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.