Single-Cell Transcriptomics of Non-Activated Latently Infected T cells Isolated from HIV+ Drug Users

从HIV+药物中分离的非活化潜伏感染T细胞的单细胞转录本 用户 阿片类药物的使用改变了大脑的表观遗传结构，但它对CD4+记忆T细胞的影响， 潜伏的HIV-1，仍然未知。该应用的中心假设是记忆T细胞的身份 携带潜伏的HIV-1的患者因阿片类药物暴露而改变，因此， 阿片类药物的使用将是有价值的。这一假设是根据已发表的结果制定的，这些结果表明阿片类药物 受体在CD4 + T细胞上表达，通过这些受体的信号传导调节T细胞活化， 分化中心假设将以高度里程碑驱动的双管齐下的方法进行检验。在 创新阶段（R61），我们的目标将优化两个必要的技术：1）Tracker-Cas9-Q，一种新的CRISPR- 基于体内DNA标记技术以可视化潜伏感染的T细胞，和2）单细胞RNA测序 和相关的计算分析，用于稳健的生物标志物开发。目的1：标记HIV-1前病毒 通过利用新型CRISPR-Cas蛋白质技术，Tracker-Cas9-Q是一种新的 催化失活的CRISPR/Cas9和特异性CRISPR/Cas9的荧光标记但内部淬灭的复合物， CRISPR向导RNA仅在DNA结合时发荧光（Murthy Lab）。潜在的工作假设 在纳米金微粒（CRISPR-Gold）内递送的Tracker-Cas9-Q允许有效的体内标记 和含有潜伏HIV DNA的T细胞系的流式分选。目的2：建立单细胞RNA-Seq， 在用双荧光HIV-1离体感染的原代T细胞中的计算生物标志物鉴定， 没有阿片类药物单个细胞的转录组-单独或在复杂的细胞群体中-现在可以 在足够的深度（Ott Lab）进行分析，以允许在HIV感染的原代细胞中开发可靠的生物标志物 （Yosef Lab）。我们的工作假设是，个体潜伏感染的原代T细胞可以被 使用RNA-Seq在单细胞基础上有效分离和分析。为了进入R33阶段， 在R61期结束时，我们将开发出一种高效递送的HIV特异性DNA标记系统 （> 50%）和可分选的荧光强度，并建立了单细胞RNA-Seq和计算平台 用于生物标志物的开发。R33阶段的一个目标是将目标1和目标2的实验系统结合起来， 2在从抗逆转录病毒治疗下的病毒血症HIV+个体分离的原代T细胞中。目标3：定性 在单细胞水平上潜伏感染的记忆T细胞，从有和没有阿片类药物的HIV+个体中分离 使用新的基于CRISPR的标记技术。我们的工作假设是， Tracker-Cas9-Q和CRISPR-Gold技术将有效标记患者来源的T细胞中的潜伏前病毒， 并结合单细胞RNA-Seq和计算生物标志物分析，将产生基本的新见解 在使用和不使用阿片类药物的HIV+个体中潜伏储库细胞的身份。我们的研究将有助于 我们将从根本上的新技术和可翻译的生物学知识应用于阿片类药物使用者艾滋病毒潜伏期的研究。

SINGLE-CELL TRANSCRIPTOMICS OF NON-ACTIVATED LATENTLY INFECTED T CELLS ISOLATED FROM HIV+ DRUG USERS Opioid use alters the epigenetic structure of the brain but its effects on CD4+ memory T cells, the main reservoir for latent HIV-1, remain unknown. The central hypothesis of this application is that the identity of memory T cells carrying latent HIV-1 is altered by opioid exposure, and thus, identifying specific biomarkers in patients with opioid use would be valuable. This hypothesis was formulated based on published results showing that opioid receptors are expressed on CD4+ T cells and signaling through these receptors modulates T-cell activation and differentiation. The central hypothesis will be tested in a two-pronged, highly milestone-driven approach. In the innovation phase (R61), our aims will optimize two necessary technologies: 1) Tracker-Cas9-Q, a new CRISPR- based in vivo DNA-labeling technique to visualize latently infected T cells, and 2) single-cell RNA sequencing and associated computational analysis for robust biomarker development. Aim 1: To label the HIV-1 proviral locus in intact cells by harnessing novel CRISPR-Cas protein technologies. Tracker-Cas9-Q is a new fluorescently labeled, but internally quenched, complex of catalytically inactive CRISPR/Cas9 and specific CRISPR guide RNAs that only fluoresces upon DNA binding (Murthy Lab). The underlying working hypothesis is that Tracker-Cas9-Q delivered within nanogold microparticles (CRISPR-Gold) allows efficient in vivo labeling and flow sorting of T cell lines containing latent HIV DNA. Aim 2: To establish single-cell RNA-Seq and computational biomarker identification in primary T cells ex vivo infected with dual-fluorescent HIV-1 with and without opioid exposure. The transcriptome of individual cells – alone or in complex cell populations – can now be analyzed at sufficient depth (Ott Lab) to allow reliable biomarker development in HIV-infected primary cell populations (Yosef Lab). Our working hypothesis is that individual latently infected primary T cells can be efficiently isolated and analyzed on a single-cell basis using RNA-Seq. In order to progress to the R33 phase, at the end of the R61 period we will have developed an HIV-specific DNA labeling system with efficient delivery (>50%) and sortable fluorescence intensities and established single-cell RNA-Seq and computational platforms for biomarker development. The R33 phase has one aim combining the experimental systems from Aims 1 and 2 in primary T cells isolated from aviremic HIV+ individuals under antiretroviral therapy. Aim 3: To characterize latently infected memory T cells at the single-cell level, isolated from HIV+ individuals with and without opioid use, using novel CRISPR-based labeling techniques. Our working hypothesis is that the newly developed Tracker-Cas9-Q and CRISPR-Gold technologies will efficiently label the latent provirus in patient-derived T cells, and combined with single-cell RNA-Seq and computational biomarker analysis, will yield fundamental new insight into the identity of latent reservoir cells in HIV+ individuals with and without opioid use. Our studies will contribute fundamentally new technologies and translatable biological knowledge to the study of HIV latency in opioid users.