Abstract
AbstractFluorescence Recovery After Photobleaching (FRAP) is an important tool used by cell biologists to study the diffusion and binding kinetics of vesicles, proteins, and other molecules in the cytoplasm, nucleus or cell membrane. While many FRAP models have been developed over the past decades, the influence of the complex boundaries of three-dimensional cellular geometries on the recovery curves, in conjunction with ROI and optical effects (imaging, photobleaching, photoswitching, and scanning), has not been well studied. Here, we developed a three-dimensional computational model of the FRAP process that incorporates particle diffusion, cell boundary effects, and the optical properties of the scanning confocal microscope, and validated this model using the tip-growing cells ofPhyscomitrella patens. We then show how these cell boundary and optical effects confound the interpretation of FRAP recovery curves, including the number of dynamic states of a given fluorescent protein, in a wide range of cellular geometries-both in two and three dimensions-namely nuclei, filopodia, and lamellipodia of mammalian cells, and in cell types such as the budding yeast,S. pombe, and tip-growing plant cells. We explored the performance of existing analytical and algorithmic FRAP models in these various cellular geometries, and determined that the VCell VirtualFRAP tool provides the best accuracy to measure diffusion coefficients. Our computational model is not limited only to these cells types, but can easily be extended to other cellular geometries via the graphical Java-based application we also provide. This particle-based simulation-called the Digital Confocal Microscopy Suite, DCMS-can also perform fluorescence dynamics assays, such as Number and Brightness (N&B), Fluorescence Correlation Spectroscopy (FCS), Raster Image Correlation Spectroscopy (RICS), and could help shape the way these techniques are interpreted.
Publisher
Cold Spring Harbor Laboratory