Inferring diffusion, reaction, and exchange parameters from imperfect FRAP.

Area of Science:

• Cell biology
• Biophysics
• Biochemistry

Background:

• Fluorescence recovery after photobleaching (FRAP) is a key technique for studying molecular dynamics and diffusion coefficients in biological systems.
• Accurate kinetic parameter inference from FRAP data is challenging due to experimental noise, coupled molecular processes, and uncontrolled initial bleaching profiles.

Purpose of the Study:

• To develop a robust method, HiFRAP, for quantifying reaction- (or exchange-) diffusion kinetic parameters from FRAP experiments under imperfect conditions.
• To provide a versatile tool for analyzing molecular dynamics that overcomes limitations of existing FRAP analysis methods.

Main Methods:

• HiFRAP utilizes a low-rank approximation of a kernel related to the model Green's function.
• Implemented as an ImageJ/Python macro, it supports one-dimensional and two-dimensional systems, including those with curved geometries.
• The method does not require prior knowledge of the initial bleaching profile and accounts for optical setup limitations.

Main Results:

• HiFRAP successfully quantifies kinetic parameters from FRAP experiments without assumptions on the initial bleach profile.
• The approach accounts for diffraction limitations and provides error estimations for parameter inference.
• It enables the inference of multiple kinetic parameters from a single experimental run and includes model goodness-of-fit testing.

Conclusions:

• HiFRAP offers a comprehensive solution for analyzing molecular dynamics from FRAP data, even under challenging experimental conditions.
• The method's ability to infer multiple parameters and provide error estimates enhances the reliability of molecular dynamics studies.
• The underlying approach has potential applications beyond FRAP for analyzing other dynamical processes described by linear partial differential equations.