Thermodynamically consistent, reduced models of gene regulatory networks

Area of Science:

• Systems Biology
• Synthetic Biology
• Computational Biology

Background:

• Synthetic biology traditionally focuses on single-cell engineering.
• Engineering cell populations requires models linking intracellular and intercellular processes.
• Existing models may lack computational efficiency or thermodynamic consistency.

Purpose of the Study:

• Develop a computationally efficient and thermodynamically consistent kinetic model of gene expression.
• Enable the rational design of synthetic gene circuits in cell populations.
• Facilitate the engineering of collective cell behaviors.

Main Methods:

• Applied a model reduction scheme to translation for computational efficiency.
• Utilized bond graphs to ensure thermodynamic consistency in the models.
• Coupled gene expression models to create toggle switch and repressilator circuits.
• Incorporated resource availability and cell-to-cell heterogeneity.

Main Results:

• The reduced gene expression model is significantly faster than the full model.
• The reduced model accurately reproduces key behaviors of the full model.
• Simulations explored the impact of resource limitations and heterogeneity on circuit function.

Conclusions:

• The developed modeling approach bridges intracellular biochemistry and intercellular interactions for cell population engineering.
• This work supports the scalable design of synthetic gene circuits in large cell populations.
• The methods pave the way for engineering collective behaviors like synchronization and division of labor.