Rapid global fitting of large fluorescence lifetime imaging microscopy datasets

Area of Science:

• Biophysics
• Microscopy
• Computational Biology

Background:

• Fluorescence lifetime imaging (FLIM) provides quantitative data for Förster Resonant Energy Transfer (FRET) measurements.
• Pixel-wise analysis of photon-limited FLIM data, especially for live cells, often results in unacceptable errors due to complex decay models.

Purpose of the Study:

• To develop a computationally efficient global analysis algorithm for FLIM data.
• To enable robust extraction of FRET efficiencies and lifetime components from photon-limited datasets.

Main Methods:

• Global analysis using variable projection for time-correlated single photon counting (TCSPC) and time-gated FLIM data.
• Simultaneous fitting of all pixels to a multi-exponential model assuming invariant lifetime components.
• Accommodates repetitive excitation, time-varying backgrounds, and instrument response functions.

Main Results:

• The algorithm analyzes large FLIM datasets (hundreds of images) in under a minute on standard PCs.
• Successfully fitted complex models, including a four-exponential FRET system and polarization-resolved lifetime data for homo-FRET.
• Demonstrated accurate FRET efficiency and population fraction extraction from photon-limited data.

Conclusions:

• The efficient global analysis algorithm significantly improves the accuracy and speed of FLIM data analysis.
• Enables robust quantitative FRET measurements in challenging live-cell and in vivo imaging scenarios.
• The open-source software package FLIMfit is available for broader scientific use.