A Systems Biology Approach to Identify Immune Targets That Control Tuberculosis Granuloma Function

Tuberculosis (TB) is a common and deadly infectious disease caused by a highly successful bacterium, Mycobacterium tuberculosis (Mtb). Multiple host immune factors control the formation of a self-organizing aggregate of immune cells termed a granuloma, after inhalation of Mtb. One such factor, tumor necrosis factor-α (TNF), is a protein that regulates inflammatory immune responses. TNF (in conjunction with the cytokine IFN-γ) induces macrophage activation, enhances immune cell recruitment to the site of infection, and augments chemokine and cytokine expression by macrophages through activation of the NF-κB signaling pathway. However, there are differences among dynamics of each of these NF-κB-associated responses as a result of differences in molecular processes (e.g. RNA and protein degradation rates) acting downstream of TNF-induced NF-κB activation. The impact of these dynamical differences on formation and function of granulomas and thus the outcome of Mtb infection is not known.

We have developed a multi-scale computational model that describes the immune response to Mtb in lung over three biological length scales: tissue, cellular and molecular. Using this model, we predict the impact of NF-κB associated response dynamics on the outcome of infection at the level of a granuloma. Our model suggests that the timing of these responses, in addition to the extent of response, plays a critical role in control of infection and inflammation. Manipulations of the dynamics of these responses lead to different outcomes, including clearance of bacteria, containment of bacteria within a stable granuloma, uncontrolled growth of bacteria, or excessive inflammation. The intracellular NF-κB associated signaling molecules and processes involved in TB immunity that we identify as crucial may be new targets for therapy.