Metabolomics driven analysis of six Nigella species seeds via UPLC-qTOF-MS and GC–MS coupled to chemometrics

• Classification of 6 Nigella sp. was carried out via UPLC-PDA-MS and GC–MS.
• 52 Metabolites including saponins, phenolics and alkaloids were identified.
• Discrimination among species was related to kaempferol glycosidic conjugates.
• UPLC-qTOF-MS was found more reliable in Nigella samples classification.

Nigella sativa, commonly known as black cumin seed, is a popular herbal supplement that contains numerous phytochemicals including terpenoids, saponins, flavonoids, alkaloids. Only a few of the ca. 15 species in the genus Nigella have been characterized in terms of phytochemical or pharmacological properties. Here, large scale metabolic profiling including UPLC-PDA-MS and GC–MS with further multivariate analysis was utilized to classify 6 Nigella species. Under optimized conditions, we were able to annotate 52 metabolites including 8 saponins, 10 flavonoids, 6 phenolics, 10 alkaloids, and 18 fatty acids. Major peaks in UPLC–MS spectra contributing to the discrimination among species were assigned as kaempferol glycosidic conjugates, with kaempferol-3-O-[glucopyranosyl-(1 → 2)-galactopyranosyl-(1 → 2)-glucopyranoside, identified as potential taxonomic marker for N. sativa. Compared with GC–MS, UPLC–MS was found much more efficient in Nigella sample classification based on genetic and geographical origin. Nevertheless, both GC–MS and UPLC–MS support the remote position of Nigella nigellastrum in relation to the other taxa.