Construction of Escherichia coli Whole-Cell Biosensors for Statin Efficacy and Production Test

Frontiers in Cell and Developmental Biology

Yunshan Wang¹  Huanjie Li¹  Luying Xun³  Rui Zhao⁴  Qingda Wang⁴  Huaiwei Liu⁴ 

[1] Medical Research and Laboratory Diagnostic Center, Jinan Central Hospital, Cheeloo College of Medicine, Shandong University, Jinan, China;School of Medicine, Cheeloo College of Medicine, Shandong University, Jinan, China;School of Molecular Biosciences, Washington State University, Pullman, WA, United States;State Key Laboratory of Microbial Technology, Shandong University, Qingdao, China;

关键词: synthetic biology;    biosensor;    statin;    precision medicine;    HMGR;   

DOI  :  10.3389/fcell.2020.00404

来源: DOAJ

【 摘 要 】

Statins are widely used cholesterol-lowering drugs. Their potential application in anti-cancer treatment is also under investigation. The individual variance in statin response has been observed, which may be caused by the variation in human HMG-CoA reductase (hHMGR)—the inhibition target of statin drugs. Herein, we reported the design and construction of two Escherichia coli whole-cell biosensors. The first one is statin-efficacy testing sensor, which is composed of two separate modules: a hybrid mevalonate (MVA) pathway and a HMG-CoA sensing system. A truncated hHMGR was used as the key enzyme of the MVA pathway and a promiscuous transcription factor (TF) BsFapR was used as the HMG-CoA sensor. When hHMGR was inhibited by statins, HMG-CoA accumulated intracellularly and was sensed by BsFapR, which subsequently turned on its cognate promoter. This biosensor has the potential to be used as a “precision medicine” tool—selecting potent statin drugs for individual patients. The second one is a statin-production testing sensor, which is based on another promiscuous TF AraCM that can sense statins. This biosensor can be used in optimization of statin-producing strains. The prototypes of these two biosensors were successfully constructed and their further optimization is highly expected.

【 授权许可】

Unknown