Evaluation of intensity-based ratiometric FRET in image cytometry--approaches and a software solution.

Full Abstract

The intensity-based ratiometric FRET (fluorescence resonance energy transfer) method is a powerful technique for following molecular interactions in living cells. Since it is not based on irreversibly destroying the donor or the acceptor fluorophores, the time course of changes in FRET efficiency values can be monitored by this method. ImageJ, a sophisticated software tool for many types of image processing allows users to extend it with programs for various purposes. Implementing intensity-based ratiometric FRET with ImageJ vastly enhances the applicability of the FRET method. We developed an efficient ImageJ plugin, RiFRET, which calculates FRET efficiency on a pixel-by-pixel basis from ratiometric FRET images. It allows the user to correct for channel cross-talk (bleed-through) and to calculate FRET from image stacks, i.e., from 3D data sets. Semiautomatic processing for larger datasets is also included in the program. Furthermore, several options for calibrating FRET efficiency calculations were tested and their applicability to various expression systems is discussed. Although the ratiometric FRET method is widely applied, our plugin is the first freely available software for evaluating such FRET data. The program is user friendly and provides reliable, standardized results.

Author information

Author/s: Roszik, János (J); Lisboa, Duarte (D); Szöllosi, János (J); Vereb, György (G);

Affiliation: Department of Biophysics and Cell Biology, Medical and Health Science Center, University of Debrecen, Debrecen, Hungary.

Journal and publication information

Publication Type: Journal Article; Research Support, Non-U.S. Gov't

Journal: Cytometry. Part A : the journal of the International Society for Analytical Cytology (Cytometry A), published in United States. (Language: eng)

Reference: 2009-Sep; vol 75 (issue 9) : pp 761-7

Dates: Created 2009/08/19; Completed 2009/10/22;

PMID: 19591240, status: MEDLINE (last retrieval date: 10/22/2009, IMS Date: )

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