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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: Jul 17, 2025

Optimization and Comparative Analysis of Plant Organellar DNA Enrichment Methods Suitable for Next-generation Sequencing
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Optimization and Comparative Analysis of Plant Organellar DNA Enrichment Methods Suitable for Next-generation Sequencing

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Deep and fast label-free Dynamic Organellar Mapping.

Julia P Schessner1, Vincent Albrecht1, Alexandra K Davies1,2

  • 1Department of Proteomics and Signal Transduction, Systems Biology of Membrane Trafficking Research Group, Max-Planck Institute of Biochemistry, Martinsried, Germany.

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|August 29, 2023
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Summary

We enhanced protein localization mapping using data-independent acquisition (DIA)-DOMs, achieving greater depth and precision. This improved spatial proteomics workflow aids in discovering cellular phenotypes and understanding protein dynamics.

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Area of Science:

  • Cell Biology
  • Proteomics
  • Mass Spectrometry

Background:

  • The Dynamic Organellar Maps (DOMs) approach provides global profiling of protein subcellular localization.
  • Shotgun-proteomics and cell fractionation are key components of the DOMs workflow.

Purpose of the Study:

  • To enhance the performance of the DOMs approach using data-independent acquisition (DIA) mass spectrometry.
  • To introduce DOM-ABC, an open-source software for analyzing profiling data.
  • To apply the enhanced workflow to study subcellular localization changes in HeLa cells.

Main Methods:

  • Data-independent acquisition (DIA) mass spectrometry was integrated with the DOMs workflow.
  • Flexible map formats were developed for varying analysis needs.
  • The DOM-ABC software was created for user-friendly data analysis.

Main Results:

  • DIA-DOMs doubled the depth of protein profiling within the same mass spectrometry runtime.
  • Profiling precision and reproducibility were substantially improved.
  • The study identified a subset of Golgi proteins cycling through endosomes in response to cellular conditions.

Conclusions:

  • DIA-DOMs represent a superior, label-free spatial proteomics workflow.
  • This method enhances systematic phenotype discovery.
  • The workflow accurately predicts protein translocation dynamics.