Fluorescence Correlation Spectroscopy with Photobleaching Correction in Slowly Diffusing Systems
Related Experiment Video
Updated: Feb 15, 2026

Measuring Diffusion Coefficients via Two-photon Fluorescence Recovery After Photobleaching
Published on: February 26, 2010
Cameron Hodges1, Rudra P Kafle1,2, J Damon Hoff1
1Department of Biophysics, University of Michigan, 930 N. University Ave., Ann Arbor, MI, 4809-1055, USA.
Abstract:
Fluorescence correlation spectroscopy (FCS) is a powerful tool to quantitatively study the diffusion of fluorescently labeled molecules. It allows in principle important questions of macromolecular transport and supramolecular aggregation in living cells to be addressed. However, the crowded environment inside the cells slows diffusion and limits the reservoir of labeled molecules, causing artifacts that arise especially from photobleaching and limit the utility of FCS in these applications. We present a method to compute the time correlation function from weighted photon arrival times, which compensates computationally during the data analysis for the effect of photobleaching. We demonstrate the performance of this method using numerical simulations and experimental data from model solutions. Using this technique, we obtain correlation functions in which the effect of photobleaching has been removed and in turn recover quantitatively accurate mean-square displacements of the fluorophores, especially when deviations from an ideal Gaussian excitation volume are accounted for by using a reference calibration correlation function. This allows quantitative FCS studies of transport processes in challenging environments with substantial photobleaching like in living cells in the future.
Related Concept Videos
Atomic Fluorescence Spectroscopy
UV–Vis Spectroscopy of Conjugated Systems
One of the factors influencing λmax is the extent of conjugation in...
2D NMR: Homonuclear Correlation Spectroscopy (COSY)
Diffusion
Correlations
Correlation and Causation
Correlation versus Causation
If the dependent variable increases or decreases when the independent variable increases, there is a positive or negative...

