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Protein Dynamics in Living Cells01:19

Protein Dynamics in Living Cells

2.1K
Different fluorescence-based techniques are used to study the protein dynamics in living cells. These techniques include FRAP, FRET, and PET.
Fluorescent recovery after photobleaching (FRAP) is a fluorescent-protein-based detection technique used to quantify protein movement rates within the cell. This method exposes a small portion of the cell to an intense laser beam. The laser beam causes permanent photobleaching of the fluorophore-tagged proteins in the exposed region. As the bleached...
2.1K
Super-resolution Fluorescence Microscopy01:37

Super-resolution Fluorescence Microscopy

6.8K
Super-resolution fluorescence microscopy (SRFM) provides a better resolution than conventional fluorescence microscopy by reducing the point spread function (PSF). PSF is the light intensity distribution from a point that causes it to appear blurred. Due to PSF, each fluorescing point appears bigger than its actual size, and it is the PSF interference of nearby fluorophores that causes the blurred image. Various approaches to achieving higher resolution through SRFM have recently been...
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Related Experiment Video

Updated: May 24, 2025

Automated Two-dimensional Spatiotemporal Analysis of Mobile Single-molecule FRET Probes
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Automated Two-dimensional Spatiotemporal Analysis of Mobile Single-molecule FRET Probes

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Photobleaching Step Counting and Localization for Fluorescence Microscopy.

Charles Truong, Thomas Bugea, Baptiste Bouhet

    Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
    |March 5, 2025
    PubMed
    Summary

    This study introduces a new supervised method for pinpointing photobleaching steps in fluorescence microscopy. It requires expert labels instead of calibration, improving accuracy in noisy biological data.

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    Area of Science:

    • Biophysics
    • Cell Biology
    • Microscopy

    Background:

    • Fluorescence microscopy is crucial for single-molecule analysis.
    • Photobleaching step patterns reveal molecular interactions.
    • Existing automated methods for step detection are complex and struggle with noise.

    Purpose of the Study:

    • To develop a user-friendly, supervised method for localizing photobleaching steps.
    • To overcome calibration challenges and improve robustness in low signal-to-noise conditions.
    • To enable accurate analysis of molecular dynamics, such as ribosome translation speed.

    Main Methods:

    • A supervised approach using expert-labeled fluorescence microscopy traces.
    • Automated tuning of a change-point detection algorithm based on provided labels.
    • Validation using simulated data and application to ribosome translation speed estimation.

    Main Results:

    • The supervised method accurately reproduces expert annotations on new signals.
    • The approach demonstrates superior performance in noisy conditions compared to existing methods.
    • Successful application to estimate ribosome translation speed.

    Conclusions:

    • Supervised learning offers a practical solution for photobleaching step analysis in fluorescence microscopy.
    • The developed algorithm is robust to noise and user-friendly, requiring no expert calibration.
    • This method enhances the study of molecular dynamics in biological systems.