The model presented here is an extension of a previous ABM that captured cellular interactions leading to granuloma formation during infection with Mtb (38 (link)). The model is considered hybrid since we incorporated both discrete entities (cells) and continuous entities (chemokines, TNF and Mtb) that interact simultaneously. ABMs are developed based on four considerations: an environment, agents that reside there, the rules that describe the agents and their interactions, and the timescales on which events are defined.
The environment represents a 2 mm × 2 mm section of lung parenchyma as a 100 × 100 square 2-dimensional lattice with individual micro-compartments scaled to the approximate size of a single macrophage: 20 μm in diameter (39 (link)). Discrete agents move on the lattice and respond to their environment based on rules reflecting known biological activities. Bacteria and effector molecules can reside anywhere on the lattice and undergo diffusion when appropriate.
Caseation represents inflammation of, and damage to, the lung parenchyma from macrophage cell death. We note a change of terminology to “caseation” from “necrosis” in previous work (38 (link)), as strict necrosis within the granuloma is now believed to be caused by substantial neutrophil infiltration and death, while caseation is likely initiated by macrophage death (unpublished data, JLF). In the ABM, caseation is defined to occur when a threshold number of activated or infected macrophage deaths take place in a micro-compartment. A final environmental feature is designation of spaces as vascular sources.
We include two types of discrete agents in the model: macrophages and T cells. As previously (20 (link), 38 (link)), macrophage agents are either resting (Mr, uninfected), infected (Mi; have taken up bacteria), chronically infected (Mci; are unable to clear their intracellular bacterial load), or activated (Ma; can effectively kill bacteria). In contrast to our previous study (38 (link)), where a single T cell class captured all cell behaviors, here we represent three distinct T cell subpopulations based on function: the Tγ class captures CD4+ and CD8+ pro-inflammatory T cells; Tc represent cytotoxic T cells; and Treg represent regulatory T cells. In this representation, all T cells in a particular class have identical function; this is simpler than in vivo, but we capture enough detail in this representation for a qualitative representation of known T cell effects.
In addition to the discrete entities, extracellular bacteria, diffusing effector molecules (CCL2, CCL5, CXCL9/10/11 and TNF) are agents (concentrations) that are tracked continuously over time. The chemokine model used here is a simplification that was chosen to include a ligand for each key chemokine receptor, while minimizing the distinct chemokine classes represented to save on computation.
Cells respond to signals in the surrounding environment according to rules that represent known activities in vivo. During simulations, each agent responds depending on its state. Examples of rules include uptake of bacteria, macrophage activation by T cells, secretion of cytokines and chemokines, etc. For a full list of rules, seeSupplement 1 .
The environment represents a 2 mm × 2 mm section of lung parenchyma as a 100 × 100 square 2-dimensional lattice with individual micro-compartments scaled to the approximate size of a single macrophage: 20 μm in diameter (39 (link)). Discrete agents move on the lattice and respond to their environment based on rules reflecting known biological activities. Bacteria and effector molecules can reside anywhere on the lattice and undergo diffusion when appropriate.
Caseation represents inflammation of, and damage to, the lung parenchyma from macrophage cell death. We note a change of terminology to “caseation” from “necrosis” in previous work (38 (link)), as strict necrosis within the granuloma is now believed to be caused by substantial neutrophil infiltration and death, while caseation is likely initiated by macrophage death (unpublished data, JLF). In the ABM, caseation is defined to occur when a threshold number of activated or infected macrophage deaths take place in a micro-compartment. A final environmental feature is designation of spaces as vascular sources.
We include two types of discrete agents in the model: macrophages and T cells. As previously (20 (link), 38 (link)), macrophage agents are either resting (Mr, uninfected), infected (Mi; have taken up bacteria), chronically infected (Mci; are unable to clear their intracellular bacterial load), or activated (Ma; can effectively kill bacteria). In contrast to our previous study (38 (link)), where a single T cell class captured all cell behaviors, here we represent three distinct T cell subpopulations based on function: the Tγ class captures CD4+ and CD8+ pro-inflammatory T cells; Tc represent cytotoxic T cells; and Treg represent regulatory T cells. In this representation, all T cells in a particular class have identical function; this is simpler than in vivo, but we capture enough detail in this representation for a qualitative representation of known T cell effects.
In addition to the discrete entities, extracellular bacteria, diffusing effector molecules (CCL2, CCL5, CXCL9/10/11 and TNF) are agents (concentrations) that are tracked continuously over time. The chemokine model used here is a simplification that was chosen to include a ligand for each key chemokine receptor, while minimizing the distinct chemokine classes represented to save on computation.
Cells respond to signals in the surrounding environment according to rules that represent known activities in vivo. During simulations, each agent responds depending on its state. Examples of rules include uptake of bacteria, macrophage activation by T cells, secretion of cytokines and chemokines, etc. For a full list of rules, see