Evolution of Virus-Host Interactions

病毒与宿主相互作用的演变

基本信息

批准号：
8389655
负责人：
John Yin
金额：
$ 35.68万
依托单位：
UNIVERSITY OF WISCONSIN-MADISON
依托单位国家：
美国
项目类别：
财政年份：
2010
资助国家：
美国
起止时间：
2010-12-03 至 2015-11-30
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/8389655
关键词：
Acquired Immunodeficiency Syndrome Address Advanced Development Basic Science Cell physiology Cells Common Cold Computer Simulation Data Disease Environment Evolution Exhibits Gene Order Goals Growth Health Hepatitis Human Infection Influenza Integration Host Factors Knowledge Laboratories Learning Malignant Neoplasms Measures Medical Methodology Methods Modeling Molecular Molecular Models Nature Oncolytic Organism Population Process Protein Biosynthesis Relative (related person)Research Resources Rest Serial Passage Structure Systems Biology Therapeutic Time Variant Vesicular stomatitis Indiana virus Viral Virus Virus Diseases Virus-Cell Membrane Interaction Work base cancer therapy design fighting fitness human disease insight molecular modeling mutant novel vaccines predictive modeling public health relevance research study therapy development tumor virus host interaction

项目摘要

DESCRIPTION (provided by applicant): Viruses pose a significant threat to human health based on their ability to cause diseases such as AIDS, influenza, hepatitis, cancer and the common cold. Basic research has revealed much about the molecular details of processes that are essential for viruses to reproduce, but a critical barrier to further progress is a lack of understanding of how factors of the host environment quantitatively impact virus growth. The proposed research aims to address this barrier by advancing new quantitative experiments and computational models of virus growth. The approach will employ, combine and extend perspectives drawn from the fields of experimental evolution and systems biology. Specific aims of the proposed project will be to: (1) advance computational models of virus growth to provide an integrated dynamic measure of cellular resource use, (2) quantify how resource use is altered during evolutionary adaptation of virus to host cells, and (3) elucidate mechanisms by which viral adaptation alters resource use. The methodology established by this research will set a basis for advancing the development of data-driven predictive models of virus growth. Results of the research will have the potential to significantly impact several fields: the design anti-viral therapeutics, applications of viruses in oncolytic (anti-tumor) cancer therapies, and development of new vaccines. At a more basic level, predictive models of virus growth will be useful for better understanding how viruses grow, evolve and persist in Nature.

描述（由申请人提供）：病毒对人类健康构成重大威胁，因为它们能够引起艾滋病、流感、肝炎、癌症和普通感冒等疾病。基础研究已经揭示了许多关于病毒繁殖所必需的过程的分子细节，但进一步进展的一个关键障碍是缺乏对宿主环境因素如何定量影响病毒生长的了解。拟议的研究旨在通过推进新的病毒生长定量实验和计算模型来解决这一障碍。该方法将采用、结合和扩展实验进化和系统生物学领域的观点。该项目的具体目标是：（1）推进病毒生长的计算模型，以提供细胞资源使用的综合动态测量，（2）量化病毒在进化适应宿主细胞过程中资源使用如何改变，以及（ 3）阐明病毒适应改变资源利用的机制。这项研究建立的方法将为推进数据驱动的病毒生长预测模型的开发奠定基础。研究结果将有可能对多个领域产生重大影响：抗病毒疗法的设计、病毒在溶瘤（抗肿瘤）癌症疗法中的应用以及新疫苗的开发。在更基础的层面上，病毒生长的预测模型将有助于更好地了解病毒如何在自然界中生长、进化和持续存在。