High-Density Proximity Mapping Reveals the Subcellular Organization of mRNA-Associated Granules and Bodies.

mRNA processing, transport, translation, and ultimately degradation involve a series of dedicated protein complexes that often assemble into large membraneless structures such as stress granules (SGs) and processing bodies (PBs). Here, systematic in vivo proximity-dependent biotinylation (BioID) analysis of 119 human proteins associated with different aspects of mRNA biology uncovers 7424 unique proximity interactions with 1,792 proteins. Classical bait-prey analysis reveals connections of hundreds of proteins to distinct mRNA-associated processes or complexes, including the splicing and transcriptional elongation machineries (protein phosphatase 4) and the CCR4-NOT deadenylase complex (CEP85, RNF219, and KIAA0355). Analysis of correlated patterns between endogenous preys uncovers the spatial organization of RNA regulatory structures and enables the definition of 144 core components of SGs and PBs. We report preexisting contacts between most core SG proteins under normal growth conditions and demonstrate that several core SG proteins (UBAP2L, CSDE1, and PRRC2C) are critical for the formation of microscopically visible SGs.

[1]  Wade H. Dunham,et al.  The eIF4E-Binding Protein 4E-T Is a Component of the mRNA Decay Machinery that Bridges the 5' and 3' Termini of Target mRNAs. , 2015, Cell reports.

[2]  E. Hafen,et al.  The RNA-binding Proteins FMR1, Rasputin and Caprin Act Together with the UBA Protein Lingerer to Restrict Tissue Growth in Drosophila melanogaster , 2013, PLoS genetics.

[3]  Kara Dolinski,et al.  The BioGRID interaction database: 2017 update , 2016, Nucleic Acids Res..

[4]  Peter Kalev,et al.  Emerging role of protein phosphatases changes the landscape of phospho-signaling in DNA damage response. , 2015, DNA repair.

[5]  Richard Bonneau,et al.  The mRNA-bound proteome and its global occupancy profile on protein-coding transcripts. , 2012, Molecular cell.

[6]  Natalie I. Tasman,et al.  iProphet: Multi-level Integrative Analysis of Shotgun Proteomic Data Improves Peptide and Protein Identification Rates and Error Estimates* , 2011, Molecular & Cellular Proteomics.

[7]  Jimin Pei,et al.  Cell-free Formation of RNA Granules: Low Complexity Sequence Domains Form Dynamic Fibers within Hydrogels , 2012, Cell.

[8]  P. Pevzner,et al.  The Generating Function of CID, ETD, and CID/ETD Pairs of Tandem Mass Spectra: Applications to Database Search* , 2010, Molecular & Cellular Proteomics.

[9]  E. Izaurralde,et al.  Towards a molecular understanding of microRNA-mediated gene silencing , 2015, Nature Reviews Genetics.

[10]  Anne-Claude Gingras,et al.  Proximity biotinylation and affinity purification are complementary approaches for the interactome mapping of chromatin-associated protein complexes. , 2015, Journal of proteomics.

[11]  E. Chan,et al.  GW182 is critical for the stability of GW bodies expressed during the cell cycle and cell proliferation , 2004, Journal of Cell Science.

[12]  Kenneth H. Buetow,et al.  Gene functional similarity search tool (GFSST) , 2006, BMC Bioinformatics.

[13]  Jean-Baptiste Morlot,et al.  P-Body Purification Reveals the Condensation of Repressed mRNA Regulons. , 2017, Molecular cell.

[14]  P. Shannon,et al.  Cytoscape: a software environment for integrated models of biomolecular interaction networks. , 2003, Genome research.

[15]  Alexey I Nesvizhskii,et al.  Empirical statistical model to estimate the accuracy of peptide identifications made by MS/MS and database search. , 2002, Analytical chemistry.

[16]  Robert H Singer,et al.  The dynamics of mammalian P body transport, assembly, and disassembly in vivo. , 2008, Molecular biology of the cell.

[17]  C. Brangwynne,et al.  Nuclear bodies: the emerging biophysics of nucleoplasmic phases. , 2015, Current opinion in cell biology.

[18]  F. Massey The Kolmogorov-Smirnov Test for Goodness of Fit , 1951 .

[19]  Marco Y. Hein,et al.  A Human Interactome in Three Quantitative Dimensions Organized by Stoichiometries and Abundances , 2015, Cell.

[20]  Jimin Pei,et al.  Cell-free Formation of RNA Granules: Bound RNAs Identify Features and Components of Cellular Assemblies , 2012, Cell.

[21]  Anthony K. L. Leung,et al.  Quantitative analysis of Argonaute protein reveals microRNA-dependent localization to stress granules , 2006, Proceedings of the National Academy of Sciences.

[22]  Tom Misteli,et al.  The dynamics of a pre-mRNA splicing factor in living cells , 1997, Nature.

[23]  Devin K. Schweppe,et al.  Architecture of the human interactome defines protein communities and disease networks , 2017, Nature.

[24]  Gaël Varoquaux,et al.  Scikit-learn: Machine Learning in Python , 2011, J. Mach. Learn. Res..

[25]  E. Nadezhdina,et al.  Microtubules govern stress granule mobility and dynamics. , 2010, Biochimica et biophysica acta.

[26]  H. Sebastian Seung,et al.  Learning the parts of objects by non-negative matrix factorization , 1999, Nature.

[27]  J. B. Rattner,et al.  Repression of GW/P body components and the RNAi microprocessor impacts primary ciliogenesis in human astrocytes , 2011, BMC Cell Biology.

[28]  M. Tyers,et al.  Data Independent Acquisition analysis in ProHits 4.0. , 2016, Journal of proteomics.

[29]  W. Filipowicz,et al.  Structure of a Human 4E-T/DDX6/CNOT1 Complex Reveals the Different Interplay of DDX6-Binding Proteins with the CCR4-NOT Complex. , 2015, Cell reports.

[30]  Mani Ramaswami,et al.  Altered Ribostasis: RNA-Protein Granules in Degenerative Disorders , 2013, Cell.

[31]  Ravali Adusumilli,et al.  Data Conversion with ProteoWizard msConvert. , 2017, Methods in molecular biology.

[32]  Tony Pawson,et al.  Protein Interaction Network of the Mammalian Hippo Pathway Reveals Mechanisms of Kinase-Phosphatase Interactions , 2013, Science Signaling.

[33]  Alos Diallo,et al.  TRIM65 regulates microRNA activity by ubiquitination of TNRC6 , 2014, Proceedings of the National Academy of Sciences.

[34]  Claire D. McWhite,et al.  Integration of over 9,000 mass spectrometry experiments builds a global map of human protein complexes , 2017, Molecular systems biology.

[35]  Jian Wang,et al.  MSPLIT-DIA: sensitive peptide identification for data-independent acquisition , 2015, Nature Methods.

[36]  G. von Heijne,et al.  Tissue-based map of the human proteome , 2015, Science.

[37]  B. Séraphin,et al.  Cytoplasmic foci are sites of mRNA decay in human cells , 2004, The Journal of cell biology.

[38]  Randal J. Kaufman,et al.  Stress granules and processing bodies are dynamically linked sites of mRNP remodeling , 2005, The Journal of cell biology.

[39]  Amber L. Couzens,et al.  Phenotypic and Interaction Profiling of the Human Phosphatases Identifies Diverse Mitotic Regulators. , 2016, Cell reports.

[40]  Hedi Peterson,et al.  g:Profiler—a web server for functional interpretation of gene lists (2016 update) , 2016, Nucleic Acids Res..

[41]  R. Aebersold,et al.  A statistical model for identifying proteins by tandem mass spectrometry. , 2003, Analytical chemistry.

[42]  R. Cencic,et al.  Hippuristanol - A potent steroid inhibitor of eukaryotic initiation factor 4A , 2016, Translation.

[43]  N. Sonenberg,et al.  Stimulation of mammalian translation initiation factor eIF4A activity by a small molecule inhibitor of eukaryotic translation. , 2005, Proceedings of the National Academy of Sciences of the United States of America.

[44]  E. Hafen,et al.  A Novel, Evolutionarily Conserved Protein Phosphatase Complex Involved in Cisplatin Sensitivity*S , 2005, Molecular & Cellular Proteomics.

[45]  Jun O. Liu,et al.  Eukaryotic Initiation Factor 2α-independent Pathway of Stress Granule Induction by the Natural Product Pateamine A* , 2006, Journal of Biological Chemistry.

[46]  Anthony Barsic,et al.  ATPase-Modulated Stress Granules Contain a Diverse Proteome and Substructure , 2016, Cell.

[47]  Norman E. Davey,et al.  Insights into RNA Biology from an Atlas of Mammalian mRNA-Binding Proteins , 2012, Cell.

[48]  Jeroen Krijgsveld,et al.  Comprehensive Identification of RNA-Binding Domains in Human Cells , 2016, Molecular cell.

[49]  V. Doye,et al.  Probing nuclear pore complex architecture with proximity-dependent biotinylation , 2014, Proceedings of the National Academy of Sciences.

[50]  Amber L. Couzens,et al.  The CRAPome: a Contaminant Repository for Affinity Purification Mass Spectrometry Data , 2013, Nature Methods.

[51]  Hyungwon Choi,et al.  ProHits-viz: a suite of web tools for visualizing interaction proteomics data , 2017, Nature Methods.

[52]  A. Gingras,et al.  PP4R4/KIAA1622 Forms a Novel Stable Cytosolic Complex with Phosphoprotein Phosphatase 4* , 2008, Journal of Biological Chemistry.

[53]  Nicola J. Mulder,et al.  DaGO-Fun: tool for Gene Ontology-based functional analysis using term information content measures , 2013, BMC Bioinformatics.

[54]  S. Eddy,et al.  Pfam: the protein families database , 2013, Nucleic Acids Res..

[55]  Ben Lehner,et al.  Analysis of a high-throughput yeast two-hybrid system and its use to predict the function of intracellular proteins encoded within the human MHC class III region. , 2004, Genomics.

[56]  Wei Li,et al.  RNA-Binding Proteins Tia-1 and Tiar Link the Phosphorylation of Eif-2α to the Assembly of Mammalian Stress Granules , 1999, The Journal of cell biology.

[57]  Guomin Liu,et al.  SAINTexpress: improvements and additional features in Significance Analysis of INTeractome software. , 2014, Journal of proteomics.

[58]  Roy Parker,et al.  P bodies and the control of mRNA translation and degradation. , 2007, Molecular cell.