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Fluorescence Lifetime Imaging of Molecular Rotors in Living Cells
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A fluorescence lifetime separation approach for FLIM live-cell imaging.

Cornelia Wetzker1,2, Marcelo Leomil Zoccoler3, Svetlana Iarovenko2,3,4

  • 1B CUBE - Center for Molecular Bioengineering, Technische Universität Dresden, Dresden, Germany.

Journal of Microscopy
|September 30, 2025
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Summary

Fluorescence lifetime imaging microscopy (FLIM) uses phasor analysis for lifetime separation, distinguishing fluorophores in live-cell imaging. This technique enhances biological sample visualization and data analysis for life science research.

Keywords:
FLIMOMEROlive‐cell imagingnapariphasor

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Area of Science:

  • Biophysics
  • Microscopy
  • Cell Biology

Background:

  • Fluorescence lifetime imaging microscopy (FLIM) provides contrast by measuring fluorophore excited-state duration.
  • Distinguishing spectrally similar fluorophores is challenging in biological imaging.
  • Phasor analysis offers a method for FLIM data interpretation.

Purpose of the Study:

  • To demonstrate lifetime separation using FLIM phasor analysis for distinguishing fluorescent molecules in live-cell imaging.
  • To showcase applications in tracking proteins and separating autofluorescence.
  • To introduce an open-source software plugin for FLIM data analysis.

Main Methods:

  • Utilized FLIM phasor analysis for lifetime separation of fluorophores.
  • Applied the technique to Caenorhabditis elegans for live-cell imaging.
  • Developed and used the open-source napari-flim-phasor-plotter plugin.

Main Results:

  • Successfully separated highly spectrally overlapping fluorophores mCherry and mKate2 in developing embryos.
  • Differentiated tagged proteins from natural autofluorescence in adult hermaphrodites.
  • Enabled distinct tracking of tagged proteins in six-dimensional datasets.

Conclusions:

  • FLIM phasor analysis provides effective lifetime separation for complex biological samples.
  • The developed open-source software facilitates FLIM data management and analysis.
  • This approach advances live-cell imaging capabilities in life science research.