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

Abstract

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.

Preclinical Studies of Amixicile, a Systemic Therapeutic Developed for Treatment of Clostridium difficile Infections That Also Shows Efficacy against Helicobacter pylori

“…C57BL/6J mice were challenged with 3 doses of 5 ϫ 10 7 CFU of the H. pylori SS1 wild-type strain in brucella broth on days 1, 3, and 5 as previously described (25,26). At 2 weeks postinfection, groups of five mice each were treated by gavage with amixicile or MTZ at 20 mg/kg as previously described (15,27).…”

“…For amixicile-treated mice, a second group received two doses of 20 mg/kg each day. At 1 week posttreatment, mice were sacrificed, their stomachs were removed and homogenized, and CFU counts were determined by plate counting (25). Briefly, weighted gastric specimens were homogenized in PBS and plated in triplicate onto Columbia agar plates with the selective antibiotics vancomycin (10 g/ml), trimethoprim (1 g/ml), amphotericin B (5 g/ml), and polymyxin B (5 g/ml).…”

“…Briefly, weighted gastric specimens were homogenized in PBS and plated in triplicate onto Columbia agar plates with the selective antibiotics vancomycin (10 g/ml), trimethoprim (1 g/ml), amphotericin B (5 g/ml), and polymyxin B (5 g/ml). Plates were incubated for 4 days at 37°C under microaerobic conditions (25,27). Bacterial numbers are reported as the mean and SD of the number of CFU/g of stomach tissue.…”

Helicobacter pylori Infection in a Pig Model Is Dominated by Th1 and Cytotoxic CD8+T Cell Responses

“…As a control, the noninfected group received sterile brucella broth without any bacteria. Due to constraints associated with the use of a large-animal model, the infection dose was optimized by conducting a series of dose-response experiments in mice as previously described (32). We chose doses that provided detectable host responses and long-term colonization, which were then adapted to the pig model.…”

Agent-based model of fecal microbial transplant effect on bile acid metabolism on suppressing Clostridium difficile infection: an example of agent-based modeling of intestinal bacterial infection

“…Gastrointestinal infections can be modeled as either the introduction of a new agent class representing an invasive pathogen, or by the conversion of a previously commensal microbe into a virulent pathogenic form in response to alterations of the gut environment such as stress, nutrient depletion or the administration of antibiotics. Agent-based modeling has previously been used to examine intestinal-bacterial interactions/infections ranging from upper GI tract Helicobacter pylori infection [36], to investigating the contribution of bacteria to necrotizing enterocolitis [37] to colonic interactions involving the pathogenesis of gut derived sepsis [38] and salmonella infection [39]. The first of these studies involved the use of an agent-based modeling platform specifically developed at the Virginia Bioinformatics Institute to study intestinal immunity [40], while the second two studies were developed using the general purpose agent-based modeling toolkit NetLogo [41].…”