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Metab Eng. 2015 Sep;31:35-43. doi: 10.1016/j.ymben.2015.06.008. Epub 2015 Jul 2.

Applications and advances of metabolite biosensors for metabolic engineering.

Author information

1
Department of Energy, Environmental and Chemical Engineering, Washington University in St. Louis, 1 Brookings Drive, Saint Louis, MO 63130, USA.
2
Division of Biological & Biomedical Sciences, Washington University in St. Louis, 1 Brookings Drive, Saint Louis, MO 63130, USA.
3
Department of Energy, Environmental and Chemical Engineering, Washington University in St. Louis, 1 Brookings Drive, Saint Louis, MO 63130, USA; Division of Biological & Biomedical Sciences, Washington University in St. Louis, 1 Brookings Drive, Saint Louis, MO 63130, USA. Electronic address: fzhang@seas.wustl.edu.

Abstract

Quantification and regulation of pathway metabolites is crucial for optimization of microbial production bioprocesses. Genetically encoded biosensors provide the means to couple metabolite sensing to several outputs invaluable for metabolic engineering. These include semi-quantification of metabolite concentrations to screen or select strains with desirable metabolite characteristics, and construction of dynamic metabolite-regulated pathways to enhance production. Taking inspiration from naturally occurring systems, biosensor functions are based on highly diverse mechanisms including metabolite responsive transcription factors, two component systems, cellular stress responses, regulatory RNAs, and protein activities. We review recent developments in biosensors in each of these mechanistic classes, with considerations towards how these sensors are engineered, how new sensing mechanisms have led to improved function, and the advantages and disadvantages of each of these sensing mechanisms in relevant applications. We particularly highlight recent examples directly using biosensors to improve microbial production, and the great potential for biosensors to further inform metabolic engineering practices.

KEYWORDS:

Dynamic pathway regulation; Metabolic engineering; Metabolite biosensor; Pathway optimization; Synthetic biology

PMID:
26142692
DOI:
10.1016/j.ymben.2015.06.008
[Indexed for MEDLINE]

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