| Description |
Epstein-Barr virus (EBV) infects more than 90% of human population worldwide and has the ability to persist for the lifetime of the infected person. Although EBV infection is most often asymptomatic, the virus causes infectious mononucleosis (IM) in teenagers and young adults. Within a host, EBV can alternate infection between B cells and epithelial cells. The presence of EBV DNA inside these infected cells has been associated with different types of cancers. Many aspects of EBV infection within a host including the switching infections between cell types, the effects of this switching, the factors involve in regulation of the persistent infection, and what parts of the regulation can go wrong that induce different types of disease, are not well understood. The aim of our work is studying these aspects using the tools of mathematical models. We first explore the role of EBV glycoprotein gp42 in the virus entry into target cells. Our models support the role of cooperation of multiple viral glycoproteins in virus entry and suggest that the intracellular interactions of gp42 with HLA class II in B cells may disrupt gp42 function. We then study the dynamics of EBV infection within a host and show that EBV switching host cell tropism shapes the persistence, evolution, and coexistence of the virus infection. Our model of the within host dynamics suggests that the age dependence of IM can be explained by the host antibodies that enhance infections of epithelial cells and the cross-reactive responses of aggressive but functionally ineffective T cells previously created by other infections. We also investigate the association of EBV infection with the development of nasopharyngeal carcinoma (NPC), a cancer of epithelial cells in the pharynx. Our model predicts a threshold of the number of effector T cells below which a bifurcation leads to a jump from a low to high level of latently infected epithelial cells that can greatly elevate the risk of NPC development. Our model also produces the patterns of age-incidence curves that have been observed in low risk and high risk populations. |
