HIV dynamics with multiple infections of target cells

The high incidence of multiple infections of cells by HIV sets the stage for rapid HIV evolution by means of recombination. Yet how HIV dynamics proceeds with multiple infections remains poorly understood. Here, we present a mathematical model that describes the dynamics of viral, target cell, and multiply infected cell subpopulations during HIV infection. Model calculations reproduce several experimental observations and provide key insights into the influence of multiple infections on HIV dynamics. We find that the experimentally observed scaling law, that the number of cells coinfected with two distinctly labeled viruses is proportional to the square of the total number of infected cells, can be generalized so that the number of triply infected cells is proportional to the cube of the number of infected cells, etc. Despite the expectation from Poisson statistics, we find that this scaling relationship only holds under certain conditions, which we predict. We also find that multiple infections do not influence viral dynamics when the rate of viral production from infected cells is independent of the number of times the cells are infected, a regime expected when viral production is limited by cellular rather than viral factors. This result may explain why extant models, which ignore multiple infections, successfully describe viral dynamics in HIV patients. Inhibiting CD4 down-modulation increases the average number of infections per cell. Consequently, altering CD4 down-modulation may allow for an experimental determination of whether viral or cellular factors limit viral production.