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

病毒基因序列代表着丰富而有价值的生物学信息来源 流程。近十年来下一代测序技术的进展 现在提供了前所未有的机会来探索病毒种群的多样性和进化 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NGS在分析病毒种群方面的优势，包括大大减少误判- 由前面的PCR步骤引入的并入和重组，减少了 测序平台，揭示初始病毒基因组/模板的采样深度 在最终数据集中实际表示的数据。在此应用程序中，我们将使用最先进的 NGS将在病毒背景下解决艾滋病毒-1人群分析中的长期问题 在缺乏治疗的情况下的进化，微小变异在预测治疗失败中的作用 治疗上的潜在蓄水池是否在复制。此外，我们将链接我们的序列数据 进行最先进的进化分析，并通过以下方式确认我们的推断的关键方面 改变病毒表型和宿主环境的措施。在目标1中，我们将分析 27名艾滋病毒感染妇女(来自WIHS队列)的纵向血浆样本，从 高的CD4+T细胞计数，直到进展到低于100个/微升的CD4+T细胞计数。 将进行多路NGS测序，以获得接近全长的HIV-1基因组序列。 我们预测，病毒群体中的X4变异体首先出现在低丰度的情况下，我们将 能够比之前观察到的更早地发现它们，并跟踪它们的演变。在……里面 此外，我们将调查所有测序区域的纵向病毒多样性变化，以 评估人群动态并将这些变化与炎症、中枢神经系统损伤等标志物联系起来， CTL反应，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 治疗失败了。我们假设耐药突变的潜在性 转义可能发生在次要变体中，这些变体太小，无法使用 到目前为止已经被使用了。我们将分析来自四个队列(马拉维和中国)的样本 通过使用Sanger测序来确定遗漏次要变量的频率。然后我们将链接 1例耐药突变导致治疗失败，治疗前其含量丰富- 控制设计。在目标3中，我们将使用水库病毒的近全长基因组测序 (生长或反弹)13名感染单一变种和 很早就开始治疗了。治疗方面的潜在进展将包括对现有CTL的关注 回应。通过这种方式，我们将提供作为病毒签名的序列进化的关键测试 在多年成功的抑制疗法中进行复制。通过此应用程序，我们可以 在缺乏治疗的情况下，检查对理解艾滋病毒-1至关重要的问题 面临着抗逆转录病毒药物的选择，以及成功的治疗。对每一项的见解 这些问题可以首先通过适当使用NGS测序来解决，但在 解释这些平台的优势和劣势的方法。高质量序列 然后，信息引导对病毒进化的洞察，以响应宿主的变化 对药物选择的反应，以及对明显的抑制治疗的反应。

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.