Temporal-quantitative control of IRF-3 and NF-kB upon pathogen recognition in single cells and living tissue

单细胞和活组织中病原体识别时 IRF-3 和 NF-kB 的时间定量控制

• 批准号: 230716034
• 负责人: Dr. Ulfert Rand
• 金额: --
• 依托单位: Faculty of Biology, Medicine and Health
• 依托单位国家: 德国
• 项目类别: Research Fellowships
• 财政年份: 2012
• 资助国家: 德国
• 起止时间: 2011-12-31 至 2013-12-31
• 项目状态: 已结题
• 来源: https://gepris.dfg.de/gepris/projekt/230716034?language=en
• 关键词: Temporal; quantitative; control; IRF; NF

The induction of type-I interferon (IFN) genes in response to viral infection is an essential process of innate immunity. Following recognition of viral RNA a complex signal transduction pathway eventually activates IRFs (interferon regulatory factors) 3 and 7 and NF-kB (nuclear factor kB). These factors mediate the transcriptional induction of type-I interferon (IFN) and other antiviral genes. Strikingly, individual cells exhibit a yet unpredictable variation in the expression of IFN and its timing. Our recent work provides for the first time a comprehensive analysis of IFN induction and action signalling at single-cell resolution (Rand et al., Molecular Systems Biology, in revision). However, the mechanistic basis of IFN expression dynamics remains unclear. With the proposed research project I want to elucidate how the recognition of pathogen patterns is translated into spatio-temporal signalling dynamics at single-cell level. It is known that a disproportionate production of type-I IFN can play an important role in the inability to control viral infections and in autoimmune disorders. Elucidating the temporal-spatial dynamics of the IRF-3 / NF-kB-mediated induction depending on variable conditions such as pathogenic load, cytokine environment or tissue structure will help to understand how appropriate control on IFN production is maintained. Therefore, I will perform time-resolved quantitative studies to investigate the concerted regulation of IRF-3 and NF-kB following recognition of dsRNA by the cell. With this I will elucidate the impact of various conditions of an inflammatory environment and the relevance of single-cell dynamics in living tissue. Data from these quantitative studies will be used to create a mathematical model with the aim to be able to predict IFN expression dynamics. The overall use of this work will be to allow predictive assumptions on the course of the early immune response following infection or vaccination. Furthermore, the results of this work can serve as a roadmap for related signalling pathways.

响应病毒感染而诱导 I 型干扰素 (IFN) 基因是先天免疫的重要过程。识别病毒 RNA 后，复杂的信号转导途径最终激活 IRF（干扰素调节因子）3 和 7 以及 NF-kB（核因子 kB）。这些因子介导 I 型干扰素 (IFN) 和其他抗病毒基因的转录诱导。引人注目的是，单个细胞在 IFN 表达及其时间上表现出不可预测的变化。我们最近的工作首次在单细胞分辨率下对 IFN 诱导和作用信号传导进行了全面分析（Rand 等人，分子系统生物学，修订中）。然而，IFN 表达动态的机制基础仍不清楚。通过拟议的研究项目，我想阐明如何将病原体模式的识别转化为单细胞水平的时空信号动力学。众所周知，I 型干扰素的过量产生可能在无法控制病毒感染和自身免疫性疾病中发挥重要作用。阐明 IRF-3 / NF-kB 介导的诱导的时空动态取决于致病负荷、细胞因子环境或组织结构等可变条件，将有助于了解如何维持对 IFN 产生的适当控制。因此，我将进行时间分辨定量研究，以研究细胞识别 dsRNA 后 IRF-3 和 NF-kB 的协同调节。借此，我将阐明炎症环境的各种条件的影响以及活组织中单细胞动力学的相关性。这些定量研究的数据将用于创建数学模型，旨在预测 IFN 表达动态。这项工作的总体用途是对感染或疫苗接种后的早期免疫反应过程进行预测假设。此外，这项工作的结果可以作为相关信号通路的路线图。