New Computational model of host responses to Clostridium difficile infection
The MIEP team has published a computational model of interactions between C. difficile, the microbiome and the host. The article, entitled “Systems Modeling of Interactions between Mucosal Immunity and the Gut Microbiome during Clostridium difficile Infection”, was published in PLOS One on July 31.
The model follows the time course of infection moving from initiation to resolution based on immunological data acquired from a mouse model of C. difficile infection. Computational simulations illustrated the effect of antimicrobial peptides generated from epithelial cells and neutrophils on the clearance of C. difficile and also the regrowth of beneficial commensal bacteria following antibiotic reduction. The impaired regrowth of the colonic host microbiome by these antimicrobial peptides may help explain why high rates of recurrence occur after initial infections with C. difficile.
Additional analysis of the model demonstrated a crucial role for the balance between CD4+ T helper cell subsets, Th17 and iTreg, and neutrophilic influx on the development of damage to the epithelium, a key pathological outcome of disease. The innovative computational immunology approaches used to simulate the effects of the host microbiome may be used to explore similar mechanisms to other gastroenteric pathogens such as H. pylori and immune-mediated diseases such as Crohn’s disease or Ulcerative colitis. The computational model used in this study is available for download at Biomodels.net (MODEL1507200000).
The NIMML tackles unsolved fundamental challenges in complex human diseases with unmet clinical needs. The NIMML combines advanced computational technologies such as computer modeling and artificial intelligence with pre-clinical and clinical experimentation to catalyze the translation of scientific discoveries into creative solutions to the most challenging problems in healthcare. NIMML is located in Blacksburg, VA.