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Updated: Apr 23, 2026
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Mapping the Emergent Spatial Organization of Mammalian Cells using Micropatterns and Quantitative Imaging
Published on: April 30, 2019
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Quantitative image analysis of cell behavior and molecular dynamics during tissue morphogenesis.
Chun Yin Bosco Leung1, Rodrigo Fernandez-Gonzalez
1Institute of Biomaterials and Biomedical Engineering, University of Toronto, 164 College Street, Toronto, ON, Canada, M5S 3G9.
Methods in Molecular Biology (Clifton, N.J.)
|September 24, 2014
Summary
SIESTA, a new tool for Scientific ImagE SegmenTation and Analysis, quantifies cell and molecular dynamics from images. This enables detailed analysis of cell behavior and molecular events in developmental processes like Drosophila axis elongation.
Area of Science:
- Developmental Biology
- Cell Biology
- Bioimaging
Background:
- Cell behaviors driving tissue morphogenesis are regulated by molecular events.
- Simultaneous tracking of molecular and cellular dynamics is crucial for understanding these regulations.
Purpose of the Study:
- To develop and present SIESTA, an integrated tool for Scientific ImagE SegmenTation and Analysis.
- To enable quantification of cell behavior and molecular events from image data.
Main Methods:
- Automated cell segmentation using the watershed algorithm.
- Semi-automated cell delineation using a minimal path search algorithm for challenging images.
- Quantification of cellular morphology and molecular dynamics in subcellular compartments.
Main Results:
- Demonstrated SIESTA's application in analyzing cell behavior and non-muscle myosin II dynamics during Drosophila embryo axis elongation.
- Showcased quantification of molecular asymmetries, such as planar cell polarity, in Drosophila embryos.
- Detailed methods for implementation in other software packages.
Conclusions:
- Quantitative imaging with SIESTA provides statistical power to detect subtle molecular differences influencing cell behavior.
- The tool facilitates a deeper understanding of molecular mechanisms underlying developmental processes.
- SIESTA supports the analysis of numerous samples for robust biological insights.
