A multi-scale and multi-system approach to understand granuloma formation in TB

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DESCRIPTION (provided by applicant): Tuberculosis is responsible for 2 million deaths per year. The interplay between host and bacterial factors leads to different disease outcomes (latency, primary tuberculosis, reactivation tuberculosis). A key outcome is the formation of a collection of immune cells termed the granuloma. This structure acts not only as an immune microenvironment and a barrier to dissemination but also as a niche for long-term bacterial survival. The long- term goal of this project is to identify factors that contribute to different outcomes of M. tuberculosis infection. We hypothesize that these different infection outcomes are reflected locally at the level of the granuloma and that granuloma structure is the result of the interplay of events at organ, tissue, cellular, and molecular scales over the time course of minutes to years. Several models of granuloma formation in tuberculosis will be integrated: pulmonary granulomas induced by M. tuberculosis antigen (PPD) coated beads in vivo, M. tuberculosis infection in mice and non-human primates, and multi-scale in silico models. Our studies will include multiple spatial and temporal scales to address the following aims. Aim 1: Determine how specific immune cells and effector molecules in the lung influence the formation of different granuloma structures. Aim 2: Determine the role of dendritic cell and T cell trafficking between lung granuloma and draining lymph nodes in influencing granuloma development. Aim 3: Identify the mechanisms that determine TNF availability for the purpose of understanding how granulomas form as well as how treatment with anti-TNF-therapies leads to TB reactivation. Our interdisciplinary team's approach for integrating data and in silico models over the relevant biological and temporal scales will allow us to predict and test hypotheses regarding key factors that influence granuloma formation and structure. These factors are likely central to determining different disease outcomes following M. tuberculosis infection and will provide a new tool for testing therapies and vaccines against M. tuberculosis. Tuberculosis (TB) is a world health issue. The immune response to TB is unique, resulting in the formation of structures called granulomas in the lungs of infected people. We seek to understand the formation and function of these structures using integrated data generated from a variety of animal and computational models. (End of Abstract)