Lab web site: https://sites.google.com/site/sokendaisasaki/
Pathogens, such as HIV and the trypanosomes causing sleeping sickness, evade attack by the host immune system with a clever strategy of continuously “changing” surface antigens after host infection. To predict the epidemics and evolution of such pathogens, we need mathematical models to simulate the evolution of viral surface antigens and the immune response in infected individuals. The figure below (phylogenetic tree) shows how new antigenic types of a virus sequentially emerge within a host, based on a simulation using a mathematical model. Such a model is used for evaluating the diversity threshold for immunodeficiency, the evolution of virulence, the evolutionary rate, the optimal mutation rate, and the efficacy of vaccines and drugs, and for predicting epidemics. Other topics, such as the proliferation strategies of pathogens within a host, the evolution of the number of sexes, the evolution in sex and recombination, bethedging strategies and genetic diversity in fluctuating environments, the evolution of phenotypic plasticity, the coevolution of resistance and virulence in coupled host-parasitoid interactions, the evolution of mutability in fitness landscapes, the evolution of cooperative behavior in finite populations, pathogen virulence in small world networks, the coexistence of antigenic types of dengue virus, spatial mosaic formation in Mullerian mimicry, the geometric desynchronization of coevolutionary cycles, sympatric speciation and niche partitioning, and the evolution of restriction enzyme recognition sequences, have all been studied using mathematical models.