Effect of iTRAQ labeling on the relative abundance of peptide fragment ions produced by MALDI-MS/MS

Tejas Gandhi, Pranav Puri, Fabrizia Fusetti, Rainer Breitling, Bert Poolman, Hjalmar P. Permentier

    Research output: Contribution to journalArticlepeer-review


    The identification of proteins in proteomics experiments is usually based on mass information derived from tandem mass spectrometry data. To improve the performance of the identification algorithms, additional information available in the fragment peak intensity patterns has been shown to be useful. In this study, we consider the effect of iTRAQ labeling on the fragment peak intensity patterns of singly charged peptides from MALDI tandem MS data. The presence of an iTRAQ-modified basic group on the N-terminus leads to a more pronounced set of b-ion peaks and distinct changes in the abundance of specific peptide types. We performed a simple intensity prediction by using a decision-tree machine learning approach and were able to show that the relative ion abundance in a spectrum can be correctly predicted and distinguished from closely related sequences. This information will be useful for the development of improved method-specific intensity-based protein identification algorithms. © 2012 American Chemical Society.
    Original languageEnglish
    Pages (from-to)4044-4051
    Number of pages7
    JournalJournal of Proteome Research
    Issue number8
    Publication statusPublished - 3 Aug 2012


    • decision-tree learning
    • iTRAQ
    • peptide fragmentation


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