User-friendly assessment of pavement cell shape features with PaCeQuant: Novel functions and tools

Area of Science:

• Plant Biology
• Cell Biology
• Computational Biology

Background:

• Leaf epidermis pavement cells exhibit complex, jigsaw-like shapes crucial for tissue development.
• These cells serve as a model system for studying cell shape formation and growth coordination in mechanically coupled tissues.

Purpose of the Study:

• To develop a high-throughput tool for robust assessment and analysis of pavement cell shape characteristics.
• To provide a comprehensive software suite for segmentation, feature extraction, manual correction, and data visualization.

Main Methods:

• Development of PaCeQuant, an ImageJ-based MiToBo plugin for automatic cell contour segmentation and feature extraction.
• Inclusion of 28 shape features, including the Largest Empty Circle criterion for mechanical stress, and 8 lobe-specific features.
• Provision of LabelImageEditor for manual postprocessing and R package PaCeQuantAna for statistical analysis and visualization.

Main Results:

• PaCeQuant enables fully automatic segmentation and extraction of 28 distinct shape features per cell.
• The software categorizes cell lobes (Type I and Type II) and quantifies mechanical stress proxies.
• Supplemental tools facilitate error correction, statistical analysis, and publication-ready data visualization.

Conclusions:

• PaCeQuant offers a powerful, automated solution for analyzing pavement cell morphology in plant research.
• The integrated software suite enhances the efficiency and accuracy of high-throughput analysis of cell shape and growth.
• This toolset supports detailed investigation into the biomechanics and developmental processes of plant epidermal tissues.