Genetic aspects of HIV-1 evolution and transmission

HIV-1 is one of the fastest evolving organisms known to man. Its rate of evolution is approximately one million times faster than that of higher organisms such as ourselves, meaning that the amount of changes within the HIV-1 genome in just one year corresponds to the amount of changes within the human genome in one million years. The reason for this remarkable property of HIV-1 is its high amount of genetic variation, created by the rapid substitution introduction, fast generation time, vast number of viral particles produced per unit of time, and various selection forces. As a consequence, an HIV-1 population within a person consists of a large number of genetically related but non-identical viruses, a population structure that gives this pathogen an opportunity of rapid adaptation to changes in its environment. Viral escape variants quickly evolve as a response to the pressure of the human immune system or antiretroviral treatment assuring survival of the virus. In addition, the great genetic variability of HIV-1, both within a person and on the host population level, makes development of an effective vaccine a difficult and complicated task. These issues make studies on HIV-1 evolution and genetic variation highly relevant. This thesis examines different genetic aspects of HIV-1 evolution within a patient and in transmission events. Prevalence of transmission of drug resistant HIV-1 in Sweden was investigated by analyzing pol gene sequences, derived from 100 newly infected and treatment naïve patients, for known resistance mutations. Mutations associated with high and intermediate level of resistance were found in 7 patients suggesting transmission of resistant viral variants. Mutations associated with low or unclear level of resistance were observed to occur at different frequencies in different subtypes. These subtype-specific patterns suggest the existence of different evolutionary paths that HIV-1 can take to develop drug resistance. Phylogenetic analyses of viral clones and isolates from two HIV-1 infected mother-child pairs revealed the origin of X4 viruses in the children. Although the mothers carried X4 variants at the time of transmission, these were shown not to be the source of X4 variants in the children. Instead, child X4 viruses had evolved from child R5 viruses present early in infection. The initial R5 viruses in the children were correlated to maternal R5 variants that co-existed with maternal X4 at the time of transmission. Viral phylogenies inferred from HIV-1 sequences derived from 10 patients belonging to a known HIV-1 transmission chain correctly reconstructed the epidemiological events from the chain, except for two of the transmissions and few of the sampling events. The few discrepancies were, however, explained by the existence of hidden viral lineages, that could make the epidemiological and virus trees completely compatible. In addition, the effect of hidden viral lineages could mislead the reconstruction of the root and the sequence evolutionary rate, indicating their importance in phylogenetic analyses of HIV-1 sequences. We developed a fast and simple method for optimization of the root and evolutionary rate using samples from at least two different time points in a phylogenetic tree. The method had no bias and the estimation of an accurate evolutionary rate was possible even in cases where there was an error in the root and where the tree topologies were incorrectly reconstructed. Hence, the method is robust and thus suitable for rate estimations in real situations where the correct root and topology of a tree are usually unknown. By analyzing HIV-1 sequences from different epidemics throughout the world we observed that the rate of evolution of HIV-1 on the population level depends on its rate of spread. The virus spreading rapidly in IDU standing social networks had significantly lower rate of evolution than the virus spreading more slowly through heterosexual contacts. In addition, viruses in mixed epidemics, spreading both slow and fast, showed an intermediate evolutionary rate. Epidemiological modeling predicted that the rate of evolution of HIV-1 spreading in a rapid manner will increase as the epidemic ages and the population gets saturated with infections