Systematic evaluation of alternating CID and ETD fragmentation for phosphorylated peptides
ABSTRACT CID has become a routine method for fragmentation of peptides in shotgun proteomics, whereas electron transfer dissociation (ETD) has been described as a preferred method for peptides carrying labile PTMs. Though both of these fragmentation techniques have their obvious advantages, they also have their own drawbacks. By combining data from CID and ETD fragmentation, some of these disadvantages can potentially be overcome because of the complementarity of fragment ions produced. To evaluate alternating CID and ETD fragmentation, we analyzed a complex mixture of phosphopeptides on an LTQ-Orbitrap mass spectrometer. When the CID and ETD-derived spectra were searched separately, we observed 2504, 491, 2584, and 3249 phosphopeptide-spectrum matches from CID alone, ETD alone, decision tree-based CID/ETD, and alternating CID and ETD, respectively. Combining CID and ETD spectra prior to database searching should, intuitively, be superior to either method alone. However, when spectra from the alternating CID and ETD method were merged prior to database searching, we observed a reduction in the number of phosphopeptide-spectrum matches. The poorer identification rates observed after merging CID and ETD spectra are a reflection of a lack of optimized search algorithms for carrying out such searches and perhaps inherent weaknesses of this approach. Thus, although alternating CID and ETD experiments for phosphopeptide identification are desirable for increasing the confidence of identifications, merging spectra prior to database search has to be carefully evaluated further in the context of the various algorithms before adopting it as a routine strategy.
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ABSTRACT: Mass spectrometry has rapidly evolved to become the platform of choice for proteomic analysis. While CID remains the major fragmentation method for peptide sequencing, electron transfer dissociation (ETD) is emerging as a complementary method for the characterization of peptides and post-translational modifications (PTMs). Here, we review the evolution of ETD and some of its newer applications including characterization of PTMs, non-tryptic peptides and intact proteins. We will also discuss some of the unique features of ETD such as its complementarity with CID and the use of alternating CID/ETD along with issues pertaining to analysis of ETD data. The potential of ETD for applications such as multiple reaction monitoring and proteogenomics in the future will also be discussed.Proteomics 02/2012; 12(4-5):530-42. DOI:10.1002/pmic.201100517 · 3.97 Impact Factor
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ABSTRACT: O-linked N-acetylglucosamine (O-GlcNAc) is a reversible posttranslational modification of Ser and Thr residues on cytosolic and nuclear proteins of higher eukaryotes catalyzed by O-GlcNAc transferase (OGT). O-GlcNAc has recently been found on Notch1 extracellular domain catalyzed by EGF domain-specific OGT. Aberrant O-GlcNAc modification of brain proteins has been linked to Alzheimer's disease (AD). However, understanding specific functions of O-GlcNAcylation in AD has been impeded by the difficulty in characterization of O-GlcNAc sites on proteins. In this study, we modified a chemical/enzymatic photochemical cleavage approach for enriching O-GlcNAcylated peptides in samples containing ∼100 μg of tryptic peptides from mouse cerebrocortical brain tissue. A total of 274 O-GlcNAcylated proteins were identified. Of these, 168 were not previously known to be modified by O-GlcNAc. Overall, 458 O-GlcNAc sites in 195 proteins were identified. Many of the modified residues are either known phosphorylation sites or located proximal to known phosphorylation sites. These findings support the proposed regulatory cross-talk between O-GlcNAcylation and phosphorylation. This study produced the most comprehensive O-GlcNAc proteome of mammalian brain tissue with both protein identification and O-GlcNAc site assignment. Interestingly, we observed O-β-GlcNAc on EGF-like repeats in the extracellular domains of five membrane proteins, expanding the evidence for extracellular O-GlcNAcylation by the EGF domain-specific OGT. We also report a GlcNAc-β-1,3-Fuc-α-1-O-Thr modification on the EGF-like repeat of the versican core protein, a proposed substrate of Fringe β-1,3-N-acetylglucosaminyltransferases.Proceedings of the National Academy of Sciences 04/2012; 109(19):7280-5. DOI:10.1073/pnas.1200425109 · 9.81 Impact Factor
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ABSTRACT: The high-throughput nature of proteomics mass spectrometry is enabled by a productive combination of data acquisition protocols and the computational tools used to interpret the resulting spectra. One of the key components in mainstream protocols is the generation of tandem mass (MS/MS) spectra by peptide fragmentation using collision induced dissociation, the approach currently used in the large majority of proteomics experiments to routinely identify hundreds to thousands of proteins from single mass spectrometry runs. Complementary to these, alternative peptide fragmentation methods such as electron capture/transfer dissociation and higher-energy collision dissociation have consistently achieved significant improvements in the identification of certain classes of peptides, proteins, and post-translational modifications. Recognizing these advantages, mass spectrometry instruments now conveniently support fine-tuned methods that automatically alternate between peptide fragmentation modes for either different types of peptides or for acquisition of multiple MS/MS spectra from each peptide. But although these developments have the potential to substantially improve peptide identification, their routine application requires corresponding adjustments to the software tools and procedures used for automated downstream processing. This review discusses the computational implications of alternative and alternate modes of MS/MS peptide fragmentation and addresses some practical aspects of using such protocols for identification of peptides and post-translational modifications.Molecular & Cellular Proteomics 05/2012; 11(9):550-7. DOI:10.1074/mcp.R112.018556 · 7.25 Impact Factor