Skip to main content


Comparison of protein expression lists from mass spectrometry of human blood fluids using exact peptide sequences versus BLAST


The proteins in blood were all first expressed as mRNAs from genes within cells. There are databases of human proteins that are known to be expressed as mRNA in human cells and tissues. Proteins identified from human blood by the correlation of mass spectra that fail to match human mRNA expression products may not be correct. We compared the proteins identified in human blood by mass spectrometry by 10 different groups by correlation to human and nonhuman nucleic acid sequences. We determined whether the peptides or proteins identified by the different groups mapped to the human known proteins of the Reference Sequence (RefSeq) database. We used Structured Query Language data base searches of the peptide sequences correlated to tandem mass spectrometry spectra and basic local alignment search tool analysis of the identified full length proteins to control for correlation to the wrong peptide sequence or the existence of the same or very similar peptide sequence shared by more than one protein. Mass spectra were correlated against large protein data bases that contain many sequences that may not be expressed in human beings yet the search returned a very high percentage of peptides or proteins that are known to be found in humans. Only about 5% of proteins mapped to hypothetical sequences, which is in agreement with the reported false-positive rate of searching algorithms conditions. The results were highly enriched in secreted and soluble proteins and diminished in insoluble or membrane proteins. Most of the proteins identified were relatively short and showed a similar size distribution compared to the RefSeq database. At least three groups agree on a nonredundant set of 1671 types of proteins and a nonredundant set of 3151 proteins were identified by at least three peptides.


  1. 1.

    Washburn, M. P., Wolters, D., and Yates, J. R., 3rd (2001) Large-scale analysis of the yeast proteome by multidimensional protein identification technology.Nat. Biotechnol. 19, 242–247.

  2. 2.

    Anderson, N. L. and Anderson, N. G. (2002) The human plasma proteome: history, character, and diagnostic prospects.Mol. Cell. Proteomics 1, 845–867.

  3. 3.

    Pieper, R., Gatlin, C. L., Makusky, A. J., et al. (2003) The human serum proteome: display of nearly 3700 chromatographically separated protein spots on two-dimensional electrophoresis gels and identification of 325 distinct proteins.Proteomics 3, 1345–1364.

  4. 4.

    Koller, A., Washburn, M. P., Lange, B. M., et al. (2002) Proteomic survey of metabolic pathways in rice.Proc. Natl. Acad. Sci. USA 99, 11,969–11,974.

  5. 5.

    Marshall, J., Jankowski, A., Furesz, S. et al. (2004) Human serum proteins preseparated by electrophoresis or chromatography followed by tandem mass spectrometry.J. Proteome Res. 3, 364–382.

  6. 6.

    Olsen, J. V., Ong, S. E., and Mann, M. (2004) Trypsin cleaves exclusively C-terminal to arginine and lysine residues.Mol. Cell. Proteomics 3, 608–614.

  7. 7.

    Carr, S., Aebersold, R., Baldwin, M., Burlingame, A., Clauser, K., and Nesvizhskii, A. (2004) The need for guidelines in publication of peptide and protein identification data: Working Group on Publication Guidelines for Peptide and Protein Identification Data.Mol. Cell. Proteomics 3, 531–533.

  8. 8.

    Adkins, J. N., Varnum, S. M., Auberry, K. J., et al. (2002) Toward a human blood serum proteome: analysis by multidimensional separation coupled with mass spectrometry.Mol. Cell. Proteomics 1, 947–955.

  9. 9.

    Shen, Y., Jacobs, J. M., Camp, D. G., 2nd, et al. (2004) Ultra-high-efficiency strong cation exchange LC/RPLC/MS/MS for high dynamic range characterization of the human plasma proteome.Anal. Chem. 76, 1134–1144.

  10. 10.

    Jin, W. H., Dai, J., Li, S. J., Xia, Q. C., Zou, H. F., and Zeng, R. (2005) Human plasma proteome analysis by multidimensional chromatography prefractionation and linear ion trap mass spectrometry identification.J. Proteome Res. 4, 613–619.

  11. 11.

    Chan, K., Lucas, D. A., Hise D. et al. (2004) Analysis of the human serum proteome.Clinical Proteomics 1, 101–225.

  12. 12.

    Shen, Y., Kim, J., Strittmatter, E. F., et al. (2005) Characterization of the human blood plasma proteome.Proteomics 5, 4034–4045.

  13. 13.

    Tirumalai, R. S., Chan, K. C., Prieto, D. A., Issaq, H. J., Conrads, T. P., and Veenstra, T. D. (2003) Characterization of the low molecular weight human serum proteome.Mol. Cell. Proteomics 2, 1096–1103.

  14. 14.

    Perkins, D. N., Pappin, D. J., Creasy, D. M., and Cottrell, J. S. (1999) Probability-based protein identification by searching sequence databases using mass spectrometry data.Electrophoresis 20, 3551–3567.

  15. 15.

    Yates, J. R., 3rd (1998) Database searching using mass spectrometry data.Electrophoresis 19, 893–900.

  16. 16.

    Yates, J. R., 3rd, Eng, J. K., McCormack, A. L., and Schieltz, D. (1995) Method to correlate tandem mass spectra of modified peptides to amino acid sequences in the protein database.Anal. Chem. 67, 1426–1436.

  17. 17.

    Chelius, D., Huhmer, A. F., Shieh, C. H., et al. (2002) Analysis of the adenovirus type 5 proteome by liquid chromatography and tandem mass spectrometry methods.J. Proteome Res. 1, 501–513.

  18. 18.

    Moore, R. E., Young, M. K., and Lee, T. D. (2002) Qscore: an algorithm for evaluating SEQUEST database search results.J. Am. Soc. Mass. Spectrom. 13, 378–386.

  19. 19.

    Craig, R. and Beavis, R. C. (2004) TANDEM: matching proteins with tandem mass spectra.Bioinformatics 20, 1466–1467.

  20. 20.

    Ping, P., Vondriska, T. M., Creighton, C. J., et al. (2005) A functional annotation of sub-proteomes in human plasma.Proteomics 5, 3506–3519.

  21. 21.

    Adams, M. D., Soares, M. B., Kerlavage, A. R., Fields, C., and Venter, J. C. (1993) Rapid cDNA sequencing (expressed sequence tags) from a directionally cloned human infant brain cDNA library.Nat. Genet. 4, 373–380.

  22. 22.

    Venter, J. C., Adams, M. D., Myers, E. W., et al. (2001) The sequence of the human genome.Science 291, 1304–1351.

  23. 23.

    Omenn, G. S., States, D. J., Adamski, M., et al. (2005) Overview of the HUPO Plasma Proteome Project: results from the pilot phase with 35 collaborating laboratories and multiple analytical groups, generating a core dataset of 3020 proteins and a publicly-available database.Proteomics 5, 3226–3245.

  24. 24.

    Maglott, D. R., Katz, K. S., Sicotte, H., and Pruitt, K. D. (2000) NCBI’s LocusLink and RefSeq.Nucleic Acids Res. 28, 126–128.

  25. 25.

    Altschul, S. F., Gish, W., Miller, W., Myers, E. W., and Lipman, D. J. (1990) Basic local alignment search tool.J. Mol. Biol. 215, 403–410.

  26. 26.

    Altschul, S. F., Madden, T. L., Schaffer, A. A., et al. (1997) Gapped BLAST and PSI-BLAST: a new generation of protein database search programs.Nucleic Acids Res. 25, 3389–3402.

  27. 27.

    Ashburner, M., Ball, C. A., Blake, J. A., et al. (2000) Gene ontology: tool for the unification of biology. The Gene Ontology Consortium.Nat. Genet. 25, 25–29.

  28. 28.

    Camon, E., Magrane, M., Barrell, D., et al. (2003) The Gene Ontology Annotation (GOA) project: implementation of GO in SWISS-PROT, TrEMBL, and InterPro.Genome Res. 13, 662–672.

  29. 29.

    Boldrick, J. C., Alizadeh, A. A., Diehn, M., et al. (2002) Stereotyped and specific gene expression programs in human innate immune responses to bacteria.Proc. Natl. Acad. Sci. USA 99, 972–977.

  30. 30.

    Tavazoie, S., Hughes, J. D., Campbell, M. J., Cho, R. J., and Church, G. M. (1999) Systematic determination of genetic network architecture.Nat. Genet. 22, 281–285.

  31. 31.

    Anderson, N. L., Polanski, M., Pieper, R., et al. (2004) The human plasma proteome: a nonredundant list developed by combination of four separate sources.Mol. Cell. Proteomics 3, 311–326.

  32. 32.

    States, D. J., Omenn, G. S., Blackwell, T. W., et al. (2006) Challenges in deriving high-confidence protein identifications from data gathered by a HUPO plasma proteome collaborative study.Nat. Biotechnol. 24, 333–338.

  33. 33.

    Cargile, B. J., Bundy, J. L., and Stephenson, J. L., Jr. (2004) Potential for false positive identifications from large databases through tandem mass spectrometry.J. Proteome Res. 3, 1082–1085.

Download references

Author information

Correspondence to Peihong Zhu or John Marshall.

Rights and permissions

Reprints and Permissions

About this article

Key Words

  • Expression
  • analysis
  • proteomics
  • protein
  • composition
  • location
  • function
  • process
  • distribution
  • chi-square statistic
  • human
  • serum
  • computation