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Integrating recombinase-based feedback and feedforward control for optimal resource decoupling
Rixin Zhang1, Rong Zhang1, Xiao-Jun Tian1
1School of Biological and Health Systems Engineering, Arizona State University, Tempe, AZ 85281, United States.
None:
Resource competition disrupts circuit modularity by introducing unintended coupling between otherwise independent gene modules, thereby compromising genetic circuit function. While various control strategies have been explored, their complexity or limited efficacy have hindered broader application. Here, we present the Re-NF-FF-Controller, a recombinase-based strategy that integrates negative feedback and feedforward regulation via promoter flipping to mitigate resource competition. Computational modeling and experimental validation demonstrate that Re-NF-FF-Controller effectively reduces resource coupling, ensuring robust gene expression and modularity. Moreover, its tunability allows for performance optimization through straightforward adjustments of recombinase enzyme levels. This strategy offers a versatile and easily implementable solution for designing reliable synthetic biological systems.
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