A high confidence, manually validated human blood plasma protein reference set.
BACKGROUND
The immense diagnostic potential of human plasma has prompted great interest and effort in cataloging its contents, exemplified by the Human Proteome Organization (HUPO) Plasma Proteome Project (PPP) pilot project. Due to challenges in obtaining a reliable blood plasma protein list, HUPO later re-analysed their own original dataset with a more stringent statistical treatment that resulted in a much reduced list of high confidence (at least 95%) proteins compared with their original findings. In order to facilitate the discovery of novel biomarkers in the future and to realize the full diagnostic potential of blood plasma, we feel that there is still a need for an ultra-high confidence reference list (at least 99% confidence) of blood plasma proteins.


METHODS
To address the complexity and dynamic protein concentration range of the plasma proteome, we employed a linear ion-trap-Fourier transform (LTQ-FT) and a linear ion trap-Orbitrap (LTQ-Orbitrap) for mass spectrometry (MS) analysis. Both instruments allow the measurement of peptide masses in the low ppm range. Furthermore, we employed a statistical score that allows database peptide identification searching using the products of two consecutive stages of tandem mass spectrometry (MS3). The combination of MS3 with very high mass accuracy in the parent peptide allows peptide identification with orders of magnitude more confidence than that typically achieved.


RESULTS
Herein we established a high confidence set of 697 blood plasma proteins and achieved a high 'average sequence coverage' of more than 14 peptides per protein and a median of 6 peptides per protein. All proteins annotated as belonging to the immunoglobulin family as well as all hypothetical proteins whose peptides completely matched immunoglobulin sequences were excluded from this protein list. We also compared the results of using two high-end MS instruments as well as the use of various peptide and protein separation approaches. Furthermore, we characterized the plasma proteins using cellular localization information, as well as comparing our list of proteins to data from other sources, including the HUPO PPP dataset.


CONCLUSIONS
Superior instrumentation combined with rigorous validation criteria gave rise to a set of 697 plasma proteins in which we have very high confidence, demonstrated by an exceptionally low false peptide identification rate of 0.29%.
Schenk
Susann
S
Department of Biochemistry and Molecular Biology, Bioinformatics, University of Southern Denmark, Campusvej 55, 5230 Odense M,Denmark. sschenk@bmb.sdu.dk
Schoenhals
Gary J
GJ
de Souza
Gustavo
G
Mann
Matthias
M
Nat Biotechnol. 2006 Mar;24(3):333-8
16525410
Urology. 2005 Sep;66(3):536-41
16140073
Anal Chem. 2006 Jan 15;78(2):493-500
16408932
Cell. 2006 Apr 7;125(1):187-99
16615899
J Mol Biol. 2006 Jan 6;355(1):47-62
16300789
Mol Cell Proteomics. 2004 Apr;3(4):311-26
14718574
Cancer Res. 1997 Sep 15;57(18):4111-7
9307301
Proc Natl Acad Sci U S A. 2004 Sep 14;101(37):13417-22
15347803
Mol Cell Proteomics. 2005 Dec;4(12):2010-21
16249172
Electrophoresis. 1992 Sep-Oct;13(9-10):707-14
1459097
Genome Biol. 2006;7(5):R40
16709260
Arterioscler Thromb Vasc Biol. 2004 Aug;24(8):1367-73
15166009
Proteomics. 2004 May;4(5):1235-40
15188391
Electrophoresis. 2005 Mar;26(6):1174-88
15704250
Proteomics. 2005 Aug;5(13):3246-61
16104057
J Biol Chem. 2004 Apr 2;279(14):14024-32
14726510
Proteomics. 2005 Aug;5(13):3226-45
16104056
Oncogene. 2005 Aug 29;24(37):5751-63
16123808
Clin Biochem. 2002 Jun;35(4):327-31
12135697
Nucleic Acids Res. 1997 Sep 1;25(17):3389-402
9254694
Genome Biol. 2006;7(9):R80
16948836
J Proteome Res. 2003 Jan-Feb;2(1):43-50
12643542
Mol Cell Proteomics. 2002 Dec;1(12):947-55
12543931
Proteomics. 2003 Jul;3(7):1345-64
12872236
J Biol Chem. 1997 Feb 28;272(9):5627-34
9038172