小柯机器人

美国加州大学Trey Ideker小组和瑞典皇家理工学院Emma Lundberg小组合作研究揭示了细胞结构水平融合蛋白图像和相互作用的多尺度图。该研究于2021年11月24日发表于国际学术期刊《自然》杂志。

研究人员将Human Protein Atlas4中的免疫荧光图像与BioPlex5中的亲和纯化相结合，以创建人类细胞结构的统一分层图。通过将每种方法配置为蛋白质距离的一般度量，然后使用机器学习校准这两个度量来实现集成。该图被称为多尺度集成细胞(MuSIC 1.0)，可解析69 个亚细胞系统。据研究人员介绍，其中有约一半是之前研究未记录的。因此，研究人员进行了134次额外亲和纯化，并验证了大多数系统的亚基关联。

该图揭示了前核糖体RNA加工组装和辅助因子，研究人员证实它们调控rRNA成熟，SRRM1、FAM120C在染色质调控和RPS3A在剪接过程中的功能。通过跨尺度整合，MuSIC提高了成像分辨率，同时为蛋白质相互作用提供了空间维度，为在蛋白质组水平细胞图谱中整合不同类型的数据铺平了道路。

研究人员表示，细胞是一个多尺度结构，具有至少四个数量级的模块化组织。绘制这种结构的两种主要方法为蛋白质荧光成像和蛋白质生物物理关联，这都生成大量数据集，但具有不同的质量和分辨率，通常需要单独分析。

附：英文原文

Title: A multi-scale map of cell structure fusing protein images and interactions

Author: Qin, Yue, Huttlin, Edward L., Winsnes, Casper F., Gosztyla, Maya L., Wacheul, Ludivine, Kelly, Marcus R., Blue, Steven M., Zheng, Fan, Chen, Michael, Schaffer, Leah V., Licon, Katherine, Bckstrm, Anna, Vaites, Laura Pontano, Lee, John J., Ouyang, Wei, Liu, Sophie N., Zhang, Tian, Silva, Erica, Park, Jisoo, Pitea, Adriana, Kreisberg, Jason F., Gygi, Steven P., Ma, Jianzhu, Harper, J. Wade, Yeo, Gene W., Lafontaine, Denis L. J., Lundberg, Emma, Ideker, Trey

Issue&Volume: 2021-11-24

Abstract: The cell is a multi-scale structure with modular organization across at least four orders of magnitude1. Two central approaches for mapping this structure—protein fluorescent imaging and protein biophysical association—each generate extensive datasets, but of distinct qualities and resolutions that are typically treated separately2,3. Here we integrate immunofluorescence images in the Human Protein Atlas4 with affinity purifications in BioPlex5 to create a unified hierarchical map of human cell architecture. Integration is achieved by configuring each approach as a general measure of protein distance, then calibrating the two measures using machine learning. The map, known as the multi-scale integrated cell (MuSIC 1.0), resolves 69 subcellular systems, of which approximately half are to our knowledge undocumented. Accordingly, we perform 134 additional affinity purifications and validate subunit associations for the majority of systems. The map reveals a pre-ribosomal RNA processing assembly and accessory factors, which we show govern rRNA maturation, and functional roles for SRRM1 and FAM120C in chromatin and RPS3A in splicing. By integration across scales, MuSIC increases the resolution of imaging while giving protein interactions a spatial dimension, paving the way to incorporate diverse types of data in proteome-wide cell maps.

DOI: 10.1038/s41586-021-04115-9

Source: https://www.nature.com/articles/s41586-021-04115-9

Nature：《自然》，创刊于1869年。隶属于施普林格·自然出版集团，最新IF：69.504
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