Analytical utility of mass spectral binning in proteomic experiments by SPectral Immonium Ion Detection (SPIID)
Research output: Contribution to journal › Journal article › Research › peer-review
Unambiguous identification of tandem mass spectra is a cornerstone in mass spectrometry (MS)-based proteomics. As the study of post-translational modifications (PTMs) by shotgun proteomics progresses in depth and coverage, the ability to correctly identify PTM-bearing peptides is essential, increasing the demand for advanced data interpretation. Several PTMs are known to generate unique fragment ions during tandem mass spectrometry (MS/MS), the so-called diagnostic ions, which unequivocally identifies that a given mass spectrum relates to a specific PTM. Although such ions hold tremendous analytical advantages, algorithms to decipher MS/MS spectra for the presence of diagnostic ions in an unbiased manner are currently lacking. Here, we present a systematic spectral pattern-based approach for the discovery of diagnostic ions, and new fragmentation mechanisms in shotgun proteomics datasets. The developed software tool is designed to analyze large sets of high resolution peptide fragmentation spectra independent of the fragmentation method, instrument type or protease employed. To benchmark the software tool we have analyzed large HCD datasets of phosphorylation, ubiquitylation, SUMOylation, formylation and lysine acetylation containing samples. Using the developed software tool we are able to identify known diagnostic ions by comparing histograms of modified and unmodified peptide spectra. Since the investigated tandem mass spectra data are acquired with high mass accuracy, unambiguous interpretation and determination of the chemical composition for the majority of detected fragment ions is feasible. Collectively we present a freely available software tool that allows for comprehensive and automatic analysis of analogous product ions in tandem mass spectra, and systematic mapping of fragmentation mechanisms related to common amino acids.
|Journal||Molecular & Cellular Proteomics|
|Number of pages||11|
|Publication status||Published - 3 Jun 2014|