Literature DB >> 26142692

Applications and advances of metabolite biosensors for metabolic engineering.

Di Liu1, Trent Evans2, Fuzhong Zhang3.   

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.
Copyright © 2015 International Metabolic Engineering Society. Published by Elsevier Inc. All rights reserved.

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

Mesh:

Substances:

Year:  2015        PMID: 26142692     DOI: 10.1016/j.ymben.2015.06.008

Source DB:  PubMed          Journal:  Metab Eng        ISSN: 1096-7176            Impact factor:   9.783


  47 in total

1.  Design of a bistable switch to control cellular uptake.

Authors:  Diego A Oyarzún; Madalena Chaves
Journal:  J R Soc Interface       Date:  2015-12-06       Impact factor: 4.118

Review 2.  Tailor-made transcriptional biosensors for optimizing microbial cell factories.

Authors:  Brecht De Paepe; Gert Peters; Pieter Coussement; Jo Maertens; Marjan De Mey
Journal:  J Ind Microbiol Biotechnol       Date:  2016-11-11       Impact factor: 3.346

3.  Fluorescence lifetime microscopy of NADH distinguishes alterations in cerebral metabolism in vivo.

Authors:  Mohammad A Yaseen; Jason Sutin; Weicheng Wu; Buyin Fu; Hana Uhlirova; Anna Devor; David A Boas; Sava Sakadžić
Journal:  Biomed Opt Express       Date:  2017-04-03       Impact factor: 3.732

4.  Performing selections under dynamic conditions for synthetic biology applications.

Authors:  Jessica M Lindle; Mary J Dunlop
Journal:  Integr Biol (Camb)       Date:  2016-01-13       Impact factor: 2.192

5.  Dynamic metabolic control: towards precision engineering of metabolism.

Authors:  Di Liu; Ahmad A Mannan; Yichao Han; Diego A Oyarzún; Fuzhong Zhang
Journal:  J Ind Microbiol Biotechnol       Date:  2018-01-29       Impact factor: 3.346

Review 6.  The emergence of adaptive laboratory evolution as an efficient tool for biological discovery and industrial biotechnology.

Authors:  Troy E Sandberg; Michael J Salazar; Liam L Weng; Bernhard O Palsson; Adam M Feist
Journal:  Metab Eng       Date:  2019-08-08       Impact factor: 9.783

Review 7.  Bacterial metabolic heterogeneity: origins and applications in engineering and infectious disease.

Authors:  Trent D Evans; Fuzhong Zhang
Journal:  Curr Opin Biotechnol       Date:  2020-06-20       Impact factor: 9.740

8.  Layered dynamic regulation for improving metabolic pathway productivity in Escherichia coli.

Authors:  Stephanie J Doong; Apoorv Gupta; Kristala L J Prather
Journal:  Proc Natl Acad Sci U S A       Date:  2018-03-05       Impact factor: 11.205

9.  Genetically Encoded Ratiometric RNA-Based Sensors for Quantitative Imaging of Small Molecules in Living Cells.

Authors:  Rigumula Wu; Aruni P K K Karunanayake Mudiyanselage; Fatemeh Shafiei; Bin Zhao; Yousef Bagheri; Qikun Yu; Kathleen McAuliffe; Kewei Ren; Mingxu You
Journal:  Angew Chem Int Ed Engl       Date:  2019-10-24       Impact factor: 15.336

10.  129Xe NMR-Protein Sensor Reveals Cellular Ribose Concentration.

Authors:  Serge D Zemerov; Benjamin W Roose; Kelsey L Farenhem; Zhuangyu Zhao; Madison A Stringer; Aaron R Goldman; David W Speicher; Ivan J Dmochowski
Journal:  Anal Chem       Date:  2020-09-23       Impact factor: 6.986

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