"MSM" A multi-scale approach for understanding antigen presentation in immunity

“MSM”一种了解免疫中抗原呈递的多尺度方法

基本信息

批准号：
7284995
负责人：
Denise E Kirschner
金额：
$ 35.16万
依托单位：
UNIVERSITY OF MICHIGAN AT ANN ARBOR
依托单位国家：
美国
项目类别：
财政年份：
2005
资助国家：
美国
起止时间：
2005-09-01 至 2009-08-31
项目状态：
已结题

项目摘要

The human immune response works to either clear or control pathogens upon infection. Antigen presentation s critical to the immune response and is the process by which peptide fragments of pathogens are taken up by cells and displayed on the cell surface. Events at multiple scales (genetic molecular, cellular, tissue, and organ) are involved in antigen presentation. Briefly, antigen-presenting cells (ARC) take up pathogens at the site of infection. Once they have been taken up, they are then processed into peptides within the APC. These peptides then bind proteins known as the major histocompatibility complex (MHC). These peptide- MHC complexes (pMHC) are then displayed on the surface of the APC for recognition by T cells. In addition, the dynamics of antigen presentation and recognition are influenced by the larger tissue-level context in which they occur, namely the structured environment of the lymph node and ultimately by external compartmental dynamics of blood and the lymphatic system. A comprehensive understanding of the process of antigen presentation during an immune response will require an integrated picture of events that are occurring over multiple spatial and time scales. Mathematical models are tools that allow for such a multiscale investigation. Not surprisingly, since pathogens meet APCs continually as a first line of defense, many have evolved ways to inhibit antigen presentation. One such intracellular bacterial pathogen is Mycobacterium tuberculosis. Upon entering the lungs, M. tuberculosis is taken up by resident macrophages and then replicates. To evade immune surveillance, M. tuberculosis is known to inhibit antigen presentation of its host macrophage. The mechanisms by which M. tuberculosis achieves this inhibition have not been completely elucidated. Our specific aims include: building mathematical and statistical models to: predict affinity of peptides for different MHCII molecules with particular emphasis on the role that peptide length plays in determining affinity; describe the processing and the presentation events occurring in a single APC; describe antigen recognition and some of the downstream events by capturing interactions of cells within a single lymph node; capture relevant immune dynamics in the body in two-compartments of blood/lymph node. Integrating the models over multiple scales will be a key goal as well as utilizing data from non-human primate and mouse systems. Our specific goal is to use the models developed above towards understanding antigen presentation during M. tuberculosis infection, the causative agent of tuberculosis, and the leading cause of death due to infectious disease in the world today. As the premise behind vaccines is to train the immune system to recognize pathogens (via antigen presentation) and to quickly respond, information gained from the studies described herein can be immediately applied to vaccine design for M. tuberculosis as well as for other pathogens.

人类免疫反应可在感染后清除或控制病原体。抗原表现对免疫反应至关重要，是病原体的肽片段被细胞吸收并显示在细胞表面上的过程。多个尺度（遗传分子，细胞，组织和器官）的事件参与抗原表现。简而言之，抗原呈递细胞（ARC）在感染部位吸收病原体。一旦被吸收，它们就会在APC中加工成肽。然后，这些肽结合称为主要组织相容性复合物（MHC）的蛋白质。然后将这些肽-MHC复合物（PMHC）显示在APC的表面上，以通过T细胞识别。此外，抗原表现和识别的动力学受到发生的较大组织水平环境的影响，即淋巴结的结构化环境，最终受血液和淋巴系统的外部隔室动力学。对免疫反应期间抗原呈递过程的全面理解将需要在多个空间和时间尺度上发生的事件的综合图像。数学模型是允许进行多尺度调查的工具。毫不奇怪，由于病原体不断作为第一道防线与APC相遇，因此许多人进化了抑制抗原表现的方法。细胞内细菌病原体是结核分枝杆菌。进入肺部后，结核分枝杆菌被常驻巨噬细胞吸收，然后重复。为了逃避免疫监测，已知结核分枝杆菌抑制其宿主巨噬细胞的抗原表现。结核分枝杆菌达到这种抑制的机制尚未完全阐明。我们的具体目的包括：构建数学和统计模型以：预测肽对不同MHCII分子的亲和力，特别强调肽长度在确定亲和力中所起的作用；描述单个APC中发生的处理和演示事件；通过捕获单个淋巴结中细胞的相互作用来描述抗原识别和某些下游事件；在血液/淋巴结的两校区中捕获体内相关的免疫动力学。在多个尺度上集成模型将是一个关键目标，也是利用非人类灵长类动物和鼠标系统的数据。我们的具体目标是使用上面开发的模型来理解结核分枝杆菌感染期间的抗原表现，结核病的病因以及当今世界上传染病引起的死亡原因。作为疫苗背后的前提是训练免疫系统以识别病原体（通过抗原表现）并迅速做出反应，因此从此处描述的研究中获得的信息可以立即用于结核分枝杆菌以及其他病原体的疫苗设计。