RT Journal Article
SR Electronic
T1 Computationally-efficient spatiotemporal correlation analysis super-resolves anomalous diffusion
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 2020.12.26.424447
DO 10.1101/2020.12.26.424447
A1 Shawn Yoshida
A1 William Schmid
A1 Nam Vo
A1 William Calabrase
A1 Lydia Kisley
YR 2020
UL http://biorxiv.org/content/early/2020/12/27/2020.12.26.424447.abstract
AB Anomalous diffusion dynamics in confined nanoenvironments govern the macroscale properties and interactions of many biophysical and material systems. Currently, it is difficult to quantitatively link the nanoscale structure of porous media to anomalous diffusion within them. Fluorescence correlation spectroscopy super-resolution optical fluctuation imaging (fcsSOFI) has been shown to extract nanoscale structure and Brownian diffusion dynamics within gels, liquid crystals, and polymers, but has limitations which hinder its wider application to more diverse, biophysically-relevant datasets. Here, we parallelize the least-squares curve fitting step on a GPU improving computation times by up to a factor of 40, implement anomalous diffusion and two-component Brownian diffusion models, and make fcsSOFI more accessible by packaging it in a user-friendly GUI. We apply fcsSOFI to simulations of the protein fibrinogen diffusing in polyacrylamide of varying matrix densities and super-resolve locations where slower, anomalous diffusion occurs within smaller, confined pores. The improvements to fcsSOFI in speed, scope, and usability will allow for the wider adoption of super-resolution correlation analysis to diverse research topics.Competing Interest StatementThe authors have declared no competing interest.