PrimeFlow RNA for detection of latently-infected CD4+ T cells

 描述(由申请人提供)：消除潜伏感染细胞和实现功能性治愈的治疗方法的开发需要可靠和可重复地评估潜伏储存库大小的标准化分析。到目前为止，有两种方法被用来估计潜在储集层的规模。基于聚合酶链式反应的检测是快速、灵敏和可重复性的，但不区分复制能力和缺陷前病毒。相反，病毒生长分析(VOA‘s)评估了含有复制能力前病毒的细胞的频率，但这些细胞是密集的、可变的和不敏感的。一种以灵敏和可重复的方式测量潜伏感染细胞频率的方法，并且适用于高通量的单细胞平台，将是在未来的临床根除研究中测量病毒库的关键工具。PrimeFlow RNA是一种通过流式细胞术在单细胞水平上测量RNA表达的技术。我们利用这项技术开发了一种灵敏、特异和可重复性的检测HIV-1感染细胞的方法。我们已经开发了三套HIV特异性探针来检测单剪接体、多剪接体和全长HIV-1转录本。通过组合两个HIV特异的探针组，我们鉴定并浓缩了感染细胞，从最初的10-100个感染细胞/106个未感染细胞的混合物中浓缩到90%的纯度，与在体内观察到的类似。该应用程序的目标是验证PrimeFlow RNA用于临床样本中潜伏感染细胞的检测、计数和表型特征。这将通过两个具体目标来实现。具体目标1，我们将通过评估潜在储集层的大小来验证该方法。 用潜伏期反转剂和有丝分裂刺激体内病毒重新激活。我们将把这些估计与聚合酶链式反应和QVOA得到的结果进行比较。此外，我们还将进行纵向分析，测量在临床试验中登记的HIV感染者体内注射潜伏期反转剂后病毒的重新激活。PrimeFlow RNA的一个显著优点是它是一种基于流式细胞术的技术，因此可以对阳性细胞进行表型鉴定和分选。在特定的目标2中将利用 这些方面。我们将在体外病毒激活后，用PrimeFlow RNA对临床样本中感染和未感染的细胞进行分类，并利用这些细胞进行比较完整的转录组分析。此外，我们将结合PrimeFlow RNA和标准的流式细胞术，对体外病毒激活后的临床样本中感染和未感染的细胞进行细胞表面和细胞内标志物的比较分析。因此，本申请中提出的研究将实现两个主要目标。首先，他们将开发一种新的灵敏技术来测量潜在储集层的大小。其次，它们将产生关于从临床样本中获得的潜伏感染细胞生物学的新的关键信息。

 DESCRIPTION (provided by applicant): The development of therapies to eliminate latently infected cells and achieve a functional cure requires standardized assays that reliably and reproducibly assess the size of the latent reservoir. Two approaches have so far been used to estimate the size of the latent reservoir. PCR-based assays are rapid, sensitive, and reproducible, but do not discriminate between replication competent and defective proviruses. By converse, viral outgrowth assays (VOA's) assess the frequency of cells harboring replication competent provirus, but are intensive, variable, and poorly sensitive. An assay that measures the frequency of latently infected cells in a sensitive and reproducible fashion, and that is amenable to a high-throughput, single-cell platform would represent a critical tool for measuring the viral reservoir in future clinical eradication studies. PrimeFlow RNA is a technology that measures RNA expression at the single-cell level by flow cytometry. We have taken advantage of this technique to develop a sensitive, specific, and reproducible assay to detect HIV-1 infected cells. We have developed three HIV-specific probe sets to detect single-spliced, multiple-spliced, and full-length HIV-1 transcripts. By combining two HIV-specific probe sets we identified and enriched infected cells to >90% purity from initial mixtures of 10-100 infected cell per 106 uninfected cells, similar to those observed in vivo. The goal of this application is to validate PrimeFlow RNA for the detection, enumeration, and phenotypic characterization of latently infected cells in clinical samples. This will be accomplished through two specific aims. I Specific Aim 1, we will validate this method by assessing the size of the latent reservoir after ex vivo viral reactivation with latency reversing agents and mitogenic stimuli. We will compare these estimates with the ones obtained by PCR and QVOA. In addition, we will perform longitudinal analyses measuring viral reactivation after in vivo administration of latency reversing agents to HIV-infected individuals enrolled in clinical trials. A significant benefit of PrimeFlow RNA is that it is a flow cytometry-based technology, thus allowing phenotypic characterization as well as sorting of the positive cells. In Specific Aim 2 will take advantage of these aspects. We will sort HIV-infected and uninfected cells from clinical samples by PrimeFlow RNA after ex vivo viral reactivation, which we will use to carry out comparative complete transcriptome analyses. In addition, we will com- bine PrimeFlow RNA with standard flow cytometry to perform comparative analyses of cell surface and intra- cellular markers in HIV-infected and uninfected cells from clinical samples after ex vivo viral reactivation. Therefore the studies proposed in this application will achieve two major goals. First, they will lead to develop a new sensitive technique to measure the size of the latent reservoir. Second, they will generate new critical information about the biology of latently infected cells obtained from clinical samples.