Kejia Chen

Single-Molecule Observation of Long Jumps in Polymer Adsorption

Single-molecule fluorescence imaging of adsorption onto initially bare surfaces shows that polymer chains need not localize immediately after arrival. In a system optimized to present limited adsorption sites (quartz surface to which polyethylene glycol (PEG) chains adsorb from aqueous solution at pH 8.2), we find that some chains diffuse back into bulk solution and readsorb at some distance away, sometimes multiple times before they either localize at a stable position or diffuse away into bulk solution. This mechanism of surface diffusion is considerably more rapid than the classical model in which adsorbed polymers crawl on surfaces while the entire molecule remains adsorbed, suggesting the conceptual generality of a recent report ( Phys. Rev. Lett. 2013 , 110 , 256101 ) but in a new experimental system and with comparison of different chain lengths. We find the trajectories with jumps to follow a truncated Lévy distribution of step size with limiting slope -2.5, consistent with a well-defined, rapid surface diffusion coefficient over the times we observe. The broad waiting time distribution appears to reflect that polymer chains possess a broad distribution of bound fraction: the smaller the bound fraction of a given chain, the shorter the surface residence time before executing the next surface jump.

Diagnosing heterogeneous dynamics in single-molecule/particle trajectories with multiscale wavelets.

We describe a simple automated method to extract and quantify transient heterogeneous dynamical changes from large data sets generated in single-molecule/particle tracking experiments. Based on wavelet transform, the method transforms raw data to locally match dynamics of interest. This is accomplished using statistically adaptive universal thresholding, whose advantage is to avoid a single arbitrary threshold that might conceal individual variability across populations. How to implement this multiscale method is described, focusing on local confined diffusion separated by transient transport periods or hopping events, with three specific examples: in cell biology, biotechnology, and glassy colloid dynamics. The discussion is generalized within the framework of continuous time random walk. This computationally efficient method can run routinely on hundreds of millions of data points analyzed within an hour on a desktop personal computer.

Extending Particle Tracking Capability with Delaunay Triangulation

Particle tracking, the analysis of individual moving elements in time series of microscopic images, enables burgeoning new applications, but there is need to better resolve conformation and dynamics. Here we describe the advantages of Delaunay triangulation to extend the capabilities of particle tracking in three areas: (1) discriminating irregularly shaped objects, which allows one to track items other than point features; (2) combining time and space to better connect missing frames in trajectories; and (3) identifying shape backbone. To demonstrate the method, specific examples are given, involving analyzing the time-dependent molecular conformations of actin filaments and λ-DNA. The main limitation of this method, shared by all other clustering techniques, is the difficulty to separate objects when they are very close. This can be mitigated by inspecting locally to remove edges that are longer than their neighbors and also edges that link two objects, using methods described here, so that the combination of Delaunay triangulation with edge removal can be robustly applied to processing large data sets. As common software packages, both commercial and open source, can construct Delaunay triangulation on command, the methods described in this paper are both computationally efficient and easy to implement.