How the T cell signaling network processes information to discriminate between self and agonist ligands
Published in Proceedings of the National Academy of Sciences of the United States of America, 2020
Recommended citation: Ganti, Raman S., et al. ``How the T cell signaling network processes information to discriminate between self and agonist ligands.' Proceedings of the National Academy of Sciences 117.42 (2020): 26020-26030. http://rganti.github.io/files/T_Cell_PNAS.pdf
Information theory was invented to solve the task of sending reliable communication over an unreliable channel. T cells have extremely reliable signal-processing capacity as they sensitively and specifically respond to a few pathogen-derived peptide ligands displayed in the noisy environment of many self-derived ligands presented on the same antigen-presenting cell. In this paper, we used information-theoretic concepts to analyze a computational model of the biochemical steps in the T cell signaling network to understand how key features of the T cell signaling pathway enable discriminatory ability. Our calculations and experiments suggest that T cells superimpose kinetic proofreading steps that must be spatially localized with the receptor and feedback loops to extract reliable information from a noisy environment.
Recommended citation: Ganti, Raman S., et al. ``How the T cell signaling network processes information to discriminate between self and agonist ligands.’’ Proceedings of the National Academy of Sciences 117.42 (2020): 26020-26030.