Comparative venom gland transcriptomics of Naja kaouthia (monocled cobra) from Malaysia and Thailand: elucidating geographical venom variation and insights into sequence novelty

Transcriptomic and Proteomic Analyses Reveal the Diversity of Venom Components from the Vaejovid Scorpion Serradigitus gertschi

To understand the diversity of scorpion venom, RNA from venomous glands from a sawfinger scorpion, Serradigitus gertschi, of the family Vaejovidae, was extracted and used for transcriptomic analysis. A total of 84,835 transcripts were assembled after Illumina sequencing. From those, 119 transcripts were annotated and found to putatively code for peptides or proteins that share sequence similarities with the previously reported venom components of other species. In accordance with sequence similarity, the transcripts were classified as potentially coding for 37 ion channel toxins; 17 host defense peptides; 28 enzymes, including phospholipases, hyaluronidases, metalloproteases, and serine proteases; nine protease inhibitor-like peptides; 10 peptides of the cysteine-rich secretory proteins, antigen 5, and pathogenesis-related 1 protein superfamily; seven La1-like peptides; and 11 sequences classified as "other venom components". A mass fingerprint performed by mass spectrometry identified 204 components with molecular masses varying from 444.26 Da to 12,432.80 Da, plus several higher molecular weight proteins whose precise masses were not determined. The LC-MS/MS analysis of a tryptic digestion of the soluble venom resulted in the de novo determination of 16,840 peptide sequences, 24 of which matched sequences predicted from the translated transcriptome. The database presented here increases our general knowledge of the biodiversity of venom components from neglected non-buthid scorpions.

Evaluating the Performance of De Novo Assembly Methods for Venom-Gland Transcriptomics

Venom-gland transcriptomics is a key tool in the study of the evolution, ecology, function, and pharmacology of animal venoms. In particular, gene-expression variation and coding sequences gained through transcriptomics provide key information for explaining functional venom variation over both ecological and evolutionary timescales. The accuracy and usefulness of inferences made through transcriptomics, however, is limited by the accuracy of the transcriptome assembly, which is a bioinformatic problem with several possible solutions. Several methods have been employed to assemble venom-gland transcriptomes, with the Trinity assembler being the most commonly applied among them. Although previous evidence of variation in performance among assembly software exists, particularly regarding recovery of difficult-to-assemble multigene families such as snake venom metalloproteinases, much work to date still employs a single assembly method. We evaluated the performance of several commonly used de novo assembly methods for the recovery of both nontoxin transcripts and complete, high-quality venom-gene transcripts across eleven snake and four scorpion transcriptomes. We varied k-mer sizes used by some assemblers to evaluate the impact of k-mer length on transcript recovery. We showed that the recovery of nontoxin transcripts and toxin transcripts is best accomplished through different assembly software, with SDT at smaller k-mer lengths and Trinity being best for nontoxin recovery and a combination of SeqMan NGen and a seed-and-extend approach implemented in Extender as the best means of recovering a complete set of toxin transcripts. In particular, Extender was the only means tested capable of assembling multiple isoforms of the diverse snake venom metalloproteinase family, while traditional approaches such as Trinity recovered at most one metalloproteinase transcript. Our work demonstrated that traditional metrics of assembly performance are not predictive of performance in the recovery of complete and high quality toxin genes. Instead, effective venom-gland transcriptomic studies should combine and quality-filter the results of several assemblers with varying algorithmic strategies.

Venom proteomics and antivenom neutralization for the Chinese eastern Russell's viper, Daboia siamensis from Guangxi and Taiwan

The eastern Russell's viper (Daboia siamensis) causes primarily hemotoxic envenomation. Applying shotgun proteomic approach, the present study unveiled the protein complexity and geographical variation of eastern D. siamensis venoms originated from Guangxi and Taiwan. The snake venoms from the two geographical locales shared comparable expression of major proteins notwithstanding variability in their toxin proteoforms. More than 90% of total venom proteins belong to the toxin families of Kunitz-type serine protease inhibitor, phospholipase A2, C-type lectin/lectin-like protein, serine protease and metalloproteinase. Daboia siamensis Monovalent Antivenom produced in Taiwan (DsMAV-Taiwan) was immunoreactive toward the Guangxi D. siamensis venom, and effectively neutralized the venom lethality at a potency of 1.41 mg venom per ml antivenom. This was corroborated by the antivenom effective neutralization against the venom procoagulant (ED = 0.044 ± 0.002 µl, 2.03 ± 0.12 mg/ml) and hemorrhagic (ED50 = 0.871 ± 0.159 µl, 7.85 ± 3.70 mg/ml) effects. The hetero-specific Chinese pit viper antivenoms i.e. Deinagkistrodon acutus Monovalent Antivenom and Gloydius brevicaudus Monovalent Antivenom showed negligible immunoreactivity and poor neutralization against the Guangxi D. siamensis venom. The findings suggest the need for improving treatment of D. siamensis envenomation in the region through the production and the use of appropriate antivenom.

Computational Studies of Snake Venom Toxins

Most snake venom toxins are proteins, and participate to envenomation through a diverse array of bioactivities, such as bleeding, inflammation, and pain, cytotoxic, cardiotoxic or neurotoxic effects. The venom of a single snake species contains hundreds of toxins, and the venoms of the 725 species of venomous snakes represent a large pool of potentially bioactive proteins. Despite considerable discovery efforts, most of the snake venom toxins are still uncharacterized. Modern bioinformatics tools have been recently developed to mine snake venoms, helping focus experimental research on the most potentially interesting toxins. Some computational techniques predict toxin molecular targets, and the binding mode to these targets. This review gives an overview of current knowledge on the ~2200 sequences, and more than 400 three-dimensional structures of snake toxins deposited in public repositories, as well as of molecular modeling studies of the interaction between these toxins and their molecular targets. We also describe how modern bioinformatics have been used to study the snake venom protein phospholipase A2, the small basic myotoxin Crotamine, and the three-finger peptide Mambalgin.