Fujita2010_Akt_Signalling_EGF

  public model
Model Identifier
BIOMD0000000262
Short description

EGF dependent Akt pathway model

made by Kazuhiro A. Fujita.

This is the EGF dependent Akt pathway model described in:
Decoupling of receptor and downstream signals in the Akt pathway by its low-pass filter characteristics.
Fujita KA, Toyoshima Y, Uda S, Ozaki Y, Kubota H, and Kuroda S. Sci Signal. 2010 Jul 27;3(132):ra56. PMID: 20664065 ; DOI: 10.1126/scisignal.2000810
Abstract:
In cellular signal transduction, the information in an external stimulus is encoded in temporal patterns in the activities of signaling molecules; for example, pulses of a stimulus may produce an increasing response or may produce pulsatile responses in the signaling molecules. Here, we show how the Akt pathway, which is involved in cell growth, specifically transmits temporal information contained in upstream signals to downstream effectors. We modeled the epidermal growth factor (EGF)–dependent Akt pathway in PC12 cells on the basis of experimental results. We obtained counterintuitive results indicating that the sizes of the peak amplitudes of receptor and downstream effector phosphorylation were decoupled; weak, sustained EGF receptor (EGFR) phosphorylation, rather than strong, transient phosphorylation, strongly induced phosphorylation of the ribosomal protein S6, a molecule downstream of Akt. Using frequency response analysis, we found that a three-component Akt pathway exhibited the property of a low-pass filter and that this property could explain decoupling of the peak amplitudes of receptor phosphorylation and that of downstream effectors. Furthermore, we found that lapatinib, an EGFR inhibitor used as an anticancer drug, converted strong, transient Akt phosphorylation into weak, sustained Akt phosphorylation, and, because of the low-pass filter characteristics of the Akt pathway, this led to stronger S6 phosphorylation than occurred in the absence of the inhibitor. Thus, an EGFR inhibitor can potentially act as a downstream activator of some effectors.

The different versions of input, step, pulse and ramp, can be simulated using the parameters EGF_conc_pulse , EGF_conc_step and EGF_conc_ramp . Depending on which one is set unequal to 0, either a continous pulse with value EGF_conc_pulse , a 60 second step with EGF_conc_step or a signal increasing from 0 to EGF_conc_pulse over a time periode of 3600 seconds are used as input. In case more than one parameter are set to values greater than 0 these input profiles are added to each other. The pulse time and the time over which the ramp input increases can be set by pulse_time and ramp_time .

This model originates from BioModels Database: A Database of Annotated Published Models. It is copyright (c) 2005-2010 The BioModels Team.
For more information see the terms of use .
To cite BioModels Database, please use Le Novère N., Bornstein B., Broicher A., Courtot M., Donizelli M., Dharuri H., Li L., Sauro H., Schilstra M., Shapiro B., Snoep J.L., Hucka M. (2006) BioModels Database: A Free, Centralized Database of Curated, Published, Quantitative Kinetic Models of Biochemical and Cellular Systems Nucleic Acids Res., 34: D689-D691.

Format
SBML (L2V4)
Related Publication
  • Decoupling of receptor and downstream signals in the Akt pathway by its low-pass filter characteristics.
  • Fujita KA, Toyoshima Y, Uda S, Ozaki Y, Kubota H, Kuroda S
  • Science signaling , 0/ 2010 , Volume 3 , pages: ra56 , PubMed ID: 20664065
  • Department of Computational Biology, Graduate School of Frontier Sciences, University of Tokyo, Kshiwanoha 5-1-5, Kashiwa, Chiba 277-8568, Japan.
  • In cellular signal transduction, the information in an external stimulus is encoded in temporal patterns in the activities of signaling molecules; for example, pulses of a stimulus may produce an increasing response or may produce pulsatile responses in the signaling molecules. Here, we show how the Akt pathway, which is involved in cell growth, specifically transmits temporal information contained in upstream signals to downstream effectors. We modeled the epidermal growth factor (EGF)-dependent Akt pathway in PC12 cells on the basis of experimental results. We obtained counterintuitive results indicating that the sizes of the peak amplitudes of receptor and downstream effector phosphorylation were decoupled; weak, sustained EGF receptor (EGFR) phosphorylation, rather than strong, transient phosphorylation, strongly induced phosphorylation of the ribosomal protein S6, a molecule downstream of Akt. Using frequency response analysis, we found that a three-component Akt pathway exhibited the property of a low-pass filter and that this property could explain decoupling of the peak amplitudes of receptor phosphorylation and that of downstream effectors. Furthermore, we found that lapatinib, an EGFR inhibitor used as an anticancer drug, converted strong, transient Akt phosphorylation into weak, sustained Akt phosphorylation, and, because of the low-pass filter characteristics of the Akt pathway, this led to stronger S6 phosphorylation than occurred in the absence of the inhibitor. Thus, an EGFR inhibitor can potentially act as a downstream activator of some effectors.
Contributors
Kazuhiro Fujita

Metadata information

is
BioModels Database MODEL1004060001
BioModels Database BIOMD0000000262
isDescribedBy
PubMed 20664065
hasTaxon
occursIn
Brenda Tissue Ontology PC-12 cell

Curation status
Curated

Tags
Name Description Size Actions

Model files

BIOMD0000000262_url.xml SBML L2V4 representation of Fujita2010_Akt_Signalling_EGF 39.04 KB Preview | Download

Additional files

BIOMD0000000262_urn.xml Auto-generated SBML file with URNs 41.96 KB Preview | Download
BIOMD0000000262.png Auto-generated Reaction graph (PNG) 53.59 KB Preview | Download
BIOMD0000000262.vcml Auto-generated VCML file 928.00 bytes Preview | Download
BIOMD0000000262.sci Auto-generated Scilab file 202.00 bytes Preview | Download
BIOMD0000000262.svg Auto-generated Reaction graph (SVG) 0.00 bytes Preview | Download
BIOMD0000000262-biopax2.owl Auto-generated BioPAX (Level 2) 22.93 KB Preview | Download
BIOMD0000000262.xpp Auto-generated XPP file 5.63 KB Preview | Download
BIOMD0000000262.m Auto-generated Octave file 7.79 KB Preview | Download
BIOMD0000000262.pdf Auto-generated PDF file 209.33 KB Preview | Download
BIOMD0000000262-biopax3.owl Auto-generated BioPAX (Level 3) 34.17 KB Preview | Download

  • Model originally submitted by : Kazuhiro Fujita
  • Submitted: 06-Apr-2010 08:51:17
  • Last Modified: 21-Feb-2014 11:14:39
Revisions
  • Version: 2 public model Download this version
    • Submitted on: 21-Feb-2014 11:14:39
    • Submitted by: Kazuhiro Fujita
    • With comment: Current version of Fujita2010_Akt_Signalling_EGF
  • Version: 1 public model Download this version
    • Submitted on: 06-Apr-2010 08:51:17
    • Submitted by: Kazuhiro Fujita
    • With comment: Original import of Akt Pathway model
Legends
: Variable used inside SBML models


Species
Species Initial Concentration/Amount
EGF 0.0 ng
EGFR

Egfr
68190.1837333797 dimensionless
pEGFR

Egfr
0.0 dimensionless
pAkt

RAC-gamma serine/threonine-protein kinase ; Phosphoprotein
0.0 dimensionless
S6

40S ribosomal protein S6
3.54316740542218 dimensionless
pAkt S6

40S ribosomal protein S6 ; RAC-gamma serine/threonine-protein kinase ; Phosphoprotein
0.0 dimensionless
pS6

40S ribosomal protein S6 ; Phosphoprotein
0.0 dimensionless
Reactions
Reactions Rate Parameters
(EGF + EGFR) => (EGF_EGFR)

([EGF] + [Egfr]) => ([Egfr; Pro-epidermal growth factor])
Cell*(k1*EGF*EGFR-k2*EGF_EGFR)

Cell*(k1*[EGF]*[Egfr]-k2*[Egfr; Pro-epidermal growth factor])
k1=0.00673816; k2=0.040749 per second
EGF_conc_ramp = 30.0 ng_per_ml; EGF_conc_impulse = 0.0 ng_per_ml; EGF_conc_step = 0.0 ng_per_ml; ramp_time = 3600.0 seconds; pulse_time = 60.0 seconds
(pEGFR + Akt) => (pEGFR_Akt)

([Egfr] + [RAC-gamma serine/threonine-protein kinase]) => ([Egfr; RAC-gamma serine/threonine-protein kinase; Phosphoprotein])
Cell*(k1*pEGFR*Akt-k2*pEGFR_Akt)

Cell*(k1*[Egfr]*[RAC-gamma serine/threonine-protein kinase]-k2*[Egfr; RAC-gamma serine/threonine-protein kinase; Phosphoprotein])
k2=0.00517473 per second; k1=1.5543E-5 per conc per second
(pAkt + S6) => (pAkt_S6)

([RAC-gamma serine/threonine-protein kinase; Phosphoprotein] + [40S ribosomal protein S6]) => ([40S ribosomal protein S6; RAC-gamma serine/threonine-protein kinase; Phosphoprotein])
Cell*(k1*pAkt*S6-k2*pAkt_S6)

Cell*(k1*[RAC-gamma serine/threonine-protein kinase; Phosphoprotein]*[40S ribosomal protein S6]-k2*[40S ribosomal protein S6; RAC-gamma serine/threonine-protein kinase; Phosphoprotein])
k1=2.10189E-6 per conc per second; k2=5.1794E-15 per second
(pAkt_S6) => (pAkt + pS6)

([40S ribosomal protein S6; RAC-gamma serine/threonine-protein kinase; Phosphoprotein]) => ([RAC-gamma serine/threonine-protein kinase; Phosphoprotein] + [40S ribosomal protein S6; Phosphoprotein])
Cell*k1*pAkt_S6

Cell*k1*[40S ribosomal protein S6; RAC-gamma serine/threonine-protein kinase; Phosphoprotein]
k1=0.00121498 per second
(pAkt) => (Akt)

([RAC-gamma serine/threonine-protein kinase; Phosphoprotein]) => ([RAC-gamma serine/threonine-protein kinase])
Cell*k1*pAkt

Cell*k1*[RAC-gamma serine/threonine-protein kinase; Phosphoprotein]
k1=0.0327962 per second
(pS6) => (S6)

([40S ribosomal protein S6; Phosphoprotein]) => ([40S ribosomal protein S6])
Cell*k1*pS6

Cell*k1*[40S ribosomal protein [40S ribosomal protein S6]; Phosphoprotein]
k1=0.00113102 per second
(pro_EGFR) => (EGFR)

([Egfr]) => ([Egfr])
Cell*EGFR_turnover*pro_EGFR

Cell*EGFR_turnover*[Egfr]
EGFR_turnover = 1.06386129269658E-4 per second
(EGFR) => ()

([Egfr]) => ()
Cell*EGFR_turnover*EGFR

Cell*EGFR_turnover*[Egfr]
EGFR_turnover = 1.06386129269658E-4 per second
Curator's comment:
(added: 24 Aug 2010, 12:49:20, updated: 24 Aug 2010, 12:49:20)
Reproduction of figure 1C from the original article using SBML ODESolver (cvs October 2009). To obtain the the various results the parameter EGF_conc_ramp was set to the desired final value of EGF.