Use of Protein Biomarkers to Identify Latent/Persistent HIV Infected Cell Reservoirs Without Induced Reactivation

 描述（由申请方提供）：目前没有能够准确测量HIV潜伏储库的功能性、可复制组分的真实大小的检测试剂盒。此外，现有的检测潜伏感染的方法都不允许从接受联合抗逆转录病毒疗法（cART）的HIV感染患者中离体捕获和富集活的潜伏感染细胞。这需要依赖于使用体外模型细胞系统来研究病毒潜伏的机制和探索靶向潜伏感染的疗法。本申请的目的是开发一种基于蛋白质的方法来选择性地鉴定潜伏感染的细胞，该方法将适用于基于实用的流式细胞术的方法，用于直接定量和分离体内潜伏储库中的细胞。中心假设是潜伏感染细胞的蛋白质生物标志物存在，并且可用于其特异性检测。拟议研究的基本原理是，鉴定独特的蛋白质特征将允许定量潜伏感染的细胞，而不需要病毒再活化，并将提供一种分离活的潜伏感染细胞的方法。 从艾滋病感染者身上提取的细胞。我们将通过追求以下具体目标来检验我们的假设：1）鉴定与原代CD 4 T细胞的潜伏性HIV感染相关的蛋白质生物标志物; 2）使用市售的抗体试剂针对鉴定的蛋白质生物标志物的子集，以评估从混合细胞群富集潜伏感染细胞的能力开发一种优化的单克隆抗体组，用于检测潜伏感染的原代CD 4 T细胞; 4）确定开发的抗体组准确鉴定来自HIV感染患者的PBMC中潜伏感染细胞的能力。在R21阶段，Aim 1将利用两种体外原代T细胞模型和一种新型的、高灵敏度的定量蛋白质组学（iTRAQ）技术来研究潜伏感染和未感染的CD 4 T细胞的整个蛋白质组。潜伏期的生物标志物将使用limma建模包（Bioconductor R）和蛋白质表达与每个样品中潜伏感染细胞的百分比的相关性分析来鉴定。目标2将通过测试商业上可获得的抗体来提供“原理证明”，所述抗体针对一小组经鉴定的质膜蛋白，以证明从细胞混合物中富集潜伏感染的细胞。在R33阶段，Aim 3将使用三种潜伏期模型（Spina、Karn和格林）优化用于潜伏感染细胞的灵敏度和特异性检测的抗体组。在目的4中，将使用来自接受抑制性cART的HIV感染患者的PBMC，评价在原代T细胞模型中具有最佳和最一致性能的抗体组。我们的方法是直接的，但创新的;它将确定主机，而不是病毒，与潜伏感染选择性相关的决定因素。这项研究意义重大，因为它将开发一种快速，实用的方法来特异性地检测潜伏感染的细胞，而无需病毒再激活。此外，所鉴定的蛋白质生物标志物可以作为未来选择性破坏潜伏性储库细胞的治疗靶点。

 DESCRIPTION (provided by applicant): There is no assay currently capable of accurately measuring the true size of the functional, replication- competent component of the HIV latent reservoir. Moreover, none of the existing approaches to detect latent infection allow for the ex vivo capture and enrichment of viable latently infected cells from HIV-infected patients on combination antiretroviral therapy (cART). This necessitates reliance on the use of in vitro model cell systems both to study the mechanisms underlying viral latency and to explore therapies to target latent infection. The objective of this application is to develop a protein-basd method to selectively identify latently infected cells that will be amenable to practical flow cytometric-based approaches for direct quantification and isolation of cells from the latent reservoir in vivo. The central hypothesis is that protein biomarkers of latently infected cells exit and can be used for their specific detection. The rationale of the proposed research is that identification of a unique protein signature will allow quantification of latently infected cells, without the requirement for virus reactivation, and will provide a means to isolate viable latently infected cells from HIV- infected patients. We will test our hypothesis by pursuing the following specific aims: 1) Identify protein biomarkers associated with latent HIV infection of primary CD4 T cells; 2) Use commercially available antibody reagents to a subset of the identified protein biomarkers to assess the ability to enrich for latently infected cells from a mixed cell population 3) Develop an optimized monoclonal antibody panel for sensitive and specific detection of latently infected primary CD4 T cells; 4) Determine the ability of the developed antibody panel(s) to accurately identify latently infected cells in PBMC from HIV-infected patients. In the R21 phase, Aim 1 will utilize two in vitro primary T cell models and a novel, highly sensitive quantitative proteomics (iTRAQ) technology to interrogate the entire proteome of latently infected and uninfected CD4 T cells. Biomarkers of latency will be identified using the limma modeling package (Bioconductor R) and correlation analysis of protein expression with the percentage of latently infected cells in each sample. Aim 2 will provide "proof of principle" by testing commercially available antibodies, against a small group of identified plasma membrane proteins, to demonstrate enrichment of latently infected cells from a cell mixture. In the R33 phase, Aim 3 will optimize the antibody panel for sensitive and specific detection of latently infected cells, using three latency models (Spina, Karn and Greene). In Aim 4, the antibody panel(s) with the optimal and most consistent performance across the primary T cell models will be evaluated, using PBMC from HIV-infected patients on suppressive cART. Our approach is direct, but innovative; it will identify host, not viral, determinants that are associated selectivly with latent infection. The research is significant, because it will develop a quick, practical method to specifically detect latently infected cells, without virus reactivation. Moreover, the identified protein biomarkers may serve as therapeutic targets in future efforts to selectively destroy cells of the latent reservoir.