Multi-Layer Autocatalytic Feedback Enables Integral Control Amidst Resource Competition and Across Scales

Area of Science:

• Synthetic biology
• Control theory
• Microbial ecology

Background:

• Integral feedback control is crucial for robust protein expression in dynamic cellular environments.
• Autocatalytic integral feedback controllers offer simplicity and robustness but face limitations like resource competition.
• Existing strategies require advancement to fully exploit controller potential in complex biological systems.

Purpose of the Study:

• To address limitations of current integral feedback controllers by introducing a multilayer feedback strategy.
• To develop population-level and multicellular integral feedback controllers for synthetic biology applications.
• To provide a mathematical framework for modeling resource competition in genetic networks.

Main Methods:

• Designed and implemented multilayer feedback strategies for autocatalytic controllers.
• Developed a generalized mathematical framework to model resource competition in genetic networks.
• Applied controllers to concentration regulation and ratiometric control tasks in synthetic biology.

Main Results:

• Achieved population-level integral feedback and multicellular integrators through coordinated cell population interactions.
• Demonstrated robust regulation of gene expression, gene ratios, population growth, and coculture composition.
• Validated controller effectiveness in engineered microbial ecosystems, showcasing adaptability across biological scales.

Conclusions:

• Multilayer autocatalytic controllers offer a versatile approach for robust adaptation and homeostasis.
• The developed framework facilitates the design of intracellular control circuits and multicellular systems.
• This work advances synthetic biology by enabling precise control from subcellular to multicellular levels.