ImpRes: A robust FRAP framework to quantify fast diffusion of cytoplasmic probes

Diffusion of molecules within live cells is a critical aspect of many biological processes. Fluorescence recovery after photobleaching (FRAP) is widely employed to measure molecular diffusivity using standard laser scanning confocal microscopy (LSCM). However, accurately determining fast cytoplasmic diffusion (on the order of 10 m^2/s) is difficult due to rapid recovery kinetics, low signal-to-noise ratios, post-bleach signal artifacts, and spatial constraints on normalization.

Although individual issues have been tackled in specific scenarios, a straightforward and dependable framework for quantifying cytoplasmic diffusivity is still lacking. In this study, a FRAP methodology is introduced that directly tackles these challenges. Leveraging the Gaussian function, which represents the impulse response of the diffusion equation in an infinite medium, the ImpRes approach utilizes the complete spatiotemporal dataset with a single-equation three-parameter fitting procedure.

This design eliminates the need for small regions of interest and arbitrary initial time-points. The methodology was tested on three datasets of increasing complexity: simulated recovery profiles, in vitro experiments with FITC-dextran in glycerol solution, and live-cell imaging of free cytoplasmic GFP. Comparative analysis with existing models reveals that the ImpRes approach significantly enhances noise and imperfect fluorescence normalization robustness, while remaining resilient to short-term biases such as transient probe photo-activation.

Due to its reliability under realistic conditions and ease of implementation, the proposed FRAP methodology serves as a valuable tool for quantitative cytoplasmic analysis.