Quantitative MS Workflow for a High-Quality Secretome Analysis by a Quantitative Secretome-Proteome Comparison

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Quantitative Methods in Proteomics

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

Abstract

Cells secrete proteins to communicate with their environment. Therefore, it is interesting to characterize the proteins which are released from cells under certain experimental conditions the so-called secretome. Here, often proteins from conditioned medium of cultured cells are analyzed, but these additionally might include also contaminating proteins of serum that have not been sufficiently removed or proteins from dying cells. To provide high-quality secretome data and minimize potential contaminants, we describe a quantitative comparison of conditioned medium and the cellular proteome. The described workflow comprises cell cultivation, sample preparation, and final data analysis which is based on the comparison of data from label-free mass spectrometric quantification of proteins from the conditioned medium with corresponding cellular proteomes enabling the detection of bona fide secreted proteins.

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References

  1. Schira-Heinen J, Grube L, Waldera-Lupa DM et al (2019) Pitfalls and opportunities in the characterization of unconventionally secreted proteins by secretome analysis. Biochim Biophys Acta Proteins Proteom 1867(12):140,237

    Article  CAS  Google Scholar 

  2. Eichelbaum K, Krijgsveld J (2014) Combining pulsed SILAC labeling and click-chemistry for quantitative secretome analysis. In: Ivanov IA (ed) Exocytosis and endocytosis. Springer New York, New York, NY, pp 101–114

    Chapter  Google Scholar 

  3. Eichelbaum K, Winter M, Diaz MB et al (2012) Selective enrichment of newly synthesized proteins for quantitative secretome analysis. Nat Biotech 30(10):984–990

    Article  CAS  Google Scholar 

  4. Mukherjee P, Mani S (2013) Methodologies to decipher the cell secretome. Biochim Biophys Acta 1834(11):2226–2232

    Article  CAS  Google Scholar 

  5. Chevallet M, Diemer H, Van Dorssealer A et al (2007) Toward a better analysis of secreted proteins: the example of the myeloid cells secretome. Proteomics 7(11):1757–1770

    Article  CAS  Google Scholar 

  6. Weigert C, Lehmann R, Hartwig S et al (2014) The secretome of the working human skeletal muscle—a promising opportunity to combat the metabolic disaster? Proteomics 8(1–2):5–18

    CAS  PubMed  Google Scholar 

  7. Luo X, Liu Y, Wang R et al (2011) A high-quality secretome of A549 cells aided the discovery of C4b-binding protein as a novel serum biomarker for non-small cell lung cancer. J Proteome 74(4):528–538

    Article  CAS  Google Scholar 

  8. Loei H, Tan HT, Lim TK et al (2012) Mining the gastric cancer secretome: identification of GRN as a potential diagnostic marker for early gastric cancer. J Proteome Res 11(3):1759–1772

    Article  CAS  Google Scholar 

  9. Stiess M, Wegehingel S, Nguyen C et al (2015) A dual SILAC proteomic labeling strategy for quantifying constitutive and cell-cell induced protein secretion. J Proteome Res 14(8):3229–3238

    Article  CAS  Google Scholar 

  10. Grube L, Dellen R, Kruse F et al (2018) Mining the secretome of C2C12 muscle cells: data dependent experimental approach to analyze protein secretion using label-free quantification and peptide based analysis. J Proteome Res 17(2):879–890

    Article  CAS  Google Scholar 

  11. Tusher VG, Tibshirani R, Chu G (2001) Significance analysis of microarrays applied to the ionizing radiation response. Proc Natl Acad Sci U S A 98(9):5116–5121

    Article  CAS  Google Scholar 

  12. 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  Google Scholar 

  13. Tyanova S, Temu T, Cox J (2016) The MaxQuant computational platform for mass spectrometry-based shotgun proteomics. Nat Protoc 11(12):2301–2319

    Article  CAS  Google Scholar 

  14. 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  Google Scholar 

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Acknowledgments

We’d like to thank Thomas Lenz for performing the A549 cell culture experiments used to exemplify the provided workflow.

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Correspondence to Kai Stühler .

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Poschmann, G., Prescher, N., Stühler, K. (2021). Quantitative MS Workflow for a High-Quality Secretome Analysis by a Quantitative Secretome-Proteome Comparison. 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_21

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  • DOI: https://doi.org/10.1007/978-1-0716-1024-4_21

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  • Publisher Name: Humana, New York, NY

  • Print ISBN: 978-1-0716-1023-7

  • Online ISBN: 978-1-0716-1024-4

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