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Updated: May 24, 2025

Mapping the Emergent Spatial Organization of Mammalian Cells using Micropatterns and Quantitative Imaging
Published on: April 30, 2019
Emergent Stable Tissue Shapes from the Regulatory Feedback between Morphogens and Cell Growth
Bivash Kaity1, Daniel Lobo1,2
1Department of Biological Sciences, University of Maryland, Baltimore County, 1000 Hilltop Circle, Baltimore, MD 21250, USA.
This study reveals how feedback between cell behavior and mechano-chemical signals drives tissue growth and pattern formation. Integrating these signals is key for multicellular organisms to achieve stable shapes and spatial organization.
Area of Science:
- Developmental Biology
- Systems Biology
- Mathematical Biology
Background:
- Multicellular organism development relies on coordinated cellular behaviors and mechano-chemical signals.
- The integration mechanisms linking these signals to emergent tissue shapes are not fully understood.
Purpose of the Study:
- To investigate the feedback mechanisms governing tissue growth and pattern formation using a novel mathematical model.
- To elucidate how mechano-chemical signaling and cellular dynamics interact to regulate tissue morphogenesis.
Main Methods:
- Developed a cell-centered agent-based mathematical model.
- Incorporated cell size dynamics influenced by morphogen concentrations and mechanical stress.
- Model does not rely on a superimposed lattice for increased applicability.
Main Results:
- Demonstrated that integrating feedback loops between cellular behaviors and mechano-chemical signaling is crucial for tissue shape and pattern regulation.
- Showed that patterning processes, like Turing systems, can induce stable tissue shapes that feedback to morphogen patterning.
- Highlighted the self-regulated loop between tissue shape and morphogenetic signals.
Conclusions:
- Emphasized the critical role of the feedback loop between morphogen patterning and cellular behaviors in regulating tissue growth and stable shape.
- Established a framework for high spatiotemporal resolution models to study whole-body development and regeneration.
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