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Mapping spatial transcriptome with light-activated proximity-dependent RNA labeling

Nature Chemical Biology volume 15, pages 1110–1119 (2019)Cite this article

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Abstract

RNA molecules are highly compartmentalized in eukaryotic cells, with their localizations intimately linked to their functions. Despite the importance of RNA targeting, our current knowledge of the spatial organization of the transcriptome has been limited by a lack of analytical tools. In this study, we develop a chemical biology approach to label RNAs in live cells with high spatial specificity. Our method, called CAP-seq, capitalizes on light-activated, proximity-dependent photo-oxidation of RNA nucleobases, which could be subsequently enriched via affinity purification and identified by high-throughput sequencing. Using this technique, we investigate the local transcriptomes that are proximal to various subcellular compartments, including the endoplasmic reticulum and mitochondria. We discover that messenger RNAs encoding for ribosomal proteins and oxidative phosphorylation pathway proteins are highly enriched at the outer mitochondrial membrane. Due to its specificity and ease of use, CAP-seq is a generally applicable technique to investigate the spatial transcriptome in many biological systems.

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Fig. 1: Development and characterization of CAP-seq method.
Fig. 2: CAP-seq reveals subcellular transcriptome in the mitochondrial matrix.
Fig. 3: Mapping of the ER-proximal transcriptome.
Fig. 4: Mapping local transcriptome at the OMM.
Fig. 5: Validation of RNAs identified in OMM CAP-seq.
Fig. 6: OMM CAP-seq with drug perturbation.

Data availability

All data presented in this study are available in the main text and Supplementary Information. Sequencing data are included in Source Data Figs. 2–4 and 6a,d.

References

  1. Buxbaum, A. R., Haimovich, G. & Singer, R. H. In the right place at the right time: visualizing and understanding mRNA localization. Nat. Rev. Mol. Cell Biol. 16, 95–109 (2015).

    Article  CAS  PubMed  Google Scholar 

  2. Jung, H., Gkogkas, C. G., Sonenberg, N. & Holt, C. E. Remote control of gene function by local translation. Cell 157, 26–40 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  3. Sepulveda, G. et al. Co-translational protein targeting facilitates centrosomal recruitment of PCNT during centrosome maturation in vertebrates. eLife 7, e34959 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  4. Martin, K. C. & Ephrussi, A. mRNA localization: gene expression in the spatial dimension. Cell 136, 719–730 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  5. Cioni, J. M., Koppers, M. & Holt, C. E. Molecular control of local translation in axon development and maintenance. Curr. Opin. Neurobiol. 51, 86–94 (2018).

    Article  CAS  PubMed  Google Scholar 

  6. Glock, C., Heumuller, M. & Schuman, E. M. mRNA transport & local translation in neurons. Curr. Opin. Neurobiol. 45, 169–177 (2017).

    Article  CAS  PubMed  Google Scholar 

  7. Engreitz, J. M., Ollikainen, N. & Guttman, M. Long non-coding RNAs: spatial amplifiers that control nuclear structure and gene expression. Nat. Rev. Mol. Cell. Biol. 17, 756–770 (2016).

    Article  CAS  PubMed  Google Scholar 

  8. Diehn, M., Bhattacharya, R., Botstein, D. & Brown, P. O. Genome-scale identification of membrane-associated human mRNAs. PLoS Genet. 2, e11 (2006).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  9. Chen, Q., Jagannathan, S., Reid, D. W., Zheng, T. & Nicchitta, C. V. Hierarchical regulation of mRNA partitioning between the cytoplasm and the endoplasmic reticulum of mammalian cells. Mol. Biol. Cell 22, 2646–2658 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. Marc, P. et al. Genome-wide analysis of mRNAs targeted to yeast mitochondria. EMBO Rep. 3, 159–164 (2002).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. Mercer, T. R. et al. The human mitochondrial transcriptome. Cell 146, 645–658 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Cajigas, I. J. et al. The local transcriptome in the synaptic neuropil revealed by deep sequencing and high-resolution imaging. Neuron 74, 453–466 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  13. Minis, A. et al. Subcellular transcriptomics-dissection of the mRNA composition in the axonal compartment of sensory neurons. Dev. Neurobiol. 74, 365–381 (2014).

    Article  CAS  PubMed  Google Scholar 

  14. Hocine, S., Raymond, P., Zenklusen, D., Chao, J. A. & Singer, R. H. Single-molecule analysis of gene expression using two-color RNA labeling in live yeast. Nat. Methods 10, 119–121 (2013).

    Article  CAS  PubMed  Google Scholar 

  15. Femino, A. M., Fay, F. S., Fogarty, K. & Singer, R. H. Visualization of single RNA transcripts in situ. Science 280, 585–590 (1998).

    Article  CAS  PubMed  Google Scholar 

  16. Chen, K. H., Boettiger, A. N., Moffitt, J. R., Wang, S. & Zhuang, X. RNA imaging. Spatially resolved, highly multiplexed RNA profiling in single cells. Science 348, aaa6090 (2015).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  17. Lee, J. H. et al. Highly multiplexed subcellular RNA sequencing in situ. Science 343, 1360–1363 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Wang, X. et al. Three-dimensional intact-tissue sequencing of single-cell transcriptional states. Science 361, eaat5691 (2018).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  19. Rhee, H. W. et al. Proteomic mapping of mitochondria in living cells via spatially restricted enzymatic tagging. Science 339, 1328–1331 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. Kaewsapsak, P., Shechner, D. M., Mallard, W., Rinn, J. L. & Ting, A. Y. Live-cell mapping of organelle-associated RNAs via proximity biotinylation combined with protein-RNA crosslinking. eLife 6, e29224 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  21. Benhalevy, D., Anastasakis, D. G. & Hafner, M. Proximity-CLIP provides a snapshot of protein-occupied RNA elements in subcellular compartments. Nat. Methods 15, 1074–1082 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  22. Fleming, A. M. & Burrows, C. J. Formation and processing of DNA damage substrates for the hNEIL enzymes. Free Radic. Biol. Med. 107, 35–52 (2017).

    Article  CAS  PubMed  Google Scholar 

  23. Bulina, M. E. et al. A genetically encoded photosensitizer. Nat. Biotechnol. 24, 95–99 (2006).

    Article  CAS  PubMed  Google Scholar 

  24. Shu, X. et al. A genetically encoded tag for correlated light and electron microscopy of intact cells, tissues, and organisms. PLoS Biol. 9, e1001041 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. Westberg, M., Holmegaard, L., Pimenta, F. M., Etzerodt, M. & Ogilby, P. R. Rational design of an efficient, genetically encodable, protein-encased singlet oxygen photosensitizer. J. Am. Chem. Soc. 137, 1632–1642 (2015).

    Article  CAS  PubMed  Google Scholar 

  26. Vegh, R. B. et al. Reactive oxygen species in photochemistry of the red fluorescent protein ‘Killer Red’. Chem. Commun. 47, 4887–4889 (2011).

    Article  CAS  Google Scholar 

  27. Makhijani, K. et al. Precision optogenetic tool for selective single- and multiple-cell ablation in a live animal model system. Cell. Chem. Biol. 24, 110–119 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  28. Moan, J. On the diffusion length of singlet oxygen in cells and tissues. J. Photoch. Photobio. B. 6, 343–347 (1990).

    Article  CAS  Google Scholar 

  29. Morikawa, M. et al. Analysis of guanine oxidation products in double-stranded DNA and proposed guanine oxidation pathways in single-stranded, double-stranded or quadruplex DNA. Biomolecules 4, 140–159 (2014).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  30. Xu, X., Muller, J. G., Ye, Y. & Burrows, C. J. DNA-protein cross-links between guanine and lysine depend on the mechanism of oxidation for formation of C5 vs C8 guanosine adducts. J. Am. Chem. Soc. 130, 703–709 (2008).

    Article  CAS  PubMed  Google Scholar 

  31. Ding, Y., Fleming, A. M. & Burrows, C. J. Sequencing the mouse genome for the oxidatively modified base 8-oxo-7,8-dihydroguanine by OG-Seq. J. Am. Chem. Soc. 139, 2569–2572 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  32. Bisby, R. H., Morgan, C. G., Hamblett, I. & Gorman, A. A. Quenching of singlet oxygen by Trolox C, ascorbate, and amino acids: effects of pH and temperature. J. Phys. Chem. A. 103, 7454–7459 (1999).

    Article  CAS  Google Scholar 

  33. Jan, C. H., Williams, C. C. & Weissman, J. S. Principles of ER cotranslational translocation revealed by proximity-specific ribosome profiling. Science 346, 1257521 (2014).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  34. Linden, A. Measuring diagnostic and predictive accuracy in disease management: an introduction to receiver operating characteristic (ROC) analysis. J. Eval. Clin. Pract. 12, 132–139 (2006).

    Article  PubMed  Google Scholar 

  35. Williams, C. C., Jan, C. H. & Weissman, J. S. Targeting and plasticity of mitochondrial proteins revealed by proximity-specific ribosome profiling. Science 346, 748–751 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  36. Lesnik, C., Golani-Armon, A. & Arava, Y. Localized translation near the mitochondrial outer membrane: an update. RNA Biol. 12, 801–809 (2015).

    Article  PubMed  PubMed Central  Google Scholar 

  37. Calvo, S. E., Clauser, K. R. & Mootha, V. K. MitoCarta2.0: an updated inventory of mammalian mitochondrial proteins. Nucleic Acids Res. 44, D1251–D1257 (2016).

    Article  CAS  PubMed  Google Scholar 

  38. Anger, A. M. et al. Structures of the human and Drosophila 80S ribosome. Nature 497, 80–85 (2013).

    Article  CAS  PubMed  Google Scholar 

  39. Khatter, H., Myasnikov, A. G., Natchiar, S. K. & Klaholz, B. P. Structure of the human 80S ribosome. Nature 520, 640–645 (2015).

    Article  CAS  PubMed  Google Scholar 

  40. Li, Y., Aggarwal, M. B., Nguyen, K., Ke, K. & Spitale, R. C. Assaying RNA localization in situ with spatially restricted nucleobase oxidation. ACS Chem. Biol. 12, 2709–2714 (2017).

    Article  CAS  PubMed  Google Scholar 

  41. Li, Y., Aggarwal, M. B., Ke, K., Nguyen, K. & Spitale, R. C. Improved analysis of RNA localization by spatially restricted oxidation of RNA-protein complexes. Biochemistry 57, 1577–1581 (2018).

    Article  CAS  PubMed  Google Scholar 

  42. Fazal, F. M. et al. Atlas of subcellular RNA localization revealed by APEX-Seq. Cell 178, 1–18 (2019).

    Article  CAS  Google Scholar 

  43. Chen, C. Y., Ezzeddine, N., & Shyu, A. B. & Messenger, R. N. A. MehMessenger RNA half-life measurements in mammalian cells. Methods Enzymol. 448, 335–357 (2008).

  44. Bustamante, J., Boisson-Dupuis, S., Abel, L. & Casanova, J. L. Mendelian susceptibility to mycobacterial disease: genetic, immunological, and clinical features of inborn errors of IFN-gamma immunity. Semin. Immunol. 26, 454–470 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  45. Kumar, K. G. et al. Identification of adropin as a secreted factor linking dietary macronutrient intake with energy homeostasis and lipid metabolism. Cell Metab. 8, 468–481 (2008).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  46. Brigelius-Flohe, R. & Maiorino, M. Glutathione peroxidases. Biochim. Biophys. Acta 1830, 3289–3303 (2013).

    Article  CAS  PubMed  Google Scholar 

  47. Kaur, S. J., McKeown, S. R. & Rashid, S. Mutant SOD1 mediated pathogenesis of amyotrophic lateral sclerosis. Gene 577, 109–118 (2016).

    Article  CAS  PubMed  Google Scholar 

  48. Maiorino, M., Conrad, M. & Ursini, F. GPx4, lipid peroxidation, and cell death: discoveries, rediscoveries, and open issues. Antioxid. Redox. Signal 29, 61–74 (2018).

    Article  CAS  PubMed  Google Scholar 

  49. Liang, H. et al. Short form glutathione peroxidase 4 is the essential isoform required for survival and somatic mitochondrial functions. J. Biol. Chem. 284, 30836–30844 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  50. Kawamata, H. & Manfredi, G. Import, maturation, and function of SOD1 and its copper chaperone CCS in the mitochondrial intermembrane space. Antioxid. Redox Signal 13, 1375–1384 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  51. Kim, D., Langmead, B. & Salzberg, S. L. HISAT: a fast spliced aligner with low memory requirements. Nat. Methods 12, 357–360 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  52. Anders, S., Pyl, P. T. & Huber, W. HTSeq-a Python framework to work with high-throughput sequencing data. Bioinformatics 31, 166–169 (2015).

    Article  CAS  PubMed  Google Scholar 

  53. Love, M. I., Huber, W. & Anders, S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol. 15, 550 (2014).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  54. Kall, L., Krogh, A. & Sonnhammer, E. L. A combined transmembrane topology and signal peptide prediction method. J. Mol. Biol. 338, 1027–1036 (2004).

    Article  CAS  PubMed  Google Scholar 

  55. Petersen, T. N., Brunak, S., von Heijne, G. & Nielsen, H. SignalP 4.0: discriminating signal peptides from transmembrane regions. Nat. Methods 8, 785–786 (2011).

    Article  CAS  PubMed  Google Scholar 

  56. Krogh, A., Larsson, B., von Heijne, G. & Sonnhammer, E. L. Predicting transmembrane protein topology with a hidden Markov model: application to complete genomes. J. Mol. Biol. 305, 567–580 (2001).

    Article  CAS  PubMed  Google Scholar 

  57. Tsanov, N. et al. smiFISH and FISH—a flexible single RNA detection approach with super-resolution capability. Nucleic Acids Res. 44, e165 (2016).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

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Acknowledgements

We acknowledge funding from the National Key R&D Program of China (Ministry of Science and Technology, grant nos. 2017YFA0503600 and 2018YFA0507600), the National Natural Science Foundation of China (grant nos. 91753131 and 21675098), Beijing Natural Science Foundation (grant no. 5182011), the Interdisciplinary Medicine Seed Fund of Peking University (grant no. BMU2017MC006), Li Ge-Zhao Ning Life Science Junior Research Fellowship and Beijing Advanced Innovation Center for Structural Biology. P.Z. and J.W. are sponsored by the National Thousand Young Talents Award. We thank X. Chen (Peking University, Beijing, China), K. Sarkisyan (Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Moscow, Russia) and A.Y. Ting (Stanford University, USA) for providing plasmids, and J. Yang (Peking University, Beijing, China) for providing HEK293T cells. T. Ding assisted with photo-oxidation product characterization. C. Xiao assisted with streptavidin dot blot analysis. We thank Y. Wang, M. Conrad and Y. Sun for advice, and the National Center for Protein Sciences at Peking University in Beijing, China, for assistance with Fragment Analyzer 12.

Author information

Author notes

  1. These authors contributed equally: Pengchong Wang, Wei Tang, Zeyao Li.

Authors and Affiliations

  1. School of Life Sciences, Tsinghua University, Beijing, China

    Pengchong Wang, Zeyao Li & Jianbin Wang

  2. College of Chemistry and Molecular Engineering, Peking University, Beijing, China

    Pengchong Wang, Zhongyu Zou, Ying Zhou & Peng Zou

  3. Synthetic and Functional Biomolecules Center, Peking University, Beijing, China

    Pengchong Wang, Zhongyu Zou, Ying Zhou & Peng Zou

  4. Beijing National Laboratory for Molecular Sciences, Peking University, Beijing, China

    Pengchong Wang, Zhongyu Zou, Ying Zhou & Peng Zou

  5. Key Laboratory of Bioorganic Chemistry and Molecular Engineering of Ministry of Education, Peking University, Beijing, China

    Pengchong Wang, Zhongyu Zou, Ying Zhou & Peng Zou

  6. Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, China

    Wei Tang & Ran Li

  7. Peking-Tsinghua Center for Life Sciences, Beijing, China

    Wei Tang, Ran Li, Jianbin Wang & Peng Zou

  8. Peking-Tsinghua-NIBS Joint Graduate Program, Tsinghua University, Beijing, China

    Zeyao Li

  9. Department of Chemical Biology, College of Chemistry, Nankai University, Tianjin, China

    Tianyu Xiong

  10. Chinese Institute for Brain Research, Beijing, China

    Jianbin Wang

  11. PKU-IDG/McGovern Institute for Brain Research, Beijing, China

    Peng Zou

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  1. Pengchong Wang
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Contributions

P.W., W.T. and P.Z. conceived the project. P.W., W.T., Z.L., J.W. and P.Z. designed the experiments. P.W. and W.T. performed all experiments, unless otherwise noted. Z.L. and J.W. designed sequencing data analysis. Z.Z. and R.L. carried out mass-spec experiments. Y.Z. carried out probe synthesis. P.W. and T.X. carried out FISH experiments. P.W., W.T., Z.L., J.W. and P.Z. analyzed data. P.W., W.T. and P.Z. wrote the paper with input from all authors.

Corresponding authors

Correspondence to Jianbin Wang or Peng Zou.

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Wang, P., Tang, W., Li, Z. et al. Mapping spatial transcriptome with light-activated proximity-dependent RNA labeling. Nat Chem Biol 15, 1110–1119 (2019). https://doi.org/10.1038/s41589-019-0368-5

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