Literature DB >> 26443778

Reconstruction and Use of Microbial Metabolic Networks: the Core Escherichia coli Metabolic Model as an Educational Guide.

Jeffrey D Orth, R M T Fleming, Bernhard Ø Palsson.   

Abstract

Biochemical network reconstructions have become popular tools in systems biology. Metabolicnetwork reconstructions are biochemically, genetically, and genomically (BiGG) structured databases of biochemical reactions and metabolites. They contain information such as exact reaction stoichiometry, reaction reversibility, and the relationships between genes, proteins, and reactions. Network reconstructions have been used extensively to study the phenotypic behavior of wild-type and mutant stains under a variety of conditions, linking genotypes with phenotypes. Such phenotypic simulations have allowed for the prediction of growth after genetic manipulations, prediction of growth phenotypes after adaptive evolution, and prediction of essential genes. Additionally, because network reconstructions are organism specific, they can be used to understand differences between organisms of species in a functional context.There are different types of reconstructions representing various types of biological networks (metabolic, regulatory, transcription/translation). This chapter serves as an introduction to metabolic and regulatory network reconstructions and models and gives a complete description of the core Escherichia coli metabolic model. This model can be analyzed in any computational format (such as MATLAB or Mathematica) based on the information given in this chapter. The core E. coli model is a small-scale model that can be used for educational purposes. It is meant to be used by senior undergraduate and first-year graduate students learning about constraint-based modeling and systems biology. This model has enough reactions and pathways to enable interesting and insightful calculations, but it is also simple enough that the results of such calculations can be understoodeasily.

Entities:  

Year:  2010        PMID: 26443778     DOI: 10.1128/ecosalplus.10.2.1

Source DB:  PubMed          Journal:  EcoSal Plus        ISSN: 2324-6200


  57 in total

1.  Mapping high-growth phenotypes in the flux space of microbial metabolism.

Authors:  Oriol Güell; Francesco Alessandro Massucci; Francesc Font-Clos; Francesc Sagués; M Ángeles Serrano
Journal:  J R Soc Interface       Date:  2015-09-06       Impact factor: 4.118

Review 2.  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

3.  Quantitative flux coupling analysis.

Authors:  Mojtaba Tefagh; Stephen P Boyd
Journal:  J Math Biol       Date:  2018-12-10       Impact factor: 2.259

4.  Metabolic network percolation quantifies biosynthetic capabilities across the human oral microbiome.

Authors:  David B Bernstein; Floyd E Dewhirst; Daniel Segrè
Journal:  Elife       Date:  2019-06-13       Impact factor: 8.140

5.  Integrated stoichiometric, thermodynamic and kinetic modelling of steady state metabolism.

Authors:  R M T Fleming; I Thiele; G Provan; H P Nasheuer
Journal:  J Theor Biol       Date:  2010-03-15       Impact factor: 2.691

6.  Environmental dependence of stationary-phase metabolism in Bacillus subtilis and Escherichia coli.

Authors:  Victor Chubukov; Uwe Sauer
Journal:  Appl Environ Microbiol       Date:  2014-02-28       Impact factor: 4.792

7.  Multi-omics Quantification of Species Variation of Escherichia coli Links Molecular Features with Strain Phenotypes.

Authors:  Jonathan M Monk; Anna Koza; Miguel A Campodonico; Daniel Machado; Jose Miguel Seoane; Bernhard O Palsson; Markus J Herrgård; Adam M Feist
Journal:  Cell Syst       Date:  2016-09-22       Impact factor: 10.304

8.  Genome-Scale Architecture of Small Molecule Regulatory Networks and the Fundamental Trade-Off between Regulation and Enzymatic Activity.

Authors:  Ed Reznik; Dimitris Christodoulou; Joshua E Goldford; Emma Briars; Uwe Sauer; Daniel Segrè; Elad Noor
Journal:  Cell Rep       Date:  2017-09-12       Impact factor: 9.423

9.  Functional reconstitution of a bacterial CO2 concentrating mechanism in Escherichia coli.

Authors:  Avi I Flamholz; Eli Dugan; Cecilia Blikstad; Shmuel Gleizer; Roee Ben-Nissan; Shira Amram; Niv Antonovsky; Sumedha Ravishankar; Elad Noor; Arren Bar-Even; Ron Milo; David F Savage
Journal:  Elife       Date:  2020-10-21       Impact factor: 8.140

10.  Quantitative assignment of reaction directionality in constraint-based models of metabolism: application to Escherichia coli.

Authors:  R M T Fleming; I Thiele; H P Nasheuer
Journal:  Biophys Chem       Date:  2009-09-01       Impact factor: 2.352

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