A hybrid, de novo based, genome-wide database search approach applied to the sea urchin neuropeptidome.
Peptidomics is the identification and study of the in vivo biologically active peptide profile. A combination of high performance liquid chromatography, mass spectrometry, and bioinformatics tools such as database search engines are commonly used to perform the analysis. We report a methodology based on a database system holding the completed translated genome, whereby de novo sequencing and genome-wide database searching are combined. The methodology was applied to the sea urchin neuropeptidome resulting in a 30% increase in identification rate.
Menschaert
Gerben
G
Department of Molecular Biotechnology, Faculty of Bioscience Engineering, Laboratory for Bioinformatics and Computational Genomics, Ghent University, B-9000 Ghent, Belgium. Gerben.Menschaert@ugent.be
Vandekerckhove
Tom T M
TT
Baggerman
Geert
G
Landuyt
Bart
B
Sweedler
Jonathan V
JV
Schoofs
Liliane
L
Luyten
Walter
W
Van Criekinge
Wim
W
D000595:Amino Acid Sequence; D000818:Animals; D002851:Chromatography, High Pressure Liquid; D030562:Databases, Protein; D016678:Genome; D008969:Molecular Sequence Data; D009419:Nerve Tissue Proteins / Q000235:genetics / Q000378:metabolism*; D020543:Proteome; D012617:Sea Urchins; D019032:Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization
D009419:Nerve Tissue Proteins; D020543:Proteome