Mathematical Biology Seminar: Ramit Mehr (Bar Ilan University)

The immune response involves cells of various types, including B, T and Natural Killer (NK) lymphocytes expressing a large diversity of receptors which recognize foreign antigens and self-molecules. The various cell types interact through a complicated network of communication and regulation mechanisms. These interactions enable the immune system to perform the functions of danger recognition, decision, action, memory and learning. As a result, the dynamics of lymphocyte repertoires are highly complex and non-linear. The humoral (antibody-generating) immune response is one of the most complex responses, as it involves somatic hypermutation of the B cell receptor (BCR) genes and subsequent antigen-driven selection of the resulting mutants. This process has been and still is extensively studied using a variety of experimental methods, ranging from intravital imaging to studying the mutations in BCR genes, and has also been one of the most often modeled phenomena in the theoretical immunology community. The problem for modelers, however, is that until recently kinetic data on the humoral immune response were so limited that all models could fit those data. We have addressed this and the challenge of following individual clones by combining modeling with a novel immunoinformatical method of generation and quantification of lineage trees from B cell clones undergoing somatic hypermutation. We applied these new analyses to the study of humoral response changes in aging, chronic or autoimmune diseases and B cell malignancies. Finally, we used simulations to answer some theoretical questions regarding the evolution of BCR genes.