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Spectral counting robust on high mass accuracy mass spectrometers

Authors

  • Wolfgang Hoehenwarter,

    Corresponding author
    1. Department of Molecular Systems Biology, Faculty of Life Sciences, University of Vienna, Althanstrasse 14, A-1090 Vienna, Austria
    • Department of Molecular Systems Biology, Faculty of Life Sciences, University of Vienna, Althanstr. 14, A-1090 Vienna, Austria.
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  • Stefanie Wienkoop

    1. Department of Molecular Systems Biology, Faculty of Life Sciences, University of Vienna, Althanstrasse 14, A-1090 Vienna, Austria
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Abstract

Mass spectrometry is central to shotgun proteomics, an application that seeks to quantify as much of the total protein complement of a biological sample as possible. The high mass accuracy, resolution, capacity and scan rate of modern mass spectrometers have greatly facilitated this endeavor. The sum of MS to MS/MS transitions in tandem mass spectrometry, the spectral count (SC), of a peptide has been shown to be a reliable estimate of its relative abundance. However, when using SCs, optimal MS configurations are crucial in order to maximize the number of low abundant proteins quantified while keeping the estimates for the highly abundant proteins within the linear dynamic range.

In this study, LC/MS/MS analysis was performed using an LTQ-OrbiTrap on a sample containing many highly abundant proteins. Tuning the LTQ-OrbiTrap mass spectrometer to minimize redundant MS/MS acquisition and to maximize resolution of the proteome by accurately measured m/z ratios resulted in an appreciable increase in quantified low abundant proteins. An exclusion duration of 90 s and an exclusion width of 10 ppm were found best of those tested. The spectral count of individual proteins was found to be highly reproducible and protein abundance ratios were not affected by the different settings that were applied. We conclude that on a high mass accuracy instrument spectral counting is a robust measure of protein abundance even for samples containing many highly abundant proteins and that tuning dynamic exclusion parameters appreciably improves the number of proteins that can be reliably quantified. Copyright © 2010 John Wiley & Sons, Ltd.

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