Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Article
  • Published:

An Argonaute phosphorylation cycle promotes microRNA-mediated silencing

Nature volume 542, pages 197–202 (2017)Cite this article

Subjects

Abstract

MicroRNAs (miRNAs) perform critical functions in normal physiology and disease by associating with Argonaute proteins and downregulating partially complementary messenger RNAs (mRNAs). Here we use clustered regularly interspaced short palindromic repeats (CRISPR) and CRISPR-associated protein 9 (Cas9) genome-wide loss-of-function screening coupled with a fluorescent reporter of miRNA activity in human cells to identify new regulators of the miRNA pathway. By using iterative rounds of screening, we reveal a novel mechanism whereby target engagement by Argonaute 2 (AGO2) triggers its hierarchical, multi-site phosphorylation by CSNK1A1 on a set of highly conserved residues (S824–S834), followed by rapid dephosphorylation by the ANKRD52–PPP6C phosphatase complex. Although genetic and biochemical studies demonstrate that AGO2 phosphorylation on these residues inhibits target mRNA binding, inactivation of this phosphorylation cycle globally impairs miRNA-mediated silencing. Analysis of the transcriptome-wide binding profile of non-phosphorylatable AGO2 reveals a pronounced expansion of the target repertoire bound at steady-state, effectively reducing the active pool of AGO2 on a per-target basis. These findings support a model in which an AGO2 phosphorylation cycle stimulated by target engagement regulates miRNA:target interactions to maintain the global efficiency of miRNA-mediated silencing.

This is a preview of subscription content, access via your institution

Access options

Buy this article

  • Purchase on Springer Link
  • Instant access to full article PDF
Buy now

Prices may be subject to local taxes which are calculated during checkout

Figure 1: A genome-wide CRISPR–Cas9 screen reveals known and novel regulators of the miRNA pathway.
Figure 2: Loss of ANKRD52–PPP6C activity globally impairs miRNA-mediated silencing and results in AGO2 hyperphosphorylation.
Figure 3: AGO2 phosphorylation impairs mRNA target association.
Figure 4: A CRISPR–Cas9 suppressor screen reveals CSNK1A1 as the inhibitory AGO2 kinase.
Figure 5: Argonaute S824–S834 phosphorylation is required for fully efficient miRNA-mediated silencing and is triggered by target binding.
Figure 6: Expansion of the target repertoire bound by AGO25XA.

Similar content being viewed by others

References

  1. Mendell, J. T. & Olson, E. N. MicroRNAs in stress signaling and human disease. Cell 148, 1172–1187 (2012)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  2. Vidigal, J. A. & Ventura, A. The biological functions of miRNAs: lessons from in vivo studies. Trends Cell Biol . 25, 137–147 (2015)

    Article  CAS  PubMed  Google Scholar 

  3. Bartel, D. P. MicroRNAs: target recognition and regulatory functions. Cell 136, 215–233 (2009)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  4. Jonas, S. & Izaurralde, E. Towards a molecular understanding of microRNA-mediated gene silencing. Nature Rev. Genet . 16, 421–433 (2015)

    Article  CAS  PubMed  Google Scholar 

  5. Grimson, A. et al. MicroRNA targeting specificity in mammals: determinants beyond seed pairing. Mol. Cell 27, 91–105 (2007)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  6. Bosson, A. D., Zamudio, J. R. & Sharp, P. A. Endogenous miRNA and target concentrations determine susceptibility to potential ceRNA competition. Mol. Cell 56, 347–359 (2014)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  7. Denzler, R., Agarwal, V., Stefano, J., Bartel, D. P. & Stoffel, M. Assessing the ceRNA hypothesis with quantitative measurements of miRNA and target abundance. Mol. Cell 54, 766–776 (2014)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. Jo, M. H. et al. Human Argonaute 2 has diverse reaction pathways on target RNAs. Mol. Cell 59, 117–124 (2015)

    Article  CAS  PubMed  Google Scholar 

  9. Salomon, W. E., Jolly, S. M., Moore, M. J., Zamore, P. D. & Serebrov, V. Single-molecule imaging reveals that Argonaute reshapes the binding properties of its nucleic acid guides. Cell 162, 84–95 (2015)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. Parry, D. H., Xu, J. & Ruvkun, G. A whole-genome RNAi screen for C. elegans miRNA pathway genes. Curr. Biol . 17, 2013–2022 (2007)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. Zhou, R. et al. Comparative analysis of argonaute-dependent small RNA pathways in Drosophila. Mol. Cell 32, 592–599 (2008)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Shalem, O. et al. Genome-scale CRISPR-Cas9 knockout screening in human cells. Science 343, 84–87 (2014)

    Article  CAS  PubMed  ADS  Google Scholar 

  13. Wang, T., Wei, J. J., Sabatini, D. M. & Lander, E. S. Genetic screens in human cells using the CRISPR-Cas9 system. Science 343, 80–84 (2014)

    Article  CAS  PubMed  ADS  Google Scholar 

  14. Jallepalli, P. V. et al. Securin is required for chromosomal stability in human cells. Cell 105, 445–457 (2001)

    Article  CAS  PubMed  Google Scholar 

  15. Sanjana, N. E., Shalem, O. & Zhang, F. Improved vectors and genome-wide libraries for CRISPR screening. Nature Methods 11, 783–784 (2014)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Luo, B. et al. Highly parallel identification of essential genes in cancer cells. Proc. Natl Acad. Sci. USA 105, 20380–20385 (2008)

    Article  CAS  PubMed  PubMed Central  ADS  Google Scholar 

  17. Stefansson, B., Ohama, T., Daugherty, A. E. & Brautigan, D. L. Protein phosphatase 6 regulatory subunits composed of ankyrin repeat domains. Biochemistry 47, 1442–1451 (2008)

    Article  CAS  PubMed  Google Scholar 

  18. He, T. C. et al. Identification of c-MYC as a target of the APC pathway. Science 281, 1509–1512 (1998)

    Article  CAS  PubMed  ADS  Google Scholar 

  19. Zuber, J. et al. RNAi screen identifies Brd4 as a therapeutic target in acute myeloid leukaemia. Nature 478, 524–528 (2011)

    Article  CAS  PubMed  PubMed Central  ADS  Google Scholar 

  20. O’Donnell, K. A., Wentzel, E. A., Zeller, K. I., Dang, C. V. & Mendell, J. T. c-Myc-regulated microRNAs modulate E2F1 expression. Nature 435, 839–843 (2005)

    Article  PubMed  ADS  CAS  Google Scholar 

  21. Ji, M. et al. The miR-17-92 microRNA cluster is regulated by multiple mechanisms in B-cell malignancies. Am. J. Pathol . 179, 1645–1656 (2011)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  22. Lee, Y. S. & Dutta, A. The tumor suppressor microRNA let-7 represses the HMGA2 oncogene. Genes Dev . 21, 1025–1030 (2007)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  23. Mayr, C., Hemann, M. T. & Bartel, D. P. Disrupting the pairing between let-7 and Hmga2 enhances oncogenic transformation. Science 315, 1576–1579 (2007)

    Article  CAS  PubMed  PubMed Central  ADS  Google Scholar 

  24. Tokumaru, S., Suzuki, M., Yamada, H., Nagino, M. & Takahashi, T. let-7 regulates Dicer expression and constitutes a negative feedback loop. Carcinogenesis 29, 2073–2077 (2008)

    Article  CAS  PubMed  Google Scholar 

  25. Kinoshita, E., Kinoshita-Kikuta, E., Takiyama, K. & Koike, T. Phosphate-binding tag, a new tool to visualize phosphorylated proteins. Mol. Cell. Proteomics 5, 749–757 (2006)

    Article  CAS  PubMed  Google Scholar 

  26. Zeng, Y., Sankala, H., Zhang, X. & Graves, P. R. Phosphorylation of Argonaute 2 at serine-387 facilitates its localization to processing bodies. Biochem. J . 413, 429–436 (2008)

    Article  CAS  PubMed  Google Scholar 

  27. Schirle, N. T. & MacRae, I. J. The crystal structure of human Argonaute2. Science 336, 1037–1040 (2012)

    Article  CAS  PubMed  PubMed Central  ADS  Google Scholar 

  28. Elkayam, E. et al. The structure of human argonaute-2 in complex with miR-20a. Cell 150, 100–110 (2012)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  29. Liu, Q. et al. miR-16 family induces cell cycle arrest by regulating multiple cell cycle genes. Nucleic Acids Res . 36, 5391–5404 (2008)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  30. Flores-Jasso, C. F., Salomon, W. E. & Zamore, P. D. Rapid and specific purification of Argonaute-small RNA complexes from crude cell lysates. RNA 19, 271–279 (2013)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. Cummins, J. M. et al. The colorectal microRNAome. Proc. Natl Acad. Sci. USA 103, 3687–3692 (2006)

    Article  CAS  PubMed  PubMed Central  ADS  Google Scholar 

  32. Pillai, R. S., Artus, C. G. & Filipowicz, W. Tethering of human Ago proteins to mRNA mimics the miRNA-mediated repression of protein synthesis. RNA 10, 1518–1525 (2004)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  33. Knippschild, U. et al. The casein kinase 1 family: participation in multiple cellular processes in eukaryotes. Cell. Signal . 17, 675–689 (2005)

    Article  CAS  PubMed  Google Scholar 

  34. Wang, C. C., Tao, M., Wei, T. & Low, P. S. Identification of the major casein kinase I phosphorylation sites on erythrocyte band 3. Blood 89, 3019–3024 (1997)

    Article  CAS  PubMed  Google Scholar 

  35. Schirle, N. T., Sheu-Gruttadauria, J. & MacRae, I. J. Structural basis for microRNA targeting. Science 346, 608–613 (2014)

    Article  CAS  PubMed  PubMed Central  ADS  Google Scholar 

  36. Hansen, T. B. et al. Natural RNA circles function as efficient microRNA sponges. Nature 495, 384–388 (2013)

    Article  CAS  PubMed  ADS  Google Scholar 

  37. Van Nostrand, E. L. et al. Robust transcriptome-wide discovery of RNA-binding protein binding sites with enhanced CLIP (eCLIP). Nature Methods 13, 508–514 (2016)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  38. Tani, H. et al. Genome-wide determination of RNA stability reveals hundreds of short-lived noncoding transcripts in mammals. Genome Res . 22, 947–956 (2012)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  39. Kluiver, J. et al. Rapid generation of microRNA sponges for microRNA inhibition. PLoS ONE 7, e29275 (2012)

    Article  CAS  PubMed  PubMed Central  ADS  Google Scholar 

  40. Largaespada, D. A. & Collier, L. S. Transposon-mediated mutagenesis in somatic cells: identification of transposon-genomic DNA junctions. Methods Mol. Biol . 435, 95–108 (2008)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  41. Wessel, D. & Flügge, U. I. A method for the quantitative recovery of protein in dilute solution in the presence of detergents and lipids. Anal. Biochem . 138, 141–143 (1984)

    Article  CAS  PubMed  Google Scholar 

  42. Rüdel, S., Flatley, A., Weinmann, L., Kremmer, E. & Meister, G. A multifunctional human Argonaute2-specific monoclonal antibody. RNA 14, 1244–1253 (2008)

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  43. Patel, R. K. & Jain, M. NGS QC Toolkit: a toolkit for quality control of next generation sequencing data. PLoS ONE 7, e30619 (2012)

    Article  CAS  PubMed  PubMed Central  ADS  Google Scholar 

  44. Kim, D. et al. TopHat2: accurate alignment of transcriptomes in the presence of insertions, deletions and gene fusions. Genome Biol . 14, R36 (2013)

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  45. Liao, Y., Smyth, G. K. & Shi, W. featureCounts: an efficient general purpose program for assigning sequence reads to genomic features. Bioinformatics 30, 923–930 (2014)

    Article  CAS  PubMed  Google Scholar 

  46. Robinson, M. D., McCarthy, D. J. & Smyth, G. K. edgeR: a Bioconductor package for differential expression analysis of digital gene expression data. Bioinformatics 26, 139–140 (2010)

    Article  CAS  PubMed  Google Scholar 

  47. Marcel, M. Cutadapt removes adapter sequences from high-throughput sequencing reads. EMBnet.journal 17, 10–12 (2011)

    Google Scholar 

  48. Quinlan, A. R. & Hall, I. M. BEDTools: a flexible suite of utilities for comparing genomic features. Bioinformatics 26, 841–842 (2010)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  49. Kim, Y. K., Kim, B. & Kim, V. N. Re-evaluation of the roles of DROSHA, Export in 5, and DICER in microRNA biogenesis. Proc. Natl Acad. Sci. USA 113, E1881–E1889 (2016)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  50. Jiang, H. & Wong, W. H. SeqMap: mapping massive amount of oligonucleotides to the genome. Bioinformatics 24, 2395–2396 (2008)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

We thank D. Bartel, C. Cepko, D. Sabatini, P. Sharp, D. Trono, T. Tuschl, and F. Zhang for plasmids; A. Guzman and R. Bruce in the McDermott Center Next Generation Sequencing Core; A. Mobley and the University of Texas Southwestern Flow Cytometry Core; H. Ball and the University of Texas Southwestern Protein Chemistry Technology Core; S. Johnson for assistance with software implementation; J. Cabrera for assistance with figure preparation; and K. O’Donnell for advice on the manuscript. This work was supported by grants from the Cancer Prevention and Research Institute of Texas (CPRIT) (R1008 and RP160249 to J.T.M., RP101251 to Y.X., RP120718 to Z.J.C., and RR150033 to V.S.T.) and the National Institutes of Health (R01CA120185 and R35CA197311 to J.T.M., R01CA152301 to Y.X., and R00DK099254 to V.S.T.). T.L. is supported by a fellowship from Cancer Research Institute. F.K. is supported by the Leopoldina Fellowship Program (LPDS 2014-12) from the German National Academy of Sciences Leopoldina. J.T.M. and V.S.T. are CPRIT Scholars in Cancer Research. J.T.M. and Z.J.C. are Investigators of the Howard Hughes Medical Institute.

Author information

Authors and Affiliations

  1. Department of Molecular Biology, University of Texas Southwestern Medical Center, Dallas, 75390, Texas, USA

    Ryan J. Golden, Tuo Li, Juliane Braun, Hema Manjunath, Xiang Chen, Tsung-Cheng Chang, Florian Kopp, Andres Ramirez-Martinez, Vincent S. Tagliabracci, Zhijian J. Chen & Joshua T. Mendell

  2. Medical Scientist Training Program, University of Texas Southwestern Medical Center, Dallas, 75390, Texas, USA

    Ryan J. Golden

  3. Quantitative Biomedical Research Center, University of Texas Southwestern Medical Center, Dallas, 75390, Texas, USA

    Beibei Chen & Yang Xie

  4. Department of Clinical Sciences, University of Texas Southwestern Medical Center, Dallas, 75390, Texas, USA

    Beibei Chen & Yang Xie

  5. Department of Microbiology and Immunology, University of California San Francisco, San Francisco, 94143, California, USA

    Jiaxi Wu

  6. Eugene McDermott Center for Human Growth & Development, University of Texas Southwestern Medical Center, Dallas, 75390, Texas, USA

    Vanessa Schmid

  7. Howard Hughes Medical Institute, University of Texas Southwestern Medical Center, Dallas, 75390, Texas, USA

    Zhijian J. Chen & Joshua T. Mendell

  8. Harold C. Simmons Comprehensive Cancer Center, University of Texas Southwestern Medical Center, Dallas, 75390, Texas, USA

    Yang Xie & Joshua T. Mendell

  9. Hamon Center for Regenerative Science and Medicine, University of Texas Southwestern Medical Center, Dallas, 75390, Texas, USA

    Joshua T. Mendell

Authors
  1. Ryan J. Golden
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Beibei Chen
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Tuo Li
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Juliane Braun
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Hema Manjunath
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Xiang Chen
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Jiaxi Wu
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Vanessa Schmid
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Tsung-Cheng Chang
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. Florian Kopp
    View author publications

    You can also search for this author in PubMed Google Scholar

  11. Andres Ramirez-Martinez
    View author publications

    You can also search for this author in PubMed Google Scholar

  12. Vincent S. Tagliabracci
    View author publications

    You can also search for this author in PubMed Google Scholar

  13. Zhijian J. Chen
    View author publications

    You can also search for this author in PubMed Google Scholar

  14. Yang Xie
    View author publications

    You can also search for this author in PubMed Google Scholar

  15. Joshua T. Mendell
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

R.J.G. performed most experiments and B.C. performed most bioinformatics analyses. T.L., X.C., J.W., and R.J.G. performed mass spectrometry analyses. J.B. and H.M. generated plasmid constructs, cell lines, and performed CLIP validation experiments. V.S. provided technical assistance for sequencing sgRNA libraries. T.-C.C. performed qPCR analyses. F.K. assisted with CLIP experiments. A.R.-M. generated plasmid constructs. B.C., Y.X., and J.T.M. performed bioinformatics analyses. V.S.T. provided guidance for the in vitro kinase assays. R.J.G., J.T.M., B.C., Y.X., Z.J.C., and T.L. designed most experiments. R.J.G and J.T.M. wrote the manuscript.

Corresponding author

Correspondence to Joshua T. Mendell.

Ethics declarations

Competing interests

The authors declare no competing financial interests.

Additional information

Reviewer Information Nature thanks S. Tavazoie, W. Wei and the other anonymous reviewer(s) for their contribution to the peer review of this work.

Extended data figures and tables

Extended Data Figure 1 Knockout of candidate miRNA regulators in HCT116EGFP cells.

Flow cytometry analysis of EGFP in HCT116EGFP cells after transduction with lentiCRISPR vectors targeting the indicated genes.

Extended Data Figure 2 BRD4, CTNNB1, and POU2F1 positively regulate miR-19 expression.

a, Model depicting how each gene may promote expression of the miR-17-92 cluster. b–d, Western blot analysis confirming loss of expression of the indicated gene in HCT116 knockout clones. Asterisk indicates non-specific band. For each protein, all lanes came from the same blot but irrelevant lanes were removed. e–g, qRT–PCR assays demonstrating reduced expression of MYC (e), pri-miR-17-92 (f), or mature miR-19a/b (g) in BRD4−/−, CTNNB1−/−, or POU2F1−/− cells. For gel source data, see Supplementary Fig. 1.

Extended Data Figure 3 Western blot analysis confirms loss of protein expression in AGO2 and ANKRD52 HCT116 clonal knockout lines.

For both AGO2 (a) and ANKRD52 (b) western blots, all lanes came from the same blot but irrelevant lanes were removed. For gel source data, see Supplementary Fig. 1.

Extended Data Figure 4 General impairment of miRNA-mediated silencing in ANKRD52–/– cells.

a, b, Flow cytometry analysis of EGFP expression in HCT116 cells stably expressing reporters for miR-16 (a) or miR-200 (b) after transduction with lentiCRISPR vectors targeting ANKRD52 or expressing a non-targeting sgRNA. c, qRT–PCR showing de-repression of established let-7 targets (DICER1 or HMGA2) in AGO2–/– or ANKRD52–/– cells. *P < 0.05, **P < 0.01, two-tailed Student’s t-test comparing AGO2–/– or ANKRD52–/– to parental. (n = 3 biological replicates, each assayed in triplicate.) d, qRT–PCR analysis of DICER1 and HMGA2 in non-transfected (NT) HCT116EGFP-miR-19 cells or after transfection with miR-19 antisense oligonucleotides (Anti-miR-19) confirms that these transcripts are not regulated by miR-19. Upregulation of the EGFP miR-19 reporter transcript served as a positive control in this experiment. (n = 3 biological replicates, each assayed in triplicate.) e, qRT–PCR was performed for the indicated miRNAs and expression levels were normalized to U6 snRNA (n = 2 biological replicates, each assayed in triplicate).

Extended Data Figure 5 The ANKRD52–PPP6C complex interacts with and dephosphorylates AGO proteins.

a, Co-immunoprecipitation of Flag–HA-AGO2 (FH-AGO2) with V5-ANKRD52 or V5-PPP6C with or without RNase A treatment. b, Phos-tag electrophoresis demonstrating AGO2 hyperphosphorylation in multiple ANKRD52/PPP6C-deficient cell lines. c, Phos-tag western blot analysis of Flag–HA-AGO1 (FH-AGO1) stably expressed in ANKRD52+/+ and ANKRD52−/− HCT116 cells. For gel source data, see Supplementary Fig. 1.

Extended Data Figure 6 Identification of multiple definitively phosphorylated residues in the S824–S834 region of AGO2 by mass spectrometry.

a, Full-scan mass spectra zoomed to the region for the AGO2 815–837 peptide. The unphosphorylated and multiply phosphosphorylated precursor ions are shown in red. Peak labels indicate the mass-to-charge ratios and the charge state. The singly charged ion with grey label (top panel) does not correspond to peptides 815–837. Data at two close elution time points are shown for ANKRD52−/− to illustrate the unphosphorylated (0P), singly (1P), doubly (2P), and triply (3P) phosphorylated peptides. b, Quantification of the indicated endogenous AGO2 phosphopeptides relative to unphosphorylated peptide as determined by mass spectrometry. Labels 1P, 2P, or 3P respectively denote singly, doubly, or triply phosphorylated peptides spanning residues 815–837 of AGO2. Superscript indicates peptide charge state. ND, not detected. c, MS/MS spectra demonstrating phosphorylation of endogenous AGO2 at S824 in ANKRD52−/− cells. Red bars denote site-determining ions. d, e, MS/MS spectra demonstrating phosphorylation of FH-AGO2 (T830A) at S824 and S828 (d) or phosphorylation of FH-AGO2 (S824A/T830A) at S828 and S831(e) in ANKRD52−/− cells.

Extended Data Figure 7 Phosphomimetic mutants of FH-AGO2 do not exhibit reduced miRNA association.

a, Western blots showing expression of the indicated FH-AGO2 mutants. Within each panel (top, middle, bottom), all lanes came from the same blot but irrelevant lanes were removed. b, miRNA association of wild-type or mutant FH-AGO2 assessed as described in Fig. 3a (n = 4 biological replicates, each assayed in triplicate). For gel source data, see Supplementary Fig. 1.

Extended Data Figure 8 Analysis of serine/threonine kinases identified in the CRISPR–Cas9 suppressor screen.

a, b, Flow cytometry demonstrating EGFP expression in HCT116EGFP-miR19 (a) or HCT116EGFP cells (b) after transduction with lentiCRISPR vectors targeting the indicated genes. c, Flow cytometry demonstrating EGFP expression in HCT116EGFP-miR19 cells treated with the indicated dose of rapamycin. NT, not treated. d, Phos-tag western blot analysis of AGO2 in ANKRD52−/− cells after treatment with rapamycin. For gel source data, see Supplementary Fig. 1.

Extended Data Figure 9 Functional characterization of CSNK1A1 and AGO2 target binding mutants.

a, Western blot analysis confirms loss of CSNK1A1 expression in HCT116 ANKRD52−/−;CSNK1A1−/− clonal knockout cells. All lanes came from the same blot but irrelevant lanes were removed. b, miR-19 expression normalized to U6 expression, assessed by qRT–PCR, in cells of the indicated genotypes (n = 4 biological replicates, each assayed in triplicate). c, Co-immunoprecipitation of V5-CSNK1A1 with FH-AGO2, with or without RNase A treatment. d, miRNA association of FH-AGO2 assessed as in Fig. 3e (n = 4 biological replicates, each assayed in triplicate). *P < 0.05 comparing mutant to wild-type AGO2, two-tailed Student’s t-test. For gel source data, see Supplementary Fig. 1.

Extended Data Figure 10 Generation and eCLIP analysis of AGO2–/– cells reconstituted with AGO2WT or AGO25XA.

a, Western blot showing equivalent expression of FH-AGO2WT and FH-AGO25XA at physiological levels. For gel source data, see Supplementary Fig. 1. b, Distribution of AGO2 binding sites determined by eCLIP. c, Validation of targets identified by eCLIP using FH-AGO2 pull-down assays performed in reconstituted AGO2−/− cells. Experiment was performed as in Fig. 3a except anti-Flag antibody was used for immunoprecipitation (n = 3 biological replicates, each assayed in triplicate). *P < 0.05, **P < 0.01, one-tailed Student’s t-test comparing FH-AGO25XA with FH-AGO2WT. NS, not significant. d, FH-AGO2WT CLIP coverage (normalized total number of reads in clusters in a given 3′ UTR divided by the FPKM) of genes whose AGO2-mediated repression is or is not rescued by FH-AGO25XA. e, The 8-, 7-, or 6-nucleotide binding sites for active miRNAs in HCT116 were identified within FH-AGO2WT/FH-AGO25XA-common CLIP clusters or FH-AGO25XA-unique CLIP clusters in 3′ UTRs. CDF plots show CLIP coverage for each class of site (normalized number of crosslinking events within ten nucleotides of each site). NS, not significant, assessed by Kolmogorov–Smirnov test. f, CDF plot showing the fold change in CLIP coverage comparing FH-AGO25XA to FH-AGO2WT for transcripts with long half-lives (top quartile) versus those with short half-lives (bottom quartile). g, Summary of the newly defined AGO2 phosphorylation cycle. Target engagement triggers the hierarchical, multi-site phosphorylation of AGO2 by CSNK1A1, which inhibits target binding. The ANKRD52–PPP6C phosphatase complex dephosphorylates these residues, allowing AGO2 to engage new targets. Continual phosphorylation/de-phosphorylation of AGO2 through this cycle is necessary to maintain the global efficiency of miRNA-mediated silencing.

Supplementary information

Supplementary Figure 1

This file contains the gel source data. (PDF 1155 kb)

Supplementary Table 1.

This file contains the simulated sgRNA enrichment in top 0.5% brightest cells. (XLSX 9 kb)

Supplementary Table 2.

This file contains the RIGER analysis of CRISPR-Cas9 screen in HCT116EGFP-miR19 cells. (XLSX 2290 kb)

Supplementary Table 3.

This file contains the RIGER analysis of CRISPR-Cas9 screen in HCT116EGFP cells. (XLSX 2291 kb)

Supplementary Table 4.

This file contains the RNA-seq results showing genes with altered expression in AGO2−/−, ANKRD52−/−, and CSNK1A1−/−; ANKRD52−/− HCT116 cells compared to wild-type HCT116 cells. (XLSX 160 kb)

Supplementary Table 5.

This file contains the RIGER analysis of CRISPR-Cas9 suppressor screen in ANKRD52−/− HCT116EGFP-miR19 cells. (XLSX 2096 kb)

Supplementary Table 6.

This file contains the RNA-seq results showing genes with altered expression in AGO2−/− cells and AGO2−/− cells reconstituted with FH-AGO2WT or FH-AGO25XA compared to wild-type HCT116 cells. (XLSX 886 kb)

Supplementary Table 7.

This file contains the eCLIP results. (XLSX 271 kb)

Supplementary Table 8.

This file contains the oligonucleotides and peptides used in this study. (XLSX 18 kb)

PowerPoint slides

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Golden, R., Chen, B., Li, T. et al. An Argonaute phosphorylation cycle promotes microRNA-mediated silencing. Nature 542, 197–202 (2017). https://doi.org/10.1038/nature21025

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/nature21025

This article is cited by

Comments

By submitting a comment you agree to abide by our Terms and Community Guidelines. If you find something abusive or that does not comply with our terms or guidelines please flag it as inappropriate.

Search

Advanced search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing