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Clinical manifestations of TB exist across a spectrum with a majority of infected individuals remaining asymptomatic, commonly referred to as latent TB infection (LTBI).\n              <jats:italic>In vitro<\/jats:italic>\n              models have demonstrated that cells from individuals with LTBI can better control\n              <jats:italic>Mtb<\/jats:italic>\n              growth and form granuloma-like structures more quickly, compared to cells from uninfected (\n              <jats:italic>Mtb<\/jats:italic>\n              -na\u00efve) individuals. These\n              <jats:italic>in vitro<\/jats:italic>\n              results agree with animal and clinical evidence that LTBI protects, to some degree, against reinfection. However, the mechanisms by which LTBI might offer protection against reinfection remain unclear, and quantifying the relative contributions of multiple control mechanisms is challenging using experimental methods alone. To complement\n              <jats:italic>in vitro<\/jats:italic>\n              models, we have developed an\n              <jats:italic>in silico<\/jats:italic>\n              agent-based model to help elucidate host responses that might contribute to protection against reinfection. Our simulations indicate that earlier contact between macrophages and CD4+ T cells leads to LTBI simulations having more activated CD4+ T cells and, in turn, more activated infected macrophages, all of which contribute to a decreased bacterial load early on. Our simulations also demonstrate that granuloma-like structures support this early macrophage activation in LTBI simulations. We find that differences between LTBI and\n              <jats:italic>Mtb<\/jats:italic>\n              -na\u00efve simulations are driven by TNF\u03b1 and IFN\u03b3-associated mechanisms as well as macrophage phagocytosis and killing mechanisms. Together, our simulations show how important the timing of the first interactions between innate and adaptive immune cells is, how this impacts infection progression, and why cells from LTBI individuals might be faster to respond to reinfection.\n            <\/jats:p>\n            <jats:sec>\n              <jats:title>IMPORTANCE<\/jats:title>\n              <jats:p>\n                Tuberculosis (TB) remains a significant global health challenge, with millions of new infections and deaths annually. Despite extensive research, the mechanisms by which latent TB infection (LTBI) confers protection against reinfection remain unclear. In this study, we developed an\n                <jats:italic>in silico<\/jats:italic>\n                agent-based model to simulate early immune responses to\n                <jats:italic>Mycobacterium tuberculosis<\/jats:italic>\n                infection based on experimental\n                <jats:italic>in vitro<\/jats:italic>\n                infection of human donor cells. Our simulations reveal that early interactions between macrophages and CD4+ T cells, driven by TNF\u03b1 and IFN\u03b3, are critical for bacterial control and granuloma formation in LTBI. These findings offer new insights into the immune processes involved in TB, which could inform the development of targeted vaccines and host-directed therapies. By integrating experimental data with computational predictions, our research provides a robust framework for understanding TB immunity and guiding future interventions to mitigate the global TB burden.\n              <\/jats:p>\n            <\/jats:sec>\n          <\/jats:sec>","DOI":"10.1128\/msystems.01290-24","type":"journal-article","created":{"date-parts":[[2025,2,7]],"date-time":"2025-02-07T14:00:43Z","timestamp":1738936843000},"update-policy":"https:\/\/doi.org\/10.1128\/asmj-crossmark-policy-page","source":"Crossref","is-referenced-by-count":7,"title":["Timing matters in macrophage\/CD4+ T cell interactions: an agent-based model comparing\n            <i>Mycobacterium tuberculosis<\/i>\n            host-pathogen interactions between latently infected and na\u00efve individuals"],"prefix":"10.1128","volume":"10","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-6667-1796","authenticated-orcid":false,"given":"Alexis","family":"Hoerter","sequence":"first","affiliation":[{"name":"Weldon School of Biomedical Engineering, Purdue University","place":["West Lafayette, USA"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Alexa","family":"Petrucciani","sequence":"additional","affiliation":[{"name":"Weldon School of Biomedical Engineering, Purdue University","place":["West Lafayette, USA"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jordan","family":"Bonifacio","sequence":"additional","affiliation":[{"name":"Texas Biomedical Research Institute","place":["San Antonio, Texas, USA"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Eusondia","family":"Arnett","sequence":"additional","affiliation":[{"name":"Texas Biomedical Research Institute","place":["San Antonio, Texas, USA"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Larry S.","family":"Schlesinger","sequence":"additional","affiliation":[{"name":"Texas Biomedical Research Institute","place":["San Antonio, Texas, USA"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5408-8795","authenticated-orcid":true,"given":"Elsje","family":"Pienaar","sequence":"additional","affiliation":[{"name":"Weldon School of Biomedical Engineering, Purdue University","place":["West Lafayette, USA"]},{"name":"Regenstrief Center for Healthcare Engineering, Purdue University","place":["West Lafayette, USA"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"235","reference":[{"key":"e_1_3_4_2_2","unstructured":"World Health Organization. 2023. 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