Harnessing cell-to-cell variability to understand viral infection outcomes

利用细胞间的变异来了解病毒感染的结果

• 批准号: 10685929
• 负责人: Nir Drayman
• 金额: $ 43.76万
• 依托单位: UNIVERSITY OF CALIFORNIA-IRVINE
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-08-18 至 2027-07-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10685929
• 关键词: Affect; Antiviral Response; Antiviral Therapy; Award; Biological Models; Biology; Cell Fraction; Cells; Cellular biology; Collaborations; Custom; Data; Development; Gene Expression; Genetic Transcription; Germ Cells; Goals; Herpesvirus 1; Infection; Infection Control; Integration Host Factors; Investments; Life Cycle Stages; Literature; Machine Learning; Measurement; Methodology; Microfluidic Microchips; Microfluidics; Modality; Modeling; Molecular; Monitor; NF-kappa B; National Institute of Allergy and Infectious Disease; Outcome; Pathway interactions; Phenotype; Positioning Attribute; Probability; Process; Production; Productivity; Research; Research Personnel; Resources; Science; Shapes; Supervision; System; Systems Biology; TNF gene; Technology; Testing; Therapeutic; Time; Titrations; Validation; Viral; Viral Genes; Virus; Virus Diseases; Virus Replication; Work; cellular imaging; design; doctoral student; high reward; high risk; improved; innovation; insight; live cell imaging; machine learning algorithm; novel; novel strategies; pathogen; pathogenic virus; programs; rational design; secondary infection; single-cell RNA sequencing; tool; transcription factor; virology; virus genetics; virus host interaction

PROJECT SUMMARY / ABSTRACT This is a DP2 NIAID New Innovators Award proposal to harness cell-to-cell variability to understand viral infection outcomes at the single cell level. Infected cells differ in the outcome of infection (abortive/productive), the timing and level of viral gene expression and the number of progeny they produce. Two striking phenomena revealed by studying infection at the single cell level are (1) the ability of some cells to abort infection after viral gene expression has commenced and (2) the fact most infected cells release very few progeny while a small fraction of cells release thousands (here termed “super producers”). While it is now accepted that cell-to-cell variability affects infection outcome, we currently lack a molecular understating of the determinants of infection outcome in single cells, mainly due to the lack of appropriate tools and methodologies. Understanding these determinants is likely to lead to the discovery of novel cellular anti-viral modalities, better design of therapeutics and deepen our understanding of the viral life cycle. In this proposal I will apply cutting-edge technologies to investigate virus-host interactions at the single cell level and gain mechanistic insights as to the host factors that control the opposing phenotypes of abortive infection and super producers. My central hypothesis, supported by my past work and preliminary data using Herpes Simplex virus 1 (HSV-1) as a model system, is that infection outcome at the single cell level is dependent on the cell’s state at the time of infection and on the activation of specific cellular transcriptional programs. To test this hypothesis I will develop new approaches to interrogate virus-host interactions by combining viral genetics, single-cell RNA-sequencing, custom-made microfluidic devices, live- cell imaging and machine learning approaches. My background in performing cross-disciplinary research through the combination of classical virology, cell-biology, microfluidics and systems biology to study virus-host interactions uniquely positions me to successfully tackle these important questions. My results will identify the host factors that determine infection outcome and define a new paradigm, using cell-to-cell variability to understand virus-host interactions. The tools and technologies will be developed using HSV-1 as a model system, and then applied to investigate other important viral pathogens, in collaboration with leading virologists. This “high-risk high-reward” project requires a considerable investment of time and resources and the construction of new tools, making it a perfect fit for the DP2 program. The award will allow me to pursue cutting-edge science at the interface of virology and single cell biology and establish a long-term research plan to decipher the cellular mechanisms that control infection outcome.

项目摘要/摘要 这是DP2 NIAID新创新者奖的提案，旨在利用细胞间的可变性来了解病毒感染 单细胞水平的结果。被感染的细胞在感染的结果(流产/繁殖)、时间和 病毒基因的表达水平及其产生的后代数量。研究揭示的两个显著现象 单细胞水平上的感染是(1)某些细胞在病毒基因表达后中止感染的能力 开始和(2)大多数受感染的细胞释放很少的后代，而一小部分细胞释放数千 (这里称为“超级制片人”)。虽然现在公认细胞间的变异性会影响感染结果，但我们 目前缺乏对单细胞感染结局决定因素的分子轻描淡写，主要是由于缺乏 适当的工具和方法。 了解这些决定因素可能会导致发现新的细胞抗病毒模式，更好地设计 并加深我们对病毒生命周期的理解。在这份提案中，我将把尖端技术应用于 在单细胞水平上研究病毒与宿主的相互作用，并对控制宿主因素的机制有深入的了解 流产感染和超级生产者的对立表型。 我的中心假设，由我过去的工作和使用单纯疱疹病毒1型(HSV-1)作为模型的初步数据支持 单细胞水平的感染结果取决于感染时细胞的状态和 激活特定的细胞转录程序。为了验证这一假设，我将开发新的方法来审问 通过结合病毒遗传学、单细胞RNA测序、定制的微流控设备、实时- 细胞成像和机器学习方法。我从事跨学科研究的背景 结合经典病毒学、细胞生物学、微流体学和系统生物学独特地研究病毒与宿主的相互作用 使我能够成功地解决这些重要问题。我的结果将确定决定 感染结果并定义一种新的范式，使用细胞间的可变性来理解病毒与宿主的相互作用。这些工具 并将以HSV-1为模型系统开发技术，然后应用于其他重要病毒的研究 病原体，与领先的病毒学家合作。 这项“高风险、高回报”的工程，需要投入相当多的时间和资源， 新的工具，使其完美地适合DP2计划。该奖项将使我能够在 病毒学和单细胞生物学的接口，并建立一个长期研究计划来破译细胞机制 来控制感染结果。