Modeling Early Immunity to Human Influenza Infection

人类流感感染的早期免疫建模

• 批准号: 9264974
• 负责人: STUART C. SEALFON
• 金额: $ 167.11万
• 依托单位: ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI
• 依托单位国家: 美国
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-05-08 至 2020-04-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9264974
• 关键词: Address; Antiviral Agents; Biological Assay; CD8-Positive T-Lymphocytes; Cell physiology; Cells; Cellular Immunity; Clinical; Complex; Containment; Contracts; Data; Data Analyses; Dendritic Cells; Development; Education; Elements; Engineering; Epithelial Cells; Epithelium; Experimental Models; Fluorescent in Situ Hybridization; Foundations; Functional disorder; Funding; Genetic Transcription; Genotype; Goals; Heterogeneity; Homeostasis; Host Defense Mechanism; Human; Immune; Immune response; Immune system; Immunity; Immunologic Surveillance; Immunological Models; Immunologics; Immunology procedure; In Vitro; Infection; Influenza; Influenza A Virus, H1N1 Subtype; Influenza A virus; Innate Immune Response; Lung; Maintenance; Methods; Modeling; Molecular; Morbidity - disease rate; National Institute of Allergy and Infectious Disease; Outcome; Pathogenesis; Pattern; Phenotype; Process; Property; Public Health; RNA; Regulation; Research; Resources; Risk; Role; Services; Shapes; Standardization; Stochastic Processes; Structure of parenchyma of lung; System; Technology; Testing; Therapeutic; Time; Tissues; Tracheobronchial; Vaccination; Vaccines; Validation; Variant; Viral Interference; Virus; Virus Diseases; Virus Replication; Work; adaptive immunity; autocrine; biodefense; cell type; clinically relevant; cytokine; data management; data modeling; experimental study; improved; in vivo; influenza virus strain; influenza virus vaccine; influenzavirus; inhibitor/antagonist; insight; intraepithelial; mathematical model; monocyte; mortality; multi-scale modeling; mutant; new technology; pandemic disease; paracrine; pathogen; predictive modeling; programs; public health relevance; recombinant virus; respiratory; response; single cell technology; tool; virology

 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.

 描述（由申请方提供）：由于每年的甲型流感病毒（IAV）发病率和死亡率、灾难性新大流行的风险以及当前疫苗和治疗方法的局限性，提高我们对甲型流感病毒（IAV）早期免疫应答的理解具有重要意义。保护性免疫的发展和人肺中免疫稳态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，早期免疫反应的初始IAV感染在人类肺部是一个新兴的财产从许多细胞类型，宿主过程，病原体的影响，和微环境因素，跨尺度传播和相互作用的空间和时间。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。预测免疫学建模，这是需要了解这个复杂的系统，需要一个协作程序，以锚模型在详细的人类时间过程中获得的免疫学数据，在原代人类细胞和人类肺组织。我们现有的NIAID合同资助的计划（PRiME）为生物防御免疫建模研究了人类单核细胞衍生的树突状细胞（mo-DC）对IAV的动态免疫反应，提供了新的见解宿主，病毒和随机机制，在感染后的mo-DC中运行。我们现在建议通过显着扩大我们的重点，以包括在空间和时间上相互作用的多种细胞类型，来推进人类IAV感染的预测建模-将为人类气管支气管上皮细胞（HTBE）开发实验验证的模型，HTBE是对抗病毒的最初防线，而CD 1c+细胞是主要的CD 1c+细胞。 人DC亚型细胞，其在感染的第一天期间响应IAV以促成立即免疫应答并启动适应性免疫。模型参数化和验证是通过我们建立的新的关键技术实现的，包括条形码重组病毒、单细胞测定、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性HTBE对IAV感染的反应。Projec 2将量化原代CD 1c + DC和新鲜人肺组织对IAV感染的反应。项目3将在培养和肺微环境的背景下开发HTBE和DC中IAV感染的多尺度模型。研究的野生型和重组病毒将在核心B：病毒学中生成。将通过Core C：免疫测定对所有实验项目的免疫测定进行标准化。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和服务核心的核心是核心A：管理，它将协调所有项目活动和开发教育项目。这项研究计划将提高对IAV免疫应答机制的理解，为改进治疗和疫苗接种策略提供基础。