Literature DB >> 25575024

Next-generation genome-scale models for metabolic engineering.

Zachary A King1, Colton J Lloyd1, Adam M Feist2, Bernhard O Palsson3.   

Abstract

Constraint-based reconstruction and analysis (COBRA) methods have become widely used tools for metabolic engineering in both academic and industrial laboratories. By employing a genome-scale in silico representation of the metabolic network of a host organism, COBRA methods can be used to predict optimal genetic modifications that improve the rate and yield of chemical production. A new generation of COBRA models and methods is now being developed--encompassing many biological processes and simulation strategies-and next-generation models enable new types of predictions. Here, three key examples of applying COBRA methods to strain optimization are presented and discussed. Then, an outlook is provided on the next generation of COBRA models and the new types of predictions they will enable for systems metabolic engineering.
Copyright © 2014 Elsevier Ltd. All rights reserved.

Mesh:

Year:  2015        PMID: 25575024     DOI: 10.1016/j.copbio.2014.12.016

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


  43 in total

Review 1.  Effective models and the search for quantitative principles in microbial evolution.

Authors:  Benjamin H Good; Oskar Hallatschek
Journal:  Curr Opin Microbiol       Date:  2018-12-06       Impact factor: 7.934

2.  Predicting the metabolic capabilities of Synechococcus elongatus PCC 7942 adapted to different light regimes.

Authors:  Jared T Broddrick; David G Welkie; Denis Jallet; Susan S Golden; Graham Peers; Bernhard O Palsson
Journal:  Metab Eng       Date:  2018-11-13       Impact factor: 9.783

3.  Applications of a metabolic network model of mesenchymal stem cells for controlling cell proliferation and differentiation.

Authors:  Hamideh Fouladiha; Sayed-Amir Marashi; Mohammad Ali Shokrgozar; Mehdi Farokhi; Amir Atashi
Journal:  Cytotechnology       Date:  2017-10-04       Impact factor: 2.058

4.  Cellular trade-offs and optimal resource allocation during cyanobacterial diurnal growth.

Authors:  Alexandra-M Reimers; Henning Knoop; Alexander Bockmayr; Ralf Steuer
Journal:  Proc Natl Acad Sci U S A       Date:  2017-07-18       Impact factor: 11.205

5.  Comprehensive analysis of glucose and xylose metabolism in Escherichia coli under aerobic and anaerobic conditions by 13C metabolic flux analysis.

Authors:  Jacqueline E Gonzalez; Christopher P Long; Maciek R Antoniewicz
Journal:  Metab Eng       Date:  2016-11-11       Impact factor: 9.783

6.  13C metabolic flux analysis of three divergent extremely thermophilic bacteria: Geobacillus sp. LC300, Thermus thermophilus HB8, and Rhodothermus marinus DSM 4252.

Authors:  Lauren T Cordova; Robert M Cipolla; Adti Swarup; Christopher P Long; Maciek R Antoniewicz
Journal:  Metab Eng       Date:  2017-10-14       Impact factor: 9.783

7.  High Substrate Uptake Rates Empower Vibrio natriegens as Production Host for Industrial Biotechnology.

Authors:  Eugenia Hoffart; Sebastian Grenz; Julian Lange; Robert Nitschel; Felix Müller; Andreas Schwentner; André Feith; Mira Lenfers-Lücker; Ralf Takors; Bastian Blombach
Journal:  Appl Environ Microbiol       Date:  2017-10-31       Impact factor: 4.792

8.  Improvements in protein production in mammalian cells from targeted metabolic engineering.

Authors:  Anne Richelle; Nathan E Lewis
Journal:  Curr Opin Syst Biol       Date:  2017-06-06

9.  Escher: A Web Application for Building, Sharing, and Embedding Data-Rich Visualizations of Biological Pathways.

Authors:  Zachary A King; Andreas Dräger; Ali Ebrahim; Nikolaus Sonnenschein; Nathan E Lewis; Bernhard O Palsson
Journal:  PLoS Comput Biol       Date:  2015-08-27       Impact factor: 4.475

Review 10.  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
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