Tumor Necrosis Factor-Regulated Granuloma Formation in Tuberculosis: Multi-Scale Modeling and Experiments.

Abstract

Tuberculosis is a deadly infectious disease caused by Mycobacterium tuberculosis (Mtb). Multiple immune factors control host responses to Mtb infection, including the formation of granulomas in the lung, which are aggregates of bacteria, infected and uninfected immune cells whose function may reflect success or failure of the host to control infection. One such factor is tumor necrosis factor-α (TNF). TNF has been experimentally characterized to affect macrophage activation, apoptosis, chemokine and cytokine production during Mtb infection. Measurement of TNF concentrations and TNF activities within a granuloma to determine the relevant mechanisms for control of infection are difficult to assess in vivo. Further, processes that control TNF availability and activities within a granuloma remain unknown. We developed a multi-scale computational model that describes the immune response to Mtb in lung over three biological length scales: tissue, cellular and molecular. We used the results of sensitivity analysis as a tool to identify which experiments were needed to measure critical model parameters in an experimental system. This system is a model of a granuloma induced in the lungs of mice following injection of mycobacterial antigen-coated beads. Using these parameters in the model, we identified processes that regulate TNF availability and cellular behaviors and thus influence the outcome of infection within a granuloma. At the level of TNF/TNF receptor dynamics, TNF receptor internalization kinetics were shown to significantly influence TNF concentration dynamics, macrophage and T cell recruitment to site of infection, macrophage activation and apoptosis. These processes play a critical role in control of inflammation and bacterial levels within a granuloma. At the level of intracellular signaling, our analysis elucidated intracellular NF-κB associated signaling molecules and processes that may be new targets for control of infection and inflammation. We also used the model to explain what mechanisms lead to clinically observed differential effects of TNF-neutralizing drugs (generally used to treat inflammatory diseases) on reactivation of tuberculosis. Ultimately, these results can help to elaborate relevant features of the immune response to Mtb infection, identifying new strategies for therapy and prevention of tuberculosis as well as for development of safer anti-TNF drugs to treat inflammatory diseases.