Goyeau, B. | bioRxiv Science

bioRxiv2026

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

Diffusion within the cytoplasm is fundamental to numerous biological processes. Fluorescence recovery after photobleaching (FRAP) is one of the most common method for quantifying molecular diffusivity in living cells using standard laser scanning confocal microscopy (LSCM). However, accurately measuring fast cytoplasmic diffusion (typically >10 m^2/s) is challenging due to rapid recovery kinetics, weak signal-to-noise ratios, post-bleach signal artifacts, and spatial restrictions affecting normalization. While individual challenges have been addressed in specific contexts, a simple and robust framework to quantify cytoplasmic diffusivity remains elusive. Here, we present a FRAP methodology specifically designed to overcome these obstacles. By utilizing the Gaussian function -- the impulse response (ImpRes) of the diffusion equation in an infinite medium -- our approach leverages the full spatiotemporal dataset through a single-equation three-parameter fitting procedure, thus releasing restrictions to small regions of interest and arbitrary initial time-points. The methodology was validated on three datasets of increasing complexity: in silico simulated recovery profiles, in vitro data from FITC-dextran in glycerol solution, and live-cell imaging of free cytoplasmic GFP. Systematic comparison with existing models demonstrates that the ImpRes approach significantly reduces sensitivity to noise and imperfect fluorescence normalization, while remaining robust against short-term biases, such as transient probe photo-activation. Given its robustness under realistic experimental conditions and its ease of implementation, the proposed FRAP methodology provides a reliable tool for quantitative cytoplasmic analysis.

biophysics↗

bioRxiv2025

Cytoplasmic crowding acts as a porous medium reducing macromolecule diffusion

Intracellular transport of macromolecules is crucial for the proper functioning of most cellular processes. Although intracellular crowding is known to strongly alter macromolecule mobility, how cytoplasmic structures physically modulate diffusion remains largely unexplored. Here we investigated the mechanisms by which cytoplasmic crowding controls diffusivity using live-cell experiments and porous media modeling approaches. Confocal microscopy combined with fluorescence recovery after photobleaching (FRAP) and fluorescence correlation spectroscopy (FCS) measurements revealed an anti-correlation between free-GFP diffusivity and the heterogeneous cytoplasmic structure abundance in live mammalian cells. This motivated the development of a multiscale model, where the cytoplasm is treated as a hierarchical porous medium with nanometric and micrometric obstacles. Numerically solving the model allowed us to predict the effective cytoplasmic diffusion coefficient for various obstacle volume fractions, and to identify tortuous and porous hydrodynamic hindrances as key diffusion reduction mechanisms. Comparison with our experimental results highlighted the importance of hydrodynamic interactions between diffusing molecules and nanometric obstacles. Importantly, we found that the effective cytoplasmic diffusivity was not dependent on specific intracellular regions but rather on the local intracellular obstacle volume fraction. Finally, the model was extended to predict the diffusivity of larger macromolecules, showing excellent agreement with literature data for several macromolecules and cell lines. This study provides new insights into the physical mechanisms impeding intracellular diffusion, demonstrating the potential of porous media modeling approaches to predict transport mechanisms in dynamic or heterogeneous intracellular structures, as in cell motility, blebbing, and apoptosis.

biophysics↗