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EAGER: Comprehensive monitoring of protein interaction networks

EAGER: Comprehensive monitoring of protein interaction networks
EAGER:蛋白质相互作用网络的全面监测
批准号:
2224211
负责人:
Marko Jovanovic
金额:
$30.0万
依托单位:
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2022
资助国家:
美国
项目状态:
已结题
起止时间:
2022-07-01 至 2024-06-30

项目摘要

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中文摘要
翻译
基因组为数千种蛋白质编码信息,这些蛋白质构成了所有生物体中细胞机制的基石。蛋白质通常不是孤立地起作用,而是在多组分复合物中起作用,因此,大多数重要的细胞功能是由蛋白质之间的基本相互作用控制的。这些蛋白质相互作用网络是动态的,相互作用的变化是引起细胞和机体功能生理和病理变化的主要原因。因此,必须有通用且易于实现的工具,使科学家能够测量蛋白质相互作用的动力学。该项目旨在开发这样一种工具,它将允许研究人员同时绘制多达数百种蛋白质在许多条件下的动态蛋白质相互作用图。这种新颖的方法将解决生物学中的许多关键问题,例如相互作用的变化驱动发育决定或由于导致病理结果的突变而发生。此外,该项目在推进生物技术方面具有很大的潜力,例如,通过系统地筛选候选药物,以确定其是否有能力特异性地破坏驱动疾病状态的蛋白质相互作用。该项目还为研究生和本科生提供跨学科的研究培训机会。该项目将采用一种新的抗体和基于测序的策略来绘制蛋白质相互作用及其变化。该战略有两个基本组成部分。首先,抗体是由一个短的DNA序列唯一的“条形码”,因此每个抗体及其靶蛋白可以很容易地通过下一代测序来识别。其次,组合条形码策略,通过溢出和池程序,添加独特的组合DNA序列到条形码抗体。只有与相同蛋白质复合物结合的抗体才会得到相同的组合条形码,通过对这些条形码进行测序和匹配,可以重建蛋白质相互作用。总之,本项目旨在提供一种简单的方法,以高通量直接研究蛋白质相互作用动力学,但同时在单一复杂的分辨率。该奖项反映了美国国家科学基金会的法定使命,并通过使用基金会的知识价值和更广泛的影响审查标准进行评估,被认为值得支持。
英文摘要
The genome encodes information for thousands of proteins, which form the building blocks of cellular machinery in all organisms. Proteins normally do not function in isolation, but rather in multi-component complexes, such that most vital cellular functions are governed by essential interactions between proteins. These protein interaction networks are dynamic, and changes in the interactions are the major cause of physiological and pathological changes in cellular and organismal function. Thus, it is essential to have universal and easily implementable tools that allow scientists to measure the dynamics of protein interactions. This project aims to develop such a tool, which will allow researchers to simultaneously map dynamic protein interactions for up to hundreds of proteins under many conditions. This novel approach will address many key issues in biology, such as which interaction changes drive developmental decisions or occur due to mutations that lead to pathological outcomes. Moreover, the project has high potential to advance biotechnology, for example, by making it possible to systematically screen drug candidates for the ability to specifically disrupt protein interactions that drive a disease state. The project also provides cross-disciplinary research training opportunities for graduate and undergraduate students.The project will employ a new antibody and sequencing-based strategy in order to map protein interactions and their changes. There are two fundamental components to the strategy. First, antibodies are uniquely “barcoded” by a short DNA sequence so that each antibody – and by extension, its target protein – can be easily identified by next-generation sequencing. Second, a combinatorial barcoding strategy, via a spilt and pool procedure, adds unique combinatorial DNA sequences to the barcoded antibodies. Only antibodies co-bound to the same protein complex will get the same combinatorial barcode and protein interactions can be reconstructed by sequencing and matching these barcodes. In summary, this project aims to provide a facile approach to directly study protein interaction dynamics at high throughput, but at the same time at single complex resolution.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
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