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Development of an LC-MS multivariate nontargeted methodology for differential analysis of the peptide profile of Asian hornet venom (Vespa velutina nigrithorax): application to the investigation of the impact of collection period variation

Abstract : Insect venom is a highly complex mixture of bioactive compounds, containing proteins, peptides, and small molecules. Environmental factors can alter the venom composition and lead to intraspecific variation in its bioactivity properties. The investigation of discriminating compounds caused by variation impacts can be a key to manage sampling and explore the bioactive compounds. The present study reports the development of a peptidomic methodology based on UHPLC-ESI-QTOF-HRMS analysis followed by a nontargeted multivariate analysis to reveal the profile variance of Vespa velutina venom collected in different conditions. The reliability of the approach was enhanced by optimizing certain XCMS data processing parameters and determining the sample peak threshold to eliminate the interfering features. This approach demonstrated a good repeatability and a criterion coefficient of variation (CV) > 30% was set for deleting nonrepeatable features from the matrix. The methodology was then applied to investigate the impact of collection period variation. PCA and PLS-DA models were used and validated by cross-validation and permutation tests. A slight discrimination was found between winter and summer hornet venom in two successive years with 10 common discriminating compounds.
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https://hal-univ-tours.archives-ouvertes.fr/hal-02794337
Contributor : Eric Darrouzet <>
Submitted on : Friday, June 19, 2020 - 11:39:09 AM
Last modification on : Saturday, September 12, 2020 - 3:35:31 AM

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Thao Nhi Le, David da Silva, Cyril Colas, Éric Darrouzet, Patrick Baril, et al.. Development of an LC-MS multivariate nontargeted methodology for differential analysis of the peptide profile of Asian hornet venom (Vespa velutina nigrithorax): application to the investigation of the impact of collection period variation. Analytical and Bioanalytical Chemistry, Springer Verlag, 2020, 412 (6), pp.1419-1430. ⟨10.1007/s00216-019-02372-2⟩. ⟨hal-02794337⟩

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