A multi-scale map of cell structure fusing protein images and interactions
| Autor: | Trey Ideker, J. Wade Harper, John J. Lee, Steven P. Gygi, Laura Pontano Vaites, Denis L. J. Lafontaine, Edward L. Huttlin, Erica Silva, Michael Chen, Jason F. Kreisberg, Casper F. Winsnes, Fan Zheng, Leah V. Schaffer, Gene W. Yeo, Tian Zhang, Wei Ouyang, Anna Bäckström, Katherine Licon, Jisoo Park, Jianzhu Ma, Emma Lundberg, Maya L. Gosztyla, Yue Qin, Steven M. Blue, Adriana Pitea, Sophie Liu, Ludivine Wacheul, Marcus R. Kelly |
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| Rok vydání: | 2021 |
| Předmět: |
Proteome
Computer science General Science & Technology Protein subunit 1.1 Normal biological development and functioning Bioengineering Computational biology computer.software_genre Data type Article Chromosomes Protein–protein interaction Nuclear Matrix-Associated Proteins Underpinning research Humans Nuclear Antigens Ribosomal Computational model Multidisciplinary business.industry RNA-Binding Proteins Antigens Nuclear Modular design Chromatin RNA Ribosomal RNA splicing RNA Generic health relevance business computer Data integration |
| Zdroj: | Nature, vol 600, iss 7889 Nature |
| Popis: | The cell is a multi-scale structure with modular organization across at least four orders of magnitude(1). 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 separately(2,3). Here we integrate immunofluorescence images in the Human Protein Atlas(4) with affinity purifications in BioPlex(5) 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. |
| Databáze: | OpenAIRE |
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