Literature DB >> 16467155

Unraveling the complexity of flux regulation: a new method demonstrated for nutrient starvation in Saccharomyces cerevisiae.

Sergio Rossell1, Coen C van der Weijden, Alexander Lindenbergh, Arjen van Tuijl, Christof Francke, Barbara M Bakker, Hans V Westerhoff.   

Abstract

An important question is to what extent metabolic fluxes are regulated by gene expression or by metabolic regulation. There are two distinct aspects to this question: (i) the local regulation of the fluxes through the individual steps in the pathway and (ii) the influence of such local regulation on the pathway's flux. We developed regulation analysis so as to address the former aspect for all steps in a pathway. We demonstrate the method for the issue of how Saccharomyces cerevisiae regulates the fluxes through its individual glycolytic and fermentative enzymes when confronted with nutrient starvation. Regulation was dissected quantitatively into (i) changes in maximum enzyme activity (Vmax, called hierarchical regulation) and (ii) changes in the interaction of the enzyme with the rest of metabolism (called metabolic regulation). Within a single pathway, the regulation of the fluxes through individual steps varied from fully hierarchical to exclusively metabolic. Existing paradigms of flux regulation (such as single- and multisite modulation and exclusively metabolic regulation) were tested for a complete pathway and falsified for a major pathway in an important model organism. We propose a subtler mechanism of flux regulation, with different roles for different enzymes, i.e., "leader," "follower," or "conservative," the latter attempting to hold back the change in flux. This study makes this subtlety, so typical for biological systems, tractable experimentally and invites reformulation of the questions concerning the drives and constraints governing metabolic flux regulation.

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Year:  2006        PMID: 16467155      PMCID: PMC1413710          DOI: 10.1073/pnas.0509831103

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


  19 in total

1.  Transcriptome meets metabolome: hierarchical and metabolic regulation of the glycolytic pathway.

Authors:  B H ter Kuile; H V Westerhoff
Journal:  FEBS Lett       Date:  2001-07-06       Impact factor: 4.124

2.  Loss of fermentative capacity in baker's yeast can partly be explained by reduced glucose uptake capacity.

Authors:  Sergio Rossell; Coen C van der Weijden; Arthur Kruckeberg; Barbara M Bakker; Hans V Westerhoff
Journal:  Mol Biol Rep       Date:  2002       Impact factor: 2.316

Review 3.  Stoichiometry and compartmentation of NADH metabolism in Saccharomyces cerevisiae.

Authors:  B M Bakker; K M Overkamp; P Kötter; M A Luttik; J T Pronk
Journal:  FEMS Microbiol Rev       Date:  2001-01       Impact factor: 16.408

4.  A theoretical evaluation of growth yields of yeasts.

Authors:  C Verduyn; A H Stouthamer; W A Scheffers; J P van Dijken
Journal:  Antonie Van Leeuwenhoek       Date:  1991-01       Impact factor: 2.271

5.  The catabolic capacity of Saccharomyces cerevisiae is preserved to a higher extent during carbon compared to nitrogen starvation.

Authors:  A Nilsson; I L Påhlman; P A Jovall; A Blomberg; C Larsson; L Gustafsson
Journal:  Yeast       Date:  2001-11       Impact factor: 3.239

Review 6.  Autophagy in yeast: mechanistic insights and physiological function.

Authors:  H Abeliovich; D J Klionsky
Journal:  Microbiol Mol Biol Rev       Date:  2001-09       Impact factor: 11.056

7.  Carbon starvation can induce energy deprivation and loss of fermentative capacity in Saccharomyces cerevisiae.

Authors:  Elisabeth Thomsson; Christer Larsson; Eva Albers; Annika Nilsson; Carl Johan Franzén; Lena Gustafsson
Journal:  Appl Environ Microbiol       Date:  2003-06       Impact factor: 4.792

8.  Role of transcriptional regulation in controlling fluxes in central carbon metabolism of Saccharomyces cerevisiae. A chemostat culture study.

Authors:  Pascale Daran-Lapujade; Mickel L A Jansen; Jean-Marc Daran; Walter van Gulik; Johannes H de Winde; Jack T Pronk
Journal:  J Biol Chem       Date:  2003-11-20       Impact factor: 5.157

9.  Physiology of Saccharomyces cerevisiae in anaerobic glucose-limited chemostat cultures.

Authors:  C Verduyn; E Postma; W A Scheffers; J P van Dijken
Journal:  J Gen Microbiol       Date:  1990-03

10.  In vivo and in vitro phosphorylation of two isoforms of yeast pyruvate kinase by protein kinase A.

Authors:  Paula Portela; Steven Howell; Silvia Moreno; Silvia Rossi
Journal:  J Biol Chem       Date:  2002-06-12       Impact factor: 5.157

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  37 in total

1.  Linking high-resolution metabolic flux phenotypes and transcriptional regulation in yeast modulated by the global regulator Gcn4p.

Authors:  Joel F Moxley; Michael C Jewett; Maciek R Antoniewicz; Silas G Villas-Boas; Hal Alper; Robert T Wheeler; Lily Tong; Alan G Hinnebusch; Trey Ideker; Jens Nielsen; Gregory Stephanopoulos
Journal:  Proc Natl Acad Sci U S A       Date:  2009-04-03       Impact factor: 11.205

2.  Quantitative analysis of the high temperature-induced glycolytic flux increase in Saccharomyces cerevisiae reveals dominant metabolic regulation.

Authors:  Jarne Postmus; André B Canelas; Jildau Bouwman; Barbara M Bakker; Walter van Gulik; M Joost Teixeira de Mattos; Stanley Brul; Gertien J Smits
Journal:  J Biol Chem       Date:  2008-06-18       Impact factor: 5.157

3.  Approaches to biosimulation of cellular processes.

Authors:  F J Bruggeman; H V Westerhoff
Journal:  J Biol Phys       Date:  2006-11-11       Impact factor: 1.365

4.  Quantifying Dynamic Regulation in Metabolic Pathways with Nonparametric Flux Inference.

Authors:  Fei He; Michael P H Stumpf
Journal:  Biophys J       Date:  2019-04-19       Impact factor: 4.033

5.  Tissue-level modeling of xenobiotic metabolism in liver: An emerging tool for enabling clinical translational research.

Authors:  Marianthi G Lerapetritou; Panos G Georgopoulos; Charles M Roth; Loannis P Androulakis
Journal:  Clin Transl Sci       Date:  2009-06       Impact factor: 4.689

6.  Activity motifs reveal principles of timing in transcriptional control of the yeast metabolic network.

Authors:  Gal Chechik; Eugene Oh; Oliver Rando; Jonathan Weissman; Aviv Regev; Daphne Koller
Journal:  Nat Biotechnol       Date:  2008-11       Impact factor: 54.908

7.  Integrating quantitative proteomics and metabolomics with a genome-scale metabolic network model.

Authors:  Keren Yizhak; Tomer Benyamini; Wolfram Liebermeister; Eytan Ruppin; Tomer Shlomi
Journal:  Bioinformatics       Date:  2010-06-15       Impact factor: 6.937

8.  Interpreting metabolomic profiles using unbiased pathway models.

Authors:  Rahul C Deo; Luke Hunter; Gregory D Lewis; Guillaume Pare; Ramachandran S Vasan; Daniel Chasman; Thomas J Wang; Robert E Gerszten; Frederick P Roth
Journal:  PLoS Comput Biol       Date:  2010-02-26       Impact factor: 4.475

9.  Cyclic AMP-dependent catabolite repression is the dominant control mechanism of metabolic fluxes under glucose limitation in Escherichia coli.

Authors:  Annik Nanchen; Alexander Schicker; Olga Revelles; Uwe Sauer
Journal:  J Bacteriol       Date:  2008-01-25       Impact factor: 3.490

Review 10.  Generalized framework for context-specific metabolic model extraction methods.

Authors:  Semidán Robaina Estévez; Zoran Nikoloski
Journal:  Front Plant Sci       Date:  2014-09-19       Impact factor: 5.753

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