QUANTIFYING THE BALANCE BETWEEN VACCINE-INDUCED T CELL PROTECTION AND PATHOLOGY

持续的病毒感染(如丙型肝炎病毒和艾滋病毒)仍然是 人类健康，并且没有屈服于传统的疫苗生产方法。 T细胞反应被认为在对抗许多持续性免疫反应中起着关键作用 病毒感染，是许多候选疫苗的重点。一个关键问题是我们的 对T细胞反应发生在什么情况下的理解不完全 感染导致保护，当它引起病理时。 我们的方法包括从目前的定性描述转向定量模型 为了了解在持续病毒感染期间病毒和T细胞反应的动态- 美味佳肴。定量模型的发展在免疫学和 发病机制有两个原因：一是病毒群体和T细胞的适应性免疫。 在感染过程中，MUNE反应的幅度可以变化一千倍以上； 第二，系统各组成部分(病原体、细胞)之间的非线性相互作用 和免疫反应的分子)可以导致复杂的动力学，而不是 仅从定性描述中得出结论。由于生物系统的复杂性，它是 对于要验证的数学模型是必不可少的。我们将通过与他们对抗来测试我们的模型 用小鼠淋巴细胞性脉络膜脑膜炎病毒(LCMV)感染的实验数据。我们 我将通过将模型与病毒和免疫的动态数据进行匹配来验证我们的模型 在持续LCMV感染期间的响应，以及生成和实验测试 对该模型的新奇预测。LCMV系统特别适合于研究PRO- 疫苗接种后的保护和病理，因为易于通过转移明确的 受体小鼠体内的病毒特异性T细胞群允许对这两个数字进行操作 以及宿主环境，从而促进了对T细胞的解剖 控制病毒和减少病理的因素。 我们将应用我们的定量数学模型来探索新的治疗策略。 以及针对持久性病原体的疫苗接种。这些策略涉及组合使用 抗病毒药物和重新激活T细胞反应的免疫调节抗体。我们会 在LCMV实验系统上对这些策略进行了测试。

Persistent virus infections (such as the hepatitis C virus and HIV) remain major problems for human health, and have not yielded to traditional approaches for the generation of vaccines. T cell responses are thought to play a key role in the immune response against many persistent viral infections, and are the focus of many vaccine candidates. A key problem is our incomplete understanding of the circumstances under which the T cell response following infection results in protection and when it causes pathology. Our approach involves going from the current qualitative description to a quantitative models for understanding the dynamics of the virus and T cell response during persistent virus in- fections. The development of quantitative models is particularly important in immunology and pathogenesis for two reasons: first, the populations of virus and the T cells of the adaptive im- mune response can change over a thousand fold in magnitude during the course of infection; second, the non-linear interactions between the components of the system (pathogens, cells and molecules of the immune response) can result in complex dynamics that cannot be intu- ited from qualitative descriptions alone. Because of the complexity of biological systems, it is essential for mathematical models to be validated. We will test our models by confronting them with experimental data from Lymphocytic choriomeningitis virus (LCMV) infections of mice. We will validate our models by fitting the models to data on the dynamics of virus and immune responses during persistent LCMV infections, as well as generating and experimentally testing novel predictions of the model. The LCMV system is particularly amenable to studying pro- tection and pathology following vaccination because the ease of adoptive transfer of defined virus-specific T cell populations into recipient mice allows manipulation of both the numbers and properties of the T cells, as well as the host environment, thus facilitating dissection of the factors that control virus and reduce pathology. We will apply our quantitative mathematical models to explore novel strategies for treatment and vaccination against persistent pathogens. These strategies involve the combined use of antiviral drugs and immune-modulating antibodies that reactivate the T cell response. We will test these strategies in the LCMV experimental system.