MCP
HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS
 QUICK SEARCH:   [advanced]


     


Originally published In Press as doi:10.1074/mcp.M500230-MCP200 on October 11, 2005.
This Article
Right arrow Full Text
Right arrow Full Text (PDF)
Right arrow Supplemental Data
Right arrow All Versions of this Article:
M500230-MCP200v1
5/1/144    most recent
Right arrow Submit a response
Right arrow Alert me when this article is cited
Right arrow Alert me when eLetters are posted
Right arrow Alert me if a correction is posted
Right arrow Citation Map
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Download to citation manager
Right arrow Glossary
Right arrow reprints & permissions
Citing Articles
Right arrow Citing Articles via HighWire
Right arrow Citing Articles via Google Scholar
Google Scholar
Right arrow Articles by Silva, J. C.
Right arrow Articles by Geromanos, S. J.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Silva, J. C.
Right arrow Articles by Geromanos, S. J.
Social Bookmarking
 Add to CiteULike   Add to Complore   Add to Connotea   Add to Del.icio.us   Add to Digg   Add to Reddit   Add to Technorati  
What's this?

Molecular & Cellular Proteomics 5:144-156, 2006.
© 2006 by The American Society for Biochemistry and Molecular Biology, Inc.


Research

Absolute Quantification of Proteins by LCMSE

A Virtue of Parallel ms Acquisition *,S

Jeffrey C. Silva{ddagger},§, Marc V. Gorenstein{ddagger}, Guo-Zhong Li{ddagger}, Johannes P. C. Vissers and Scott J. Geromanos{ddagger}

From the {ddagger} Waters Corporation, Milford, Massachusetts 01757-3696 and Waters Corporation, Transistorstraat 18, 1322 CE Almere, The Netherlands

Relative quantification methods have dominated the quantitative proteomics field. There is a need, however, to conduct absolute quantification studies to accurately model and understand the complex molecular biology that results in proteome variability among biological samples. A new method of absolute quantification of proteins is described. This method is based on the discovery of an unexpected relationship between MS signal response and protein concentration: the average MS signal response for the three most intense tryptic peptides per mole of protein is constant within a coefficient of variation of less than ±10%. Given an internal standard, this relationship is used to calculate a universal signal response factor. The universal signal response factor (counts/mol) was shown to be the same for all proteins tested in this study. A controlled set of six exogenous proteins of varying concentrations was studied in the absence and presence of human serum. The absolute quantity of the standard proteins was determined with a relative error of less than ±15%. The average MS signal responses of the three most intense peptides from each protein were plotted against their calculated protein concentrations, and this plot resulted in a linear relationship with an R2 value of 0.9939. The analyses were applied to determine the absolute concentration of 11 common serum proteins, and these concentrations were then compared with known values available in the literature. Additionally within an unfractionated Escherichia coli lysate, a subset of identified proteins known to exist as functional complexes was studied. The calculated absolute quantities were used to accurately determine their stoichiometry.


§ To whom correspondence should be addressed: Waters Corp., 34 Maple St., Milford, MA 01757-3696. Tel.: 508-482-3005; Fax: 508-482-2055; E-mail: jeff_silva{at}waters.com


Add to CiteULike CiteULike   Add to Complore Complore   Add to Connotea Connotea   Add to Del.icio.us Del.icio.us   Add to Digg Digg   Add to Reddit Reddit   Add to Technorati Technorati    What's this?


This article has been cited by other articles:


Home page
Brief Funct Genomic ProteomicHome page
M. Wang, J. You, K. G. Bemis, T. J. Tegeler, and D. P. G. Brown
Label-free mass spectrometry-based protein quantification technologies in proteomic analysis
Brief Funct Genomic Proteomic, June 25, 2008; (2008) eln031v1.
[Abstract] [Full Text] [PDF]


Home page
Mol. Cell. ProteomicsHome page
A. Prakash, B. Piening, J. Whiteaker, H. Zhang, S. A. Shaffer, D. Martin, L. Hohmann, K. Cooke, J. M. Olson, S. Hansen, et al.
Assessing Bias in Experiment Design for Large Scale Mass Spectrometry-based Quantitative Proteomics
Mol. Cell. Proteomics, October 1, 2007; 6(10): 1741 - 1748.
[Abstract] [Full Text] [PDF]


Home page
Mol. Cell. ProteomicsHome page
J. P. C. Vissers, J. I. Langridge, and J. M. F. G. Aerts
Analysis and Quantification of Diagnostic Serum Markers and Protein Signatures for Gaucher Disease
Mol. Cell. Proteomics, May 1, 2007; 6(5): 755 - 766.
[Abstract] [Full Text] [PDF]


Home page
Mol. Cell. ProteomicsHome page
J. D. Jaffe, D. R. Mani, K. C. Leptos, G. M. Church, M. A. Gillette, and S. A. Carr
PEPPeR, a Platform for Experimental Proteomic Pattern Recognition
Mol. Cell. Proteomics, October 1, 2006; 5(10): 1927 - 1941.
[Abstract] [Full Text] [PDF]


Home page
Mol. Cell. ProteomicsHome page
S.-L. Wu, J. Kim, R. W. Bandle, L. Liotta, E. Petricoin, and B. L. Karger
Dynamic Profiling of the Post-translational Modifications and Interaction Partners of Epidermal Growth Factor Receptor Signaling after Stimulation by Epidermal Growth Factor Using Extended Range Proteomic Analysis (ERPA)
Mol. Cell. Proteomics, September 1, 2006; 5(9): 1610 - 1627.
[Abstract] [Full Text] [PDF]




HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS
 All ASBMB Journals   Journal of Biological Chemistry 
 Journal of Lipid Research   ASBMB Today 
Copyright © 2006 by the American Society for Biochemistry and Molecular Biology.