文献类型：期刊文献

英文题名：Transcription Factor Engineering for High-Throughput Strain Evolution and Organic Acid Bioproduction: A Review

作者：Li, Jia-Wei[1];Zhang, Xiao-Yan[1];Wu, Hui[1];Bai, Yun-Peng[1]

机构：[1]East China Univ Sci & Technol, State Key Lab Bioreactor Engn, Shanghai, Peoples R China

年份：2020

卷号：8

外文期刊名：FRONTIERS IN BIOENGINEERING AND BIOTECHNOLOGY

收录：;EI(收录号：20201108288176);WOS:【SCI-EXPANDED(收录号:WOS:000518953900001)】；

基金：We are grateful to China's National Key Research and Development Program (2016YFA0204300), the Shanghai Natural Science Foundation (No. 18ZR1409900), and the Key Project of the Shanghai Science and Technology Committee (18DZ1112703) for supporting this work.

语种：英文

外文关键词：transcription factor; biosensor; metabolic engineering; synthetic biology; organic acid; high-throughput screening

摘要：Metabolic regulation of gene expression for the microbial production of fine chemicals, such as organic acids, is an important research topic in post-genomic metabolic engineering. In particular, the ability of transcription factors (TFs) to respond precisely in time and space to various small molecules, signals and stimuli from the internal and external environment is essential for metabolic pathway engineering and strain development. As a key component, TFs are used to construct many biosensors in vivo using synthetic biology methods, which can be used to monitor the concentration of intracellular metabolites in organic acid production that would otherwise remain "invisible" within the intracellular environment. TF-based biosensors also provide a high-throughput screening method for rapid strain evolution. Furthermore, TFs are important global regulators that control the expression levels of key enzymes in organic acid biosynthesis pathways, therefore determining the outcome of metabolic networks. Here we review recent advances in TF identification, engineering, and applications for metabolic engineering, with an emphasis on metabolite monitoring and high-throughput strain evolution for the organic acid bioproduction.