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Mapping cell structure across scales by fusing protein images and interactions

By Yue Qin, Casper F. Winsnes, Edward L. Huttlin, Fan Zheng, Wei Ouyang, Jisoo Park, Adriana Pitea, Jason F. Kreisberg, Steven P. Gygi, J. Wade Harper, Jianzhu Ma, Emma Lundberg, Trey Ideker

Posted 22 Jun 2020
bioRxiv DOI: 10.1101/2020.06.21.163709

The eukaryotic cell is a multi-scale structure with modular organization across at least four orders of magnitude. 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. Here, we integrate immunofluorescent images in the Human Protein Atlas with ongoing affinity purification experiments from the BioPlex resource to create a unified hierarchical map of eukaryotic cell architecture. Integration involves configuring each approach to produce a general measure of protein distance, then calibrating the two measures using machine learning. The evolving map, called the Multi-Scale Integrated Cell (MuSIC 1.0), currently resolves 69 subcellular systems of which approximately half are undocumented. Based on these findings we perform 134 additional affinity purifications, validating close subunit associations for the majority of systems. The map elucidates roles for poorly characterized proteins, such as the appearance of FAM120C in chromatin; identifies new protein assemblies in ribosomal biogenesis, RNA splicing, nuclear speckles, and ion transport; and reveals crosstalk between cytoplasmic and mitochondrial ribosomal proteins. By integration across scales, MuSIC substantially increases the mapping resolution obtained from imaging while giving protein interactions a spatial dimension, paving the way to incorporate many molecular data types in proteome-wide maps of cells. ### Competing Interest Statement The authors have declared no competing interest.

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