Exploring Top-Down Mass Spectrometric Approaches To Probe Forest Cobra ( Naja melanoleuca ) Venom Proteoforms.
C Ruth WangMuhammad A ZenaideeMarten F SnelTara Louise PukalaPublished in: Journal of proteome research (2024)
Snake venoms are comprised of bioactive proteins and peptides that facilitate severe snakebite envenomation symptoms. A comprehensive understanding of venom compositions and the subtle heterogeneity therein is important. While bottom-up proteomics has been the well-established approach to catalogue venom compositions, top-down proteomics has emerged as a complementary strategy to characterize venom heterogeneity at the intact protein level. However, top-down proteomics has not been as widely implemented in the snake venom field as bottom-up proteomics, with various emerging top-down methods yet to be developed for venom systems. Here, we have explored three main top-down mass spectrometry methodologies in a proof-of-concept study to characterize selected three-finger toxin and phospholipase A 2 proteoforms from the forest cobra ( Naja melanoleuca ) venom. We demonstrated the utility of a data-independent acquisition mode "MS E " for untargeted fragmentation on a chromatographic time scale and its improvement in protein sequence coverage compared to conventional targeted tandem mass spectrometry analysis. We also showed that protein identification can be further improved using a hybrid fragmentation approach, combining electron-capture dissociation and collision-induced dissociation. Lastly, we reported the promising application of multifunctional cyclic ion mobility separation and post-ion mobility fragmentation on snake venom proteins for the first time.
Keyphrases
- mass spectrometry
- liquid chromatography
- tandem mass spectrometry
- gas chromatography
- high performance liquid chromatography
- ultra high performance liquid chromatography
- high resolution mass spectrometry
- simultaneous determination
- high resolution
- climate change
- escherichia coli
- amino acid
- drug delivery
- cancer therapy
- oxidative stress
- protein protein
- binding protein
- healthcare
- ms ms
- physical activity
- quantum dots
- machine learning
- electronic health record
- single cell
- solid phase extraction
- artificial intelligence
- early onset
- diabetic rats
- big data
- drug induced
- gas chromatography mass spectrometry