Automated 3D bio-imaging analysis of nuclear organization by NucleusJ 2.0

Area of Science:

• Cell Biology
• Bioinformatics
• Image Analysis

Background:

• NucleusJ 1.0 is an ImageJ plugin for analyzing nuclear morphology and chromatin organization.
• Previous versions required manual interaction and had limitations in processing speed.

Purpose of the Study:

• To introduce NucleusJ 2.0, a significantly improved version of the NucleusJ software.
• To enhance nuclear segmentation accuracy and processing speed for 3D nuclei analysis.
• To facilitate the creation of large, curated datasets for computational biology applications.

Main Methods:

• NucleusJ 2.0 utilizes a command-line interface for faster image processing.
• Introduced a new 3D gift-wrapping segmentation method alongside the Otsu-modified method.
• Compared segmentation accuracy using community datasets and evaluated performance on plant genetic material.

Main Results:

• NucleusJ 2.0 demonstrates faster image processing compared to previous versions.
• The 3D gift-wrapping method improves segmentation by accounting for nuclear indentations and unstained nucleoli.
• The software effectively analyzes nuclei stained with DNA dyes and processed via 3D-DNA Fluorescence *in situ* hybridization.

Conclusions:

• NucleusJ 2.0 offers enhanced capabilities for analyzing 3D nuclear structures in diverse biological samples.
• The software supports the generation of large datasets crucial for benchmarking and training machine learning models in image analysis.
• This advancement provides a valuable tool for researchers in plant and animal cell biology and bioinformatics.