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Widespread changes in protein synthesis induced by microRNAs

Author

Listed:
  • Matthias Selbach

    (Max Delbrück Center for Molecular Medicine, Robert-Rössle Str. 10, D-13125 Berlin, Germany)

  • Björn Schwanhäusser

    (Max Delbrück Center for Molecular Medicine, Robert-Rössle Str. 10, D-13125 Berlin, Germany)

  • Nadine Thierfelder

    (Max Delbrück Center for Molecular Medicine, Robert-Rössle Str. 10, D-13125 Berlin, Germany)

  • Zhuo Fang

    (Max Delbrück Center for Molecular Medicine, Robert-Rössle Str. 10, D-13125 Berlin, Germany)

  • Raya Khanin

    (15 University Gardens, University of Glasgow, Glasgow, G12 8QQ, UK)

  • Nikolaus Rajewsky

    (Max Delbrück Center for Molecular Medicine, Robert-Rössle Str. 10, D-13125 Berlin, Germany)

Abstract

Animal microRNAs (miRNAs) regulate gene expression by inhibiting translation and/or by inducing degradation of target messenger RNAs. It is unknown how much translational control is exerted by miRNAs on a genome-wide scale. We used a new proteomic approach to measure changes in synthesis of several thousand proteins in response to miRNA transfection or endogenous miRNA knockdown. In parallel, we quantified mRNA levels using microarrays. Here we show that a single miRNA can repress the production of hundreds of proteins, but that this repression is typically relatively mild. A number of known features of the miRNA-binding site such as the seed sequence also govern repression of human protein synthesis, and we report additional target sequence characteristics. We demonstrate that, in addition to downregulating mRNA levels, miRNAs also directly repress translation of hundreds of genes. Finally, our data suggest that a miRNA can, by direct or indirect effects, tune protein synthesis from thousands of genes.

Suggested Citation

  • Matthias Selbach & Björn Schwanhäusser & Nadine Thierfelder & Zhuo Fang & Raya Khanin & Nikolaus Rajewsky, 2008. "Widespread changes in protein synthesis induced by microRNAs," Nature, Nature, vol. 455(7209), pages 58-63, September.
    • Handle: RePEc:nat:nature:v:455:y:2008:i:7209:d:10.1038_nature07228
    DOI: 10.1038/nature07228
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    Cited by:

    1. Urmo Võsa & Tõnu Esko & Silva Kasela & Tarmo Annilo, 2015. "Altered Gene Expression Associated with microRNA Binding Site Polymorphisms," PLOS ONE, Public Library of Science, vol. 10(10), pages 1-24, October.
    2. Panagiotis Alexiou & Manolis Maragkakis & Giorgio L Papadopoulos & Victor A Simmosis & Lin Zhang & Artemis G Hatzigeorgiou, 2010. "The DIANA-mirExTra Web Server: From Gene Expression Data to MicroRNA Function," PLOS ONE, Public Library of Science, vol. 5(2), pages 1-7, February.
    3. Ramkrishna Mitra & Sanghamitra Bandyopadhyay, 2011. "MultiMiTar: A Novel Multi Objective Optimization based miRNA-Target Prediction Method," PLOS ONE, Public Library of Science, vol. 6(9), pages 1-13, September.
    4. Wenliang Zhu & Xuan Kan, 2014. "Neural Network Cascade Optimizes MicroRNA Biomarker Selection for Nasopharyngeal Cancer Prognosis," PLOS ONE, Public Library of Science, vol. 9(10), pages 1-7, October.
    5. Yuheng Lu & Christina S Leslie, 2016. "Learning to Predict miRNA-mRNA Interactions from AGO CLIP Sequencing and CLASH Data," PLOS Computational Biology, Public Library of Science, vol. 12(7), pages 1-18, July.
    6. Zhdanov, Vladimir P., 2010. "ncRNA-mediated bistability in the synthesis of hundreds of distinct mRNAs and proteins," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(4), pages 887-890.
    7. David Lyon & Maria Angeles Castillejo & Christiana Staudinger & Wolfram Weckwerth & Stefanie Wienkoop & Volker Egelhofer, 2014. "Automated Protein Turnover Calculations from 15N Partial Metabolic Labeling LC/MS Shotgun Proteomics Data," PLOS ONE, Public Library of Science, vol. 9(4), pages 1-10, April.
    8. Adam A Margolin & Shao-En Ong & Monica Schenone & Robert Gould & Stuart L Schreiber & Steven A Carr & Todd R Golub, 2009. "Empirical Bayes Analysis of Quantitative Proteomics Experiments," PLOS ONE, Public Library of Science, vol. 4(10), pages 1-15, October.
    9. Chikako Ragan & Michael Zuker & Mark A Ragan, 2011. "Quantitative Prediction of miRNA-mRNA Interaction Based on Equilibrium Concentrations," PLOS Computational Biology, Public Library of Science, vol. 7(2), pages 1-11, February.
    10. Youjia Hua & Shiwei Duan & Andrea E Murmann & Niels Larsen & Jørgen Kjems & Anders H Lund & Marcus E Peter, 2011. "miRConnect: Identifying Effector Genes of miRNAs and miRNA Families in Cancer Cells," PLOS ONE, Public Library of Science, vol. 6(10), pages 1-16, October.
    11. Peng Wang & Shangwei Ning & Qianghu Wang & Ronghong Li & Jingrun Ye & Zuxianglan Zhao & Yan Li & Teng Huang & Xia Li, 2013. "mirTarPri: Improved Prioritization of MicroRNA Targets through Incorporation of Functional Genomics Data," PLOS ONE, Public Library of Science, vol. 8(1), pages 1-12, January.
    12. W.L. Bai & Y.L. Dang & R.H. Yin & R.L. Yin & W.Q. Jiang & Z.Y. Wang & Y.B. Zhu & J.J. Wang & Z.H. Zhao & G.B. Luo, 2016. "Combination of let-7d-5p, miR-26a-5p, and miR-15a-5p is suitable normalizer for studying microRNA expression in skin tissue of Liaoning cashmere goat during hair follicle cycle," Czech Journal of Animal Science, Czech Academy of Agricultural Sciences, vol. 61(3), pages 99-107.
    13. Yasemin Oztemur & Tufan Bekmez & Alp Aydos & Isik G Yulug & Betul Bozkurt & Bala Gur Dedeoglu, 2015. "A Ranking-Based Meta-Analysis Reveals Let-7 Family as a Meta-Signature for Grade Classification in Breast Cancer," PLOS ONE, Public Library of Science, vol. 10(5), pages 1-16, May.
    14. Parawee Lekprasert & Michael Mayhew & Uwe Ohler, 2011. "Assessing the Utility of Thermodynamic Features for microRNA Target Prediction under Relaxed Seed and No Conservation Requirements," PLOS ONE, Public Library of Science, vol. 6(6), pages 1-13, June.
    15. Evelyn Zacharewicz & Paul Della Gatta & John Reynolds & Andrew Garnham & Tamsyn Crowley & Aaron P Russell & Séverine Lamon, 2014. "Identification of MicroRNAs Linked to Regulators of Muscle Protein Synthesis and Regeneration in Young and Old Skeletal Muscle," PLOS ONE, Public Library of Science, vol. 9(12), pages 1-25, December.
    16. Jana Zecha & Wassim Gabriel & Ria Spallek & Yun-Chien Chang & Julia Mergner & Mathias Wilhelm & Florian Bassermann & Bernhard Kuster, 2022. "Linking post-translational modifications and protein turnover by site-resolved protein turnover profiling," Nature Communications, Nature, vol. 13(1), pages 1-14, December.
    17. Ray M Marín & Jiří Vaníček, 2012. "Optimal Use of Conservation and Accessibility Filters in MicroRNA Target Prediction," PLOS ONE, Public Library of Science, vol. 7(2), pages 1-11, February.

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