Cargando…
Predictive Computational Modeling of the Mucosal Immune Responses during Helicobacter pylori Infection
T helper (Th) cells play a major role in the immune response and pathology at the gastric mucosa during Helicobacter pylori infection. There is a limited mechanistic understanding regarding the contributions of CD4+ T cell subsets to gastritis development during H. pylori colonization. We used two c...
Autores principales: | , , , , , , , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2013
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3764126/ https://www.ncbi.nlm.nih.gov/pubmed/24039925 http://dx.doi.org/10.1371/journal.pone.0073365 |
_version_ | 1782283099093073920 |
---|---|
author | Carbo, Adria Bassaganya-Riera, Josep Pedragosa, Mireia Viladomiu, Monica Marathe, Madhav Eubank, Stephen Wendelsdorf, Katherine Bisset, Keith Hoops, Stefan Deng, Xinwei Alam, Maksudul Kronsteiner, Barbara Mei, Yongguo Hontecillas, Raquel |
author_facet | Carbo, Adria Bassaganya-Riera, Josep Pedragosa, Mireia Viladomiu, Monica Marathe, Madhav Eubank, Stephen Wendelsdorf, Katherine Bisset, Keith Hoops, Stefan Deng, Xinwei Alam, Maksudul Kronsteiner, Barbara Mei, Yongguo Hontecillas, Raquel |
author_sort | Carbo, Adria |
collection | PubMed |
description | T helper (Th) cells play a major role in the immune response and pathology at the gastric mucosa during Helicobacter pylori infection. There is a limited mechanistic understanding regarding the contributions of CD4+ T cell subsets to gastritis development during H. pylori colonization. We used two computational approaches: ordinary differential equation (ODE)-based and agent-based modeling (ABM) to study the mechanisms underlying cellular immune responses to H. pylori and how CD4+ T cell subsets influenced initiation, progression and outcome of disease. To calibrate the model, in vivo experimentation was performed by infecting C57BL/6 mice intragastrically with H. pylori and assaying immune cell subsets in the stomach and gastric lymph nodes (GLN) on days 0, 7, 14, 30 and 60 post-infection. Our computational model reproduced the dynamics of effector and regulatory pathways in the gastric lamina propria (LP) in silico. Simulation results show the induction of a Th17 response and a dominant Th1 response, together with a regulatory response characterized by high levels of mucosal Treg) cells. We also investigated the potential role of peroxisome proliferator-activated receptor γ (PPARγ) activation on the modulation of host responses to H. pylori by using loss-of-function approaches. Specifically, in silico results showed a predominance of Th1 and Th17 cells in the stomach of the cell-specific PPARγ knockout system when compared to the wild-type simulation. Spatio-temporal, object-oriented ABM approaches suggested similar dynamics in induction of host responses showing analogous T cell distributions to ODE modeling and facilitated tracking lesion formation. In addition, sensitivity analysis predicted a crucial contribution of Th1 and Th17 effector responses as mediators of histopathological changes in the gastric mucosa during chronic stages of infection, which were experimentally validated in mice. These integrated immunoinformatics approaches characterized the induction of mucosal effector and regulatory pathways controlled by PPARγ during H. pylori infection affecting disease outcomes. |
format | Online Article Text |
id | pubmed-3764126 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2013 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-37641262013-09-13 Predictive Computational Modeling of the Mucosal Immune Responses during Helicobacter pylori Infection Carbo, Adria Bassaganya-Riera, Josep Pedragosa, Mireia Viladomiu, Monica Marathe, Madhav Eubank, Stephen Wendelsdorf, Katherine Bisset, Keith Hoops, Stefan Deng, Xinwei Alam, Maksudul Kronsteiner, Barbara Mei, Yongguo Hontecillas, Raquel PLoS One Research Article T helper (Th) cells play a major role in the immune response and pathology at the gastric mucosa during Helicobacter pylori infection. There is a limited mechanistic understanding regarding the contributions of CD4+ T cell subsets to gastritis development during H. pylori colonization. We used two computational approaches: ordinary differential equation (ODE)-based and agent-based modeling (ABM) to study the mechanisms underlying cellular immune responses to H. pylori and how CD4+ T cell subsets influenced initiation, progression and outcome of disease. To calibrate the model, in vivo experimentation was performed by infecting C57BL/6 mice intragastrically with H. pylori and assaying immune cell subsets in the stomach and gastric lymph nodes (GLN) on days 0, 7, 14, 30 and 60 post-infection. Our computational model reproduced the dynamics of effector and regulatory pathways in the gastric lamina propria (LP) in silico. Simulation results show the induction of a Th17 response and a dominant Th1 response, together with a regulatory response characterized by high levels of mucosal Treg) cells. We also investigated the potential role of peroxisome proliferator-activated receptor γ (PPARγ) activation on the modulation of host responses to H. pylori by using loss-of-function approaches. Specifically, in silico results showed a predominance of Th1 and Th17 cells in the stomach of the cell-specific PPARγ knockout system when compared to the wild-type simulation. Spatio-temporal, object-oriented ABM approaches suggested similar dynamics in induction of host responses showing analogous T cell distributions to ODE modeling and facilitated tracking lesion formation. In addition, sensitivity analysis predicted a crucial contribution of Th1 and Th17 effector responses as mediators of histopathological changes in the gastric mucosa during chronic stages of infection, which were experimentally validated in mice. These integrated immunoinformatics approaches characterized the induction of mucosal effector and regulatory pathways controlled by PPARγ during H. pylori infection affecting disease outcomes. Public Library of Science 2013-09-05 /pmc/articles/PMC3764126/ /pubmed/24039925 http://dx.doi.org/10.1371/journal.pone.0073365 Text en © 2013 Carbo et al http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited. |
spellingShingle | Research Article Carbo, Adria Bassaganya-Riera, Josep Pedragosa, Mireia Viladomiu, Monica Marathe, Madhav Eubank, Stephen Wendelsdorf, Katherine Bisset, Keith Hoops, Stefan Deng, Xinwei Alam, Maksudul Kronsteiner, Barbara Mei, Yongguo Hontecillas, Raquel Predictive Computational Modeling of the Mucosal Immune Responses during Helicobacter pylori Infection |
title | Predictive Computational Modeling of the Mucosal Immune Responses during Helicobacter pylori Infection |
title_full | Predictive Computational Modeling of the Mucosal Immune Responses during Helicobacter pylori Infection |
title_fullStr | Predictive Computational Modeling of the Mucosal Immune Responses during Helicobacter pylori Infection |
title_full_unstemmed | Predictive Computational Modeling of the Mucosal Immune Responses during Helicobacter pylori Infection |
title_short | Predictive Computational Modeling of the Mucosal Immune Responses during Helicobacter pylori Infection |
title_sort | predictive computational modeling of the mucosal immune responses during helicobacter pylori infection |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3764126/ https://www.ncbi.nlm.nih.gov/pubmed/24039925 http://dx.doi.org/10.1371/journal.pone.0073365 |
work_keys_str_mv | AT carboadria predictivecomputationalmodelingofthemucosalimmuneresponsesduringhelicobacterpyloriinfection AT bassaganyarierajosep predictivecomputationalmodelingofthemucosalimmuneresponsesduringhelicobacterpyloriinfection AT pedragosamireia predictivecomputationalmodelingofthemucosalimmuneresponsesduringhelicobacterpyloriinfection AT viladomiumonica predictivecomputationalmodelingofthemucosalimmuneresponsesduringhelicobacterpyloriinfection AT marathemadhav predictivecomputationalmodelingofthemucosalimmuneresponsesduringhelicobacterpyloriinfection AT eubankstephen predictivecomputationalmodelingofthemucosalimmuneresponsesduringhelicobacterpyloriinfection AT wendelsdorfkatherine predictivecomputationalmodelingofthemucosalimmuneresponsesduringhelicobacterpyloriinfection AT bissetkeith predictivecomputationalmodelingofthemucosalimmuneresponsesduringhelicobacterpyloriinfection AT hoopsstefan predictivecomputationalmodelingofthemucosalimmuneresponsesduringhelicobacterpyloriinfection AT dengxinwei predictivecomputationalmodelingofthemucosalimmuneresponsesduringhelicobacterpyloriinfection AT alammaksudul predictivecomputationalmodelingofthemucosalimmuneresponsesduringhelicobacterpyloriinfection AT kronsteinerbarbara predictivecomputationalmodelingofthemucosalimmuneresponsesduringhelicobacterpyloriinfection AT meiyongguo predictivecomputationalmodelingofthemucosalimmuneresponsesduringhelicobacterpyloriinfection AT hontecillasraquel predictivecomputationalmodelingofthemucosalimmuneresponsesduringhelicobacterpyloriinfection |