Literature DB >> 25576846

Computational methods in metabolic engineering for strain design.

Matthew R Long1, Wai Kit Ong2, Jennifer L Reed3.   

Abstract

Metabolic engineering uses genetic approaches to control microbial metabolism to produce desired compounds. Computational tools can identify new biological routes to chemicals and the changes needed in host metabolism to improve chemical production. Recent computational efforts have focused on exploring what compounds can be made biologically using native, heterologous, and/or enzymes with broad specificity. Additionally, computational methods have been developed to suggest different types of genetic modifications (e.g. gene deletion/addition or up/down regulation), as well as suggest strategies meeting different criteria (e.g. high yield, high productivity, or substrate co-utilization). Strategies to improve the runtime performances have also been developed, which allow for more complex metabolic engineering strategies to be identified. Future incorporation of kinetic considerations will further improve strain design algorithms.
Copyright © 2015 Elsevier Ltd. All rights reserved.

Mesh:

Year:  2015        PMID: 25576846     DOI: 10.1016/j.copbio.2014.12.019

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


  31 in total

Review 1.  In Silico Constraint-Based Strain Optimization Methods: the Quest for Optimal Cell Factories.

Authors:  Paulo Maia; Miguel Rocha; Isabel Rocha
Journal:  Microbiol Mol Biol Rev       Date:  2015-11-25       Impact factor: 11.056

2.  Genome-Scale Metabolic Modeling from Yeast to Human Cell Models of Complex Diseases: Latest Advances and Challenges.

Authors:  Yu Chen; Gang Li; Jens Nielsen
Journal:  Methods Mol Biol       Date:  2019

Review 3.  Engineering biological systems using automated biofoundries.

Authors:  Ran Chao; Shekhar Mishra; Tong Si; Huimin Zhao
Journal:  Metab Eng       Date:  2017-06-07       Impact factor: 9.783

4.  Computational design and engineering of an Escherichia coli strain producing the nonstandard amino acid para-aminophenylalanine.

Authors:  Ali R Zomorrodi; Colin Hemez; Pol Arranz-Gibert; Terrence Wu; Farren J Isaacs; Daniel Segrè
Journal:  iScience       Date:  2022-06-09

5.  Introduction of NADH-dependent nitrate assimilation in Synechococcus sp. PCC 7002 improves photosynthetic production of 2-methyl-1-butanol and isobutanol.

Authors:  Hugh M Purdy; Brian F Pfleger; Jennifer L Reed
Journal:  Metab Eng       Date:  2021-11-10       Impact factor: 8.829

Review 6.  Quantitative metabolic fluxes regulated by trans-omic networks.

Authors:  Satoshi Ohno; Saori Uematsu; Shinya Kuroda
Journal:  Biochem J       Date:  2022-03-31       Impact factor: 3.766

7.  Model-guided development of an evolutionarily stable yeast chassis.

Authors:  Filipa Pereira; Helder Lopes; Paulo Maia; Britta Meyer; Justyna Nocon; Paula Jouhten; Dimitrios Konstantinidis; Eleni Kafkia; Miguel Rocha; Peter Kötter; Isabel Rocha; Kiran R Patil
Journal:  Mol Syst Biol       Date:  2021-07       Impact factor: 11.429

Review 8.  Shikimic Acid Production in Escherichia coli: From Classical Metabolic Engineering Strategies to Omics Applied to Improve Its Production.

Authors:  Juan Andrés Martínez; Francisco Bolívar; Adelfo Escalante
Journal:  Front Bioeng Biotechnol       Date:  2015-09-23

Review 9.  Systems Biology of Microbial Exopolysaccharides Production.

Authors:  Ozlem Ates
Journal:  Front Bioeng Biotechnol       Date:  2015-12-18

Review 10.  Applications of Genome-Scale Metabolic Models in Biotechnology and Systems Medicine.

Authors:  Cheng Zhang; Qiang Hua
Journal:  Front Physiol       Date:  2016-01-07       Impact factor: 4.566

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