How antigen quantity and quality determine T cell decisions in lymphoid tissue

Departments of Chemical Engineering, Chemistry, and Biological Engineering, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, MA 02139; Department of Pathology and the CBR Institute for Biomedical Research, Harvard Medical School, 77 Louis Pasteur Avenue, Boston, MA 02115; Theoretical Biology and Biophysics, Los Alamos National Laboratory, Los Alamos, NM 87545

^* To whom correspondence should be addressed. Email: arupc{at}mit.edu.

	Abstract

T lymphocytes (T cells) express T cell receptor (TCR) molecules on their surface that can recognize peptides (p) derived from antigenic proteins bound to products of the major histocompatibility (MHC) genes. The pMHC molecules are expressed on the surface of antigen presenting cells, such as dendritic cells (DC). T cells first encounter antigen on DCs in lymph nodes (LN). Intravital microscopy experiments show that, upon entering the LN containing antigen, CD8+ T cells first move rapidly. After a few hours, they stop and make extended contacts with DCs. The factors that determine when and how this transition occurs are not well understood. We report results from computer simulations that suggest that the duration of phase one is related to the low probability of productive interactions between T cells and DCs. This is demonstrated by our finding that antigen dose and type determine when such a transition occurs. These results are in agreement with experimental observations. TCR-pMHC binding characteristics and antigen dose determine the time required for a productive T cell-DC encounter (resulting in sustained contact). We find that the ratio of this time scale and the half-life of the pMHC complex itself provides a consolidated measure of antigen quantity and type. Results obtained upon varying different measures of antigen quantity and type fall on one curve when graphed against this ratio of time scales. Thus, we provide a mechanism for how the effects of varying one set of parameters is influenced by other prevailing conditions. This understanding should help guide future experimentation.