Stochastic Gene Expression in Retroviral Latency

逆转录病毒潜伏期的随机基因表达

• 批准号: 9285693
• 负责人: Leor S Weinberger
• 金额: $ 44.02万
• 依托单位: J. DAVID GLADSTONE INSTITUTES
• 依托单位国家: 美国
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-06-01 至 2019-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9285693
• 关键词: AIDS/HIV problem; Address; Adjuvant; Affect; Anti-Retroviral Agents; Automobile Driving; Bacteria; Bacteriophages; CD4 Positive T Lymphocytes; Cells; Chimera organism; Clinical; Combined Modality Therapy; Data; Development; Devices; Elements; Ensure; Exhibits; Gene Expression; Genetic Transcription; Geography; Goals; HIV; HIV vaccine; HIV-1; Health; Heterogeneity; Human; Image; Individual; Infection; Jurkat Cells; Knowledge; Laboratories; Life; Medical; Modeling; Molecular; Noise; Outcome; Pathway interactions; Patients; Pattern; Population; Recombinants; Regulation; Research; Scheme; Source; System; Testing; Transcription Coactivator; Transformed Cell Line; Viral reservoir; Virus; Virus Replication; antiretroviral therapy; base; cellular imaging; drug candidate; drug resistant virus; imaging approach; integration site; killings; latent infection; mathematical model; novel strategies; prevent; profiles in patients; public health relevance; purge; reactivation from latency; small molecule libraries

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.

描述(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”)已导致全球3000万人死亡，3600万人感染艾滋病毒/艾滋病。目前还没有有效的艾滋病毒疫苗。现有的治疗艾滋病毒的抗逆转录病毒疗法(ARTS)不能治愈感染的患者。抗逆转录病毒治疗必须终身进行，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。这些潜伏的蓄水池是长期存在的，确保了病毒的终生存留，并被认为是从患者身上根除艾滋病毒的最大障碍。正在积极寻求“激活和杀死”这些潜伏的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重新激活潜伏的艾滋病毒。我们已经确定，这种异质性在很大程度上是由转录的随机波动造成的，这种随机波动驱动了艾滋病毒的命运“开关”。如果我们希望有效地重新激活潜伏的艾滋病毒，关键是要表征驱动这些转录波动的分子机制，并解决如何调节活跃感染和潜伏感染之间的“切换”。我们的长期目标是确定有效地“激活和杀死”潜伏的艾滋病毒的分子途径。该项目的目标是开发HIV潜伏期的定量模型，在捐赠者来源的原始CD4+T细胞中实验验证该模型，并扰乱导致潜伏期HIV部分重新激活的变异源。基于我们广泛的初步研究，我们的中心假设是艾滋病毒转录的随机波动(即。噪声)限制了HIV的重新激活，而操纵噪声将增强HIV的重新激活。在细菌和噬菌体中，调整基因表达的可变性可以显著改变类似的细胞命运决定。这个项目的基本原理是，确定调整艾滋病毒变异性的方法将使我们能够调整艾滋病毒潜在的重新激活和有效地清除潜伏的储存库。我们将通过依赖单细胞成像和单细胞数据数学建模的特定目标来实现我们的目标。具体地说，我们利用一套新的微孔设备和成像方法来开发供者来源的原始CD4+T细胞中HIV潜伏期的数学模型。我们将确定随机涨落的分子来源，以确定哪些参数对微扰最敏感。这一模型将使我们能够理性地测试在原代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，这项拟议的研究还具有广泛的意义，因为驱动命运决定开关可变性的机制总体上尚不清楚，特别是在哺乳动物系统中。该项目将为哺乳动物系统中由噪音驱动的发育开关提供亟需的定量表征。最终，所获得的知识将指导新的方法，不仅在艾滋病毒中，而且在不同的哺乳动物系统中调整命运开关。