Abstract

LC-MALDI provides an often overlooked opportunity to exploit the separation between LC-MS and MS/MS stages of a 2D-LC-MS-based proteomics experiment, that is, by making a smarter selection for precursor fragmentation. Apex Peptide Elution Chain Selection (APECS) is a simple and powerful method for intensity-based peptide selection in a complex sample separated by 2D-LC, using a MALDI-TOF/TOF instrument. It removes the peptide redundancy present in the adjacent first-dimension (typically strong cation exchange, SCX) fractions by constructing peptide elution profiles that link the precursor ions of the same peptide across SCX fractions. Subsequently, the precursor ion most likely to fragment successfully in a given profile is selected for fragmentation analysis, selecting on precursor intensity and absence of adjacent ions that may cofragment. To make the method independent of experiment-specific tolerance criteria, we introduce the concept of the branching factor, which measures the likelihood of false clustering of precursor ions based on past experiments. By validation with a complex proteome sample of Arabidopsis thaliana, APECS identified an equivalent number of peptides as a conventional data-dependent acquisition method but with a 35% smaller work load. Consequently, reduced sample depletion allowed further selection of lower signal-to-noise ratio precursor ions, leading to a larger number of identified unique peptides.

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