian Brownian Diffusion Normal?

The dynamics of colloids and proteins in dense suspensions is of fundamental importance, from a standpoint of understanding the biophysics of proteins in the cytoplasm and for the many interesting physical phenomena in colloidal dispersions. Recent experiments and simulations have raised questions about our understanding of the dynamics of these systems. Experiments on vesicles in nematic fluids and colloids in an actin network have shown that the dynamics of particles can be non-Gaussian; that is, the self-part of the van Hove correlation function, G(s)(r,t), is an exponential rather than Gaussian function of r, in regimes where the mean-square displacement is linear in t. It is usually assumed that a linear mean-square displacement implies a Gaussian G(s)(r,t). In a different result, simulations of a mixture of proteins, aimed at mimicking the cytoplasm of Escherichia coli, have shown that hydrodynamic interactions (HI) play a key role in slowing down the dynamics of proteins in concentrated (relative to dilute) solutions. In this work, we study a simple system, a dilute tracer colloidal particle immersed in a concentrated solution of larger spheres, using simulations with and without HI. The simulations reproduce the non-Gaussian Brownian diffusion of the tracer, implying that this behavior is a general feature of colloidal dynamics and is a consequence of local heterogeneities on intermediate time scales. Although HI results in a lower diffusion constant, G(s)(r,t) is very similar to and without HI, provided they are compared at the same value of the mean-square displacement.