Using Multi-Scale Modeling to explore the effects of Mycobacterium tuberculosis on T cell responsiveness in granulomas
posterposted on 24.04.2019, 18:25 by Jess Millar, JoAnne Flynn, Jennifer Linderman, Denise Kirschner
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 (producing cytokines in response to Mtb). Surprisingly, a low frequency of Mtb-responsive T cells (~ 10%) in granulomas have been observed. As Mtb-specific T cells are key to 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 (MSM) approach. Our lab has previously created an agent-based model (ABM), known as GranSim, that tracks bacteria as individual immune cells as agents. In addition, we have an existing system of ODEs that captures Mtb-mediated down-regulation of MHCII presentation of peptides in macrophages that we have previously published. We create a novel hybrid, multi-scale computational model by linking these two models putting these equations directly into antigen presenting cells within GranSim resulting in a MSM that spans scales from intracellular to tissue. We performed a sensitivity and uncertainty analysis, and preliminary results suggest critical input parameters relating to MHC II transcription and translation are most influential during the first 50 days of infection, while input parameters relating to Mtb antigen uptake and processing are most influential during the first 100 days or more. This work provides insights into mechanisms that could be either enhanced or inhibited to therapeutically increase frequencies of Mtb-responsive T cells and at the same to helping to understand what mechanisms may be contributing to the low levels of responsiveness.
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