Literature DB >> 20810924

A quantitative model of glucose signaling in yeast reveals an incoherent feed forward loop leading to a specific, transient pulse of transcription.

Sooraj Kuttykrishnan1, Jeffrey Sabina, Laura L Langton, Mark Johnston, Michael R Brent.   

Abstract

The ability to design and engineer organisms demands the ability to predict kinetic responses of novel regulatory networks built from well-characterized biological components. Surprisingly, few validated kinetic models of complex regulatory networks have been derived by combining models of the network components. A major bottleneck in producing such models is the difficulty of measuring in vivo rate constants for components of complex networks. We demonstrate that a simple, genetic approach to measuring rate constants in vivo produces an accurate kinetic model of the complex network that Saccharomyces cerevisiae employs to regulate the expression of genes encoding glucose transporters. The model predicts a transient pulse of transcription of HXT4 (but not HXT2 or HXT3) in response to addition of a small amount of glucose to cells, an outcome we observed experimentally. Our model also provides a mechanistic explanation for this result: HXT2-4 are governed by a type 2, incoherent feed forward regulatory loop involving the Rgt1 and Mig2 transcriptional repressors. The efficiency with which Rgt1 and Mig2 repress expression of each HXT gene determines which of them have a pulse of transcription in response to glucose. Finally, the model correctly predicts how lesions in the feed forward loop change the kinetics of induction of HXT4 expression.

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Year:  2010        PMID: 20810924      PMCID: PMC2944743          DOI: 10.1073/pnas.0912483107

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


  31 in total

1.  Grr1-dependent inactivation of Mth1 mediates glucose-induced dissociation of Rgt1 from HXT gene promoters.

Authors:  Karin M Flick; Nathalie Spielewoy; Tatyana I Kalashnikova; Marisela Guaderrama; Qianzheng Zhu; Hui-Chu Chang; Curt Wittenberg
Journal:  Mol Biol Cell       Date:  2003-05-18       Impact factor: 4.138

2.  Integrative analysis of cell cycle control in budding yeast.

Authors:  Katherine C Chen; Laurence Calzone; Attila Csikasz-Nagy; Frederick R Cross; Bela Novak; John J Tyson
Journal:  Mol Biol Cell       Date:  2004-05-28       Impact factor: 4.138

3.  Mechanistic systems models of cell signaling networks: a case study of myocyte adrenergic regulation.

Authors:  Jeffrey J Saucerman; Andrew D McCulloch
Journal:  Prog Biophys Mol Biol       Date:  2004 Jun-Jul       Impact factor: 3.667

4.  A nonlinear discrete dynamical model for transcriptional regulation: construction and properties.

Authors:  John Goutsias; Seungchan Kim
Journal:  Biophys J       Date:  2004-04       Impact factor: 4.033

5.  Glucose repression/derepression in budding yeast: SNF1 protein kinase is activated by phosphorylation under derepressing conditions, and this correlates with a high AMP:ATP ratio.

Authors:  W A Wilson; S A Hawley; D G Hardie
Journal:  Curr Biol       Date:  1996-11-01       Impact factor: 10.834

6.  Characterization of the yeast transcriptome.

Authors:  V E Velculescu; L Zhang; W Zhou; J Vogelstein; M A Basrai; D E Bassett; P Hieter; B Vogelstein; K W Kinzler
Journal:  Cell       Date:  1997-01-24       Impact factor: 41.582

7.  Stochastic mechanisms in gene expression.

Authors:  H H McAdams; A Arkin
Journal:  Proc Natl Acad Sci U S A       Date:  1997-02-04       Impact factor: 11.205

8.  The OR control system of bacteriophage lambda. A physical-chemical model for gene regulation.

Authors:  M A Shea; G K Ackers
Journal:  J Mol Biol       Date:  1985-01-20       Impact factor: 5.469

9.  Global analysis of protein expression in yeast.

Authors:  Sina Ghaemmaghami; Won-Ki Huh; Kiowa Bower; Russell W Howson; Archana Belle; Noah Dephoure; Erin K O'Shea; Jonathan S Weissman
Journal:  Nature       Date:  2003-10-16       Impact factor: 49.962

10.  Three different regulatory mechanisms enable yeast hexose transporter (HXT) genes to be induced by different levels of glucose.

Authors:  S Ozcan; M Johnston
Journal:  Mol Cell Biol       Date:  1995-03       Impact factor: 4.272

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  17 in total

1.  Automated refinement and inference of analytical models for metabolic networks.

Authors:  Michael D Schmidt; Ravishankar R Vallabhajosyula; Jerry W Jenkins; Jonathan E Hood; Abhishek S Soni; John P Wikswo; Hod Lipson
Journal:  Phys Biol       Date:  2011-08-10       Impact factor: 2.583

2.  Enhanced xylose fermentation capacity related to an altered glucose sensing and repression network in a recombinant Saccharomyces cerevisiae.

Authors:  Yu Shen; Jin Hou; Xiaoming Bao
Journal:  Bioengineered       Date:  2013-06-26       Impact factor: 3.269

3.  Gene regulatory networks and the role of robustness and stochasticity in the control of gene expression.

Authors:  Lesley T Macneil; Albertha J M Walhout
Journal:  Genome Res       Date:  2011-02-04       Impact factor: 9.043

4.  Cellular effects and epistasis among three determinants of adaptation in experimental populations of Saccharomyces cerevisiae.

Authors:  Lucas S Parreiras; Linda M Kohn; James B Anderson
Journal:  Eukaryot Cell       Date:  2011-08-19

Review 5.  Nutritional control of growth and development in yeast.

Authors:  James R Broach
Journal:  Genetics       Date:  2012-09       Impact factor: 4.562

6.  Helix-loop-helix/basic helix-loop-helix transcription factor network represses cell elongation in Arabidopsis through an apparent incoherent feed-forward loop.

Authors:  Miroslava K Zhiponova; Kengo Morohashi; Isabelle Vanhoutte; Katja Machemer-Noonan; Miglena Revalska; Marc Van Montagu; Erich Grotewold; Eugenia Russinova
Journal:  Proc Natl Acad Sci U S A       Date:  2014-02-06       Impact factor: 11.205

7.  Innate immune memory and homeostasis may be conferred through crosstalk between the TLR3 and TLR7 pathways.

Authors:  Bing Liu; Qian Liu; Lei Yang; Sucheendra K Palaniappan; Ivet Bahar; P S Thiagarajan; Jeak Ling Ding
Journal:  Sci Signal       Date:  2016-07-12       Impact factor: 8.192

8.  Model-based transcriptome engineering promotes a fermentative transcriptional state in yeast.

Authors:  Drew G Michael; Ezekiel J Maier; Holly Brown; Stacey R Gish; Christopher Fiore; Randall H Brown; Michael R Brent
Journal:  Proc Natl Acad Sci U S A       Date:  2016-11-03       Impact factor: 11.205

Review 9.  Regulations of sugar transporters: insights from yeast.

Authors:  J Horák
Journal:  Curr Genet       Date:  2013-03-01       Impact factor: 3.886

Review 10.  The structure of dynamic GPCR signaling networks.

Authors:  Patrick R O'Neill; Lopamudra Giri; W K Ajith Karunarathne; Anilkumar K Patel; K V Venkatesh; N Gautam
Journal:  Wiley Interdiscip Rev Syst Biol Med       Date:  2014 Jan-Feb
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