Literature DB >> 23703951

Constraint-based strain design using continuous modifications (CosMos) of flux bounds finds new strategies for metabolic engineering.

Cameron Cotten1, Jennifer L Reed.   

Abstract

In recent years, a growing number of metabolic engineering strain design techniques have employed constraint-based modeling to determine metabolic and regulatory network changes which are needed to improve chemical production. These methods use systems-level analysis of metabolism to help guide experimental efforts by identifying deletions, additions, downregulations, and upregulations of metabolic genes that will increase biological production of a desired metabolic product. In this work, we propose a new strain design method with continuous modifications (CosMos) that provides strategies for deletions, downregulations, and upregulations of fluxes that will lead to the production of the desired products. The method is conceptually simple and easy to implement, and can provide additional strategies over current approaches. We found that the method was able to find strain design strategies that required fewer modifications and had larger predicted yields than strategies from previous methods in example and genome-scale networks. Using CosMos, we identified modification strategies for producing a variety of metabolic products, compared strategies derived from Escherichia coli and Saccharomyces cerevisiae metabolic models, and examined how imperfect implementation may affect experimental outcomes. This study gives a powerful and flexible technique for strain engineering and examines some of the unexpected outcomes that may arise when strategies are implemented experimentally.
Copyright © 2013 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim.

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Year:  2013        PMID: 23703951     DOI: 10.1002/biot.201200316

Source DB:  PubMed          Journal:  Biotechnol J        ISSN: 1860-6768            Impact factor:   4.677


  11 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.  Integrating proteomic or transcriptomic data into metabolic models using linear bound flux balance analysis.

Authors:  Mingyuan Tian; Jennifer L Reed
Journal:  Bioinformatics       Date:  2018-11-15       Impact factor: 6.937

Review 3.  Applications of genome-scale metabolic network model in metabolic engineering.

Authors:  Byoungjin Kim; Won Jun Kim; Dong In Kim; Sang Yup Lee
Journal:  J Ind Microbiol Biotechnol       Date:  2014-12-03       Impact factor: 3.346

4.  Expanding Metabolic Engineering Algorithms Using Feasible Space and Shadow Price Constraint Modules.

Authors:  Christopher J Tervo; Jennifer L Reed
Journal:  Metab Eng Commun       Date:  2014-12-01

5.  Succinate Overproduction: A Case Study of Computational Strain Design Using a Comprehensive Escherichia coli Kinetic Model.

Authors:  Ali Khodayari; Anupam Chowdhury; Costas D Maranas
Journal:  Front Bioeng Biotechnol       Date:  2015-01-05

Review 6.  Computational approaches to metabolic engineering utilizing systems biology and synthetic biology.

Authors:  Stephen S Fong
Journal:  Comput Struct Biotechnol J       Date:  2014-08-27       Impact factor: 7.271

7.  Stoichiometric Representation of Gene-Protein-Reaction Associations Leverages Constraint-Based Analysis from Reaction to Gene-Level Phenotype Prediction.

Authors:  Daniel Machado; Markus J Herrgård; Isabel Rocha
Journal:  PLoS Comput Biol       Date:  2016-10-06       Impact factor: 4.475

8.  Yeast metabolic chassis designs for diverse biotechnological products.

Authors:  Paula Jouhten; Tomasz Boruta; Sergej Andrejev; Filipa Pereira; Isabel Rocha; Kiran Raosaheb Patil
Journal:  Sci Rep       Date:  2016-07-19       Impact factor: 4.379

Review 9.  Co-evolution of strain design methods based on flux balance and elementary mode analysis.

Authors:  Daniel Machado; Markus J Herrgård
Journal:  Metab Eng Commun       Date:  2015-05-21

10.  k-OptForce: integrating kinetics with flux balance analysis for strain design.

Authors:  Anupam Chowdhury; Ali R Zomorrodi; Costas D Maranas
Journal:  PLoS Comput Biol       Date:  2014-02-20       Impact factor: 4.475

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