Transcriptomic Messiness in the Venom Duct of Conus miles Contributes to Conotoxin Diversity

Abstract

Marine cone snails have developed sophisticated chemical strategies to capture prey and defend themselves against predators. Among the vast array of bioactive molecules in their venom, peptide components called conotoxins or conopeptides dominate, with many binding with high affinity and selectivity to a broad range of cellular targets, including receptors and transporters of the nervous system. Whereas the conopeptide gene precursor organization has a conserved topology, the peptides in the venom duct are highly processed. Indeed, deep sequencing transcriptomics has uncovered on average fewer than 100 toxin gene precursors per species, whereas advanced proteomics has revealed >10-fold greater diversity at the peptide level. In the present study, second-generation sequencing technologies coupled to highly sensitive mass spectrometry methods were applied to rapidly uncover the conopeptide diversity in the venom of a worm-hunting species, Conus miles. A total of 662 putative conopeptide encoded sequences were retrieved from transcriptomic data, comprising 48 validated conotoxin sequences that clustered into 10 gene superfamilies, including 3 novel superfamilies and a novel cysteine framework (C-C-C-CCC-C-C) identified at both transcript and peptide levels. A surprisingly large number of conopeptide gene sequences were expressed at low levels, including a series of single amino acid variants, as well as sequences containing deletions and frame and stop codon shifts. Some of the toxin variants generate alternative cleavage sites, interrupted or elongated cysteine frameworks, and highly variable isoforms within families that could be identified at the peptide level. Together with the variable peptide processing identified previously, background genetic and phenotypic levels of biological messiness in venoms contribute to the hypervariability of venom peptides and their ability to evolve rapidly. Molecular & Cellular Proteomics 12:

Optimized deep-targeted proteotranscriptomic profiling reveals unexplored Conus toxin diversity and novel cysteine frameworks

“…Although the pipeline described here has allowed matching more peptide fragments with conotoxin transcripts than the only two comparable Conus studies [144 peptides mapped to 3,303 fulllength precursor transcripts (4.4%); Dutertre et al (59), 43 vs. 75-57%; Jin et al (46), 29 vs. 48-60%], the task still remains delicate. Indeed, the difference of sequencing depth between Illumina and current mass spectrometers necessitates enriching protein samples to detect low expressed proteins.…”

“…However, using traditional protein-centric drug discovery approaches has been a tedious and time-consuming task that allows only superficial mining of the huge chemical diversity of natural products and that usually leads to the identification of only a few bioactive peptides per experiment (77). During the past decade, several studies focusing solely on cone snail venom duct (43,44,49,(78)(79)(80) or salivary gland (9,43,44,49,(78)(79)(80) transcriptomes, and later complemented by proteome profiling (46,47,50,59,81), have allowed the report of no more than only a hundred (47 on average) full-length precursor conotoxins each. The great majority of these studies used the ROCHE 454 next-generation sequencing platform because it produced low amounts of long reads that were possible to annotate by performing simple homology BLAST searches.…”

“…Despite a weak correlation between gene superfamilies and pharmacological properties, some functional redundancy among members of a same superfamily exists (56). To date, 16 empirical gene superfamilies (designated as A, D, I1, I2, I3, J, L, M, O1, O2, O3, P, S, T, V, Y) have been annotated (57), plus 31 novel superfamilies have been discovered during the past two years (38,39,46,(57)(58)(59)(60).…”

Conopeptide-Derived κ-Opioid Agonists (Conorphins): Potent, Selective, and Metabolic Stable Dynorphin A Mimetics with Antinociceptive Properties

“…For each of the different isomers one pair of cysteine residues was incorporated into the sequence, using Cys(Trt) protection while the other Cys pair used the orthogonal protection of Cys(Acm). After cleavage and purification of the reduced peptide the first disulfide bond was formed using the standard 30% DMSO/0.1 M NH 4 OAc buffer (pH 6) method described above.…”

An efficient transcriptome analysis pipeline to accelerate venom peptide discovery and characterisation

“…Recent advances in transcriptomic and proteomic approaches, and the development of complementary bioinformatics tools have established 'venomics' as an accelerated method for studying venoms, with several seminal discoveries reported using this approach (Pineda et al, 2014;Prashanth et al, 2014;Zelanis and Tashima, 2014). In addition to novel toxin discoveries Viala et al, 2015), venomics has helped uncover the mechanisms governing toxin diversification Jin et al, 2013), distinct defensive and predatory venom gland specialisation in Conidae , and the morphological constraints driving the evolution of centipede venoms (Undheim et al, 2015). In the absence of reference genomes for many venomous animals, transcriptome sequencing of venom glands has come to underpin the venomics approach and has enabled novel toxin discovery at an unprecedented level from snakes (Durban et al, 2011), spiders (Pineda et al, 2014), scorpions (Rendón-Anaya et al, 2015), cone snails (Prashanth et al, 2014), and even relatively poorly characterised animals such as ants (Bouzid et al, 2013).…”