A Fragmentation Event Model for Peptide Identification by Mass Spectrometry

Author(s):  
Yu Lin ◽  
Yantao Qiao ◽  
Shiwei Sun ◽  
Chungong Yu ◽  
Gongjin Dong ◽  
...  
2018 ◽  
Vol 2018 ◽  
pp. 1-11 ◽  
Author(s):  
Zhiwu An ◽  
Qingbo Shu ◽  
Hao Lv ◽  
Lian Shu ◽  
Jifeng Wang ◽  
...  

Confident characterization of intact glycopeptides is a challenging task in mass spectrometry-based glycoproteomics due to microheterogeneity of glycosylation, complexity of glycans, and insufficient fragmentation of peptide bones. Open mass spectral library search is a promising computational approach to peptide identification, but its potential in the identification of glycopeptides has not been fully explored. Here we present pMatchGlyco, a new spectral library search tool for intact N-linked glycopeptide identification using high-energy collisional dissociation (HCD) tandem mass spectrometry (MS/MS) data. In pMatchGlyco, (1) MS/MS spectra of deglycopeptides are used to create spectral library, (2) MS/MS spectra of glycopeptides are matched to the spectra in library in an open (precursor tolerant) manner and the glycans are inferred, and (3) a false discovery rate is estimated for top-scored matches above a threshold. The efficiency and reliability of pMatchGlyco were demonstrated on a data set of mixture sample of six standard glycoproteins and a complex glycoprotein data set generated from human cancer cell line OVCAR3.


2012 ◽  
Vol 9 (5) ◽  
pp. 1273-1280 ◽  
Author(s):  
Pengyi Yang ◽  
Jie Ma ◽  
Penghao Wang ◽  
Yunping Zhu ◽  
Bing B. Zhou ◽  
...  

Blood ◽  
2011 ◽  
Vol 118 (21) ◽  
pp. 2890-2890
Author(s):  
Attaya Suvannasankha ◽  
Colin D. Crean ◽  
Heather M. Sahm ◽  
Rafat Abonour ◽  
Sherif Farag ◽  
...  

Abstract Abstract 2890 Background: Multiple myeloma is an incurable and fatal hematologic malignancy. Recent gene microarray studies showed distinct gene expression profiles defining MM subgroups and their association with cytogenetic abnormalities and treatment outcome. However, aside from transcriptional control, a variety of post-transcriptional/post-translational modifications likely play an important role in regulating protein expression and function, and ultimately may prove informative for predicting tumor behavior. Objectives: We hypothesize that the protein profile in MM cells is different than normal plasma cells. Methodology: Normal plasma cells and myeloma cells were isolated using CD138 immune magnetic beads from bone marrow aspirates from healthy volunteers or patients with newly diagnosed MM, respectively. CD138+ cells were frozen and subsequently analyzed in one batch. Proteins were digested by trypsin. Tryptic peptides were injected onto an HPLC system and analyzed on a Thermo-Fisher LTQ mass spectrometer. Peptide identification and quantification were carried out using proprietary algorithms. Identified proteins were categorized into priority groups based on the quality of the peptide identification by tandem mass spectrometry. Proteins with significant changes in expression level were further analyzed by bioinformatics tools for the determination of the biological significance. Results: In the discovery phase of this study, 433 proteins were identified and their expression levels were quantitatively compared. 169 of these proteins demonstrated a significant difference between normal plasma cells and MM cells. Among the significantly changed proteins, 18 were identified and quantified with high confidence, and were therefore chosen for further validation. The identified proteins are known to be involved in the glycolysis/gluconeogenesis pathway, the oxidative phosphorylation pathway, cysteine metabolism and the pentose phosphate pathway. None of these proteins are known to be of prognostic value or being currently targeted for therapy in MM. A high-throughput LC/MS-based multiple-reaction-monitoring (MRM) assay for quantitative validation of these candidates with clinical samples is ongoing. To date, using the MRM assay, we were able to detect MRM peptides for 13 of the 18 targeted proteins in clinical samples. The quantification of these peptides will be further confirmed using a separate set of clinical samples. Conclusion: Significant differences in protein expression were observed between MM and normal plasma cells. The study presents an important step toward using proteomics as a tool to develop diagnostic and/or prognostic biomarkers in the clinical setting. However, both follow-up analytical and clinical validations are required before they can serve as disease-specific biomarkers. Disclosures: Abonour: Celgene: Membership on an entity's Board of Directors or advisory committees.


PROTEOMICS ◽  
2004 ◽  
Vol 4 (4) ◽  
pp. 961-969 ◽  
Author(s):  
Jane Razumovskaya ◽  
Victor Olman ◽  
Dong Xu ◽  
Edward C. Uberbacher ◽  
Nathan C. VerBerkmoes ◽  
...  

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