Understanding host-virus interactions at the single cell level

了解单细胞水平的宿主-病毒相互作用

• 批准号: 9377495
• 负责人: David A VAN VALEN
• 金额: $ 6.48万
• 依托单位: STANFORD UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-05-04 至 2018-04-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9377495
• 关键词: Algorithms; Automobile Driving; Bacteria; Bacterial Physiology; Bacteriophage lambda; Bacteriophages; Benign; Biochemical; Biological Models; Biology; Carbon; Cell Size; Cells; Computer Vision Systems; Consensus; Coupled; Cytolysis; DNA; Data; Data Analyses; Decision Making; Development; Disease; Enzymes; Escherichia coli; Genetic; Genetic Materials; Genome; Goals; Health; Horizontal Gene Transfer; Human; Image; Individual; Infection; Label; Learning; Libraries; Literature; Lysogeny; Lytic; Manuals; Measurement; Measures; Mediating; Modeling; Modern Medicine; Modernization; Molecular; Molecular Target; Outcome; Peptide Hydrolases; Phosphorus; Physiological; Physiology; Plasmids; Play; Probability; Process; Proteins; Regulatory Element; Reporter; Reporting; Resistance; Role; Source; System; Technology; Temperature; Testing; Viral Physiology; Viral Proteins; Viral Regulatory Proteins; Virus; Weight; Work; base; cellular imaging; experimental study; genetic regulatory protein; imaging Segmentation; live cell imaging; microbial; new technology; novel; pathogen; protein function; public health relevance; transcription factor; virus host interaction

 DESCRIPTION (provided by applicant): The microbial world presents one of the largest challenges to modern medicine in the 21st century in the form of novel, untreatable pathogens. Bacteriophages, the viruses that infect bacteria, are a major driver of this challenge. In particular, bacteriophages mediate the exchange of novel genetic materials (a process known as horizontal gene transfer, or HGT) between bacteria, transforming otherwise benign bacteria into human pathogens and driving the rapid emergence of pathogens resistant to existing treatments. Accordingly, there is a critical need to elucidate when, where, and how phage-mediated HGT occurs. One critical aspect of phage-mediated HGT is lysogenization, the process by which phage DNA is integrated into the host bacterium's genome. Which bacterial cells are capable of being lysogenized and how the process of lysogenization is coupled to the physiology of the host bacterial cell are key questions in phage biology that remain unanswered. Recent technological advances in computer vision and single-cell imaging along with our lab's existing expertise in bacterial physiology enable us to interrogate this model system with unprecedented precision and find concrete answers to these long standing questions. We therefore propose to study these questions using E. coli and phage lambda as our initial model system. Our guiding hypothesis is that the physiology of the host bacterial cells plays a critical role in the occurrence of lysogeny. Interrogating this problem of bacteria-phage interactions requires a systems level view of bacterial physiology and detailed dynamic measurements of lysogeny development. The goal of this proposal is to develop a system capable of measuring the activities of viral transcription factors, host proteins, and infection outcomes simultaneously in single cells. The analysis and interpretation of these data will lead to the discovery of novel host-virus interactions underlying lysogenic development and ultimately identify molecular targets that can be exploited to suppress phage-mediated horizontal gene transfer.

 描述（由适用提供）：微生物世界以新颖，不可治疗的病原体的形式提出了21世纪现代医学的最大挑战之一。噬菌体是感染细菌的病毒，是这一挑战的主要驱动力。特别是，细菌噬菌体介导细菌之间的新型遗传材料（一种称为水平基因转移或HGT的过程）的交换，否则将良性细菌转化为人类病原体，并推动病原体对现有治疗有抗性的快速出现。彼此之间，迫切需要阐明何时，何地和噬菌体介导的HGT发生。噬菌体介导的HGT的一个关键方面是溶酶体化，这是将噬菌体DNA整合到宿主细菌基因组中的过程。哪些细菌细胞能够被溶性化，以及如何与宿主细菌细胞的生理学结合的溶酶体化过程是噬菌体生物学的关键问题，尚未得到解决。计算机视觉和单细胞成像的最新技术进步以及我们实验室现有的细菌生理学专业知识使我们能够以前所未有的精度询问该模型系统，并找到这些长期存在的问题的具体答案。因此，我们建议使用大肠杆菌和噬菌体Lambda作为我们的初始模型系统研究这些问题。我们的指导假设是宿主细菌细胞的生理学作用至关重要 在发生溶酶体的发生中的作用。询问这种细菌 - 含量相互作用的问题需要细菌生理学的系统级别视图和溶液发育的详细动态测量。该提案的目的是开发一个能够简单地测量病毒转录因子，宿主蛋白和感染结果的活动的系统 在单细胞中。这些数据的分析和解释将导致发现溶菌发生发展的新型宿主病毒相互作用，并最终识别可以探索可以抑制噬菌体介导的水平基因转移的分子靶标。

项目成果

Deep Learning Automates the Quantitative Analysis of Individual Cells in Live-Cell Imaging Experiments.

• DOI: 10.1371/journal.pcbi.1005177
• 发表时间: 2016-11
• 期刊: PLoS computational biology
• 影响因子: 4.3
• 作者: Van Valen DA;Kudo T;Lane KM;Macklin DN;Quach NT;DeFelice MM;Maayan I;Tanouchi Y;Ashley EA;Covert MW
• 通讯作者: Covert MW