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Related Concept Videos

Protein Dynamics in Living Cells01:19

Protein Dynamics in Living Cells

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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...
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Related Experiment Video

Updated: Apr 20, 2026

Fluorescence Recovery after Photobleaching of Yellow Fluorescent Protein Tagged p62 in Aggresome-like Induced Structures
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Fluorescence Recovery after Photobleaching of Yellow Fluorescent Protein Tagged p62 in Aggresome-like Induced Structures

Published on: March 26, 2019

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Localization precision in stepwise photobleaching experiments.

Ingmar Schoen1

  • 1Laboratory of Applied Mechanobiology, Department of Health Sciences and Technology, ETH Zurich, Zurich, Switzerland.

Biophysical Journal
|November 25, 2014
PubMed
Summary
This summary is machine-generated.

Precise localization microscopy relies on understanding stepwise photobleaching. This study reveals how noise and error propagation limit precision, offering a framework to improve biomolecular structure analysis.

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Area of Science:

  • Biophysics
  • Optical Microscopy
  • Structural Biology

Background:

  • Precise determination of fluorescent label positions is crucial for quantitative biomolecular structure studies using localization microscopy.
  • Stepwise photobleaching is a promising technique for measuring nanometer-scale distances between labels, but its precision limits are not well understood.

Purpose of the Study:

  • To investigate the factors limiting localization precision in stepwise photobleaching.
  • To establish fundamental precision limits (Cràmer-Rao lower bounds) for this technique.
  • To evaluate different data analysis methods for optimizing localization precision.

Main Methods:

  • Incorporation of point spread function-shaped shot noise into the Fisher matrix to derive Cràmer-Rao lower bounds (CRBLs).
  • Benchmarking analysis procedures against theoretical CRLBs using simulations.
  • Analysis of image subtraction, sequential fitting, and global fitting methods.

Main Results:

  • Shot noise and error propagation were identified as key factors compromising localization precision.
  • Derived CRLBs are anisotropic and depend on emitter intensity and position.
  • Image subtraction and sequential fitting showed reduced precision due to noise accumulation and error propagation, respectively.
  • Global fitting optimally utilized information but was still affected by error propagation.

Conclusions:

  • The study provides a quantitative framework for analyzing stepwise photobleaching experiments.
  • Cràmer-Rao lower bounds accurately quantify the precision of distance measurements, dependent on bleaching kinetics.
  • Understanding these limitations is vital for advancing localization microscopy and related techniques.