Literature DB >> 16581276

The fractional contributions of elementary modes to the metabolism of Escherichia coli and their estimation from reaction entropies.

Aaron P Wlaschin1, Cong T Trinh, Ross Carlson, Friedrich Srienc.   

Abstract

The metabolism of a cell can be viewed as a weighted sum of elementary modes. Due to the multiplicity of modes the identification of the individual weights represents a non-trivial problem. To enable the determination of weighting factors we have identified and implemented two gene deletions in combination with defined growth conditions that limit the metabolism from 4374 original elementary modes to 24 elementary modes for a non-PHB synthesizing control and 40 modes for a PHB synthesizing strain. These remaining modes can be further grouped into five families that have the same overall stoichiometry. Thus, the complexity of the problem is significantly reduced, and weighting factors for each family of modes could be determined from the measurement of accumulation rates of metabolites. Moreover, it is shown that individual weights are inversely correlated with the entropy generated by the operation of the used pathways defined in elementary modes. This suggests that evolution developed cellular regulatory patterns that permit diversity of pathways while favoring efficient pathways with low entropy generation. Furthermore, such correlation provides a rational way of estimating metabolic fluxes based on the thermodynamic properties of elementary modes. This is demonstrated with an example in which experimentally determined, intracellular fluxes are shown to be highly correlated with fluxes computed based on elementary modes and reaction entropies. The analysis suggests that the set of elementary modes can be interpreted analogous to a metabolic ensemble of quantum states of a macroscopic system.

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Year:  2006        PMID: 16581276     DOI: 10.1016/j.ymben.2006.01.007

Source DB:  PubMed          Journal:  Metab Eng        ISSN: 1096-7176            Impact factor:   9.783


  14 in total

1.  Elimination of D-lactate synthesis increases poly(3-hydroxybutyrate) and ethanol synthesis from glycerol and affects cofactor distribution in recombinant Escherichia coli.

Authors:  Pablo I Nikel; Andrea M Giordano; Alejandra de Almeida; Manuel S Godoy; M Julia Pettinari
Journal:  Appl Environ Microbiol       Date:  2010-09-24       Impact factor: 4.792

2.  Minimal Escherichia coli cell for the most efficient production of ethanol from hexoses and pentoses.

Authors:  Cong T Trinh; Pornkamol Unrean; Friedrich Srienc
Journal:  Appl Environ Microbiol       Date:  2008-04-18       Impact factor: 4.792

Review 3.  Recent advances in elementary flux modes and yield space analysis as useful tools in metabolic network studies.

Authors:  Predrag Horvat; Martin Koller; Gerhart Braunegg
Journal:  World J Microbiol Biotechnol       Date:  2015-06-12       Impact factor: 3.312

4.  A new metabolomics analysis technique: steady-state metabolic network dynamics analysis.

Authors:  Ali Cakmak; Xinjian Qi; A Ercument Cicek; Ilya Bederman; Leigh Henderson; Mitchell Drumm; Gultekin Ozsoyoglu
Journal:  J Bioinform Comput Biol       Date:  2012-02       Impact factor: 1.122

5.  Escherichia coli responds to environmental changes using enolasic degradosomes and stabilized DicF sRNA to alter cellular morphology.

Authors:  Oleg N Murashko; Sue Lin-Chao
Journal:  Proc Natl Acad Sci U S A       Date:  2017-09-05       Impact factor: 11.205

6.  Metabolic networks evolve towards states of maximum entropy production.

Authors:  Pornkamol Unrean; Friedrich Srienc
Journal:  Metab Eng       Date:  2011-09-01       Impact factor: 9.783

7.  Quantification of metabolism in Saccharomyces cerevisiae under hyperosmotic conditions using elementary mode analysis.

Authors:  Jignesh H Parmar; Sharad Bhartiya; K V Venkatesh
Journal:  J Ind Microbiol Biotechnol       Date:  2012-02-22       Impact factor: 3.346

8.  Utilizing elementary mode analysis, pathway thermodynamics, and a genetic algorithm for metabolic flux determination and optimal metabolic network design.

Authors:  Brett A Boghigian; Hai Shi; Kyongbum Lee; Blaine A Pfeifer
Journal:  BMC Syst Biol       Date:  2010-04-23

9.  Metabolic engineering of Escherichia coli for efficient conversion of glycerol to ethanol.

Authors:  Cong T Trinh; Friedrich Srienc
Journal:  Appl Environ Microbiol       Date:  2009-09-04       Impact factor: 4.792

Review 10.  Elementary mode analysis: a useful metabolic pathway analysis tool for characterizing cellular metabolism.

Authors:  Cong T Trinh; Aaron Wlaschin; Friedrich Srienc
Journal:  Appl Microbiol Biotechnol       Date:  2008-11-15       Impact factor: 4.813

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