Single cell RNA-seq and single molecule RNA-FISH approaches to study stochasticity of latent HIV-1 reactivation

持久性蓄水池是治愈HIV-1病毒的终极障碍。消灭艾滋病毒的“杀戮”战略-- 1水库需要用潜伏期反转剂(LRA)重新激活所有潜伏期前病毒，目前 不可能。用QVOA(定量病毒生长分析)定量检测患者来源的潜伏病毒 结果表明，只有约1/60%的全长复制能力潜伏前病毒被LRA激活。原因 因为这种差异并不完全被理解，但已被归因于不同的表观遗传调控 前病毒(由于前病毒整合的不同位置)，病毒基因组的差异(遗传变异性)， 患者细胞因子的差异表达或不同的转录或转录后阻断- 衍生的潜伏细胞。在ExVivo和细胞培养模型中，单个病毒克隆用于感染 没有遗传异质性，只有一小部分细胞重新激活，表达水平不同 病毒RNA和蛋白质的变化表明在重新激活过程中细胞之间存在差异。这些研究还显示， 目前的方法并不能激活大多数的潜伏细胞。当前的策略没有解决小区到小区的问题 前病毒激活的变异和了解体内的这种变异对于实现以下两个方面的完全 重新激活或完全抑制这些储集层。 这个应用程序的目标是利用创新的单细胞和多组学平台来研究 在单细胞水平上以比以往更高的精度和更高的分辨率研究艾滋病毒持续存在的机制 以前使用传统技术实现的。基于Stellaris的定量单分子RNA-FISH (smRNA-FISH)，它允许更高的分辨率和对RNA分子数量的精确定量 在单细胞内，已被用于研究真核基因转录的随机性。我们已经申请了 SmRNA-FISH结合免疫荧光技术称为SmirA(单细胞、单分子免疫荧光技术) 在潜伏期模型中研究HIV-1的重新激活并对单个RNA分子进行定量 使用一种计算算法FISH-QUANT。此外，我们还高速地结合了这些研究 并用高分辨率扫描显微镜鉴定罕见阳性细胞/S在大量阴性细胞池中。 使用这些方法，我们的目标是量化潜伏细胞中细胞间的可变性。我们的假设是细胞- HIV-1重新激活对细胞的影响既有“内在”因素，也有“外在”因素。通过将单细胞和 单细胞rna测序的单分子方法(scRNA-seq) 导致HIV-1重新激活变化的决定因素，并扩大这些研究以确定这些 病人样本中的标志物。在目标一中，我们将描述并确定所涉及的基因和途径 在随机激活的HIV-1潜伏细胞中使用Smira、HSHRS和RNA-seq分析。在AIM II中， 我们将在以下模型中验证确定的影响HIV-1随机激活的基因和途径 潜伏期和ART抑制的患者样本中。我们的分析将确定新的基因和途径， 影响HIV-1重新激活的细胞间变异性，并最终将导致新疗法的开发 以对抗HIV-1潜伏期。

The persistent reservoirs are the ultimate hurdle to HIV-1 cure. ‘Shock and Kill’ strategy to eliminate HIV- 1 reservoirs requires reactivation of all latent proviruses with latency reversing agents (LRA), which is currently not possible. Quantitation of patient derived latent reservoirs by QVOA (Quantitative Viral Outgrowth Assay) indicated that only ~1/60th of full-length replication competent latent proviruses are activated by LRA. The reason for this variability is not completely understood but has been attributed to differential epigenetic regulation of provirus (due to different sites of proviral integration), differences in the viral genome (genetic variability), differential expression of cellular factors or different transcriptional or post-transcriptional blocks in the patient- derived latent cells. In the ExVivo and cell culture models of latency, where a single viral clone is used for infection with no genetic heterogeneity, reactivation of only a small percentage of cells and different levels of expression of viral RNA and proteins indicate cell-to-cell variation in reactivation. These studies also revealed that the majority of latent cells are not activated by current approaches. Current strategies do not address cell-to-cell variation in proviral reactivation and understanding this variability in vivo is essential to achieve either full reactivation or full suppression of these reservoirs. The goal of this application is to employ innovative single-cell and multi-omics platforms to investigate mechanisms of HIV persistence at the single-cell level with greater precision and higher resolution than has been achieved previously using traditional techniques. Stellaris-based quantitative single molecule RNA-FISH (smRNA-FISH), that allows the greater resolution and precise quantitation of the number of RNA molecules within single cells, have been used to study stochasticity in eukaryotic gene transcription. We have applied smRNA-FISH combined with Immunofluorescence (IF) termed SMIRA (Single cell and single molecule IF and RNA-FISH based Assay) to study HIV-1 reactivation in latency models and quantitated the single RNA molecules using FISH-quant, a computational algorithm. In addition, we have combined these studies with a high speed and high resolution scanning (HSHRS) microscopy to identify rare positive cell/s in a large pool of negative cells. Using these methods, our goal is to quantitate the cell-to-cell variability in latent cells. Our hypothesis is that cell- to-cell variation in HIV-1 reactivation is due to both ‘intrinsic’ and ‘extrinsic’ factors. By combining single cell and single molecule approaches with single cell RNA-sequencing (scRNA-seq) methodologies we propose to identify the determinants responsible for variation in the HIV-1 reactivation and extend these studies to identify these markers in patient samples. In aim I, we will characterize and determine the genes and pathways involved in the stochastic activation in HIV-1 latent cells using SMIRA, HSHRS and RNA-seq analysis. In aim II, we will validate the genes and pathways identified to influence HIV-1 stochastic activation in models of latency and in ART-suppressed patient samples. Our analyses will identify novel genes and pathways that influence cell-to-cell variability in HIV-1 reactivation and ultimately will lead to the development of novel therapies to combat HIV-1 latency.