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Developing and Testing a Bayesian Analysis of Fluorescence Lifetime Measurements.

Bryan Kaye1,2, Peter J Foster1,2, Tae Yeon Yoo1,2

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We developed a Bayesian analysis for Fluorescence Lifetime Imaging Microscopy (FLIM) to accurately measure Förster Resonance Energy Transfer (FRET) from complex biological samples. This method precisely quantifies FRET even with limited photon counts or low FRET fractions.

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Area of Science:

  • Biophysics
  • Optical Microscopy
  • Molecular Imaging

Background:

  • Förster Resonance Energy Transfer (FRET) provides nanoscale spatial information beyond light diffraction limits.
  • Fluorescence Lifetime Imaging Microscopy (FLIM) measures FRET by detecting reduced fluorescence lifetimes.
  • FLIM data are complex, comprising mixed populations of FRETing and non-FRETing fluorophores.

Purpose of the Study:

  • To present a robust Bayesian inference method for analyzing FLIM data.
  • To address experimental challenges in FRET measurements, including low photon counts and low FRET fractions.
  • To accurately extract FRET parameters from complex experimental data.

Main Methods:

  • Bayesian inference framework for analyzing photon arrival time histograms.
  • Modeling of mixed exponential decay curves characteristic of FLIM-FRET.
  • Validation using controlled experimental data with known FRET parameters.

Main Results:

  • The Bayesian method accurately deconvolves mixed exponential lifetimes in FLIM data.
  • Precise extraction of FRET parameters demonstrated, even in low-photon and low-fraction regimes.
  • The analysis rigorously accounts for experimental complications.

Conclusions:

  • The developed Bayesian approach offers a significant advancement for quantitative FRET analysis using FLIM.
  • This method enhances the reliability and accuracy of FRET measurements in complex biological systems.
  • Enables more precise dynamic spatial information retrieval at the nanoscale.