Programming Juxtacrine-Based Synthetic Signaling Networks in a Cellular Potts Framework.

Area of Science:

• Synthetic biology
• Computational modeling
• Tissue engineering

Background:

• Synthetic development aims to reprogram eukaryotic cells for tissue formation.
• Designing effective signaling networks for this purpose is challenging due to prediction difficulties and costly in vitro testing.

Purpose of the Study:

• To develop a computational framework and an in silico cell line (ISCL) for efficient design and testing of synthetic signaling networks.
• To overcome the limitations of predicting tissue/morphogenic outcomes and reduce the cost/time of in vitro experimentation.

Main Methods:

• Developed a computational framework incorporating an in silico cell line (ISCL) with modifiable cellular behaviors (adhesion, motility, growth, division).
• Engineered ISCL with custom genetic circuits to test signaling network designs.
• Implemented the framework within the CompuCell3D cellular Potts modeling software.

Main Results:

• Demonstrated the ability to quickly engineer ISCL with custom genetic circuits.
• Provided a method for testing, improving, and exploring different signaling network designs computationally.
• Generated an example signaling network through programming custom genetic circuits into ISCL.

Conclusions:

• The developed computational framework and ISCL offer an efficient method for designing synthetic signaling networks.
• This approach facilitates the exploration of genetic circuit designs for synthetic biology and tissue engineering.
• The framework integrated into CompuCell3D provides a accessible tool for researchers in the field.