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Fluorescence Lifetime Imaging of Molecular Rotors in Living Cells
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Practical guide to fluorescence lifetime imaging microscopy.

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Fluorescence lifetime imaging microscopy (FLIM) offers advanced cellular analysis by sensing molecular environments and enabling RNA quantification. This guide empowers researchers to utilize FLIM for diverse biosensors and microscopy applications.

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Area of Science:

  • Biophotonics and advanced microscopy techniques.

Background:

  • Fluorescence lifetime imaging microscopy (FLIM) provides unique advantages over traditional intensity-based methods, including sensitivity to molecular environments and concentration independence.
  • FLIM has been recently adapted for quantitative RNA sensing in live cells, creating the Riboglow-FLIM platform.
  • The technology holds significant potential to complement and enhance existing microscopy platforms.

Purpose of the Study:

  • To provide a practical guide for utilizing FLIM with diverse fluorescence sensors.
  • To introduce researchers to the fundamental concepts and best practices for designing and executing FLIM experiments.
  • To demonstrate the broad applicability of FLIM workflows through real-world case studies.

Main Methods:

  • Discussion of FLIM basics, including principles of operation and data acquisition.
  • Explanation of experimental setup considerations for FLIM.
  • Overview of data-fitting principles and analysis techniques relevant to FLIM data.

Main Results:

  • Demonstration of FLIM's capability for quantitative RNA sensing in live cells using the Riboglow-FLIM platform.
  • Case studies showcasing the application of FLIM with well-characterized fluorescent proteins.
  • Validation of FLIM workflows for diverse fluorescence sensing applications.

Conclusions:

  • FLIM is a powerful modality for sensing molecular environments, binding events, and metabolism.
  • The Riboglow-FLIM platform represents a significant advancement for quantitative RNA analysis in live cells.
  • This guide equips researchers with the knowledge to effectively implement FLIM for various biological sensing applications.