Spatial pattern dynamics of 3D stem cell loss of pluripotency via rules-based computational modeling

Area of Science:

• Stem cell biology
• Computational biology
• Regenerative medicine

Background:

• Pluripotent embryonic stem cells (ESCs) are crucial for regenerative medicine but controlling their differentiation is challenging.
• Embryoid bodies (EBs) are used to induce ESC differentiation, but cell fate specification within them is poorly understood.
• Predicting and controlling ESC differentiation is key to developing new therapies.

Purpose of the Study:

• To investigate the processes influencing initial cell fate transitions in 3D microenvironments using rules-based cellular modeling.
• To understand the temporal and spatial patterns of pluripotency loss (Oct4 expression) during EB formation.
• To establish the utility of rules-based modeling for generating hypotheses about ESC differentiation.

Main Methods:

• Utilized rules-based cellular modeling and physics-based aggregation simulations.
• Differentiated mouse ESCs (D3 cell line) and analyzed Oct4 expression patterns using confocal microscopy.
• Compared experimental EB physical parameters and Oct4 patterns with simulation results.

Main Results:

• Rules-based modeling accurately recapitulated global EB properties and Oct4 expression patterns.
• Loss of Oct4 was modeled as a binary process governed by simple rules combining stochasticity and intercellular communication.
• Competing influences between Oct4+ and Oct4- neighbors drive pluripotency loss patterns, independent of EB structure, size, or cell division.

Conclusions:

• Rules-based modeling is effective for understanding and predicting ESC differentiation in 3D microenvironments.
• Intercellular communication and baseline stochasticity are key drivers of initial cell fate decisions in EBs.
• This modeling approach can guide strategies for engineering cellular microenvironments and advancing regenerative medicine therapies.