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. 2016 Apr;89(4):325-7.
doi: 10.1002/cyto.a.22851.

Overcoming limitations of FRET measurements

Silas J Leavesley  1   2   3 , Thomas C Rich  2   3   4
Affiliations

Overcoming limitations of FRET measurements

Silas J Leavesley et al. Cytometry A. 2016 Apr.
No abstract available

Keywords: FLIM; FRET; Förster resonance energy transfer; fluorescence; imaging; lifetime; microscopy; spectral imaging; spectroscopy.

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Figures

Figure 1
Figure 1
Current state-of-the-art FRET measurement technologies suffer from reduced signal-to-noise ratios (SNR) when compared to measurement of a single fluorescent label or protein. A: Image of single-label acceptor emission using acceptor excitation (Venus, excited at 488 nm, expressed in pulmonary microvascular endothelial cells); (B) image of calculated FRET efficiency using hyperspectral confocal imaging shows reduced SNR when compared to the single-label image in Panel (A)–image shows a single expressing cell (Turquoise-Epac-Venus cAMP reporter(5), excited at 405 nm, expressed in pulmonary microvascular endothelial cells); (C) image of fluorescence lifetime where greyscale intensity represents lifetime, masked to illustrate a single cell (Turqouoise-Epac-Venus cAMP reporter (5), expressed in HEK-293 cells); (D) the image from Panel (B), masked to remove nuclei, false-colored, and scaled to highlight changes in FRET efficiency; (E) the image from Panel (C), false-colored and scaled to highlight changes in fluorescence lifetime. Images (A, B, and D) were taken using identical objectives and acquisition parameters using a Nikon A1R spectral confocal microscope, with the exception of using a 488 nm laser for direct excitation of Venus in Panel (A). Images were then linearly unmixed using a non-negatively constrained unmixing algorithm implemented in MATLAB software, and converted to 8-bit and scaled linearly for display. Images (C, E) were provided by courtesy of Dr. Kees Jalink, van Leeuwenhoek Centre of Advanced Microscopy, Amsterdam, The Netherlands. SNR was calculated as described by Bernas and colleagues (6)–in brief, pixels in regions of similar (but not oversaturated) intensity were identified using an 8-way high-pass filter and the mean intensity (signal) was calculated from the most homogeneous regions, while noise was calculated as the standard deviation of these regions and the SNR calculated as the ratio of mean intensity to standard deviation. [Color figure can be viewed in the online issue which is available at wileyonlinelibrary.com]
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