Universal antigen encoding of T cell activation from high-dimensional cytokine dynamics
Sooraj Achar, François X. P. Bourassa, Thomas J. Rademaker, Angela Lee, Taisuke Kondo, Emanuel Salazar-Cavazos, John Davies, Naomi Taylor, Paul François, Grégoire Altan‐Bonnet
Abstract
Systems immunology lacks a framework with which to derive theoretical understanding from high-dimensional datasets. We combined a robotic platform with machine learning to experimentally measure and theoretically model CD8 + T cell activation. High-dimensional cytokine dynamics could be compressed onto a low-dimensional latent space in an antigen-specific manner (so-called “antigen encoding”). We used antigen encoding to model and reconstruct patterns of T cell immune activation. The model delineated six classes of antigens eliciting distinct T cell responses. We generalized antigen encoding to multiple immune settings, including drug perturbations and activation of chimeric antigen receptor T cells. Such universal antigen encoding for T cell activation may enable further modeling of immune responses and their rational manipulation to optimize immunotherapies.