Leber2016 - Expanded model of Tfh-Tfr differentiation - Helicobacter pylori infection

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Short description
Leber2016 - Expanded model of Tfh-Tfr differentiation - Helicobacter pylori infection

The parameters used in the model were obtained from experiments conducted by the authors, previous publications [ 1, 2, 3] and parameter optimisation carried out in the paper using particle swarm and genetic algorithms. 

This model is described in the article:

Leber A, Abedi V, Hontecillas R, Viladomiu M, Hoops S, Ciupe S, Caughman J, Andrew T, Bassaganya-Riera J.
J. Theor. Biol. 2016 Jun; 398: 74-84

Abstract:

T follicular helper (Tfh) cells are a highly plastic subset of CD4+ T cells specialized in providing B cell help and promoting inflammatory and effector responses during infectious and immune-mediate diseases. Helicobacter pylori is the dominant member of the gastric microbiota and exerts both beneficial and harmful effects on the host. Chronic inflammation in the context of H. pylori has been linked to an upregulation in T helper (Th)1 and Th17 CD4+ T cell phenotypes, controlled in part by the cytokine, interleukin-21. This study investigates the differentiation and regulation of Tfh cells, major producers of IL-21, in the immune response to H. pylori challenge. To better understand the conditions influencing the promotion and inhibition of a chronically elevated Tfh population, we used top-down and bottom-up approaches to develop computational models of Tfh and T follicular regulatory (Tfr) cell differentiation. Stability analysis was used to characterize the presence of two bi-stable steady states in the calibrated Tfh/Tfr models. Stochastic simulation was used to illustrate the ability of the parameter set to dictate two distinct behavioral patterns. Furthermore, sensitivity analysis helped identify the importance of various parameters on the establishment of Tfh and Tfr cell populations. The core network model was expanded into a more comprehensive and predictive model by including cytokine production and signaling pathways. From the expanded network, the interaction between TGFB-Induced Factor Homeobox 1 (Tgif1) and the retinoid X receptor (RXR) was displayed to exert control over the determination of the Tfh response. Model simulations predict that Tgif1 and RXR respectively induce and curtail Tfh responses. This computational hypothesis was validated experimentally by assaying Tgif1, RXR and Tfh in stomachs of mice infected with H. pylori.

The impulse of RXR as shown in the paper (figure 7C) can be implemented by creating an event in the curated SBML file.

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
  • Bistability analyses of CD4+ T follicular helper and regulatory cells during Helicobacter pylori infection.
  • Leber A, Abedi V, Hontecillas R, Viladomiu M, Hoops S, Ciupe S, Caughman J, Andrew T, Bassaganya-Riera J
  • Journal of theoretical biology , 6/ 2016 , Volume 398 , pages: 74-84
  • Nutritional Immunology and Molecular Medicine Laboratory, Biocomplexity Institute of Virginia Tech, Blacksburg, VA, USA; Center for Modeling Immunity to Enteric Pathogens, Biocomplexity Institute of Virginia Tech, Blacksburg, VA, USA.
  • T follicular helper (Tfh) cells are a highly plastic subset of CD4+ T cells specialized in providing B cell help and promoting inflammatory and effector responses during infectious and immune-mediate diseases. Helicobacter pylori is the dominant member of the gastric microbiota and exerts both beneficial and harmful effects on the host. Chronic inflammation in the context of H. pylori has been linked to an upregulation in T helper (Th)1 and Th17 CD4+ T cell phenotypes, controlled in part by the cytokine, interleukin-21. This study investigates the differentiation and regulation of Tfh cells, major producers of IL-21, in the immune response to H. pylori challenge. To better understand the conditions influencing the promotion and inhibition of a chronically elevated Tfh population, we used top-down and bottom-up approaches to develop computational models of Tfh and T follicular regulatory (Tfr) cell differentiation. Stability analysis was used to characterize the presence of two bi-stable steady states in the calibrated Tfh/Tfr models. Stochastic simulation was used to illustrate the ability of the parameter set to dictate two distinct behavioral patterns. Furthermore, sensitivity analysis helped identify the importance of various parameters on the establishment of Tfh and Tfr cell populations. The core network model was expanded into a more comprehensive and predictive model by including cytokine production and signaling pathways. From the expanded network, the interaction between TGFB-Induced Factor Homeobox 1 (Tgif1) and the retinoid X receptor (RXR) was displayed to exert control over the determination of the Tfh response. Model simulations predict that Tgif1 and RXR respectively induce and curtail Tfh responses. This computational hypothesis was validated experimentally by assaying Tgif1, RXR and Tfh in stomachs of mice infected with H. pylori.
Contributors
Andrew Leber

Metadata information

is
BioModels Database MODEL1603010000
BioModels Database BIOMD0000000625
isDescribedBy
PubMed 26947272
hasTaxon
Taxonomy Mus musculus
Taxonomy Helicobacter pylori
isVersionOf
hasProperty
Mathematical Modelling Ontology Ordinary differential equation model
Human Disease Ontology duodenal ulcer
Human Disease Ontology peptic ulcer disease
occursIn
Brenda Tissue Ontology gastrointestinal mucosa
Curation status
Curated
Original model(s)
Leber2016_TfhTfrExpanded
Name Description Size Actions

Model files

BIOMD0000000625_url.xml SBML L2V4 representation of Leber2016 - Expanded model of Tfh-Tfr differentiation - Helicobacter pylori infection 155.24 KB Preview | Download

Additional files

BIOMD0000000625.pdf Auto-generated PDF file 312.74 KB Preview | Download
BIOMD0000000625.png Auto-generated Reaction graph (PNG) 194.08 KB Preview | Download
BIOMD0000000625.m Auto-generated Octave file 16.79 KB Preview | Download
BIOMD0000000625_urn.xml Auto-generated SBML file with URNs 153.80 KB Preview | Download
BIOMD0000000625.sci Auto-generated Scilab file 154.00 bytes Preview | Download
BIOMD0000000625-biopax3.owl Auto-generated BioPAX (Level 3) 58.67 KB Preview | Download
BIOMD0000000625.vcml Auto-generated VCML file 181.40 KB Preview | Download
BIOMD0000000625-biopax2.owl Auto-generated BioPAX (Level 2) 38.66 KB Preview | Download
BIOMD0000000625.xpp Auto-generated XPP file 12.34 KB Preview | Download
BIOMD0000000625.svg Auto-generated Reaction graph (SVG) 79.13 KB Preview | Download

  • Model originally submitted by : Andrew Leber
  • Submitted: Mar 1, 2016 4:21:29 PM
  • Last Modified: Jun 16, 2017 8:20:21 PM
Revisions
  • Version: 2 public model Download this version
    • Submitted on: Jun 16, 2017 8:20:21 PM
    • Submitted by: Andrew Leber
    • With comment: Current version of Leber2016 - Expanded model of Tfh-Tfr differentiation - Helicobacter pylori infection
  • Version: 1 public model Download this version
    • Submitted on: Mar 1, 2016 4:21:29 PM
    • Submitted by: Andrew Leber
    • With comment: Original import of Expanded model of Tfh-Tfr differentiation
Curator's comment:
(added: 27 Mar 2017, 11:40:00, updated: 27 Mar 2017, 11:40:00)
The model reproduces figure 7b in the paper qualitatively. In comparison to the figure in the paper, the time taken by the system to reach steady state is twice as long. The model was simulated on Cell Designer 4.4 and the plot was generated using Matlab.