HIV Evolution Defines Virus-Host/Drug Interactions In Viremic and Aviremic People

病毒基因序列代表了生物信息的丰富和有价值的来源， 流程.下一代测序（NGS）技术在过去十年中的进展 现在提供了前所未有的机会来探测病毒种群的多样性和进化 的方式我们开发了专门的测序策略来克服几个严重的限制 传统的NGS在分析病毒种群，包括大大减少错误， 通过前面的PCR步骤引入的掺入和重组，减少了 测序平台，并揭示初始病毒基因组/模板的采样深度 最终的数据集里的数据。在这个应用程序中，我们将使用最先进的 NGS将解决在病毒背景下艾滋病毒-1人群分析中的长期问题 缺乏治疗的演变，微小变异在预测治疗失败中的作用，以及 治疗过程中的潜在储存库是否在复制此外，我们将把我们的序列数据 最先进的进化分析，并确认我们推论的关键方面， 改变病毒表型和宿主环境。在目标1中，我们将分析 来自27名HIV感染女性（来自WIHS队列）的纵向血浆样本， 高CD 4 + T细胞计数，直至CD 4 + T细胞计数低于100个细胞/微升。我们 将进行多重NGS测序，以获得接近全长的HIV-1基因组序列。 我们预测，X4变异体在病毒群体中首先以低丰度出现， 能够比以前观察到的更早地发现它们，并跟踪它们的演变。在 此外，我们将研究所有测序区域的纵向病毒多样性变化， 评估种群动态，并将这些变化与炎症，CNS损伤， CTL应答以及中和抗体的广度和效力。在目标2中，我们将应用 多重NGS测序作为预测微小耐药变异的筛选工具 治疗失败我们假设，耐药突变介导 逃逸可能发生在微小的变异体上，微小的变异体太小而不能用 至今仍在使用。我们将分析来自四个队列（马拉维和中国）的样本， 通过使用桑格测序确定微小变异被遗漏的频率。然后我们将链接 在一个病例中，耐药突变导致治疗失败，且其治疗前含量丰富- 控制设计在目标3中，我们将使用储库病毒的近全长基因组测序 （无论是生长或反弹）在13名参与者谁感染了一个单一的变种， 很早就开始治疗了治疗的潜在进展将包括关注现存的CTL 应答通过这种方式，我们将提供一个关键的测试序列进化作为一个签名的病毒 在多年成功的抑制治疗中复制。有了这个应用程序， 在没有治疗的情况下，检查对理解HIV-1至关重要的问题， 面临抗逆转录病毒药物的选择，以及成功的治疗。深入了解 这些问题首先可以通过适当使用NGS测序来解决， 说明这些平台的优势和劣势的方式。高质量序列 然后，信息引导我们深入了解病毒对不断变化的宿主的反应， 对药物选择的反应，以及对明显抑制性治疗的反应。

Viral gene sequences represent a rich and valuable source of information about biological processes. Advances in next generation sequencing (NGS) technology over the past decade now provide the opportunity to probe viral population diversity and evolution in unprecedented ways. We developed specialized sequencing strategies to overcome several serious limitations of conventional NGS in analyzing viral populations, including greatly reducing the mis- incorporation and recombination introduced by the preceding PCR step, reducing the errors of the sequencing platform, and revealing sampling depth of the initial viral genomes/templates that are actually represented in the final data set. In this application we will use state-of-the-art NGS to address long-standing issues in HIV-1 population analysis in the context of viral evolution in the absence of therapy, the role of minor variants in predicting failed therapy, and whether the latent reservoir on therapy is replicating. In addition, we will link our sequence data to state-of-the-art evolutionary analysis, and confirm key aspects of our inferences with measures of changing viral phenotypes and host environment. In Aim 1, we will analyze longitudinal plasma samples from 27 HIV-infected women (from the WIHS cohort) starting with high CD4+ T cell counts until they progress to CD4+ T cell counts of less than 100 cells/µL. We will perform multiplexed NGS sequencing to obtain near full length HIV-1 genome sequences. We predict that X4 variants in viral populations first emerge at low abundance and that we will be able to detect them much earlier than previously observed and follow their evolution. In addition, we will investigate longitudinal viral diversity changes in all sequenced regions to assess population dynamics and link these changes to markers of inflammation, CNS damage, CTL response, and the breadth and potency of neutralizing antibodies. In Aim 2, we will apply multiplexed NGS sequencing as a screening tool for minor drug resistance variants that predict therapy failure. We hypothesize that the potential for drug resistance mutations to mediate escape can occur from minor variants, too minor to be reliably detected with the methods that have been used to date. We will analyze samples from four cohorts (Malawi and China) to determine how often minor variants are missed by using Sanger sequencing. We will then link resistance mutations leading to therapy failure with their pretherapy abundance in a case- control design. In Aim 3, we will use near full length genome sequencing of reservoir virus (either outgrowth or rebound) in 13 participants who were infected with a single variant and started therapy early. Potential evolution on therapy will include a focus on extant CTL responses. In this way we will provide a critical test of sequence evolution as a signature of viral replication during years of successful suppressive therapy. With this application we are examining questions that are central to understanding HIV-1 in the absence of therapy, when faced with the selection of antiretroviral drugs, and on successful therapy. Insights into each of these questions can be first approached with the appropriate use of NGS sequencing but in ways that account for the strengths and weaknesses of these platforms. High quality sequence information then leads the way to insights in viral evolution in response to a changing host, in response to drug selection, and in response to apparently suppressive therapy.