How Does Lagenaria siceraria (Bottle Gourd) Metabolome Compare to Cucumis sativus (Cucumber) F. Cucurbitaceae? A Multiplex Approach of HR-UPLC/MS/MS and GC/MS Using Molecular Networking and Chemometrics

Abstract

Cucurbitaceae comprises 800 species, the majority of which are known for their nutritive, economic, and health-promoting effects. This study aims at the metabolome profiling of cucumber (Cucumis sativus) and bottle gourd (Lagenaria siceraria) fruits in a comparative manner for the first time, considering that both species are reported to exhibit several in-common phytochemical classes and bioactivities. Nevertheless, bottle gourd is far less known and/or consumed than cucumber, which is famous worldwide. A multiplex approach, including HR-UPLC/MS/MS, GNPS networking, SPME, and GC/MS, was employed to profile primary and secondary metabolites in both species that could mediate for new health and nutritive aspects, in addition to their aroma profiling, which affects the consumers’ preferences. Spectroscopic datasets were analyzed using multivariate data analyses (PCA and OPLS) for assigning biomarkers that distinguish each fruit. Herein, 107 metabolites were annotated in cucumber and bottle gourd fruits via HR-UPLC/MS/MS analysis in both modes, aided by GNPS networking. Metabolites belong to amino acids, organic acids, cinnamates, alkaloids, flavonoids, pterocarpans, alkyl glycosides, sesquiterpenes, saponins, lignans, fatty acids/amides, and lysophospholipids, including several first-time reported metabolites and classes in Cucurbitaceae. Aroma profiling detected 93 volatiles presented at comparable levels in both species, from which it can be inferred that bottle gourds possess a consumer-pleasant aroma, although data analyses detected further enrichment of bottle gourd with ketones and esters versus aldehydes in cucumber. GC/MS analysis of silylated compounds detected 49 peaks in both species, including alcohols, amino acids, fatty acids/esters, nitrogenous compounds, organic acids, phenolic acids, steroids, and sugars, from which data analyses recognized that the bottle gourd was further enriched with fatty acids in contrast to higher sugar levels in cucumber. This study provides new possible attributes for both species in nutrition and health-care fields based on the newly detected metabolites, and further highlights the potential of the less famous fruit “bottle gourd”, recommending its propagation.

Seasonal and taxa impact on edible sea cucumber's metabolome and in relation to its cytotoxicity as analyzed via UHPLC/HR‐MS/MS‐based molecular networking and chemometrics

“…Metabolites were characterized by analyzing tandem HR‐MS data and employing MN, aided by GNPS software, and its spectral library. Accordingly, we were able to pinpoint the annotated compounds to the unknown peaks (El‐Akad et al., 2023; Hegazi et al., 2022; Shakour et al., 2023). Two MNs were constructed, one for each ion mode, which represented samples as pie charts based on metabolite abundance.…”

“…Basically, metabolites were tentatively identified according to their retention time (Rt. min), degree of unsaturation (rdb), mass spectral data—including precursor and product ions, their predicted formulae (mass accuracy <10 ppm), fragmentation pattern—and comparing the collective data with reported literature and databases such as MarinLit, PubChem, LIPID MAPS, HMDB, and predicted spectra generated by CFM‐ID server, in addition to Global Natural Products Social (GNPS) library annotations and extrapolating the identification of annotated compounds to the unknown peaks within the same cluster (El‐Akad et al., 2023; Hegazi et al., 2022; Shakour et al., 2023). All assigned formulae are top ranked by Orbitrap analyzer, and in some instances, the only predicted ones.…”

“…The MN parameters were as follows: minimum cosine score is 0.70; 0.1 Da precursor mass tolerance and 0.5 Da as fragment ion tolerance. Clustering was created from metabolites having at least four matched fragment peaks, with a minimum cluster size of 2 (El‐Akad et al., 2023). Filtering against blank file (G6) was performed on GNPS to exclude peaks produced by solvent impurities or artifacts from sample metabolite networking.…”

“…Freeze-dried samples of sea cucumbers (n = 3 each) were ground in liquid nitrogen (Sigma-Aldrich, purity 99.998%) using pestle and mortar. The extraction procedure followed the same protocol reported in El-Akad et al (2023), in which 150 mg of the powdered samples was mixed with 5 mL methanol containing 10 μg/mL umbelliferone as an internal standard (Sigma-Aldrich, purity 98.0%) and homogenized with an ULTRA-TURRAX (IKA) at 11,000 rpm, 5 × 60 s. Extracts were then vortexed, centrifuged at 3000 g for 30 min, and filtered through a 22 μm pore size filter.…”

Profiling of primary and phytonutrients in edible mahlab cherry (Prunus mahaleb L.) seeds in the context of its different cultivars and roasting as analyzed using molecular networking and chemometric tools

“…This is the first study of LCMS metabolomics and molecular networking to profile red and white mahlab ( Prunus mahaleb ) seeds from two different origins in the Mediterranean region where the tree grows, and further in response to roasting. Advanced chemical profiling such as liquid chromatography (LC-MS) or gas chromatography coupled to mass spectrometry (GC-MS) has recently shown remarkable contribution towards food and functional food analysis in emerging food metabolomics owing for their sensitivity and structural elucidation power ( El-Akad, El-Din & Farag, 2023 ). We have previously reported on the use of GC-MS for aroma profiling in P. mahaleb L. in context to its cultivar type and roasting ( Farag et al., 2021 ).…”