Skip to main content
SpringerLink
Log in

Quantitative Proteomics of Secreted Proteins

  • Protocol
  • First Online:
Innate Immune Activation

Part of the book series: Methods in Molecular Biology ((MIMB,volume 1714))

Abstract

Secreted proteins such as cytokines, interleukins, growth factors, and hormones have pleiotropic functions and facilitate intercellular communication in organisms. Quantification of these proteins conventionally relies on antibody-based methods, i.e., enzyme-linked immunosorbent assays (ELISA), whose large-scale use is limited by availability, specificity, and affordability.

Here, we describe an experimental and bioinformatics workflow to comprehensively quantify cellular protein secretion by mass spectrometry. Secreted proteins are collected in vitro or ex vivo, digested with proteases and the resulting peptide mixtures are analyzed in single liquid chromatography–mass spectrometry (LC-MS/MS) runs. Label-free quantification and bioinformatics analysis is conducted in the MaxQuant and Perseus computational environment. Our workflow allows the quantification of thousands of secreted proteins spanning a concentration range of four orders of magnitude and permits the systems-level characterization of secretory programs as well as the discovery of proteins with unexpected extracellular functions.

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

Access this chapter

Log in via an institution

Institutional subscriptions

Similar content being viewed by others

References

  1. Mann M, Nils a K, Nagaraj N et al (2013) The coming age of complete, accurate, and ubiquitous proteomes. Mol Cell 49:583–590

    Article  CAS  PubMed  Google Scholar 

  2. Larance M, Lamond AI (2015) Multidimensional proteomics for cell biology. Nat Rev Mol Cell Biol 16:269–280

    Article  CAS  PubMed  Google Scholar 

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

    Article  CAS  PubMed  Google Scholar 

  4. Altelaar AFM, Munoz J, Heck AJR (2013) Next-generation proteomics: towards an integrative view of proteome dynamics. Nat Rev Genet 14:35–48

    Article  CAS  PubMed  Google Scholar 

  5. Meissner F, Scheltema RA, Mollenkopf H-J et al (2013) Direct proteomic quantification of the secretome of activated immune cells. Science 340:475–478

    Article  CAS  PubMed  Google Scholar 

  6. Rieckmann JC, Geiger R, Hornburg D, Wolf T, Kveler K, Jarrossay D, Sallusto F, Shen-Orr SS, Lanzavecchia A, Mann M, Meissner F (2017) Social network architecture of human immune cells unveiled by quantitative proteomics. Nat Immunol 18(5):583–593

    Google Scholar 

  7. 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 26:1367–1372

    Article  CAS  PubMed  Google Scholar 

  8. Tyanova S, Temu T, Sinitcyn P et al (2016) The Perseus computational platform for comprehensive analysis of (prote)omics data. Nat Methods 13(9):731–740

    Article  CAS  PubMed  Google Scholar 

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

    Article  CAS  PubMed  Google Scholar 

  10. Wisniewski JR, Zougman A, Mann M (2009) Combination of FASP and StageTip-based fractionation allows in-depth analysis of the hippocampal membrane proteome. J Proteome Res 8:5674–5678

    Article  CAS  PubMed  Google Scholar 

  11. Wisniewski JR, Zougman A, Nagaraj N et al (2009) Universal sample preparation method for proteome analysis. Nat Methods 6:359–362

    Article  CAS  PubMed  Google Scholar 

  12. Scheltema RA, Hauschild J-P, Lange O et al (2014) The Q exactive HF, a benchtop mass spectrometer with a pre-filter, high-performance quadrupole and an ultra-high-field orbitrap analyzer. Mol Cell Proteomics 13:3698–3708

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  13. Cox J, Neuhauser N, Michalski A et al (2011) Andromeda: a peptide search engine integrated into the maxquant environment. J Proteome Res 10:1794–1805

    Article  CAS  PubMed  Google Scholar 

  14. Luber CA, Cox J, Lauterbach H et al (2010) Quantitative proteomics reveals subset-specific viral recognition in dendritic cells. Immunity 32:279–289

    Article  CAS  PubMed  Google Scholar 

  15. 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 13:2513–2526

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Rappsilber J, Ishihama Y, Mann M (2003) Stop and go extraction tips for matrix-assisted laser desorption/ionization, nanoelectrospray, and LC/MS sample pretreatment in proteomics. Anal Chem 75:663–670

    Article  CAS  PubMed  Google Scholar 

  17. Griss J, Perez-Riverol Y, Lewis S et al (2016) Recognizing millions of consistently unidentified spectra across hundreds of shotgun proteomics datasets. Nat Methods 13:651–656

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Liew AW-C, Law N-F, Yan H (2011) Missing value imputation for gene expression data: computational techniques to recover missing data from available information. Brief Bioinform 12:498–513

    Article  PubMed  Google Scholar 

  19. Tusher VG, Tibshirani R, Chu G (2001) Significance analysis of microarrays applied to the ionizing radiation response. Proc Natl Acad Sci 98:5116–5121

    Article  CAS  PubMed  PubMed Central  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Experimental Systems Immunology Laboratory, Max-Planck-Institute of Biochemistry, Am Klopferspitz 18, D-82152, Martinsried, Germany

    Annika Frauenstein & Felix Meissner Ph.D.

  2. Department of Proteomics and Signal Transduction, Max-Planck Institute of Biochemistry, Am Klopferspitz 18, D-82152, Martinsried, Germany

    Annika Frauenstein

Authors
  1. Annika Frauenstein
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Felix Meissner Ph.D.
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Felix Meissner Ph.D. .

Editor information

Editors and Affiliations

  1. Inflammation Division, The Walter & Eliza Hall Institute of Medical Research, Parkville, Victoria, Australia

    Dominic De Nardo

  2. Chemical Biology Division, The Walter & Eliza Hall Institute of Medical Research, Parkville, Victoria, Australia

    Christine M De Nardo

Rights and permissions

Reprints and permissions

Copyright information

© 2018 Springer Science+Business Media LLC

About this protocol

Check for updates. Verify currency and authenticity via CrossMark

Cite this protocol

Frauenstein, A., Meissner, F. (2018). Quantitative Proteomics of Secreted Proteins. In: De Nardo, D., De Nardo, C. (eds) Innate Immune Activation. Methods in Molecular Biology, vol 1714. Humana Press, New York, NY. https://doi.org/10.1007/978-1-4939-7519-8_14

Download citation

  • DOI: https://doi.org/10.1007/978-1-4939-7519-8_14

  • Published:

  • Publisher Name: Humana Press, New York, NY

  • Print ISBN: 978-1-4939-7518-1

  • Online ISBN: 978-1-4939-7519-8

  • eBook Packages: Springer Protocols

Publish with us

Policies and ethics

Search

Navigation