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Biophysical Reviews

, Volume 3, Issue 2, pp 63–70 | Cite as

Non fitting based FRET–FLIM analysis approaches applied to quantify protein–protein interactions in live cells

  • Sergi Padilla-ParraEmail author
  • Nicolas Auduge
  • Maite Coppey-Moisan
  • Marc TramierEmail author
Review

Abstract

New imaging methodologies in quantitative fluorescence microscopy and nanoscopy have been developed in the last few years and are beginning to be extensively applied to biological problems, such as the localization and quantification of protein interactions. Fluorescence resonance energy transfer (FRET) detected by fluorescence lifetime imaging microscopy (FLIM) is currently employed not only in biophysics or chemistry but also in bio-medicine, thanks to new advancements in technology and also new developments in data treatment. FRET–FLIM can be a very useful tool to ascertain protein interactions occurring in single living cells. In this review, we stress the importance of increasing the acquisition speed when working in vivo employing Time-Domain FLIM. The development of the new mathematical-based non-fitting methods allows the determining of the fraction of interacting donor without the requirement of high count statistics, and thus allows the performing of high speed acquisitions in FRET–FLIM to still be quantitative.

Keywords

Quantitative fluorescence microscopy Nanoscopy Förster resonance energy transfer (FRET) Fluorescence lifetime imaging microscopy (FLIM) 

Notes

Acknowledgement

This work was supported by the Fondation pour la Recherche Médicale, the Région Ile de France (Soutien aux Equipes Scientifiques pour l’Acquisition de Moyens Expérimentaux), the Association Nationale pour le Recherche (ANR-PFTV) (to M, C,-M,), IBiSA (to M, C,-M, and M,T,), Rennes Métropole and Région Bretagne (to M,T,).

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Copyright information

© International Union for Pure and Applied Biophysics (IUPAB) and Springer 2011

Authors and Affiliations

  1. 1.Department of Pediatrics, Infectious DiseasesEmory UniversityAtlantaUSA
  2. 2.Institut Jacques Monod, UMR 7592, CNRSUniversité Paris-DiderotParisFrance
  3. 3.CNRS, UMR 6061, Institut Génétique et Développement de RennesRennesFrance
  4. 4.Faculté de MédecineUniversité Rennes 1, UEB, IFR 140RennesFrance
  5. 5.Institut de Génétique et Développement de Rennes, UMR 6061 CNRSUniversité Rennes 1Rennes CedexFrance

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