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Distinguishing multiple roles of T cell and macrophage involvement in determining lymph node fates during Mycobacterium tuberculosis infection 
Kathryn C. Krupinsky(1), Christian T. Michael(1), Pariksheet Nanda(1), Josh T. Mattila(2), Denise Kirschner(1) (1) - Department of Microbiology and Immunology, University of Michigan-Michigan Medicine, Ann Arbor, MI, United States (2) - Department of Infectious Disease and Microbiology, School of Public Health, University of Pittsburgh, Pittsburgh, PA, USA. ABSTRACT Tuberculosis (TB) is a disease of major public health concern with an estimated one-fourth of the world currently infected with M. tuberculosis (Mtb) bacilli. Mtb infection occurs after inhalation of Mtb, following which, highly structured immune structures called granulomas form within lungs to immunologically restrain and physically constrain spread of infection. Most lung granulomas are very successful at controlling or even eliminating their bacterial loads, but others fail to control infection and promote disease. Granulomas also form within lung-draining lymph nodes (LNs), variably affecting their function. Both lung and LN granulomas vary widely in ability to control2 infection, even within a single host, with outcomes ranging from bacterial clearance to uncontrolled bacterial growth. While lung granulomas are well-studied, data on LN TB is scarce; it is unknown what mechanisms drive LN Mtb infection progression and variability in severity. Recent data suggest that LN granulomas are niches for bacterial replication and can reduce control over lung infection. To identify mechanisms driving LN Mtb infection, we developed a mathematical model with multiple lung-draining LNs calibrated to data from a nonhuman primate TB model (one of the only models that parallels human TB infection). Our model predicts temporal trajectories for LN macrophage, T-cell, and Mtb populations during simulated Mtb infection. We also predict a clinically measurable feature from PET/CT imaging, FDG avidity. Using uncertainty and sensitivity analysis methods, we identify key mechanisms driving LN granuloma fate, T-cell efflux rates, and a role for LNs in pulmonary infection control.
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