New PhytologistCell BiologyPeer-reviewed journal article
TipQUANT: A robust algorithm for quantitative analysis of spatiotemporally dynamic activities in tip-growing cells
Jingzhe GuoiD, Julian Le Gouic, Rémi Rosenthal, Ailing Zou, Xiang ZhouiD, Nicolas BruneliD, Zhenbiao YangiD, Xinping CuiiD
Abstract
Cell polarity, essential for cell development and function, relies on dynamic subcellular distribution of structural and signaling molecules. Tip growth, an extreme form of polar growth, involves unidirectional expansion at the apical region of cells and requires precise spatiotemporal coordination to achieve periodic and directional growth. Understanding their spatiotemporal dynamics is critical for elucidating mechanisms and functions of cell polarity. However, manual quantification of such dynamics is extremely time-consuming, hindering advancements in the field. Current algorithms have limited power and flexibility in analyzing the distribution and dynamics of molecules and structures, particularly for tip-growing cells with oscillatory and dynamic behavior. To address this challenge, we present TipQuant, an automated analysis tool that robustly detects tips and analyzes spatiotemporal dynamics of fluorescently labeled molecules/structures on plasma membranes and in cytoplasm at apices of tip-growing cells, enabling quantitative understanding of signaling and structural components in these systems.
- assay: fluorescence / live-cell microscopy
- research focus: cell type annotation
- research focus: trajectory inference
- research focus: spatial domain detection
- approach: deep learning
- approach: statistical model
- Citations
- 0
- FWCI
- 0.00
- Field percentile
- 29th percentile
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