Literature DB >> 26289659

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

Oriol Güell1, Francesco Alessandro Massucci2, Francesc Font-Clos3, Francesc Sagués1, M Ángeles Serrano4.   

Abstract

Experimental and empirical observations on cell metabolism cannot be understood as a whole without their integration into a consistent systematic framework. However, the characterization of metabolic flux phenotypes is typically reduced to the study of a single optimal state, such as maximum biomass yield that is by far the most common assumption. Here, we confront optimal growth solutions to the whole set of feasible flux phenotypes (FFPs), which provides a benchmark to assess the likelihood of optimal and high-growth states and their agreement with experimental results. In addition, FFP maps are able to uncover metabolic behaviours, such as aerobic fermentation accompanying exponential growth on sugars at nutrient excess conditions, that are unreachable using standard models based on optimality principles. The information content of the full FFP space provides us with a map to explore and evaluate metabolic behaviour and capabilities, and so it opens new avenues for biotechnological and biomedical applications.
© 2015 The Author(s).

Entities:  

Keywords:  cellular metabolism; flux balance analysis; flux space

Mesh:

Year:  2015        PMID: 26289659      PMCID: PMC4614465          DOI: 10.1098/rsif.2015.0543

Source DB:  PubMed          Journal:  J R Soc Interface        ISSN: 1742-5662            Impact factor:   4.118


  45 in total

Review 1.  The acetate switch.

Authors:  Alan J Wolfe
Journal:  Microbiol Mol Biol Rev       Date:  2005-03       Impact factor: 11.056

2.  Multidimensional optimality of microbial metabolism.

Authors:  Robert Schuetz; Nicola Zamboni; Mattia Zampieri; Matthias Heinemann; Uwe Sauer
Journal:  Science       Date:  2012-05-04       Impact factor: 47.728

3.  The complete genome sequence of Escherichia coli K-12.

Authors:  F R Blattner; G Plunkett; C A Bloch; N T Perna; V Burland; M Riley; J Collado-Vides; J D Glasner; C K Rode; G F Mayhew; J Gregor; N W Davis; H A Kirkpatrick; M A Goeden; D J Rose; B Mau; Y Shao
Journal:  Science       Date:  1997-09-05       Impact factor: 47.728

4.  Synergy between (13)C-metabolic flux analysis and flux balance analysis for understanding metabolic adaptation to anaerobiosis in E. coli.

Authors:  Xuewen Chen; Ana P Alonso; Doug K Allen; Jennifer L Reed; Yair Shachar-Hill
Journal:  Metab Eng       Date:  2010-12-01       Impact factor: 9.783

5.  In silico predictions of Escherichia coli metabolic capabilities are consistent with experimental data.

Authors:  J S Edwards; R U Ibarra; B O Palsson
Journal:  Nat Biotechnol       Date:  2001-02       Impact factor: 54.908

6.  Effect of oxygen limitation and medium composition on Escherichia coli fermentation in shake-flask cultures.

Authors:  Mario Losen; Bettina Frölich; Martina Pohl; Jochen Büchs
Journal:  Biotechnol Prog       Date:  2004 Jul-Aug

7.  Stoichiometric flux balance models quantitatively predict growth and metabolic by-product secretion in wild-type Escherichia coli W3110.

Authors:  A Varma; B O Palsson
Journal:  Appl Environ Microbiol       Date:  1994-10       Impact factor: 4.792

8.  Characterization of the metabolic shift between oxidative and fermentative growth in Saccharomyces cerevisiae by comparative 13C flux analysis.

Authors:  Oliver Frick; Christoph Wittmann
Journal:  Microb Cell Fact       Date:  2005-11-03       Impact factor: 5.328

9.  Extensive exometabolome analysis reveals extended overflow metabolism in various microorganisms.

Authors:  Nicole Paczia; Anke Nilgen; Tobias Lehmann; Jochem Gätgens; Wolfgang Wiechert; Stephan Noack
Journal:  Microb Cell Fact       Date:  2012-09-11       Impact factor: 5.328

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  1 in total

1.  Comparison of metabolic states using genome-scale metabolic models.

Authors:  Chaitra Sarathy; Marian Breuer; Martina Kutmon; Michiel E Adriaens; Chris T Evelo; Ilja C W Arts
Journal:  PLoS Comput Biol       Date:  2021-11-08       Impact factor: 4.475

  1 in total

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