(416e) Computational Modeling of Tuberculosis Granuloma Activation
AIChE Annual Meeting
Tuesday, October 31, 2017 - 4:31pm to 4:50pm
A previously developed mathematical model of the immune response to Mtb in the lungs  is used as the basis for this work. This previous model can track the levels of T cells, bacteria, cytokines and chemokines and can simulate the possible outcomes of the infection: clearance, latency, and reactivation. The infection outcome of interest in this work is latency. The previous model is a system of 16 ordinary differential equations (ODEs). To model the effect of MMP-1 dysregulation, 2 additional ODEs for the concentration of MMP-1 and collagen were developed, and a term was added to a preexisting ODE to represent the leakage of extracellular bacteria. The preexisting model and new ODEs were incorporated into a Python class, and an ode solver included in the Scipy package was used to solve the system of ODEs. A global sensitivity analysis using SALibâs implementation of Saltelli sampling and Sobol analysis was done on the model.
With the new equations to the model, a long term progression towards a leaking case is possible. Using a set of parameters that generates a latent case in the previous model, the new model at first starts to tend towards the latent case. After the bacterial population establishes itself, production of MMP-1 is increased. This drives the degradation of collagen, which allows bacteria to escape the granuloma. The case ultimately tends towards a steady state with a constant rate of bacterial leakage.
The model proposed here is intended to provide a possible mechanism for the link between MMP-1 dysregulation and TB activation. The new equations added into the model serve to add a leaking case that represents the formation of a necrotic cavity, which is characteristic of activation after a period of latency. Further work includes validating individual model parameters, sensitivity analysis, and model results under other conditions.
References:  Sud, Bigbee, Flynn & Kirschner. 2006. The Journal of Immunology, 176 (7), 4296â4314.
Acknowledgments: This work is supported in part by the Oklahoma Center for Respiratory Infectious Diseases, supported by the National Institute of General Medical Sciences of the National Institutes of Health under Award Number P20GM103648.