Evaluation of HCD- and CID-type fragmentation within their respective detection platforms for murine phosphoproteomics.
ABSTRACT Protein phosphorylation modulates a myriad of biological functions, and its regulation is vital for proper cellular activity. Mass spectrometry is the enabling tool for phosphopeptide analysis, where recent instrumentation advances in both speed and sensitivity in linear ion trap and orbitrap technologies may yield more comprehensive phosphoproteomic analyses in less time. Protein phosphorylation analysis by MS relies on structural information derived through controlled peptide fragmentation. Compared with traditional, ion-trap-based collision-induced dissociation (CID), a more recent type of fragmentation termed HCD (higher energy collisional dissociation) provides beam type CID tandem MS with detection of fragment ions at high resolution in the orbitrap mass analyzer. Here we compared HCD to traditional CID for large-scale phosphorylation analyses of murine brain under three separate experimental conditions. These included a same-precursor analysis where CID and HCD scans were performed back-to-back, separate analyses of a phosphotyrosine peptide immunoprecipitation experiment, and separate whole phosphoproteome analyses. HCD generally provided higher search engine scores with more peptides identified, thus out-performing CID for back-to-back experiments for most metrics tested. However, for phosphotyrosine IPs and in a full phosphoproteome study of mouse brain, the greater acquisition speed of CID-only analyses provided larger data sets. We reconciled our results with those in direct contradiction from Nagaraj N, D'Souza RCJ et al. (J. Proteome Res. 9:6786, 2010). We conclude, for large-scale phosphoproteomics, CID fragmentation with rapid detection in the ion trap still produced substantially richer data sets, but the back-to-back experiments demonstrated the promise of HCD and orbitrap detection for the future.
- SourceAvailable from: Jean-Charles Sanchez[Show abstract] [Hide abstract]
ABSTRACT: The proposed protocol presents a comprehensive approach for large-scale qualitative and quantitative analysis of glycated proteins (GP) in complex biological samples including biological fluids and cell lysates such as plasma and red blood cells. The method, named glycation isotopic labeling (GIL), is based on the differential labeling of proteins with isotopic [(13)C6]-glucose, which supports quantitation of the resulting glycated peptides after enzymatic digestion with endoproteinase Glu-C. The key principle of the GIL approach is the detection of doublet signals for each glycated peptide in MS precursor scanning (glycated peptide with in vivo [(12)C6]- and in vitro [(13)C6]-glucose). The mass shift of the doublet signals is +6, +3 or +2 Da depending on the peptide charge state and the number of glycation sites. The intensity ratio between doublet signals generates quantitative information of glycated proteins that can be related to the glycemic state of the studied samples. Tandem mass spectrometry with high-energy collisional dissociation (HCD-MS2) and data-dependent methods with collision-induced dissociation (CID-MS3 neutral loss scan) are used for qualitative analysis.Journal of Proteome Research 01/2014; · 5.06 Impact Factor
- [Show abstract] [Hide abstract]
ABSTRACT: Alzheimer's disease (AD) is the most common form of dementia, characterized by progressive loss of cognitive function. One of the pathological hallmarks of AD is the formation of neurofibrillary tangles composed of abnormally hyperphosphorylated tau protein, but global deregulation of protein phosphorylation in AD is not well analyzed. Here we report a pilot investigation of AD phosphoproteome by titanium dioxide enrichment coupled with high resolution liquid chromatography-tandem mass spectrometry (LC-MS/MS). During the optimization of the enrichment method, we found that phosphate ion at a low concentration (e.g. 1 mM) worked efficiently as a non-phosphopeptide competitor to reduce background. The procedure was further tuned with respect to peptide-to-bead ratio, phosphopeptide recovery and purity. Using this refined method and 9 h LC-MS/MS, we analyzed phosphoproteome in one milligram of digested AD brain lysate, identifying 5243 phosphopeptides containing 3715 non-redundant phosphosites on 1455 proteins, including 31 phosphosites on the tau protein. This modified enrichment method is simple and highly efficient. The AD case study demonstrates its feasibility of dissecting phosphoproteome in a limited amount of postmortem human brain.This article is protected by copyright. All rights reservedProteomics 10/2014; · 4.43 Impact Factor
- [Show abstract] [Hide abstract]
ABSTRACT: Phosphorylation site assignment of high throughput tandem mass spectrometry (LC-MS/MS) data is one of the most common and critical aspects of phosphoproteomics. Correctly assigning phosphorylated residues helps us understand their biological significance. The design of common search algorithms (such as Sequest, Mascot etc.) do not incorporate site assignment; therefore additional algorithms are essential to assign phosphorylation sites for mass spectrometry data. The main contribution of this study is the design and implementation of a linear time and space dynamic programming strategy for phosphorylation site assignment referred to as PhosSA. The proposed algorithm uses summation of peak intensities associated with theoretical spectra as an objective function. Quality control of the assigned sites is achieved using a post-processing redundancy criteria that indicates the signal-to-noise ratio properties of the fragmented spectra. The quality assessment of the algorithm was determined using experimentally generated data sets using synthetic peptides for which phosphorylation sites were known. We report that PhosSA was able to achieve a high degree of accuracy and sensitivity with all the experimentally generated mass spectrometry data sets. The implemented algorithm is shown to be extremely fast and scalable with increasing number of spectra (we report up to 0.5 million spectra/hour on a moderate workstation). The algorithm is designed to accept results from both Sequest and Mascot search engines. An executable is freely available at http://helixweb.nih.gov/ESBL/PhosSA/ for academic research purposes.Proteome Science 11/2013; 11(Suppl 1):S14. · 2.42 Impact Factor