Abstract

A critical hurdle in ant venom proteomic investigations is the lack of databases to comprehensively and specifically identify the sequence and function of venom proteins and peptides. To resolve this, we used venom gland transcriptomics to generate a sequence database that was used to assign the tandem mass spectrometry (MS) fragmentation spectra of venom peptides and proteins to specific transcripts. This was performed alongside a shotgun liquid chromatography–mass spectrometry (LC-MS/MS) analysis of the venom to confirm that these assigned transcripts were expressed as proteins. Through the combined transcriptomic and proteomic investigation of Paraponera clavata venom, we identified four times the number of proteins previously identified using 2D-PAGE alone. In addition to this, by mining the transcriptomic data, we identified several novel peptide sequences for future pharmacological investigations, some of which conform with inhibitor cysteine knot motifs. These types of peptides have the potential to be developed into pharmaceutical or bioinsecticide peptides.

Highlights

  • Animal venoms are an increasingly popular source of drug leads, as they are rich in bioactive peptides

  • We identified novel components of P. clavata venom and highlight the advantages of using combined proteomics and transcriptomics approaches for a holistic overview of the complexity of ant venom arsenals

  • Illumina Hiseq 2500 sequencing of the cDNA library from P. clavata venom glands yielded over 17 million paired end reads after quality control (QC)

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Summary

Introduction

Animal venoms are an increasingly popular source of drug leads, as they are rich in bioactive peptides. These peptides have evolved over millions of years, and they target a wide variety of receptors and other biological processes [1,2]. There are six venom-derived peptides on the therapeutic drug market and one insecticide [2]. There is potential for many more, as only a small fraction of venom-derived peptides has been investigated. New developments in sensitivity and accuracy in mass spectrometry and transcriptomic sequencing are likely to accelerate this process. One of the hurdles of venom proteomics investigations has been the lack of appropriate databases to assign peptide sequence information using bottom-up mass spectrometry. The use of venom gland mRNA to deduce protein sequence information is becoming increasingly common, in conjunction with venom proteomics analysis, as this overcomes some of the problems of predicting open reading frames (ORFs) or de novo assembly

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