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PPiSeq: High-Throughput Protein-Protein Interaction Sequencing

PPiSeq：高通量蛋白质-蛋白质相互作用测序

基本信息

批准号：
10653194
负责人：
Gavin J Sherlock
金额：
$ 41.16万
依托单位：
STANFORD UNIVERSITY
依托单位国家：
美国
项目类别：
财政年份：
2015
资助国家：
美国
起止时间：
2015-09-16 至 2025-06-30
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10653194
关键词：
Animals Antiviral Agents Bar Codes Biological Assay Cell Culture Techniques Cell physiology Cells Communication Communities Complement Cowpox DHFR gene Data Data Set Dihydrofolate Reductase Drug Screening Drug Targeting Epidemic Funding Genes Grant Health Hepatitis E Herpesviridae Human Infection Influenza B Virus Influenza C Virus Learning Libraries Maps Measures Molecular Mutagenesis Natural regeneration Open Reading Frames Output Pathway interactions Pharmaceutical Preparations Process Protein Fragment Protein-Protein Interaction Map Proteins Rabies Readiness Research Resources Scanning System Technology Testing Variant Viral Viral Proteins Virulence Virus Work Yeasts Zoonoses dimer drug testing gene synthesis genetic analysis genetic variant genome-wide high throughput screening human coronavirus human population genetics particle pathogenic virus protein protein interaction screening sequencing platform small molecule small molecule libraries zoonotic spillover

项目摘要

Project Summary/Abstract Emerging and endemic viral pathogens are a persistent threat to human health, the global economy, and national readiness. Viral proteins interact with host proteins to hijack host cells and replicate transmissible viral particles. Human-viral and viral-viral protein-protein interactions (PPls) have been comprehensively characterized for a limited set of viruses, identifying a "PPI profile" for each virus screened. However, these efforts have characterized only a small fraction of the known viruses. A complete viral-human PPI map would be an invaluable resource, enabling analyses of how often interacting viral proteins converge on common human protein targets, cellular functions, or pathways, and which of these interactions are associated with transmissibility or virulence. Combining the viral-human PPI map with human population genetic analyses will enable characterization of the molecular mechanisms underlying extant and ancient epidemics and how these PPIs drive much of human adaptation. In addition, PPI profiles of human viruses could be used to aid screening of animal reservoirs to identify potential threats before a zoonotic spillover occurs. Despite its great promise, characterization of the viral-human PPI map remains a challenge given the throughput of current viral-human PPI screening assays. Current high-throughput assays also lack a quantitative output, meaning that the emergent human-viral PPI map, or viral-viral PPI maps, would be difficult to exploit for important downstream variant scanning or drug screening applications. Here we will use a quantitative sequencing-based protein-protein interaction assay platform to screen for PPls between -24 million viral-human or viral-viral protein pairs. We will further develop this technology into a massively parallel drug screening platform and use it to screen >3 million drug-PPI combinations for small-molecule compounds that promote or antagonize a PPI. The viral-human PPI and drug-PPI maps developed here will be an invaluable resource for a broad research community. In addition, this work will establish new massively parallel and quantitative PPI and drug-PPI screening technologies that will scale with advances in gene synthesis, mutagenesis and sequencing, enabling parallel screening of tens of thousands of gene and gene variants of extant, emerging, and potentially zoonotic viruses.

项目摘要/摘要新出现的和地方性的病毒病原体是对人类健康、全球经济和国家准备的持续威胁。病毒蛋白与宿主蛋白相互作用，劫持宿主细胞，复制可传播的病毒颗粒。人类-病毒和病毒-病毒蛋白-蛋白相互作用(PPL)已经针对有限的一组病毒进行了全面的表征，为每一种筛选的病毒确定了“PPI图谱”。然而，这些努力只表现出已知病毒中的一小部分。完整的病毒-人类PPI图谱将是一个宝贵的资源，可以分析相互作用的病毒蛋白多久会聚在共同的人类蛋白质靶标、细胞功能或途径上，以及这些相互作用中的哪些与传播性或毒力有关。将病毒-人类PPI图谱与人类种群遗传分析相结合，将能够描述现存和古代流行病背后的分子机制，以及这些PPI如何驱动人类的大部分适应。此外，人类病毒的PPI图谱可以用来帮助筛选动物宿主，以便在人畜共患病溢出发生之前识别潜在的威胁。尽管前景看好，但考虑到目前病毒-人PPI筛查分析的吞吐量，病毒-人PPI图谱的表征仍然是一个挑战。目前的高通量分析也缺乏定量输出，这意味着新出现的人-病毒PPI图谱，或病毒-病毒PPI图谱，将难以用于重要的下游变异扫描或药物筛选应用。在这里，我们将使用基于定量测序的蛋白质-蛋白质相互作用分析平台来筛选-2400万病毒-人类或病毒-病毒蛋白质对之间的ppls。我们将进一步将这项技术发展成为大规模并行药物筛选平台，并利用它筛选300万种药物-PPI组合，以寻找促进或拮抗PPI的小分子化合物。这里开发的病毒-人PPI和药物-PPI图将是广泛研究社区的宝贵资源。此外，这项工作将建立新的大规模并行和定量的PPI和药物PPI筛选技术，这些技术将随着基因合成、突变和测序方面的进展而扩大规模，使并行筛选现有的、新出现的和潜在的人畜共患病病毒的数万个基因和基因变体成为可能。

项目成果

期刊论文数量（15）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

iSeq 2.0: A Modular and Interchangeable Toolkit for Interaction Screening in Yeast.

DOI：
10.1016/j.cels.2019.03.005
发表时间：
2019-04
期刊：
Cell systems
影响因子：
9.3
作者：
Xianan Liu;Zhimin Liu;Adam Dziulko;Fangfei Li;Darach Miller;Robert D Morabito;Danielle Francois;Sasha F. Levy
通讯作者：
Xianan Liu;Zhimin Liu;Adam Dziulko;Fangfei Li;Darach Miller;Robert D Morabito;Danielle Francois;Sasha F. Levy

The interplay of additivity, dominance, and epistasis on fitness in a diploid yeast cross.