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

量化疫苗诱导的 T 细胞保护与病理学之间的平衡

• 批准号: 8793097
• 负责人: RUSTOM NOSHIR ANTIA
• 金额: $ 38.7万
• 依托单位: EMORY UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-02-01 至 2019-01-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8793097
• 关键词: Acute; Address; Adoptive Transfer; Antibodies; Antigens; Antiviral Agents; Avidity; Biological Models; Blocking Antibodies; CD8B1 gene; Cell division; Cells; Combined Modality Therapy; Complex; Data; Death Rate; Development; Dissection; Dose; Drug usage; Environment; Epitopes; Equilibrium; Generations; Grant; HIV; Health; Hepatitis C; Hepatitis C virus; Human; Immune; Immune response; Immunity; Immunology; Infection; Infection Control; Intervention; Lymphocytic choriomeningitis virus; Measurement; Memory; Modeling; Mus; Outcome; Pathogenesis; Pathology; Pathway interactions; Play; Population; Property; Proteins; Ribavirin; Role; Staging; System; T Virus; T cell response; T-Lymphocyte; T-Lymphocyte Epitopes; Testing; Time; Vaccination; Vaccines; Variant; Viral load measurement; Virus; Virus Diseases; Work; adaptive immunity; base; biological systems; cell killing; clinical application; exhaustion; habituation; killings; mathematical model; mouse model; novel; novel strategies; pathogen; research study; response; treatment strategy; vaccine candidate; vaccine-induced immunity

DESCRIPTION: 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 infections. 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 immune 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 intuited 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 protection 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 vius 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.

产品说明：持续性病毒感染（如丙型肝炎病毒和艾滋病毒）仍然是人类健康的主要问题，并没有屈服于传统的疫苗生产方法。T细胞应答被认为在针对许多持续性病毒感染的免疫应答中起关键作用，并且是许多候选疫苗的焦点。一个关键的问题是我们对感染后T细胞反应产生保护作用的情况以及何时引起病理学的不完全理解。我们的方法涉及从目前的定性描述到定量模型，以了解持续病毒感染期间病毒和T细胞反应的动态。定量模型的发展在免疫学和发病机制中特别重要，原因有二：第一，在感染过程中，适应性免疫应答的病毒群体和T细胞的数量可以变化一千倍以上;第二，系统各组成部分之间的非线性相互作用（病原体、免疫反应的细胞和分子）可能导致复杂的动力学，不能仅从定性描述中直观地看出。由于生物系统的复杂性，数学模型的有效性是必不可少的。我们将测试我们的模型，面对他们的实验数据，从淋巴细胞脉络丛脑膜炎病毒（LCMV）感染的小鼠。我们将通过将模型拟合到持续LCMV感染期间病毒和免疫反应动态的数据，以及生成和实验测试模型的新预测来验证我们的模型。LCMV系统特别适合于研究疫苗接种后的保护和病理学，因为将限定的病毒特异性T细胞群过继转移到受体小鼠中的容易性允许操纵T细胞的数量和性质以及宿主环境，从而促进控制病毒和减少病理学的因子的解剖。我们将应用我们的定量数学模型来探索针对持久性病原体的治疗和疫苗接种的新策略。这些策略包括联合使用抗病毒药物和免疫调节抗体，重新激活T细胞反应。我们将在LCMV实验系统中测试这些策略。