Literature DB >> 26453944

Genome scale engineering techniques for metabolic engineering.

Rongming Liu1, Marcelo C Bassalo2, Ramsey I Zeitoun3, Ryan T Gill4.   

Abstract

Metabolic engineering has expanded from a focus on designs requiring a small number of genetic modifications to increasingly complex designs driven by advances in genome-scale engineering technologies. Metabolic engineering has been generally defined by the use of iterative cycles of rational genome modifications, strain analysis and characterization, and a synthesis step that fuels additional hypothesis generation. This cycle mirrors the Design-Build-Test-Learn cycle followed throughout various engineering fields that has recently become a defining aspect of synthetic biology. This review will attempt to summarize recent genome-scale design, build, test, and learn technologies and relate their use to a range of metabolic engineering applications.
Copyright © 2015 International Metabolic Engineering Society. Published by Elsevier Inc. All rights reserved.

Keywords:  Design-Build-Test-Learn; Genome scale engineering; Metabolic engineering; Synthetic biology

Mesh:

Substances:

Year:  2015        PMID: 26453944     DOI: 10.1016/j.ymben.2015.09.013

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


  12 in total

Review 1.  Virulence factor activity relationships (VFARs): a bioinformatics perspective.

Authors:  Hassan Waseem; Maggie R Williams; Tiffany Stedtfeld; Benli Chai; Robert D Stedtfeld; James R Cole; James M Tiedje; Syed A Hashsham
Journal:  Environ Sci Process Impacts       Date:  2017-03-22       Impact factor: 4.238

Review 2.  Recent advances in CRISPR/Cas9 mediated genome editing in Bacillus subtilis.

Authors:  Kun-Qiang Hong; Ding-Yu Liu; Tao Chen; Zhi-Wen Wang
Journal:  World J Microbiol Biotechnol       Date:  2018-09-29       Impact factor: 3.312

Review 3.  Recent advances in genetic engineering tools based on synthetic biology.

Authors:  Jun Ren; Jingyu Lee; Dokyun Na
Journal:  J Microbiol       Date:  2020-01-02       Impact factor: 3.422

Review 4.  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 5.  Biofuel metabolic engineering with biosensors.

Authors:  Stacy-Anne Morgan; Dana C Nadler; Rayka Yokoo; David F Savage
Journal:  Curr Opin Chem Biol       Date:  2016-10-18       Impact factor: 8.822

6.  An automated Design-Build-Test-Learn pipeline for enhanced microbial production of fine chemicals.

Authors:  Pablo Carbonell; Adrian J Jervis; Christopher J Robinson; Cunyu Yan; Mark Dunstan; Neil Swainston; Maria Vinaixa; Katherine A Hollywood; Andrew Currin; Nicholas J W Rattray; Sandra Taylor; Reynard Spiess; Rehana Sung; Alan R Williams; Donal Fellows; Natalie J Stanford; Paul Mulherin; Rosalind Le Feuvre; Perdita Barran; Royston Goodacre; Nicholas J Turner; Carole Goble; George Guoqiang Chen; Douglas B Kell; Jason Micklefield; Rainer Breitling; Eriko Takano; Jean-Loup Faulon; Nigel S Scrutton
Journal:  Commun Biol       Date:  2018-06-08

7.  Impact framework: A python package for writing data analysis workflows to interpret microbial physiology.

Authors:  Naveen Venayak; Kaushik Raj; Radhakrishnan Mahadevan
Journal:  Metab Eng Commun       Date:  2019-04-04

Review 8.  Predicting Drug Resistance Using Deep Mutational Scanning.

Authors:  Gur Pines; Reilly G Fankhauser; Carrie A Eckert
Journal:  Molecules       Date:  2020-05-11       Impact factor: 4.411

9.  mSphere of Influence: Synthetic Biology of Natural Product Biosynthesis.

Authors:  Mark C Walker
Journal:  mSphere       Date:  2020-01-08       Impact factor: 4.389

Review 10.  Repositioning microbial biotechnology against COVID-19: the case of microbial production of flavonoids.

Authors:  Tobias Goris; Álvaro Pérez-Valero; Igor Martínez; Dong Yi; Luis Fernández-Calleja; David San León; Uwe T Bornscheuer; Patricia Magadán-Corpas; Felipe Lombó; Juan Nogales
Journal:  Microb Biotechnol       Date:  2020-10-13       Impact factor: 5.813

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