Identifying mechanisms driving formation of granuloma-associated fibrosis during Mycobacterium tuberculosis infection

Abstract

Mycobacterium tuberculosis (Mtb), the causative agent of tuberculosis (TB), is a pulmonary pathogen of major global concern. A key feature of Mtb infection in primates is the formation of granulomas, dense cellular structures surrounding infected lung tissue. These structures serve as the main site of host-pathogen interaction in TB, and thus to effectively treat TB we must clarify mechanisms of granuloma formation and their function in disease. Fibrotic granulomas are associated with both good and bad disease outcomes. Fibrosis can serve to isolate infected tissue from healthy tissue, but it can also cause difficulty breathing as it leaves scars. Little is known about fibrosis in TB, and data from non-human primates is just beginning to clarify the picture. This work focuses on constructing a hybrid multi-scale model of fibrotic granuloma formation, in order to identify mechanisms driving development of fibrosis in Mtb infected lungs. We combine dynamics of molecular, cellular, and tissue scale models from previously published studies to characterize the formation of two common sub-types of fibrotic granulomas: peripherally fibrotic, with a cuff of collagen surrounding granulomas, and centrally fibrotic, with collagen throughout granulomas. Uncertainty and sensitivity analysis, along with large simulation sets, enable us to identify mechanisms differentiating centrally versus peripherally fibrotic granulomas. These findings suggest that heterogeneous cytokine environments exist within granulomas and may be responsible for driving tissue scale morphologies. Using this model we are primed to better understand the complex structure of granulomas, a necessity for developing successful treatments for TB.

Figure A1. Snapshots of numerous simulated granulomas at day 150 PI

Shown is simulation of 2mm × 2mm lung tissue. Cells are represented by different colors: resting macrophages are green, activated macrophages are blue, infected macrophages are orange, chronically infected macrophages are red, IFNγ producing T-cells are pink, cytotoxic T cells are violet, regulatory T cells are cyan, fibroblasts are maroon, and myofibroblasts are gold. Caseum is represented in these images as brown compartments. Cytokine distributions for active TGF-β1 shown.

Figure 1. NHP M. tuberculosis granulomas show TGF-β1 driven fibrosis

Top panels feature granulomas stained for collagen I (red), TGF-β1 signaling (green), and macrophages (primary granuloma cell type) (blue). Bottom panels feature granulomas stained for activated TGF-β1 (red), latent TGF-β1 (green), and myofibroblasts (αSMA) (blue). Magnification ×200. A) Granuloma from an animal following two months of antibiotic treatment. B, C, D) Granulomas are from animals with active TB.

Figure 2. Fibroblast dynamics within hybrid multi-scale model architecture

A) Cellular and molecular scale interactions of fibroblasts in the hybrid multi-scale computational model. Fibroblasts, regulatory T cells, and resting macrophages secrete TGF-β1. Fibroblasts, resting and infected macrophages, and all T cell types secrete IL10. Fibroblast to myofibroblast differentiation, as well as myofibroblast secretion of collagen, are promoted by TGF-β1 and inhibited by IL-10. Fibroblasts migrate in response to granuloma associated chemokine milieu. Agent based model rules are available at: http://malthus.micro.med.umich.edu/GranSim/. B) Individual scale models are combined to create a single hybrid multi-scale model of lung granuloma formation and function. The molecular scale includes TGF-β1 receptor ligand signaling dynamics within a single fibroblast, cytokine secretion and diffusion within the environment. At the cellular scale, individual agents, including macrophages, T cells, and fibroblasts, respond based on probabilistic rules to stimuli and cytokines within their local environment. The dynamics from Panel A are included within this scale. At the tissue scale we observe emergent behavior that can be characterized and compared to experimental data.

Figure 3. Simulations of cellular localization and granuloma morphology over time

Representative images of a single granuloma over time generated with baseline parameter set (Table. 1). Shown is simulation of 2mm × 2mm lung tissue. Cells are represented by different colors: resting macrophages are green, activated macrophages are blue, infected macrophages are orange, chronically infected macrophages are red, IFNγ producing T-cells are pink, cytotoxic T cells are violet, regulatory T cells are cyan, fibroblasts are maroon, and myofibroblasts are gold. Caseum is represented in these images as brown compartments. Cytokine distributions are not shown.

Figure 4. Localization of fibroblasts and myofibroblasts from a simulated fibrotic granuloma over time

In this representative simulation (same simulation as Figure 3) fibroblasts are represented as maroon, and myofibroblasts are represented as gold. As time progresses the number of both fibroblasts and myofibroblasts increases. They surround and penetrate the granuloma beginning at about 125 day PI.

Figure 5. Collagen localization in a simulated fibrotic granuloma over time

Collagen concentration is represented in the above images with red representing the highest concentration and blue representing no collagen, relative color bar shown (same simulation as Figures 3,4). Collagen formation is first visible at day 100 PI and it continues to accumulate throughout the simulation, until day 200 PI when it covers the entire simulation space.

Figure 6. IL10 localization in a simulated fibrotic granuloma over time

IL10 concentration is represented in the above images for a single representative granuloma over time (same simulation as in Figures 3,4,5. IL10 is visible early in infection and continues be present throughout the infection. Red represents the highest concentration of IL-10 and blue represents no IL-10 (relative color bar shown).

Figure 7. Active TGF-β1 localization in a simulated fibrotic granuloma over time

Active TGF-β1 concentration is represented in the above images for a single representative granuloma (same simulation as in Figures 3,4,5,6). Red represents the highest concentration of active TGF-β1 and blue represents no active TGF-β1 (relative color bar shown).

Figure 8. Latent TGF-β1 localization in a simulated fibrotic granuloma over time

Latent TGF-β1 concentration is represented in the above images for a single representative granuloma. Latent TGF-β1 is visible early in infection and continues be present throughout infection (same simulation as in Figures 3,4,5,6,7). Red represents the highest concentration of latent TGF-β1 and blue represents no latent TGF-β1 (relative color bar shown).

Figure 9. Fibroblast and myofibroblast numbers in 500 simulated granulomas over time

Each line represents and individual granuloma from the fibrosis parameter set (Table 1). A) Fibroblasts per granuloma over 300 days PI. B) Myofibroblasts per granuloma over 300 days PI.

Figure 10. Snapshots of a simulated granulomas comparing fibroblast localization when fibroblast movement is enabled and inhibited

Simulation of 2mm ×2mm lung tissue. A) Snapshot of simulated granuloma showing the fibroblasts localization when fibroblast movement is permitted. Cells are represented by different colors as follows: resting macrophages are green, activated macrophages are blue, infected macrophages are orange, chronically infected macrophages are red, IFNγ producing T-cells are pink, cytotoxic T cells are violet, regulatory T cells are cyan, fibroblasts are maroon, and myofibroblasts are gold. B) Snapshot of the same simulated granuloma as shown in A, when fibroblast movement is completely inhibited. Distributions of cytokines not shown.

Figure 11. Snapshot of a simulated granuloma exhibiting central fibrosis at 150 days post infection

Simulation of 2mm ×2mm lung tissue. A) Snapshot of simulated granuloma showing localization of all cell types. Myofibroblasts can be seen in the center of the lesion. Cells are represented by different colors as follows: resting macrophages are green, activated macrophages are blue, infected macrophages are orange, chronically infected macrophages are red, IFNγ producing T-cells are pink, cytotoxic T cells are violet, regulatory T cells are cyan, fibroblasts are maroon, and myofibroblasts are gold. B) Snapshot of simulated granuloma displaying only fibroblasts, myofibroblasts, and caseum. Caseum is represented in these images as brown compartments. Cytokine distributions not shown.