Investigation of protein-protein interactions is important in understanding the structure-function relations in living cells. Fluorescence resonance energy transfer (FRET) techniques are excellent tools for determining association patterns of transmembrane proteins at the cell surface. With the help of FRET, molecular dimensions and molecular proximity can be measured and determined in functioning, live cells and provide information that would be hindered by the implicit aggregating nature of other classic approaches.
The theory of FRET was first developed by Theodor Förster (1). The FRET process is a dipole-dipole interaction in which an excited donor fluorophore transfers its energy to an acceptor molecule in close vicinity (1–10 nm) in a nonradiative way. The main application of FRET as a spectroscopic ruler (2) is based on the fact that the rate of energy transfer depends on the inverse sixth power of the distance between the two interacting molecules. The common way to measure FRET processes is by the decrease in donor fluorescence in the presence of an acceptor, which can be accompanied by an increase of fluorescence of the acceptor (if the acceptor is a fluorescent molecule). In recent years numerous FRET-based techniques have been developed for flow cytometry (3–5) and microscopy (6–10). Several biological structures have been successfully investigated by these methods: receptors involved in immune response (11–13), growth factor receptors on tumor cells (14–16), determination of lipid microdomain structures (17, 18), and protein conformation (19, 20).
Fluorescence-activated cell sorting and analysis or flow cytometry is one solution for high-speed quantitative analysis of cell. With this technique cell populations can be studied and evaluated relatively fast and the energy transfer efficiency values can be determined on a cell-by-cell basis. Because of the large number of cells, it can provide relatively good statistics (21), but the energy transfer values are averaged for each cell, so no information is available about the diversity of these values on the cell surface of single cells.
Different fluorescent microscopic techniques have become very popular during the last 15 years for studying various components of the cell. Parallel to the evolution of these techniques has been the realization of the importance of the lateral distribution and topology of the different cell surface components. There are several spectroscopic methods adapted and applied together with microscopic techniques. For the imaging techniques the application of FRET for inspection of receptor associations provides an extra possibility for surpassing the actual diffraction limited resolution of the light microscope.
Upon continuous excitation of the donor molecules, their fluorescence intensity decreases due to photobleaching, an irreversible, oxygen-dependent photochemical degradation process. For a double-labeled sample, i.e., with donor and acceptor molecules present, FRET between the fluorophores opens an additional relaxation pathway for the excited donor molecules. Thus the decline in the number of donor excited states by photobleaching takes longer. This method was designated “donor photobleaching FRET (pbFRET)” at the time of its introduction (22–24).
Because of the uneven distribution of cell surface components, there are several regions at the labeled surface that demonstrate different fluorescence intensities. These spatial heterogeneities can also be very important to answer relevant biological questions (25–28).
To determine the transfer efficiency (E), two series of images should be recorded, one from the sample labeled solely by donor and one from a sample double-labeled by donor and acceptor. A convenient means for generating the “acceptor-alone” reference state is to photobleach the acceptor in an appropriate region of the sample and convenient combined protocols for donor and acceptor photobleaching have been implemented (29).
The photobleaching decay curves can be obtained from the image series by fitting exponential function to each pixel series (22–24). At the time when the initial fluorescence intensity decreases to 1/e, part of its initial value is defined as the photobleaching time constant. The energy transfer efficiency can be calculated from the bleaching time constants of the donor-only labeled and donor-acceptor double-labeled samples.
Several commercially available programs have options to record and display bleaching image series and to generate bleaching curves from the recorded images, but they do not support curve fitting or only single curve fitting is possible (30). Because of the large number of pixels (in general 512 × 512 pixel image size) and the time-consuming calculations, this procedure should be assisted by a powerful image processing software.
We have developed a program to calculate FRET efficiency from raw image file series in Windows 9x and Windows XP operating systems. The program automatically generates the bleaching decay curves from the image series and fits them with optional single, double, or triple exponential functions. The bleaching time constant values can be displayed and saved in color-coded images (“tau map”) and histograms. The program also calculates statistical values of histograms to determine the mean bleaching time constant value and its standard deviation. We provide a short description of the theoretical background of pbFRET and the functionality of the software in addition to a representative experiment to demonstrate how the program works.
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- THEORETICAL BACKGROUND
- MATERIALS AND METHODS
- LITERATURE CITED
The photophysical consequences of the FRET phenomenon offer several ways to measure FRET efficiency. One of these possibilities is the acceptor-depletion FRET technique (13, 40–42), which is a useful pixel-by-pixel based fluorescence method. Using conventional fluorescence farfield image microscopic technique, a whole energy transfer map can be generated for cell surface receptors. With this method, some corrections have to be considered in the calculation because the results can be affected by background fluorescence and photobleaching of the donor molecules during acceptor bleaching. Despite these problems, the acceptor-depletion method has the obvious advantage that FRET can be determined from a single sample labeled with donor and acceptor.
Using the donor pbFRET method, the above-mentioned two technical drawbacks (background fluorescence and acceptor bleaching upon donor excitation) can be minimized. This technique is a powerful microscopic method to study the proximity and distribution of cell surface proteins on a molecular scale. To determine the energy transfer efficiency, two series of images should be recorded, one with a cell sample labeled solely with donor fluorophores and one with cells labeled with donor and acceptor. From the image series the distribution of the cell surface molecules can be studied. Moreover, from the image series the photobleaching time constants can be calculated by fitting the decay curves with an exponential function. To increase the accuracy of the mean of photobleaching time constant, values can be determined on a pixel-by-pixel basis. In general, the method allows for the selection of any desired region of interest in various regions of single cells, cell conjugates, or thin tissue slices.
Although the method is simple and does not need a complicated hardware configuration, there is a lack of analysis software because commercially available software can only record and display a bleaching image series and generate bleaching curves from the recorded images, but usually do not support curve fitting algorithms or only single exponential curve fitting is possible.
Here we present a LabVIEW application, with which the raw image series can be processed to determine the photobleaching time constant values. The resulting values can be plotted as a color-coded photobleaching time constant map to investigate the spatial distribution of the cell membrane components. Further, histograms can be generated from the fitting coefficients calculated on a pixel-by-pixel basis. The histograms can be gated by different color gates and fitted with Gaussian functions. The gated values are displayed on the first image of the captured image series by the gating color.
The program can be used to analyze bleaching image series measured by any instrument because it was developed to process raw image files. The program uses this image format because different equipments have several image formats to store the measured data, but most image analysis programs are able to convert image files to raw format.
The fitted data are saved to a simple ASCII text file, so they can be opened by any data processing software. The software package contains tools to convert the resultant data map to Tagged Image File Format (TIFF) or Image Cytometry Standard (ICS) image formats for further analysis. These tools for formatting results are also installed by the software. Details about their usage can be found in the software manual.
The application can be used without an existing LabVIEW developer environment because the LabVIEW runtime engine is automatically installed by the Install Shield wizard. The software is freely distributed and can be obtained free of charge from the authors. The software package includes a complete help and tutorial to help the first-time user.
In conclusion, we have introduced a new version of pbFRET analysis and data processing software that are able to generate a full analysis pattern of donor photobleaching decay image series at various conditions, independently of the complexity of the decay process and therefore of the nature of applied fluorophore. It allows for analysis of selected regions of interest on single cells or high throughput screening statistics on a large number of cells. The donor pbFRET approach together with the acceptor-depletion method used in conventional fluorescence or confocal laser scanning microscopes are of a continuously wide interest nowadays in studying molecular aspects of cellular recognition, communication, and signal processes in living cells, particularly in cell biology, immunobiology, and neurobiology.