A population dynamics analysis of the interaction between adaptive regulatory T cells and antigen presenting cells.
BACKGROUND
Regulatory T cells are central actors in the maintenance of tolerance of self-antigens or allergens and in the regulation of the intensity of the immune response during infections by pathogens. An understanding of the network of the interaction between regulatory T cells, antigen presenting cells and effector T cells is starting to emerge. Dynamical systems analysis can help to understand the dynamical properties of an interaction network and can shed light on the different tasks that can be accomplished by a network.


RESULTS
We used a mathematical model to describe a interaction network of adaptive regulatory T cells, in which mature precursor T cells may differentiate into either adaptive regulatory T cells or effector T cells, depending on the activation state of the cell by which the antigen was presented. Using an equilibrium analysis of the mathematical model we show that, for some parameters, the network has two stable equilibrium states: one in which effector T cells are strongly regulated by regulatory T cells and another in which effector T cells are not regulated because the regulatory T cell population is vanishingly small. We then simulate different types of perturbations, such as the introduction of an antigen into a virgin system, and look at the state into which the system falls. We find that whether or not the interaction network switches from the regulated (tolerant) state to the unregulated state depends on the strength of the antigenic stimulus and the state from which the network has been perturbed.


CONCLUSIONS
Our findings suggest that the interaction network studied in this paper plays an essential part in generating and maintaining tolerance against allergens and self-antigens.
Fouchet
David
D
Institute of Integrative Biology, Die Eidgenössische Technische Hochschule Zentrum, Zürich, Switzerland. david.fouchet@env.ethz.ch
Regoes
Roland
R
D000938:Antigen-Presenting Cells / Q000276:immunology*; D006801:Humans; D008962:Models, Theoretical; D050378:T-Lymphocytes, Regulatory / Q000276:immunology*