Enhanced FRET contrast in lifetime imaging.

Area of Science:

• Biophysics
• Cell Biology
• Microscopy Techniques

Background:

• Fluorescence Lifetime Imaging Microscopy (FLIM) combined with two-photon excitation is a powerful technique for quantifying subcellular protein-protein interactions in living cells.
• Accurate analysis of FLIM data, often employing Time-Correlated Single Photon Counting (TCSPC), relies on fitting photon decay curves, a process complicated by the need to determine the optimal number of exponential terms.
• Current methods often use a simplified mono-model for entire images, which can be labor-intensive and lead to inaccurate interpretations, especially for heterogeneous samples.

Purpose of the Study:

• To develop an automated, pixel-by-pixel analysis algorithm for FLIM data to improve the accuracy and efficiency of protein-protein interaction studies.
• To enable optimized Förster resonance energy transfer (FRET) quantification and provide a more realistic representation of interaction maps in living cells.
• To offer an easy-to-use procedure for multi-model FLIM analysis, mitigating misinterpretations common with heterogeneous biological samples.

Main Methods:

• Development of a novel algorithm, Lichi, which performs pixel-by-pixel analysis of FLIM data based on the Deltachi(2) value.
• Validation of the Lichi algorithm using simulated photon decay curves with known lifetimes and proportions.
• Application of Lichi to lifetime images acquired from living cells to assess its performance in real biological samples.

Main Results:

• The Lichi algorithm demonstrated high robustness for analyzing decay curves containing more than 10^3 photons.
• Pixel-by-pixel analysis using Lichi resulted in more realistic interaction maps compared to traditional whole-image analysis.
• The developed multi-model FLIM analysis procedure proved effective for optimizing FRET quantification and analyzing interaction textures.

Conclusions:

• Lichi provides an efficient and accurate method for pixel-by-pixel FLIM analysis, improving the reliability of subcellular protein-protein interaction studies.
• The algorithm facilitates optimized FRET quantification and is particularly valuable for studying heterogeneous samples, avoiding common misinterpretations.
• This approach enhances the utility of FLIM for quantitative biological research, offering a more realistic representation of molecular interactions within living cells.