2014/07/25 by Andreas Mayer, Vijay Balasubramanian, Thierry Mora +1 · 5 citations
Biochemistry, Genetics and Molecular Biology · Engineering · Neuroscience · Physics and Astronomy · #Artificial Immune Systems Applications #Biology #Computer science #Immune system #Immunology #Neuroinflammation and Neurodegeneration Mechanisms #Tryptophan and brain disorders #cond-mat.dis-nn #physics.bio-ph #q-bio.PE
paper · pdf · doi:10.1073/pnas.1421827112
arxiv created 2014/07/25 · openalex publication_date 2015/04/27 · arxiv updated 2016/02/17 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/06
The repertoire of lymphocyte receptors in the adaptive immune system protects organisms from diverse pathogens. A well-adapted repertoire should be tuned to the pathogenic environment to reduce the cost of infections. We develop a general framework for predicting the optimal repertoire that minimizes the cost of infections contracted from a given distribution of pathogens. The theory predicts that the immune system will have more receptors for rare antigens than expected from the frequency of encounters; individuals exposed to the same infections will have sparse repertoires that are largely different, but nevertheless exploit cross-reactivity to provide the same coverage of antigens; and the optimal repertoires can be reached via the dynamics of competitive binding of antigens by receptors and selective amplification of stimulated receptors. Our results follow from a tension between the statistics of pathogen detection, which favor a broader receptor distribution, and the effects of cross-reactivity, which tend to concentrate the optimal repertoire onto a few highly abundant clones. Our predictions can be tested in high-throughput surveys of receptor and pathogen diversity.