Performance Characteristics of Electron Transfer Dissociation Mass Spectrometry

Abstract

We performed a large scale study of electron transfer dissociation (ETD) performance, as compared with ion trap collision-activated dissociation (CAD), for peptides ranging from approximately 1000 to 5000 Da (n approximately 4000). These data indicate relatively little overlap in peptide identifications between the two methods ( approximately 12%). ETD outperformed CAD for all charge states greater than 2; however, regardless of precursor charge a linear decrease in percent fragmentation, as a function of increasing precursor m/z, was observed with ETD fragmentation. We postulate that several precursor cation attributes, including peptide length, charge distribution, and total mass, could be relevant players. To examine these parameters unique ETD-identified peptides were sorted by length, and the ratio of amino acid residues per precursor charge (residues/charge) was calculated. We observed excellent correlation between the ratio of residues/charge and percent fragmentation. For peptides of a given residue/charge ratio, there is no correlation between peptide mass and percent fragmentation; instead we conclude that the ratio of residues/charge is the main factor in determining a successful ETD outcome. As charge density decreases so does the probability of non-covalent interactions that can bind a newly formed c/z-type ion pair. Recently we have described a supplemental activation approach (ETcaD) to convert these non-dissociative electron transfer product ions to useful c- and z-type ions. Automated implementation of such methods should remove this apparent precursor m/z ceiling. Finally, we evaluated the role of ion density (both anionic and cationic) and reaction duration for an ETD experiment. These data indicate that the best performance is achieved when the ion trap is filled to its space charge limit with anionic reagents. In this largest scale study of ETD to date, ETD continues to show great promise to propel the field of proteomics and, for small- to medium-sized peptides, is highly complementary to ion trap CAD.