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Studying Venom Toxin Variation Using Accurate Masses from Liquid Chromatography–Mass Spectrometry Coupled with Bioinformatic Tools

  • Luis L. Alonso
  • , Jory van Thiel
  • , Julien Slagboom
  • , Nathan Dunstan
  • , Cassandra M. Modahl
  • , Timothy N.W. Jackson
  • , Saer Samanipour
  • , Jeroen Kool*
  • *Corresponding author for this work

Research output: Contribution to JournalArticleAcademicpeer-review

Abstract

This study provides a new methodology for the rapid analysis of numerous venom samples in an automated fashion. Here, we use LC-MS (Liquid Chromatography–Mass Spectrometry) for venom separation and toxin analysis at the accurate mass level combined with new in-house written bioinformatic scripts to obtain high-throughput results. This analytical methodology was validated using 31 venoms from all members of a monophyletic clade of Australian elapids: brown snakes (Pseudonaja spp.) and taipans (Oxyuranus spp.). In a previous study, we revealed extensive venom variation within this clade, but the data was manually processed and MS peaks were integrated into a time-consuming and labour-intensive approach. By comparing the manual approach to our new automated approach, we now present a faster and more efficient pipeline for analysing venom variation. Pooled venom separations with post-column toxin fractionations were performed for subsequent high-throughput venomics to obtain toxin IDs correlating to accurate masses for all fractionated toxins. This workflow adds another dimension to the field of venom analysis by providing opportunities to rapidly perform in-depth studies on venom variation. Our pipeline opens new possibilities for studying animal venoms as evolutionary model systems and investigating venom variation to aid in the development of better antivenoms.

Original languageEnglish
Article number181
Pages (from-to)1-15
Number of pages15
JournalToxins
Volume16
Issue number4
Early online date7 Apr 2024
DOIs
Publication statusPublished - Apr 2024

Bibliographical note

This article belongs to the Special Issue: Venomous Snakes: Taxonomy, Toxicology and Clinical Management of Envenomation.

Publisher Copyright:
© 2024 by the authors.

Funding

This research was funded in part by the Wellcome Trust [221712/Z/20/Z]. For the purpose of open access availability, the author has applied a CC BY public copyright license to any Author Accepted Manuscript version arising from this submission.

FundersFunder number
Wellcome Trust221712/Z/20/Z, 221712

    Keywords

    • data analysis
    • high throughput
    • LC-MS
    • snake venom

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