Stochastic Gene Expression in Retroviral Latency

描述（由申请人提供）：逆转录病毒感染对人类健康造成巨大损害。人类免疫缺陷病毒1型（HIV- 1，或“HIV”）已在全球造成3000万人死亡，3600万人感染了艾滋病毒/艾滋病。目前还没有有效的艾滋病疫苗。用于治疗艾滋病毒的现有抗逆转录病毒疗法（ARTs）不能治愈受感染的患者。抗逆转录病毒治疗必须终生服用，因为艾滋病毒可以通过潜伏感染CD4+ T细胞而处于休眠状态。这些潜伏宿主寿命很长，确保病毒终生存在，并被认为是从患者身上根除艾滋病毒的最大障碍。目前正在积极寻求“激活和杀死”这些潜伏宿主并治愈艾滋病毒感染者的方法。然而，即使在理想的实验室条件下，最强大的激活剂也只能部分激活潜伏的HIV。我们已经确定，这种异质性在很大程度上是由于转录的随机波动导致的，这种波动驱动了HIV的命运“开关”。如果我们希望有效地重新激活潜伏的HIV，那么描述驱动这些转录波动的分子机制并解决如何调节活性和潜伏感染之间的“切换”是至关重要的。我们的长期目标是确定有效地“激活和杀死”潜伏艾滋病毒的分子途径。该项目的目标是建立HIV潜伏期的定量模型，在供体来源的原发CD4+ T细胞中实验验证该模型，并干扰产生潜伏HIV部分再激活的变异性来源。基于我们广泛的初步研究，我们的中心假设是HIV转录的随机波动(即。“噪声”)限制HIV的再激活，而操纵噪声将增强HIV的再激活。在细菌和噬菌体中，调节基因表达变异性可以显著改变类似的细胞命运决定。该项目的基本原理是确定调整HIV变异性的方法将使我们能够调整HIV潜伏再激活并有效清除潜伏库。我们将通过依赖于单细胞成像和单细胞数据的数学建模的特定目标来实现我们的目标。具体来说，我们利用一套新的微孔设备和成像方法来开发供体来源的原发CD4+ T细胞中HIV潜伏期的数学模型。我们将确定随机波动的分子来源，以确定哪些参数对扰动最敏感。该模型将使我们能够合理地测试在原发CD4+ T细胞中重新激活潜伏HIV的新方法。除了医学上的相关性外，这项研究还具有广泛的意义，因为在一般情况下，特别是在哺乳动物系统中，驱动命运决策转换变异性的机制尚不清楚。该项目将为哺乳动物系统中噪声驱动的发育开关提供急需的定量表征。最终，获得的知识将指导新的方法来调整命运开关，不仅在艾滋病毒中，而且在各种哺乳动物系统中。

DESCRIPTION (provided by applicant): Retroviral infections take an enormous toll on human health. The human immunodeficiency virus type 1 (HIV- 1, or "HIV") has killed 30 million people worldwide and 36 million people are living with HIV/AIDS. There is no effective vaccine for HIV. The available antiretroviral therapies (ARTs) for treating HIV cannot cure infected patients. ART must be taken life-long because HIV can exist in a dormant state by latently infecting CD4+ T cells. These latent reservoirs are long lived, ensuring lifelong persistence of the virus, and are recognized as the greatest obstacle to eradicating HIV from patients. Approaches to 'activate and kill' these latent reservoirs, and cure HIV-infected individuals, are being actively pursued. However, even under ideal laboratory conditions, the most powerful activators only partially reactivate latent HIV. We have established that this heterogeneity results in large part from stochastic fluctuations in transcription that drive a fate 'switch' in HIV. If we hope to efficienty reactivate latent HIV, it is critical to characterize the molecular mechanisms driving these transcriptional fluctuations and address how the 'switch' between active and latent infection is regulated. Our long-term goal is to identify the molecular pathways to efficiently 'activate and kil' latent HIV. The objectives of this project are to develop a quantitative model of HIV latency, experimentally validate this model in donor-derived primary CD4+ T cells, and perturb the sources of variability that generate partial reactivation of latent HIV. Based upon our extensive preliminary studies, our central hypothesis is that stochastic fluctuations in HIV transcription (ie. 'noise') limit HIV reactivation and that manipulating noise will enhance HIV reactivation. In bacteria and phage, tuning gene-expression variability can significantly alter similar cell-fate decisions. The rationale for this project is that identifying approaches to tune HIV variability wil enable us to tune HIV latent reactivation and efficiently purge of the latent reservoir. We will achieve our objective through specific aims that rely on single-cell imaging and mathematical modeling of single-cell data. Specifically, we capitalize on a new suite of microwell devices and imaging approaches to develop a mathematical model of HIV latency in donor-derived primary CD4+ T cells. We will identify the molecular sources of stochastic fluctuations to determine which parameters are most sensitive to perturbation. This model will enable us to rationally test new approaches for reactivating latent HIV in primary CD4+ T cells. In addition to the medical relevance, the proposed research has broad significance since the mechanisms driving variability in fate-decision switches are unclear in general, especially in mammalian systems. This project would provide a much-needed quantitative characterization of a noise-driven developmental switch in a mammalian system. Ultimately, the knowledge gained will guide new approaches to tune fate switches not just in HIV, but also in diverse mammalian systems.