Exploring the direct effects of Mycobacterium tuberculosis on T cell responsiveness

The pathologic hallmark of infection with Mycobacterium tuberculosis (Mtb) are granulomas, collections of host immune cells (e.g. macrophages and T cells) that organize in an attempt to contain and eliminate the infection. Since granulomas are the sites of infection within lungs, we expect them to be enriched substantially in Mtb-responsive T cells (cells producing cytokines in response to Mtb). Surprisingly, a low frequency of Mtb-responsive T cells (~ 8%) in granulomas have been observed. As an increase in Mtb specific T cells early post-infection is thought to lead to quicker clearance of the pathogen, it is important to determine why the frequency of functional T cells in granulomas is so low. One hypothesis is that T cells are being down-regulated directly by Mtb. To study this dynamic, we use a multi-scale modeling approach. Our lab has previously created an agent based model (ABM), known as GranSim, that tracks bacteria as individual immune cells as agents. This allows us to capture Mtb heterogeneity in terms of growth and division by tracking its environment to predict the impact of bacterial factors on T cell behavior. To allow fine tuning at the molecular level of macrophage-T-cell interaction, we will integrate a system of ODEs that captures Mtb-mediated down-regulation of MHC II presentation of peptides in macrophages that we have previously published directly into cells within GranSim, creating a MSM that spans intracellular to tissue scales. This work can provide insights into mechanisms that could be either enhanced or inhibited to therapeutically increase frequencies of Mtb-responsive T cells and at the same time help to understand what mechanisms may be contributing to the extremely low levels of responsiveness