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A Theoretical Framework for Implementable Nucleic Acids Feedback Systems

  • Nuno M.G. Paulino
  • , Mathias Foo
  • , Tom F.A. de Greef
  • , Jongmin Kim
  • , Declan G. Bates (Corresponding author)

Research output: Contribution to journal › Article › Academic › peer-review

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Abstract

Chemical reaction networks can be utilised as basic components for nucleic acid feedback control systems’ design for Synthetic Biology application. DNA hybridisation and programmed strand-displacement reactions are effective primitives for implementation. However, the experimental validation and scale-up of nucleic acid control systems are still considerably falling behind their theoretical designs. To aid with the progress heading into experimental implementations, we provide here chemical reaction networks that represent two fundamental classes of linear controllers: integral and static negative state feedback. We reduced the complexity of the networks by finding designs with fewer reactions and chemical species, to take account of the limits of current experimental capabilities and mitigate issues pertaining to crosstalk and leakage, along with toehold sequence design. The supplied control circuits are quintessential candidates for the first experimental validations of nucleic acid controllers, since they have a number of parameters, species, and reactions small enough for viable experimentation with current technical capabilities, but still represent challenging feedback control systems. They are also well suited to further theoretical analysis to verify results on the stability, performance, and robustness of this important new class of control systems.

Keywords: feedback control; chemical reaction networks; nucleic acids; strand displacement circuits; synthetic biology
Original languageEnglish
Article number466
Number of pages31
JournalBioengineering
Volume10
Issue number4
DOIs
Publication statusPublished - 12 Apr 2023

Keywords

  • chemical reaction networks
  • feedback control
  • nucleic acids
  • strand displacement circuits
  • synthetic biology

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