Abstract
Application of synthetic nucleoside analogues to capture newly transcribed RNAs has unveiled key features of RNA metabolism. Whether this approach could be adapted to isolate the RNA-bound proteome (RNA interactome) was, however, unexplored. We have developed a new method (capture of the newly transcribed RNA interactome using click chemistry, or RICK) for the systematic identification of RNA-binding proteins based on the incorporation of 5-ethynyluridine into newly transcribed RNAs followed by UV cross-linking and click chemistry-mediated biotinylation. The RNA–protein adducts are then isolated by affinity capture using streptavidin-coated beads. Through high-throughput RNA sequencing and mass spectrometry, the RNAs and proteins can be elucidated globally. A typical RICK experimental procedure takes only 1 d, excluding the steps of cell preparation, 5-ethynyluridine labeling, validation (silver staining, western blotting, quantitative reverse-transcription PCR (qRT-PCR) or RNA sequencing (RNA-seq)) and proteomics. Major advantages of RICK are the capture of RNA-binding proteins interacting with any type of RNA and, particularly, the ability to discern between newly transcribed and steady-state RNAs through controlled labeling. Thanks to its versatility, RICK will facilitate the characterization of the total and newly transcribed RNA interactome in different cell types and conditions.
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Data availability
RNA-seq data shown in this paper have been deposited in GEO under accession code GSE100756. Source data are provided with this paper. Source data files for other figures can be accessed via the supporting primary research article19.
Code availability
Code used to analyze the RNA-seq data can be accessed under accession code GSE100756 in GEO. Code used to process the MS data has been described in the Procedure steps, and more details are available from the corresponding author upon request.
References
Cech, T. R. & Steitz, J. A. The noncoding RNA revolution-trashing old rules to forge new ones. Cell 157, 77–94 (2014).
Esteller, M. Non-coding RNAs in human disease. Nat. Rev. Genet. 12, 861–874 (2011).
Jankowsky, E. & Harris, M. E. Specificity and nonspecificity in RNA-protein interactions. Nat. Rev. Mol. Cell Biol. 16, 533–544 (2015).
Anderson, D. M. et al. A micropeptide encoded by a putative long noncoding RNA regulates muscle performance. Cell 160, 595–606 (2015).
Hentze, M. W., Castello, A., Schwarzl, T. & Preiss, T. A brave new world of RNA-binding proteins. Nat. Rev. Mol. Cell Biol. 19, 327–341 (2018).
Castello, A., Hentze, M. W. & Preiss, T. Metabolic enzymes enjoying new partnerships as RNA-binding proteins. Trends Endocrinol. Metab. 26, 746–757 (2015).
Lv, Y., Tariq, M., Guo, X., Kanwal, S. & Esteban, M. A. Intricacies in the cross talk between metabolic enzymes, RNA, and protein translation. J. Mol. Cell Biol. 11, 813–815 (2019).
Gerstberger, S., Hafner, M. & Tuschl, T. A census of human RNA-binding proteins. Nat. Rev. Genet. 15, 829–845 (2014).
McHugh, C. A., Russell, P. & Guttman, M. Methods for comprehensive experimental identification of RNA-protein interactions. Genome Biol. 15, 203 (2014).
Nechay, M. & Kleiner, R. E. High-throughput approaches to profile RNA-protein interactions. Curr. Opin. Chem. Biol. 54, 37–44 (2020).
Castello, A. et al. Insights into RNA biology from an atlas of mammalian mRNA-binding proteins. Cell 149, 1393–1406 (2012).
Baltz, A. G. et al. The mRNA-bound proteome and its global occupancy profile on protein-coding transcripts. Mol. Cell 46, 674–690 (2012).
Queiroz, R. M. L. et al. Comprehensive identification of RNA-protein interactions in any organism using orthogonal organic phase separation (OOPS). Nat. Biotechnol. 37, 169–178 (2019).
Trendel, J. et al. The human RNA-binding proteome and its dynamics during translational arrest. Cell 176, 391–403 e319 (2019).
Urdaneta, E. C. et al. Purification of cross-linked RNA-protein complexes by phenol-toluol extraction. Nat. Commun. 10, 990 (2019).
Asencio, C., Chatterjee, A. & Hentze, M. W. Silica-based solid-phase extraction of cross-linked nucleic acid-bound proteins. Life Sci. Alliance 1, e201800088 (2018).
Shchepachev, V. et al. Defining the RNA interactome by total RNA-associated protein purification. Mol. Syst. Biol. 15, e8689 (2019).
Kim, B., Arcos, S., Rothamel, K. & Ascano, M. Viral crosslinking and solid-phase purification enables discovery of ribonucleoprotein complexes on incoming RNA virus genomes. Nat. Protoc. 16, 516–531 (2021).
Bao, X. et al. Capturing the interactome of newly transcribed RNA. Nat. Methods 15, 213–220 (2018).
Huang, R., Han, M., Meng, L. & Chen, X. Transcriptome-wide discovery of coding and noncoding RNA-binding proteins. Proc. Natl Acad. Sci. USA. 115, E3879–E3887 (2018).
He, C. et al. High-resolution mapping of RNA-binding regions in the nuclear proteome of embryonic stem cells. Mol. Cell 64, 416–430 (2016).
Wu, Q. et al. Poly A-transcripts expressed in HeLa cells. PLoS One 3, e2803 (2008).
Cheng, J. et al. Transcriptional maps of 10 human chromosomes at 5-nucleotide resolution. Science 308, 1149–1154 (2005).
Core, L. J., Waterfall, J. J. & Lis, J. T. Nascent RNA sequencing reveals widespread pausing and divergent initiation at human promoters. Science 322, 1845–1848 (2008).
Garibaldi, A., Carranza, F. & Hertel, K. J. Isolation of newly transcribed RNA using the metabolic label 4-thiouridine. Methods Mol. Biol. 1648, 169–176 (2017).
Jao, C. Y. & Salic, A. Exploring RNA transcription and turnover in vivo by using click chemistry. Proc. Natl Acad. Sci. USA 105, 15779–15784 (2008).
Battich, N. et al. Sequencing metabolically labeled transcripts in single cells reveals mRNA turnover strategies. Science 367, 1151–1156 (2020).
Tani, H. & Akimitsu, N. Genome-wide technology for determining RNA stability in mammalian cells: historical perspective and recent advantages based on modified nucleotide labeling. RNA Biol. 9, 1233–1238 (2012).
Burger, K. et al. 4-Thiouridine inhibits rRNA synthesis and causes a nucleolar stress response. RNA Biol. 10, 1623–1630 (2013).
Zhang, X. O. et al. Complementary sequence-mediated exon circularization. Cell 159, 134–147 (2014).
Wang, D. et al. Reprogramming transcription by distinct classes of enhancers functionally defined by eRNA. Nature 474, 390–394 (2011).
Park, J. E., Yi, H., Kim, Y., Chang, H. & Kim, V. N. Regulation of poly(A) tail and translation during the somatic cell cycle. Mol. Cell 62, 462–471 (2016).
Yang, L., Duff, M. O., Graveley, B. R., Carmichael, G. G. & Chen, L. L. Genomewide characterization of non-polyadenylated RNAs. Genome Biol. 12, R16 (2011).
Chu, C. et al. Systematic discovery of Xist RNA binding proteins. Cell 161, 404–416 (2015).
O’Connell, M. R. et al. Programmable RNA recognition and cleavage by CRISPR/Cas9. Nature 516, 263–266 (2014).
Ramanathan, M. et al. RNA-protein interaction detection in living cells. Nat. Methods 15, 207–212 (2018).
Blenkiron, C. et al. Uropathogenic Escherichia coli releases extracellular vesicles that are associated with RNA. PLoS One 11, e0160440 (2016).
Meng, L. et al. Metabolic RNA labeling for probing RNA dynamics in bacteria. Nucleic Acids Res. 48, 12566–12576 (2020).
Yang, E. et al. Decay rates of human mRNAs: correlation with functional characteristics and sequence attributes. Genome Res. 13, 1863–1872 (2003).
Suchanek, M., Radzikowska, A. & Thiele, C. Photo-leucine and photo-methionine allow identification of protein-protein interactions in living cells. Nat. Methods 2, 261–267 (2005).
Rostovtsev, V. V., Green, L. G., Fokin, V. V. & Sharpless, K. B. A stepwise huisgen cycloaddition process: copper(I)-catalyzed regioselective “ligation” of azides and terminal alkynes. Angew. Chem. Int. Ed. Engl. 41, 2596–2599 (2002).
Hong, V., Steinmetz, N. F., Manchester, M. & Finn, M. G. Labeling live cells by copper-catalyzed alkyne-azide click chemistry. Bioconjug. Chem. 21, 1912–1916 (2010).
Presolski, S. I., Hong, V. P. & Finn, M. G. Copper-catalyzed azide-alkyne click chemistry for bioconjugation. Curr. Protoc. Chem. Biol. 3, 153–162 (2011).
Wisniewski, J. R., Zougman, A., Nagaraj, N. & Mann, M. Universal sample preparation method for proteome analysis. Nat. Methods 6, 359–362 (2009).
Ross, P. L. et al. Multiplexed protein quantitation in Saccharomyces cerevisiae using amine-reactive isobaric tagging reagents. Mol. Cell Proteomics 3, 1154–1169 (2004).
Ong, S. E. & Mann, M. A practical recipe for stable isotope labeling by amino acids in cell culture (SILAC). Nat. Protoc. 1, 2650–2660 (2006).
Tyanova, S., Temu, T. & Cox, J. The MaxQuant computational platform for mass spectrometry-based shotgun proteomics. Nat. Protoc. 11, 2301–2319 (2016).
Perkins, D. N., Pappin, D. J., Creasy, D. M. & Cottrell, J. S. Probability-based protein identification by searching sequence databases using mass spectrometry data. Electrophoresis 20, 3551–3567 (1999).
Kwon, S. C. et al. The RNA-binding protein repertoire of embryonic stem cells. Nat. Struct. Mol. Biol. 20, 1122–1130 (2013).
Ying, Q. L. et al. The ground state of embryonic stem cell self-renewal. Nature 453, 519–523 (2008).
Choi, J. et al. Prolonged Mek1/2 suppression impairs the developmental potential of embryonic stem cells. Nature 548, 219–223 (2017).
Yagi, M. et al. Derivation of ground-state female ES cells maintaining gamete-derived DNA methylation. Nature 548, 224–227 (2017).
Zhang, M. et al. -Catenin safeguards the ground state of mousepluripotency by strengthening the robustness of the transcriptional apparatus. Sci. Adv. 6, eaba1593 (2020).
Du, J., Cullen, J. J. & Buettner, G. R. Ascorbic acid: chemistry, biology and the treatment of cancer. Biochim. Biophys. Acta 1826, 443–457 (2012).
Arun, G., Akhade, V. S., Donakonda, S. & Rao, M. R. mrhl RNA, a long noncoding RNA, negatively regulates Wnt signaling through its protein partner Ddx5/p68 in mouse spermatogonial cells. Mol. Cell Biol. 32, 3140–3152 (2012).
Castello, A. et al. System-wide identification of RNA-binding proteins by interactome capture. Nat. Protoc. 8, 491–500 (2013).
Livak, K. J. & Schmittgen, T. D. Analysis of relative gene expression data using real-time quantitative PCR and the 2(-Delta Delta C(T)) Method. Methods 25, 402–408 (2001).
Langmead, B. & Salzberg, S. L. Fast gapped-read alignment with Bowtie 2. Nat. Methods 9, 357–359 (2012).
Gentleman, R. C. et al. Bioconductor: open software development for computational biology and bioinformatics. Genome Biol. 5, R80 (2004).
Smyth, G. K. Linear models and empirical Bayes methods for assessing differential expression in microarray experiments. Stat. Appl. Genet. Mol. Biol. 3, Article3 (2004).
Benjamini, Y. & Hochberg, Y. Controlling the false discovery rate: a practical and powerful approach to multiple testing. J. R. Stat. Soc. B Methodol. 57, 289–300 (1995).
Danan, C., Manickavel, S. & Hafner, M. PAR-CLIP: a method for transcriptome-wide identification of RNA binding protein interaction sites. Methods Mol. Biol. 1358, 153–173 (2016).
Conrad, T. et al. Serial interactome capture of the human cell nucleus. Nat. Commun. 7, 11212 (2016).
Perez-Perri, J. I. et al. Global analysis of RNA-binding protein dynamics by comparative and enhanced RNA interactome capture. Nat. Protoc. 16, 27–60 (2021).
Mahat, D. B. et al. Base-pair-resolution genome-wide mapping of active RNA polymerases using precision nuclear run-on (PRO-seq). Nat. Protoc. 11, 1455–1476 (2016).
Fuchs, G. et al. 4sUDRB-seq: measuring genomewide transcriptional elongation rates and initiation frequencies within cells. Genome Biol. 15, R69 (2014).
Schwalb, B. et al. TT-seq maps the human transient transcriptome. Science 352, 1225–1228 (2016).
Herzog, V. A. et al. Thiol-linked alkylation of RNA to assess expression dynamics. Nat. Methods 14, 1198–1204 (2017).
Paulsen, M. T. et al. Use of Bru-Seq and BruChase-Seq for genome-wide assessment of the synthesis and stability of RNA. Methods 67, 45–54 (2014).
Acknowledgements
We thank all members of the Esteban lab for their support. This work was supported by the National Key Research and Development Program of China (2018YFA0106903, 2016YFA0100102 to M.A.E. and 2016YFA0100701 to X.B.), the Strategic Priority Research Program of the Chinese Academy of Sciences (XDA16030502 to M.A.E.), the Youth Innovation Promotion Association of the Chinese Academy of Sciences (Y201967 to X.B.), the Innovative Team Program of the Bioland Laboratory (Guangzhou Regenerative Medicine and Health Guangdong Laboratory) (2018GZR110103001 to M.A.E.), the National Natural Science Foundation of China (U20A2015, 92068106 to M.A.E. and 31900617 to X.G.), the Joint Research Project of Chinese Academy of Sciences and Japan Society for the Promotion of Science (GJHZ2093 to M.A.E.), the Natural Science Foundation of Guangdong Province (2018B030306042 to X.B.) and the Science and Technology Planning Project of Guangdong Province (2020B1212060052 to M.A.E.).
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X.B., X.G. and M.A.E. designed the original RICK experimental protocol; X.G., M.T., Y.L., S.K., Y.L. and X.W. performed all the experiments with help from N.L., M.J., J.M., M.Y., J.H. and J.Y; M.A.E. X.G. and X.B. wrote the manuscript with help from M.T., Y.L., S.K., Y.L. and X.W.; X.B. and M.A.E. approved the final version; Z.L., C.W., G.V., D.W., B.Q. and B.Z. provided advice and infrastructural support.
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Bao, X. et al. Nat. Methods 15, 213–220 (2018): https://doi.org/10.1038/nmeth.4595
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Guo, X., Tariq, M., Lai, Y. et al. Capture of the newly transcribed RNA interactome using click chemistry. Nat Protoc 16, 5193–5219 (2021). https://doi.org/10.1038/s41596-021-00609-y
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DOI: https://doi.org/10.1038/s41596-021-00609-y
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