Literature DB >> 17012329

A rate equation approach to elucidate the kinetics and robustness of the TGF-beta pathway.

Pontus Melke1, Henrik Jönsson, Evangelia Pardali, Peter ten Dijke, Carsten Peterson.   

Abstract

We present a rate equation model for the TGF-beta pathway in endothelial cells together with novel measurements. This pathway plays a prominent role in inter- and intracellular communication and subversion can lead to cancer, fibrosis vascular disorders, and immune diseases. The model successfully describes the kinetics of experimental data and also correctly predicts the behavior in experiments where the system is perturbed. A novel method in this context, simulated tempering, is used to fit the model parameters to the data. It provides an ensemble of high quality solutions, which are analyzed with clustering methods and display a hierarchical structure highlighting distinct parameter subspaces with biological interpretations. This analysis discriminates between different biological mechanisms to achieve a transient signal from a sustained TGF-beta input, where one mechanism is to use a negative feedback to turn the signal off. Further analysis in terms of parameter sensitivity reveals that this negative feedback loop in TGF-beta signaling renders the system global robustness. This sheds light upon the role of the Smad7 protein in this system.

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Year:  2006        PMID: 17012329      PMCID: PMC1779910          DOI: 10.1529/biophysj.105.080408

Source DB:  PubMed          Journal:  Biophys J        ISSN: 0006-3495            Impact factor:   4.033


  20 in total

1.  Smurf1 interacts with transforming growth factor-beta type I receptor through Smad7 and induces receptor degradation.

Authors:  T Ebisawa; M Fukuchi; G Murakami; T Chiba; K Tanaka; T Imamura; K Miyazono
Journal:  J Biol Chem       Date:  2001-02-13       Impact factor: 5.157

Review 2.  Mechanisms of TGF-beta signaling from cell membrane to the nucleus.

Authors:  Yigong Shi; Joan Massagué
Journal:  Cell       Date:  2003-06-13       Impact factor: 41.582

3.  Non-linear optimization of biochemical pathways: applications to metabolic engineering and parameter estimation.

Authors:  P Mendes; D Kell
Journal:  Bioinformatics       Date:  1998       Impact factor: 6.937

Review 4.  Patterns and emerging mechanisms of the angiogenic switch during tumorigenesis.

Authors:  D Hanahan; J Folkman
Journal:  Cell       Date:  1996-08-09       Impact factor: 41.582

5.  Distinct endocytic pathways regulate TGF-beta receptor signalling and turnover.

Authors:  Gianni M Di Guglielmo; Christine Le Roy; Anne F Goodfellow; Jeffrey L Wrana
Journal:  Nat Cell Biol       Date:  2003-05       Impact factor: 28.824

6.  Induction of inhibitory Smad6 and Smad7 mRNA by TGF-beta family members.

Authors:  M Afrakhte; A Morén; S Jossan; S Itoh; K Sampath; B Westermark; C H Heldin; N E Heldin; P ten Dijke
Journal:  Biochem Biophys Res Commun       Date:  1998-08-19       Impact factor: 3.575

Review 7.  New insights into TGF-beta-Smad signalling.

Authors:  Peter ten Dijke; Caroline S Hill
Journal:  Trends Biochem Sci       Date:  2004-05       Impact factor: 13.807

8.  Nucleocytoplasmic shuttling of Smads 2, 3, and 4 permits sensing of TGF-beta receptor activity.

Authors:  Gareth J Inman; Francisco J Nicolás; Caroline S Hill
Journal:  Mol Cell       Date:  2002-08       Impact factor: 17.970

9.  Signal processing in the TGF-beta superfamily ligand-receptor network.

Authors:  Jose M G Vilar; Ronald Jansen; Chris Sander
Journal:  PLoS Comput Biol       Date:  2006-01-27       Impact factor: 4.475

10.  Smad7 and protein phosphatase 1alpha are critical determinants in the duration of TGF-beta/ALK1 signaling in endothelial cells.

Authors:  Gudrun Valdimarsdottir; Marie-José Goumans; Fumiko Itoh; Susumu Itoh; Carl-Henrik Heldin; Peter ten Dijke
Journal:  BMC Cell Biol       Date:  2006-03-29       Impact factor: 4.241

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  27 in total

1.  Trafficking coordinate description of intracellular transport control of signaling networks.

Authors:  Jose M G Vilar; Leonor Saiz
Journal:  Biophys J       Date:  2011-11-15       Impact factor: 4.033

2.  Computational modelling of Smad-mediated negative feedback and crosstalk in the TGF-β superfamily network.

Authors:  Daniel Nicklas; Leonor Saiz
Journal:  J R Soc Interface       Date:  2013-06-26       Impact factor: 4.118

3.  Spatial aspects in the SMAD signaling pathway.

Authors:  J Claus; E Friedmann; U Klingmüller; R Rannacher; T Szekeres
Journal:  J Math Biol       Date:  2012-09-18       Impact factor: 2.259

4.  Literature-based automated reconstruction, expansion, and refinement of the TGF-β superfamily ligand-receptor network.

Authors:  Qian Mei; Leonor Saiz
Journal:  J Membr Biol       Date:  2014-03-02       Impact factor: 1.843

5.  An integrative modeling framework reveals plasticity of TGF-β signaling.

Authors:  Geoffroy Andrieux; Michel Le Borgne; Nathalie Théret
Journal:  BMC Syst Biol       Date:  2014-03-12

Review 6.  Decoding the quantitative nature of TGF-beta/Smad signaling.

Authors:  David C Clarke; Xuedong Liu
Journal:  Trends Cell Biol       Date:  2008-08-15       Impact factor: 20.808

7.  Cross-scale, cross-pathway evaluation using an agent-based non-small cell lung cancer model.

Authors:  Zhihui Wang; Christina M Birch; Jonathan Sagotsky; Thomas S Deisboeck
Journal:  Bioinformatics       Date:  2009-07-04       Impact factor: 6.937

8.  Transforming growth factor beta depletion is the primary determinant of Smad signaling kinetics.

Authors:  David C Clarke; Meredith L Brown; Richard A Erickson; Yigong Shi; Xuedong Liu
Journal:  Mol Cell Biol       Date:  2009-02-17       Impact factor: 4.272

9.  Quantitative modeling and analysis of the transforming growth factor beta signaling pathway.

Authors:  Seung-Wook Chung; Fayth L Miles; Robert A Sikes; Carlton R Cooper; Mary C Farach-Carson; Babatunde A Ogunnaike
Journal:  Biophys J       Date:  2009-03-04       Impact factor: 4.033

10.  Input-output behavior of ErbB signaling pathways as revealed by a mass action model trained against dynamic data.

Authors:  William W Chen; Birgit Schoeberl; Paul J Jasper; Mario Niepel; Ulrik B Nielsen; Douglas A Lauffenburger; Peter K Sorger
Journal:  Mol Syst Biol       Date:  2009-01-20       Impact factor: 11.429

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