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Protein Dynamics in Living Cells

Protein Dynamics in Living Cells

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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Updated: Jun 20, 2026

An Analytical Tool that Quantifies Cellular Morphology Changes from Three-dimensional Fluorescence Images

An Analytical Tool that Quantifies Cellular Morphology Changes from Three-dimensional Fluorescence Images

Published on: August 31, 2012

Quantifying cellular interaction dynamics in 3D fluorescence microscopy data.

Frederick Klauschen¹, Masaru Ishii, Hai Qi

¹Program in Systems Immunology and Infectious Disease Modeling, National Institute of Allergy and Infectious Diseases, NIH, Bethesda, MD, USA. fklauschen@mail.nih.gov

Nature Protocols

|August 22, 2009

Summary

This summary is machine-generated.

We developed an automated 3D fluorescence microscopy analysis method to quantify cellular interactions. This high-throughput approach enables rapid, standardized analysis of complex biological systems, crucial for understanding cellular behavior.

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Image Processing Protocol for the Analysis of the Diffusion and Cluster Size of Membrane Receptors by Fluorescence Microscopy

Image Processing Protocol for the Analysis of the Diffusion and Cluster Size of Membrane Receptors by Fluorescence Microscopy

Published on: April 9, 2019

Area of Science:

Cell biology
Biophysics
Microscopy

Background:

Advanced fluorescence microscopy provides high-resolution data on cellular processes.
Analyzing complex cellular interactions in 3D requires efficient, high-throughput methods.
Manual or semi-automated analyses are insufficient for large datasets.

Purpose of the Study:

To present a fully automated approach for analyzing cellular interaction behavior in 3D fluorescence microscopy images.
To enable rapid, standardized, and quantitative analysis of large biological datasets.
To facilitate the study of molecular mechanisms underlying cellular interactions.

Main Methods:

The protocol integrates adaptive threshold segmentation, object detection, adaptive color channel merging, and neighborhood analysis.
It is designed for fully automated analysis of 3D fluorescence microscopy data.
The method allows for quantitative analysis and comparison of relevant features.

Main Results:

The approach was successfully applied to analyze drug-induced and S1P(1)-knockout-related changes in bone-osteoclast interactions.
It was also used to analyze dendritic cell spatial association with the fibroblastic reticular cell network in lymph nodes.
The method was effective for analyzing T-B lymphocyte synapse formation.

Conclusions:

This automated protocol significantly enhances the ability to analyze cellular interactions in complex biological systems.
It overcomes limitations of manual/semi-automated methods for large-scale quantitative analysis.
The approach provides valuable insights into molecular mechanisms governing cellular interactions.