Abstract
Peptide identification using tandem mass spectrometry is a core technology in proteomics. Latest generations of mass spectrometry instruments enable the use of electron transfer dissociation (ETD) to complement collision induced dissociation (CID) for peptide fragmentation. However, a critical limitation to the use of ETD has been optimal database search software. Percolator is a post-search algorithm, which uses semi-supervised machine learning to improve the rate of peptide spectrum identifications (PSMs) together with providing reliable significance measures. We have previously interfaced the Mascot search engine with Percolator and demonstrated sensitivity and specificity benefits with CID data. Here, we report recent developments in the Mascot Percolator V2.0 software including an improved feature calculator and support for a wider range of ion series. The updated software is applied to the analysis of several CID and ETD fragmented peptide data sets. This version of Mascot Percolator increases the number of CID PSMs by up to 80% and ETD PSMs by up to 60% at a 0.01 q-value (1% false discovery rate) threshold over a standard Mascot search, notably recovering PSMs from high charge state precursor ions. The greatly increased number of PSMs and peptide coverage afforded by Mascot Percolator has enabled a fuller assessment of CID/ETD complementarity to be performed. Using a data set of CID and ETcaD spectral pairs, we find that at a 1% false discovery rate, the overlap in peptide identifications by CID and ETD is 83%, which is significantly higher than that obtained using either stand-alone Mascot (69%) or OMSSA (39%). We conclude that Mascot Percolator is a highly sensitive and accurate post-search algorithm for peptide identification and allows direct comparison of peptide identifications using multiple alternative fragmentation techniques.
Highlights
There are several factors to consider when interpreting electron transfer dissociation (ETD) fragmented data
It is worth noting that in this study we examine the numbers of unique peptide and protein identifications made by Mascot Percolator, and that as we move from peptide spectrum matches (PSMs) to peptides and to proteins the size of the data set changes and so does the FDR [29]
The numbers of triply charged PSMs significantly identified by Mascot Percolator is consistent to the numbers of doubly charged PSMs for both fragmentation methods; noticeably here collision induced dissociation (CID) fragmentation generates more PSMs with better posterior error probabilities (PEPs) compared with other methods
Summary
Enhanced Peptide Identification by Electron Transfer Dissociation Using an Improved Mascot Percolator*□S. The updated software is applied to the analysis of several CID and ETD fragmented peptide data sets This version of Mascot Percolator increases the number of CID PSMs by up to 80% and ETD PSMs by up to 60% at a 0.01 q-value (1% false discovery rate) threshold over a standard Mascot search, notably recovering PSMs from high charge state precursor ions. There has recently been a significant rise in the number of proteomics studies using electron transfer dissociation (ETD) fragmentation and electron capture dissociation (ECD) (1, 4 – 6) These alternative fragmentation techniques can be advantageous for the identification and localization of labile modifications such as phosphorylation [7,8,9,10,11,12], as well as sampling peptides that are not readily identified through CID fragmentation [5].
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