Self-organized multicellular structures from simple cell signaling: a computational model.

Area of Science:

• Synthetic Biology
• Computational Biology
• Developmental Biology

Background:

• Synthetic biology experiments demonstrate that signaling modules targeting cell-cell adhesion can induce self-organization in multicellular structures.
• Changes in homotypic adhesion, mediated by contact-dependent signaling, lead to the sorting of cell aggregates into layered structures.

Purpose of the Study:

• To investigate the formation, maintenance, and robustness of self-organized multicellular structures using a computational model.
• To understand the dynamic mechanisms underlying the maintenance of these emergent morphologies.

Main Methods:

• Integration of an established Notch/ligand signaling model with the cellular Potts model.
• Simulation of differential E-cadherin expression to drive cell sorting and adhesion dynamics.
• Tracking of cell state changes, adhesion properties, and spatio-temporal rearrangement.

Main Results:

• The computational model successfully reproduced experimentally observed two- and three-layered multicellular structures.
• Analysis revealed the dynamic maintenance of emergent morphologies through intercellular signaling and cell rearrangement.
• The model provides insights into the link between intracellular/intercellular signaling and emergent collective behavior.

Conclusions:

• Differential cell adhesion, regulated by signaling pathways, is a key principle for self-organization in multicellular systems.
• Computational modeling offers a powerful approach to dissect the dynamic processes underlying emergent biological structures.
• This work highlights the importance of dynamic maintenance mechanisms in understanding biological self-organization at the cellular level.