24 June 2022
Grégoire Altan-Bonnet
Laboratory of Integrative Cancer Immunology
National Cancer Institute
Paul François
Department of Physics
McGill University, Canada
We present an experimental/theoretical pipeline to build a quantitative model of antigen discrimination by T cells. We find that the multiplexed dynamics of cytokine production and consumption by T cells ex-vivo can be compressed into a 1D model using tools from machine learning. This model highlights two modalities of T cell activation that enforce adaptive kinetic proofreading of antigen-TCR interaction and that encode antigen discrimination. We discuss theoretical as well as practical applications of rigorous antigen quantification across varied immunological settings.