Information processing in the adaptive immune response

The adaptive immune system surveils a large distribution of antigens and implements a range of complex multi-cellular outcomes in response. Each antigen is characterized by features encoded in its physical structure and the dynamics of its source pathogen. Although systems immunology has catalogued the molecular interactions mediating the immune response, we lack an understanding of how the response is calibrated to antigen features. Furthermore, as the response is constrained by molecular noise and phenotypic variation in responding cells, it is unclear how the system delivers an appropriate and effective response. Here, using computational and analytic methods, we investigate how the network of agents – antigens, cytokines, naïve, effector, memory and regulatory cells – processes information about antigen features. We compare the information capacity of many network structures and identify biologically plausible networks that maximize information transmission in the adaptive immune response. A comprehensive understanding of these networks may be critical for the safe and robust application of perturbative immune therapies in cancer and other diseases.