Crosstalks between Cytokines and Sonic Hedgehog in <i>Helicobacter pylori</i> Infection: A Mathematical Model

<div><p><i>Helicobacter pylori</i> infection of gastric tissue results in an immune response dominated by Th1 cytokines and has also been linked with dysregulation of Sonic Hedgehog (SHH) signaling pathway in gastric tissue. However, since interactions between the cytokines and SHH during <i>H. pylori</i> infection are not well understood, any mechanistic understanding achieved through interpretation of the statistical analysis of experimental results in the context of currently known circuit must be carefully scrutinized. Here, we use mathematical modeling aided by restraints of experimental data to evaluate the consistency between experimental results and temporal behavior of <i>H. pylori</i> activated cytokine circuit model. Statistical analysis of qPCR data from uninfected and <i>H. pylori</i> infected wild-type and parietal cell-specific SHH knockout (PC-SHH^KO) mice for day 7 and 180 indicate significant changes that suggest role of SHH in cytokine regulation. The experimentally observed changes are further investigated using a mathematical model that examines dynamic crosstalks among pro-inflammatory (IL1β, IL-12, IFNγ, MIP-2) cytokines, anti-inflammatory (IL-10) cytokines and SHH during <i>H. pylori</i> infection. Response analysis of the resulting model demonstrates that circuitry, as currently known, is inadequate for explaining of the experimental observations; suggesting the need for additional specific regulatory interactions. A key advantage of a computational model is the ability to propose putative circuit models for <i>in-silico</i> experimentation. We use this approach to propose a parsimonious model that incorporates crosstalks between NFĸB, SHH, IL-1β and IL-10, resulting in a feedback loop capable of exhibiting cyclic behavior. Separately, we show that analysis of an independent time-series GEO microarray data for IL-1β, IFNγ and IL-10 in mock and <i>H. pylori</i> infected mice further supports the proposed hypothesis that these cytokines may follow a cyclic trend. Predictions from the <i>in-silico</i> model provide useful insights for generating new hypothesis and design of subsequent experimental studies.</p></div

Trajectories of cytokines in mock-infected and <i>H. pylori</i> infected mice from GEO microarray dataset.

<p>(A) IL-1β, (B) IL-10 and (C) IFNγ for day 2, 7, 14 and 28 from chief cell of mock-infected and <i>H. pylori</i> infected mice. The temporal profiles indicate that these cytokines potentially display a cyclic expression pattern in response to <i>H. pylori</i> infection.</p

In-silico SHH KO results show a decrease in cytokines as comared to WT.

<p>SHH KO condition was simulated by setting SHHi to zero. Graph A–F shows profiles of (A) SHH (B) IL-1β (C) IL12 (D) IFNγ (E) MIP2 (F) IL10. Wild type condition (SHHi  = 1) is shown in green and <i>in-silico</i> SHH KO condition (SHHi  = 0) is represented in red.</p

Diagram of mathematical model of cytokine-SHH network during <i>H. pylori</i> infection.

<p>This reduced network derived from interaction map, represents the key cytokines activated as host's immune response to <i>H. pylori</i>. Blue arrows represent activation whereas while red arrows depict inhibition. Model species with suffix “i” represent the inactive form. The link between SHH and cytokines, as predicted by our experimental data is modelled through unknown model species “X” (grey colored). Detailed interaction network of host immune response to <i>H. pylori</i> is available in MethodsS1.</p

Temporal profiles of model species in uninfected and infected conditions.

<p>Simulation results comparing temporal profiles of model species in (A) absence and (B) presence of <i>H. pylori</i>. Graph C–F show temporal profiles of (C) SHH (D) MIP-2 (E) IL-1β and (F) IL-10 in absence and presence of <i>H. pylori</i>.</p

Effect of <i>H. pylori</i> on SHH and cytokines' expression in WT and PC-SHH^KO mouse stomachs, day 7 and day 180 post-inoculation.

<p>RNA was extracted from stomachs of uninfected and <i>H. pylori</i>-infected wild type (WT) and parietal cell-specific SHH knock out (PC-SHH-KO) mice 7 and 180 days post-inoculation. Expression of genes was measured by qPCR and two-way ANOVA test was performed, followed by Bonferroni test to compare uninfected (-HP) with <i>H. pylori</i> infected group (+HP) in each genotype. The graphs show average fold change in expression of IL-1β (A, B), IL-12 (C, D), MIP-2 (E, F), IL-10 (G, H) and SHH (I, J) upon <i>H. pylori</i> infection relative to uninfected condition. Bars represent the mean ± SEM, n = 3-4 per group.</p

Interaction between infection status and genotype.

<p>RNA was extracted from stomachs of uninfected (-HP) and <i>H. pylori</i>-infected (+HP) wild type (WT) and parietal cell specific SHH knock out (PC-SHH-KO) mice 7 and 180 days post-inoculation. Expression of genes was measured by qPCR and interaction test was performed. Parallel lines imply that <i>H. pylori</i> has same effect on gene's expression in WT and PC-SHH^KO mice whereas intersecting or non-parallel lines indicate an interaction between genotype and infection. The graphs show interaction plot between infection status and genotype for (A) IL1β on day 7, (B) IL1β on day 180, (C) IL-12 on day 7, (D) IL-12 on day 180, (E) MIP-2 on day 7 (F) MIP-2 on day 180 (G) IL-10 on day 7 and (H) IL-10 on day 180. P-value for interaction between infection and genotype were calculated by two-way ANOVA test. Y-axis: mean of negative dCT value of cytokine, X-axis: infection status, trace-factor: genotype.</p