Redox signaling-driven modulation of microbial biosynthesis and biocatalysis

Na Chen, Na Du, Ruichen Shen, Tianpei He, Jing Xi, Jie Tan, Guangkai Bian, Yanbing Yang, Tiangang Liu, Weihong Tan, Lilei Yu () and Quan Yuan ()
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Na Chen: Wuhan University
Na Du: Wuhan University
Ruichen Shen: Hunan University
Tianpei He: Wuhan University
Jing Xi: Wuhan University
Jie Tan: Hunan University
Guangkai Bian: Chinese Academy of Sciences
Yanbing Yang: Wuhan University
Tiangang Liu: Wuhan University
Weihong Tan: Hunan University
Lilei Yu: Wuhan University
Quan Yuan: Wuhan University

Nature Communications, 2023, vol. 14, issue 1, 1-13

Abstract: Abstract Microbial communication can drive coordinated functions through sensing, analyzing and processing signal information, playing critical roles in biomanufacturing and life evolution. However, it is still a great challenge to develop effective methods to construct a microbial communication system with coordinated behaviors. Here, we report an electron transfer triggered redox communication network consisting of three building blocks including signal router, optical verifier and bio-actuator for microbial metabolism regulation and coordination. In the redox communication network, the Fe3+/Fe2+ redox signal can be dynamically and reversibly transduced, channeling electrons directly and specifically into bio-actuator cells through iron oxidation pathway. The redox communication network drives gene expression of electron transfer proteins and simultaneously facilitates the critical reducing power regeneration in the bio-actuator, thus enabling regulation of microbial metabolism. In this way, the redox communication system efficiently promotes the biomanufacturing yield and CO2 fixation rate of bio-actuator. Furthermore, the results demonstrate that this redox communication strategy is applicable both in co-culture and microbial consortia. The proposed electron transfer triggered redox communication strategy in this work could provide an approach for reducing power regeneration and metabolic optimization and could offer insights into improving biomanufacturing efficiency.

Date: 2023
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DOI: 10.1038/s41467-023-42561-3

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