Kok2020 - IFNalpha-induced signaling in Huh7.5 cells

  public model
Model Identifier
BIOMD0000000959
Short description 
The proposed ODE model describes dynamics of IFNalpha-induced signaling in Huh7.5 cells for a time scale up to 32 hours after stimulation with IFNalpha. The model consists of an IFN receptor model, formation/degradation and cytoplasmic/nuclear shuttling of STAT1-homodimers, STAT1-STAT2-heterodimers and STAT1-STAT2-IRF9 (ISGF3) complexes. On top, formation of feedback proteins STAT1, STAT2, IRF9, USP18, SOCS1, SOCS3 and IRF2 and corresponding influences on IFNalpha signaling dynamics was incorporated. The model was calibrated by dose response and time course measurements over 32 hours as well as time courses for USP18 inhibition and overexpression experiments. As a special focus, the model is able to describe dose-dependent sensitization and desensitization of IFNalpha signaling in form of double treatment experiments at 0h and 24h.
Format
SBML (L2V4)
Related Publication
  • Disentangling molecular mechanisms regulating sensitization of interferon alpha signal transduction.
  • Kok F, Rosenblatt M, Teusel M, Nizharadze T, Gonçalves Magalhães V, Dächert C, Maiwald T, Vlasov A, Wäsch M, Tyufekchieva S, Hoffmann K, Damm G, Seehofer D, Boettler T, Binder M, Timmer J, Schilling M, Klingmüller U
  • Molecular systems biology , 7/ 2020 , Volume 16 , Issue 7 , pages: e8955 , PubMed ID: 32696599
  • Division Systems Biology of Signal Transduction, German Cancer Research Center (DKFZ), Heidelberg, Germany.
  • Tightly interlinked feedback regulators control the dynamics of intracellular responses elicited by the activation of signal transduction pathways. Interferon alpha (IFNα) orchestrates antiviral responses in hepatocytes, yet mechanisms that define pathway sensitization in response to prestimulation with different IFNα doses remained unresolved. We establish, based on quantitative measurements obtained for the hepatoma cell line Huh7.5, an ordinary differential equation model for IFNα signal transduction that comprises the feedback regulators STAT1, STAT2, IRF9, USP18, SOCS1, SOCS3, and IRF2. The model-based analysis shows that, mediated by the signaling proteins STAT2 and IRF9, prestimulation with a low IFNα dose hypersensitizes the pathway. In contrast, prestimulation with a high dose of IFNα leads to a dose-dependent desensitization, mediated by the negative regulators USP18 and SOCS1 that act at the receptor. The analysis of basal protein abundance in primary human hepatocytes reveals high heterogeneity in patient-specific amounts of STAT1, STAT2, IRF9, and USP18. The mathematical modeling approach shows that the basal amount of USP18 determines patient-specific pathway desensitization, while the abundance of STAT2 predicts the patient-specific IFNα signal response.
Contributors
Submitter of the first revision: Marcus Rosenblatt
Submitter of this revision: Krishna Kumar Tiwari
Modellers: Krishna Kumar Tiwari, Marcus Rosenblatt

Metadata information

is (3 statements)
BioModels Database MODEL2005110001
BioModels Database BIOMD0000000959
BioModels Database MODEL2005110001

isDescribedBy (1 statement)
PubMed 32696599

hasProperty (3 statements)
occursIn (1 statement)
Brenda Tissue Ontology Huh-7.5 cell

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

Connected external resources

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Name Description Size Actions

Model files
Kok2020.xml SBML L2V4 representation of IFNa signalling model 271.56 KB Preview | Download

Additional files
Kok2020.cps COPASI 4.29 (Build228) model file for the model 308.41 KB Preview | Download
Kok2020.sedml SEDML file for the model 56.80 KB Preview | Download
SBML_IFNa_Huh75 (1).xml Original xml file submitted by author 228.59 KB Preview | Download

  • Model originally submitted by : Marcus Rosenblatt
  • Submitted: Jul 29, 2020 12:21:38 PM
  • Last Modified: Aug 17, 2020 7:03:50 PM
Revisions
  • Version: 8 public model Download this version
    • Submitted on: Aug 17, 2020 7:03:50 PM
    • Submitted by: Krishna Kumar Tiwari
    • With comment: Automatically added model identifier BIOMD0000000959
  • Version: 6 public model Download this version
    • Submitted on: Jul 29, 2020 12:21:38 PM
    • Submitted by: Krishna Kumar Tiwari
    • With comment: Updated authors list for the submitted model

(*) 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
USP18

Q9UMW8 		1746.0 nmol
STAT2n

P52630 ; Nuclear 		3039.0 nmol
SOCS1mRNA

Messenger RNA ; Suppressor of cytokine signaling 1 		0.8286 nmol
STAT1 LC 2

Signal transducer and activator of transcription 1-alpha/beta ; Translation ; Signal transducer and activator of transcription 1-alpha/beta 		460600.0 nmol
STAT1 LC 3

Signal transducer and activator of transcription 1-alpha/beta ; Translation ; Signal transducer and activator of transcription 1-alpha/beta 		460600.0 nmol
STAT2 LC 2

P52630 ; Translation ; P52630 		2520.0 nmol
USP18 LC 1

Q9UMW8 ; Translation ; Q9UMW8 		1745.0 nmol
STAT2c

P52630 ; C13226 		30390.0 nmol
SOCS3mRNA

Messenger RNA ; Suppressor of cytokine signaling 3 		1.081 nmol
STAT2 LC 5

P52630 ; Translation ; P52630 		2520.0 nmol
Reactions
Reactions Rate Parameters
USP18 => compartment*k1*USP18 k1=0.6719
STAT2n => STAT2c compartment*k1*STAT2n k1=1.81
=> SOCS1mRNA compartment*v v=1.301
STAT1_LC_1 => STAT1_LC_2 compartment*k1*STAT1_LC_1 k1=0.5275
STAT1_LC_2 => STAT1_LC_3 compartment*k1*STAT1_LC_2 k1=0.5275
STAT2_LC_2 => STAT2_LC_3 compartment*k1*STAT2_LC_2 k1=1.77
=> USP18_LC_1; USP18mRNA compartment*synthUSP18*USP18mRNA synthUSP18=1658.0
=> SOCS3mRNA; OccGASbs compartment*synthSOCS3mRNA*OccGASbs synthSOCS3mRNA=0.01205
STAT2_LC_5 => STAT2c compartment*k1*STAT2_LC_5 k1=1.77
Curator's comment:
(added: 17 Aug 2020, 19:03:35, updated: 17 Aug 2020, 19:03:35)
Model simulated using copasi 4.29(build288) and results plotted using microsoft excel. Model reproduced figure 3A and 3b all simulation results. For IFNa stimulation of 0, 2.8, 28 and 1400 pM , extrapolated IFNa values taken were 100, 1000, 50000 respectively.