Evaluation of Several MS/MS Search Algorithms for Analysis of Spectra Derived from Electron Transfer Dissociation Experiments

McKusick-Nathans Institute for Genetic Medicine and Department of Biological Chemistry, Johns Hopkins University, Baltimore, Maryland 21205, USA.
Analytical Chemistry (Impact Factor: 5.64). 07/2009; 81(17):7170-80. DOI: 10.1021/ac9006107
Source: PubMed


Electron transfer dissociation (ETD) is increasingly becoming popular for high-throughput experiments especially in the identification of the labile post-translational modifications. Most search algorithms that are currently in use for querying MS/MS data against protein databases have been optimized on the basis of matching fragment ions derived from collision induced dissociation of peptides, which are dominated by b and y ions. However, electron transfer dissociation of peptides generates completely different types of fragments: c and z ions. The goal of our study was to test the ability of different search algorithms to handle data from this fragmentation method. We compared four MS/MS search algorithms (OMSSA, Mascot, Spectrum Mill, and X!Tandem) using approximately 170,000 spectra generated from a standard protein mix, as well as from complex proteomic samples which included a large number of phosphopeptides. Our analysis revealed (1) greater differences between algorithms than has been previously reported for CID data, (2) a significant charge state bias resulting in >60-fold difference in the numbers of matched doubly charged peptides, and (3) identification of 70% more peptides by the best performing algorithm than the algorithm identifying the least number of peptides. Our results indicate that the search engines for analyzing ETD derived MS/MS spectra are still in their early days and that multiple search engines could be used to reduce individual biases of algorithms.

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