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Quantitative Approaches for Studying Cellular Structures and Organelle Morphology in Caenorhabditis elegans

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Segmentation and quantification of subcellular structures in fluorescence microscopy images using Squassh.

Aurélien Rizk¹, Grégory Paul², Pietro Incardona³

¹1] Paul Scherrer Institute, Biomolecular Research, Molecular Cell Biology, Villigen PSI, Switzerland. [2] MOSAIC Group, Center of Systems Biology Dresden, Max Planck Institute of Molecular Cell Biology and Genetics, Dresden, Germany.

Nature Protocols

|February 15, 2014

Summary

Squassh software offers a new method for analyzing subcellular structures in fluorescence microscopy images. This segmentation and quantification of subcellular shapes tool provides object-specific data, improving accuracy over pixel-wise analyses.

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Rapid Analysis and Exploration of Fluorescence Microscopy Images

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Published on: March 19, 2014

Area of Science:

Cell Biology
Microscopy
Image Analysis

Background:

Analyzing fluorescently labeled molecules in subcellular compartments is crucial for cell biology.
Traditional pixel-wise colocalization analyses lack object-specific information and are sensitive to noise and background fluorescence.

Purpose of the Study:

To present a versatile protocol for 'Squassh' (segmentation and quantification of subcellular shapes).
To provide user-friendly software for detecting, delineating, and quantifying subcellular structures in fluorescence microscopy images.

Main Methods:

Developed a software workflow implemented in freely available, user-friendly software.
The method handles both 2D and 3D images, correcting for microscope optics and uneven backgrounds.
Computes cell masks and offers subpixel accuracy for detailed analysis.

Main Results:

Squassh software enables both colocalization and shape analyses of subcellular structures.
The protocol is suitable for batch processing on desktop computers or clusters.
Processing times are efficient, typically under 1 minute for 2D and under 5 minutes for 3D images.

Conclusions:

Squassh provides an accurate and efficient method for analyzing subcellular structures in fluorescence microscopy.
The software offers object-specific insights, overcoming limitations of pixel-wise approaches.
Recommended for researchers with basic computer skills and fluorescence microscopy experience.