OpenCell: Endogenous tagging for the cartography of human cellular organization

• Published in: Science (American Association for the Advancement of Science) Vol. 375; no. 6585; p. eabi6983
• Main Authors: Cho, Nathan H., Cheveralls, Keith C., Brunner, Andreas-David, Kim, Kibeom, Michaelis, André C., Raghavan, Preethi, Kobayashi, Hirofumi, Savy, Laura, Li, Jason Y., Canaj, Hera, Kim, James Y. S., Stewart, Edna M., Gnann, Christian, McCarthy, Frank, Cabrera, Joana P., Brunetti, Rachel M., Chhun, Bryant B., Dingle, Greg, Hein, Marco Y., Huang, Bo, Mehta, Shalin B., Weissman, Jonathan S., Gómez-Sjöberg, Rafael, Itzhak, Daniel N., Royer, Loïc A., Mann, Matthias, Leonetti, Manuel D.
• Format: Journal Article
• Language: English
• Published: United States The American Association for the Advancement of Science 11.03.2022
• Subjects: Artificial Intelligence; Cartography; Cell lines; Cellular communication; Cluster Analysis; Clustering; CRISPR; CRISPR-Cas Systems; Cytology; Datasets; Datasets as Topic; Filaments; Fluorescent Dyes; Fluoroscopic imaging; Gene expression; Gene mapping; Genome editing; Genomes; HEK293 Cells; High-throughput screening; Humans; Image analysis; Image processing; Immunoprecipitation; Individualized Instruction; Learning algorithms; Libraries; Localization; Machine Learning; Marking; Mass Spectrometry; Mass spectroscopy; Microscopy; Microscopy, Confocal; Nucleotide sequence; Organic Chemistry; Peptide mapping; Protein interaction; Protein Interaction Mapping; Proteins; Proteins - metabolism; Proteome - metabolism; Proteomes; Proteomics - methods; Ribonucleic acid; RNA; RNA-binding protein; RNA-Binding Proteins - metabolism; Scientific imaging; Signatures; Spatial Analysis; Spatial distribution; Spectroscopy; Subgroups; Tags; Websites
• ISSN: 0036-8075; 1095-9203; 1095-9203
• DOI: 10.1126/science.abi6983

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. Improved understanding of how proteins are organized within human cells should enhance our systems-level understanding of how cells function. Cho et al . used CRISPR technology to express more than 1000 different proteins at near endogenous amounts with labels that allowed both fluorescent imaging of their location and immunoprecipitation and mass spectrometry analysis of interacting protein partners (see the Perspective by Michnick and Levy). The large-scale data are made available on an interactive website, with clustering and analysis performed by machine learning. The studies emphasize the unusual properties of RNA-binding proteins and indicate that protein localization is very specific and may allow predictions of function. —LBR Combining genome engineering, live-cell imaging, mass spectrometry, and data science are used to map the localization and interactions of human proteins.