Literature DB >> 17652176

Intracellular crowding defines the mode and sequence of substrate uptake by Escherichia coli and constrains its metabolic activity.

Q K Beg1, A Vazquez, J Ernst, M A de Menezes, Z Bar-Joseph, A-L Barabási, Z N Oltvai.   

Abstract

The influence of the high intracellular concentration of macromolecules on cell physiology is increasingly appreciated, but its impact on system-level cellular functions remains poorly quantified. To assess its potential effect, here we develop a flux balance model of Escherichia coli cell metabolism that takes into account a systems-level constraint for the concentration of enzymes catalyzing the various metabolic reactions in the crowded cytoplasm. We demonstrate that the model's predictions for the relative maximum growth rate of wild-type and mutant E. coli cells in single substrate-limited media, and the sequence and mode of substrate uptake and utilization from a complex medium are in good agreement with subsequent experimental observations. These results suggest that molecular crowding represents a bound on the achievable functional states of a metabolic network, and they indicate that models incorporating this constraint can systematically identify alterations in cellular metabolism activated in response to environmental change.

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Year:  2007        PMID: 17652176      PMCID: PMC1937523          DOI: 10.1073/pnas.0609845104

Source DB:  PubMed          Journal:  Proc Natl Acad Sci U S A        ISSN: 0027-8424            Impact factor:   11.205


  32 in total

1.  Global transcriptional programs reveal a carbon source foraging strategy by Escherichia coli.

Authors:  Mingzhu Liu; Tim Durfee; Julio E Cabrera; Kai Zhao; Ding J Jin; Frederick R Blattner
Journal:  J Biol Chem       Date:  2005-02-10       Impact factor: 5.157

2.  Topological units of environmental signal processing in the transcriptional regulatory network of Escherichia coli.

Authors:  G Balázsi; A-L Barabási; Z N Oltvai
Journal:  Proc Natl Acad Sci U S A       Date:  2005-05-20       Impact factor: 11.205

Review 3.  Influence of macromolecular crowding upon the stability and state of association of proteins: predictions and observations.

Authors:  Allen P Minton
Journal:  J Pharm Sci       Date:  2005-08       Impact factor: 3.534

4.  Protein mobility in the cytoplasm of Escherichia coli.

Authors:  M B Elowitz; M G Surette; P E Wolf; J B Stock; S Leibler
Journal:  J Bacteriol       Date:  1999-01       Impact factor: 3.490

5.  Genome-scale thermodynamic analysis of Escherichia coli metabolism.

Authors:  Christopher S Henry; Matthew D Jankowski; Linda J Broadbelt; Vassily Hatzimanikatis
Journal:  Biophys J       Date:  2005-11-18       Impact factor: 4.033

6.  The underlying pathway structure of biochemical reaction networks.

Authors:  C H Schilling; B O Palsson
Journal:  Proc Natl Acad Sci U S A       Date:  1998-04-14       Impact factor: 11.205

7.  Expanded metabolic reconstruction of Helicobacter pylori (iIT341 GSM/GPR): an in silico genome-scale characterization of single- and double-deletion mutants.

Authors:  Ines Thiele; Thuy D Vo; Nathan D Price; Bernhard Ø Palsson
Journal:  J Bacteriol       Date:  2005-08       Impact factor: 3.490

8.  Cluster analysis and display of genome-wide expression patterns.

Authors:  M B Eisen; P T Spellman; P O Brown; D Botstein
Journal:  Proc Natl Acad Sci U S A       Date:  1998-12-08       Impact factor: 11.205

9.  Genome-scale in silico models of E. coli have multiple equivalent phenotypic states: assessment of correlated reaction subsets that comprise network states.

Authors:  Jennifer L Reed; Bernhard Ø Palsson
Journal:  Genome Res       Date:  2004-09       Impact factor: 9.043

10.  Estimation of macromolecule concentrations and excluded volume effects for the cytoplasm of Escherichia coli.

Authors:  S B Zimmerman; S O Trach
Journal:  J Mol Biol       Date:  1991-12-05       Impact factor: 5.469

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  138 in total

1.  Prediction of metabolic fluxes by incorporating genomic context and flux-converging pattern analyses.

Authors:  Jong Myoung Park; Tae Yong Kim; Sang Yup Lee
Journal:  Proc Natl Acad Sci U S A       Date:  2010-08-02       Impact factor: 11.205

2.  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 3.  Pseudomonad reverse carbon catabolite repression, interspecies metabolite exchange, and consortial division of labor.

Authors:  Heejoon Park; S Lee McGill; Adrienne D Arnold; Ross P Carlson
Journal:  Cell Mol Life Sci       Date:  2019-11-25       Impact factor: 9.261

4.  A critical view of metabolic network adaptations.

Authors:  Balázs Papp; Bas Teusink; Richard A Notebaart
Journal:  HFSP J       Date:  2008-12-03

Review 5.  Gene expression profiling and the use of genome-scale in silico models of Escherichia coli for analysis: providing context for content.

Authors:  Nathan E Lewis; Byung-Kwan Cho; Eric M Knight; Bernhard O Palsson
Journal:  J Bacteriol       Date:  2009-04-10       Impact factor: 3.490

Review 6.  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

7.  Metabolic specialization and the assembly of microbial communities.

Authors:  David R Johnson; Felix Goldschmidt; Elin E Lilja; Martin Ackermann
Journal:  ISME J       Date:  2012-05-17       Impact factor: 10.302

8.  Elementary Growth Modes provide a molecular description of cellular self-fabrication.

Authors:  Daan H de Groot; Josephus Hulshof; Bas Teusink; Frank J Bruggeman; Robert Planqué
Journal:  PLoS Comput Biol       Date:  2020-01-27       Impact factor: 4.475

Review 9.  The implications of human metabolic network topology for disease comorbidity.

Authors:  D-S Lee; J Park; K A Kay; N A Christakis; Z N Oltvai; A-L Barabási
Journal:  Proc Natl Acad Sci U S A       Date:  2008-07-03       Impact factor: 11.205

10.  Integration of genome-scale modeling and transcript profiling reveals metabolic pathways underlying light and temperature acclimation in Arabidopsis.

Authors:  Nadine Töpfer; Camila Caldana; Sergio Grimbs; Lothar Willmitzer; Alisdair R Fernie; Zoran Nikoloski
Journal:  Plant Cell       Date:  2013-04-23       Impact factor: 11.277

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