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Quantitation of Glycopeptides by ESI/MS - size of the peptide part strongly affects the relative proportions and allows discovery of new glycan compositions of Ceruloplasmin

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Abstract

Significant changes of glycan structures are observed in humans if diseases like cancer, arthritis or inflammation are present. Thus, interest in biomarkers based on glycan structures has rapidly emerged in recent years and monitoring disease specific changes of glycosylation and their quantification is of great interest. Mass spectrometry is most commonly used to characterize and quantify glycopeptides and glycans liberated from the glycoprotein of interest. However, ionization properties of glycopeptides can strongly depend on their composition and can therefore lead to intensities that do not reflect the actual proportions present in the intact glycoprotein. Here we show that an increase in the length of the peptide can lead to a more accurate determination and quantification of the glycans. The four glycosylation sites of human serum ceruloplasmin from 17 different individuals were analyzed using glycopeptides of varying peptide lengths, obtained by action of different proteases and by limited digestion. In most cases, highly sialylated compositions showed an increased relative abundance with increasing peptide length. We observed a relative increase of triantennary glycans of up to a factor of three and, even more, MS peaks corresponding to tetraantennary compositions on ceruloplasmin at glycosite 137N in all 17 samples, which we did not detect using a bottom up approach. The data presented here leads to the conclusion that a middle down - or when possible a top down - approach is favorable for qualitative and quantitative analysis of the glycosylation of glycoproteins.

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Abbreviations

H:

hexose

N:

N-acetylhexosamine

S:

sialic acid

F:

fucose

References

  1. Maverakis, E., Kim, K., Shimoda, M., Gershwin, M.E., Patel, F., Wilken, R., Raychaudhuri, S., Ruhaak, L.R., Lebrilla, C.B.: Glycans in the immune system and the altered glycan theory of autoimmunity: a critical review. J. Autoimmun. 57, 1–13 (2015). https://doi.org/10.1016/j.jaut.2014.12.002

    Article  CAS  PubMed  Google Scholar 

  2. Kenan, N., Larsson, A., Axelsson, O., Helander, A.: Changes in transferrin glycosylation during pregnancy may lead to false-positive carbohydrate-deficient transferrin (CDT) results in testing for riskful alcohol consumption. Clin. Chim. Acta. 412(1), 129–133 (2011). https://doi.org/10.1016/j.cca.2010.09.022

    Article  CAS  PubMed  Google Scholar 

  3. Golka, K., Wiese, A.: Carbohydrate-deficient transferrin (CDT)-a biomarker for long-term alcohol consumption. J. Toxicol. Environ. Health B. 7(4), 319–337 (2004). https://doi.org/10.1080/10937400490432400

    Article  CAS  Google Scholar 

  4. Sorvajärvi, K., Blake, J.E., Israel, Y., Niemelä, O.: Sensitivity and specificity of carbohydrate-deficient transferrin as a marker of alcohol abuse are significantly influenced by alterations in serum transferrin: comparison of two methods. Alcohol. Clin. Exp. Res. 20(3), 449–454 (1996). https://doi.org/10.1111/j.1530-0277.1996.tb01074.x

    Article  PubMed  Google Scholar 

  5. Yin, H., Lin, Z., Nie, S., Wu, J., Tan, Z., Zhu, J., Dai, J., Feng, Z., Marrero, J., Lubman, D.M.: Mass-selected site-specific Core-Fucosylation of Ceruloplasmin in alcohol-related hepatocellular carcinoma. J. Proteome Res. 13(6), 2887–2896 (2014). https://doi.org/10.1021/pr500043k

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  6. Balmaña, M., Sarrats, A., Llop, E., Barrabés, S., Saldova, R., Ferri, M.J., Figueras, J., Fort, E., de Llorens, R., Rudd, P.M., Peracaula, R.: Identification of potential pancreatic cancer serum markers: increased sialyl-Lewis X on ceruloplasmin. Clin. Chim. Acta. 442, 56–62 (2015). https://doi.org/10.1016/j.cca.2015.01.007

    Article  CAS  PubMed  Google Scholar 

  7. Bowman, M.J., Zaia, J.: Novel tags for the stable isotopic labeling of carbohydrates and quantitative analysis by mass spectrometry. Anal. Chem. 79(15), 5777–5784 (2007). https://doi.org/10.1021/ac070581b

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. Zhang, H., Yan, W., Aebersold, R.: Chemical probes and tandem mass spectrometry: a strategy for the quantitative analysis of proteomes and subproteomes. Curr. Opin. Chem. Biol. 8(1), 66–75 (2004). https://doi.org/10.1016/j.cbpa.2003.12.001

    Article  CAS  PubMed  Google Scholar 

  9. Zhang, H., Yi, E.C., Li, X.-j., Mallick, P., Kelly-Spratt, K.S., Masselon, C.D., Camp, D.G., Smith, R.D., Kemp, C.J., Aebersold, R.: High throughput quantitative analysis of serum proteins using Glycopeptide capture and liquid chromatography mass spectrometry. Mol. Cell. Proteomics. 4(2), 144–155 (2005). https://doi.org/10.1074/mcp.M400090-MCP200

    Article  CAS  PubMed  Google Scholar 

  10. Wohlgemuth, J., Karas, M., Eichhorn, T., Hendriks, R., Andrecht, S.: Quantitative site-specific analysis of protein glycosylation by LC-MS using different glycopeptide-enrichment strategies. Anal. Biochem. 395(2), 178–188 (2009). https://doi.org/10.1016/j.ab.2009.08.023

    Article  CAS  PubMed  Google Scholar 

  11. Hofmann, J., Hahm, H.S., Seeberger, P.H., Pagel, K.: Identification of carbohydrate anomers using ion mobility–mass spectrometry. Nature. 526, 241–244 (2015). https://doi.org/10.1038/nature15388

    Article  CAS  PubMed  Google Scholar 

  12. Wuhrer, M., Catalina, M.I., Deelder, A.M., Hokke, C.H.: Glycoproteomics based on tandem mass spectrometry of glycopeptides. J. Chromatogr. B. 849(1), 115–128 (2007). https://doi.org/10.1016/j.jchromb.2006.09.041

    Article  CAS  Google Scholar 

  13. Zaia, J.: Mass spectrometry and Glycomics. OMICS. 14(4), 401–418 (2010). https://doi.org/10.1089/omi.2009.0146

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Ruhaak, L.R., Miyamoto, S., Lebrilla, C.B.: Developments in the identification of glycan biomarkers for the detection of Cancer. Mol. Cell. Proteomics. 12(4), 846–855 (2013). https://doi.org/10.1074/mcp.R112.026799

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  15. Aizpurua-Olaizola, O., Sastre Toraño, J., Falcon-Perez, J.M., Williams, C., Reichardt, N., Boons, G.J.: Mass spectrometry for glycan biomarker discovery. TrAC Trends Anal. Chem. 100, 7–14 (2018). https://doi.org/10.1016/j.trac.2017.12.015

    Article  CAS  Google Scholar 

  16. Svarovsky, S.A., Joshi, L.: Cancer glycan biomarkers and their detection – past, present and future. Anal. Methods. 6(12), 3918–3936 (2014). https://doi.org/10.1039/C3AY42243G

    Article  CAS  Google Scholar 

  17. Gilgunn, S., Conroy, P.J., Saldova, R., Rudd, P.M., O'Kennedy, R.J.: Aberrant PSA glycosylation—a sweet predictor of prostate cancer. Nat. Rev. Urol. 10, 99–107 (2013). https://doi.org/10.1038/nrurol.2012.258

    Article  CAS  PubMed  Google Scholar 

  18. Ercan, A., Cui, J., Chatterton, D.E.W., Deane, K.D., Hazen, M.M., Brintnell, W., O'Donnell, C.I., Derber, L.A., Weinblatt, M.E., Shadick, N.A., Bell, D.A., Cairns, E., Solomon, D.H., Holers, V.M., Rudd, P.M., Lee, D.M.: Aberrant IgG galactosylation precedes disease onset, correlates with disease activity, and is prevalent in autoantibodies in rheumatoid arthritis. Arthritis Rheum. 62(8), 2239–2248 (2010). https://doi.org/10.1002/art.27533

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. Han, L., Costello, C.E.: Mass spectrometry of Glycans. Biochemistry. Biokhimiia. 78(7), 710–720 (2013). https://doi.org/10.1134/S0006297913070031

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. Wada, Y., Azadi, P., Costello, C.E., Dell, A., Dwek, R.A., Geyer, H., Geyer, R., Kakehi, K., Karlsson, N.G., Kato, K., Kawasaki, N., Khoo, K.-H., Kim, S., Kondo, A., Lattova, E., Mechref, Y., Miyoshi, E., Nakamura, K., Narimatsu, H., Novotny, M.V., Packer, N.H., Perreault, H., Peter-Katalinić, J., Pohlentz, G., Reinhold, V.N., Rudd, P.M., Suzuki, A., Taniguchi, N.: Comparison of the methods for profiling glycoprotein glycans—HUPO human disease Glycomics/proteome initiative multi-institutional study. Glycobiology. 17(4), 411–422 (2007). https://doi.org/10.1093/glycob/cwl086

    Article  CAS  PubMed  Google Scholar 

  21. Grünwald-Gruber, C., Thader, A., Maresch, D., Dalik, T., Altmann, F.: Determination of true ratios of different N-glycan structures in electrospray ionization mass spectrometry. Anal. Bioanal. Chem. 409(10), 2519–2530 (2017). https://doi.org/10.1007/s00216-017-0235-8

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  22. Walker, S.H., Papas, B.N., Comins, D.L., Muddiman, D.C.: The interplay of permanent charge and hydrophobicity in the electrospray ionization of Glycans. Anal. Chem. 82(15), 6636–6642 (2010). https://doi.org/10.1021/ac101227a

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  23. Harvey, D.J.: Quantitative aspects of the matrix-assisted laser desorption mass spectrometry of complex oligosaccharides. Rapid Commun. Mass Spectrom. 7(7), 614–619 (1993). https://doi.org/10.1002/rcm.1290070712

    Article  CAS  PubMed  Google Scholar 

  24. Chen, F.-T.A., Dobashi, T.S., Evangelista, R.A.: Quantitative analysis of sugar constituents of glycoproteins by capillary electrophoresis. Glycobiology. 8(11), 1045–1052 (1998). https://doi.org/10.1093/glycob/8.11.1045

    Article  CAS  PubMed  Google Scholar 

  25. Yamashita, K., Liang, C.J., Funakoshi, S., Kobata, A.: Structural studies of asparagine-linked sugar chains of human ceruloplasmin. Structural characteristics of the triantennary complex type sugar chains of human plasma glycoproteins. J. Biol. Chem. 256(3), 1283–1289 (1981)

    CAS  PubMed  Google Scholar 

  26. Endo, M., Suzuki, K., Schmid, K., Fournet, B., Karamanos, Y., Montreuil, J., Dorland, L., van Halbeek, H., Vliegenthart, J.F.: The structures and microheterogeneity of the carbohydrate chains of human plasma ceruloplasmin. A study employing 500-MHz 1H-NMR spectroscopy. J. Biol. Chem. 257(15), 8755–8760 (1982)

    CAS  PubMed  Google Scholar 

  27. Bielli, P., Calabrese, L.: Structure to function relationships in ceruloplasmin: a 'moonlighting' protein. Cell. Mol. Life Sci. 59(9), 1413–1427 (2002). https://doi.org/10.1007/s00018-002-8519-2

    Article  CAS  PubMed  Google Scholar 

  28. Sogabe, M., Nozaki, H., Tanaka, N., Kubota, T., Kaji, H., Kuno, A., Togayachi, A., Gotoh, M., Nakanishi, H., Nakanishi, T., Mikami, M., Suzuki, N., Kiguchi, K., Ikehara, Y., Narimatsu, H.: Novel Glycobiomarker for ovarian Cancer that detects clear cell carcinoma. J. Proteome Res. 13(3), 1624–1635 (2014). https://doi.org/10.1021/pr401109n

    Article  CAS  PubMed  Google Scholar 

  29. Harazono, A., Kawasaki, N., Itoh, S., Hashii, N., Ishii-Watabe, A., Kawanishi, T., Hayakawa, T.: Site-specific N-glycosylation analysis of human plasma ceruloplasmin using liquid chromatography with electrospray ionization tandem mass spectrometry. Anal. Biochem. 348(2), 259–268 (2006). https://doi.org/10.1016/j.ab.2005.10.036

    Article  CAS  PubMed  Google Scholar 

  30. Burkhart, J.M., Schumbrutzki, C., Wortelkamp, S., Sickmann, A., Zahedi, R.P.: Systematic and quantitative comparison of digest efficiency and specificity reveals the impact of trypsin quality on MS-based proteomics. J. Proteome. 75(4), 1454–1462 (2012). https://doi.org/10.1016/j.jprot.2011.11.016

    Article  CAS  Google Scholar 

  31. Bento, I., Peixoto, C., Zaitsev, V.N., Lindley, P.F.: Ceruloplasmin revisited: structural and functional roles of various metal cation-binding sites. Acta Crystallogr. D Biol. Crystallogr. 63(Pt 2), 240–248 (2007). https://doi.org/10.1107/S090744490604947X

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  32. Kyte, J., Doolittle, R.F.: A simple method for displaying the hydropathic character of a protein. J. Mol. Biol. 157(1), 105–132 (1982). https://doi.org/10.1016/0022-2836(82)90515-0

    Article  CAS  PubMed  Google Scholar 

  33. Clerc, F., Reiding, K.R., Jansen, B.C., Kammeijer, G.S.M., Bondt, A., Wuhrer, M.: Human plasma protein N-glycosylation. Glycoconj. J. 33(3), 309–343 (2016). https://doi.org/10.1007/s10719-015-9626-2

    Article  CAS  PubMed  Google Scholar 

  34. Guthals, A., Bandeira, N.: Peptide identification by tandem mass spectrometry with alternate fragmentation modes. Mol. Cell. Proteomics. 11(9), 550–557 (2012). https://doi.org/10.1074/mcp.r112.018556

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  35. Huang, Y., Triscari, J.M., Tseng, G.C., Pasa-Tolic, L., Lipton, M.S., Smith, R.D., Wysocki, V.H.: Statistical characterization of the charge state and residue dependence of low-energy CID peptide dissociation patterns. Anal. Chem. 77(18), 5800–5813 (2005). https://doi.org/10.1021/ac0480949

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  36. Harrison, A.G.: Energy-resolved mass spectrometry: a comparison of quadrupole cell and cone-voltage collision-induced dissociation. Rapid Commun. Mass Spectrom. 13(16), 1663–1670 (1999). https://doi.org/10.1002/(SICI)1097-0231(19990830)13:16<1663::AID-RCM695>3.0.CO;2-T

    Article  CAS  PubMed  Google Scholar 

  37. Hiroshi, M., Toshifumi, T., Yasutsugu, S., Takekiyo, M.: Optimization of skimmer voltages of an electrospray ion source coupled with a magnetic sector instrument. Rapid Commun. Mass Spectrom. 8(2), 205–210 (1994). https://doi.org/10.1002/rcm.1290080216

    Article  Google Scholar 

  38. Lin, C.-H., Krisp, C., Packer, N.H., Molloy, M.P.: Development of a data independent acquisition mass spectrometry workflow to enable glycopeptide analysis without predefined glycan compositional knowledge. J. Proteome. 172, 68–75 (2018). https://doi.org/10.1016/j.jprot.2017.10.011

    Article  CAS  Google Scholar 

  39. Zacchi, L.F., Schulz, B.L.: SWATH-MS Glycoproteomics reveals consequences of defects in the glycosylation machinery. Mol. Cell. Proteomics. 15(7), 2435–2447 (2016). https://doi.org/10.1074/mcp.M115.056366

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  40. Yeo, K.Y.B., Chrysanthopoulos, P.K., Nouwens, A.S., Marcellin, E., Schulz, B.L.: High-performance targeted mass spectrometry with precision data-independent acquisition reveals site-specific glycosylation macroheterogeneity. Anal. Biochem. 510, 106–113 (2016). https://doi.org/10.1016/j.ab.2016.06.009

    Article  CAS  PubMed  Google Scholar 

  41. Tsou, C.-C., Avtonomov, D., Larsen, B., Tucholska, M., Choi, H., Gingras, A.-C., Nesvizhskii, A.I.: DIA-umpire: comprehensive computational framework for data-independent acquisition proteomics. Nat. Methods. 12, 258–264 (2015). https://doi.org/10.1038/nmeth.3255

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  42. MacLean, B., Tomazela, D.M., Shulman, N., Chambers, M., Finney, G.L., Frewen, B., Kern, R., Tabb, D.L., Liebler, D.C., MacCoss, M.J.: Skyline: an open source document editor for creating and analyzing targeted proteomics experiments. Bioinformatics. 26(7), 966–968 (2010). https://doi.org/10.1093/bioinformatics/btq054

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  43. Gillet, L.C., Navarro, P., Tate, S., Röst, H., Selevsek, N., Reiter, L., Bonner, R., Aebersold, R.: Targeted data extraction of the MS/MS spectra generated by data-independent acquisition: a new concept for consistent and accurate proteome analysis. Mol. Cell. Proteomics. 11(6), O111.016717 (2012). https://doi.org/10.1074/mcp.O111.016717

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  44. Yang, Y., Wang, G., Song, T., Lebrilla, C.B., Heck, A.J.R.: Resolving the micro-heterogeneity and structural integrity of monoclonal antibodies by hybrid mass spectrometric approaches. mAbs. 9(4), 638–645 (2017). https://doi.org/10.1080/19420862.2017.1290033

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  45. Sinha, S., Pipes, G., Topp, E.M., Bondarenko, P.V., Treuheit, M.J., Gadgil, H.S.: Comparison of LC and LC/MS methods for quantifying N-glycosylation in recombinant IgGs. J. Am. Soc. Mass Spectrom. 19(11), 1643–1654 (2008). https://doi.org/10.1016/j.jasms.2008.07.004

    Article  CAS  PubMed  Google Scholar 

  46. Tipton, J.D., Tran, J.C., Catherman, A.D., Ahlf, D.R., Durbin, K.R., Kelleher, N.L.: Analysis of intact protein isoforms by mass spectrometry. J. Biol. Chem. 286(29), 25451–25458 (2011). https://doi.org/10.1074/jbc.R111.239442

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  47. Hochstrasser, H., Bauer, P., Walter, U., Behnke, S., Spiegel, J., Csoti, I., Zeiler, B., Bornemann, A., Pahnke, J., Becker, G., Riess, O., Berg, D.: Ceruloplasmin gene variations and substantia nigra hyperechogenicity in Parkinson disease. Neurology. 63(10), 1912–1917 (2004). https://doi.org/10.1212/01.wnl.0000144276.29988.c3

    Article  CAS  PubMed  Google Scholar 

  48. Hochstrasser, H., Tomiuk, J., Walter, U., Behnke, S., Spiegel, J., Krüger, R., Becker, G., Riess, O., Berg, D.: Functional relevance of ceruloplasmin mutations in Parkinson’s disease. FASEB J. 19(13), 1851–1853 (2005). https://doi.org/10.1096/fj.04-3486fje

    Article  CAS  PubMed  Google Scholar 

  49. Leymarie, N., Griffin, P.J., Jonscher, K., Kolarich, D., Orlando, R., McComb, M., Zaia, J., Aguilan, J., Alley, W.R., Altmann, F., Ball, L.E., Basumallick, L., Bazemore-Walker, C.R., Behnken, H., Blank, M.A., Brown, K.J., Bunz, S.-C., Cairo, C.W., Cipollo, J.F., Daneshfar, R., Desaire, H., Drake, R.R., Go, E.P., Goldman, R., Gruber, C., Halim, A., Hathout, Y., Hensbergen, P.J., Horn, D.M., Hurum, D., Jabs, W., Larson, G., Ly, M., Mann, B.F., Marx, K., Mechref, Y., Meyer, B., Möginger, U., Neusüβ, C., Nilsson, J., Novotny, M.V., Nyalwidhe, J.O., Packer, N.H., Pompach, P., Reiz, B., Resemann, A., Rohrer, J.S., Ruthenbeck, A., Sanda, M., Schulz, J.M., Schweiger-Hufnagel, U., Sihlbom, C., Song, E., Staples, G.O., Suckau, D., Tang, H., Thaysen-Andersen, M., Viner, R.I., An, Y., Valmu, L., Wada, Y., Watson, M., Windwarder, M., Whittal, R., Wuhrer, M., Zhu, Y., Zou, C.: Interlaboratory study on differential analysis of protein glycosylation by mass spectrometry: the ABRF glycoprotein research multi-institutional study 2012. Mol. Cell. Proteomics. 12(10), 2935–2951 (2013). https://doi.org/10.1074/mcp.M113.030643

    Article  CAS  PubMed  PubMed Central  Google Scholar 

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  1. Organic Chemistry, Department of Chemistry, University of Hamburg, Martin-Luther-King Platz 6, 20146, Hamburg, Germany

    Melissa Baerenfaenger, Manuela Moritz & Bernd Meyer

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  1. Melissa Baerenfaenger
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Baerenfaenger, M., Moritz, M. & Meyer, B. Quantitation of Glycopeptides by ESI/MS - size of the peptide part strongly affects the relative proportions and allows discovery of new glycan compositions of Ceruloplasmin. Glycoconj J 36, 13–26 (2019). https://doi.org/10.1007/s10719-018-9852-5

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