Literature DB >> 16299075

Genome-scale thermodynamic analysis of Escherichia coli metabolism.

Christopher S Henry1, Matthew D Jankowski, Linda J Broadbelt, Vassily Hatzimanikatis.   

Abstract

Genome-scale metabolic models are an invaluable tool for analyzing metabolic systems as they provide a more complete picture of the processes of metabolism. We have constructed a genome-scale metabolic model of Escherichia coli based on the iJR904 model developed by the Palsson Laboratory at the University of California at San Diego. Group contribution methods were utilized to estimate the standard Gibbs free energy change of every reaction in the constructed model. Reactions in the model were classified based on the activity of the reactions during optimal growth on glucose in aerobic media. The most thermodynamically unfavorable reactions involved in the production of biomass in E. coli were identified as ATP phosphoribosyltransferase, ATP synthase, methylene-tetra-hydrofolate dehydrogenase, and tryptophanase. The effect of a knockout of these reactions on the production of biomass and the production of individual biomass precursors was analyzed. Changes in the distribution of fluxes in the cell after knockout of these unfavorable reactions were also studied. The methodologies and results discussed can be used to facilitate the refinement of the feasible ranges for cellular parameters such as species concentrations and reaction rate constants.

Entities:  

Mesh:

Substances:

Year:  2005        PMID: 16299075      PMCID: PMC1367295          DOI: 10.1529/biophysj.105.071720

Source DB:  PubMed          Journal:  Biophys J        ISSN: 0006-3495            Impact factor:   4.033


  29 in total

1.  KEGG: kyoto encyclopedia of genes and genomes.

Authors:  M Kanehisa; S Goto
Journal:  Nucleic Acids Res       Date:  2000-01-01       Impact factor: 16.971

2.  Energy balance for analysis of complex metabolic networks.

Authors:  Daniel A Beard; Shou-dan Liang; Hong Qian
Journal:  Biophys J       Date:  2002-07       Impact factor: 4.033

Review 3.  Cellular concentrations of enzymes and their substrates.

Authors:  K R Albe; M H Butler; B E Wright
Journal:  J Theor Biol       Date:  1990-03-22       Impact factor: 2.691

4.  Thermodynamic-based computational profiling of cellular regulatory control in hepatocyte metabolism.

Authors:  Daniel A Beard; Hong Qian
Journal:  Am J Physiol Endocrinol Metab       Date:  2004-10-26       Impact factor: 4.310

5.  Estimation of standard Gibbs energy changes of biotransformations.

Authors:  M L Mavrovouniotis
Journal:  J Biol Chem       Date:  1991-08-05       Impact factor: 5.157

6.  Enzymatic reaction rate limits with constraints on equilibrium constants and experimental parameters.

Authors:  D R Bish; M L Mavrovouniotis
Journal:  Biosystems       Date:  1998 Jun-Jul       Impact factor: 1.973

7.  Robustness analysis of the Escherichia coli metabolic network.

Authors:  J S Edwards; B O Palsson
Journal:  Biotechnol Prog       Date:  2000 Nov-Dec

8.  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

9.  Endothelial cell surface F1-F0 ATP synthase is active in ATP synthesis and is inhibited by angiostatin.

Authors:  T L Moser; D J Kenan; T A Ashley; J A Roy; M D Goodman; U K Misra; D J Cheek; S V Pizzo
Journal:  Proc Natl Acad Sci U S A       Date:  2001-05-29       Impact factor: 11.205

10.  An expanded genome-scale model of Escherichia coli K-12 (iJR904 GSM/GPR).

Authors:  Jennifer L Reed; Thuy D Vo; Christophe H Schilling; Bernhard O Palsson
Journal:  Genome Biol       Date:  2003-08-28       Impact factor: 13.583

View more
  87 in total

1.  Quantitative assignment of reaction directionality in a multicompartmental human metabolic reconstruction.

Authors:  H S Haraldsdóttir; I Thiele; R M T Fleming
Journal:  Biophys J       Date:  2012-04-18       Impact factor: 4.033

Review 2.  Systematizing the generation of missing metabolic knowledge.

Authors:  Jeffrey D Orth; Bernhard Ø Palsson
Journal:  Biotechnol Bioeng       Date:  2010-10-15       Impact factor: 4.530

3.  Thermodynamic calculations for biochemical transport and reaction processes in metabolic networks.

Authors:  Stefan J Jol; Anne Kümmel; Vassily Hatzimanikatis; Daniel A Beard; Matthias Heinemann
Journal:  Biophys J       Date:  2010-11-17       Impact factor: 4.033

4.  The Influence of Crowding Conditions on the Thermodynamic Feasibility of Metabolic Pathways.

Authors:  Liliana Angeles-Martinez; Constantinos Theodoropoulos
Journal:  Biophys J       Date:  2015-12-01       Impact factor: 4.033

Review 5.  Metabolic flux analysis of Escherichia coli knockouts: lessons from the Keio collection and future outlook.

Authors:  Christopher P Long; Maciek R Antoniewicz
Journal:  Curr Opin Biotechnol       Date:  2014-03-28       Impact factor: 9.740

6.  L-malate production by metabolically engineered Escherichia coli.

Authors:  X Zhang; X Wang; K T Shanmugam; L O Ingram
Journal:  Appl Environ Microbiol       Date:  2010-11-19       Impact factor: 4.792

7.  The thermodynamic meaning of metabolic exchange fluxes.

Authors:  Wolfgang Wiechert
Journal:  Biophys J       Date:  2007-05-25       Impact factor: 4.033

8.  Group contribution method for thermodynamic analysis of complex metabolic networks.

Authors:  Matthew D Jankowski; Christopher S Henry; Linda J Broadbelt; Vassily Hatzimanikatis
Journal:  Biophys J       Date:  2008-08       Impact factor: 4.033

Review 9.  The growing scope of applications of genome-scale metabolic reconstructions using Escherichia coli.

Authors:  Adam M Feist; Bernhard Ø Palsson
Journal:  Nat Biotechnol       Date:  2008-06       Impact factor: 54.908

10.  The cost of efficiency in energy metabolism.

Authors:  Arion I Stettner; Daniel Segrè
Journal:  Proc Natl Acad Sci U S A       Date:  2013-05-31       Impact factor: 11.205

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.