Bacterial Determinants of Tuberculosis Susceptibiliy

项目2：敏感性的细菌决定因素 摘要： 结核病感染的结果在个体之间差异很大;大多数人没有表现出结核病的迹象。 疾病，但有些人会出现疾病进展。这些结果上的差异似乎是由 因为人与人之间的差异，也因为分枝杆菌菌株之间的差异， 他们感染的肺结核。事实上，人类基因差异似乎与细菌相互作用， 差异，使得相同的细菌可能能够在一个宿主中引起疾病，而不是另一个宿主， 同样，一个人可能对某种细菌敏感，但对另一个人却不敏感。在这个项目中，我们力求 理解细菌特征与宿主遗传学的交叉，我们称之为“宿主-病原体” 偏好”。在目标1中，我们将通过测试来定义影响宿主-病原体偏好的细菌因素 大量的M.一组高度多样化的小鼠中的结核菌株（ CC小鼠）。我们将确定细菌和宿主的遗传标记，以确定很可能导致 并将测试这些标记物预测人类疾病的能力。目标2，我们将确定 某些细菌菌株比其他菌株更具毒性的机制。最后，在目标3中，我们将测试 假设BCG疫苗接种可防止某些M.结核菌株而不是其他菌株。 这些研究也将使我们能够开发M的实验模型。结核病感染，反映了 人类面临的细菌多样性，并为更成功的疫苗和治疗提供了途径 试验.

Project 2: Bacterial Determinants of Susceptibility Abstract: The outcome of tuberculosis infection varies tremendously between individuals; most people show no signs of disease but some people will develop progressive disease. These differences in outcome seem to arise both because of differences between people but also because of differences between the strains of Mycobacterium tuberculosis with which they are infected. Indeed, human genetic differences seem to interact with bacterial differences such that the same bacterium may be able to cause disease in one host but not another and similarly, one person may be susceptible to a given bacterium but not another. In this project, we seek to understand this intersection of bacterial features with host genetics, which we term “host-pathogen preference”. In Aim 1, we will define the bacterial factors that influence host-pathogen preference by testing the growth of a very large number of M. tuberculosis strains in a panel of mice bred to be highly diverse (the CC mice). We will identify bacterial and host genetic markers for interactions that are very likely to cause disease and will test the ability of these markers to predict human disease. Aim 2, we will determine the mechanisms by which some bacterial strains are more virulent than others. Finally, in Aim 3, we will test the hypothesis that BCG vaccination protects against infection with some M. tuberculosis strains but not others. These studies will also allow us to develop experimental models of M. tuberculosis infection that reflect the diversity of bacteria that humans face and provide an avenue for more successful vaccine and therapeutic testing.