title: Correlating anomalous diffusion with lipid bilayer membrane structure using single molecule tracking and atomic force microscopy.
abstract: Anomalous diffusion has been observed abundantly in the plasma membrane of biological cells, but the underlying mechanisms are still unclear. In general, it has not been possible to directly image the obstacles to diffusion in membranes, which are thought to be skeleton bound proteins, protein aggregates, and lipid domains, so the dynamics of diffusing particles is used to deduce the obstacle characteristics. We present a supported lipid bilayer system in which we characterized the anomalous diffusion of lipid molecules using single molecule tracking, while at the same time imaging the obstacles to diffusion with atomic force microscopy. To explain our experimental results, we performed lattice Monte Carlo simulations of tracer diffusion in the presence of the experimentally determined obstacle configurations. We correlate the observed anomalous diffusion with obstacle area fraction, fractal dimension, and correlation length. To accurately measure an anomalous diffusion exponent, we derived an expression to account for the time-averaging inherent to all single molecule tracking experiments. We show that the length of the single molecule trajectories is critical to the determination of the anomalous diffusion exponent. We further discuss our results in the context of confinement models and the generating stochastic process.
authors.affiliation: Department of Chemical Engineering and Materials Science, University of California Davis, Davis, California 95616, USA.
authors.forename: Michael J
authors.initials: MJ
authors.lastname: Skaug
authors.forename: Roland
authors.initials: R
authors.lastname: Faller
authors.forename: Marjorie L
authors.initials: ML
authors.lastname: Longo
mesh_terms: D002462:Cell Membrane / Q000648:ultrastructure*; D003198:Computer Simulation; D004058:Diffusion; D008051:Lipid Bilayers / Q000737:chemistry*; D018625:Microscopy, Atomic Force / Q000379:methods*; D008954:Models, Biological; D015233:Models, Statistical; D009010:Monte Carlo Method; D011506:Proteins / Q000032:analysis
chemical_list: D008051:Lipid Bilayers; D011506:Proteins