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Updated: Apr 25, 2026

Protein-protein Interactions Visualized by Bimolecular Fluorescence Complementation in Tobacco Protoplasts and Leaves
Published on: March 9, 2014
Investigating protein-protein interactions in the plant endomembrane system using multiphoton-induced FRET-FLIM
Jennifer Schoberer1, Stanley W Botchway
1Department of Applied Genetics and Cell Biology, University of Natural Resources and Life Sciences, BOKU Vienna, Muthgasse 18, Vienna, 1190, Austria, jennifer.schoberer@boku.ac.at.
Abstract:
Real-time noninvasive fluorescence-based protein assays enable a direct access to study interactions in their natural environment and hence overcome the limitations of other methods that rely on invasive cell disruption techniques. The determination of Förster resonance energy transfer (FRET) by means of fluorescence lifetime imaging microscopy (FLIM) is currently the most advanced method to observe protein-protein interactions at nanometer resolution inside single living cells and in real-time. In the FRET-FLIM approach, the information gained using steady-state FRET between interacting proteins is considerably improved by monitoring changes in the excited-state lifetime of the donor fluorophore where its quenching in the presence of the acceptor is evidence for a direct physical interaction. The combination of confocal laser scanning microscopy with the sensitive advanced technique of time-correlated single photon counting allows the mapping of the spatial distribution of fluorescence lifetimes inside living cells on a pixel-by-pixel basis that is the same as the fluorescence image. Moreover, the use of multiphoton excitation particularly for plant cells provides further advantages such as reduced phototoxicity and photobleaching. In this protocol, we briefly describe the instrumentation and experimental design to study protein interactions within the plant endomembrane system, with a focus on the imaging of plant cells expressing fluorescent proteins and acquisition and analysis of fluorescence lifetime resolved data.
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