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（由申请人提供）：逆转录病毒感染对人类健康造成了巨大损失。 1型人类免疫缺陷病毒（HIV-1或“艾滋病毒”）在全球范围内丧生3000万人，3600万人患有艾滋病毒/艾滋病。艾滋病毒没有有效的疫苗。用于治疗HIV的可用抗逆转录病毒疗法（ART）无法治愈感染的患者。必须将ART赋予终生，因为HIV可以通过潜在地感染CD4+ T细胞来处于休眠状态。这些潜在的储层长期存在，确保了病毒的终生持久性，并被认为是从患者中消除HIV的最大障碍。正在积极追求这些潜在的储层，并治愈感染的艾滋病毒感染者的方法。但是，即使在理想的实验室条件下，最强大的激活剂也只会部分重新激活潜在的艾滋病毒。我们已经确定，这种异质性很大程度上是由于转录的随机波动而导致的，这些转录驱动了HIV中的命运“开关”。如果我们希望有效地重新激活潜在的HIV，那么表征驱动这些转录波动的分子机制至关重要，并解决了如何调节主动感染和潜在感染之间的“开关”。我们的长期目标是确定有效“激活和KIL”潜伏艾滋病毒的分子途径。该项目的目标是开发一个艾滋病毒潜伏期的定量模型，在供体衍生的原代CD4+ T细胞中实验验证该模型，并扰动产生潜在HIV的部分重新激活的可变性来源。基于我们广泛的初步研究，我们的中心假设是HIV转录中的随机波动（即'噪声'）限制了HIV重新激活，并且操纵噪声将增强HIV的重新激活。在细菌和噬菌体中，调整基因表达变异性可以显着改变相似的细胞命运决策。该项目的理由是，确定调整HIV变异性的方法使我们能够调整艾滋病毒潜在的重新激活并有效地清除潜在储层。我们将通过依靠单细胞数据的单细胞成像和数学建模的特定目标来实现我们的目标。具体而言，我们利用了新的Microwell设备和成像方法，以开发供体衍生的原代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新方法，以重新激活主CD4+ T细胞中的潜在HIV。除了医学相关性外，拟议的研究具有广泛的意义，因为通常在命运否决开关中的变异性的机制一般不清楚，尤其是在哺乳动物系统中。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，所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。