This study attempts to elucidate the secondary metabolite profiles of Ficus lyrata leaves and fruits grown in Egypt. Non-targeted metabolite profiling via ultra performance liquid chromatography (UPLC)-qTOF-MS was used to identify various chemical classes in F. lyrata fruits and leaves (i.e. flavonoids, phenolic acids and fatty acids) analysed by chemometrics. A total of 72 metabolites were evaluated via a UPLC-qTOF-MS-based metabolomic study. Seventeen flavonoids were characterised and tentatively identified with the main constituents being catechins/procyanidins, O- and C-linked flavonoid glycosides. The major procyanidins were dimers and trimers comprising (epi)catechin and (epi)afzelechin units, whereas the predominant flavones were C-glycosides of luteolin and apigenin. Aside from these major flavonoid classes, a group of benzoic acids, caffeoylquinic acids, fatty acid and sphingolipids were also annotated. This study provides the most complete map for polyphenol distribution in F. lyrata leaves and fruits and the basis for future investigation of its fruits nutritional value or possible nutraceutical uses.

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.

Date palm fruits of the species Phoenix dactylifera exhibit a great diversity in sensory attributes including skin color, smell and taste. This study attempts to elucidate the primary and secondary metabolite profiles of 21 date varieties from Egypt. A major difficulty is sugar rich matrix and skin-fibers embedding the secondary metabolites. A total of 49 metabolites extracted from the fruit skin were evaluated in a UPLC/PDA/ESI–qTOF-MS based metabolomics study. The total phenolic contents of the varieties varied from 233 to 1897 mg/100 g (2.3–19 g/kg) dry weight. The predominant flavones were glycosides of luteolin and apigenin, quercetin conjugates were the principal flavonols, whereas caffeoyl shikimic acid was the main hydroxycinnamic acid conjugate. Aside from these major phenolic classes, a group of sphingolipids, fatty and other organic acids was also identified. The total non-fatty organic acid content correlates with reported shelf lives. GC–MS was further utilized to localize primary metabolites in fruits (i.e. sugars and organic acids) with glucose and fructose accounting for up to 95% of TIC among most varieties. Principal component and clustering analyses reveal that flavonols and sugars, both contribute the most to variety classification. This study provides the most complete map for polyphenol & sugar distribution in Egyptian date fruit varieties. By describing the metabolite profiles in a diverse dataset of P. dactylifera, this study provides the basis for future investigations of date fruit nutritional value beyond providing energy and its potential for nutraceutical enhancement or storability.

The development of fast and effective spectroscopic methods that can detect most compounds in an untargeted manner is of increasing interest in plant extracts fingerprinting or profiling projects. Metabolite fingerprinting by nuclear magnetic resonance (NMR) is a fast growing field which is increasingly applied for quality control of herbal products, mostly via 1D 1H NMR coupled to multivariate data analysis. Nevertheless, signal overlap is a common problem in 1H NMR profiles that hinders metabolites identification and results in incomplete data interpretation. Herein, we introduce a novel approach in coupling 2D NMR datasets with principal component analysis (PCA) exemplified for hop resin classification. Heteronuclear multiple bond correlation (HMBC) profile maps of hop resins (Humulus lupulus) were generated for a comparative study of 13 hop cultivars. The method described herein combines reproducible metabolite fingerprints with a minimal sample preparation effort and an experimental time of ca. 28 min per sample, comparable to that of a standard HPLC run. Moreover, HMBC spectra provide not only unequivocal assignment of hop major secondary metabolites, but also allow to identify several isomerization and degradation products of hop bitter acids including the sedative principal of hop (2-methylbut-3-en-2-ol). We do believe that combining 2D NMR datasets to chemometrics, i.e. PCA, has great potential for application in other plant metabolome projects of (commercially relevant) nutraceuticals and or herbal drugs.

The metabolomic differences in phenolics from leaves derived from 3 artichoke cultivars (Cynara scolymus): American Green Globe, French Hyrious and Egyptian Baladi, collected at different developmental stages, were assessed using UHPLC–MS coupled to chemometrics. Ontogenic changes were considered as leaves were collected at four different time intervals and positions (top and basal) during artichoke development. Unsupervised principal component analysis (PCA) and supervised orthogonal projection to latent structures-discriminant analysis (O2PLS-DA) were used for comparing and classification of samples harvested from different cultivars at different time points and positions. A clear separation among the three investigated cultivars was revealed, with the American Green Globe samples found most enriched in caffeic acid conjugates and flavonoids vs. other cultivars. Furthermore, these metabolites also showed a marked effect on the discrimination between leaf samples from cultivars harvested at different positions, regardless of the plant age. Metabolite absolute quantifications further confirmed that discrimination was mostly influenced by phenolic compounds, namely caffeoylquinic acids and flavonoids. This study demonstrates an effect of artichoke leaf position, regardless of plant age, on its secondary metabolites composition. To the best of our knowledge, this is the first report for compositional differences among artichoke leaves, based on their positions, via a metabolomic approach and suggesting that top positioned artichoke leaves present a better source of caffeoylquinic acids, compared to basal ones.

Hypericum perforatum, commonly known as St. John’s wort, is a popular herbal supplement used for the treatment of mild to moderate depression. The major secondary metabolites of St. John’s wort extracts include phenylpropanoids, flavonoids, xanthones, phloroglucinols, and naphthodianthrones. There are over 400 species in the genus Hypericum world-wide, most of which are little or not characterized in terms of phytochemical or pharmacological properties. Metabolomics techniques were used to investigate the natural product diversity within the genus Hypericum (Hypericaceae) and its correlation to bioactivity, exemplified by cytotoxic properties. Utilizing nuclear magnetic resonance (NMR) fingerprinting and mass spectrometry (MS) metabolic profiling techniques, MS and NMR spectra of extracts from H. perforatum, H. polyphyllum, H. tetrapterum, H. androsaemum, H. inodorum, H. undulatum and H. kouytchense were evaluated and submitted to statistical multivariate analyses. Although comparable score plots in principal component analysis were derived from both MS and NMR datasets, loading plots reveal, that different set of metabolites contribute for species segregation in each dataset. Major peaks in 1H NMR and MS spectra contributing to species discrimination were assigned as those of hyperforins, lipids, chlorogenic and shikimic acid. Shikimic acid and its downstream phenylpropanoids were more enriched in H. perforatum, H. androsaemum, H. kouytchense and H. inodorum extracts; whereas a novel hyperforin was found exclusively in H. polyphyllum. Next to H. perforatum, H. polyphyllum and H. tetrapterum show the highest levels of hypericins, and H. perforatum and H. polyphyllum are highest in phloroglucinols, suggesting that the latter species might be used as an alternative to St. John’s wort. However, the major hyperforin-type compound in H. polyphyllum possesses a novel constitution of yet unknown bioactivity. Anti-cancer in vitro assays to evaluate the ability of extracts from Hypericum species in inhibiting prostate and colon cancer growth suggest that such bioactivity might be predicted by gross metabolic profiling.