OpenCell: Endogenous tagging for the cartography of human cellular organization
Open accessPublished version of a preprint
Abstract
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.
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Other systematic image-based approaches have catalogued the location of human proteins in several cell types and used the locations of proteins and structures within cells to identify differences in intracellular spatial patterns among cells in distinct states.
“Other systematic image-based approaches have catalogued the location of human proteins in several cell types and used the locations of proteins and structures within cells to identify differences in intracellular spatial patterns among cells in distinct states6–12,19,29.”
From Integrated intracellular organization and its variations in human iPS cells (2023) · cites this paper as [12]
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Experimental — accuracy not yet measuredClassical imaging technologies (including live-cell), newer structural imaging technologies (such as cryoelectron tomography and soft X-ray tomography), and novel spatial omics technologies offer opportunities to model biomolecules and functions across scales.
“Here, classical imaging technologies,65,100,101 including live-cell, and newer structural imaging technologies, such as cryoelectron tomography and soft X-ray tomography,66,102,103 as well as novel spatial omics technologies,104,105 offer opportunities to model biomolecules and functions across scales.”
From How to build the virtual cell with artificial intelligence: Priorities and opportunities (2024) · cites this paper as [100]
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References 105 · Cited by 567
Research works printed but not linked: 3
- [77]Go CD, Knight JDR, Rajasekharan A, Rathod B, Hesketh GG, Abe KT, Youn J-Y, Samavarchi-Tehrani P, Zhang H, Zhu LY, Popiel E, Lambert J-P, Coyaud É, Cheung SWT, Rajendran D, Wong CJ, Antonicka H, Pelletier L, Raught B, Palazzo AF, Shoubridge EA, Gingras A-C, A proximity biotinylation map of a human cell. Biorxiv, 796391 (2019).
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- [105]Bonald T, Charpentier B, Galland A, Hollocou A, Hierarchical Graph Clustering using Node Pair Sampling. Arxiv (2018).
- Authors
- Cho, N. H., Cheveralls, K. C., Brunner, A.-D., Kim, K., Michaelis, A. C., Raghavan, P., Kobayashi, H., Savy, L., Li, J. Y., Canaj, H., Kim, J. Y. S., Stewart, E. M., Gnann, C., McCarthy, F., Cabrera, J. P., Brunetti, R. M., Chhun, B. B., Dingle, G., Hein, M. Y., Huang, B., Mehta, S. B., Weissman, J. S., Gómez-Sjöberg, R., Itzhak, D. N., Royer, L. A., Mann, M., & Leonetti, M. D.
- Affiliations
- Chan Zuckerberg Biohub San Francisco (US)
- Max Planck Institute of Biochemistry (DE)
- Science for Life Laboratory (SE)
- University of California, San Francisco (US)
- Howard Hughes Medical Institute (US)
- Chan Zuckerberg Biohub, San Francisco, CA, USA.
- University of Copenhagen (DK)
- Corresponding author
- Leonetti, Manuel D.
- ORCID
- Cho, Nathan H.
- Cheveralls, Keith C.
- Brunner, Andreas-David
- Kim, Kibeom
- Michaelis, André C.
- Raghavan, Preethi
- Kobayashi, Hirofumi
- 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.
- Venue
- Science
- Published
- 2022-03-11
- Volume
- 375
- Issue
- 6585
- Pages
- eabi6983-eabi6983
- ISSN
- 0036-8075 (ISSN-L)
- 1095-9203
- PMC
- PMC9119736
- OpenAlex
- W4221117452
- Cited by
- 567
- References
- 105
- Citations by year
- 2026: 125 · 2025: 150 · 2024: 147 · 2023: 94 · 2022: 42 · 2021: 8
- FWCI
- 35.84
- Type
- journal article
- Language
- en
- Open access
- green
- doi.org
- Licence
- cc-by-nc-nd
- Locations
- Science (publishedVersion)
- bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by-nc-nd)
- PubMed (publishedVersion)
- Research at the University of Copenhagen (University of Copenhagen) (publishedVersion, other-oa)
- PubMed Central (acceptedVersion)
- Funders
- Howard Hughes Medical Institute
- National Institutes of Health
- Japan Society for the Promotion of Science
- National Heart, Lung, and Blood Institute (F31HL143882)
- National Human Genome Research Institute (RM1HG009490)
- National Institute of General Medical Sciences (R01GM131641)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Bioinformatics and Genomic Networks
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Cell Biology › Biotin and Related Studies
- Physical Sciences › Chemistry › Spectroscopy › Advanced Proteomics Techniques and Applications
- Keywords
- endogenous tagging, human proteome, protein localization, protein-protein interaction, spatial proteomics, RNA-binding proteins, live-cell imaging
- MeSH terms
- Machine Learning, Fluorescent Dyes, Humans, Proteins, Mass Spectrometry, Cluster Analysis, RNA-Binding Proteins, Microscopy, Confocal, Proteome, Protein Interaction Mapping, Proteomics, Immunoprecipitation, HEK293 Cells, Spatial Analysis, CRISPR-Cas Systems, Datasets as Topic
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