Literature DB >> 35158314

Biosensor-enabled pathway optimization in metabolic engineering.

Yuxi Teng1, Jianli Zhang1, Tian Jiang1, Yusong Zou1, Xinyu Gong1, Yajun Yan2.   

Abstract

Microbes can convert inexpensive renewable substrates to valuable metabolites by their natural metabolic pathways. To maximize the productivity, the pathways yet require further optimization, which remains challenging for our limited knowledge of complex biology. Genetically encoded biosensors are able to detect metabolite concentrations or environmental changes and transfer these inputs to measurable or actionable outputs, thus providing enabling regulation and monitoring tools for complicated pathway optimization. Here, we review recent advances in biosensor-mediated dynamic regulation and strain screening for the highest microbial production of diverse desirable products.
Copyright © 2022 Elsevier Ltd. All rights reserved.

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Year:  2022        PMID: 35158314      PMCID: PMC9177593          DOI: 10.1016/j.copbio.2022.102696

Source DB:  PubMed          Journal:  Curr Opin Biotechnol        ISSN: 0958-1669            Impact factor:   10.279


  62 in total

1.  A biosensor-based approach reveals links between efflux pump expression and cell cycle regulation in pleiotropic drug resistance of yeast.

Authors:  Jian Li; Kristen Kolberg; Ulrich Schlecht; Robert P St Onge; Ana Maria Aparicio; Joe Horecka; Ronald W Davis; Maureen E Hillenmeyer; Colin J B Harvey
Journal:  J Biol Chem       Date:  2018-12-04       Impact factor: 5.157

2.  Repurposing type III polyketide synthase as a malonyl-CoA biosensor for metabolic engineering in bacteria.

Authors:  Dongsoo Yang; Won Jun Kim; Seung Min Yoo; Jong Hyun Choi; Shin Hee Ha; Mun Hee Lee; Sang Yup Lee
Journal:  Proc Natl Acad Sci U S A       Date:  2018-09-19       Impact factor: 11.205

Review 3.  Applications of genetically-encoded biosensors for the construction and control of biosynthetic pathways.

Authors:  Joshua K Michener; Kate Thodey; Joe C Liang; Christina D Smolke
Journal:  Metab Eng       Date:  2011-09-18       Impact factor: 9.783

Review 4.  Biosensor-based engineering of biosynthetic pathways.

Authors:  Jameson K Rogers; Noah D Taylor; George M Church
Journal:  Curr Opin Biotechnol       Date:  2016-03-18       Impact factor: 9.740

Review 5.  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

6.  Design and Characterization of Rapid Optogenetic Circuits for Dynamic Control in Yeast Metabolic Engineering.

Authors:  Evan M Zhao; Makoto A Lalwani; Robert J Lovelett; Sergio A García-Echauri; Shannon M Hoffman; Christopher L Gonzalez; Jared E Toettcher; Ioannis G Kevrekidis; José L Avalos
Journal:  ACS Synth Biol       Date:  2020-11-24       Impact factor: 5.110

7.  Quorum-sensing linked RNA interference for dynamic metabolic pathway control in Saccharomyces cerevisiae.

Authors:  T C Williams; N J H Averesch; G Winter; M R Plan; C E Vickers; L K Nielsen; J O Krömer
Journal:  Metab Eng       Date:  2015-03-16       Impact factor: 9.783

8.  Exploiting nongenetic cell-to-cell variation for enhanced biosynthesis.

Authors:  Yi Xiao; Christopher H Bowen; Di Liu; Fuzhong Zhang
Journal:  Nat Chem Biol       Date:  2016-03-21       Impact factor: 15.040

9.  Combining genetically-encoded biosensors with high throughput strain screening to maximize erythritol production in Yarrowia lipolytica.

Authors:  Xueliang Qiu; Peng Xu; Xinrui Zhao; Guocheng Du; Juan Zhang; Jianghua Li
Journal:  Metab Eng       Date:  2020-03-26       Impact factor: 9.783

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

Authors:  Yaping Yang; Yuheng Lin; Jian Wang; Yifei Wu; Ruihua Zhang; Mengyin Cheng; Xiaolin Shen; Jia Wang; Zhenya Chen; Chenyi Li; Qipeng Yuan; Yajun Yan
Journal:  Nat Commun       Date:  2018-08-02       Impact factor: 14.919

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