Literature DB >> 29413747

Design and optimization of genetically encoded biosensors for high-throughput screening of chemicals.

Hyun Gyu Lim1, Sungho Jang1, Sungyeon Jang1, Sang Woo Seo2, Gyoo Yeol Jung3.   

Abstract

Evolutionary engineering of microbes for the production of metabolites requires efficient screening methods to test vast mutant libraries. Genetically encoded biosensors are regarded as promising screening devices owing to their wide range of detectable ligands and great applicability to high-throughput screening and selection. Here, we reviewed the current progress in design and optimization of biosensors for high-throughput screening of chemicals. First, we summarized genetic parts of biosensors and strategies for their discovery and development. Next, we explained the properties of biosensors that are relevant to high-throughput screening. Finally, we described various methods for tuning biosensors to fulfill requirements of an efficient screening.
Copyright © 2018 Elsevier Ltd. All rights reserved.

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Year:  2018        PMID: 29413747     DOI: 10.1016/j.copbio.2018.01.011

Source DB:  PubMed          Journal:  Curr Opin Biotechnol        ISSN: 0958-1669            Impact factor:   9.740


  13 in total

1.  Tools and systems for evolutionary engineering of biomolecules and microorganisms.

Authors:  Sungho Jang; Minsun Kim; Jaeseong Hwang; Gyoo Yeol Jung
Journal:  J Ind Microbiol Biotechnol       Date:  2019-05-27       Impact factor: 3.346

Review 2.  Biosensor-enabled pathway optimization in metabolic engineering.

Authors:  Yuxi Teng; Jianli Zhang; Tian Jiang; Yusong Zou; Xinyu Gong; Yajun Yan
Journal:  Curr Opin Biotechnol       Date:  2022-02-11       Impact factor: 10.279

3.  Cheating the Cheater: Suppressing False-Positive Enrichment during Biosensor-Guided Biocatalyst Engineering.

Authors:  Vikas D Trivedi; Karishma Mohan; Todd C Chappell; Zachary J S Mays; Nikhil U Nair
Journal:  ACS Synth Biol       Date:  2021-12-16       Impact factor: 5.249

4.  Vibrio sp. dhg as a platform for the biorefinery of brown macroalgae.

Authors:  Hyun Gyu Lim; Dong Hun Kwak; Sungwoo Park; Sunghwa Woo; Jae-Seong Yang; Chae Won Kang; Beomhee Kim; Myung Hyun Noh; Sang Woo Seo; Gyoo Yeol Jung
Journal:  Nat Commun       Date:  2019-06-06       Impact factor: 14.919

Review 5.  Genetically encoded biosensors for lignocellulose valorization.

Authors:  Guadalupe Alvarez-Gonzalez; Neil Dixon
Journal:  Biotechnol Biofuels       Date:  2019-10-15       Impact factor: 6.040

Review 6.  Recent Advances in Synthetic Biology Approaches to Optimize Production of Bioactive Natural Products in Actinobacteria.

Authors:  Lei Li; Xiaocao Liu; Weihong Jiang; Yinhua Lu
Journal:  Front Microbiol       Date:  2019-11-05       Impact factor: 5.640

7.  Development of High-Performance Whole Cell Biosensors Aided by Statistical Modeling.

Authors:  Adokiye Berepiki; Ross Kent; Leopoldo F M Machado; Neil Dixon
Journal:  ACS Synth Biol       Date:  2020-02-17       Impact factor: 5.110

8.  A multiplexed, automated evolution pipeline enables scalable discovery and characterization of biosensors.

Authors:  Brent Townshend; Joy S Xiang; Gabriel Manzanarez; Eric J Hayden; Christina D Smolke
Journal:  Nat Commun       Date:  2021-03-04       Impact factor: 14.919

Review 9.  Application of combinatorial optimization strategies in synthetic biology.

Authors:  Gita Naseri; Mattheos A G Koffas
Journal:  Nat Commun       Date:  2020-05-15       Impact factor: 14.919

10.  Auxotrophic Selection Strategy for Improved Production of Coenzyme B12 in Escherichia coli.

Authors:  Myung Hyun Noh; Hyun Gyu Lim; Daeyeong Moon; Sunghoon Park; Gyoo Yeol Jung
Journal:  iScience       Date:  2020-02-07
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