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Related Experiment Video

Updated: Jun 20, 2026

Correlative Microscopy for 3D Structural Analysis of Dynamic Interactions

Correlative Microscopy for 3D Structural Analysis of Dynamic Interactions

Published on: June 24, 2013

A novel approach for correlative light electron microscopy analysis.

Giuseppe Vicidomini¹, Maria C Gagliani, Katia Cortese

¹MicroSCoBiO Research Center, University of Genoa, 16146, Genoa, Italy.

Microscopy Research and Technique

|September 3, 2009

Summary

A new correlative light and electron microscopy (CLEM) method enhances speed and 3D analysis. This technique allows for statistically relevant data in molecular biology research by processing more samples efficiently.

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Area of Science:

Cell Biology
Microscopy Techniques
Molecular Biology

Background:

Correlative light and electron microscopy (CLEM) integrates fluorescence light microscopy (FLM) and electron microscopy (EM) data.
Traditional CLEM is time-consuming and lacks statistical relevance due to low throughput.
Bridging resolution gaps in cellular and subcellular analysis remains a challenge.

Purpose of the Study:

To develop an improved CLEM method for high-throughput, 3D correlative analysis.
To overcome the limitations of speed and statistical power in existing CLEM techniques.
To validate the new method for analyzing subcellular compartments.

Main Methods:

A novel CLEM protocol utilizing robust cryosectioning (Tokuyasu method).
An innovative image processing toolbox for multimodal analysis.
Serial cryosections and electron tomography microscopy (ETM) for 3D correlation.
Sample protection strategies against physical damage and fluorescence loss.

Main Results:

Enabled correlation of hundreds of cells/structures/events per session, a hundredfold increase.
Achieved three-dimensional correlation between FLM and EM data.
Demonstrated high success rates and compatibility with immunolabeling techniques.
Successfully validated for correlative analysis of Russel Bodies.

Conclusions:

The developed CLEM method significantly enhances throughput and enables 3D correlative analysis.
This approach provides statistically relevant data for molecular and cell biology.
The method is robust, efficient, and versatile for various biological applications.