Particle-based phasor-FLIM-FRET resolves protein- protein interactions inside single viral particles

BIOPHYSICAL REPORTS(2023)

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摘要
Fluorescence lifetime imaging microscopy (FLIM) is a popular modality to create additional contrast in fluorescence images. By carefully analyzing pixel-based nanosecond lifetime patterns, FLIM allows studying complex molecular populations. At the single-molecule or single-particle level, however, image series often suffer from low signal intensities per pixel, rendering it difficult to quantitatively disentangle different lifetime species, such as during Forster resonance energy transfer (FRET) analysis in the presence of a significant donor-only fraction. In this article we investigate whether an object localization strategy and the phasor approach to FLIM have beneficial effects when carrying out FRET analyses of single particles. Using simulations, we first showed that an average of similar to 300 photons, spread over the different pixels encompassing single fluorescing particles and without background, is enough to determine a correct phasor signature (SD < 5% for a 4-ns lifetime). For immobilized single-or double-labeled dsDNA molecules, we next validated that particle-based phasor-FLIM-FRET readily allows estimating fluorescence lifetimes and FRET from single molecules. Thirdly, we applied particle-based phasor-FLIM-FRET to investigate protein-protein interactions in subdiffraction HIV-1 viral particles. To do this, we first quantitatively compared the fluorescence brightness, lifetime, and photostability of different popular fluorescent protein-based FRET probes when genetically fused to the HIV-1 integrase enzyme in viral particles, and conclude that eGFP, mTurquoise2, and mScarlet perform best. Finally, for viral particles coexpressing FRET-donor/acceptor-labeled IN, we determined the absolute FRET efficiency of IN oligomers. Available in a convenient open-source graphical user interface, we believe that particle-based phasor-FLIM-FRET is a promising tool to provide detailed insights in samples suffering from low overall signal intensities.
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