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，常规的艾滋病毒治疗几乎消除了所有 被活跃感染的细胞。然而，潜伏感染细胞的小水库，可以保持休眠 在变得活跃并产生新的病毒颗粒之前的很长一段时间，是 彻底治愈了这种疾病。识别识别潜伏感染细胞或生化因素的标记 这种控制潜伏期的激活可以有效地使用“电击和杀死”策略，其中特定的靶向 或者，潜伏感染细胞的激活消除了病毒库。我们最近的研究表明，全球 在造血分化过程中，转录和表观基因组的改变会影响病毒的潜伏期和激活。 此外，我们最近发现，组蛋白脱乙酰酶活性的全局抑制增加了病毒在 这些细胞，进一步暗示了表观基因组的激活变化。这些结果提出了一些根本性的问题： 潜伏感染细胞的标志物是什么？细胞的转录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 识别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， 我们最近开发的计算积分方法来研究这些问题。我们的 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，以 为整合基因表达、染色质可及性、 和血统形成了病毒潜伏和激活的单一图景。具体地说，本项目将(1)使用单细胞 Rna-seq和单细胞atac-seq来定位感染细胞的多样性，(2)研究 造血分化状态和病毒激活；(3)通过单细胞确定病毒整合部位 RNA-seq，(4)计算整合单细胞转录组和表观基因组图谱，以及(5)计算 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 主要研究内容如下：(1)研究了潜伏性和表观基因组的遗传多样性。 被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期。(3)调查 CART抑制患者再激活和体外感染细胞的单细胞多样性。加在一起，这些 AIMS将制作一份全面的、综合的艾滋病毒宿主的转录和表观基因组图谱，确定 潜伏期的DNA和RNA生物标记物，并表征克隆扩展模式。我们的工作还开发了一种 广泛适用的实验和计算框架，为发现新的 对艾滋病毒潜伏期和激活的洞察。

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.