Manchanda2014 - Effect on Immune System by 4 different Influenza A virus strains

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Model Identifier
BIOMD0000000712
Short description
Format
SBML (L2V4)
Related Publication
  • Within-host influenza dynamics: a small-scale mathematical modeling approach.
  • Manchanda H, Seidel N, Krumbholz A, Sauerbrei A, Schmidtke M, Guthke R
  • Bio Systems , 4/ 2014 , Volume 118 , pages: 51-59 , PubMed ID: 24614233
  • Leibniz Institute for Natural Product Research and Infection Biology - Hans Knöll Institute, Jena, Germany; Jena University Hospital, Department of Virology and Antiviral Therapy, Jena, Germany.
  • The emergence of new influenza viruses like the pandemic H1N1 influenza A virus in 2009 (A(H1N1)pdm09) with unpredictable difficulties in vaccine coverage and established antiviral treatment protocols emphasizes the need of new murine models to prove the activity of novel antiviral compounds in vivo. The aim of the present study was to develop a small-scale mathematical model based on easily attainable experimental data to explain differences in influenza kinetics induced by different virus strains in mice. To develop a three-dimensional ordinary differential equation model of influenza dynamics, the following variables were included: (i) viral pathogenicity (P), (ii) antiviral immune defense (D), and (iii) inflammation due to pro-inflammatory response (I). Influenza virus-induced symptoms (clinical score S) in mice provided the basis for calculations of P and I. Both, mono- and biphasic course of mild to severe influenza induced by three clinical A(H1N1)pdm09 strains and one European swine H1N2 virus were comparatively and quantitatively studied by fitting the mathematical model to the experimental data. The model hypothesizes reasons for mild and severe influenza with mono- as well as biphasic course of disease. According to modeling results, the second peak of the biphasic course of infection is caused by inflammation. The parameters (i) maximum primary pathogenicity, (ii) viral infection rate, and (iii) rate of activation of the immune system represent most important parameters that quantitatively characterize the different pattern of virus-specific influenza kinetics.
Contributors
Submitter of the first revision: Sarubini Kananathan
Submitter of this revision: Sarubini Kananathan
Modellers: Sarubini Kananathan

Metadata information

is (3 statements)
BioModels Database MODEL1808280001
BioModels Database BIOMD0000000712
BioModels Database MODEL1808280001

isDescribedBy (1 statement)
PubMed 24614233

hasTaxon (2 statements)
hasProperty (3 statements)
Mathematical Modelling Ontology Ordinary differential equation model
Experimental Factor Ontology influenza infection
NCIt Immune Response Process

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

Connected external resources

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Name Description Size Actions

Model files
Jena5258.xml SBML L2V4 representation of Manchanda2014 - Effect on Immune System by 4 different Influenza A virus strains 29.27 KB Preview | Download

Additional files
Bakum1832.cps Copasi file for strain Bakum1832 55.34 KB Preview | Download
Jena2688.cps Copasi file for strain Jena2688 55.34 KB Preview | Download
Jena5258.cps Copasi file for strain Jena5258 55.40 KB Preview | Download
Jena5555.cps Copasi file for strain Jena5555 55.38 KB Preview | Download

  • Model originally submitted by : Sarubini Kananathan
  • Submitted: Aug 28, 2018 9:25:09 AM
  • Last Modified: Oct 16, 2018 2:31:56 PM
Revisions
  • Version: 7 public model Download this version
    • Submitted on: Oct 16, 2018 2:31:56 PM
    • Submitted by: Sarubini Kananathan
    • With comment: Automatically added model identifier BIOMD0000000712
  • Version: 4 public model Download this version
    • Submitted on: Aug 28, 2018 9:25:09 AM
    • Submitted by: Sarubini Kananathan
    • With comment: Edited model metadata online.

(*) 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
D

Antiviral Response 		0.0 mmol
I

Inflammation 		0.0 mmol
P

pathogenicity design 		0.01 mmol
S

Clinical Classification 		0.01 mmol
Reactions
Reactions Rate Parameters
=> D; P compartment*gamma*P gamma = 0.51
I => compartment*rho*I rho = 1.82
=> P compartment*alpha*P*(1-P/k_p) k_p = 3.23; alpha = 3.63
=> I compartment*epsilon*f_D epsilon = 6.81; f_D = 0.0
S = P+I [] []
D => compartment*theta*D theta = 0.01
P => ; D compartment*beta*D*P/(P+0.01) beta = 1.0
Curator's comment:
(added: 16 Oct 2018, 14:29:24, updated: 16 Oct 2018, 14:29:24)
Figure 2 of the reference publication has been reproduced. Model shows the effect on the immune system with 4 different influenza a virus strains. The model file attached is for strain Jena/5258(H1N1). Initial conditions were taken from the publication. The model was simulated using Copasi 4.22 and the figure was generated using Python 2.7.