Helicobacter pylori (H. pylori), a gram-negative bacterium, infects the stomach of approximately 50% of the world population. H. pylori infection is a risk factor for developing chronic gastric ulcers and gastric cancer. The bacteria produce two main cytotoxic proteins: Vacuolating cytotoxin A (VacA) and Cytotoxin-Associated gene A (CagA). When these proteins enter the host cell they interfere with the host MAP Kinase and Apoptosis signaling pathways leading to aberrant cell growth and premature apoptosis. The present study expanded existing quantitative models of the MAP Kinase and Apoptosis signaling pathways to take into account the protein interactions across species using the CellDesigner tool. The resulting network contained hundreds of differential equations in which the coefficients for the biochemical rate constants were estimated from previously published studies. The effect of VacA and CagA on the function of this network were simulated by increasing levels of bacterial load. Simulations showed that increasing bacterial load affected the MAP Kinase signaling in a dose dependant manner. The introduction of CagA decreased the activation time of mapK signaling and extended activation indefinitely despite normal cellular activity to deactivate the protein. Introduction of VacA produced a similar response in the apoptosis pathway. Bacterial load activated both pathways even in the absence of external stimulation. Time course of emergence of transcription factors associated with cell division and cell death predicted by our simulation showed close agreement with that determined from a publicly accessible microarray data set of H. pylori infected stomach epithelium. The quantitative model presented in this study lays the foundation for investigating the affects of single nucleotide polymorphisms (SNPs) on the efficiency of drug treatment. © 2007 Elsevier Ltd. All rights reserved.
Dampier, W., & Tozeren, A. (2007). Signaling perturbations induced by invading H. pylori proteins in the host epithelial cells: A mathematical modeling approach. Journal of Theoretical Biology, 248(1), 130–144. https://doi.org/10.1016/j.jtbi.2007.03.014