BME PhD Preliminary Exam Announcement for Alexis Hoerter (E. Pienaar, advisor) Everyone is invited to attend the public presentation beginning at 11:00am. Research Title: Agent Based Models Characterizing In Vitro M. Tuberculosis Granuloma Dynamics: Host-Immune Status Determinants and HIV Coinfection Mechanisms Date: Wednesday, November 16th, 2022 Time: 11:00am Location: MJIS 2001 and with the following zoom link: https://purdue-edu.zoom.us/j/95200759998?pwd=ZG1PMDh6eG9jWGFqWWptM0RuNkVhUT0... <https://purdue-edu.zoom.us/j/95200759998?pwd=ZG1PMDh6eG9jWGFqWWptM0RuNkVhUT09> Thesis Committee: * Dr. Elsje Pienaar - Major Professor * Dr. Larry S. Schlesinger * Dr. Alexandria Volkening * Dr. Qing Deng Abstract: Tuberculosis (TB) is the 2nd most deadly infectious disease behind Covid-19 with ~10 million new cases and ~1.5 million deaths worldwide in 2020. TB infection is associated with a wide spectrum of outcomes ranging from complete elimination of bacteria, to bacterial containment in asymptomatic clinical states [latent TB infection (LTBI)], to high bacterial replication in active disease with severe clinical symptoms. How individuals move throughout this spectrum is still being uncovered; however, the host immune status is a strong determinant of infection progression. The risk of active TB is ~10% in individuals with LTBI and 15-21 times higher in those coinfected with human immunodeficiency virus-1 (HIV). The hallmark of TB infection is the formation of granulomas – unique microenvironments orchestrated by the immune response to contain Mycobacterium tuberculosis (Mtb) and localize host-pathogen interactions. Granulomas are the main site of infection and driver of disease progression, but studying intra-granuloma dynamics of human Mtb infection in vivo is challenging. In vitro Mtb granulomas using human donor cells have shown how the host immune status (LTBI vs Mtb-naïve) as well as coinfection with HIV can have critical and distinct impacts on the formation of granulomas. However, identifying mechanisms behind these differences using experimental data alone is a formidable task. Here, we present a complementary approach using an agent-based model of these in vitro granulomas to help elucidate differences between LTBI and naïve host cell responses as well as mechanisms of coinfection with HIV. Coupling computational modeling with experimental efforts could accelerate new treatment discoveries.