Skip to main content
SpringerLink
Log in

Response of peptide intensity to concentration in ESI-MS-based proteome

  • Articles
  • Special Topic Mass Spectrometry Analysis
  • Published:
Science China Chemistry Aims and scope Submit manuscript

Abstract

High-throughput quantification with label-free methods has received considerable attention in electrospray ionization (ESI)-mass spectrometry (MS), but the manner by which MS signals respond to peptide concentration remains unclear in proteomics. We developed a new mathematical formula to describe the intrinsic log-log relationship between the MS intensity response and peptide concentration in an analytical ESI process. Experimental results showed that the calibration curve is fairly fit to the log-log formula with a linear dynamic range of approximate four to five orders of magnitude. However, we found that the ionization of analytical peptides can be severely suppressed by coexisting matrix peptides, such that the calibration curve can be poorly leveled off on both ends. Our study suggests that the interferences from coexisting matrix peptides should be reduced in the ESI process to use the log-log calibration curve successfully for the high-throughput quantification.

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

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  1. Beck M, Schmidt A, Malmstroem J, Claassen M, Ori A, Szymborska, A, Herzog F, Rinner O, Aebersold R. The quantitative proteome of a human cell line. Mol Sys Biol, 2011, 7: 549

    Article  Google Scholar 

  2. Domon B, Aebersold R. Options and considerations when selecting a quantitative proteomics strategy. Nat Biotech, 2010, 28: 710–721

    Article  CAS  Google Scholar 

  3. Lu P, Vogel C, Wang R, Yao X, Marcotte EM. Absolute protein expression profiling estimates the relative contributions of transcriptional and translational regulation. Nat Biotech, 2006, 25: 117–124

    Article  Google Scholar 

  4. Bantscheff M, Schirle M, Sweetman G, Rick J, Kuster B. Quantitative mass spectrometry in proteomics: a critical review. Anal Bioanal Chem, 2007, 389: 1017–1031

    Article  CAS  Google Scholar 

  5. Matzke M, Brown J, Gritsenko M, Metz T, Pounds J, Rodland K, Shukla A, Smith R, Waters K, McDermott J, Webb-Robertson B. A comparative analysis of computational approaches to relative protein quantification using peptide peak intensities in label-free LC-MS proteomics experiments. Proteomics, 2013, 13: 493–503

    Article  CAS  Google Scholar 

  6. Ning K, Fermin D, Nesvizhskii AI. Comparative analysis of different label-free mass spectrometry based protein abundance estimates and their correlation with RNA-Seq gene expression data. J Proteome Res, 2012, 11: 2261–2271

    Article  CAS  Google Scholar 

  7. Cheng F, Blackburn K, Lin Y, Goshe M, Williamson, J. Absolute protein quantification by LC/MSE for global analysis of salicylic acid-induced plant protein secretion responses. J Proteome Res, 2008, 8: 82–93

    Article  Google Scholar 

  8. Schwanhäusser B, Busse D, Li N, Dittmar G, Schuchhardt J, Wolf J, et al. Global quantification of mammalian gene expression control. Nature, 2011, 473: 337–342

    Article  Google Scholar 

  9. Ishihama Y, Oda Y, Tabata T, Sato T, Nagasu T, et al. Exponentially modified protein abundance index (emPAI) for estimation of absolute protein amount in proteomics by the number of sequenced peptides per protein. Mol Cell Proteomics, 2005, 4: 1265–1272

    Article  CAS  Google Scholar 

  10. Arike L, Valgepea K, Peril L, Nahku R, Adamberg K, et al. Comparison and applications of label-free absolute proteome quantification methods on Escherichia coli. J Proteomics, 2012, 75: 5437–5448

    Article  CAS  Google Scholar 

  11. Polpitiya, A, Qian, W, Jaitly, N, Sato T, Nagasu T, Rappsilber J, Mann M. DAnTE: a statistical tool for quantitative analysis of-omics data. Bioinformatics, 2008, 24: 1556–1558

    Article  CAS  Google Scholar 

  12. Karpievitch Y, Stanley J, Taverner T, Huang J, Adkins J, Ansong C, Heffron F, Metz T, Qian W, Yoon H, Smith R, Dabney A. A statistical framework for protein quantitation in bottom-up MS-based proteomics. Bioinformatics, 2009, 25: 2028–2034

    Article  CAS  Google Scholar 

  13. Clough T, Key M, Ott I, Ragg S, Schadow G, Vitek O. Protein quantification in label-free LC-MS experiments. J Proteome Res, 2009, 8: 5275–5284

    Article  CAS  Google Scholar 

  14. Schmidt A, Karas M, Dülcks T. Effect of different solution flow rates on analyte ion signals in nano-ESI MS, or: when does ESI turn into nano-ESI? J Am Soc Mass Spectrom, 2003, 14: 492–500

    Article  CAS  Google Scholar 

  15. Tang L, Kebarle P. Effect of the conductivity of the electrosprayed solution on the electrospray current. Factors determining analyte sensitivity in electrospray mass spectrometry. Anal Chem, 1991, 63: 2709–2715

    Article  CAS  Google Scholar 

  16. Hendricks, JR CD, Pfeifer RJ. Parametric studies of electrohydrodynamic spraying. Aiaa J, 1968, 6: 496–502

    Article  Google Scholar 

  17. La Mora D, Fernandez J. The current emitted by highly conducting Taylor cones. J Fluid Mech, 1994, 260: 155–184

    Article  Google Scholar 

  18. Beach DG, Gabryelski W. Linear and nonlinear regimes of electrospray signal response in analysis of urine by electrospray ionization-high field asymmetric waveform ion mobility spectrometry-MS and implications for nontarget quantification. Anal Chem, 2013, 85: 2127–2134

    Article  CAS  Google Scholar 

  19. La Mora D, Fernandez J. The current emitted by highly conducting Taylor cones. J Fluid Mech, 1994, 260: 155–184

    Article  Google Scholar 

  20. Tang L, Kebarle P. Effect of the conductivity of the electrosprayed solution on the electrospray current. Factors determining analyte sensitivity in electrospray mass spectrometry. Anal Chem, 1991, 63: 2709–2715

    Article  CAS  Google Scholar 

  21. Ganan-Calvo A. Cone-jet analytical extension of Taylor’s electrostat ic solution and the asymptotic universal scaling laws in electrospraying. Phys Rev Lett, 1997, 79: 217–220

    Article  CAS  Google Scholar 

  22. Gañán-Calvo A. The surface charge in electrospraying: its nature and its universal scaling laws. J Aeros Sci, 1999, 30: 863–872

    Article  Google Scholar 

  23. Van Berkel GJ. Electrolytic deposition of metals on to the high-voltage contact in an electrospray emitter: Implications for gas-phase ion formation. J Mass Spectrom, 2000, 35: 773–783

    Article  Google Scholar 

  24. Wei W, Gu Z, Wang S, Zhang Y, Lei K, Kase K. Numerical simulation of the cone-jet formation and current generation in electrostatic spray-modeling as regards space charged droplet effect. J Micromech Microeng, 2013, 23: 15004–15014

    Article  Google Scholar 

  25. Addona T, Abbatiello S, Schilling B, Skates S, Mani D, Bunk Dm Spiegelman C, Zimmerman L, Ham A, Keshishian H. Multi-site assessment of the precision and reproducibility of multiple reaction monitoring-based measurements of proteins in plasma. Nat Biotech, 2009, 27: 633–641

    Article  CAS  Google Scholar 

  26. Jiang Y, Ying W, Wu S, Chen M, Guan W, Yang D, Song Y, Liu X, Li J, Hao Y. First insight into the human liver proteome from PROTEOMESKY-LIVERHu 1.0, a publicly available database. J Proteome Res, 2010, 9: 79–94

    Article  Google Scholar 

  27. Smith RD, Shen Y, Tang K. Ultrasensitive and quantitative analyses from combined separations-mass spectrometry for the characterization of proteomes. Acc Chem Res, 2004, 37: 269

    Article  CAS  Google Scholar 

  28. Schmelzeisen-Redeker G, Bütfering L, Röllgen F W. Desolvation of ions and molecules in thermospray mass spectrometry. Int J Mass Spectrom Ion Proc, 1989, 90: 139–150

    Article  CAS  Google Scholar 

  29. Nehring H, Thiebes S, Bütfering L, Röllgen FW. Cluster ion formation in thermospray mass-spectrometry of ammonium-salts. Int J Mass Spectrom Ion Processes, 1993, 128: 123–132

    Article  CAS  Google Scholar 

  30. Iribarne JV, Thomson BA. On the evaporation of small ions from charged droplets. J Chem Phys, 1976, 64: 2287–2294

    Article  CAS  Google Scholar 

  31. Enke C G. A predictive model for matrix and analyte effects in electrospray ionization of singly-charged ionic analytes. Anal Chem, 1997, 69: 4885–4893

    Article  CAS  Google Scholar 

  32. Cech NB, Krone JR, Enke CG. Predicting electrospray response from chromatographic retention time. Anal Chem, 2001, 73: 208–213

    Article  CAS  Google Scholar 

  33. Cech NB, Enke CG. Effect of affinity for droplet surfaces on the fraction of analyte molecules charged during electrospray droplet fission. Anal Chem, 2001, 73: 4632–4639

    Article  CAS  Google Scholar 

  34. Koivusalo M, Haimi P, Heikinheimo L, Kostiainen R, Somerharju P. Quantitative determination of phospholipid compositions by ESI-MS: effects of acyl chain length, unsaturation, and lipid concentration on instrument response. J Lipid Res, 2001, 42: 663–672

    Google Scholar 

  35. Gangl ET, Annan M, Spooner N, Vouros P. Reduction of signal suppression effects in ESI-MS using a nanosplitting device. Anal Chem, 2001, 73: 5635–5644

    Article  CAS  Google Scholar 

  36. Valaskovic G, Utley L, Lee M, Wu J. Ultra-low flow nanospray for the normalization of conventional liquid chromatography/mass spectrometry through equimolar response: standard-free quantitative estimation of metabolite levels in drug discovery. Rap Commun Mass Spectrom, 2006, 20: 1087–1096

    Article  CAS  Google Scholar 

  37. Juraschek R, Dülcks T, Karas M. Nanoelectrospray-more than just a minimized-flow electrospray ionization source. J Am Soc Mass Spectrom, 1999, 10: 300–308

    Article  CAS  Google Scholar 

  38. Wilm MS, Mann M. Electrospray and Taylor-cone theory, Dole’s beam of macromolecules at last? Int J Mass Spectrom Ion Proc, 1994, 136: 167–180

    Article  CAS  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Chemistry and Institutes of Biomedical Sciences, Fudan University, Shanghai, 200433, China

    WenYuan Lu, XueFei Yin, XiaoHui Liu, GuoQuan Yan & PengYuan Yang

Authors
  1. WenYuan Lu
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. XueFei Yin
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. XiaoHui Liu
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. GuoQuan Yan
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. PengYuan Yang
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to PengYuan Yang.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Lu, W., Yin, X., Liu, X. et al. Response of peptide intensity to concentration in ESI-MS-based proteome. Sci. China Chem. 57, 686–694 (2014). https://doi.org/10.1007/s11426-014-5096-9

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11426-014-5096-9

Keywords

Search

Navigation