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.

Affinity-based profiling of endogenous phosphoprotein phosphatases by mass spectrometry

Abstract

Phosphoprotein phosphatases (PPPs) execute >90% of serine/threonine dephosphorylation in cells and tissues. While the role of PPPs in cell biology and diseases such as cancer, cardiac hypertrophy and Alzheimer’s disease is well established, the molecular mechanisms governing and governed by PPPs still await discovery. Here we describe a chemical proteomic strategy, phosphatase inhibitor beads and mass spectrometry (PIB-MS), that enables the identification and quantification of PPPs and their posttranslational modifications in as little as 12 h. Using a specific but nonselective PPP inhibitor immobilized on beads, PIB-MS enables the efficient affinity-capture, identification and quantification of endogenous PPPs and associated proteins (‘PPPome’) from cells and tissues. PIB-MS captures functional, endogenous PPP subunit interactions and enables discovery of new binding partners. It performs PPP enrichment without exogenous expression of tagged proteins or specific antibodies. Because PPPs are among the most conserved proteins across evolution, PIB-MS can be employed in any cell line, tissue or organism.

Access options

Rent or Buy article

Get time limited or full article access on ReadCube.

from$8.99

All prices are NET prices.

Fig. 1: PIB-MS flowthrough.
Fig. 2: PPPome discovery experiment.
Fig. 3: Comparison of mitotic and asynchronous PPPome and phospho-PPPome by TMT.

Data availability

The data presented here have been previously published, and the associated raw data are available through the original publications10,11.

References

  1. 1.

    Brautigan, D. L. & Shenolikar, S. Protein serine/threonine phosphatases: keys to unlocking regulators and substrates. Annu. Rev. Biochem. 87, 921–964 (2018).

    CAS  PubMed  Article  Google Scholar 

  2. 2.

    Virshup, D. M. & Shenolikar, S. From promiscuity to precision: protein phosphatases get a makeover. Mol. Cell 33, 537–545 (2009).

    CAS  PubMed  Article  Google Scholar 

  3. 3.

    Brautigan, D. L. Protein Ser/Thr phosphatases—the ugly ducklings of cell signalling. FEBS J. 280, 324–345 (2013).

    CAS  PubMed  Article  Google Scholar 

  4. 4.

    Sun, L. et al. Inhibition of protein phosphatase 2A- and protein phosphatase 1-induced tau hyperphosphorylation and impairment of spatial memory retention in rats. Neuroscience 118, 1175–1182 (2003).

    CAS  PubMed  Article  Google Scholar 

  5. 5.

    Kamat, P. K., Rai, S. & Nath, C. Okadaic acid induced neurotoxicity: an emerging tool to study Alzheimer’s disease pathology. Neurotoxicology 37, 163–172 (2013).

    CAS  PubMed  Article  Google Scholar 

  6. 6.

    Sontag, J. M., Nunbhakdi-Craig, V., White, C. L., Halpain, S. & Sontag, E. The protein phosphatase PP2A/Bα binds to the microtubule-associated proteins Tau and MAP2 at a motif also recognized by the kinase Fyn: Implications for tauopathies. J. Biol. Chem. 287, 14984–14993 (2012).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  7. 7.

    Chen, W. et al. Identification of specific PP2A complexes involved in human cell transformation. Cancer Cell 5, 127–136 (2004).

    CAS  PubMed  Article  Google Scholar 

  8. 8.

    Arroyo, J. D. & Hahn, W. C. Involvement of PP2A in viral and cellular transformation. Oncogene 24, 7746–7755 (2005).

    CAS  PubMed  Article  Google Scholar 

  9. 9.

    Molkentin, J. D. et al. A calcineurin-dependent transcriptional pathway for cardiac hypertrophy. Cell 93, 215–228 (1998).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  10. 10.

    Lyons, S. P. et al. A quantitative chemical proteomic strategy for profiling phosphoprotein phosphatases from yeast to humans. Mol. Cell Proteomics 17, 2448–2461 (2018).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  11. 11.

    Nasa, I. et al. Quantitative kinase and phosphatase profiling reveal that CDK1 phosphorylates PP2Ac to promote mitotic entry. Sci. Signal. 13, eaba7823 (2020).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  12. 12.

    Frohner, I. E., Mudrak, I., Kronlachner, S., Schüchner, S. & Ogris, E. Antibodies recognizing the C terminus of PP2A catalytic subunit are unsuitable for evaluating PP2A activity and holoenzyme composition. Sci. Signal. 13, eaax6490 (2020).

    CAS  PubMed  Article  Google Scholar 

  13. 13.

    Couzens, A. L. et al. Protein interaction network of the mammalian Hippo pathway reveals mechanisms of kinase-phosphatase interactions.Sci. Signal. 6, rs15 (2013).

    PubMed  Article  CAS  Google Scholar 

  14. 14.

    St-Denis, N. et al. Phenotypic and interaction profiling of the human phosphatases identifies diverse mitotic regulators. Cell Rep. 17, 2488–2501 (2016).

    CAS  PubMed  Article  Google Scholar 

  15. 15.

    Yadav, L. et al. Systematic analysis of human protein phosphatase interactions and dynamics. Cell Syst. 4, 430–444 e5 (2017).

    CAS  PubMed  Article  Google Scholar 

  16. 16.

    Heroes, E. et al. The PP1 binding code: a molecular-lego strategy that governs specificity. FEBS J. 280, 584–595 (2013).

    CAS  PubMed  Article  Google Scholar 

  17. 17.

    Swingle, M., Ni, L. & Honkanen, R. E. Small-molecule inhibitors of ser/thr protein phosphatases: Specificity, use and common forms of abuse. Methods Mol. Biol. 365, 23–38 (2007).

    PubMed  PubMed Central  Google Scholar 

  18. 18.

    Moorhead, G. B. G., Haystead, T. A. J. & MacKintosh, C. Synthesis and use of the protein phosphatase affinity matrices microcystin-sepharose and microcystin-biotin-sepharose. Methods Mol. Biol. 365, 39–45 (2007).

    PubMed  Google Scholar 

  19. 19.

    Duncan, J. S. et al. Dynamic reprogramming of the kinome in response to targeted MEK inhibition in triple-negative breast cancer. Cell 149, 307–321 (2012).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  20. 20.

    Godl, K. et al. An efficient proteomics method to identify the cellular targets of protein kinase inhibitors. Proc. Natl Acad. Sci. USA 100, 15434–15444 (2003).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  21. 21.

    Bantscheff, M. et al. Quantitative chemical proteomics reveals mechanisms of action of clinical ABL kinase inhibitors. Nat. Biotechnol. 25, 1035–1044 (2007).

    CAS  PubMed  Article  Google Scholar 

  22. 22.

    Kruse, U. et al. Chemoproteomics-based kinome profiling and target deconvolution of clinical multi-kinase inhibitors in primary chronic lymphocytic leukemia cells. Leukemia 25, 89–100 (2011).

    CAS  PubMed  Article  Google Scholar 

  23. 23.

    Midland, A. A. et al. Defining the expressed breast cancer kinome. Cell Res. 22, 620–623 (2012).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  24. 24.

    Stuhlmiller, T. J. et al. Inhibition of lapatinib-induced kinome reprogramming in ERBB2-positive breast cancer by targeting BET family bromodomains. Cell Rep. 11, 390–404 (2015).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  25. 25.

    Cooper, M. J. et al. Application of multiplexed kinase inhibitor beads to study kinome adaptations in drug-resistant leukemia. PLoS One 8, e66755 (2013).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  26. 26.

    Johnson, G. L., Stuhlmiller, T. J., Angus, S. P., Zawistowski, J. S. & Graves, L. M. Molecular pathways: adaptive kinome reprogramming in response to targeted inhibition of the BRAF-MEK-ERK pathway in cancer. Clin. Cancer Res. 20, 2516–2522 (2014).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  27. 27.

    Klaeger, S. et al. The target landscape of clinical kinase drugs. Science 358, eaan4368 (2017).

    PubMed  PubMed Central  Article  CAS  Google Scholar 

  28. 28.

    Hughes, P. F. et al. A highly selective Hsp90 affinity chromatography resin with a cleavable linker. Bioorganic Med. Chem. 20, 3298–3305 (2012).

    CAS  Article  Google Scholar 

  29. 29.

    Ranjitkar, P., Brock, A. M. & Maly, D. J. Affinity reagents that target a specific inactive form of protein kinases. Chem. Biol. 17, 195–206 (2010).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  30. 30.

    Moorhead, G., MacKintosh, R. W., Morrice, N., Gallagher, T. & MacKintosh, C. Purification of type 1 protein (serine/threonine) phosphatases by microcystin-Sepharose affinity chromatography. FEBS Lett 356, 46–50 (1994).

    CAS  PubMed  Article  Google Scholar 

  31. 31.

    Hughes, C. S. et al. Single-pot, solid-phase-enhanced sample preparation for proteomics experiments. Nat. Protoc. 14, 68–85 (2019).

    CAS  PubMed  Article  Google Scholar 

  32. 32.

    Ting, L., Rad, R., Gygi, S. P. & Haas, W. MS3 eliminates ratio distortion in isobaric multiplexed quantitative proteomics. Nat. Methods 8, 937–940 (2011).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  33. 33.

    Eng, J. K., Jahan, T. A. & Hoopmann, M. R. Comet: an open-source MS/MS sequence database search tool. Proteomics 13, 22–24 (2013).

    CAS  PubMed  Article  Google Scholar 

  34. 34.

    Valot, B., Langella, O., Nano, E. & Zivy, M. MassChroQ: a versatile tool for mass spectrometry quantification. Proteomics 11, 3572–3577 (2011).

    CAS  PubMed  Article  Google Scholar 

  35. 35.

    R Core Team. The R Project for Statistical Computing. https://www.R-project.org/ (2019).

  36. 36.

    Tyanova, S. et al. The Perseus computational platform for comprehensive analysis of (prote)omics data. Nat. Methods 13, 731–740 (2016).

    CAS  PubMed  Article  Google Scholar 

  37. 37.

    Yu, S. H. et al. Expanding the Perseus software for omics data analysis with custom plugins. Curr. Protoc. Bioinformatics 71, 1–29 (2020).

    Article  Google Scholar 

  38. 38.

    Johnson, W. E., Li, C. & Rabinovic, A. Adjusting batch effects in microarray expression data using empirical Bayes methods. Biostatistics 8, 118–127 (2007).

    Article  Google Scholar 

  39. 39.

    Rappsilber, J., Mann, M. & Ishihama, Y. Protocol for micro-purification, enrichment, pre-fractionation and storage of peptides for proteomics using StageTips. Nat. Protoc. 2, 1896–1906 (2007).

    CAS  PubMed  Article  Google Scholar 

  40. 40.

    Zecha, J. et al. TMT labeling for the masses: a robust and cost-efficient, in-solution labeling approach. Mol. Cell Proteomics 18, 1468–1478 (2019).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  41. 41.

    Kettenbach, A. N. & Gerber, S. A. Rapid and reproducible single-stage phosphopeptide enrichment of complex peptide mixtures: application to general and phosphotyrosine-specific phosphoproteomics experiments. Anal. Chem. 83, 7635–7644 (2011).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  42. 42.

    Bollen, M., Peti, W., Ragusa, M. J. & Beullens, M. The extended PP1 toolkit: designed to create specificity. Trends Biochem. Sci. 35, 450–458 (2010).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  43. 43.

    Nilsson, J. Protein phosphatases in the regulation of mitosis. J. Cell Biol. 218, 395–409 (2019).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  44. 44.

    Krystkowiak, I. & Davey, N. E. SLiMSearch: a framework for proteome-wide discovery and annotation of functional modules in intrinsically disordered regions. Nucleic Acids Res. 45, W464–W469 (2017).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  45. 45.

    Chen, M. J., Dixon, J. E. & Manning, G. Genomics and evolution of protein phosphatases. Sci. Signal. 10, eaag1796 (2017).

    PubMed  Article  CAS  Google Scholar 

  46. 46.

    Uhlen, M. et al. Tissue-based map of the human proteome. Science 347, 1260419–1260419 (2015).

    PubMed  Article  CAS  Google Scholar 

  47. 47.

    Nusinow, D. P. et al. Quantitative proteomics of the Cancer Cell Line Encyclopedia. Cell 180, 387–402 (2020).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  48. 48.

    Wang, D. et al. A deep proteome and transcriptome abundance atlas of 29 healthy human tissues. Mol. Syst. Biol. 15, e8503 (2019).

    PubMed  PubMed Central  Article  CAS  Google Scholar 

  49. 49.

    Xu, Y. et al. Structure of the protein phosphatase 2A holoenzyme. Cell 127, 1239–1251 (2006).

    CAS  PubMed  Article  Google Scholar 

  50. 50.

    Cho, U. S. & Xu, W. Crystal structure of a protein phosphatase 2A heterotrimeric holoenzyme. Nature 445, 53–57 (2007).

    CAS  PubMed  Article  Google Scholar 

  51. 51.

    Seshacharyulu, P., Pandey, P., Datta, K. & Batra, S. K. Phosphatase: PP2A structural importance, regulation and its aberrant expression in cancer. Cancer Lett. 335, 9–18 (2013).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  52. 52.

    da Cruz e Silva, E. F. & Cohen, P. T. Isolation of a cDNA likely to encode a novel Ca2+-dependent/calmodulin-stimulated protein phosphatase. Biochim. Biophys. Acta 1009, 293–296 (1989).

    PubMed  Article  Google Scholar 

  53. 53.

    Klee, C. B., Ren, H. & Wang, X. Regulation of the calmodulin-stimulated protein phosphatase, calcineurin. J. Biol. Chem. 273, 13367–13370 (1998).

    CAS  PubMed  Article  Google Scholar 

  54. 54.

    Rusnak, F. & Mertz, P. Calcineurin: form and function. Physiol. Rev. 80, 1483–1521 (2000).

    CAS  PubMed  Article  Google Scholar 

  55. 55.

    Li, H., Rao, A. & Hogan, P. G. Interaction of calcineurin with substrates and targeting proteins. Trends Cell Biol. 21, 91–103 (2011).

    CAS  PubMed  Article  Google Scholar 

  56. 56.

    Gingras, A. C. et al. A novel, evolutionarily conserved protein phosphatase complex involved in cisplatin sensitivity. Mol. Cell Proteomics 4, 1725–1740 (2005).

    CAS  PubMed  Article  Google Scholar 

  57. 57.

    Kloeker, S. & Wadzinski, B. E. Purification and identification of a novel subunit of protein serine/threonine phosphatase 4. J. Biol. Chem. 274, 5339–5347 (1999).

    CAS  PubMed  Article  Google Scholar 

  58. 58.

    Chen, M. X. et al. A novel human protein serine/threonine phosphatase, which possesses four tetratricopeptide repeat motifs and localizes to the nucleus. EMBO J. 13, 4278–4290 (1994).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  59. 59.

    Das, A. K., Cohen, P. W. & Barford, D. The structure of the tetratricopeptide repeats of protein phosphatase 5: implications for TPR-mediated protein-protein interactions. EMBO J. 17, 1192–1199 (1998).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  60. 60.

    Guergnon, J., Derewenda, U., Edelson, J. R. & Brautigan, D. L. Mapping of protein phosphatase-6 association with its SAPS domain regulatory subunit using a model of helical repeats. BMC Biochem. 10, 24 (2009).

    PubMed  PubMed Central  Article  CAS  Google Scholar 

  61. 61.

    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).

    CAS  PubMed  Article  Google Scholar 

  62. 62.

    Huang, X. & Honkanen, R. E. Molecular cloning, expression, and characterization of a novel human serine/threonine protein phosphatase, PP7, that is homologous to Drosophila retinal degeneration C gene product (rdgC). J. Biol. Chem. 273, 1462–1468 (1998).

    CAS  PubMed  Article  Google Scholar 

  63. 63.

    Verbinnen, I., Ferreira, M. & Bollen, M. Biogenesis and activity regulation of protein phosphatase 1. Biochem. Soc. Trans. 45, 89–99 (2017).

    CAS  PubMed  Article  Google Scholar 

  64. 64.

    Hertz, E. P. T. et al. A conserved motif provides binding specificity to the PP2A-B56 phosphatase. Mol. Cell 63, 686–695 (2016).

    CAS  PubMed  Article  Google Scholar 

  65. 65.

    Wang, X., Bajaj, R., Bollen, M., Peti, W. & Page, R. Expanding the PP2A interactome by defining a B56-specific SLiM. Structure 24, 2174–2181 (2016).

    PubMed  PubMed Central  Article  CAS  Google Scholar 

  66. 66.

    Roy, J. & Cyert, M. S. Cracking the phosphatase code: docking interactions determine substrate specificity. Sci. Signal. 2, re9 (2009).

    PubMed  Article  Google Scholar 

  67. 67.

    Roy, J., Li, H., Hogan, P. G. & Cyert, M. S. A conserved docking site modulates substrate affinity for calcineurin, signaling output, and in vivo function. Mol. Cell 25, 889–901 (2007).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  68. 68.

    Ueki, Y. et al. A consensus binding motif for the PP4 protein phosphatase. Mol. Cell 76, 953–964 (2019).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

Download references

Acknowledgements

A.N.K. and S.A.G. acknowledge support from NCI R33 CA225458. S.A.G. received support from NCI P30 CA0231008. K.W. was supported by a Burroughs-Wellcome Big Data in the Life Sciences Fellowship. We thank K. Smolen for assistance with video editing.

Author information

Affiliations

Authors

Contributions

B.L.B., S.M., G.B.M. and A.N.K. developed and wrote the protocol. B.L.B. drew the illustrations. K.W. and S.A.G. contributed to the design of the data analysis workflow. S.A.G. contributed to the editing of the manuscript.

Corresponding author

Correspondence to Arminja N. Kettenbach.

Ethics declarations

Competing interests

The authors declare no competing interests.

Additional information

Peer review information Nature Protocols thanks Albert J. R. Heck, Martin R. Larsen and the other, anonymous reviewer(s) for their contribution to the peer review of this work.

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Related links

Key references using this protocol

Lyons, S. P. et al. Mol. Cell Proteomics 17, 2448–2461 (2018): https://doi.org/10.1074/mcp.RA118.000822

Nasa, I. et al. Sci. Signal. 13, eaba7823 (2020): https://doi.org/10.1126/scisignal.aba7823

Supplementary information

Supplementary Table 1

Annotated PPP subunits and interactors. Uniprot ID and entry name are given for each protein, alongside its gene name and description. PPP subunit indicates the PPP the proteins belong to (PP1-7), whether it is a catalytic subunit (C), a regulatory subunit (R), an inhibitory protein (i), or an activating protein (a).

Supplementary Video 1

A step-by-step demonstration of making a StageTip and using it to desalt a TMT label check sample.

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Brauer, B.L., Wiredu, K., Mitchell, S. et al. Affinity-based profiling of endogenous phosphoprotein phosphatases by mass spectrometry. Nat Protoc (2021). https://doi.org/10.1038/s41596-021-00604-3

Download citation

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

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