基本信息
浏览量:3
职业迁徙
个人简介
My laboratory is primarily focused on understanding how heterogeneity and collective interactions within virus populations influence broader patterns of viral evolution and infection outcomes. Influenza virus populations are enormously heterogeneous, and most viral particles carry a functionally incomplete set of gene segments and thus cannot replicate independently. Rather than serving as dead-end products, widespread co-infection in vivo allows these incomplete particles to replicate and exchange gene segments through complementation. Collective interactions between heterogeneous particles can have profound effects on the behavior of the population as a whole, and the outcome of infection. We and our collaborators are currently employing a wide range of approaches spanning molecular virology, cell biology, evolutionary biology, single cell microfluidics, bioinformatics, and mathematical modeling to better understand this crucial, under-explored area of virus biology.
We are also interested in understanding the genetics of influenza virus immune escape and transmission, with the overall goal of improving strategies for universal vaccination. The specific factors that govern the continual antigenic evolution of influenza virus within the human population remain poorly understood. We have developed improved methods for ultra-deep viral population sequencing that allow us to dissect the process of antigenic evolution within and transmit between hosts like never before.
Specific areas of study within the lab include:
Defining how patterns of viral heterogeneity and collective interactions within viral populations influence their evolutionary and pathogenic potential.
Understanding how cellular heterogeneity and stochastic patterns of antiviral immune induction shape the host response to infection.
Defining the epistatic interactions between viral gene segments and determining how they influence viral evolution.
Using single-particle/single-cell analysis to examine how the interplay between viral and host heterogeneity shapes infection outcome.
Employing ultra-deep population sequencing methods to understand how influenza populations maintain fitness while evading host immunity.
研究兴趣
论文共 64 篇作者统计合作学者相似作者
按年份排序按引用量排序主题筛选期刊级别筛选合作者筛选合作机构筛选
时间
引用量
主题
期刊级别
合作者
合作机构
JOURNAL OF VIROLOGYno. 1 (2024): e0161823-e0161823
JOURNAL OF VIROLOGYno. 1 (2024): e0179123-e0179123
Tongyu Liu, William K. Reiser,Timothy J C Tan,Huibin Lv,Joel Rivera-Cardona, Kyle Heimburger, Nicholas C Wu,Christopher B. Brooke
biorxiv(2024)
Natureno. 7958 (2023): 668-669
Nature Microbiologyno. 7 (2023): 1195-1196
加载更多
作者统计
合作学者
合作机构
D-Core
- 合作者
- 学生
- 导师
数据免责声明
页面数据均来自互联网公开来源、合作出版商和通过AI技术自动分析结果,我们不对页面数据的有效性、准确性、正确性、可靠性、完整性和及时性做出任何承诺和保证。若有疑问,可以通过电子邮件方式联系我们:report@aminer.cn