Minchul Kang

A Generalization of Theory for Two-Dimensional Fluorescence Recovery after Photobleaching Applicable to Confocal Laser Scanning Microscopes

Fluorescence recovery after photobleaching (FRAP) using confocal laser scanning microscopes (confocal FRAP) has become a valuable technique for studying the diffusion of biomolecules in cells. However, two-dimensional confocal FRAP sometimes yields results that vary with experimental setups, such as different bleaching protocols and bleaching spot sizes. In addition, when confocal FRAP is used to measure diffusion coefficients (D) for fast diffusing molecules, it often yields D-values that are one or two orders-of-magnitude smaller than that predicted theoretically or measured by alternative methods such as fluorescence correlation spectroscopy. Recently, it was demonstrated that this underestimation of D can be corrected by taking diffusion during photobleaching into consideration. However, there is currently no consensus on confocal FRAP theory, and no efforts have been made to unify theories on conventional and confocal FRAP. To this end, we generalized conventional FRAP theory to incorporate diffusion during photobleaching so that analysis by conventional FRAP theory for a circular region of interest is easily applicable to confocal FRAP. Finally, we demonstrate the accuracy of these new (to our knowledge) formulae by measuring D for soluble enhanced green fluorescent protein in aqueous glycerol solution and in the cytoplasm and nucleus of COS7 cells.

Nucleocytoplasmic Distribution and Dynamics of the Autophagosome Marker EGFP-LC3

The process of autophagy involves the formation of autophagosomes, double-membrane structures that encapsulate cytosol. Microtubule-associated protein light chain 3 (LC3) was the first protein shown to specifically label autophagosomal membranes in mammalian cells, and subsequently EGFP-LC3 has become one of the most widely utilized reporters of autophagy. Although LC3 is currently thought to function primarily in the cytosol, the site of autophagosome formation, EGFP-LC3 often appears to be enriched in the nucleoplasm relative to the cytoplasm in published fluorescence images. However, the nuclear pool of EGFP-LC3 has not been specifically studied in previous reports, and mechanisms by which LC3 shuttles between the cytoplasm and nucleoplasm are currently unknown. In this study, we therefore investigated the regulation of the nucleo-cytoplasmic distribution of EGFP-LC3 in living cells. By quantitative fluorescence microscopy analysis, we demonstrate that soluble EGFP-LC3 is indeed enriched in the nucleus relative to the cytoplasm in two commonly studied cell lines, COS-7 and HeLa. Although LC3 contains a putative nuclear export signal (NES), inhibition of active nuclear export or mutation of the NES had no effect on the nucleo-cytoplasmic distribution of EGFP-LC3. Furthermore, FRAP analysis indicates that EGFP-LC3 undergoes limited passive nucleo-cytoplasmic transport under steady state conditions, and that the diffusional mobility of EGFP-LC3 was substantially slower in the nucleus and cytoplasm than predicted for a freely diffusing monomer. Induction of autophagy led to a visible decrease in levels of soluble EGFP-LC3 relative to autophagosome-bound protein, but had only modest effects on the nucleo-cytoplasmic ratio or diffusional mobility of the remaining soluble pools of EGFP-LC3. We conclude that the enrichment of soluble EGFP-LC3 in the nucleus is maintained independently of active nuclear export or induction of autophagy. Instead, incorporation of soluble EGFP-LC3 into large macromolecular complexes within both the cytoplasm and nucleus may prevent its rapid equilibrium between the two compartments.

Simplified equation to extract diffusion coefficients from confocal FRAP data.

Quantitative measurements of diffusion can provide important information about how proteins and lipids interact with their environment within the cell and the effective size of the diffusing species. Confocal fluorescence recovery after photobleaching (FRAP) is one of the most widely accessible approaches to measure protein and lipid diffusion in living cells. However, straightforward approaches to quantify confocal FRAP measurements in terms of absolute diffusion coefficients are currently lacking. Here, we report a simplified equation that can be used to extract diffusion coefficients from confocal FRAP data using the half time of recovery and effective bleach radius for a circular bleach region, and validate this equation for a series of fluorescently labeled soluble and membrane‐bound proteins and lipids. We show that using this approach, diffusion coefficients ranging over three orders of magnitude can be obtained from confocal FRAP measurements performed under standard imaging conditions, highlighting its broad applicability.

A Closed-Form Analytic Expression for FRAP Formula for the Binding Diffusion Model

One of the most dominant methods cells use for a large class of cellular processes is reaction (or binding) diffusion kinetics, which are controlled by kinetic constants such as diffusion coefficients and on/off binding rate constants. Fluorescence recovery after photobleaching (FRAP) can be used to determine these kinetic constants in living cells. While an analytic expression for FRAP formulae for pure diffusion has been available for some time, an analytic FRAP formula for the binding diffusion model has not been reported yet. Here, we present an analytic FRAP formula for the binding diffusion model in an explicit form allowing for diffusion of the bound complex for either a uniform circle laser profile or a Gaussian laser profile.

Analysis of Protein and Lipid Dynamics Using Confocal Fluorescence Recovery After Photobleaching (FRAP)

Fluorescence recovery after photobleaching (FRAP) is a powerful, versatile, and widely accessible tool to monitor molecular dynamics in living cells that can be performed using modern confocal microscopes. Although the basic principles of FRAP are simple, quantitative FRAP analysis requires careful experimental design, data collection, and analysis. In this unit, we discuss the theoretical basis for confocal FRAP, followed by step‐by‐step protocols for FRAP data acquisition using a laser‐scanning confocal microscope for (1) measuring the diffusion of a membrane protein, (2) measuring the diffusion of a soluble protein, and (3) analysis of intracellular trafficking. Finally, data analysis procedures are discussed, and an equation for determining the diffusion coefficient of a molecular species undergoing pure diffusion is presented. Curr. Protoc. Cytom. 62:2.19.1‐2.19.29.

The variety of cytosolic calcium responses and possible roles of PLC and PKC

A model of ligand-induced intracellular calcium (Ca2+) responses incorporating phospholipase C (PLC) and protein kinase C (PKC) is developed for the purpose of understanding the mechanisms underlying the observed temporal patterns of intracellular calcium (Ca(i)2+) under sustained agonist stimulation. Some studies have suggested that inhibition of ligand receptors and PLC by PKC could generate sinusoidal Ca2+ oscillations, while PKC-independent Ca2+-induced Ca2+ release (CICR) via IP(3)-gated Ca2+ channels on the endoplasmic reticulum (ER) is believed to be responsible for baseline spiking. However, some evidence also indicates that baseline spiking can be observed under high-PKC activity, or under low-PKC activity with low agonist stimulus, as well. Insight into the basis of these observations regarding the role of PKC in Ca(i)2+ response patterns can be gained by developing and analyzing a mathematical model of Ca(i)2+ responses. We do this herein and find that (1) interaction of CICR and the sarcoplasmic/endoplasmic reticulum calcium ATPase (SERCA) pump is enough to generate both types of Ca(i)2+ oscillations, (2) there exist four possible Ca(i)2+ response patterns under sustained agonist stimulus: a sub-threshold response (SR), baseline spiking, sinusoidal oscillations (SO) and transient with plateau, and (3) the IP(3) concentration, which is controlled by the strength of the interaction between PKC and PLC, can be used to predict the Ca(i)2+ response patterns. From this analysis we conclude that the different patterns of Ca(i)2+ oscillations can be understood as a generic consequence of the interactions between CICR via the IP(3)-gated Ca(2+) channels in response to changes in the level of IP(3), and re-uptake into the ER/SR via the SERCA pump. PKC, in conjunction with PLC, can act as a switch between different Ca(i)2+ response patterns by modulating the cytosolic IP(3) level, which determines the Ca(i)2+ patterns.

Validation of Normalizations, Scaling, and Photofading Corrections for FRAP Data Analysis.

Fluorescence Recovery After Photobleaching (FRAP) has been a versatile tool to study transport and reaction kinetics in live cells. Since the fluorescence data generated by fluorescence microscopy are in a relative scale, a wide variety of scalings and normalizations are used in quantitative FRAP analysis. Scaling and normalization are often required to account for inherent properties of diffusing biomolecules of interest or photochemical properties of the fluorescent tag such as mobile fraction or photofading during image acquisition. In some cases, scaling and normalization are also used for computational simplicity. However, to our best knowledge, the validity of those various forms of scaling and normalization has not been studied in a rigorous manner. In this study, we investigate the validity of various scalings and normalizations that have appeared in the literature to calculate mobile fractions and correct for photofading and assess their consistency with FRAP equations. As a test case, we consider linear or affine scaling of normal or anomalous diffusion FRAP equations in combination with scaling for immobile fractions. We also consider exponential scaling of either FRAP equations or FRAP data to correct for photofading. Using a combination of theoretical and experimental approaches, we show that compatible scaling schemes should be applied in the correct sequential order; otherwise, erroneous results may be obtained. We propose a hierarchical workflow to carry out FRAP data analysis and discuss the broader implications of our findings for FRAP data analysis using a variety of kinetic models.

Complex Applications of Simple FRAP on Membranes

There is an old adage that says “To see is to believe,” and it still seems to be true in many fields of biology. For an experimental validation of hypotheses, modern biology takes advantage of various fluorescence-based techniques (fluorescence microscopy, digital image analysis) for visualization and quantification. Fluorescence Recovery after Photobleaching (FRAP), a widely used fluorescence-based technique to visualize and quantify the diffusion of fluorescently tagged proteins, is one good example. The first observation of fluorescence was made by Sir John Frederick William Herschel (1845) from a quinine solution, and the concept of fluorescence was first named after fluorite by Sir George G. Stokes (1857). On a microscopic scale, fluorescence was first observed by August K?ler (1904), who discovered that a biological tissue could autofluoresce under ultraviolet light irradiation. Later, it became popular in the biological field after M. Haitinger (1933) succeeded in staining histological specimens with fluorescent dyes for the first time, which is called the technique of secondary fluorescence, distinguishing it from autofluorescent tissue previously observed by M. Haitinger. Haitinger and others extended the application of the technique of secondary fluorescence to stain not only specific tissues but also bacteria, or other pathogens that are not autofluorescent [1]. Although the technique of secondary fluorescence demonstrated that nonfluorescent cells can be made fluorescent, it was a nonspecific staining technique. The breakthrough in a specific immunofluorescence staining technique was provided by Albert Coons in 1941 by attaching a fluorescent dye to an antibody [2]. Later, Coons and N.H. Kaplan developed the fluorescein isothiocyanate (FITC) immunofluorescence technique [3].