Resolving Fast, Confined Diffusion in Bacteria with Image Correlation Spectroscopy.

By following single fluorescent molecules in a microscope, single-particle tracking (SPT) can measure diffusion and binding on the nanometer and millisecond scales. Still, although SPT can at its limits characterize the fastest biomolecules as they interact with subcellular environments, this measurement may require advanced illumination techniques such as stroboscopic illumination. Here, we address the challenge of measuring fast subcellular motion by instead analyzing single-molecule data with spatiotemporal image correlation spectroscopy (STICS) with a focus on measurements of confined motion. Our SPT and STICS analysis of simulations of the fast diffusion of confined molecules shows that image blur affects both STICS and SPT, and we find biased diffusion rate measurements for STICS analysis in the limits of fast diffusion and tight confinement due to fitting STICS correlation functions to a Gaussian approximation. However, we determine that with STICS, it is possible to correctly interpret the motion that blurs single-molecule images without advanced illumination techniques or fast cameras. In particular, we present a method to overcome the bias due to image blur by properly estimating the width of the correlation function by directly calculating the correlation function variance instead of using the typical Gaussian fitting procedure. Our simulation results are validated by applying the STICS method to experimental measurements of fast, confined motion: we measure the diffusion of cytosolic mMaple3 in living Escherichia coli cells at 25 frames/s under continuous illumination to illustrate the utility of STICS in an experimental parameter regime for which in-frame motion prevents SPT and tight confinement of fast diffusion precludes stroboscopic illumination. Overall, our application of STICS to freely diffusing cytosolic protein in small cells extends the utility of single-molecule experiments to the regime of fast confined diffusion without requiring advanced microscopy techniques.

Top-hat and asymmetric Gaussian-based fitting functions for quantifying directional single-molecule motion.

Single-molecule fluorescence permits super-resolution imaging, but traditional algorithms for localizing these isolated fluorescent emitters assume stationary point light sources. Proposed here are two fitting functions that achieve similar nanometer-scale localization precision as the traditional symmetric Gaussian function, while allowing, and explicitly accounting for, directed motion. The precision of these methods is investigated through Fisher information analysis, simulation and experiments, and the new fitting functions are then used to measure, for the first time, the instantaneous velocity and direction of motion of live bacteria cells. These new methods increase the information content of single-molecule images of fast-moving molecules without sacrificing localization precision, thus permitting slower imaging speeds, and our new fitting functions promise to improve tracking algorithms by calculating velocity and direction during each image acquisition.