Characterizing and Engineering a Succinate-Responsive Biosensor System in <i>Escherichia coli</i>

Metabolic engineering enables the sustainable production of valuable compounds, but challenges such as metabolic imbalances and limited regulatory tools hinder optimal yields and efficiencies. Transcription factor (TF)-based biosensors have emerged as robust solutions, allowing dynamic sensing and regulation of intracellular metabolites. However, their limited diversity often restricts their broader applications in metabolic engineering. To overcome this limitation, it is essential to develop biosensors that are responsive to central metabolic intermediates, enabling more versatile pathway control. In this study, we characterized a succinate-responsive biosensor system regulated by the IclR family TF, PcaR, and elucidated the dual-function mechanism observed in this PcaR biosensor system. Initially, we fine-tuned the expression of PcaR, fully recovering the corresponding promoter strength. Then, we discovered a dual-function mechanism of PcaR through homologue pairing, further elucidated by employing site-directed mutagenesis and promoter engineering. Meanwhile, we established a succinate-responsive biosensor library guided by PcaR-succinate complex analysis with varied dynamic ranges, identifying the superior P1-AII variant with nearly a 33-fold improvement in dynamic range. Finally, we constructed a bifunctional regulatory circuit controlled by succinate and a single regulator, demonstrating its potential for dynamic metabolic regulation. Given the primary role of succinate in central metabolism, the engineered PcaR biosensor system provides a promising tool for real-time metabolic monitoring and optimization of microbial production.

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Publication Details

Journal
ACS Synthetic Biology
Published
2025-08-08
DOI
https://doi.org/10.1021/acssynbio.5c00290
Primary Topic
Gene Regulatory Network Analysis
Type
article
Field-Weighted Citation Impact
0.00

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article

Characterizing and Engineering a Succinate-Responsive Biosensor System in Escherichia coli

Yingxiao Qian, Chad M. Parish, Yajun Yan, Yusong Zou et al.
ACS Synthetic Biology
Gene Regulatory Network Analysis
article

Characterizing and Engineering a Succinate-Responsive Biosensor System in Escherichia coli

Yingxiao Qian, Chad M. Parish, Yajun Yan, Yusong Zou, Logan Huddle
article en

Abstract

Metabolic engineering enables the sustainable production of valuable compounds, but challenges such as metabolic imbalances and limited regulatory tools hinder optimal yields and efficiencies. Transcription factor (TF)-based biosensors have emerged as robust solutions, allowing dynamic sensing and regulation of intracellular metabolites. However, their limited diversity often restricts their broader applications in metabolic engineering. To overcome this limitation, it is essential to develop biosensors that are responsive to central metabolic intermediates, enabling more versatile pathway control. In this study, we characterized a succinate-responsive biosensor system regulated by the IclR family TF, PcaR, and elucidated the dual-function mechanism observed in this PcaR biosensor system. Initially, we fine-tuned the expression of PcaR, fully recovering the corresponding promoter strength. Then, we discovered a dual-function mechanism of PcaR through homologue pairing, further elucidated by employing site-directed mutagenesis and promoter engineering. Meanwhile, we established a succinate-responsive biosensor library guided by PcaR-succinate complex analysis with varied dynamic ranges, identifying the superior P1-AII variant with nearly a 33-fold improvement in dynamic range. Finally, we constructed a bifunctional regulatory circuit controlled by succinate and a single regulator, demonstrating its potential for dynamic metabolic regulation. Given the primary role of succinate in central metabolism, the engineered PcaR biosensor system provides a promising tool for real-time metabolic monitoring and optimization of microbial production.

ACS Synthetic BiologyVol. 14(9)
University of Georgia (US), Applied Materials (United States) (US)
University of Georgia, National Institute of General Medical Sciences
Openalex Percentile: Top 82%
Gene Regulatory Network Analysis
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