We develop a mathematical framework for modeling regulatory mechanisms
the adaptive immune system. The model describes dynamics of several
components of the immune system, including effector and regulatory T
cells, antigen-presenting cells, and cell signaling. The model also
incorporates two key microenvironments: the lymph node and the tissue.
The model captures three features of the dynamics and regulation of
primary adaptive response: 1) Transition between expansion and
phases of the immune response, 2) Self/non-self discrimination, and 3)
cell traffic between the lymph node and tissue during the course of
primary response. All three of these self-regulatory mechanisms are
mediated in large part by regulatory T cells.
In this talk, we focus primarily on deepening our understanding the
point, namely the timely transition between expansion and contraction
phases. In trying to unravel the mechanism behind a normal, healthy T
cell response, we draw connections to the behavior of other well-known
excitable systems studied in molecular biology and physiology.
Although various computational models exist, the fundamental dynamics
immune regulation still remains unexplained, so in closing, we propose
few potential approaches to unraveling this mystery.