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Improving the identification rate of endogenous peptides using electron transfer dissociation and collision-induced dissociation

Eisuke Hayakawa, Gerben Menschaert UGent, Pieter-Jan De Bock, Walter Luyten, Kris Gevaert UGent, Geert Baggerman and Liliane Schoofs (2013) JOURNAL OF PROTEOME RESEARCH. 12(12). p.5410-5421
abstract
Tandem mass spectrometry (MS/MS) combined with bioinformatics tools have enabled fast and systematic protein identification based on peptide-to-spectrum matches. However, it remains challenging to obtain accurate identification of endogenous peptides, such as neuropeptides, peptide hormones, peptide pheromones, venom peptides, and antimicrobial peptides. Since these peptides are processed at sites that are difficult to predict reliably, the search of their MS/MS spectra in sequence databases needs to be done without any protease setting. In addition, many endogenous peptides carry various post-translational modifications, making it essential to take these into account in the database search. These characteristics of endogenous peptides result in a huge search space, frequently leading to poor confidence of the peptide characterizations in peptidomics studies. We have developed a new MS/MS spectrum search tool for highly accurate and confident identification of endogenous peptides by combining two different fragmentation methods. Our approach takes advantage of the combination of two independent fragmentation methods (collision-induced dissociation and electron transfer dissociation). Their peptide spectral matching is carried out separately in both methods, and the final score is built as a combination of the two separate scores. We demonstrate that this approach is very effective in discriminating correct peptide identifications from false hits. We applied this approach to a spectral data set of neuropeptides extracted from mouse pituitary tumor cells. Compared to conventional MS-based identification, i.e., using a single fragmentation method, our approach significantly increased the peptide identification rate. It proved also highly effective for scanning spectra against a very large search space, enabling more accurate genome-wide searches and searches including multiple potential post-translational modifications.
Please use this url to cite or link to this publication:
author
organization
year
type
journalArticle (original)
publication status
published
subject
keyword
neuropeptide, endogenous peptide, peptidomics, neuropeptidomics, peptidogenomics, peptide identification, bioinformatics, tandem mass spectrometry, electron transfer dissociation, TANDEM MASS-SPECTROMETRY, STATISTICAL SIGNIFICANCE, PROTEIN IDENTIFICATION, DATABASE SEARCH, PEPTIDOMICS, FRAGMENTATION, ETD, NEUROPEPTIDES, SPECTRA, HCD
journal title
JOURNAL OF PROTEOME RESEARCH
J. Proteome Res.
volume
12
issue
12
pages
5410 - 5421
Web of Science type
Article
Web of Science id
000328231300006
JCR category
BIOCHEMICAL RESEARCH METHODS
JCR impact factor
5.001 (2013)
JCR rank
9/78 (2013)
JCR quartile
1 (2013)
ISSN
1535-3893
DOI
10.1021/pr400446z
language
English
UGent publication?
yes
classification
A1
copyright statement
I have transferred the copyright for this publication to the publisher
id
4186273
handle
http://hdl.handle.net/1854/LU-4186273
date created
2013-11-19 11:24:07
date last changed
2016-12-19 15:44:51
@article{4186273,
  abstract     = {Tandem mass spectrometry (MS/MS) combined with bioinformatics tools have enabled fast and systematic protein identification based on peptide-to-spectrum matches. However, it remains challenging to obtain accurate identification of endogenous peptides, such as neuropeptides, peptide hormones, peptide pheromones, venom peptides, and antimicrobial peptides. Since these peptides are processed at sites that are difficult to predict reliably, the search of their MS/MS spectra in sequence databases needs to be done without any protease setting. In addition, many endogenous peptides carry various post-translational modifications, making it essential to take these into account in the database search. These characteristics of endogenous peptides result in a huge search space, frequently leading to poor confidence of the peptide characterizations in peptidomics studies. We have developed a new MS/MS spectrum search tool for highly accurate and confident identification of endogenous peptides by combining two different fragmentation methods. Our approach takes advantage of the combination of two independent fragmentation methods (collision-induced dissociation and electron transfer dissociation). Their peptide spectral matching is carried out separately in both methods, and the final score is built as a combination of the two separate scores. We demonstrate that this approach is very effective in discriminating correct peptide identifications from false hits. We applied this approach to a spectral data set of neuropeptides extracted from mouse pituitary tumor cells. Compared to conventional MS-based identification, i.e., using a single fragmentation method, our approach significantly increased the peptide identification rate. It proved also highly effective for scanning spectra against a very large search space, enabling more accurate genome-wide searches and searches including multiple potential post-translational modifications.},
  author       = {Hayakawa, Eisuke and Menschaert, Gerben and De Bock, Pieter-Jan and Luyten, Walter and Gevaert, Kris and Baggerman, Geert and Schoofs, Liliane},
  issn         = {1535-3893},
  journal      = {JOURNAL OF PROTEOME RESEARCH},
  keyword      = {neuropeptide,endogenous peptide,peptidomics,neuropeptidomics,peptidogenomics,peptide identification,bioinformatics,tandem mass spectrometry,electron transfer dissociation,TANDEM MASS-SPECTROMETRY,STATISTICAL SIGNIFICANCE,PROTEIN IDENTIFICATION,DATABASE SEARCH,PEPTIDOMICS,FRAGMENTATION,ETD,NEUROPEPTIDES,SPECTRA,HCD},
  language     = {eng},
  number       = {12},
  pages        = {5410--5421},
  title        = {Improving the identification rate of endogenous peptides using electron transfer dissociation and collision-induced dissociation},
  url          = {http://dx.doi.org/10.1021/pr400446z},
  volume       = {12},
  year         = {2013},
}

Chicago
Hayakawa, Eisuke, Gerben Menschaert, Pieter-Jan De Bock, Walter Luyten, Kris Gevaert, Geert Baggerman, and Liliane Schoofs. 2013. “Improving the Identification Rate of Endogenous Peptides Using Electron Transfer Dissociation and Collision-induced Dissociation.” Journal of Proteome Research 12 (12): 5410–5421.
APA
Hayakawa, E., Menschaert, G., De Bock, P.-J., Luyten, W., Gevaert, K., Baggerman, G., & Schoofs, L. (2013). Improving the identification rate of endogenous peptides using electron transfer dissociation and collision-induced dissociation. JOURNAL OF PROTEOME RESEARCH, 12(12), 5410–5421.
Vancouver
1.
Hayakawa E, Menschaert G, De Bock P-J, Luyten W, Gevaert K, Baggerman G, et al. Improving the identification rate of endogenous peptides using electron transfer dissociation and collision-induced dissociation. JOURNAL OF PROTEOME RESEARCH. 2013;12(12):5410–21.
MLA
Hayakawa, Eisuke, Gerben Menschaert, Pieter-Jan De Bock, et al. “Improving the Identification Rate of Endogenous Peptides Using Electron Transfer Dissociation and Collision-induced Dissociation.” JOURNAL OF PROTEOME RESEARCH 12.12 (2013): 5410–5421. Print.