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- Cho, Nathan H., et al.
(författare)
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OpenCell : Endogenous tagging for the cartography of human cellular organization
- 2022
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Ingår i: Science. - : American Association for the Advancement of Science (AAAS). - 0036-8075 .- 1095-9203. ; 375:6585, s. 1143-
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Tidskriftsartikel (refereegranskat)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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| 2. |
- Gnann, Christian, et al.
(författare)
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Widespread enzyme expression variations underlie diverse metabolic capacities within cell types
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Annan publikation (övrigt vetenskapligt/konstnärligt)abstract
- Metabolic enzymes perform life-sustaining functions in various compartments of the cell. Recent studies have shown some enzymes to exhibit varied expression or localization between genetically identical cells and that this heterogeneity impacts drug resistance, metastasis, differentiation, and immune cell activation. However, no systematic analysis of metabolic cellular heterogeneity has been performed. Here, we leverage imaging-based single-cell spatial proteomic data to reveal the extent of non-genetic partitioning of the metabolic proteome. Over half of all enzymes localize to multiple cellular compartments, hinting at moonlighting potential. In addition, nearly two fifths of metabolic enzymes exhibit cell-to-cell variable expression. We demonstrate that individual cells reproduce these highly heterogeneous cell populations using clonal expansion, establishing that cells recapitulate myriad metabolic phenotypes over just a few cell divisions. To identify multifunctional moonlighting enzymes, we mine protein-protein interaction datasets to find interacting proteins with distinct functional roles, and using a timeresolved transcriptomic dataset, we find that metabolic heterogeneity arises largely independently of cell cycle progression and is established mostly post-transcriptionally or posttranslationally. Taken together, our data suggest that the heterogeneity of metabolic enzymes establish diverse cellular phenotypes, which are reflected in tissues, and which may ultimately allow targeted studies of their roles in health and disease.
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