Massively parallel mapping of all molecular interactions in a single tube

单管中所有分子相互作用的大规模并行映射

• 批准号: 9145743
• 负责人: Saeed F Tavazoie
• 金额: $ 65.03万
• 依托单位: COLUMBIA UNIVERSITY HEALTH SCIENCES
• 依托单位国家: 美国
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-09-21 至 2020-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9145743
• 关键词: Affect; Architecture; Binding; Biological Assay; Biological Process; Biology; Cell physiology; Cells; Chemicals; Communities; Computing Methodologies; DNA; Data; Development; Disease; Engineering; Environment; Enzymes; Event; Evolution; Genomics; Health; High-Throughput Nucleotide Sequencing; Human; Hybrids; Knowledge; Laboratories; Lead; Libraries; Life; Ligation; Maps; Measurement; Measures; Mediating; Messenger RNA; Methods; Modeling; Molecular; Monitor; Nature; Nucleic Acids; Organism; Pathway interactions; Patient Self-Report; Pharmaceutical Preparations; Physiological; Population Heterogeneity; Process; Proteins; RNA; RNA-Protein Interaction; Reaction; Reading; Research; Research Personnel; Robotics; Scheme; Surveys; System; Systems Biology; Technology; Temperature; Textbooks; Time; Tube; Variant; Vision; Work; Yeasts; base; computerized tools; cost; design; high throughput technology; in vivo; innovation; insight; interest; molecular recognition; network architecture; new technology; novel; protein aminoacid sequence; rapid detection; research study; response; scaffold; transcriptomics; yeast two hybrid system

 DESCRIPTION (provided by applicant): Molecular interactions are at the core of all biological processes. Despite the existence of powerful methods such as the yeast two-hybrid and its variants, comprehensive quantitative surveys of molecular interactions remain low-throughput, costly, labor-intensive, and suffer from biases that limit coverage to only a few percent of all possible interactions. A major challenge in biology is to develop novel methods that allow rapid, near- comprehensive coverage of all bi-molecular interactions. If they were available, such ultra-deep interactome maps will revolutionize biology by providing a rich knowledge scaffold for a systems-level understanding of biological processes and their high-level organization. We propose to develop a revolutionary ultra-high- throughput technology to easily and comprehensively map protein-protein, protein-DNA, and protein-RNA interactions in any organism of interest. The technology will be: (1) ultra-high-throughput, allowing a single investigator to conduct a deep and comprehensive survey of all pair-wise interactions (e.g. ~109 for all human proteins) in a single tube; (2) It will have the sensitivity and dynamic-range to provide a quantitative readout of interaction-strengths; (3) It will be extremely fast, enabling a single investigator to conduct a global survey on the timescale of a few days; (4) It will enable the monitoring of interactome dynamics-as a function of cellular- state or other perturbations; (5) it will capture the native in vivo physiological state of proteins; and (6) It will be extremely lo-cost and not require the use of specialized robotics or large laboratory real estate. The comprehensive and quantitative nature of these maps will allow us to go beyond the current low-hanging-fruit limits, and for the first time, measure the entire distribution of interaction strengths. This capacity will reveal an unbiased view of connectivity and modularity, potentially revamping our fundamental understanding of molecular network evolution and function. The unprecedented scale of these observations will present unique opportunities for extracting novel insights that are not possible with the low coverage and sparsity of existing technologies. In the second major aim, with the development of computational tools, we aim to achieve a predictive understanding of the observed molecular interactions in terms of nucleic-acid and peptide sequence- motifs that mediate interactions. The astronomical scale of these observations may enable a new plateau in understanding and modeling molecular recognition rules, paving the way for ab initio engineering of molecular network architecture and dynamics.

 描述(申请人提供)：分子相互作用是所有生物过程的核心。尽管存在强大的方法，如酵母双杂交及其变种，但分子相互作用的全面定量调查仍然低通量、昂贵、劳动密集型，并且存在将覆盖范围限制在所有可能的相互作用的几个百分点的偏差。生物学中的一个主要挑战是开发新的方法，允许快速、近乎全面地覆盖所有双分子相互作用。如果它们可用，这种超深度相互作用组图将通过为系统级理解生物过程及其高级组织提供丰富的知识支架，从而使生物学发生革命性变化。我们建议开发一种革命性的超高通量技术，以方便和全面地绘制任何感兴趣生物中的蛋白质-蛋白质、蛋白质-DNA和蛋白质-RNA相互作用图。这项技术将是：(1)超高通量，允许一名研究人员在一个试管中对所有成对相互作用进行深入和全面的调查(例如，所有人类蛋白质的~109)；(2)它将具有灵敏度和动态范围，以提供相互作用强度的定量读数；(3)它将非常快，使一名研究人员能够在几天的时间尺度上进行全球调查；(4)它将能够监测相互作用组的动态--作为细胞状态或其他扰动的函数；(5) 它将捕捉蛋白质在体内的自然生理状态；以及(6)它的成本非常低，不需要使用专门的机器人或大型实验室。这些地图的全面性和量化性质将使我们能够超越目前低挂果的限制，并首次衡量互动强度的整个分布。这种能力将揭示连接和模块化的不偏不倚的观点，潜在地改变我们对分子网络进化和功能的基本理解。这些观察的前所未有的规模将为提取新的见解提供独特的机会，而现有技术的低覆盖率和稀疏性是不可能的。在第二个主要目标中，随着计算工具的发展，我们的目标是根据介导相互作用的核酸和肽序列基序来实现对观察到的分子相互作用的预测性理解。这些观测的天文尺度可能会在理解和模拟分子识别规则方面达到一个新的平台，为分子网络结构和动力学的从头工程铺平道路。