In Vivo Validation of a Bioinformatics Based Tool to Identify Reduced Replication Capacity in HIV-1

Abstract

Although antiretroviral drug resistance is common in treated HIV infected individuals, it is not a consistent indicator of HIV morbidity and mortality. To the contrary, HIV resistance-associated mutations may lead to changes in viral fitness that are beneficial to infected individuals. Using a bioinformatics-based model to assess the effects of numerous drug resistance mutations, we determined that the D30N mutation in HIV-1 protease had the largest decrease in replication capacity among known protease resistance mutations. To test thisin silicoresult in anin vivoenvironment, we constructed several drug-resistant mutant HIV-1 strains and compared their relative fitness utilizing the SCID-hu mouse model. We found HIV-1 containing the D30N mutation had a significant defectin vivo, showing impaired replication kinetics and a decreased ability to deplete CD4+ thymocytes, compared to the wild-type or virus without the D30N mutation. In comparison, virus containing the M184V mutation in reverse transcriptase, which shows decreased replication capacityin vitro, did not have an effect on viral fitnessin vivo. Thus, in this study we have verified anin silicobioinformatics result with a biological assessment to identify a unique mutation in HIV-1 that has a significant fitness defectin vivo.