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Originally published In Press as doi:10.1074/mcp.M900223-MCP200 on October 16, 2009.
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Submitted on May 6, 2009
Revised on October 13, 2009
Accepted on October 16, 2009

Performance metrics for liquid chromatography-tandem mass spectrometry systems in proteomic analyses and evaluation by the CPTAC network

Paul A Rudnick, Karl R Clauser, Lisa E Kilpatrick, Dmitrii V Tchekhovskoi, Pedatsur Neta, Niksa Blonder, Dean D Billheimer, Ronald K Blackman, David M Bunk, Helene L Cardasis, Amy-Joan L Ham, Jacob D Jaffe, Christopher R Kinsinger, Mehdi Mesri, Thomas A Neubert, Birgit Schilling, David L Tabb, Tony J Tegeler, Lorenzo Vega-Montoto, Asokan Mulayath Variyath, Mu Wang, Pei Wang, Jeffrey R. Whiteaker, Lisa J. Zimmerman, Steven A. Carr, Susan J. Fisher, Bradford W. Gibson, Amanda G. Paulovich, Fred E. Regnier, Henry Rodriguez, Cliff Spiegelman, Paul Tempst, Daniel C. Liebler, and Stephen E. Stein

National Institute of Standards and Technology, Gaithersburg, MD 20899

Corresponding Author: steve.stein{at}nist.gov

A major unmet need in liquid chromatography-tandem mass spectrometry (LC-MS/MS)-based proteomic analyses is a set of tools for quantitative assessment of system performance and evaluation of technical variability. Here we describe 46 system performance metrics for monitoring chromatographic performance, electrospray source stability, MS1 and MS2 signals, dynamic sampling of ions for MS/MS and peptide identification. Applied to datasets from replicate LC-MS/MS analyses, these metrics display consistent, reasonable responses to controlled perturbations. The metrics typically display variations less than 10% and thus can reveal even subtle differences in performance of system components. Analyses of data from interlaboratory studies conducted under a common standard operating procedure identified outlier data and provided clues to specific causes. Moreover, interlaboratory variation reflected by the metrics indicates which system components vary the most between laboratories. Application of these metrics enables rational, quantitative quality assessment for proteomics and other LC-MS/MS analytical applications.


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