Mitigating Winner-Take-All Resource Competition through Antithetic Control Mechanism.

Suchana Chakravarty, Rishabh Guttal, Rong Zhang, Xiao-Jun Tian
Author Information
  1. Suchana Chakravarty: School of Biological and Health Systems Engineering, Arizona State University, Tempe, Arizona 85281, United States.
  2. Rishabh Guttal: School of Life Sciences, Arizona State University, Tempe, Arizona 85281, United States.
  3. Rong Zhang: School of Biological and Health Systems Engineering, Arizona State University, Tempe, Arizona 85281, United States.
  4. Xiao-Jun Tian: School of Biological and Health Systems Engineering, Arizona State University, Tempe, Arizona 85281, United States. ORCID

Abstract

Competition among genes for limited transcriptional and translational resources impairs the functionality and modularity of synthetic gene circuits. Traditional control mechanisms, such as feedforward and negative feedback loops, have been proposed to alleviate these challenges, but they often focus on individual modules or inadvertently increase the burden on the system. In this study, we introduce three novel multimodule control strategies���local regulation, global regulation, and negatively competitive regulation (NCR)���that employ an antithetic regulatory mechanism to mitigate resource competition. Our systematic analysis reveals that while all three control mechanisms can alleviate resource competition to some extent, the NCR controller consistently outperforms both the global and local controllers. This superior performance stems from the unique architecture of the NCR controller, which is independent of specific parameter choices. Notably, the NCR controller not only facilitates the activation of less active modules through cross-activation mechanisms but also effectively utilizes the resource consumption within the controller itself. These findings emphasize the critical role of carefully designing the topology of multimodule controllers to ensure robust performance.

Keywords

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Grants

  1. R35 GM142896/NIGMS NIH HHS

MeSH Term

Gene Regulatory Networks
Synthetic Biology
Feedback, Physiological

Word Cloud

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