A Mixed-Bait-Strategy for Protein Interactome Mapping

描述（由申请人提供）：在全基因组范围内了解蛋白质功能是生物学的主要目标。实现这一目标的重要一步是解开蛋白质相互作用组网络。尽管在高通量技术方面取得了进展，但具有蛋白质组范围覆盖的文库对文库筛选仍然是一项艰巨的任务。该建议提出了一种新的合并和去卷积策略（MBS），通常适用于在各种情况下最大限度地提高筛选效率。MBS有三个关键组成部分：诱饵的假想标记（二进制编码）、组合混合诱饵筛选以及内置的猎物-诱饵跟踪和交叉验证。MBS达到显着更高的覆盖率比传统的单诱饵策略下的实验误差很大。MBS具有极大地加速从酵母到人类的相互作用组作图的潜力，并且对于许多其他库对库筛选（包括药物筛选）是有用的。MBS的主要优势包括更好的准确性，覆盖范围和效率。它的多功能性在于虚拟标记，无论查询的性质如何（分子，细胞，生物体等），它都是普遍适用的。蛋白质-蛋白质相互作用（PPI）是多种生理和疾病过程的基础。尽管在高通量技术的进步，大规模的PPI映射仍然是一个艰巨的任务，由于时间和资源的巨大需求。我们引入了一种新的策略（称为MBS），它将大大减少所需的屏幕数量，同时提高准确性和覆盖率。MBS指导的社区努力将大大加速从酵母到人类的相互作用组映射，并发现许多其他生物医学应用。

DESCRIPTION (provided by applicant): Understanding protein function on a genome-wide scale is a main goal of biology. An important step towards achieving this goal is through unraveling protein interactome networks. Despite advances in high- throughput technologies, library-against-library screening with proteome-wide coverage remains a daunting task. This proposal presents a novel pooling and deconvolution strategy (MBS) that is generally applicable to maximize screening efficiency in a wide variety of situations. MBS has three key components: imaginary tagging (binary coding) of baits, combinatorial mix-bait screening, and built-in prey-bait tracking and cross- validation. MBS reaches significantly higher coverage than conventional single-bait strategy under a wide range of experimental errors. MBS has the potential to greatly accelerate interactome mapping from yeast to human and is useful for many other library-against-library screens (including drug screening). The key advantages of MBS include better accuracy, coverage, and efficiency. Its versatility lies in imaginary tagging, which is universally applicable regardless of the nature of the query (molecules, cells, organisms, etc). Protein-protein interactions (PPIs) underlie a wide range of physiological and disease processes. Despite advances in high-throughput technologies, large-scale PPI mapping remains a daunting task due to the huge demand of time and resources. We introduce a novel strategy (called MBS) that will greatly reduces the number of screens needed while simultaneously increasing accuracy and coverage. MBS-guided community efforts should greatly accelerate interactome mapping from yeast to human, and find many other biomedical applications.