Quantitative FRAP in Analysis of Molecular Binding Dynamics In Vivo
Introduction
Fluorescence recovery after photobleaching (FRAP) is now widely used to study protein mobility in living cells. FRAP is performed by photobleaching fluorescent molecules at a specified location in a cell, and then monitoring the rate at which the bleached molecules are replaced by unbleached ones. The rate of recovery reflects the rate of movement of the fluorescently tagged molecules at that location within the cell.
Molecular mobilities as obtained from FRAP are informative for several reasons. First, they can provide information about the rates of cellular diffusion in different subcellular compartments. Indeed, most of the early FRAP studies focused on the diffusion of proteins and lipids within membranes (Edidin 1994, Liebman 1974, Poo 1974).
Second, molecular mobilities often reveal that apparently static structures within cells are actually constructed from highly dynamic protein constituents. FRAP uncovers this hidden flux by selectively marking a subset of molecules, and so discloses the exchange of proteins or other molecules that occur within and between cellular compartments even when the system is at equilibrium (Misteli 2001, Webb 2003).
Third, molecular mobilities can also be used for the measurement of cellular binding interactions. FRAP of different green fluorescent protein (GFP)‐fusion proteins will sometimes reveal that their mobilities are considerably slower than expected for a purely diffusing molecule of that size, or even for a large molecular complex. This often indicates retardation of the protein's mobility by cellular binding interactions. Since stronger interactions will retard mobilities more than weaker interactions, the FRAP curve can be used to estimate the strengths of in vivo molecular binding interactions (Sprague and McNally, 2005).
This chapter focuses on how to extract quantitative information about molecular binding interactions from the FRAP data.
Section snippets
Rationale
Most estimates of protein binding affinity have been performed in vitro. This typically involves isolating the protein and its binding target, incubating the binding partners under appropriate conditions, and then measuring binding affinities by one of several established techniques, such as surface plasmon resonance, calorimetry, capillary electrophoresis, or filter binding assays (He 2004, Leavitt 2001, Riggs 1970, Schuck 1997).
How close are these in vitro affinity measurements to in vivo
Methods
There are two principal steps in using FRAP to extract in vivo estimates of binding parameters: data acquisition and data analysis.
Materials
In addition to both a confocal microscope and cells expressing GFP and the GFP‐fusion protein, software is also required for the quantitative analysis of FRAP data. Image‐analysis software is needed for averaging image intensities within the bleach spot. Often these routines are available with the confocal microscope software. If not, the same procedures can be performed in virtually any image‐analysis package, such as ImageJ. The resultant quantitative data can be imported into a spreadsheet
Utility of Parameters Estimated by the Models
Correct fitting of experimental FRAP data provides estimates for the association and dissociation rates of binding, and . These numbers can be compared to in vitro estimates of binding as a way to judge if in vitro biochemistry has accurately captured what is transpiring in vivo. However, in comparing in vivo and in vitro estimates, it is important to realize that the association rate, , measured by FRAP is actually the product of the molecular on rate times the concentration of
Summary
Described herein is a method for acquiring FRAP data, followed by a step‐by‐step procedure for fitting the data to a series of increasingly complex mathematical models. Successful application of this procedure will yield estimates of the in vivo association and dissociation binding rates for the GFP‐tagged protein under study. The protein is presumed to bind to an immobilized substrate that is uniformly distributed throughout a cellular compartment, and diffusion within the compartment is
Acknowledgments
I thank Waltraud Müller and Tim Stasevich for comments on the manuscript, and Brian Sprague for suggesting the original format for Fig. 2. I also thank Florian Müller for help with the derivations of the diffusion‐uncoupled FRAPs and for comments on the manuscript.
References (38)
- et al.
Translational diffusion of globular proteins in the cytoplasm of cultured muscle cells
Biophys. J.
(2000) - et al.
Dissecting the contribution of diffusion and interactions to the mobility of nuclear proteins
Biophys. J.
(2006) - et al.
Characterizing fluorescence recovery curves for nuclear proteins undergoing binding events
Bull. Math. Biol.
(2004) - et al.
The DNA binding activity of p53 displays reaction‐diffusion kinetics
Biophys. J.
(2006) - et al.
A biological approach to computational models of proteomic networks
Curr. Opin. Chem. Biol.
(2006) - et al.
Quantification of transport and binding parameters using fluorescence recovery after photobleaching. Potential for in vivo applications
Biophys. J.
(1990) - et al.
Direct measurement of protein binding energetics by isothermal titration calorimetry
Curr. Opin. Struct. Biol.
(2001) - et al.
Rapid periodic binding and displacement of the glucocorticoid receptor during chromatin remodeling
Mol. Cell
(2004) - et al.
Quantitative analysis of the glucocorticoid receptor‐DNA interaction at the mouse mammary tumor virus glucocorticoid response element
J. Biol. Chem.
(1990) - et al.
Lac repressor‐operator interaction. I. Equilibrium studies
J. Mol. Biol.
(1970)
Anomalous subdiffusion in fluorescence photobleaching recovery: A Monte Carlo study
Biophys. J.
Theoretical analysis of fluorescence photobleaching recovery experiments
Biophys. J.
FRAP analysis of binding: Proper and fitting
Trends Cell Biol.
Analysis of binding at a single spatially localized cluster of binding sites by fluorescence recovery after photobleaching
Biophys. J.
Analysis of binding reactions by fluorescence recovery after photobleaching
Biophys. J.
Photobleaching recovery and anisotropy decay of green fluorescent protein GFP‐S65T in solution and cells: Cytoplasmic viscosity probed by green fluorescent protein translational and rotational diffusion
Biophys. J.
Illuminating adhesion complexes in migrating cells: Moving toward a bright future
Curr. Opin. Cell. Biol.
Anomalous subdiffusion is a measure for cytoplasmic crowding in living cells
Biophys. J.
MAP kinase phosphatase as a locus of flexibility in a mitogen‐activated protein kinase signaling network
Science
Cited by (96)
Beyond analytic solution: Analysis of FRAP experiments by spatial simulation of the forward problem
2023, Biophysical JournalSpatial resolution of virus replication: RSV and cytoplasmic inclusion bodies
2023, Advances in Virus ResearchVisualizing sphingolipid biosynthesis in cells
2019, Chemistry and Physics of LipidsCharacterization of Cell Boundary and Confocal Effects Improves Quantitative FRAP Analysis
2018, Biophysical JournalSurface charge and overlayer pH influence the dynamics of supported phospholipid films
2018, Journal of Electroanalytical Chemistry