Comprehensive comparison of collision induced dissociation and electron transfer dissociation

Abstract

Electron transfer dissociation (ETD) is a recently introduced mass spectrometric technique which has proven to be an excellent tool for the elucidation of labile post-translational modifications such as phosphorylation and O-GlcNAcylation of serine and threonine residues. However, unlike collision induced dissociation (CID), which has been studied for decades, the intricacies of ETD-based fragmentation have not yet been firmly established or systematically addressed. In this analysis, we have systematically compared the CID and ETD fragmentation patterns for the large majority of the peptides that do not contain such labile modifications. Using a standard 48 protein mix, we were able to measure false-positive rates for the experiments and also assess a large number of peptides for a detailed comparison of CID and ETD fragmentation pattern. Analysis of approximately 19,000 peptides derived from both standard proteins and complex protein samples revealed that (i) CID identified 50% more peptides than ETD; (ii) ETD resulted in approximately 20% increase in amino acid sequence coverage over CID; and (iii) combining CID and ETD fragmentation increased the sequence coverage for an average tryptic peptide to 92%. Interestingly, our analysis revealed that nearly 60% of all ETD-identified peptides carried two positive charges, which is in sharp contrast to what has been generally accepted. We also present a novel strategy for automatic validation of peptide assignments based on identification of a peptide by consecutive CID and ETD fragmentation in an alternating mode.

Figure 1

Analysis of extracted standard peptides fragmented by CID and ETD. Extraction was performed without any validation. Spectra that could be matched to the standard proteins (Universal Proteomics Standard, UPS1) were analyzed with respect to charge state distribution (A and B). These data were also analyzed with respect to (C) score; (D) score difference between a normal search and a reverse search; (E) score difference between best match and second best match, and (F) the percent of assigned fragmentation signal − scored peak intensity. In the plots, ETD distributions are shown in blue and CID distributions in orange. Distributions for doubly charge peptides are marked in a bold full line where distributions for triply charged peptides are truncated.

Figure 2

Analysis of a large alternating CID/ETD data set. The CID data were validated using default Spectrum Mill validation criteria whereas the ETD data were validated using a threshold specific for ETD. (A) Peptide length distribution of CID and ETD identified peptides, (B) the distribution of percent sequence coverage for CID and ETD identified peptides. ETD distribution is marked in blue, CID in orange. (C and D) Charge state distributions for CID (C) and ETD (D) identified peptides. (E and F) Scatter plots of sequence coverage for CID (E) and ETD (F) identified peptides as a function for mass-to-charge ratio. Color code: red, 2+ peptides; violet, 3+ peptides; and yellow, 4+ peptides.

Figure 3

A schematic of the proposed and tested conditional consecutive CID/ETD validation. (A) The most stringent type of validation is to require that both CID and ETD matches the same peptide as the best match, (B) validation where at least one of the fragmentation methods has identified the peptide as being the best match. (C) The requirement for the least stringent validation is that a peptide is matched by both CID and ETD spectra irrespectively of ranking.

Figure 4

Venn diagram illustrating the overlap of unique peptide ions identified and validated in an alternating CID/ETD experiment. Orange area corresponds to Spectrum Mill validated peptides identified by CID where blue is the corresponding ETD peptides. Red area is peptides ions validated by conditional consecutive CID/ETD validation. In the diagram, the area encompassed by a bold Lare peptides that have been validated by the Spectrum Mill validation and conditional consecutive CID/ETD validation. False positive rates were calculated using the standard (UPS1) peptides contained in the data sets.

Figure 5

Four representative peptides identified by both CID (top panels) and ETD (lower panels) in an alternating CID/ETD experiment. Each set of spectra are recorded of the same precursor ion. The inserts in each figure (A−D) show the amino acid sequence coverage obtained from the CID experiments and the ETD experiments. The sequence maps marked [Comb.] are the combined CID/ETD sequence map. In all the four examples, the amino acid sequence coverage increases when combining the CID and ETD experiments. Only selected fragment ions are marked. Legends for the peptide sequence maps: (\) C-terminal fragment ion, (/) N-terminal fragment ion, and (|) both C- and N-terminal fragment ions.

Figure 6

Histogram showing the distribution of peptide length of CID (orange) and ETD (blue) matched peptides. Only peptides for which the sequence coverage differed by 20% or more in-between the two fragmentation techniques are counted. The pie chart inserts show the charge state distribution of these two sets of peptides.

Figure 7

Heatmap showing averaged ETD over CID intensity ratios. Green indicates favorable ETD fragmentation over CID, while red indicates a favorable CID over ETD fragmentation. Black indicates differences of less than 2-fold. The heatmap is generated from the spectra of all the >9 000 peptides identified by consecutive CID/ETD. “m” indicates oxidized methionine. All cysteines, C, are alkylated. Similar diagrams, but divided into charge states (2+ and 3+) are shown in Supporting Information Figure 1.