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Engineering quorum sensing-based genetic circuits enhances growth and productivity robustness of industrial E. coli at low pH

Xiaofang Yan, Anqi Bu, Yanfei Yuan, Xin Zhang, Zhanglin Lin, Xiaofeng Yang

2024Microbial Cell Factories14 citationsDOIOpen Access PDF

Abstract

Microbial organisms hold significant potential for converting renewable substrates into valuable chemicals. Low pH fermentation in industrial settings offers key advantages, including reduced neutralizer usage and decreased wastewater generation, particularly in the production of amino acids and organic acids. Engineering acid-tolerant strains represents a viable strategy to enhance productivity in acidic environments. Synthetic biology provides dynamic regulatory tools, such as gene circuits, facilitating precise expression of acid resistance (AR) modules in a just-in-time and just-enough manner. In this study, we aimed to enhance the robustness and productivity of Escherichia coli , a workhorse for amino acid and organic acid production, in industrial fermentation under mild acidic conditions. We employed an Esa-type quorum sensing circuit to dynamically regulate the expression of an AR module (DsrA-Hfq) in a just-in-time and just-enough manner. Through careful engineering of the critical promoter P esaS and stepwise evaluation, we developed an optimal Esa-P BD (L) circuit that conferred upon an industrial E. coli strain SCEcL3 comparable lysine productivity and enhanced yield at pH 5.5 compared to the parent strain at pH 6.8. This study exemplifies the practical application of gene circuits in industrial environments, which present challenges far beyond those of well-controlled laboratory conditions.

Topics & Concepts

Quorum sensingRobustness (evolution)ProductivityElectronic circuitSynthetic biologyBiochemical engineeringBiotechnologyComputer scienceBiologyEngineeringComputational biologyGeneticsBacteriaGeneEconomicsBiofilmElectrical engineeringMacroeconomicsMicrobial Metabolic Engineering and BioproductionBacterial Genetics and BiotechnologyGene Regulatory Network Analysis
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