Convolution-based one and two component FRAP analysis: theory and application.

The method of fluorescence redistribution after photobleaching (FRAP) is increasingly receiving interest in biological applications as it is nowadays used not only to determine mobility parameters per se, but to investigate dynamic changes in the concentration or distribution of diffusing molecules. Here, we develop a new simple convolution-based approach to analyze FRAP data using the whole image information. This method does not require information about the timing and localization of the bleaching event but uses the first image acquired directly after photobleaching to calculate the intensity distributions, instead. Changes in pools of molecules with different velocities, which are monitored by applying repetitive FRAP experiments within a single cell, can be analyzed by means of a global model by assuming two global diffusion coefficients with changing portions. We validate the approach by simulation and show that translocation of the YFP-fused PH-domain of phospholipase Cdelta1 can be quantitatively monitored by FRAP analysis in a time-resolved manner. The new FRAP data analysis procedure may be applied to investigate signal transduction pathways using biosensors that change their mobility. An altered mobility in response to the activation of signaling cascades may result either from an altered size of the biosensor, e.g. due to multimerization processes or from translocation of the sensor to an environment with different viscosity.