Skip to main content

High-Throughput Profiling of Proteome and Posttranslational Modifications by 16-Plex TMT Labeling and Mass Spectrometry

  • Protocol
  • First Online:
Quantitative Methods in Proteomics

Part of the book series: Methods in Molecular Biology ((MIMB,volume 2228))

Abstract

Mass spectrometry (MS)-based proteomic profiling of whole proteome and protein posttranslational modifications (PTMs) is a powerful technology to measure the dynamics of proteome with high throughput and deep coverage. The reproducibility of quantification benefits not only from the fascinating developments in high-performance liquid chromatography (LC) and high-resolution MS with enhanced scan rates but also from the invention of multiplexed isotopic labeling strategies, such as the tandem mass tags (TMT). In this chapter, we introduce a 16-plex TMT-LC/LC-MS/MS protocol for proteomic profiling of biological and clinical samples. The protocol includes protein extraction, enzymatic digestion, PTM peptide enrichment, TMT labeling, and two-dimensional reverse-phase liquid chromatography fractionation coupled with tandem mass spectrometry (MS/MS) analysis, followed by computational data processing. In general, more than 10,000 proteins and tens of thousands of PTM sites (e.g., phosphorylation and ubiquitination) can be confidently quantified. This protocol provides a general protein measurement tool, enabling the dissection of protein dysregulation in any biological samples and human diseases.

Kaiwen Yu and Zhen Wang are the co-first authors.

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

Access this chapter

Protocol
USD 49.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 109.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 149.00
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 199.99
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

Institutional subscriptions

References

  1. Zhang Y, Fonslow BR, Shan B et al (2013) Protein analysis by shotgun/bottom-up proteomics. Chem Rev 113(4):2343–2394

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  2. Aebersold R, Mann M (2016) Mass-spectrometric exploration of proteome structure and function. Nature 537(7620):347–355

    Article  CAS  PubMed  Google Scholar 

  3. Huttlin EL, Bruckner RJ, Paulo JA et al (2017) Architecture of the human interactome defines protein communities and disease networks. Nature 545(7655):505–509

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  4. Yu J, Peng J, Chi H (2019) Systems immunology: integrating multi-omics data to infer regulatory networks and hidden drivers of immunity. Curr Opin Sys Biol 15:19–29

    Article  Google Scholar 

  5. Toby TK, Fornelli L, Kelleher NL (2016) Progress in top-down proteomics and the analysis of proteoforms. Annu Rev Anal Chem (Palo Alto, Calif) 9(1):499–519

    Article  CAS  Google Scholar 

  6. Peng J, Gygi SP (2001) Proteomics: the move to mixtures. J Mass Spectrom 36(10):1083–1091

    Article  CAS  PubMed  Google Scholar 

  7. Wang H, Yang Y, Li Y et al (2015) Systematic optimization of long gradient chromatography mass spectrometry for deep analysis of brain proteome. J Proteome Res 14(2):829–838

    Article  CAS  PubMed  Google Scholar 

  8. Bai B, Tan H, Pagala VR et al (2017) Deep profiling of proteome and phosphoproteome by isobaric labeling, extensive liquid chromatography, and mass spectrometry. Methods Enzymol 585:377–395

    Article  CAS  PubMed  Google Scholar 

  9. Huttlin EL, Jedrychowski MP, Elias JE et al (2010) A tissue-specific atlas of mouse protein phosphorylation and expression. Cell 143(7):1174–1189

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. Kim W, Bennett EJ, Huttlin EL et al (2011) Systematic and quantitative assessment of the ubiquitin-modified proteome. Mol Cell 44(2):325–340

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. Mertins P, Mani DR, Ruggles KV et al (2016) Proteogenomics connects somatic mutations to signalling in breast cancer. Nature 534(7605):55–62

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Vasaikar S, Huang C, Wang X et al (2019) Proteogenomic analysis of human colon cancer reveals new therapeutic opportunities. Cell 177(4):1035–1049. e1019

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  13. Stewart E, McEvoy J, Wang H et al (2018) Identification of therapeutic targets in rhabdomyosarcoma through integrated genomic, pigenomic, and proteomic analyses. Cancer Cell 34(3):411–426. e419

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Wang H, Diaz AK, Shaw TI et al (2019) Deep multiomics profiling of brain tumors identifies signaling networks downstream of cancer driver genes. Nat Commun 10(1):3718

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  15. Bai B, Hales CM, Chen PC et al (2013) U1 small nuclear ribonucleoprotein complex and RNA splicing alterations in Alzheimer's disease. Proc Natl Acad Sci U S A 110(41):16562–16567

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Bai B, Wang X, Li Y et al (2020) Deep multilayer brain proteomics identifies molecular networks in Alzheimer’s disease progression. Neuron 105:975–991.e7. [Epub ahead of print]:online 8 January 2020.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  17. Liu H, Sadygov RG, Yates JR 3rd (2004) A model for random sampling and estimation of relative protein abundance in shotgun proteomics. Anal Chem 76(14):4193–4201

    Article  CAS  PubMed  Google Scholar 

  18. Cox J, Hein MY, Luber CA et al (2014) Accurate proteome-wide label-free quantification by delayed normalization and maximal peptide ratio extraction, termed MaxLFQ. Mol Cell Proteomics 13(9):2513–2526

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. Venable JD, Dong MQ, Wohlschlegel J et al (2004) Automated approach for quantitative analysis of complex peptide mixtures from tandem mass spectra. Nat Methods 1(1):39–45

    Article  CAS  PubMed  Google Scholar 

  20. Ludwig C, Gillet L, Rosenberger G et al (2018) Data-independent acquisition-based SWATH-MS for quantitative proteomics: a tutorial. Mol Syst Biol 14(8):e8126

    Article  PubMed  PubMed Central  Google Scholar 

  21. Bache N, Geyer PE, Bekker-Jensen DB et al (2018) A novel LC system embeds analytes in pre-formed gradients for rapid, ultra-robust proteomics. Mol Cell Proteomics 17(11):2284–2296

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  22. Thompson A, Schafer J, Kuhn K et al (2003) Tandem mass tags: a novel quantification strategy for comparative analysis of complex protein mixtures by MS/MS. Anal Chem 75(8):1895–1904

    Article  CAS  PubMed  Google Scholar 

  23. Ross PL, Huang YN, Marchese JN et al (2004) Multiplexed protein quantitation in Saccharomyces cerevisiae using amine-reactive isobaric tagging reagents. Mol Cell Proteomics 3(12):1154–1169

    Article  CAS  PubMed  Google Scholar 

  24. Frost DC, Greer T, Li L (2015) High-resolution enabled 12-plex DiLeu isobaric tags for quantitative proteomics. Anal Chem 87(3):1646–1654

    Article  CAS  PubMed  Google Scholar 

  25. Rauniyar N, Yates JR 3rd (2014) Isobaric labeling-based relative quantification in shotgun proteomics. J Proteome Res 13(12):5293–5309

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  26. Thompson A, Wolmer N, Koncarevic S et al (2019) TMTpro: design, synthesis, and initial evaluation of a proline-based isobaric 16-plex tandem mass tag reagent set. Anal Chem 91(24):15,941–15,950

    Article  CAS  Google Scholar 

  27. Hogrebe A, von Stechow L, Bekker-Jensen DB et al (2018) Benchmarking common quantification strategies for large-scale phosphoproteomics. Nat Commun 9(1):1045

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  28. Ting L, Rad R, Gygi SP et al (2011) MS3 eliminates ratio distortion in isobaric multiplexed quantitative proteomics. Nat Methods 8(11):937–940

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  29. Niu M, Cho JH, Kodali K et al (2017) Extensive peptide fractionation and y1 ion-based interference detection method for enabling accurate quantification by isobaric labeling and mass spectrometry. Anal Chem 89(5):2956–2963

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  30. Wenger CD, Lee MV, Hebert AS et al (2011) Gas-phase purification enables accurate, multiplexed proteome quantification with isobaric tagging. Nat Methods 8(11):933–935

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. Savitski MM, Mathieson T, Zinn N et al (2013) Measuring and managing ratio compression for accurate iTRAQ/TMT quantification. J Proteome Res 12(8):3586–3598

    Article  CAS  PubMed  Google Scholar 

  32. Wuhr M, Haas W, McAlister GC et al (2012) Accurate multiplexed proteomics at the MS2 level using the complement reporter ion cluster. Anal Chem 84(21):9214–9221

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  33. Peng J, Schwartz D, Elias JE et al (2003) A proteomics approach to understanding protein ubiquitination. Nat Biotechnol 21(8):921–926

    Article  CAS  PubMed  Google Scholar 

  34. Udeshi ND, Mani DR, Eisenhaure T et al (2012) Methods for quantification of in vivo changes in protein ubiquitination following proteasome and deubiquitinase inhibition. Mol Cell Proteomics 11(5):148–159

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  35. Udeshi ND, Svinkina T, Mertins P et al (2013) Refined preparation and use of anti-diglycine remnant (K-epsilon-GG) antibody enables routine quantification of 10,000s of ubiquitination sites in single proteomics experiments. Mol Cell Proteomics 12(3):825–831

    Article  CAS  PubMed  Google Scholar 

  36. Rose CM, Isasa M, Ordureau A et al (2016) Highly multiplexed quantitative mass spectrometry analysis of ubiquitylomes. Cell Syst 3(4):395–403. e394

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  37. Wang X, Li Y, Wu Z et al (2014) JUMP: a tag-based database search tool for peptide identification with high sensitivity and accuracy. Mol Cell Proteomics 13(12):3663–3673

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  38. Li Y, Wang X, Cho JH et al (2016) JUMPg: an integrative proteogenomics pipeline identifying unannotated proteins in human brain and cancer cells. J Proteome Res 15(7):2309–2320

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  39. Xu P, Duong DM, Peng JM (2009) Systematical optimization of reverse-phase chromatography for shotgun proteomics. J Proteome Res 8(8):3944–3950

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  40. Peng J, Cheng D (2005) Proteomic analysis of ubiquitin conjugates in yeast. Methods Enzymol 399:367–381

    Article  CAS  PubMed  Google Scholar 

  41. Na CH, Jones DR, Yang Y et al (2012) Synaptic protein ubiquitination in rat brain revealed by antibody-based ubiquitome analysis. J Proteome Res 11(9):4722–4732

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  42. Pagala VR, High AA, Wang X et al (2015) Quantitative protein analysis by mass spectrometry. Methods Mol Biol 1278:281–305

    Article  CAS  PubMed  Google Scholar 

  43. Peng J, Elias JE, Thoreen CC et al (2003) Evaluation of multidimensional chromatography coupled with tandem mass spectrometry (LC/LC-MS/MS) for large-scale protein analysis: the yeast proteome. J Proteome Res 2(1):43–50

    Article  CAS  PubMed  Google Scholar 

  44. Elias JE, Gygi SP (2007) Target-decoy search strategy for increased confidence in large-scale protein identifications by mass spectrometry. Nat Methods 4(3):207–214

    Article  CAS  PubMed  Google Scholar 

  45. Nielsen ML, Vermeulen M, Bonaldi T et al (2008) Iodoacetamide-induced artifact mimics ubiquitination in mass spectrometry. Nat Methods 5(6):459–460

    Article  CAS  PubMed  Google Scholar 

  46. Xu P, Duong DM, Seyfried NT et al (2009) Quantitative proteomics reveals the function of unconventional ubiquitin chains in proteasomal degradation. Cell 137(1):133–145

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  47. Bustos D, Bakalarski CE, Yang Y et al (2012) Characterizing ubiquitination sites by peptide based immunoaffinity enrichment. Mol Cell Proteomics 11(12):1529–1540

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  48. Chen PC, Na CH, Peng J (2012) Quantitative proteomics to decipher ubiquitin signaling. Amino Acids 43(3):1049–1060

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  49. Pirmoradian M, Budamgunta H, Chingin K et al (2013) Rapid and deep human proteome analysis by single-dimension shotgun proteomics. Mol Cell Proteomics 12(11):3330–3338

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  50. Xu P, Peng J (2006) Dissecting the ubiquitin pathway by mass spectrometry. Biochim Biophys Acta 1764(12):1940–1947

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  51. Gao Y, Li Y, Zhang C et al (2016) Enhanced purification of ubiquitinated proteins by engineered tandem hybrid ubiquitin-binding domains (ThUBDs). Mol Cell Proteomics 15(4):1381–1396

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  52. Seyfried NT, Xu P, Duong DM et al (2008) Systematic approach for validating the ubiquitinated proteome. Anal Chem 80(11):4161–4169

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  53. Kelstrup CD, Jersie-Christensen RR, Batth TS et al (2014) Rapid and deep proteomes by faster sequencing on a benchtop quadrupole ultra-high-field orbitrap mass spectrometer. J Proteome Res 13(12):6187–6195

    Article  CAS  PubMed  Google Scholar 

Download references

Acknowledgments

This work was partially supported by the National Institutes of Health (R01GM114260, R01AG047928, R01AG053987, and RF1AG064909) and ALSAC (American Lebanese Syrian Associated Charities). The MS analysis was performed in the Center of Proteomics and Metabolomics at St. Jude Children’s Research Hospital, partially supported by NIH Cancer Center Support Grant (P30CA021765).

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Junmin Peng .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2021 Springer Science+Business Media, LLC, part of Springer Nature

About this protocol

Check for updates. Verify currency and authenticity via CrossMark

Cite this protocol

Yu, K., Wang, Z., Wu, Z., Tan, H., Mishra, A., Peng, J. (2021). High-Throughput Profiling of Proteome and Posttranslational Modifications by 16-Plex TMT Labeling and Mass Spectrometry. In: Marcus, K., Eisenacher, M., Sitek, B. (eds) Quantitative Methods in Proteomics. Methods in Molecular Biology, vol 2228. Humana, New York, NY. https://doi.org/10.1007/978-1-0716-1024-4_15

Download citation

  • DOI: https://doi.org/10.1007/978-1-0716-1024-4_15

  • Published:

  • Publisher Name: Humana, New York, NY

  • Print ISBN: 978-1-0716-1023-7

  • Online ISBN: 978-1-0716-1024-4

  • eBook Packages: Springer Protocols

Publish with us

Policies and ethics