Modeling intercellular interactions in the peripheral immune system

• Authors: Stephanie Forrest;Christina Elizabeth Warrender
• Venue: Modeling intercellular interactions in the peripheral immune system
• Year: 2004

Peripheral tissue microenvironments play an important role in determining responses to infection, but these small-scale interactions are usually not included in immune system models. An immune response to a pathogen involves numerous cells of several different types, each with a limited ability to sense its environment and to act. These cells produce many kinds of signalling molecules called cytokines that act locally to affect cell behavior. The dynamical interactions among this heterogeneous collection of cells and molecules are extremely complex. To begin to understand such a system, we need modeling approaches that can relate population-level dynamics to individual cell interactions and responses to cytokines. This thesis describes a spatially explicit simulator that tracks individual cell responses to local molecular signals, and the use of that simulator to study models of peripheral tissue dynamics in normal and disease conditions. The simulator implements a hybrid framework combining discrete representation of individual cells and continuous representation of molecular concentrations. Cell behaviors consist of sensing, intracellular processing, and action functions that can be combined in various ways to accommodate a variety of models. Connecting extracellular signals to individual cell actions is difficult because intracellular signalling itself is complex and incompletely understood. Many of the processes involved occur on different timescales and stochastic effects may be important. The approach presented here abstracts away much of this intracellular signalling complexity, while capturing the aspects most likely to affect intercellular dynamics. Separation of sensing and processing allows the kind of pleiotropy seen in intercellular systems—each cytokine may affect multiple cell actions, and multiple cytokines may affect a single action. The goal of this work is to relate individual cell actions and intercellular interactions to observed population-level dynamics. For concreteness, this study focuses on alveolar lung tissue and the response to Mycobacterium tuberculosis. In the absence of infection, a dynamic population of peripheral immune system effector cells provides a sentinel function. In an effective response to pathogenic challenge, this population expands and changes function to either eliminate the pathogen, or—as in many cases of tuberculosis—isolate it and minimize the effects on surrounding tissues. This requires recruitment and spatial organization of the right kinds of cells and appropriate regulation of their effector functions. The models presented here explore the relative importance of various regulatory mechanisms in effectively controlling a local population of immune cells.