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Abstract :
[en] Alkaloids are a class of naturally occurring organic nitrogen-containing bases that are found primarily in plants. They display a huge diversity with more than 3,000 different types already identified. Next to their different pharmacological and therapeutic effects, alkaloids can have a deleterious impact on organisms as they are known to be neurotoxic and cardiotoxic for mammals and insects. In the current context of worldwide bee decline, occurrence of such compounds in floral production, i.e. nectar and pollen, raises major concerns. They could be beneficial to bees by protecting them against disease and pathogens but they could also cause toxicity. Until now alkaloids, and their effect on human health, are mainly studied in vegetative parts of plants. More recently the natural occurrence of alkaloids in nectar was also studied to investigate their effect on bee health. Whereas nectar chemicals can relatively easily and quickly be analyzed by chromatography, extracting chemicals from low pollen amount remains a challenge because of pollen structure and complexity. However, characterization of pollen chemicals can lead to valuable insight in their impact on pollinators allowing the development of mitigation strategies.
In this study, we used a UHPLC-(ESI)-Q-ToF/MS method allowing the identification and quantification of alkaloids in pollen matrices from four Aconitum species; A. lycoctonum, A. napellus compactum, A. napellus neomontanum and A. variegatum. Alkaloid extraction was performed using bead-beating disruption of the pollen sample and chromatographic analysis was carried out on an Acquity UPLC system interfaced with a Synapt G2 QTOF. The separation was achieved in gradient mode on an Acquity UPLC BEH C18 column and detection was performed in electrospray positive ionization mode (ES+). Alkaloid concentrations were measured as aconitine equivalents by using a pure aconitine standard as reference compound.
The total amount of alkaloids in Aconitum pollen ranged from 0.75 to 1.20 mg/g with 859 different compounds detected, some of them being pollen-specific. Statistical analyses were conducted on the global dataset to assess both quantitative and qualitative interspecific differences. One-way analysis of variance was performed on the total alkaloid content while a permutational test of multivatiate analysis of variance was used to compare the alkaloid profiles among the four Aconitum species. Results are briefly discussed in an ecological context.