Resolving Fast, Confined Diffusion in Bacteria with Image Correlation Spectroscopy

Abstract

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 singlemolecule experiments to the regime of fast confined diffusion without requiring advanced microscopy techniques.

Measuring molecular motions inside single cells with improved analysis of single-particle trajectories

“…Fluorescence correlation spectroscopy (FCS) and the related methods of spatiotemporal image correlation spectroscopy (STICS), raster image correlation spectroscopy (RICS), or particle image correlation spectroscopy (PICS) can also quantify diffusion; these approaches all employ spatial or temporal correlation functions which can also be fit to multicomponent diffusion models, [28][29][30][31][32] but it is rare for the signal-to-noise to be high enough for the analysis of complex heterogeneous motion such as are found in bacterial systems. [33] The ability of single-particle tracking to isolate high quality trajectories from noisy single molecule data can present a more attractive conduit for analysis.…”

Two essential replicative DNA polymerases exchange dynamically during DNA replication and after replication fork arrest

“…If DnaE had such a role, we would expect the DnaE localization data to have been very similar to what we observe for PolC.We applied spatiotemporal image correlation spectroscopy (STICS) to our DnaE-PAmCherry data to quantify the DnaE dynamics in the absence of measurable singlemolecule trajectories(Fig. 2B); this analysis uses image correlation instead of tracking information to calculate the average diffusion coefficient in a cell(31,32). STICS calculated a very rapid average DnaE-PAmCherry diffusion coefficient, DDnaE,avg = 1.9 ± 0.2 μm 2 /s (Fig.…”

“…Spatiotemporal image correlation spectroscopy (STICS). We identified the individual cell outlines with a code for cell segmentation (20), and then quantified the diffusion coefficients of molecules moving too fast to track with spatiotemporal image correlation spectroscopy (STICS) (31,32). STICS computes the correlation function of an entire fluorescence-imaging movie instead of using localization and tracking information, so it can resolve the dynamics of very fast diffusion that precludes fitting.…”

Adaptive optics microspectrometer for cross-correlation measurement of microfluidic flows

“…The increase of the efficiency of the nonlinear excitation obtained by the optical aberrations correction, the accuracy in the laser spot positioning, and the use of no movable parts make our setup particularly suited to characterize flows in complex vessel networks, 57,58 in confined environments, 59 or in vivo 8 by means of cross-correlation methods. For these applications, it is essential to be able to select the observation volumes on an image collected with the same setting of the optical setup, particularly for low brightness and signal/noise ratio samples.…”