Miao2010 - Innate and adaptive immune responses to primary Influenza A Virus infection

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Model Identifier
BIOMD0000000546
Short description
Miao2010 - Innate and adaptive immune responses to primary Influenza A Virus infection

This model is described in the article:

Miao H, Hollenbaugh JA, Zand MS, Holden-Wiltse J, Mosmann TR, Perelson AS, Wu H, Topham DJ.
J. Virol. 2010 Jul; 84(13): 6687-6698

Abstract:

Seasonal and pandemic influenza A virus (IAV) continues to be a public health threat. However, we lack a detailed and quantitative understanding of the immune response kinetics to IAV infection and which biological parameters most strongly influence infection outcomes. To address these issues, we use modeling approaches combined with experimental data to quantitatively investigate the innate and adaptive immune responses to primary IAV infection. Mathematical models were developed to describe the dynamic interactions between target (epithelial) cells, influenza virus, cytotoxic T lymphocytes (CTLs), and virus-specific IgG and IgM. IAV and immune kinetic parameters were estimated by fitting models to a large data set obtained from primary H3N2 IAV infection of 340 mice. Prior to a detectable virus-specific immune response (before day 5), the estimated half-life of infected epithelial cells is approximately 1.2 days, and the half-life of free infectious IAV is approximately 4 h. During the adaptive immune response (after day 5), the average half-life of infected epithelial cells is approximately 0.5 days, and the average half-life of free infectious virus is approximately 1.8 min. During the adaptive phase, model fitting confirms that CD8(+) CTLs are crucial for limiting infected cells, while virus-specific IgM regulates free IAV levels. This may imply that CD4 T cells and class-switched IgG antibodies are more relevant for generating IAV-specific memory and preventing future infection via a more rapid secondary immune response. Also, simulation studies were performed to understand the relative contributions of biological parameters to IAV clearance. This study provides a basis to better understand and predict influenza virus immunity.

To the extent possible under law, all copyright and related or neighbouring rights to this encoded model have been dedicated to the public domain worldwide. Please refer to CC0 Public Domain Dedication for more information.

Format
SBML (L2V4)
Related Publication
  • Quantifying the early immune response and adaptive immune response kinetics in mice infected with influenza A virus.
  • Miao H, Hollenbaugh JA, Zand MS, Holden-Wiltse J, Mosmann TR, Perelson AS, Wu H, Topham DJ
  • Journal of virology , 7/ 2010 , Volume 84 , pages: 6687-6698 , PubMed ID: 20410284
  • Department of Biostatistics and Computational Biology, University of Rochester, Rochester, New York 146421, USA.
  • Seasonal and pandemic influenza A virus (IAV) continues to be a public health threat. However, we lack a detailed and quantitative understanding of the immune response kinetics to IAV infection and which biological parameters most strongly influence infection outcomes. To address these issues, we use modeling approaches combined with experimental data to quantitatively investigate the innate and adaptive immune responses to primary IAV infection. Mathematical models were developed to describe the dynamic interactions between target (epithelial) cells, influenza virus, cytotoxic T lymphocytes (CTLs), and virus-specific IgG and IgM. IAV and immune kinetic parameters were estimated by fitting models to a large data set obtained from primary H3N2 IAV infection of 340 mice. Prior to a detectable virus-specific immune response (before day 5), the estimated half-life of infected epithelial cells is approximately 1.2 days, and the half-life of free infectious IAV is approximately 4 h. During the adaptive immune response (after day 5), the average half-life of infected epithelial cells is approximately 0.5 days, and the average half-life of free infectious virus is approximately 1.8 min. During the adaptive phase, model fitting confirms that CD8(+) CTLs are crucial for limiting infected cells, while virus-specific IgM regulates free IAV levels. This may imply that CD4 T cells and class-switched IgG antibodies are more relevant for generating IAV-specific memory and preventing future infection via a more rapid secondary immune response. Also, simulation studies were performed to understand the relative contributions of biological parameters to IAV clearance. This study provides a basis to better understand and predict influenza virus immunity.
Contributors
Alain Leblanc, Rahuman Sheriff

Metadata information

is
BioModels Database MODEL1405150000
BioModels Database BIOMD0000000546
isDerivedFrom
BioModels Database MODEL1406230000
isDescribedBy
PubMed 20410284
hasTaxon
isVersionOf
Gene Ontology innate immune response
Gene Ontology adaptive immune response
hasVersion
Human Disease Ontology influenza

Curation status
Curated


Original model(s)
Miao2010_FluImmuneResponse_Early

Tags
Name Description Size Actions

Model files

BIOMD0000000546_url.xml SBML L2V4 representation of Miao2010 - Innate and adaptive immune responses to primary Influenza A Virus infection 33.27 KB Preview | Download

Additional files

BIOMD0000000546.sci Auto-generated Scilab file 154.00 bytes Preview | Download
BIOMD0000000546.xpp Auto-generated XPP file 1.97 KB Preview | Download
BIOMD0000000546_urn.xml Auto-generated SBML file with URNs 33.08 KB Preview | Download
BIOMD0000000546-biopax2.owl Auto-generated BioPAX (Level 2) 10.86 KB Preview | Download

  • Model originally submitted by : Alain Leblanc
  • Submitted: May 15, 2014 7:46:39 PM
  • Last Modified: Oct 10, 2014 12:00:17 PM
Revisions
  • Version: 2 public model Download this version
    • Submitted on: Oct 10, 2014 12:00:17 PM
    • Submitted by: Alain Leblanc
    • With comment: Current version of Miao2010 - Innate and adaptive immune responses to primary Influenza A Virus infection
  • Version: 1 public model Download this version
    • Submitted on: May 15, 2014 7:46:39 PM
    • Submitted by: Alain Leblanc
    • With comment: Original import of BIOMD0000000546.xml.origin
Legends
: Variable used inside SBML models


Species
Species Initial Concentration/Amount
s1

Epithelial cell
580000.0 mol
s5 0.0 mol
s7 0.0 mol
s2

Epithelial cell
0.0 mol
s3

Influenza A virus (strain A/X-31 H3N2)
1473.0 mol
s4 0.0 mol
s6 0.0 mol
Reactions
Reactions Rate Parameters
rho_E*s1

rho_E*s1
rho_E = 6.2E-8 substance
delta_Es*s2

delta_Es*s2
delta_Es = 0.6 substance
pi_a*s2

pi_a*s2
pi_a = 100.0 substance
beta_a*s1*s3

beta_a*s1*s3
beta_a = 2.4E-6 substance
c_V*s3

c_V*s3
c_V = 4.2 substance
Curator's comment:
(added: 04 Sep 2014, 13:48:48, updated: 04 Sep 2014, 13:48:48)
Parameter scan was done with varying values (1e-06 to 1)of beta_a. The green plot in figure 6A for Ep and Ep* (Eps in the model) that correspond to beta_a=1e-06 has been reproduced here. The simulation was done using Copasi v4.12 (Build 81). The plots were generated using Gnuplot.