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OpenCell: Proteome-scale endogenous tagging enables the cartography of human cellular organization

ABSTRACT: Mapping the global proteome circuitry of the human cell is one of the central goals of the post-genomic era. Here, we combine high-throughput genome engineering of ~1,300 cell lines endogenously tagged with fluorescent protein fusions, 3D live-cell imaging, mass spectrometry (MS)-based high-speed interactomics and advanced machine learning to decode the interaction and localization architecture of the human proteome. We delineate interacting protein families and facilitate unbiased biological discovery by unsupervised clustering, while hierarchical analyses of the interactome superimposed to localization uncover principles that template cellular organization. Furthermore, we discover that localization patterns alone are often enough to predict molecular interactions. ‘OpenCell’ is a global proteome-scale resource for human protein localization and interaction at endogenous expression levels. Our analytical methods are open-source and our data set is presented as an advanced interactive website (‘OpenCell’.czbiohub.org) to empower the community with the quantitative cartography of human cellular organization at proteome level.

INSTRUMENT(S): timsTOF Pro

ORGANISM(S): Homo Sapiens (human)

TISSUE(S): Cell Culture

SUBMITTER: Mario Oroshi

LAB HEAD: Matthias Mann

PROVIDER: PXD024909 | Pride | 2022-03-14

REPOSITORIES: Pride

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OpenCell: Proteome-scale endogenous tagging enables the cartography of human cellular organization

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