One of the major obstacles to developing suitable therapies for the treatment of specific pathogens is their ability to mutate and evolve in response to therapeutic intervention (1), including the emergence of antibiotic- resistant bacteria, yearly strains of influenza, and human immunodeficiency virus (HIV) strains that become resistant to the effects of highly active antiretroviral therapy (HAART). With 38 million people infected with HIV worldwide, it is important to understand how this virus mutates and develops resistance in order to design successful therapies. The central objective of this proposal is to analyze how populations of HIV mutate over time in response to evolutionary pressure, in this case an RNA antisense therapy. This study will use novel """"""""next generation"""""""" DNA sequencing methods because they may generate near-complete coverage of the HIV genomes present in clinical samples. Specifically, I will sequence the HIV quasispecies population both before and after treatment with the lentiviral vector VRX496"""""""", which encodes an antisense sequence that targets the envelope of HIV, allowing me to study the impact of therapeutic intervention on HIV evolution over time. Furthermore, the results will enable me to develop a computational, population genetics model of quasispecies evolution over time. The resulting data and model may in the future aid the design of more effective treatments for people infected with HIV. The experimental portion of this proposal will be performed in the lab of Dr. David Schaffer (sponsor) with collaboration from Dr. Arkin's lab for computational modeling, and clinical samples used for analysis will be obtained from the VIRxSYS corporation.
Aim 1. To determine whether the development of an unbiased sequencing method can yield >10,000x coverage of the HIV genome.
Aim 2. To determine whether next generation sequencing can be applied to elucidate mechanisms of HIV evolution in response to a selective pressure - specifically a lentiviral-based antisense therapy.
Aim 3. To determine if an accurate computational model of HIV quasispecies evolution in response to a selective pressure can be developed.
An estimated 38 million people worldwide are currently infected with HIV with an additional 4.1 million people becoming infected each year. There is a compelling need to develop alternative therapies for the treatment of HIV due to the limitations of HAART, and this work will yield deep insights into viral responses to a new lentiviral-based antisense therapy. Additionally, the general methods described in this work will be applicable to studying other highly heterogeneous, rapidly evolving viral populations, such as influenza, West Nile virus, Ebola, and others.
