Model Identifier
BIOMD0000000223
Short description

described in: Systems-level interactions between insulin-EGF networks amplify mitogenic signaling.
Borisov N, Aksamitiene E, Kiyatkin A, Legewie S, Berkhout J, Maiwald T, Kaimachnikov NP, Timmer J, Hoek JB, Kholodenko BN.;Mol Syst Biol. 2009;5:256. Epub 2009 Apr 7. PMID:19357636; doi:10.1038/msb.2009.19
Abstract:
Crosstalk mechanisms have not been studied as thoroughly as individual signaling pathways. We exploit experimental and computational approaches to reveal how a concordant interplay between the insulin and epidermal growth factor (EGF) signaling networks can potentiate mitogenic signaling. In HEK293 cells, insulin is a poor activator of the Ras/ERK (extracellular signal-regulated kinase) cascade, yet it enhances ERK activation by low EGF doses. We find that major crosstalk mechanisms that amplify ERK signaling are localized upstream of Ras and at the Ras/Raf level. Computational modeling unveils how critical network nodes, the adaptor proteins GAB1 and insulin receptor substrate (IRS), Src kinase, and phosphatase SHP2, convert insulin-induced increase in the phosphatidylinositol-3,4,5-triphosphate (PIP(3)) concentration into enhanced Ras/ERK activity. The model predicts and experiments confirm that insulin-induced amplification of mitogenic signaling is abolished by disrupting PIP(3)-mediated positive feedback via GAB1 and IRS. We demonstrate that GAB1 behaves as a non-linear amplifier of mitogenic responses and insulin endows EGF signaling with robustness to GAB1 suppression. Our results show the feasibility of using computational models to identify key target combinations and predict complex cellular responses to a mixture of external cues.

An extracellular compartment with 34 times the volume of the cell was added and the association rate as well as the dissociation constants for Insulin and EGF binding were altered (kon'=34*kon, KD'=KD/34). This was done to allow using the concentrations for those species given in the article and retaining the same dynamics and Ligand depletion as in the matlab file the SBML file was exported from.

SBML model exported from PottersWheel on 2008-10-14 16:26:44.

This model originates from BioModels Database: A Database of Annotated Published Models (http://www.ebi.ac.uk/biomodels/). It is copyright (c) 2005-2011 The BioModels.net Team.
For more information see the terms of use.
To cite BioModels Database, please use: Li C, Donizelli M, Rodriguez N, Dharuri H, Endler L, Chelliah V, Li L, He E, Henry A, Stefan MI, Snoep JL, Hucka M, Le Novère N, Laibe C (2010) BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models. BMC Syst Biol., 4:92.

Format
SBML (L2V4)
Related Publication
  • Systems-level interactions between insulin-EGF networks amplify mitogenic signaling.
  • Nikolay Borisov, Edita Aksamitiene, Anatoly Kiyatkin, Stefan Legewie, Jan Berkhout, Thomas Maiwald, Nikolai P Kaimachnikov, Jens Timmer, Jan B Hoek, Boris N Kholodenko
  • Molecular systems biology , 0/ 2009 , Volume 5 , pages: 256 , PubMed ID: 19357636
Contributors
Submitter of the first revision: Nicolas Le Novère
Submitter of this revision: Lucian Smith
Curator: Lucian Smith
Modeller: Nicolas Le Novère

Metadata information

is (2 statements)
BioModels Database BIOMD0000000223
BioModels Database MODEL6194251662

isDerivedFrom (9 statements)
BioModels Database BIOMD0000000028
BioModels Database BIOMD0000000030
BioModels Database BIOMD0000000031
BioModels Database BIOMD0000000048
BioModels Database BIOMD0000000146
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isDescribedBy (1 statement)
PubMed 19357636

hasTaxon (1 statement)
Taxonomy Homo sapiens

isVersionOf (1 statement)
hasVersion (4 statements)
hasProperty (1 statement)
Mathematical Modelling Ontology Ordinary differential equation model


Curation status
Curated


Connected external resources