2022年3月11日出版的《科学》杂志发表了美国科学家的一项最新研究成果。来自陈·扎克伯格研究中心
研究人员将基因组工程、共聚焦活细胞成像、质谱分析和数据科学结合起来，系统地绘制人类蛋白质的定位和相互作用。这个方法对组织蛋白质组的分子和空间网络进行了数据驱动的描述。这些网络的无监督聚类划定了促进生物发现的功能社区。
研究人员发现，从蛋白质的定位模式中可以得到非常精确的功能信息，这些模式通常包含足够的信息来识别分子相互作用，RNA结合蛋白形成了一个由独特的相互作用和定位特性定义的特定亚群。与一个完全互动的网站（opencell.czbiohub.org）相配，这项工作构成了人类细胞组织的定量制图资源。
据介绍，阐明人体细胞的线路图是后基因组时代的一个核心目标。
附：英文原文
Title: OpenCell: Endogenous tagging for the cartography of human cellular organization
Author: Nathan H. Cho, Keith C. Cheveralls, Andreas-David Brunner, Kibeom Kim, André C. Michaelis, Preethi Raghavan, Hirofumi Kobayashi, Laura Savy, Jason Y. Li, Hera Canaj, James Y. S. Kim, Edna M. Stewart, Christian Gnann, Frank McCarthy, Joana P. Cabrera, Rachel M. Brunetti, Bryant B. Chhun, Greg Dingle, Marco Y. Hein, Bo Huang, Shalin B. Mehta, Jonathan S. Weissman, Rafael Gómez-Sjberg, Daniel N. Itzhak, Loc A. Royer, Matthias Mann, Manuel D. Leonetti
Issue&Volume: 2022-03-11
Abstract: Abstract
Elucidating the wiring diagram of the human cell is a central goal of the postgenomic era. We combined genome engineering, confocal live-cell imaging, mass spectrometry, and data science to systematically map the localization and interactions of human proteins. Our approach provides a data-driven description of the molecular and spatial networks that organize the proteome. Unsupervised clustering of these networks delineates functional communities that facilitate biological discovery. We found that remarkably precise functional information can be derived from protein localization patterns, which often contain enough information to identify molecular interactions, and that RNA binding proteins form a specific subgroup defined by unique interaction and localization properties. Paired with a fully interactive website (opencell.czbiohub.org), our work constitutes a resource for the quantitative cartography of human cellular organization.
DOI: abi6983
Source: https://www.science.org/doi/10.1126/science.abi6983