4.7 Article

Engineering Modular Biosensors to Confer Metabolite-Responsive Regulation of Transcription

Journal

ACS SYNTHETIC BIOLOGY
Volume 6, Issue 2, Pages 311-325

Publisher

AMER CHEMICAL SOC
DOI: 10.1021/acssynbio.6b00184

Keywords

metabolite biosensor; protein engineering; promoter engineering; maltose binding protein; zinc finger DNA binding domain

Funding

  1. National Science Foundation [MCB-1341414]
  2. Environmental Protection Agency (STAR) [F13A30124]
  3. Northwestern University
  4. Northwestern University Graduate School Cluster in Biotechnology, Systems, and Synthetic Biology
  5. EPA [673528, F13A30124] Funding Source: Federal RePORTER

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Efforts to engineer microbial factories have benefitted from mining biological diversity and high throughput synthesis of novel enzymatic pathways, yet screening and optimizing metabolic pathways remain rate-limiting steps. Metabolite-responsive biosensors may help to address these persistent challenges by enabling the monitoring of metabolite levels in individual cells and metabolite-responsive feedback control. We are currently limited to naturally evolved biosensors, which are insufficient for monitoring many metabolites of interest. Thus, a method for engineering novel biosensors would be powerful, yet we lack a generalizable approach that enables the construction of a wide range of biosensors. As a step toward this goal, we here explore several strategies for converting a metabolite-binding protein into a metabolite-responsive transcriptional regulator. By pairing a modular protein design approach with a library of synthetic promoters and applying robust statistical analyses, we identified: strategies for engineering biosensor-regulated bacterial promoters and for achieving design-driven improvements of biosensor performance. We demonstrated the feasibility of this strategy by fusing a programmable DNA binding motif (zinc finger module) with a model ligand binding protein (maltose binding protein), to generate a novel biosensor conferring maltose-regulated gene expression. This systematic investigation provides insights that may guide the development of additional novel biosensors for diverse synthetic biology applications.

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