Sensor-regulator and RNAi based bifunctional dynamic control network for engineered microbial synthesis

Yaping Yang, Yuheng Lin, Jian Wang, Yifei Wu, Ruihua Zhang, Mengyin Cheng, Xiaolin Shen, Jia Wang, Zhenya Chen, Chenyi Li, Qipeng Yuan and Yajun Yan ()
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Yaping Yang: The University of Georgia
Yuheng Lin: The University of Georgia
Jian Wang: The University of Georgia
Yifei Wu: Beijing University of Chemical Technology
Ruihua Zhang: The University of Georgia
Mengyin Cheng: The University of Georgia
Xiaolin Shen: Beijing University of Chemical Technology
Jia Wang: Beijing University of Chemical Technology
Zhenya Chen: Beijing University of Chemical Technology
Chenyi Li: The University of Georgia
Qipeng Yuan: Beijing University of Chemical Technology
Yajun Yan: The University of Georgia

Nature Communications, 2018, vol. 9, issue 1, 1-10

Abstract: Abstract Writing artificial logic and dynamic function into complex cellular background to achieve desired phenotypes or improved outputs calls for the development of new genetic tools as well as their innovative use. In this study, we present a sensor-regulator and RNAi-based bifunctional dynamic control network that can provide simultaneous upregulation and downregulation of cellular metabolism for engineered biosynthesis. The promoter-regulator-mediated upregulation function and its transduced downregulation function through RNAi are systematically verified and characterized. We apply this dynamic control network to regulate the phosphoenolpyruvate metabolic node in Escherichia coli and achieve autonomous distribution of carbon flux between its native metabolism and the engineered muconic acid biosynthetic pathway. This allows muconic acid biosynthesis to reach 1.8 g L−1. This study also suggests the circumstances where dynamic control approaches are likely to take effects.

Date: 2018
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DOI: 10.1038/s41467-018-05466-0

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