Integrative Single-Cell Analysis of Transcriptome, Epigenome, and Lineage in HIV Latency and Activation

摘要 随着三联抗逆转录病毒疗法的发展，常规艾滋病毒治疗几乎消除了所有 活跃的感染细胞尽管如此，潜伏感染细胞的小水库，可以保持休眠状态， 在变得活跃并产生新的病毒颗粒之前的很长一段时间，是一个关键的屏障， 彻底治愈疾病。鉴定可识别潜伏感染细胞或生化因子的标记物 控制潜伏期激活可以有效地使用"休克和杀死"策略， 或激活潜伏感染的细胞消除了病毒库。我们最近的研究表明， 造血分化过程中的转录组和表观基因组变化影响病毒潜伏期和激活。 此外，我们最近发现，组蛋白去乙酰化酶活性的全面抑制增加了病毒的激活， 这些细胞，进一步暗示活化中的表观基因组变化。这些结果提出了一些基本问题： 潜伏感染细胞的标志物是什么？细胞的转录组和表观基因组状态如何影响 延迟和激活？分化状态与病毒潜伏期有何关系？在这里，我们利用我们的实验 用于鉴定潜伏和活跃感染细胞的平台，单细胞转录组和表观基因组测序， 以及我们最近开发的计算积分方法来研究这些问题。我们 跨学科团队结合了艾滋病毒基础科学、艾滋病毒临床治疗和生物信息学方面的专业知识， 开发一个实验和计算框架，用于整合基因表达，染色质可及性， 和谱系的一个单一的图片病毒潜伏期和激活。具体而言，该项目将（1）使用单细胞 RNA-seq和单细胞ATAC-seq，以绘制感染细胞的多样性，（2）研究 造血分化状态和病毒活化;（3）通过单细胞确定病毒整合位点 RNA-seq，（4）计算整合单细胞转录组和表观基因组谱，以及（5）计算整合 推断病毒基因组和感染细胞之间的细胞谱系关系。为了实现这些目标，我们将 目的：（1）研究单潜伏期和多潜伏期植物的谱系、转录组和表观基因组多样性， 活跃感染的原代细胞(2)研究体外分化过程中的潜伏期和激活。(3)调查 来自cART抑制患者的再活化和体外感染细胞的单细胞多样性。所有这些 目的是制作一个全面的，综合的转录组学和表观基因组图谱的艾滋病毒水库，确定 潜伏期的DNA和RNA生物标志物，并表征克隆扩增模式。我们的工作还开发了一个 广泛适用的实验和计算框架，为发现新的 深入了解艾滋病毒的潜伏期和激活。

Abstract With the development of triple combination antiretroviral therapy, routine HIV treatment eliminates nearly all actively infected cells. Nevertheless, the small reservoir of latently infected cells, which can remain dormant for long periods of time before becoming active and producing new virus particles, represents a crucial barrier to completely curing the disease. Identifying markers that identify latently infected cells or the biochemical factors that control latency activation could enable the effective use of a “shock and kill” strategy, where specific targeting or activation of latently infected cells eliminates the viral reservoir. Our recent work suggests that the global transcriptomic and epigenomic changes during hematopoietic differentiation affect viral latency and activation. Additionally, we recently found that global inhibition of histone deacetylase activity increases viral activation in these cells, further implicating epigenomic changes in activation. These results raise fundamental questions: What are the markers of latently infected cells? How do the transcriptomic and epigenomic state of a cell affect latency and activation? How does differentiation state relate to viral latency? Here, we leverage our experimental platform for identifying latently and actively infected cells, single cell transcriptome and epigenome sequencing, and our recently developed computational integration methods to investigate these questions. Our interdisciplinary team combines expertise in HIV basic science, HIV clinical treatment, and bioinformatics to develop an experimental and computational framework for integrated gene expression, chromatin accessibility, and lineage into a single picture of viral latency and activation. Specifically, this project will (1) use single-cell RNA-seq and single-cell ATAC-seq to map diversity of infected cells, (2) investigate the relationship between hematopoietic differentiation state and viral activation, (3) determine viral integration sites through single-cell RNA-seq, (4) computationally integrate single cell transcriptome and epigenome profiles, and (5) computationally infer cell lineage relationships among viral genomes and infected cells. To accomplish these goals, we will carry out the following aims: (1) Characterize lineage, transcriptomic and epigenomic diversity of single latently and actively infected primary cells. (2) Investigate latency and activation during in vitro differentiation. (3) Survey single cell diversity of re-activated and in vitro infected cells from cART-suppressed patients. Together, these aims will produce a comprehensive, integrated transcriptomic and epigenomic atlas of the HIV reservoir, identify DNA and RNA biomarkers of latency, and characterize clonal expansion patterns. Our work also develops a broadly applicable experimental and computational framework, laying a foundation for the discovery of novel insights into HIV latency and activation.