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ACS Synth Biol. 2017 Oct 20;6(10):1851-1859. doi: 10.1021/acssynbio.7b00172. Epub 2017 Aug 9.

Fundamental Design Principles for Transcription-Factor-Based Metabolite Biosensors.

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Department of Mathematics, Imperial College London , London SW7 2AZ, U.K.
Department of Energy, Environmental & Chemical Engineering, Washington University in St. Louis , St. Louis, Missouri 63130, United States.


Metabolite biosensors are central to current efforts toward precision engineering of metabolism. Although most research has focused on building new biosensors, their tunability remains poorly understood and is fundamental for their broad applicability. Here we asked how genetic modifications shape the dose-response curve of biosensors based on metabolite-responsive transcription factors. Using the lac system in Escherichia coli as a model system, we built promoter libraries with variable operator sites that reveal interdependencies between biosensor dynamic range and response threshold. We developed a phenomenological theory to quantify such design constraints in biosensors with various architectures and tunable parameters. Our theory reveals a maximal achievable dynamic range and exposes tunable parameters for orthogonal control of dynamic range and response threshold. Our work sheds light on fundamental limits of synthetic biology designs and provides quantitative guidelines for biosensor design in applications such as dynamic pathway control, strain optimization, and real-time monitoring of metabolism.


dynamic pathway regulation; metabolic engineering; metabolite biosensor; model-based design; pathway optimization; transcriptional regulator

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