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Comparison of MS(2)-only, MSA, and MS(2)/MS(3) methodologies for phosphopeptide identification - PubMed

Comparison of MS(2)-only, MSA, and MS(2)/MS(3) methodologies for phosphopeptide identification

Peter J Ulintz et al. J Proteome Res. 2009 Feb.

Abstract

Current mass spectrometers provide a number of alternative methodologies for producing tandem mass spectra specifically for phosphopeptide analysis. In particular, generation of MS(3) spectra in a data-dependent manner upon detection of the neutral loss of a phosphoric acid in MS(2) spectra is a popular technique for circumventing the problem of poor phosphopeptide backbone fragmentation. The newer Multistage Activation method provides another option. Both these strategies require additional cycle time on the instrument and therefore reduce the number of spectra that can be measured in the same amount of time. Additional informatics is often required to make most efficient use of the additional information provided by these spectra as well. This work presents a comparison of several commonly used mass spectrometry methods for the study of phosphopeptide-enriched samples: an MS(2)-only method, a Multistage Activation method, and an MS(2)/MS(3) data-dependent neutral loss method. Several strategies for dealing effectively with the resulting MS(3) data in the latter approach are also presented and compared. The overall goal is to infer whether any one methodology performs significantly better than another for identifying phosphopeptides. On data presented here, the Multistage Activation methodology is demonstrated to perform optimally and does not result in significant loss of unique peptide identifications.

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Figures

Figure 1
Figure 1. MS3 precursor mass replacement

A toy fragmentation model of the theoretical phosphopeptide MLLS[+80]LK ([M+H]+ = 784 Da). Only y-ions are shown for clarity. Calculated peaks are +1 charge, and peak intensity is arbitrary. a) Precursor spectrum (MS1). b) MS2 spectrum, with a dominant neutral loss peak in red. c) MS3 spectrum corresponding to the fragmentation of the 686 Da neutral loss peak. Database search with the MS3 precursor mass, −18 Da shift on S as a variable modification. Observed peaks are labeled as y ions. d) MS3 spectrum, database search with precursor mass replacement (MS2 precursor mass), +80 Da shift on S residue as a variable modification. Peaks corresponding to fragment ions containing S residue are labeled as y-p ions: y3-p, y4-p, and y5-p (p: − 98 Da neutral loss).

Figure 2
Figure 2. Direct comparison of MS methodology on phosphopeptide WIpSKDDYTWEK

a)Full-scan MS2 spectrum indicating predominant neutral loss precursor ion. Lower abundant sequence ions are identified as annotated. b) Full-scan MS3 spectrum obtained in a neutral loss triple stage methodology showing a two order of magnitude loss of intensity. Annotated are sequence ions that may or may not have been obtained in the MS2 spectra. c) Full-scan MSA spectrum showing only a 35% loss of intensity compared with the MS2 spectra, but showing an increased number of sequence ions vs. both MS2 and MS3 spectra. Fragment ions observed in MS3 and MSA spectra are labeled with respect to the precursor ion selected for MS2 fragmentation.

Figure 2
Figure 2. Direct comparison of MS methodology on phosphopeptide WIpSKDDYTWEK

a)Full-scan MS2 spectrum indicating predominant neutral loss precursor ion. Lower abundant sequence ions are identified as annotated. b) Full-scan MS3 spectrum obtained in a neutral loss triple stage methodology showing a two order of magnitude loss of intensity. Annotated are sequence ions that may or may not have been obtained in the MS2 spectra. c) Full-scan MSA spectrum showing only a 35% loss of intensity compared with the MS2 spectra, but showing an increased number of sequence ions vs. both MS2 and MS3 spectra. Fragment ions observed in MS3 and MSA spectra are labeled with respect to the precursor ion selected for MS2 fragmentation.

Figure 2
Figure 2. Direct comparison of MS methodology on phosphopeptide WIpSKDDYTWEK

a)Full-scan MS2 spectrum indicating predominant neutral loss precursor ion. Lower abundant sequence ions are identified as annotated. b) Full-scan MS3 spectrum obtained in a neutral loss triple stage methodology showing a two order of magnitude loss of intensity. Annotated are sequence ions that may or may not have been obtained in the MS2 spectra. c) Full-scan MSA spectrum showing only a 35% loss of intensity compared with the MS2 spectra, but showing an increased number of sequence ions vs. both MS2 and MS3 spectra. Fragment ions observed in MS3 and MSA spectra are labeled with respect to the precursor ion selected for MS2 fragmentation.

Figure 3
Figure 3. Number of unique peptide identified in each yeast dataset

The instrument method is indicated in the dataset name: MS2-only (MS2), MSA, or the MS2/MS3 (MS2+3) methodology. Peptide identifications are filtered to achieve a 0.05 FDR.

Figure 4
Figure 4. Comparison of MS2/MS3 data processing methodologies

Data are shown for the two replicate runs for which MS3 spectra were generated (run IDs 10192 and 10193). Results from two alternative refinements, the combined 1-(1-PMS2)(1-PMS3) probability score (“MS2+3comb”), and summation spectra (labeled “MS2+3sum”), are compared with the results obtained by straightforward combination of MS2 and MS3-database search results.

Figure 5
Figure 5. Comparison of replicate experiments using the MSA method

Area-proportional Venn diagrams of the three replicates of the yeast sample are shown for both the peptide (a) and protein (b) levels. Proteins represent protein group with probability scores calculated by ProteinProphet and passing a 0.02 FDR threshold. Peptide identifications are included for all selected proteins if the peptide NSP-adjusted probability scores are equal or greater than 0.5.

Figure 6
Figure 6. Comparison of protein and peptide identifications for combined datasets

Venn diagrams of the three primary run methodologies are compared for combined yeast (Panels a and b, top) and drosophila (Panels c and d, bottom) samples. The figures compare unique peptide assignments (left panel) and protein identifications (right panel). Total counts for all areas corresponding to each dataset are shown in parentheses. Proteins are selected based on an estimated FDR of 0.05. Peptides are included for all significant proteins if their NSP adjusted probability scores are equal or greater than 0.5. Venn diagrams are not area-proportional.

Figure 7
Figure 7. Localization score histograms for individual run methods

Data shown are for yeast. Each bin value represents the total percent of all peptide identifications in that bin range for the corresponding method. The distributions are calculated using only unique phosphopeptides identified by all three methodologies.

Figure 8
Figure 8. Mass accuracy of fragment ion assignments from MS2 and MSA methodologies

Results for individual peptides are sorted on the horizontal axis by increasing peptide length. The vertical axis shows the RMS mass error in ppm of theoretical fragment ion matches to the experimental spectra produced by MS2 (blue) and MSA (red) spectra. Linear regression curves are fit to the data for each method, shown as dashed lines.

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References

    1. Hunter T. Signaling--2000 and beyond. Cell. 2000;100:113–27. - PubMed
    1. Cohen P. The regulation of protein function by multisite phosphorylation– a 25 year update. Trends Biochem Sci. 2000;25:596–601. - PubMed
    1. Manning G, Whyte DB, Martinez R, Hunter T, Sudarsanam S. The protein kinase complement of the human genome. Science. 2002;298:1912–34. - PubMed
    1. Caenepeel S, Charydczak G, Sudarsanam S, Hunter T, Manning G. The mouse kinome: discovery and comparative genomics of all mouse protein kinases. Proc Natl Acad Sci U S A. 2004;101:11707–12. - PMC - PubMed
    1. Kersten B, Agrawal GK, Iwahashi H, Rakwal R. Plant phosphoproteomics: a long road ahead. Proteomics. 2006;6:5517–28. - PubMed

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