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Intercellular communication and the organization of simple multicellular animals
P Japón1, F Jiménez-Morales2, F Casares3
1CABD, GEM-DMC2 Unit (CSIC-Universidad Pablo de Olavide-Junta de Andalucía), 41013 Seville, Spain; Department of Condensed Matter Physics, University of Sevilla, 41012 Seville, Spain.
Cells & Development
|August 27, 2021
Summary
This study models abstract cell collectives, or "bioswarmers," using coupled interacting particles. It reveals how intercellular communication rules and memory influence collective organization, differentiation, and directed migration in multicellular systems.
Area of Science:
- Computational Biology
- Systems Biology
- Biophysics
Background:
- Animal cells exhibit decentralized coordination, organizing into complex structures like embryos and organoids through intercellular communication.
- Understanding the fundamental rules governing cell-cell interactions is crucial for deciphering multicellular organization.
Purpose of the Study:
- To investigate the rules of intercellular relationships governing the organization of abstract cell collectives into metazoan-like structures.
- To explore the dynamics and conditions for multicellular organization using a computational model.
Main Methods:
- Utilized a modified "Swarmalator" computational model, representing cells as interacting particles with position and internal state (phase).
- Implemented the model in both 2D and 3D, exploring various coupling parameters to simulate intercellular communication.
- Investigated the impact of altering communication strength and cellular memory on collective behavior.
Main Results:
- Demonstrated that intercellular communication strength influences bioswarmer structure and cell differentiation.
- Showed that internal polarization can emerge, triggering collective directed migration.
- Identified that partial erasure of cellular memory is essential for state transitions in bioswarmers.
- Found that ensemble size can regulate cell differentiation independently of relationship rules.
Conclusions:
- The study provides insights into the fundamental principles of multicellular organization and collective behavior.
- The swarmalator model offers a versatile framework for studying emergent properties in biological systems.
- Findings highlight the critical roles of communication, polarization, memory, and size in shaping multicellular dynamics.
Keywords:
Computational modelsDecentralized systemsIntercellular communicationMulticellular organizationSelf-organizationSwarmalatorMore Related Videos
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