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      Spatiotemporally-resolved mapping of RNA binding proteins via functional proximity labeling reveals a mitochondrial mRNA anchor promoting stress recovery

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          Abstract

          Proximity labeling (PL) with genetically-targeted promiscuous enzymes has emerged as a powerful tool for unbiased proteome discovery. By combining the spatiotemporal specificity of PL with methods for functional protein enrichment, we show that it is possible to map specific protein subclasses within distinct compartments of living cells. In particular, we develop a method to enrich subcompartment-specific RNA binding proteins (RBPs) by combining peroxidase-catalyzed PL with organic-aqueous phase separation of crosslinked protein-RNA complexes (“APEX-PS”). We use APEX-PS to generate datasets of nuclear, nucleolar, and outer mitochondrial membrane (OMM) RBPs, which can be mined for novel functions. For example, we find that the OMM RBP SYNJ2BP retains specific nuclear-encoded mitochondrial mRNAs at the OMM during translation stress, facilitating their local translation and import of protein products into the mitochondrion during stress recovery. Functional PL in general, and APEX-PS in particular, represent versatile approaches for the discovery of proteins with novel function in specific subcellular compartments.

          Abstract

          Proximity labeling is used to map and discover proteins in specific subcellular compartments. Here the authors combine APEX-mediated proximity labeling with organic-aqueous phase separation to identify nuclear, nucleolar, and outer mitochondrial membrane RNA binding proteins.

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          A subcellular map of the human proteome

          Resolving the spatial distribution of the human proteome at a subcellular level greatly increases our understanding of human biology and disease. Here, we present a comprehensive image-based map of the subcellular protein distribution, the Cell Atlas, built by integrating transcriptomics and antibody-based immunofluorescence microscopy with validation by mass spectrometry. Mapping the in situ localization of 12,003 human proteins at a single-cell level to 30 subcellular structures enabled the definition of 13 major organelle proteomes. Exploration of the proteomes reveals single-cell variations of abundance or spatial distribution, and localization of approximately half of the proteins to multiple compartments. This subcellular map can be used to refine existing protein-protein interaction networks and provides an important resource to deconvolute the highly complex architecture of the human cell.
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            Efficient proximity labeling in living cells and organisms with TurboID

            Protein interaction networks and protein compartmentalization underlie all signaling and regulatory processes in cells. Enzyme-catalyzed proximity labeling (PL) has emerged as a new approach to study the spatial and interaction characteristics of proteins in living cells. However, current PL methods require over 18 hour labeling times or utilize chemicals with limited cell permeability or high toxicity. We used yeast display-based directed evolution to engineer two promiscuous mutants of biotin ligase, TurboID and miniTurbo, which catalyze PL with much greater efficiency than BioID or BioID2, and enable 10-minute PL in cells with non-toxic and easily deliverable biotin. Furthermore, TurboID extends biotin-based PL to flies and worms.
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              A census of human RNA-binding proteins.

              Post-transcriptional gene regulation (PTGR) concerns processes involved in the maturation, transport, stability and translation of coding and non-coding RNAs. RNA-binding proteins (RBPs) and ribonucleoproteins coordinate RNA processing and PTGR. The introduction of large-scale quantitative methods, such as next-generation sequencing and modern protein mass spectrometry, has renewed interest in the investigation of PTGR and the protein factors involved at a systems-biology level. Here, we present a census of 1,542 manually curated RBPs that we have analysed for their interactions with different classes of RNA, their evolutionary conservation, their abundance and their tissue-specific expression. Our analysis is a critical step towards the comprehensive characterization of proteins involved in human RNA metabolism.
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                Author and article information

                Contributors
                ayting@stanford.edu
                Journal
                Nat Commun
                Nat Commun
                Nature Communications
                Nature Publishing Group UK (London )
                2041-1723
                17 August 2021
                17 August 2021
                2021
                : 12
                : 4980
                Affiliations
                [1 ]GRID grid.168010.e, ISNI 0000000419368956, Departments of Biology, Genetics, and Chemistry, , Stanford University, ; Stanford, CA USA
                [2 ]GRID grid.499295.a, Chan Zuckerberg Biohub, ; San Francisco, CA USA
                [3 ]GRID grid.66859.34, The Broad Institute of MIT and Harvard, ; Cambridge, MA USA
                [4 ]GRID grid.185006.a, ISNI 0000 0004 0461 3162, La Jolla Institute for Immunology, ; La Jolla, CA USA
                Author information
                http://orcid.org/0000-0002-8277-5226
                Article
                25259
                10.1038/s41467-021-25259-2
                8370977
                34404792
                bb844f46-efef-4473-90e9-4675b3d6a0cb
                © The Author(s) 2021

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 16 March 2021
                : 29 July 2021
                Funding
                Funded by: FundRef https://doi.org/10.13039/501100006321, MEXT | National Institutes of Natural Sciences (NINS);
                Funded by: FundRef https://doi.org/10.13039/100000002, U.S. Department of Health & Human Services | National Institutes of Health (NIH);
                Award ID: R01-DK121409
                Award Recipient :
                Categories
                Article
                Custom metadata
                © The Author(s) 2021

                Uncategorized
                rna,proteomics,organelles
                Uncategorized
                rna, proteomics, organelles

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