Identifying novel conopepetides from the venom ducts of Conus litteratus through integrating transcriptomics and...

The venom ducts of marine cone snails secrete highly complex mixtures of cysteine-rich active peptides, which are generally known as conotoxins or conopeptides and provide a potential fertile resource for pharmacological neuroscience research and the discovery of new drugs. Previous studies have devoted substantial effort to the identification of novel conopeptides, and the 109 cone snail species have yielded 7000 known conopeptides to date. Here, we used de novo deep transcriptome sequencing analyses combined with traditional Sanger sequencing and liquid chromatography-mass spectrometry/mass spectrometry (LC-MS/MS) to identify 30 distinct conopeptide precursors. Twenty of these were previously reported and the other 10 were novel conopeptide precursors. The study provides the first identification of the Con-ikot-ikot, NSF-bt05, O3 and I1 gene superfamilies in C. litteratus. A new putative superfamily was identified. In addition, the following cysteine frameworks were first identified in this study: CC-C-C-C-C-C-C-C-C-C-C-C-CC-C-C-C-C-C and C-C-C-C-C-CC-C. Several isomerases involved in post-translational modification of conopeptides were identified as well. The discovery of new conopeptides in C. litteratus will enhance our understanding of the conopeptide diversity in this particular clade of cone snails. We also found the existence of intraspecific variations in vermivorous species. Finally, the analysis strategy offers a relatively reliable workflow for screening for peptide drug candidates. SIGNIFICANCE: These novel conopeptides provide a potential resource for the development of new channel-targeting drugs. The intraspecific variation in C. litteratus enhance our understanding of the conopeptide diversity in this particular clade of cone snails. The identified three cysteine residues, which might participate in the formation of disulfide bonds, provide a clue to get the connectivity of cysteine frameworks. Finally, the analysis strategy offers a relatively reliable workflow for screening for peptide drug candidates.