In-depth analysis of tandem mass spectrometry data from disparate instrument types

Abstract

Mass spectrometric analyses of protein digests produce large numbers of fragmentation spectra that are not identified by routine database searching strategies. Some of these spectra could be identified by development of improved search engines. However, many of these spectra represent fragmentation of peptide components bearing modifications that are not routinely considered in database searches. Here we present new software within Protein Prospector that allows comprehensive analysis of data sets by analyzing the data at increasing levels of depth. Analysis of published data sets is presented to illustrate that the software is not biased to any instrument types. The results show that these data sets contain many modified peptides. As well as searching for known modification types, Protein Prospector permits the detection and identification of unexpected or novel modifications by searching for any mass shift within a user-specified mass range to any chosen amino acid(s). Several modifications never previously reported in proteomics data were identified in these standard data sets using this mass modification searching approach.

Fig. 1.

Receiver-operating characteristic curves for Protein Prospector (PP) searches of the different instrument data. The predicted number of incorrect answers is derived by doubling the number of matches to the decoy part of the database in the concatenated database search. The data points for the Sequest results are derived from the average number of peptides reported in the publication for each instrument with the number of predicted incorrect results indicated assuming a 2.5% FDR as reported in the publication.

Fig. 2.

Venn diagram showing the levels of overlap between Protein Prospector (PP) and Inspect results, both without any confidence level threshold and while applying thresholds of E-value < 0. 1 and p < 0.1.

Fig. 3.

Duplication of peak lists for different charge states causes false positive identifications of the wrong charge state peak list to homologous peptides to the correct answer. Both of the matches presented are derived from the same mass spectrum. The match in a is assuming a 2+ precursor charge state; the match in b is assuming a 3+ precursor charge state.

Fig. 4.

Different charge state assignments to the same precursor can also lead to false positive matches in searches with defined variable mass modifications. a and b show the matches to 2+ and 3+ precursor charge state peak lists of the spectrum that was acquired at 34.1304 min.

Fig. 5.

Histogram of mass modifications reported by Protein Prospector when analyzing the QSTAR standard data set.

Fig. 6.

Identification of the peak list 1975. A precursor of m/z 854.931 was fragmented, and Protein Prospector reported a confident assignment to the peptide VPTPNVSVVDLTCR with a modification of +209 Da on the cysteine residue (a). Inspect reported a match to a homologous peptide, VPTPDVSVVDTVKLAK, with a modification of a loss of 71 Da from the C-terminal lysine (b). Plots in the top right corners of each panel show mass errors for fragment ion assignments. The intensity of the precursor ion in these figures has been artificially reduced to allow easier visualization of the fragment ions.

Fig. 7.

Identification of the peak list 2465 to the peptide VLDALDSIK with a mass modification of +26 Da on the peptide N terminus. This modification corresponds to an acetaldehyde Schiff base modification to the N-terminal amine group.

Fig. 8.

Identification of peak list 1480 as VVDLMVHMASK with a modification of 41 Da somewhere on the peptide that is subsequently lost as a neutral group and therefore is not present on any of the fragment ions. The plot in the top right corner shows the mass errors for fragment ion assignments.