Skip to main content
Book cover

ATM Kinase pp 229–244Cite as

Statistical Analysis of ATM-Dependent Signaling in Quantitative Mass Spectrometry Phosphoproteomics

  • Protocol
  • First Online:

Part of the book series: Methods in Molecular Biology ((MIMB,volume 1599))

Abstract

Ataxia-telangiectasia mutated (ATM) is a serine/threonine protein kinase, which when perturbed is associated with modified protein signaling that ultimately leads to a range of neurological and DNA repair defects. Recent advances in phospho-proteomics coupled with high-resolution mass-spectrometry provide new opportunities to dissect signaling pathways that ATM utilize under a number of conditions. This chapter begins by providing a brief overview of ATM function, its various regulatory roles and then leads into a workflow focused on the use of the statistical programming language R, together with code, for the identification of ATM-dependent substrates in the cytoplasm. This chapter cannot cover statistical properties in depth nor the range of possible methods in great detail, but instead aims to equip researchers with a set of tools to perform analysis between two conditions through examples with R functions.

This is a preview of subscription content, log in via an institution.

Buying options

Protocol
USD   49.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   129.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   169.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD   169.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

Springer Nature is developing a new tool to find and evaluate Protocols. Learn more

References

  1. Tranchant C, Anheim M (2009) Autosomal recessive cerebellar ataxias. Presse Med 38(12):1852–1859. doi:10.1016/j.lpm.2009.01.025

    Article  PubMed  Google Scholar 

  2. Lavin MF (2008) Ataxia-telangiectasia: from a rare disorder to a paradigm for cell signalling and cancer. Nat Rev Mol Cell Biol 9(10):759–769. doi:10.1038/nrm2514

    Article  CAS  PubMed  Google Scholar 

  3. Paull TT (2015) Mechanisms of ATM activation. Annu Rev Biochem 84:711–738. doi:10.1146/annurev-biochem-060614-034335

    Article  CAS  PubMed  Google Scholar 

  4. Gross S, Rahal R, Stransky N, Lengauer C, Hoeflich KP (2015) Targeting cancer with kinase inhibitors. J Clin Invest 125(5):1780–1789. doi:10.1172/JCI76094

    Article  PubMed  PubMed Central  Google Scholar 

  5. Manning G, Whyte DB, Martinez R, Hunter T, Sudarsanam S (2002) The protein kinase complement of the human genome. Science 298(5600):1912–1934. doi:10.1126/science.1075762

    Article  CAS  PubMed  Google Scholar 

  6. Kim ST, Lim DS, Canman CE, Kastan MB (1999) Substrate specificities and identification of putative substrates of ATM kinase family members. J Biol Chem 274(53):37538–37543

    Article  CAS  PubMed  Google Scholar 

  7. Choudhary C, Mann M (2010) Decoding signalling networks by mass spectrometry-based proteomics. Nat Rev Mol Cell Biol 11(6):427–439. doi:10.1038/nrm2900

    Article  CAS  PubMed  Google Scholar 

  8. Bensimon A, Schmidt A, Ziv Y, Elkon R, Wang SY, Chen DJ, Aebersold R, Shiloh Y (2010) ATM-dependent and -independent dynamics of the nuclear phosphoproteome after DNA damage. Sci Signal 3(151):rs3. doi:10.1126/scisignal.2001034

    Article  CAS  PubMed  Google Scholar 

  9. Beli P, Lukashchuk N, Wagner SA, Weinert BT, Olsen JV, Baskcomb L, Mann M, Jackson SP, Choudhary C (2012) Proteomic investigations reveal a role for RNA processing factor THRAP3 in the DNA damage response. Mol Cell 46(2):212–225. doi:10.1016/j.molcel.2012.01.026

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. Bastos de Oliveira FM, Kim D, Cussiol JR, Das J, Jeong MC, Doerfler L, Schmidt KH, Yu H, Smolka MB (2015) Phosphoproteomics reveals distinct modes of Mec1/ATR signaling during DNA replication. Mol Cell 57(6):1124–1132. doi:10.1016/j.molcel.2015.01.043

    Article  CAS  PubMed  Google Scholar 

  11. Kozlov SV, Waardenberg AJ, Engholm-Keller K, Arthur JW, Graham ME, Lavin M (2016) Reactive oxygen species (ROS)-activated ATM-dependent phosphorylation of cytoplasmic substrates identified by large-scale phosphoproteomics screen. Mol Cell Proteomics 15(3):1032–1047. doi:10.1074/mcp.M115.055723

    Article  CAS  PubMed  Google Scholar 

  12. Mazouzi A, Stukalov A, Muller AC, Chen D, Wiedner M, Prochazkova J, Chiang SC, Schuster M, Breitwieser FP, Pichlmair A, El-Khamisy SF, Bock C, Kralovics R, Colinge J, Bennett KL, Loizou JI (2016) A comprehensive analysis of the dynamic response to aphidicolin-mediated replication stress uncovers targets for ATM and ATMIN. Cell Rep. doi:10.1016/j.celrep.2016.03.077

    PubMed  Google Scholar 

  13. Bennetzen MV, Larsen DH, Bunkenborg J, Bartek J, Lukas J, Andersen JS (2010) Site-specific phosphorylation dynamics of the nuclear proteome during the DNA damage response. Mol Cell Proteomics 9(6):1314–1323. doi:10.1074/mcp.M900616-MCP200

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Pursiheimo A, Vehmas AP, Afzal S, Suomi T, Chand T, Strauss L, Poutanen M, Rokka A, Corthals GL, Elo LL (2015) Optimization of statistical methods impact on quantitative proteomics data. J Proteome Res 14(10):4118–4126. doi:10.1021/acs.jproteome.5b00183

    Article  CAS  PubMed  Google Scholar 

  15. Schwartz D, Gygi SP (2005) An iterative statistical approach to the identification of protein phosphorylation motifs from large-scale data sets. Nat Biotechnol 23(11):1391–1398. doi:10.1038/nbt1146

    Article  CAS  PubMed  Google Scholar 

  16. Xue Y, Zhou F, Zhu M, Ahmed K, Chen G, Yao X (2005) GPS: a comprehensive www server for phosphorylation sites prediction. Nucleic Acids Res 33(Web Server issue):W184–W187. doi:10.1093/nar/gki393

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  17. Dennis G Jr, Sherman BT, Hosack DA, Yang J, Gao W, Lane HC, Lempicki RA (2003) DAVID: database for annotation, visualization, and integrated discovery. Genome Biol 4(5):P3

    Article  PubMed  Google Scholar 

  18. Snel B, Lehmann G, Bork P, Huynen MA (2000) STRING: a web-server to retrieve and display the repeatedly occurring neighbourhood of a gene. Nucleic Acids Res 28(18):3442–3444

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. Gentleman RC, Carey VJ, Bates DM, Bolstad B, Dettling M, Dudoit S, Ellis B, Gautier L, Ge Y, Gentry J, Hornik K, Hothorn T, Huber W, Iacus S, Irizarry R, Leisch F, Li C, Maechler M, Rossini AJ, Sawitzki G, Smith C, Smyth G, Tierney L, Yang JY, Zhang J (2004) Bioconductor: open software development for computational biology and bioinformatics. Genome Biol 5(10):R80. doi:10.1186/gb-2004-5-10-r80

    Article  PubMed  PubMed Central  Google Scholar 

  20. Troyanskaya O, Cantor M, Sherlock G, Brown P, Hastie T, Tibshirani R, Botstein D, Altman RB (2001) Missing value estimation methods for DNA microarrays. Bioinformatics 17(6):520–525

    Article  CAS  PubMed  Google Scholar 

  21. Stacklies W, Redestig H, Scholz M, Walther D, Selbig J (2007) pcaMethods—a bioconductor package providing PCA methods for incomplete data. Bioinformatics 23(9):1164–1167. doi:10.1093/bioinformatics/btm069

    Article  CAS  PubMed  Google Scholar 

  22. Wickham H (2011) The split-apply-combine strategy for data analysis. J Stat Softw 40(1):29. doi:10.18637/jss.v040.i01

    Article  Google Scholar 

  23. Breitling R, Armengaud P, Amtmann A, Herzyk P (2004) Rank products: a simple, yet powerful, new method to detect differentially regulated genes in replicated microarray experiments. FEBS Lett 573(1–3):83–92. doi:10.1016/j.febslet.2004.07.055

    Article  CAS  PubMed  Google Scholar 

  24. Leek JT, Storey JD (2007) Capturing heterogeneity in gene expression studies by surrogate variable analysis. PLoS Genet 3(9):1724–1735. doi:10.1371/journal.pgen.0030161

    Article  CAS  PubMed  Google Scholar 

  25. Boutet E, Lieberherr D, Tognolli M, Schneider M, Bairoch A (2007) UniProtKB/Swiss-Prot. Methods Mol Biol 406:89–112

    CAS  PubMed  Google Scholar 

  26. Cox J, Mann M (2008) MaxQuant enables high peptide identification rates, individualized p.p.b.-range mass accuracies and proteome-wide protein quantification. Nat Biotechnol 26(12):1367–1372. doi:10.1038/nbt.1511

    Article  CAS  PubMed  Google Scholar 

  27. Cox J, Matic I, Hilger M, Nagaraj N, Selbach M, Olsen JV, Mann M (2009) A practical guide to the MaxQuant computational platform for SILAC-based quantitative proteomics. Nat Protoc 4(5):698–705. doi:10.1038/nprot.2009.36

    Article  CAS  PubMed  Google Scholar 

  28. Dudoit S, Yang YH, Callow MJ, Speed TP (2002) Statistical methods for identifying differentially expressed genes in replicated cDNA microarray experiments. Stat Sin 12:111–139

    Google Scholar 

  29. Bolstad BM, Irizarry RA, Astrand M, Speed TP (2003) A comparison of normalization methods for high density oligonucleotide array data based on variance and bias. Bioinformatics 19(2):185–193

    Article  CAS  PubMed  Google Scholar 

  30. Abdi H, Williams LJ (2010) Principal component analysis. Wiley Interdiscip Rev Comput Stats 2(4):433–459. doi:10.1002/wics.101

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Ashley J. Waardenberg .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2017 Springer Science+Business Media LLC

About this protocol

Cite this protocol

Waardenberg, A.J. (2017). Statistical Analysis of ATM-Dependent Signaling in Quantitative Mass Spectrometry Phosphoproteomics. In: Kozlov, S. (eds) ATM Kinase. Methods in Molecular Biology, vol 1599. Humana Press, New York, NY. https://doi.org/10.1007/978-1-4939-6955-5_17

Download citation

  • DOI: https://doi.org/10.1007/978-1-4939-6955-5_17

  • Published:

  • Publisher Name: Humana Press, New York, NY

  • Print ISBN: 978-1-4939-6953-1

  • Online ISBN: 978-1-4939-6955-5

  • eBook Packages: Springer Protocols

Publish with us

Policies and ethics