(376c) Model-Based Analysis and Quantitative Measurement of Key Components of Tumor Necrosis Factor Trafficking in a Tuberculosis Granuloma

Tuberculosis (TB) is caused by a highly successful bacterium, Mycobacterium tuberculosis (Mtb), and is responsible for 2 million deaths per year. The interplay between host and bacterial factors at a variety of length and time scales leads to different disease outcomes (primary disease, latency, or TB reactivation). A key outcome of TB infection is the formation of a granuloma. Tuberculosis granulomas are organized collections of immune cells composed of macrophages, lymphocytes and other cells that form in the lung in response to Mtb infection. Granuloma formation is essential for immunologic and physical control of mycobacterial infection. Maintenance of granulomas is required during latent TB, during which infection is contained with no symptoms. Our overall hypothesis is that events at several spatial (molecular, cellular, tissue, body) and time (minutes to years) scales affect the development and maintenance of TB granulomas, and that a model of granuloma formation that encompasses multiple scales is necessary to fully understand the immune response to Mtb. In this work, we focus specifically on molecular, cellular, and multi-cellular aspects of the granuloma and the central role of tumor necrosis factor α (TNF) in these interactions.

TNF is well-known as a key effector molecule in the host protective immune response against tuberculosis. This cytokine can be produced by immune cells including macrophages, neutrophils, and T cells and exerts its action on multiple cell types by affecting cell activation and migration, expression of chemokines, apoptosis and other biological processes. Numerous reports have revealed the role of TNF in granuloma formation, granuloma maintenance and the containment of Mtb infection [1-3]. Granuloma formation in mice that lack TNF or the TNF receptor 1 has been reported to be aberrant or delayed. Neutralization of TNF in mice with chronic infection leads to disorganization of the granulomas and subsequent death.

Our hypothesis is that TNF availability within granulomas is crucial in granuloma formation, functionality and integrity and thus control of TB infection. TNF availability is controlled at the molecular level by the kinetics of a combination of events, including TNF synthesis and release, receptor binding, internalization and degradation. Hence, to characterize the mechanisms by which TNF availability within a TB granuloma is controlled, we developed a reaction/diffusion-based differential equation model that describes a TB granuloma as a continuous collection of immune cells forming concentric layers and includes TNF-associated molecular-level events. These events include TNF synthesis by TNF-producing cells, TNF release to the extracellular space due to the activity of TNF-α converting enzyme (TACE), reversible binding of TNF to two types of TNF receptors on the cell membranes, TNF/TNF receptor intracellular trafficking, as well as TNF diffusion within granuloma. The model outcome is the fraction of TNF-bound cell surface TNF receptors in the granuloma, the major factor that controls TNF-mediated signaling and thus cellular level responses in TB infection. Parameters that significantly influence the outcome of the model were identified by sensitivity analysis. Cellular composition of granuloma, the number of TNF receptors on each cell type within granuloma, affinity of TNF receptors for binding to TNF, and the rate of TNF receptor-mediated endocytosis of TNF were shown to be the most important determinants of TNF availability within granuloma.

Experiments were performed to measure the required parameters in pulmonary granulomas induced in pre-sensitized mice by bead-immobilized mycobacterial purified protein derivative (PPD) by using multi-color flow cytometry. This experimental model has been previously demonstrated to induce an immune response typified by a type 1 cytokine phenotype which has been characterized in TB [4, 5]. PPD bead granulomas form at day 2 and reach their maximal size at day 4 following intravenous injection of PPD-coated beads. To identify the cellular composition of PPD bead granulomas and cell fractions, fluorescing antibodies for specific cell surface markers of different types of immune cells were used. Experimental results indicate that dendritic cells, macrophages, B cells, CD4+ and CD8+ T cells compose more than eighty percent of the structure of PPD-bead granulomas with B cells and macrophages showing the greatest cell fractions. A significant increase in the fraction of T cells (which represent the adaptive immune response) was observed with granuloma development up to day 4. In order to determine the rate of TNF synthesis, an inhibitor for protease activity of TACE such as TNF-α proteinase inhibitor-1 (TAPI-1) was used to inhibit TNF release from the cell membrane and the rate of TNF accumulation on the membrane was identified by quantitative flow cytometry. Dendritic cells and macrophages (at the core of granuloma) were shown to be the major TNF-producing cells within granuloma. Quantitative flow cytometry was also used to determine the cell-specific numbers of receptors within granuloma. Almost all cell types express TNF receptors, while lymphocytes down-regulate TNF receptor expression with granuloma development.

Using these experimental data on TNF-associated molecular processes and the cellular composition of PPD-bead granulomas as inputs to our multi-cellular mathematical model, we studied the role of these processes in controlling TNF availability in a TB granuloma. Our modeling results show that immune cell organization (with different levels of TNF and TNF receptor expression) within a TB granuloma is a significant factor that controls TNF availability and thus TNF signaling. Because cellular organization undergoes dynamic changes with granuloma development and at different stages of immune response (innate versus adaptive) to TB infection, it can be a factor controlling the diverse activities of TNF according to the stage of infection in the lung tissue. Cellular organization can also significantly influence the outcome of anti-TNF treatments during different stages of infection. Our modeling and experimental findings on TNF-associated molecular and multi-cellular scale aspects of granuloma can be incorporated into larger scale models describing the immune response to TB infection, including, for example, cellular input from the lymph node and circulation of immune cells in the blood. Ultimately, these modeling and experimental results can help identify new strategies for TB disease control/therapy.

[1] Flynn JL, Goldstein MM, Chan J, Triebold KJ, Pfeffer K, et al. (1995) Tumor necrosis factor-alpha is required in the protective immune response against mycobacterium tuberculosis in mice. Immunity 2: 561-572.

[2] Egen JG, Rothfuchs AG, Feng CG, Winter N, Sher A, et al. (2008) Macrophage and T cell dynamics during the development and disintegration of mycobacterial granulomas. Immunity 28: 271-284.

[3] Chakravarty SD, Zhu G, Tsai MC, Mohan VP, Marino S, et al. (2008) Tumor necrosis factor blockade in chronic murine tuberculosis enhances granulomatous inflammation and disorganizes granulomas in the lungs. Infect Immun 76: 916-926.

[4] Chensue SW, Warmington K, Ruth J, Lincoln P, Kuo MC, et al. (1994) Cytokine responses during mycobacterial and schistosomal antigen-induced pulmonary granuloma formation. production of Th1 and Th2 cytokines and relative contribution of tumor necrosis factor. Am J Pathol 145: 1105-1113.

[5] Qiu B, Frait KA, Reich F, Komuniecki E, Chensue SW (2001) Chemokine expression dynamics in mycobacterial (type-1) and schistosomal (type-2) antigen-elicited pulmonary granuloma formation. Am J Pathol 158: 1503-1515.