Literature DB >> 15083505

Metabolic pathway analysis of yeast strengthens the bridge between transcriptomics and metabolic networks.

Tunahan Cakir1, Betül Kirdar, Kutlu O Ulgen.   

Abstract

Central carbon metabolism of the yeast Saccharomyces cerevisiae was analyzed using metabolic pathway analysis tools. Elementary flux modes for three substrates (glucose, galactose, and ethanol) were determined using the catabolic reactions occurring in yeast. Resultant elementary modes were used for gene deletion phenotype analysis and for the analysis of robustness of the central metabolism and network functionality. Control-effective fluxes, determined by calculating the efficiency of each mode, were used for the prediction of transcript ratios of metabolic genes in different growth media (glucose-ethanol and galactose-ethanol). A high correlation was obtained between the theoretical and experimental expression levels of 38 genes when ethanol and glucose media were considered. Such analysis was shown to be a bridge between transcriptomics and fluxomics. Control-effective flux distribution was found to be promising in in silico predictions by incorporating functionality and regulation into the metabolic network structure. Copyright 2004 Wiley Periodicals, Inc.

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Year:  2004        PMID: 15083505     DOI: 10.1002/bit.20020

Source DB:  PubMed          Journal:  Biotechnol Bioeng        ISSN: 0006-3592            Impact factor:   4.530


  18 in total

1.  Analysis of metabolic subnetworks by flux cone projection.

Authors:  Sayed-Amir Marashi; Laszlo David; Alexander Bockmayr
Journal:  Algorithms Mol Biol       Date:  2012-05-29       Impact factor: 1.405

2.  Pathway analysis of liver metabolism under stressed condition.

Authors:  Mehmet A Orman; Francois Berthiaume; Ioannis P Androulakis; Marianthi G Ierapetritou
Journal:  J Theor Biol       Date:  2010-12-14       Impact factor: 2.691

3.  Computation of elementary modes: a unifying framework and the new binary approach.

Authors:  Julien Gagneur; Steffen Klamt
Journal:  BMC Bioinformatics       Date:  2004-11-04       Impact factor: 3.169

4.  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

5.  Transformation to ischaemia tolerance of frog brain function corresponds to dynamic changes in mRNA co-expression across metabolic pathways.

Authors:  Min Hu; Joseph M Santin
Journal:  Proc Biol Sci       Date:  2022-07-27       Impact factor: 5.530

Review 6.  Which metabolic pathways generate and characterize the flux space? A comparison among elementary modes, extreme pathways and minimal generators.

Authors:  Francisco Llaneras; Jesús Picó
Journal:  J Biomed Biotechnol       Date:  2010-05-11

Review 7.  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

8.  Improving metabolic flux predictions using absolute gene expression data.

Authors:  Dave Lee; Kieran Smallbone; Warwick B Dunn; Ettore Murabito; Catherine L Winder; Douglas B Kell; Pedro Mendes; Neil Swainston
Journal:  BMC Syst Biol       Date:  2012-06-19

9.  Validation of a constraint-based model of Pichia pastoris metabolism under data scarcity.

Authors:  Marta Tortajada; Francisco Llaneras; Jesús Picó
Journal:  BMC Syst Biol       Date:  2010-08-17

10.  Pyruvate kinase triggers a metabolic feedback loop that controls redox metabolism in respiring cells.

Authors:  Nana-Maria Grüning; Mark Rinnerthaler; Katharina Bluemlein; Michael Mülleder; Mirjam M C Wamelink; Hans Lehrach; Cornelis Jakobs; Michael Breitenbach; Markus Ralser
Journal:  Cell Metab       Date:  2011-09-07       Impact factor: 27.287

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