Predicting immune responses that correlate with protection against tuberculosis

描述（由申请人提供）：结核病每年造成200万人死亡。即使经过几十年的研究，我们对人类预防结核病的机制的理解仍然存在许多差距。在这个建议中，我们采取了一种独特的多管齐下的系统生物学方法，结合非人灵长类M。结核病感染密切模仿人类M.结核病感染的疫苗，只有部分有效的（导致受保护和非保护的动物），和最先进的活动物成像，免疫监测和计算模型，以确定和预测免疫机制，对结核病的保护。这项提案将开发一个多学科的“工具箱”，用于解剖人体免疫反应，提供对细菌感染的保护，甚至超过结核病。我们在结核病的计算建模方面积累了相当多的经验，并将首次生成具有多尺度相互作用（分子到细胞到器官到宿主尺度）的血液、肺、淋巴结的3个生理隔室模型，并将该项目中从非人灵长类动物生成的数据以及我们以前的数据和文献中的数据结合起来。这些模型将用于识别保护的替代标志物，其将用于预测受该疫苗保护的动物。反过来，实验动物将成为肉芽肿和淋巴结组织的来源，以探测感染部位的实际保护反应，这是不可能在人类身上进行的研究。通过计算和实验模型之间的迭代，我们将确定共同有助于保护性免疫反应的因素。这些研究是一个必要的步骤，以更详细地了解宿主免疫反应，保护对结核病，并开发和测试新的治疗和干预策略，以防止这种疾病。

DESCRIPTION (provided by applicant): Tuberculosis is responsible for 2 million deaths every year. Even after decades of research, there are still numerous gaps in our understanding of the mechanisms that provide protection against tuberculosis in humans. In this proposal, we take a unique multipronged systems biology approach, combining a non-human primate model of M. tuberculosis infection that closely mimics all aspects of human M. tuberculosis infection, with a vaccine that is only partially effective (resulting in protected and non-protected animals), and state-of- the-art live animal imaging, immunologic monitoring, and computational models, to identify and predict the immunologic mechanisms that are protective against TB. This proposal will develop a multi-disciplinary "tool- box" for dissecting human immune responses that provide protection against bacterial infections, even beyond TB. We build on considerable experience in computational modeling of tuberculosis and will generate a first- time 3 physiologic compartment model of blood, lung, lymph node with multi-scale interactions (molecular to cellular to organ to host scales), incorporating data generated in this project from the non-human primate, as well as our previous data and that from the literature. These models will be used to identify surrogate markers of protection, which will be used to predict the animals that are protected by this vaccine. In turn, the experimental animals will be the source of granuloma and lymph node tissue to probe the actual protective responses at the site of infection, studies that are impossible to do in humans. Through iteration between computational and experimental models, we will identify the factors that together can contribute to a protective immune response. These studies are a necessary step to a more detailed understanding of host immune responses protective against tuberculosis, and development and testing of new therapeutic and intervention strategies to prevent this disease.