In the first part of the talk we will introduce a mathematical model addressing the origin of universal dynamics of sequence divergence and diversity during chronic phase of HIV infection. The prediction of the model was examined by performing phylogenetic analysis to estimate the change in the rate of evolution during infection. In agreement with our modeling, in 13 out of 15 patients (followed for 3-12 years) we found that the rate of intrahost HIV-1 evolution was not constant, but rather slowed down at a rate correlated with the rate of CD4+ T-cell decline.
Second part of the talk focuses on very early stage of infection. Starting from a single variant of infected cell's proviral DNA, we explicitly simulated random mutations in the population of exponentially growing infected cells. With previous estimates of a single cycle error rate of reverse transcriptase, viral generation time, and basic reproductive ratio, we classified a single strain infection from multiple variant infection and estimated days post infection from detailed comparisons of the model to 3,499 complete envelope genes derived by single genome amplification from 102 subjects with acute HIV-1 (clade B) infection.