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Special Report

Integration of transcriptomic and proteomic approaches for snake venom profiling

, &
Pages 827-834 | Received 31 Aug 2021, Accepted 15 Oct 2021, Published online: 01 Nov 2021
 

ABSTRACT

Introduction

Snake venoms contain many protein and peptide isoforms with high levels of sequence variation, even within a single species.

Areas covered

In this review, we highlight several examples, from both published and unpublished work in our lab, demonstrating how a combined venom gland transcriptome and proteome methodology allows for comprehensive characterization of venoms, including those from understudied rear-fanged snake species, and we provide recommendations for using these approaches.

Expert Opinion

When characterizing venoms, peptide mass fingerprinting using databases built predominately from protein sequences originating from model organisms can be disadvantageous, especially when the intention is to document protein diversity. Therefore, the use of species-specific venom gland transcriptomes corrects for the absence of these unique peptide sequences in databases. The integration of transcriptomics and proteomics improves the accuracy of either approach alone for venom profiling.

Supplementary material

Supplemental data for this article can be accessed here.

Article highlights

  • Use of a species-specific venom gland transcriptome allows for more accurate proteomic quantification of venom components

  • Different databases can bias proteomic results, and smaller databases increase detection sensitivity

  • Species-specific databases better detect unique peptide sequences

Declaration of interests

The authors have no relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript. This includes employment, consultancies, honoraria, stock ownership or options, expert testimony, grants or patents received or pending, or royalties.

Additional information

Funding

This work was supported by a grant from the NSF (DEB Phylogenetic Systematics; DEB-1655571) to SPM.

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