Profiling of pyrrolizidine alkaloids using a retronecine-based untargeted metabolomics approach coupled to the quantitation of the retronecine-core in medicinal plants using UHPLC-QTOF.

Pyrrolizidine alkaloids (PA) are secondary metabolites of high toxicological relevance. Several PA quantitative methodologies were developed based on a limited number of certified standards, including time consuming solid phase extraction (SPE) purification steps. Herein, we shed light on the variability of PA in herbal extracts and propose a quantification methodology based on ultra-high-performance liquid chromatography high-resolution mass spectrometry (UHPLC-HRMS) for the evaluation of the total PA content as retronecine-equivalents (RE) directly from crude matrices. Particularly in the focus of the investigation were Alkanna spp. (Boraginaceae), which possess a wide range of pharmaceutical properties. In addition, a comparative PA screening of crude and SPE enriched extracts was performed and PA-containing plants from Fabaceae and Compositae families were included to demonstrate universal applicability. In total, 105 PA were identified using HRMSe experiments, specific MS/MS fragmentation PA patterns, a customized in-house library and literature data. Among them, 18 glycosidic PA derivatives were reported for the first time in literature. Using a hierarchical clustering approach, PA distribution in herbal extracts was shown to be family-dependent and significantly different among species. This was further supported by the results of the total PA concentrations, obtained using a retronecine/heliotridine/internal standard-based targeted UHPLC-HRMS quantification method, which varied from 8.64 ± 0.08-3096.28 ± 273.72 µg RE/g extract dry weight in shoots extracts of Alkanna spp. and leaves extracts of Crotalaria retusa L. respectively. Worth mentioning is that the procedure allowed to quantify PA in Alkanna spp. If the procedure based on 35 specific PA recommended by European regulations had been used, results would have been equal to zero for the four species since none were observed in Alkanna spp. Finally, by combining the RE results with the corresponding dereplication results, a customized correction factor for each extract (ranging from 2.12 to 2.48) was assessed leading to a more accurate estimate of the PA content regardless of the molecular weight of each PA. The present methodology will facilitate PA quantification directly from crude extracts and avoid the underestimation the real PA content due to limited availabilty of authentic reference compounds in botanical extracts used in phytomedicines or food supplements/cosmetics.

Open and reusable annotated mass spectrometry dataset of a chemodiverse collection of 1,600 plant extracts.

As privileged structures, natural products often display potent biological activities. However, the discovery of novel bioactive scaffolds is often hampered by the chemical complexity of the biological matrices they are found in. Large natural extract collections are thus extremely valuable for their chemical novelty potential but also complicated to exploit in the frame of drug-discovery projects. In the end, it is the pure chemical substances that are desired for structural determination purposes and bioactivity evaluation. Researchers interested in the exploration of large and chemodiverse extract collections should thus establish strategies aiming to efficiently tackle such chemical complexity and access these structures. Establishing carefully crafted digital layers documenting the spectral and chemical complexity as well as bioactivity results of natural extracts collections can help prioritize time-consuming but mandatory isolation efforts. In this note, we report the results of our initial exploration of a collection of 1,600 plant extracts in the frame of a drug-discovery effort. After describing the taxonomic coverage of this collection, we present the results of its liquid chromatography high-resolution mass spectrometric profiling and the exploitation of these profiles using computational solutions. The resulting annotated mass spectral dataset and associated chemical and taxonomic metadata are made available to the community, and data reuse cases are proposed. We are currently continuing our exploration of this plant extract collection for drug-discovery purposes (notably looking for novel antitrypanosomatids, anti-infective and prometabolic compounds) and ecometabolomics insights. We believe that such a dataset can be exploited and reused by researchers interested in computational natural products exploration.