Impact of data-dependent exclusion list based mass spectrometry on label-free proteomic quantification

Abstract

RATIONALESpectral count analysis via data-dependent acquisition (DDA) mode mass spectrometry is used as label-free protein quantification. However, combination of the DDA mode with exclusion list based DDA (DDA-EL) for the similar purpose has not yet been tested. Therefore, we have taken the initiative to check the protein abundance using DDA-EL and measured their suitability. METHODSTo check the protein abundance correlation between different samples, multiple replicates of mass spectrometric analysis of peptides were conducted primarily in DDA mode. Subsequently, peptides were analyzed in multiple replicates in DDA-EL mode with an exclusion mass list prepared from the previous DDA analyses. The normalized spectral abundance factor (NSAF) for each identified protein was compared among replicated datasets of single DDA, DDA-EL, merged two DDAs, and merged DDA+DDA-EL or between different types of datasets. RESULTSA strong and linear NSAF correlation with an average correlation coefficient of 0.939 was observed in the comparison between each pair of DDA data. Similar connotation was also monitored in the comparison among DDA-EL data (r =0.928) or among merged DDA+DDA-EL data (r =0.960) while a reduced correlation coefficient (r =0.892) with increased deviation was marked between DDA and DDA-EL data. CONCLUSIONSEvaluation of protein abundance patterns from different cellular states can successfully be conducted by DDA-EL-based mass spectrometric analysis. Therefore, the new workflow, DDA-EL merged to DDA mode, is a potential alternative to protein identification and quantification method. Copyright (c) 2014 John Wiley & Sons, Ltd.