Modeling Early Immunity to Human Influenza Infection

 描述(由申请人提供)：鉴于甲型流感病毒每年的发病率和死亡率、新一轮灾难性大流行的风险以及现有疫苗和疗法的局限性，提高我们对甲型流感病毒(IAV)早期免疫反应的了解具有重要意义。人类肺中保护性免疫的发展和免疫平衡的维持的许多方面在很大程度上是未知的。我们的中心主题是，人肺对初始IAV感染的早期免疫应答是一种来自多种细胞类型、宿主过程、病原体效应和微环境因素的紧急特性，跨尺度传播，在空间和时间上相互作用。随机过程和由此产生的单细胞反应变化如何影响组织水平的免疫反应是我们准备解决的一个重要问题。为了理解这一复杂的系统，预测性免疫建模需要一个协作程序，以锚定在原代人类细胞和人类肺组织中获得的详细的人类时间进程免疫学数据中的模型。我们现有的NIAID合同资助计划(Prime)用于模拟生物防御的免疫，研究了人单核细胞来源的树突状细胞(mo-DC)对IAV的动态免疫反应，为了解宿主、病毒和感染后mo-DC中运行的随机机制提供了新的见解。我们现在建议通过显著扩展我们的关注点以包括多种在空间和时间上相互作用的细胞类型来推进对人类IAV感染的预测建模--将为人类气管支气管上皮细胞(HTBE)和初级CD1c+细胞开发实验验证的模型，HTBE是抵御病毒的初始防线。 人类DC亚型细胞在感染的第一天对IAV做出反应，以促进即时免疫反应并启动适应性免疫。模型的参数化和验证是由我们建立的新的关键技术实现的，包括条形码重组病毒、单细胞分析、人肺外植体和多尺度建模方法。项目I将量化完全分化的原发HTBE对IAV感染的反应。Projec 2将量化原代CD1c+DC和新鲜人类肺组织对IAV感染的反应。项目3将在HTBE和DC中开发多尺度的IAV感染模型，并在培养和肺微环境的背景下进行。研究的野生型和重组病毒将在核心B：病毒学中产生。核心C：免疫分析将对所有实验项目的免疫分析进行标准化。核心D：模型和数据管理将促进模型和数据的数据分析、数据处理和传播。所有实验和建模项目以及服务核心的核心是核心A：管理，它将协调所有计划活动并开发教育计划。这项研究计划将提高对IAV免疫应答潜在机制的理解，以便为改进治疗和疫苗接种策略提供基础。

 DESCRIPTION (provided by applicant): Improving our understanding of the early immunological responses to influenza A virus (IAV) is significant due to the annual IAV morbidity and mortality, the risk of a catastrophic new pandemic and the limitations of current vaccines and therapeutics. Many aspects of the development of protective immunity and the maintenance of immune homeostasis in the human lung are largely unknown. Our central theme is that the early immune response to the initial IAV infection in human lung is an emergent property from many cell types, host processes, pathogen effects, and microenvironment factors, propagating across scales and interacting in space and time. How stochastic processes and the resulting single cell response variation influence tissue level immunological response is an important question we are poised to address. Predictive immunological modeling, which is needed to understand this complex system, requires a collaborative program to anchor models in detailed human time course immunological data obtained in primary human cells and human lung tissue. Our existing NIAID contract-funded program (PRiME) for modeling immunity for biodefense has studied the dynamic immunological responses of human monocyte-derived dendritic cells (mo-DC) to IAV, providing new insights into host, virus and stochastic mechanisms that operate in mo-DCs following infection. We now propose to advance predictive modeling of IAV infection in humans by significantly expanding our focus to include multiple cell types that interact in space and time--experimentally-validated models will be developed for the human tracheobronchial epithelial cells (HTBE), which are the initial line of defense against virus, and the primary CD1c+ human DC subtype cells which respond to IAV during the first days of infection to contribute to the immediate immune response and to initiate adaptive immunity. Model parameterization and validation are enabled by new key technologies we have established, including barcoded recombinant viruses, single cell assays, human lung explants and multiscale modeling methods. Project I will quantify the responses of fully differentiated primary HTBE to IAV infection. Projec 2 will quantify the responses of primary CD1c+ DC and fresh human lung tissue to IAV infection. Project 3 will develop multiscale models of IAV infection in HTBE and DC in culture and in the context of the lung microenvironment. The wild-type and recombinant viruses studied will be generated in Core B: Virology. The immune assays will be standardized for all experimental projects by Core C: Immune Assay. The data analysis, data handling and dissemination of models and data will be facilitated by Core D: Model and Data Management. Central to all experimental and modeling projects and service cores is Core A: Administrative, which will coordinate all program activities and develop educational programs. This research program will improve the understanding of the mechanisms underlying the immune response to IAV in order to provide the basis for improved strategies for therapeutics and vaccination.