Abstract
Determination of secreted proteins provides highly valuable information about cell functions. While the typical methods for the determination of biologically relevant but low abundant molecular species still rely on the use of specific antibodies, mass spectrometry-based methods are now gaining sufficient sensitivity to cope with such challenges as well. In the current study, we have identified several cytokines and chemokines which were induced in primary human umbilical vein endothelial cells upon inflammatory activation. Based on the high-resolution mass spectrometry data obtained with a Q Exactive orbitrap, we built an MRM method to quantify the most relevant molecules selected from the screening experiment. All experimental data are available via ProteomeXchange, PXD002211/12, and Panorama (www.panoramaweb.org). Using nano-flow Chip-HPLC coupled to a 6490 triple-quadrupole MS for MRM analyses, we achieved calibration curves covering a linear range of four orders of magnitude and detection limits in the low attomol per microliter concentration range. Carryover was consistently less than 0.005 %, the accuracy was between 80 and 120 %, and the median coefficient of variation for LC/MS was only 2.2 %. When including the variance of quantification introduced by cell culture and digestion, the coefficient of variation was less than 20 % for most peptides. With appropriate marker molecules, we monitored typical variations introduced by cell culture caused by differences in cell numbers, proliferative states, and cell death. As a result, here, we present a robust and efficient MRM-based assay for the accurate and sensitive determination of cytokines and chemokines representative for functional cell states and including comprehensive quality controls.
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References
Dranoff G (2004) Cytokines in cancer pathogenesis and cancer therapy. Nat Rev Cancer 4(1):11–22. doi:10.1038/nrc1252
Shahzad A, Knapp M, Lang I, Kohler G (2010) Interleukin 8 (IL-8)—a universal biomarker? Int Arch Med 3:11. doi:10.1186/1755-7682-3-11
Paltridge JL, Belle L, Khew-Goodall Y (2013) The secretome in cancer progression. Biochim Biophys Acta 1834(11):2233–2241. doi:10.1016/j.bbapap.2013.03.014
Balkwill FR, Burke F (1989) The cytokine network. Immunol Today 10(9):299–304. doi:10.1016/0167-5699(89)90085-6
Bileck A, Kreutz D, Muqaku B, Slany A, Gerner C (2014) Comprehensive assessment of proteins regulated by dexamethasone reveals novel effects in primary human peripheral blood mononuclear cells. J Proteome Res 13(12):5989–6000. doi:10.1021/pr5008625
Riss TL, Moravec RA, Niles AL (2011) Cytotoxicity testing: measuring viable cells, dead cells, and detecting mechanism of cell death. Methods Mol Biol 740:103–114. doi:10.1007/978-1-61779-108-6_12
Rudolf AF, Skovgaard T, Knapp S, Jensen LJ, Berthelsen J (2014) A comparison of protein kinases inhibitor screening methods using both enzymatic activity and binding affinity determination. PLoS One 9(6), e98800. doi:10.1371/journal.pone.0098800
Fischer PM (2008) Computational chemistry approaches to drug discovery in signal transduction. Biotechnol J 3(4):452–470. doi:10.1002/biot.200700259
Greenbaum D, Luscombe NM, Jansen R, Qian J, Gerstein M (2001) Interrelating different types of genomic data, from proteome to secretome: oming in on function. Genome Res 11(9):1463–1468. doi:10.1101/Gr.207401
Michalski A, Damoc E, Hauschild JP, Lange O, Wieghaus A, Makarov A, Nagaraj N, Cox J, Mann M, Horning S (2011) Mass spectrometry-based proteomics using Q exactive, a high-performance benchtop quadrupole orbitrap mass spectrometer. Mol Cell Proteomics 10(9). doi:10.1074/mcp.M111.011015
Nagaraj N, Kulak NA, Cox J, Neuhauser N, Mayr K, Hoerning O, Vorm O, Mann M (2012) System-wide perturbation analysis with nearly complete coverage of the yeast proteome by single-shot ultra HPLC runs on a bench top orbitrap. Mol Cell Proteomics 11(3). doi:10.1074/mcp.M111.013722
Method of the Year 2012 (2013) Nat Methods 10(1):1
Kuzyk MA, Smith D, Yang J, Cross TJ, Jackson AM, Hardie DB, Anderson NL, Borchers CH (2009) Multiple reaction monitoring-based, multiplexed, absolute quantitation of 45 proteins in human plasma. Mol Cell Proteomics 8(8):1860–1877. doi:10.1074/mcp.M800540-MCP200
Abbatiello SE, Schilling B, Mani DR, Zimmerman LJ, Hall SC, MacLean B, Albertolle M, Allen S, Burgess M, Cusack MP, Ghosh M, Hedrick V, Held JM, Inerowicz HD, Jackson A, Keshishian H, Kinsinger CR, Lyssand J, Makowski L, Mesri M, Rodriguez H, Rudnick P, Sadowski P, Sedransk N, Shaddox K, Skates SJ, Kuhn E, Smith D, Whiteaker JR, Whitwell C, Zhang S, Borchers CH, Fisher SJ, Gibson BW, Liebler DC, MacCoss MJ, Neubert TA, Paulovich AG, Regnier FE, Tempst P, Carr SA (2015) Large-scale inter-laboratory study to develop, analytically validate and apply highly multiplexed, quantitative peptide assays to measure cancer-relevant proteins in plasma. Mol Cell Proteomics. doi:10.1074/mcp.M114.047050
Surinova S, Huttenhain R, Chang CY, Espona L, Vitek O, Aebersold R (2013) Automated selected reaction monitoring data analysis workflow for large-scale targeted proteomic studies. Nat Protoc 8(8):1602–1619. doi:10.1038/nprot.2013.091
Anderson NL, Anderson NG (2002) The human plasma proteome—history, character, and diagnostic prospects. Mol Cell Proteomics 1(11):845–867. doi:10.1074/mcp.R200007-MCP200
Cox J, Neuhauser N, Michalski A, Scheltema RA, Olsen JV, Mann M (2011) Andromeda: a peptide search engine integrated into the MaxQuant environment. J Proteome Res 10(4):1794–1805. doi:10.1021/pr101065j
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
Cox J, Mann M (2012) 1D and 2D annotation enrichment: a statistical method integrating quantitative proteomics with complementary high-throughput data. BMC Bioinformatics 13(Suppl 16):S12. doi:10.1186/1471-2105-13-S16-S12
Vizcaino JA, Deutsch EW, Wang R, Csordas A, Reisinger F, Rios D, Dianes JA, Sun Z, Farrah T, Bandeira N, Binz PA, Xenarios I, Eisenacher M, Mayer G, Gatto L, Campos A, Chalkley RJ, Kraus HJ, Albar JP, Martinez-Bartolome S, Apweiler R, Omenn GS, Martens L, Jones AR, Hermjakob H (2014) ProteomeXchange provides globally coordinated proteomics data submission and dissemination. Nat Biotechnol 32(3):223–226. doi:10.1038/nbt.2839
MacLean B, Tomazela DM, Shulman N, Chambers M, Finney GL, Frewen B, Kern R, Tabb DL, Liebler DC, MacCoss MJ (2010) Skyline: an open source document editor for creating and analyzing targeted proteomics experiments. Bioinformatics 26(7):966–968. doi:10.1093/bioinformatics/btq054
Bereman MS, MacLean B, Tomazela DM, Liebler DC, MacCoss MJ (2012) The development of selected reaction monitoring methods for targeted proteomics via empirical refinement. Proteomics 12(8):1134–1141. doi:10.1002/pmic.201200042
Sharma V, Eckels J, Taylor GK, Shulman NJ, Stergachis AB, Joyner SA, Yan P, Whiteaker JR, Halusa GN, Schilling B, Gibson BW, Colangelo CM, Paulovich AG, Carr SA, Jaffe JD, MacCoss MJ, MacLean B (2014) Panorama: a targeted proteomics knowledge base. J Proteome Res 13(9):4205–4210. doi:10.1021/pr5006636
van Amsterdam P, Companjen A, Brudny-Kloeppel M, Golob M, Luedtke S, Timmerman P (2013) The European Bioanalysis Forum community’s evaluation, interpretation and implementation of the European Medicines Agency guideline on Bioanalytical Method Validation. Bioanalysis 5(6):645–659. doi:10.4155/bio.13.19
Chappey O, Wautier MP, Boval B, Wautier JL (1996) Endothelial cells in culture: an experimental model for the study of vascular dysfunctions. Cell Biol Toxicol 12(4–6):199–205
Kato Y, Lewalle JM, Baba Y, Tsukuda M, Sakai N, Baba M, Kobayashi K, Koshika S, Nagashima Y, Frankenne F, Noel A, Foidart JM, Hata RI (2001) Induction of SPARC by VEGF in human vascular endothelial cells. Biochem Biophys Res Commun 287(2):422–426. doi:10.1006/bbrc.2001.5622
Legrand C, Bour JM, Jacob C, Capiaumont J, Martial A, Marc A, Wudtke M, Kretzmer G, Demangel C, Duval D et al (1992) Lactate dehydrogenase (LDH) activity of the cultured eukaryotic cells as marker of the number of dead cells in the medium [corrected]. J Biotechnol 25(3):231–243
Deutsch EW, Lam H, Aebersold R (2008) PeptideAtlas: a resource for target selection for emerging targeted proteomics workflows. EMBO Rep 9(5):429–434. doi:10.1038/embor.2008.56
Stenken JA, Poschenrieder AJ (2015) Bioanalytical chemistry of cytokines—a review. Anal Chim Acta 853C:95–115. doi:10.1016/j.aca.2014.10.009
Zhang Q, Faca V, Hanash S (2011) Mining the plasma proteome for disease applications across seven logs of protein abundance. J Proteome Res 10(1):46–50. doi:10.1021/pr101052y
Malekzadeh A, de Groot V, Beckerman H, van Oosten BW, Blankenstein MA, Teunissen C (2012) Challenges in multi-plex and mono-plex platforms for the discovery of inflammatory profiles in neurodegenerative diseases. Methods 56(4):508–513. doi:10.1016/j.ymeth.2012.03.017
Surinova S, Schiess R, Huttenhain R, Cerciello F, Wollscheid B, Aebersold R (2011) On the development of plasma protein biomarkers. J Proteome Res 10(1):5–16. doi:10.1021/pr1008515
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Muqaku, B., Slany, A., Bileck, A. et al. Quantification of cytokines secreted by primary human cells using multiple reaction monitoring: evaluation of analytical parameters. Anal Bioanal Chem 407, 6525–6536 (2015). https://doi.org/10.1007/s00216-015-8817-9
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DOI: https://doi.org/10.1007/s00216-015-8817-9