4.7 Article

Design of Synthetic Quorum Sensing Achieving Induction Timing-Independent Signal Stabilization for Dynamic Metabolic Engineering of E. coli

Journal

ACS SYNTHETIC BIOLOGY
Volume 10, Issue 6, Pages 1384-1393

Publisher

AMER CHEMICAL SOC
DOI: 10.1021/acssynbio.1c00008

Keywords

Escherichia coli; genetic circuit; metabolome analysis; quorum sensing

Funding

  1. JSPS KAKENHI [JP20H02544, JP17H06304, JP18K14065, JP17H06299]
  2. Adaptable and Seamless Technology Transfer Program through Target-Driven R&D (A-STEP) from Japan Science and Technology Agency (JST)
  3. Japan Association for Chemical Innovation (JACI)
  4. Basic Science Research Project from the Sumitomo Foundation

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This study redesigned the QS-MTS to improve its stability and efficiency in metabolic regulation, which was confirmed through metabolome analysis. The redesigned QS-MTS showed better performance in long-term processes such as fed-batch fermentation compared to the conventional QS-MTS. A circuit redesign based on dynamic characteristic evaluation and metabolome analysis was presented for metabolic flux control.
Dynamic metabolic engineering that harnesses synthetic biological tools is a next-generation strategy for microbial chemical and fuel production. We previously reported a synthetic quorum sensing system combined with a metabolic toggle switch (QS-MTS) in E. coli. It autonomously redirected endogenous metabolic flux toward the synthetic metabolic pathway and improved biofuel production. However, its functions and effects on host metabolism were attenuated by induction timing delay. Here, we redesigned the QS-MTS to stabilize QS signaling efficiency and metabolic regulation. We performed a metabolome analysis to clarify the effects of QS-MTS redesign on host metabolism. We compared the contributions of conventional and redesigned QS-MTS to fed-batch fermentation. The redesigned QS-MTS was more conducive than the conventional QS-MTS to long-term processes such as fed-batch fermentation. Here, we present a circuit redesign for metabolic flux control based on dynamic characteristic evaluation and metabolome analysis.

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