Model-guided gene circuit design for engineering genetically stable cell populations in diverse applications

Area of Science:

• Synthetic Biology
• Genetic Engineering
• Cellular Engineering

Background:

• Synthetic genetic constructs can burden host cells, leading to growth defects and mutations that impair engineered functions.
• Existing strategies to prevent mutation spread are context-dependent and require circuit-specific tailoring.
• Non-functional mutants can proliferate, compromising the stability and utility of engineered cell populations.

Purpose of the Study:

• To develop and analyze a novel biomolecular controller for maintaining genetic stability in engineered cell populations.
• To create a controller that mitigates mutant cell growth independently of the specific synthetic gene.
• To provide a universally applicable strategy for preventing the spread of non-functional mutants.

Main Methods:

• Development and computational modeling of a novel biomolecular controller.
• Analysis of the controller's performance across various synthetic gene circuits.
• Utilizing a resource-aware cell modeling simulation approach to link design parameters to population-level behavior.

Main Results:

• The proposed controller effectively depresses mutant cell growth irrespective of the mutated synthetic gene.
• The controller demonstrates superior performance compared to existing gene-specific mutation spread mitigation strategies.
• The controller can be deployed with diverse synthetic circuits without re-engineering, showcasing its adaptability.

Conclusions:

• The developed biomolecular controller offers a broadly applicable solution for enhancing genetic stability in synthetic biology.
• This adaptable design promises to mitigate mutation spread across a wider range of applications.
• The study provides a blueprint for employing resource-aware cell models in synthetic circuit design and analysis.