Predominance of positive epistasis among drug resistance-associated mutations in HIV-1 protease

Author summary Antiretroviral drugs have achieved great success in controlling the HIV pandemic. However, the therapy fails sometimes owing to the low drug adherence and/or the emergence of resistance associated mutations on viral genome. The persistence of drug resistance poses challenges in using antiretroviral drugs for long term control or pre-exposure prophylaxis. To understand the mechanisms of resistance evolution and persistence, we profiled the replication fitness of over 1000 HIV-1 mutants with combinations of resistance associated mutations on its protease gene. We found that although resistance associated mutations greatly reduce replication fitness, they interact positively to alleviate the mutational load. These genetic interactions, termed epistasis, increase the ruggedness along the evolution paths, restricting resistance associated mutations from reversal. Our data support the clinical observations that drug resistance mutations tend to persist even when antiretroviral drug is discontinued. Drug-resistant mutations often have deleterious impacts on replication fitness, posing a fitness cost that can only be overcome by compensatory mutations. However, the role of fitness cost in the evolution of drug resistance has often been overlooked in clinical studies or in vitro selection experiments, as these observations only capture the outcome of drug selection. In this study, we systematically profile the fitness landscape of resistance-associated sites in HIV-1 protease using deep mutational scanning. We construct a mutant library covering combinations of mutations at 11 sites in HIV-1 protease, all of which are associated with resistance to protease inhibitors in clinic. Using deep sequencing, we quantify the fitness of thousands of HIV-1 protease mutants after multiple cycles of replication in human T cells. Although the majority of resistance-associated mutations have deleterious effects on viral replication, we find that epistasis among resistance-associated mutations is predominantly positive. Furthermore, our fitness data are consistent with genetic interactions inferred directly from HIV sequence data of patients. Fitness valleys formed by strong positive epistasis reduce the likelihood of reversal of drug resistance mutations. Overall, our results support the view that strong compensatory effects are involved in the emergence of clinically observed resistance mutations and provide insights to understanding fitness barriers in the evolution and reversion of drug resistance.