Modeling host-pathogen interactions: H. sapiens as a host and C. difficile as a pathogen

Many complex mechanisms in immunological studies cannot be measured by experiments, but can be analyzed by mathematical simulations. Using theoretical modeling techniques, general principles of host-pathogen system interactions can be explored and clinical treatment schedules can be optimized to lower the microbial toxin burden and side effects in the host system. In this study, we use a computational modeling technique that aims to explain the host-pathogen interactions and suggests how the host system tries to survive from the pathogen attack. The method generates data on reaction fluxes in a pathway at steady state. A set of constraints is incorporated and an objective function for the minimization of toxin expression, with respect to some parameters such as concentration of signaling molecules, is formulated. We have integrated the toxin expression regulatory pathway in Clostridium difficile, apoptosis and mitogen-activated protein kinase pathways in an infected host (Homo sapiens). We have found that due to the minimization of the toxin expression, the signal flow values for most of the survival genes are at the higher side, whereas it is the reverse for most of the proapoptotic genes. We have observed increased signal flow values of the molecules for extracellular regulated kinase as compared with the molecules present in c-Jun NH2-terminal kinase/p38 pathways. In light of these observations, we can hypothesize that lower toxin level in a pathogen implies higher chance of host survival.