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Spectral clustering in peptidomics studies allows homology searching and modification profiling: HomClus, a versatile tool

Gerben Menschaert UGent, Eisuke Hayakawa, Liliane Schoofs, Wim Van Criekinge UGent and Geert Baggerman (2012) JOURNAL OF PROTEOME RESEARCH. 11(5). p.2774-2785
abstract
Many genomes of nonmodel organisms are yet to be annotated. Peptidomics research on those organisms therefore cannot adopt the commonly used database-driven identification strategy, leaving the more difficult de novo sequencing approach as the only alternative. The reported tool uses the growing resources of publicly or in-house available fragmentation spectra and sequences of (model) organisms to elucidate the identity of peptides of experimental spectra of nonannotated species. Clustering algorithms are implemented to infer the identity of unknown peak lists based on their publicly or in-house available counterparts. The reported tool, which we call the HomClus-tool, can cope with post-translational modifications and amino acid substitutions. We applied this tool on two locusts (Schistocerca gregaria and Locusta migratoria) LC-MALDI-TOF/TOF datasets. Compared to a Mascot database search (using the available UniProt-KB proteins of these species), we were able to double the amount of peptide identifications for both spectral sets. Known bioactive peptides from Drosophila melanogaster (i.e., fragmentations spectra generated in silico thereof) were used as a starting point for clustering, trying to reveal their experimental homologues' counterparts.
Please use this url to cite or link to this publication:
author
organization
year
type
journalArticle (original)
publication status
published
subject
keyword
bioactive peptides, peptidomics, Locusta migratoria, Schistocerca gregaria, spectral clustering, PTMs, post-translational modification, homology searching, TANDEM MASS-SPECTROMETRY, ENDOGENOUS PEPTIDES, PROTEIN IDENTIFICATION, DATABASE, NEUROPEPTIDE, SYSTEM, RESOURCE, LIBRARY, LOCUSTS, GENOME
journal title
JOURNAL OF PROTEOME RESEARCH
J. Proteome Res.
volume
11
issue
5
pages
2774 - 2785
Web of Science type
Article
Web of Science id
000303492100012
JCR category
BIOCHEMICAL RESEARCH METHODS
JCR impact factor
5.056 (2012)
JCR rank
10/74 (2012)
JCR quartile
1 (2012)
ISSN
1535-3893
DOI
10.1021/pr201114m
language
English
UGent publication?
yes
classification
A1
copyright statement
I have transferred the copyright for this publication to the publisher
id
2096969
handle
http://hdl.handle.net/1854/LU-2096969
date created
2012-05-02 11:47:51
date last changed
2012-09-28 13:00:35
@article{2096969,
  abstract     = {Many genomes of nonmodel organisms are yet to be annotated. Peptidomics research on those organisms therefore cannot adopt the commonly used database-driven identification strategy, leaving the more difficult de novo sequencing approach as the only alternative. The reported tool uses the growing resources of publicly or in-house available fragmentation spectra and sequences of (model) organisms to elucidate the identity of peptides of experimental spectra of nonannotated species. Clustering algorithms are implemented to infer the identity of unknown peak lists based on their publicly or in-house available counterparts. The reported tool, which we call the HomClus-tool, can cope with post-translational modifications and amino acid substitutions. We applied this tool on two locusts (Schistocerca gregaria and Locusta migratoria) LC-MALDI-TOF/TOF datasets. Compared to a Mascot database search (using the available UniProt-KB proteins of these species), we were able to double the amount of peptide identifications for both spectral sets. Known bioactive peptides from Drosophila melanogaster (i.e., fragmentations spectra generated in silico thereof) were used as a starting point for clustering, trying to reveal their experimental homologues' counterparts.},
  author       = {Menschaert, Gerben and Hayakawa, Eisuke and Schoofs, Liliane and Van Criekinge, Wim and Baggerman, Geert},
  issn         = {1535-3893},
  journal      = {JOURNAL OF PROTEOME RESEARCH},
  keyword      = {bioactive peptides,peptidomics,Locusta migratoria,Schistocerca gregaria,spectral clustering,PTMs,post-translational modification,homology searching,TANDEM MASS-SPECTROMETRY,ENDOGENOUS PEPTIDES,PROTEIN IDENTIFICATION,DATABASE,NEUROPEPTIDE,SYSTEM,RESOURCE,LIBRARY,LOCUSTS,GENOME},
  language     = {eng},
  number       = {5},
  pages        = {2774--2785},
  title        = {Spectral clustering in peptidomics studies allows homology searching and modification profiling: HomClus, a versatile tool},
  url          = {http://dx.doi.org/10.1021/pr201114m},
  volume       = {11},
  year         = {2012},
}

Chicago
Menschaert, Gerben, Eisuke Hayakawa, Liliane Schoofs, Wim Van Criekinge, and Geert Baggerman. 2012. “Spectral Clustering in Peptidomics Studies Allows Homology Searching and Modification Profiling: HomClus, a Versatile Tool.” Journal of Proteome Research 11 (5): 2774–2785.
APA
Menschaert, G., Hayakawa, E., Schoofs, L., Van Criekinge, W., & Baggerman, G. (2012). Spectral clustering in peptidomics studies allows homology searching and modification profiling: HomClus, a versatile tool. JOURNAL OF PROTEOME RESEARCH, 11(5), 2774–2785.
Vancouver
1.
Menschaert G, Hayakawa E, Schoofs L, Van Criekinge W, Baggerman G. Spectral clustering in peptidomics studies allows homology searching and modification profiling: HomClus, a versatile tool. JOURNAL OF PROTEOME RESEARCH. 2012;11(5):2774–85.
MLA
Menschaert, Gerben, Eisuke Hayakawa, Liliane Schoofs, et al. “Spectral Clustering in Peptidomics Studies Allows Homology Searching and Modification Profiling: HomClus, a Versatile Tool.” JOURNAL OF PROTEOME RESEARCH 11.5 (2012): 2774–2785. Print.