AI Article Synopsis
- There is a significant challenge in studying ant venom due to a lack of databases that can accurately identify venom protein sequences and functions.
- To address this, researchers created a sequence database using venom gland transcriptomics, which helped match mass spectrometry data to specific venom transcripts.
- This approach led to identifying four times more proteins than previous methods and uncovered potential new peptides for pharmaceutical development, specifically those with inhibitor cysteine knot motifs.
Article 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 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.
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| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7290781 | PMC |
| http://dx.doi.org/10.3390/toxins12050324 | DOI Listing |
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