Developing novel deep sequencing techniques for studying HIV evolution

描述（由申请人提供）：开发适合治疗特定病原体的治疗方法的主要障碍之一是它们在治疗干预(1)下发生突变和进化的能力，包括抗生素耐药细菌的出现，每年的流感菌株和人类免疫缺陷病毒（HIV）菌株对高活性抗逆转录病毒治疗（HAART）的效果产生耐药性。全世界有3800万人感染艾滋病毒，了解这种病毒如何变异和产生耐药性对于设计成功的治疗方法非常重要。这项提议的中心目标是分析HIV群体如何随着时间的推移而对进化压力做出反应，在这种情况下是RNA反义疗法。这项研究将使用新的“下一代”DNA测序方法，因为它们可能产生近乎完全覆盖临床样本中存在的HIV基因组。具体来说，我将用慢病毒载体VRX496”对治疗前后的HIV准种群体进行测序，该载体编码一个针对HIV包膜的反义序列，使我能够研究治疗干预对HIV进化的影响。此外，这些结果将使我能够开发准物种随时间进化的计算种群遗传学模型。由此产生的数据和模型将来可能有助于设计对艾滋病毒感染者更有效的治疗方法。本提案的实验部分将在Dr. David Schaffer（发起人）的实验室进行，并与Dr. Arkin的实验室合作进行计算建模，用于分析的临床样本将从VIRxSYS公司获得。目的1。为了确定一种无偏测序方法的发展是否能产生100万倍的HIV基因组覆盖率。目标2。确定下一代测序是否可以应用于阐明HIV在选择性压力下的进化机制-特别是基于慢病毒的反义治疗。目标3。以确定是否一个准确的计算模型的艾滋病毒准种进化响应选择压力可以开发。

DESCRIPTION (provided by applicant): 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. PUBLIC HEALTH RELEVANCE: 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.