Yan2012 - Rb-E2F pathway dynamics with miR449

  public model
Model Identifier
BIOMD0000000720
Short description
MiRNAs, which are a family of small non-coding RNAs, regulate a broad array of physiological and developmental processes. However, their regulatory roles have remained largely mysterious. E2F is a positive regulator of cell cycle progression and also a potent inducer of apoptosis. Positive feedback loops in the regulation of Rb-E2F pathway are predicted and shown experimentally. Recently, it has been discovered that E2F induce a cluster of miRNAs called miR449. In turn, E2F is inhibited by miR449 through regulating different transcripts, thus forming negative feedback loops in the interaction network. Here, based on the integration of experimental evidence and quantitative data, we studied Rb-E2F pathway coupling the positive feedback loops and negative feedback loops mediated by miR449. Therefore, a mathematical model is constructed based in part on the model proposed in Yao-Lee et al. (2008) and nonlinear dynamical behaviors including the stability and bifurcations of the model are discussed.
Format
SBML (L2V4)
Related Publication
  • Dynamical behaviors of Rb-E2F pathway including negative feedback loops involving miR449.
  • Yan F, Liu H, Hao J, Liu Z
  • PloS one , 1/ 2012 , Volume 7 , Issue 9 , pages: e43908 , PubMed ID: 23028477
  • Department of Mathematics, Shanghai University, Shanghai, PR China.
  • MiRNAs, which are a family of small non-coding RNAs, regulate a broad array of physiological and developmental processes. However, their regulatory roles have remained largely mysterious. E2F is a positive regulator of cell cycle progression and also a potent inducer of apoptosis. Positive feedback loops in the regulation of Rb-E2F pathway are predicted and shown experimentally. Recently, it has been discovered that E2F induce a cluster of miRNAs called miR449. In turn, E2F is inhibited by miR449 through regulating different transcripts, thus forming negative feedback loops in the interaction network. Here, based on the integration of experimental evidence and quantitative data, we studied Rb-E2F pathway coupling the positive feedback loops and negative feedback loops mediated by miR449. Therefore, a mathematical model is constructed based in part on the model proposed in Yao-Lee et al. (2008) and nonlinear dynamical behaviors including the stability and bifurcations of the model are discussed. A comparison is given to reveal the implication of the fundamental differences of Rb-E2F pathway between regulation and deregulation of miR449. Coherent with the experiments it predicts that miR449 plays a critical role in regulating the cell cycle progression and provides a twofold safety mechanism to avoid excessive E2F-induced proliferation by cell cycle arrest and apoptosis. Moreover, numerical simulation and bifurcation analysis shows that the mechanisms of the negative regulation of miR449 to three different transcripts are quite distinctive which needs to be verified experimentally. This study may help us to analyze the whole cell cycle process mediated by other miRNAs more easily. A better knowledge of the dynamical behaviors of miRNAs mediated networks is also of interest for bio-engineering and artificial control.
Contributors
Submitter of the first revision: Ashley Xavier
Submitter of this revision: Ashley Xavier
Modellers: Ashley Xavier

Metadata information

isDescribedBy (3 statements)
BioModels Database BIOMD0000000318
DOI 10.1371/journal.pone.0043908
PubMed 23028477

is (2 statements)
BioModels Database BIOMD0000000720
BioModels Database MODEL1811080001

isDerivedFrom (5 statements)
Taxonomy Mammalia
Gene Ontology cell cycle
Reactome G1/S Transition
BioModels Database BIOMD0000000318
Mathematical Modelling Ontology Ordinary differential equation model

hasTaxon (1 statement)
Taxonomy Mammalia

hasPart (1 statement)
Gene Ontology cell cycle

hasProperty (1 statement)
Mathematical Modelling Ontology Ordinary differential equation model

isPartOf (1 statement)
Reactome G1/S Transition

Curation status
Curated
Modelling approach(es)
ordinary differential equation model
Tags

Connected external resources

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Name Description Size Actions

Model files
Yan2012.xml SBML lvl2 file containing the model 60.18 KB Preview | Download

Additional files
Yan2012.cps copasi file to generate figure 7 (i) 118.32 KB Preview | Download

  • Model originally submitted by : Ashley Xavier
  • Submitted: Nov 8, 2018 10:10:08 AM
  • Last Modified: Nov 8, 2018 11:34:52 AM
Revisions
  • Version: 6 public model Download this version
    • Submitted on: Nov 8, 2018 11:34:52 AM
    • Submitted by: Ashley Xavier
    • With comment: Automatically added model identifier BIOMD0000000720
  • Version: 3 public model Download this version
    • Submitted on: Nov 8, 2018 10:10:08 AM
    • Submitted by: Ashley Xavier
    • With comment: Automatically added model identifier BIOMD0000000720

(*) You might be seeing discontinuous revisions as only public revisions are displayed here. Any private revisions unpublished model revision of this model will only be shown to the submitter and their collaborators.

Legends
: Variable used inside SBML models


Species
Species Initial Concentration/Amount
Myc

Myc proto-oncogene protein 		0.0 mmol
CycD

Cyclin-dependent kinase 6 ; Cyclin-dependent kinase 4 ; G1/S-specific cyclin-D2 ; G1/S-specific cyclin-D3 ; G1/S-specific cyclin-D1 		0.0 mmol
RE

Transcription factor E2F1 ; Retinoblastoma-associated protein 		0.0 mmol
RB

Retinoblastoma-associated protein 		0.55 mmol
PRB

Retinoblastoma-associated protein ; Phosphorylated Peptide 		0.0 mmol
miR449

MIMAT0001541 		0.0 mmol
Reactions
Reactions Rate Parameters
miR449 + Myc => ; miR449 compartment*kdM2*miR449*Myc/(JM+Myc) kdM2 = 0.6; JM = 0.15
=> Myc; S compartment*ksM*S/(JS+S) ksM = 1.0; JS = 0.5
=> CycD; Myc compartment*ksCD2*Myc/(JM+Myc) JM = 0.15; ksCD2 = 0.03
RE => compartment*kdRE*RE kdRE = 0.03
E2F + RB => RE compartment*kRE*E2F*RB kRE = 180.0
PRB => compartment*kdP*PRB kdP = 0.06
RE => E2F + PRB; CycE compartment*kP2*CycE*RE/(JCE+RE) JCE = 0.92; kP2 = 18.0
miR449 + CycE => ; miR449 compartment*kdCE2*miR449*CycE/(JCE+CycE) kdCE2 = 0.7; JCE = 0.92
miR449 + CycD => ; miR449 compartment*kdCD2*miR449*CycD/(JCD+CycD) JCD = 0.92; kdCD2 = 1.0
RE => E2F + PRB; CycD compartment*kP1*CycD*RE/(JCD+RE) JCD = 0.92; kP1 = 18.0
Curator's comment:
(added: 08 Nov 2018, 10:09:43, updated: 08 Nov 2018, 10:09:43)
The model was encoded and simulated using COPASI 4.24 and the figure was plotted using R 3.5.1.