Spectral Clustering in Peptidomics Studies Allows Homology Searching and Modification Profiling: HomClus, a Versatile Tool

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 res...

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Bibliographic Details
Published in:Journal of proteome research 2012-05, Vol.11 (5), p.2774-2785
Main Authors: Menschaert, Gerben, Hayakawa, Eisuke, Schoofs, Liliane, Van Criekinge, Wim, Baggerman, Geert
Format: Article
Language:English
Subjects:
Algorithms
Amino Acid Sequence
Animals
Databases, Protein
Drosophila melanogaster - chemistry
Insect Proteins - analysis
Insect Proteins - chemistry
Insect Proteins - isolation & purification
Locusta migratoria - chemistry
Molecular Sequence Annotation
Molecular Sequence Data
Peptides - analysis
Peptides - chemistry
Peptides - isolation & purification
Protein Processing, Post-Translational
Proteomics - methods
Search Engine
Sequence Analysis, Protein - methods
Sequence Homology, Amino Acid
Software
Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization - methods
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Summary: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.
ISSN:1535-3893
1535-3907
DOI:10.1021/pr201114m