Abstract
Agent-based simulation is a powerful method for investigating the complex interplay of the processes occurring in a lymph node during an adaptive immune response. We have previously established an agent-based modeling framework for the interactions between T cells and dendritic cells within the paracortex of lymph nodes. This model simulates in three dimensions the “random-walk” T cell motility observed in vivo, so that cells interact in space and time as they process signals and commit to action such as proliferation. On-lattice treatment of cell motility allows large numbers of densely packed cells to be simulated, so that the low frequency of T cells capable of responding to a single antigen can be dealt with realistically. In this paper we build on this model by incorporating new numerical methods to address the crucial processes of T cell ingress and egress, and chemotaxis, within the lymph node. These methods enable simulation of the dramatic expansion and contraction of the T cell population in the lymph node paracortex during an immune response. They also provide a novel probabilistic method to simulate chemotaxis that will be generally useful in simulating other biological processes in which chemotaxis is an important feature.
Highlights
We have previously developed an agent-based model to simulate lymphocyte behaviour in the lymph node (LN), in which cells move on a three-dimensional lattice [1,2,3]
To simulate the dramatic changes in lymphocyte ingress that occur during an immune response, driving first the expansion the contraction of the T cell population, a sub-model has been developed to link influx rate to inflammation signals, by way of changes in vascularity modulated by growth factors
Reflecting the level of uncertainty about how lymph node blood vessels change in response to infection, no precise physiological meaning is attached to the term ‘‘vascularity’’ – it is treated as a factor that multiplies the baseline uninfected rate of influx
Summary
We have previously developed an agent-based model to simulate lymphocyte behaviour in the lymph node (LN), in which cells move on a three-dimensional lattice [1,2,3]. At its current stage of development, the model is restricted to processes involving T cells and dendritic cells (DCs) in the lymph node paracortex, and the aim is to represent T cell activation and proliferation during an immune response. In the relatively-short intravital tracking periods (typically no more than an hour) the cells appear to follow trajectories that are well described as persistent random walks, and it was initially thought that their motion was purely random (with characteristics strongly influenced by the random structure of the underlying fiber network). Some experimental observations suggest that subtle biases in the motion resulting from chemotactic signals, for example from activated DCs bearing antigen, could have significant effects on the immune response, even if those signals were below the level of detection in the early in vivo microscopy studies [8,9]. We have been interested to explore methods to incorporate subtle chemotactic effects into our model
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