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• W2079666952 abstract "Förster resonance energy transfer (FRET) is a physical phenomenon that has been of incredible utility to the scientific community, enabling the study of a wide range of nanoscale, distance-dependent measurements. FRET occurs when energy is nonradiatively transferred from an excited fluorophore (the donor fluorophore) to a second fluorophore in near proximity (the acceptor fluorophore) 1, 2. Because the rate at which energy is transferred from the donor to the acceptor fluorophore depends on the intermolecular distance raised to the sixth power, FRET provides a highly sensitive measure of intermolecular spacing 2, 3. The key parameter in FRET measurements is the FRET efficiency. FRET efficiency is most often described as the ratio of the number of quantized energy events (sometimes referred to as virtual photons 4) transferred from the donor fluorophore to the acceptor fluorophore, divided by the total number of quantized energy events (photons) absorbed by the donor fluorophore 5. Using appropriate measurement and computational techniques, FRET efficiency represents a quantifiable value describing the intermolecular spacing and orientation within a sample. For fluorophores with fixed intermolecular spacing, the value of the measured FRET efficiency has been shown to be relatively constant, regardless of the measurement technique used 6. Hence, FRET reporters can be used to provide absolute quantitative data describing inter- and intramolecular interactions. Computing the FRET efficiency, whether in fluorescence microscopy or flow cytometry measurements, typically requires a ratiometric calculation 7. Because FRET efficiencies often range from 20 to 60% for biological reporters, the fluorescence emission from the acceptor fluorophore, when excited via energy transfer, usually provides lower signal strength than measurements of acceptor fluorophore emission resulting from direct excitation. Performing ratiometric calculations using relatively weak signals as the inputs can result in compounding error propagation 8. Thus, while FRET, as a tool, offers the ability to probe molecular distances within images or flow cytometry data, it also introduces substantial limitations in sensitivity and variance, due to low signal strength. Low signal strength may also limit spatial and temporal resolution. When performing FRET experiments, trade-offs must usually be made between signal strength (accuracy of the FRET efficiency calculation), spatial resolution, and temporal resolution. For example, if utilizing a FRET reporter to study high-speed signaling events, a likely trade-off would be to sacrifice spatial resolution, perhaps even performing the experiment in bulk solution, to maintain adequate signal strength and allow interpretation of the results. These trade-offs can place large limitations on utilizing FRET reporters to measure single-cell signaling events, especially those occurring at high speed or in discrete regions of a cell. Compounding the inherent limitations of signal strength are limitations that arise from making simultaneous ratiometric measurements of two fluorescent molecules (three if trimolecular FRET is considered). These limitations include differential photobleaching, relative concentration changes of fluorophores, and changes in environmental conditions (pH, ionic gradients, refractive index), necessitating the use of carefully planned experimental controls 9. Two classes of approaches were developed for overcoming FRET measurement limitations: new instrumentation/measurement strategies and new computational tools. The first class of approaches, instrumentation and measurement strategies, includes techniques such as acceptor photobleaching, fluorescence lifetime, spectral imaging, and fluorescence anisotropy. In fact, there are now such a wide range of technological options available for measuring FRET that it can be difficult to evaluate which option is appropriate for a given experimental situation. Under the best of circumstances, when performed with high-excitation efficiency, high-quantum efficiency, and chemically stable fluorophores, FRET can be accurately measured using standard epifluorescence microscope configurations. In other cases, however, sophisticated instrumentation is required to accurately assess changes in FRET efficiency. It is likely that new cytometric technologies and biological labeling approaches will continue to be developed in an effort to enable FRET assays with increased sensitivity, decreased variance, and increased dynamic range. The second class of approaches for overcoming FRET measurement limitations is to improve the accuracy of computational tools used in calculating the FRET efficiency. This approach is taken by Nagy et al. in the article—Maximum likelihood estimation (MLE) of FRET efficiency and its implications for distortions in pixelwise calculation of FRET in microscopy—on page 942 in this edition of Cytometry, Part A 10. In this article, the authors use MLE to calculate the FRET efficiency from data acquired using a photon counting detector. Additional FRET-related parameters, such as spectral overspill coefficients, are also calculated. The effectiveness of the MLE approach was evaluated using a series of theoretical Monte Carlo FRET simulations, in vitro experiments using a set of fluorescent protein FRET “standards” 6, and ex vivo tissue slices. The most dramatic improvements of the MLE method (over standard pixel-by-pixel-based methods or total intensity methods) are shown to occur when the photon flux is very low. This improvement occurs because the proposed MLE method accounts for Poisson statistics inherent in photon-based measurements. In addition to improving the accuracy of FRET calculations, the MLE approach may also function well for removal of outlier pixels, which are common when performing FRET with low intensity fluorescence emission. To allow MLE estimates to be made, all pixels within a field-of-view are utilized, resulting in a single FRET efficiency value per image. For many assays, an ensemble response is all that is desired. However, the authors also demonstrate that MLE approaches can be employed to calculate the FRET efficiency within a spatial subset (region) of an image. This approach could be of high importance to investigators performing low signal-to-noise or high-speed FRET measurements. In the past decade, we have seen a great expansion in the variety of fluorescence microscopy instruments, add-ons, and approaches that have allowed new capabilities for spatial, temporal, and wavelength resolutions, as well as improved spectral sampling and sensitivity. This has led to increasingly quantitative, automated, and sophisticated single-cell microscopy studies. It is interesting that many of these new technologies, instead of making FRET assays obsolete, have enhanced the accessibility and accuracy of FRET approaches. This trend is likely to continue. For example, one could envision super-resolution, three-dimensional FRET assays that would be of very high utility. The ability to accurately assess FRET efficiencies in organelles, suborganellar regions, endosomes, or microparticles could transform our understanding of localized signaling domains and cell-signaling compartmentalization, discussed in 11, 12. Similarly, the ability to accurately measure FRET using high-speed time-lapse microscopy is important for understanding subtle kinetic events. One could envision scenarios requiring both high resolution and high speed, such as measuring cyclic adenosine monophosphate (cAMP) signals produced by activated endosomal signaling complexes as they traffic through migrating cells. Although these scenarios depend on improved microscopy technologies, it is likely that they will also require advances in analysis techniques, such as the statistical approaches described by Nagy et al., as well as image cytometry approaches that utilize improved algorithms for automated image analysis, cell segmentation, and feature extraction. In fact, it is likely that it will be at the interface of multiple technological improvements—improved microscope instrumentation, improved FRET calculations, and improved image segmentation and feature extraction algorithms—that we will realize the greatest impact on localized, single-cell, and subcellular FRET measurements." @default.
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• W2079666952 title "FRET: Signals hidden within the noise" @default.
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