DYNAMICS AND EVOLUTION OF IMMUNE RESPONSES TO INFLUENZA VIRUSES

项目概要/摘要 我们的目标是建立一个量化的框架，用于生成，提升和维护 免疫记忆数学模型是有用的，因为免疫和感染涉及 快速变化的病毒群体和多个免疫细胞群体的相互作用。我们首先 用小鼠实验开发和验证模型。然后，我们使用这些验证模型来分析 来自人类疫苗接种研究的数据。 目标1询问先前的免疫力如何影响和潜在地限制免疫力的增强，并将其应用于 流感。我们的方法是建立模型，以了解为什么先前的免疫力限制了 病毒保守区的抗体。具体来说，我们使用模型来更好地了解 先前的免疫可能会限制对干细胞上保守区域的抗体应答的加强， 血凝素分子是通用流感疫苗的重点。 目的2考虑影响体液免疫记忆持久性的因素，并提出问题 例如为什么用蛋白质抗原免疫产生的记忆不如免疫持久 产生的病毒感染，以及如何事先免疫可以不同地影响加强和代 新流感病毒的记忆。 目的3考虑CD 8 T细胞对流感和黄热病记忆的产生。我们将确定 反复接触流感如何影响产生的CD 8 T细胞反应的多样性。我们有 访问一个独特的数据集，该数据集遵循YFV特异性CD 8 T细胞的数量， 表型，和他们的营业额从重水标记研究为期一年以上。我们的分析 这一数据集将使我们能够解决一个正在进行的争论， CD 8记忆干细胞在免疫后迅速产生，或者随着时间的推移逐渐产生。 目标4描述了我们将建立的用于B细胞受体序列分析的计算工具， 可视化，并用于模拟免疫反应的动态。这些工具将广泛 在线访问，并在我们组织的研讨会和科学研讨会上推广。

PROJECT SUMMARY/ABSTRACT Our goal is to develop a quantitative framework for the generation, boosting and maintenance of immunological memory. Mathematical models are useful because immunization and infection involve the interaction of rapidly changing populations of virus and multiple populations of immune cells. We first develop and validate models using experiments in mice. We then use these validated models to analyze data from human vaccination studies. Aim 1 asks how prior immunity affects and potentially limit the boosting of immunity and apply this to influenza. Our approach is to develop models to understand why prior immunity limits boosting of antibodies to conserved regions of the virus. Specifically, we use our models to better understand how prior immunity might limit boosting of antibody responses to conserved regions on the stem of the hemagglutinin molecule that is the focus of universal influenza vaccines. Aim 2 considers the factors that affect the durability of humoral immune memory, and address questions such as why memory generated by immunization with protein antigens is less durable than immunity generated by virus infection, and how prior immunity can differentially affect the boosting and generation of memory to new strains of influenza. Aim 3 considers the generation of CD8 T cell memory to influenza and yellow fever. We will determine how repeated exposure to influenza affects the diversity of the CD8 T cell responses generated. We have access to a unique dataset that follows the number of YFV-specific CD8 T cells, changes in their phenotype, and their turnover from heavy water labelling studies for a period of over one year. Our analysis of this dataset will allow us to address an ongoing controversy regarding whether are long-term memory CD8 memory stem cells are generated rapidly after immunization or only gradually over time. Aim 4 describes computational tools that we will build for B cell receptor sequence analysis and visualization, and for simulation of the dynamics of immune responses. These tools will be widely accessible online, and promoted at workshops and scientific symposia we organize.