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SAMMSON fosters cancer cell fitness by concertedly enhancing mitochondrial and cytosolic translation

Nature Structural & Molecular Biology volume 25, pages 1035–1046 (2018)Cite this article

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Abstract

Synchronization of mitochondrial and cytoplasmic translation rates is critical for the maintenance of cellular fitness, with cancer cells being especially vulnerable to translational uncoupling. Although alterations of cytosolic protein synthesis are common in human cancer, compensating mechanisms in mitochondrial translation remain elusive. Here we show that the malignant long non-coding RNA (lncRNA) SAMMSON promotes a balanced increase in ribosomal RNA (rRNA) maturation and protein synthesis in the cytosol and mitochondria by modulating the localization of CARF, an RNA-binding protein that sequesters the exo-ribonuclease XRN2 in the nucleoplasm, which under normal circumstances limits nucleolar rRNA maturation. SAMMSON interferes with XRN2 binding to CARF in the nucleus by favoring the formation of an aberrant cytoplasmic RNA–protein complex containing CARF and p32, a mitochondrial protein required for the processing of the mitochondrial rRNAs. These data highlight how a single oncogenic lncRNA can simultaneously modulate RNA–protein complex formation in two distinct cellular compartments to promote cell growth.

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Fig. 1: SAMMSON induces a malignant phenotype outside of the melanocytic lineage.
Fig. 2: Desynchronization of cytosolic and mitochondrial translation machinery decreases melanoma cell fitness and can be therefore exploited therapeutically.
Fig. 3: SAMMSON interacts with XRN2 and CARF.
Fig. 4: Identification of SAMMSON-binding region on XRN2 and of SAMMSON protein-binding domain.
Fig. 5: SAMMSON modulates XRN2 localization and function.
Fig. 6: SAMMSON promotes CARF localization to the cytoplasm and its binding to p32.
Fig. 7: SAMMSON expression increases rRNA processing thus promoting protein synthesis.
Fig. 8: Schematic representation of SAMMSON mechanism of action.

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Data availability

Small RNA sequencing data have been submitted to the Sequence Read Archive under accession code SRP151840. Source data and statistical analysis for Figs. 1a,b,d,e, 2a,c,e,f, 3a,d,f,h, 4c,e, 5c, 6d,g,h and 7b–g are available in the in the Supplementary Information online. All other data that support the findings of this study are available from the corresponding author upon reasonable request.

References

  1. Vander Heiden, M. G., Cantley, L. C. & Thompson, C. B. Understanding the Warburg Effect: the metabolic requirements of cell proliferation. Science (80-.). 324, 1029–1033 (2009).

    Article  Google Scholar 

  2. Wang, M. & Pestov, D. G. 5’-end surveillance by Xrn2 acts as a shared mechanism for mammalian pre-rRNA maturation and decay. Nucleic Acids Res. 39, 1811–1822 (2011).

    Article  Google Scholar 

  3. Teng, T., Thomas, G. & Mercer, C. A. Growth control and ribosomopathies. Curr. Opin. Genet. Dev. 23, 63–71 (2013).

    Article  CAS  Google Scholar 

  4. Wu, H., Sun, H., Liang, X., Lima, W. F. & Crooke, S. T. Human RNase H1 is associated with protein P32 and is involved in mitochondrial pre-rRNA processing. PLoS ONE 8, e71006 (2013).

    Article  CAS  Google Scholar 

  5. Ruggero, D. & Pandolfi, P. P. Does the ribosome translate cancer?. Nat. Rev. Cancer 3, 179–192 (2003).

    Article  CAS  Google Scholar 

  6. Mayer, C. & Grummt, I. Ribosome biogenesis and cell growth: mTOR coordinates transcription by all three classes of nuclear RNA polymerases. Oncogene 25, 6384–6391 (2006).

    Article  CAS  Google Scholar 

  7. Yang, L. et al. Regulation of SirT1-nucleomethylin binding by rRNA coordinates ribosome biogenesis with nutrient availability. Mol. Cell. Biol. 33, 3835–3848 (2013).

    Article  CAS  Google Scholar 

  8. Nishimura, K. et al. Perturbation of ribosome biogenesis drives cells into senescence through 5S RNP-mediated p53 activation. Cell Rep. 10, 1310–1323 (2015).

    Article  CAS  Google Scholar 

  9. Schmidt, O., Pfanner, N. & Meisinger, C. Mitochondrial protein import: from proteomics to functional mechanisms. Nat. Rev. Mol. Cell Biol. 11, 655–667 (2010).

    Article  CAS  Google Scholar 

  10. Fogal, V. et al. Mitochondrial p32 protein is a critical regulator of tumor metabolism via maintenance of oxidative phosphorylation. Mol. Cell. Biol. 30, 1303–1318 (2010).

    Article  CAS  Google Scholar 

  11. Skrtić, M. et al. Inhibition of mitochondrial translation as a therapeutic strategy for human acute myeloid leukemia. Cancer Cell. 20, 674–688 (2011).

    Article  Google Scholar 

  12. D’Andrea, A. et al. The mitochondrial translation machinery as a therapeutic target in Myc-driven lymphomas. Oncotarget 7, 72415–72430 (2016).

    Article  Google Scholar 

  13. Battersby, B. J. & Richter, U. Why translation counts for mitochondria – retrograde signalling links mitochondrial protein synthesis to mitochondrial biogenesis and cell proliferation. J. Cell. Sci. 126, 4331–4338 (2013).

    Article  CAS  Google Scholar 

  14. Wang, X. & Chen, X. J. A cytosolic network suppressing mitochondria-mediated proteostatic stress and cell death. Nature 524, 481–484 (2015).

    Article  CAS  Google Scholar 

  15. Wrobel, L. et al. Mistargeted mitochondrial proteins activate a proteostatic response in the cytosol. Nature 524, 485–488 (2015).

    Article  CAS  Google Scholar 

  16. Rosenwald, I. B. The role of translation in neoplastic transformation from a pathologist’s point of view. Oncogene 23, 3230–3247 (2004).

    Article  CAS  Google Scholar 

  17. Ruggero, D. The role of Myc-induced protein synthesis in cancer. Cancer Res. 69, 8839–8843 (2009).

    Article  CAS  Google Scholar 

  18. Fogal, V. et al. Mitochondrial p32 is upregulated in Myc expressing brain cancers and mediates glutamine addiction. Oncotarget 6, 1157–1170 (2015).

    Article  Google Scholar 

  19. Leucci, E. et al. Melanoma addiction to the long non-coding RNA SAMMSON. Nature 531, 518–522 (2016).

    Article  CAS  Google Scholar 

  20. Tollervey, D. Termination by torpedo. Nature 432, 456–457 (2004).

    Article  CAS  Google Scholar 

  21. Watanabe, K. et al. Degradation of initiator tRNAMet by Xrn1/2 via its accumulation in the nucleus of heat-treated HeLa cells. Nucleic Acids Res. 41, 4671–4685 (2013).

    Article  CAS  Google Scholar 

  22. Watanabe, K., Ijiri, K. & Ohtsuki, T. MTOR regulates the nucleoplasmic diffusion of Xrn2 under conditions of heat stress. FEBS Lett. 588, 3454–3460 (2014).

    Article  CAS  Google Scholar 

  23. Petfalski, E., Dandekar, T., Henry, Y. & Tollervey, D. Processing of the precursors to small nucleolar RNAs and rRNAs requires common components. Mol. Cell. Biol. 18, 1181–1189 (1998).

    Article  CAS  Google Scholar 

  24. Henras, A. K., Plisson-Chastang, C., O’Donohue, M. F., Chakraborty, A. & Gleizes, P. E. An overview of pre-ribosomal RNA processing in eukaryotes. Wiley Interdiscip. Rev. RNA 6, 225–242 (2015).

    Article  CAS  Google Scholar 

  25. Preti, M. et al. Gradual processing of the ITS1 from the nucleolus to the cytoplasm during synthesis of the human 18S rRNA. Nucleic Acids Res. 41, 4709–4723 (2013).

    Article  CAS  Google Scholar 

  26. Sato, S. et al. Collaborator of alternative reading frame protein (CARF) regulates early processing of pre-ribosomal RNA by retaining XRN2 (5′-3′ exoribonuclease) in the nucleoplasm. Nucleic Acids Res. 43, 10397–10410 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  27. Gupta, P. B. et al. The melanocyte differentiation program predisposes to metastasis after neoplastic transformation. Nat. Genet. 37, 1047–1054 (2005).

    Article  CAS  Google Scholar 

  28. Boshuizen, J. et al. Cooperative targeting of melanoma heterogeneity with an AXL antibody-drug conjugate and BRAF/MEK inhibitors. Nat. Med. 24, 203–212 (2018).

    Article  CAS  Google Scholar 

  29. Tripathi, V. et al. The nuclear-retained noncoding RNA MALAT1 regulates alternative splicing by modulating SR splicing factor phosphorylation. Mol. Cell 39, 925–938 (2010).

    Article  CAS  Google Scholar 

  30. Novo, C. et al. The heterochromatic chromosome caps in great apes impact telomere metabolism. Nucleic Acids Res. 41, 4792–4801 (2013).

    Article  CAS  Google Scholar 

  31. Livi, C. M., Klus, P., Delli Ponti, R. & Tartaglia, G. G. CatRAPID signature: identification of ribonucleoproteins and RNA-binding regions. Bioinformatics 32, 773–775 (2015).

    Article  Google Scholar 

  32. Richter, U. et al. A mitochondrial ribosomal and RNA decay pathway blocks cell proliferation. Curr. Biol. 23, 535–541 (2013).

    Article  CAS  Google Scholar 

  33. West, J. A. et al. The long noncoding RNAs NEAT1 and MALAT1 bind active chromatin sites. Mol. Cell 55, 791–802 (2014).

    Article  CAS  Google Scholar 

  34. Adriaens, C. et al. P53 induces formation of NEAT1 lncRNA-containing paraspeckles that modulate replication stress response and chemosensitivity. Nat. Med. 22, 861–868 (2016).

    Article  CAS  Google Scholar 

  35. Schillewaert, S., Wacheul, L., Lhomme, F. & Lafontaine, D. L. J. The evolutionarily conserved protein Las1 is required for pre-rRNA processing at both ends of ITS2. Mol. Cell. Biol. 32, 430–444 (2012).

    Article  CAS  Google Scholar 

  36. Tollervey, D. & Kiss, T. Function and synthesis of small nucleolar RNAs. Curr. Opin. Cell Biol. 9, 337–342 (1997).

    Article  CAS  Google Scholar 

  37. Weinstein, L. B. & Steitz, J. A. Guided tours: from precursor snoRNA to functional snoRNP. Curr. Opin. Cell Biol. 11, 378–384 (1999).

    Article  CAS  Google Scholar 

  38. Schmidt, E. K., Clavarino, G., Ceppi, M. & Pierre, P. SUnSET, a nonradioactive method to monitor protein synthesis. Nat. Methods 6, 275–277 (2009).

    Article  CAS  Google Scholar 

  39. Pianese, G., Teuscher, R. & Ziegler, E. Beitrag zur Histologie und Aetiologie des Carcinoms: Histologische und experimentelle Untersuchungen. (G. Fischer, Jena, Germany, 1896).

    Google Scholar 

  40. Bywater, M. J. et al. Inhibition of RNA polymerase I as a therapeutic strategy to promote cancer-specific activation of p53. Cancer Cell. 22, 51–65 (2012).

    Article  CAS  Google Scholar 

  41. Quin, J. E. et al. Targeting the nucleolus for cancer intervention. Biochim. Biophys. Acta 1842, 802–816 (2014).

    Article  CAS  Google Scholar 

  42. Silvera, D., Formenti, S. C. & Schneider, R. J. Translational control in cancer. Nat. Rev. Cancer 10, 254–266 (2010).

    Article  CAS  Google Scholar 

  43. Richter-Dennerlein, R., Dennerlein, S. & Rehling, P. Integrating mitochondrial translation into the cellular context. Nat. Rev. Mol. Cell Biol. 16, 586–592 (2015).

    Article  Google Scholar 

  44. Richter-Dennerlein, R. et al. Mitochondrial protein synthesis adapts to influx of nuclear-encoded protein. Cell 167, 471–483.e10 (2016).

    Article  CAS  Google Scholar 

  45. Richter, U., Lahtinen, T., Marttinen, P., Suomi, F. & Battersby, B. J. Quality control of mitochondrial protein synthesis is required for membrane integrity and cell fitness. J. Cell. Biol. 211, 373–389 (2015).

    Article  CAS  Google Scholar 

  46. Delloye-Bourgeois, C. et al. Nucleolar localization of a netrin-1 isoform enhances tumor cell proliferation. Sci. Signal. 5, ra57–ra57 (2012).

    Article  Google Scholar 

  47. Bellucci, M., Agostini, F., Masin, M. & Tartaglia, G. G. Predicting protein associations with long noncoding RNAs. Nat. Methods 8, 444–445 (2011).

    Article  CAS  Google Scholar 

  48. Cirillo, D. et al. Quantitative predictions of protein interactions with long noncoding RNAs: to the editor. Nat. Methods 14, 5–6 (2016).

    Article  Google Scholar 

  49. Ishikawa, H. et al. Identification of truncated forms of U1 snRNA reveals a novel RNA degradation pathway during snRNP biogenesis. Nucleic Acids Res. 42, 2708–2724 (2014).

    Article  CAS  Google Scholar 

  50. McHugh, C. A. et al. The Xist lncRNA interacts directly with SHARP to silence transcription through HDAC3. Nature 521, 232–236 (2015).

    Article  CAS  Google Scholar 

  51. Ishikawa, H. et al. Truncated forms of U2 snRNA (U2-tfs) are shunted toward a novel uridylylation pathway that differs from the degradation pathway for U1-tfs. RNA Biol. 15, 261–268 (2018).

    Article  Google Scholar 

  52. Tafforeau, L. et al. The complexity of human ribosome biogenesis revealed by systematic nucleolar screening of pre-rRNA processing factors. Mol. Cell 51, 539–551 (2013).

    Article  CAS  Google Scholar 

  53. Kozomara, A. & Griffiths-Jones, S. MiRBase: annotating high confidence microRNAs using deep sequencing data. Nucleic Acids Res. 42, D68–D73 (2014).

    Article  CAS  Google Scholar 

  54. Speir, M. L. et al. The UCSC Genome Browser database: 2016 update. Nucleic Acids Res. 44, D717–D725 (2016).

    Article  CAS  Google Scholar 

  55. Yates, A. et al. Ensembl 2016. Nucleic Acids Res. 44, D710–D716 (2016).

    Article  CAS  Google Scholar 

Download references

Acknowledgements

GapmeRs were designed by J. Lai (Exiqon, Copenhagen Denmark). We would like to thank M. Leucci for reading and editing the manuscript. This study was supported by the Fund Emile Carpentier—Fund André Vander Stricht—Fund Van Damme 2017-J1810830-207301. The authors wish to thank H. Brems for providing NHEM cultures, A. Sablina (VIB-KULeuven) for providing the SV40 LTA plasmid, M. Spinazzi (VIB-KULeuven) for the technical assistance and for sharing some antibodies, G. Ghanem (Jules Bordet Institute) for the patient-derived melanoma cell line and somersault18:24 (http://www.somersault1824.com/) for providing some graphical illustrations. R.V. is a recipient of the FWO PhD fellowship 1S08316N. D.L. is supported by Fonds National de la Recherche (FRS/FNRS). G.G.T.’s research is supported by the European Research Council (grant no. RIBOMYLOME_309545) and the Spanish Ministry of Economy and Competitiveness (grant nos. BFU2014-55054-P and BFU2017-86970-P).

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Authors and Affiliations

  1. Laboratory for RNA Cancer Biology, Department of Oncology, LKI, KU Leuven, Leuven, Belgium

    Roberto Vendramin, Yvessa Verheyden, Lucas Goedert & Eleonora Leucci

  2. Laboratory for Molecular Cancer Biology, Department of Oncology, LKI, KU Leuven, Leuven, Belgium

    Roberto Vendramin & Jean-Christophe Marine

  3. Laboratory For Molecular Cancer Biology, Center for Cancer Biology, VIB, Leuven, Belgium

    Roberto Vendramin & Jean-Christophe Marine

  4. Department of Applied Biological Science, Global Innovation Research Organizations, Tokyo University of Agriculture and Technology, Tokyo, Japan

    Hideaki Ishikawa, Keichi Izumikawa & Nobuhiro Takahashi

  5. RNA Molecular Biology, Center for Microscopy and Molecular Imaging, Université Libre de Bruxelles, Charleroi, Belgium

    Emilien Nicolas, Kritika Saraf & Denis L. J. Lafontaine

  6. Centre for Genomic Regulation, University Pompeu Fabra and Catalan Institution for Research and Advanced Studies, Barcelona, Spain

    Alexandros Armaos, Riccardo Delli Ponti & Gian Gaetano Tartaglia

  7. Center for Medical Genetics, Gent University, Gent, Belgium

    Pieter Mestdagh

  8. Cancer Research Institute Gent, Gent University, Gent, Belgium

    Pieter Mestdagh

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Contributions

E.L. and R.V. performed most experiments. Y.V. performed experiments described in Fig. 2f. E.N. and K.S. performed the nuclear rRNA northern blot (Fig. 5b and Supplementary Fig. 4a). R.D.P. and A.A. ran the RNA secondary structure prediction and in silico binding (Fig. 4f). P.M. performed the small RNA-seq (Fig. 5d and Supplementary Fig. 4d). H.I. and K.I. performed the experiments in Fig. 4g–i and Supplementary Fig. 4c. L.G. helped with Figs. 5a and 6a and in additional experiments provided to the reviewers and not included in the final manuscript. D.L., G.G.T. and N.T. helped in the interpretation of the data. E.L. and R.V. designed the study. J.C.M. and E.L. wrote the manuscript with input from all the authors.

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Correspondence to Eleonora Leucci.

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Supplementary Figure 1 SAMMSON actively participates to malignant transformation.

a, SAMMSON relative expression measured by RT–qPCR in Mel-ST cells infected with an empty (Ctrl) or a SAMMSON-encoding (SAMMSON O/E) expression vector; n = 7. b, Cell proliferation assays in Mel-ST cells described in a. Error bars represent mean +/− s.e.m.; n = 3. c, Colony formation assays 5 days after seeding 1 × 103 Mel-ST cells as described in a. The violet color is given by crystal violet, a compound that binds intracellular DNA and protein thus highlighting the cells in the plate. Representative image of five independent experiments. d, Quantification of colony formation assays of Mel-ST cells as described in a and c presented as the mean density (% of area occupancy); n = 5. e, Representative picture of xenograft tumors (encircled by the white dashed line) grown in nude mice derived from subcutaneous injection of 5 × 103 Mel-ST cells as described in a. f, Representative picture of resected xenograft tumors as described in e. Scale bar, 1 cm. g, Tumor volume of xenografts as described in e. Error bars represent mean +/− s.e.m.; n = 6. Box boundaries represent 25th and 75th percentiles; center line represents the median; whiskers, last data point within a ±1.5 interquartile range. P values were calculated by paired two-tailed Student’s t-test. * P < 0.05; ** P < 0.01; *** P < 0.001; **** P < 0.0001.

Supplementary Figure 2 XRN2, CARF and p32 levels are increased in melanoma.

a, Western blot for XRN2, CARF and p32 in NHEM, in SK-MEL-28 WT or BRAFi resistant (SK-MEL-28-R) and in a panel of short-term melanoma cultures (MM-lines, with different mutational backgrounds and phenotype). b, SAMMSON and HRPT pulldown in native (−) and ultraviolet crosslinking (+) conditions (using two sets of 48 biotinylated probes recognizing mature transcripts, p) and western blotting in SK-MEL-28 cells. Representative image of three independent experiments. Uncropped gel images are shown in Supplementary Data Set 1.

Supplementary Figure 3 CARF and XRN2 localization are specifically affected by SAMMSON knockdown and not by other stressors.

a, XRN2 (cyan) and CARF (yellow) IF in SK-MEL-28 cells 30 h after transfection with a non-targeting GapmeR (Ctrl), GapmeR3 or GapmeR11. Scale bar low magnification, 10 μm; high magnification, 2 μm. Representative image of three independent experiments. b, Puromycin (Puro, white) or p32 (magenta) IF in SK-MEL-28 cells treated for 48 h with 200 μg ml−1 chloramphenicol or vehicle (EtOH). Cell nuclei are stained with DAPI (cyan). Scale bar low magnification, 10 μm; high magnification, 2 μm. Representative image of three independent experiments. c, XRN2 (cyan) and fibrillarin (yellow) IF in SK-MEL-28 cells treated as in b. Scale bar low magnification, 10 μm; high magnification, 7 μm. Representative image of three independent experiments. d, NEAT1 (red) RNA FISH in untreated SK-MEL-28 cells (Mock) or in cells 72 h after transfection with a control siRNA pool (siCtrl) or pools targeting NEAT1 (siNEAT1) or siNEAT1 long form only (siNEAT1 long). Cell nuclei are stained with DAPI (blue). Scale bar low magnification, 10 μm; high magnification, 2 μm. Representative image of three independent experiments. e, XRN2 (cyan) and fibrillarin (yellow) IF in SK-MEL-28 cells treated as described in d. Scale bar low magnification, 10 μm; high magnification, 2 μm. Representative image of three independent experiments.

Supplementary Figure 4 XRN2 functions are specifically affected by SAMMSON knockdown.

a, Left, schematic representation of the pre-rRNAs and the mature rRNAs detected by northern blotting, the orange arrows indicate the sites of pre-rRNA-processing inhibition in the 5'-ETS (01, A0, and 1). The probe used is highlighted in grey. ETS: external transcribed spacers; ITS: internal transcribed spacers. The aberrant 34S RNA is produced when cleavage occurs in ITS1 prior to 5’-ETS. *, truncated form of the 34S RNA. Right, northern blot hybridization analysis of pre-rRNA isolated from three melanoma cell lines (with different mutational backgrounds and phenotype) transfected with a non-targeting GapmeR (Ctrl) or GapmeR11 (G11) or of SK-MEL-28 transfected with a XRN2-targeting (siXRN2) or control (siCtrl) siRNA. Knockdown efficiency is shown for both SAMMSON knockdown and XRN2 knockdown. Representative image of three independent experiments. b, SAMMSON (SAM), 18S, 16S, 12S, Cyclooxygenase 1 (COX1) and NADH-ubiquinone oxidoreductase chain 1 (ND1) relative expression measured by RT–qPCR in SK-MEL-28 cells 30 h after transfection with a non-targeting GapmeR (Ctrl) or with GapmeR11; n = 5. c, Northern blot hybridization analysis of mitochondrial pre-rRNA (mt_pre-rRNA) isolated from SK-MEL-28 cells transfected with a non-targeting GapmeR (Ctrl), GapmeR3 (G3) or a GapmeR11 (G11). Efficiency of SAMMSON knockdown and ratios of mt_pre-rRNA over 28S (the mature 28S is visualized by methylene blue staining of the denaturing agarose gel) rRNA are shown below the gel. Representative image of three independent experiments. d, tRNA61-MetCAT expression levels in SK-MEL-28 cells treated with a non-targeting GapmeR (Ctrl) and GapmeR3; n = 3. Box boundaries represent 25th and 75th percentiles; center line represents the median; whiskers, last data point within a ±1.5 interquartile range. P values were calculated by paired two-tailed Student’s t-test. * P < 0.05; ** P < 0.01; NS, not significant. Uncropped gel images are shown in Supplementary Data Set 1.

Supplementary Figure 5 CARF localization and its interaction with p32 are RNA and SAMMSON-dependent.

a, p32 (yellow) IF combined with 12S (red) RNA FISH in SK-MEL-28 cells 30 h after transfection with a non-targeting GapmeR (Ctrl), GapmeR3 or GapmeR11. Cell nuclei are stained with DAPI (cyan). Scale bar, 4 μm. Representative image of three independent experiments. b, PLA (cyan) using antibodies against CARF and p32 in SK-MEL-28 cells in normal conditions (Ctrl) or after addition of RNase A. Cell nuclei are stained with DAPI (blue). Scale bar low magnification, 10 μm; high magnification, 2 μm. Representative image of three independent experiments. c, p32 RIP in LCL cells infected with an empty (−) or a SAMMSON-encoding (+) expression vector and western blotting. Representative image of three independent experiments. d, CARF (red) and p32 (yellow) IF in LCL cells as described in c. Cell nuclei are stained with DAPI (blue). Scale bar low magnification, 10 μm, Scale bar high magnification, 2 μm. Representative image of three independent experiments. Uncropped gel images are shown in Supplementary Data Set 1.

Supplementary Figure 6 SAMMSON regulates the interaction between XRN2, CARF and p32.

a, CARF (magenta) and mitotracker (white) IF in SK-MEL-28 cells 72 h after transfection with a control siRNA pool (siCtrl) or an siRNA pool targeting CARF (siCARF). Cell nuclei are stained with DAPI (cyan). Scale bar, 10 μm. Representative image of three independent experiments. b, PLA (cyan) assay using antibodies against CARF and p32 in Mel-ST cells described in Supplementary Fig. 1a. Cell nuclei are stained with DAPI (blue). Scale bar low magnification, 10 μm; high magnification, 2 μm. c, SAMMSON relative expression measured by RT–qPCR in SK-MEL-28 cells 30 h after transfection with a non-targeting GapmeR (Ctrl) or GapmeR11 (G11). Error bars represent mean +/− s.e.m.; n = 3. d, CARF IP in SK-MEL-28 cells treated as described in c and western blotting. Representative image of three independent experiments. P values were calculated by paired two-tailed Student’s t-test. ** P < 0.01. Uncropped gel images are shown in Supplementary Data Set 1.

Supplementary Figure 7 SAMMSON regulates rRNA biogenesis and protein synthesis.

a, Pre-rRNA-processing analysis in Mel-ST cells infected with an empty (Ctrl) or a SAMMSON-encoding (SAM O/E) expression vector. Left, structure of the pre-rRNAs detected and probes used. The aberrant 34S RNA observed after SAMMSON depletion (see Fig. 5b) is highlighted in red. Right, northern blot hybridizations. The mature rRNAs are visualized by ethidium-bromide staining of the denaturing agarose gel. Representative image of three independent experiments. b, Western blotting after a 10-min pulse with puromycin and subsequent cytosol (Cyto)/mitochondria (Mito)/mitoplast (Mitopl) fractionation in Mel-ST cells infected with an empty (Ctrl) or a SAMMSON-encoding (SAM O/E). Representative image of four (Total and Cyto) and three (Mito and Mitopl) independent experiments. c, Western blotting after a 10-min pulse with puromycin and subsequent cytosol (Cyto)/mitochondria (Mito)/mitoplast (Mitopl) fractionation in LCL cells described in a. Representative image of five independent experiments. d, Western blotting after cytosol (Cyto)/mitochondria (Mito)/proteinase K-treated mitochondria (Mito+PK) fractionation in LCL cells described in Fig. 1a. Representative image of four independent experiments. e, Western blotting after a 3-h pulse with azidohomoalanine, followed by cytosol (Cyto)/mitochondria (Mito)/proteinase K-treated mitochondria (Mito+PK) fractionation and subsequent Click-iT alkyne reaction in LCL cells described in Fig. 1a. f, Immunohistochemistry Ki67 staining of xenograft tumors as described in Supplementary Fig. 1e–g. Scale bar, 100 μm. Representative image of eight independent experiments. g, Immunohistochemistry puromycin staining of tumors as described in Supplementary Fig. 1e–g. Scale bar, 100 μm. Representative image of eight independent experiments. Uncropped gel images are shown in Supplementary Data Set 1.

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Vendramin, R., Verheyden, Y., Ishikawa, H. et al. SAMMSON fosters cancer cell fitness by concertedly enhancing mitochondrial and cytosolic translation. Nat Struct Mol Biol 25, 1035–1046 (2018). https://doi.org/10.1038/s41594-018-0143-4

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