GraFT: A robust network-based spatiotemporal analysis of filamentous structures.

Area of Science:

• Plant cell biology
• Cytoskeletal dynamics
• Bioimaging analysis

Background:

• The plant actin cytoskeleton forms complex filamentous networks crucial for cellular processes.
• Quantifying the spatiotemporal properties of these actin structures is challenging due to segmentation difficulties.

Purpose of the Study:

• To develop a robust computational method for tracing and tracking actin filamentous structures in plant cells.
• To enable automated quantification of cytoskeletal properties for detailed analysis.

Main Methods:

• A network-based approach named Graph of Filaments over Time (GraFT) was developed.
• GraFT processes two-dimensional time series imaging data of cytoskeleton networks.
• The method was validated using synthetic data and real actin networks from *Arabidopsis thaliana* hypocotyls.

Main Results:

• GraFT accurately traces and tracks filamentous structures in plant actin cytoskeleton networks.
• The method successfully quantified structural properties under different experimental treatments.
• Automated analysis provided fine-grained insights into treatment effects on individual actin structures.

Conclusions:

• GraFT provides a substantial advancement for automated spatiotemporal studies of the plant actin cytoskeleton.
• This approach facilitates a deeper understanding of cytoskeletal dynamics and function in plants.
• GraFT enables robust quantification essential for plant cell biology research.