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Engineering repressors with coevolutionary cues facilitates toggle switches with a master reset.

Rey P Dimas1, Xian-Li Jiang2, Jose Alberto de la Paz2

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Summary

Scientists engineered modular repressors for complex biological signal processing. This framework enables custom genetic circuits, like living diagnostics, by predicting component compatibility using coevolutionary data.

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Area of Science:

  • Synthetic biology
  • Genetic engineering
  • Systems biology

Background:

  • Allosteric transcriptional repressors combine environmental sensing modules (ESMs) and DNA recognition modules (DRMs) for biological control.
  • Rewiring genetic networks requires flexible tools for complex signal processing.

Purpose of the Study:

  • To engineer hybrid repressors by fusing distinct ESMs and DRMs for flexible genetic network control.
  • To develop a predictive model for ESM-DRM compatibility using coevolutionary traits.
  • To create a system of toggle switches with a master OFF signal for diverse biological applications.

Main Methods:

  • Constructing hybrid repressors by fusing different environmental sensing modules and DNA recognition modules.
  • Utilizing coevolutionary traits among LacI homologs to build a compatibility prediction model.
  • Testing the performance of 40 engineered repressors against model predictions.

Main Results:

  • The developed model accurately predicted the performance of 40 engineered repressors.
  • A system of multiple toggle switches with a master OFF signal was successfully created.
  • Each engineered activity could be switched ON by specific chemicals and OFF by a common signal.

Conclusions:

  • Modular repressors designed with coevolutionary information offer a powerful framework for engineering genetic circuits.
  • This approach enables complex signal processing and the development of novel applications like living diagnostics.
  • The study demonstrates a versatile platform for exploring diverse circuit topologies in synthetic biology.