Role of Virus Recombination in Multiple Drug Resisitance

点击翻译按钮获取中文摘要

DESCRIPTION (provided by applicant): Human immunodeficiency virus (HIV) infection ranks among the top five causes of death globally and presents a major threat to public health. By using antiretroviral drug combination (Highly Active Antiretroviral Therapy), HAART has been effective in dramatically reducing HIV-related mortality and morbidity. However, nearly half of HIV-infected patients still fail HAART. Although genetic analyses of viral genomes from these patients show multiple-drug resistance mutations in the pol gene, the molecular mechanisms for the emergence of drug-resistance are not yet known. Therefore, it is important to delineate the mechanisms for multiple-drag resistance in order to more efficiently control HIV infection. Here, we propose to study the role of viral recombination in generation of multiple-drug resistance during HAART. We have established a prospective clinical cohort and developed methods to analyze recombinant viral genomes within an infected individual. Specific aims of this proposal are: (i) We will genetically characterize the baseline viral population and determine their predictive values for treatment failure by sequencing multiple clones from each patient before HAART treatment. (ii) To determine the role of recombination in generation of multiple-drug resistance, we will compare the drug-resistant viral population with the baseline viral population and identify recombinant genomes and recombinant index increase of the viral population from patients who fail HAART. (iii) We will obtain viral populations before and after each treatment failure in the consecutive HAART regimes and analyze the dynamic changes of viral populations to determine mechanisms of repeated drug-resistance and fitness of drug-resistance viruses. Understanding the viral population changes, drug-resistance mechanisms and viral fitness during HAART will allow for the development of more effective antiretroviral agents, better treatment regimens and accurate prediction of treatment efficacy. Knowledge obtained from this study can be broadly applied toward understanding mechanisms of viral escape from immune surveillance and other selective forces.