Predictive Computational Modeling of the Mucosal Immune Responses during Helicobacter pylori Infection

dc.contributorVirginia Techen
dc.contributor.authorCarbo, Adriaen
dc.contributor.authorBassaganya-Riera, Josepen
dc.contributor.authorPedragosa, Mireiaen
dc.contributor.authorViladomiu, Monicaen
dc.contributor.authorMarathe, Madhaven
dc.contributor.authorEubank, Stephenen
dc.contributor.authorWendesdorf, Katherineen
dc.contributor.authorBisset, Keith R.en
dc.contributor.authorHoops, Stefanen
dc.contributor.authorDeng, Xinweien
dc.contributor.authorAlam, Maksudulen
dc.contributor.authorKronsteiner, Barbaraen
dc.contributor.authorMei, Yongguoen
dc.contributor.authorHontecillas, Raquelen
dc.description.abstractT 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 levelys 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.en
dc.description.sponsorshipThis work was supported in part by a grant from the National Institutes of Health (5R01AT004308) to JBR, NIAID Conact No. HHSN272201000056C to JBR, and funds from the Nutritional Immunology and Molecular Medicine Laboratory (URL: The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.en
dc.identifier.citationCarbo A, Bassaganya-Riera J, Pedragosa M, Viladomiu M, Marathe M, et al. (2013) Predictive Computational Modeling of the Mucosal Immune Responses during Helicobacter pylori Infection. PLoS ONE 8(9): e73365. doi:10.1371/journal.pone.0073365en
dc.publisherPublic Library of Scienceen
dc.rightsIn Copyrighten
dc.subjectEpithelial cellsen
dc.subjectGastrointestinal infectionsen
dc.subjectHelicobacter pylorien
dc.subjectHelicobacter pylori infectionen
dc.subjectImmune responseen
dc.subjectRegulatory T cellsen
dc.subjectT cellsen
dc.titlePredictive Computational Modeling of the Mucosal Immune Responses during Helicobacter pylori Infectionen
dc.title.serialPLoS ONEen
dc.typeArticle - Refereeden


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