Piper nigrum L. (black and white peppercorn) is one of the most common culinary spices used worldwide. The current study aims to dissect pepper metabolome using 1H-NMR targeting of its major primary and secondary metabolites. Eighteen metabolites were identified with piperine detected in black and white pepper at 20.2 and 23.9 mg mg−1, respectively. Aroma profiling using HS-SPME coupled to GC-MS analysis and in the context of autoclave treatment led to the detection of a total of 52 volatiles with an abundance of b-caryophyllene at 82% and 59% in black and white pepper, respectively. Autoclaving of black and white pepper revealed improvement of pepper aroma as manifested by an increase in oxygenated compounds\' level. In vitro remote antimicrobial activity against food-borne Gram-positive and Gram-negative bacteria revealed the highest activity against P. aeruginosa (VP-MIC 16.4 and 12.9 mg mL−1) and a direct effect against Enterobacter cloacae at ca. 11.6 mg mL−1 for both white and black pepper.

Balanites aegyptiaca (L.) Delile (Zygophyllaceae), also known as the desert date, is an edible fruit-producing tree popular for its nutritional and several health benefits. In this study, multi-targeted comparative metabolic profiling and fingerprinting approaches were conducted for the assessment of the nutrient primary and secondary metabolite heterogeneity in different parts, such as leaves, stems, seeds, unripe, and ripe fruits of B. aegyptiaca using nuclear magnetic resonance (NMR), ultra-performance liquid chromatography (UPLC-MS), and gas chromatography mass-spectrometry (GC-MS) based metabolomics coupled to multivariate analyses and in relation to its cytotoxic activities. NMR-based metabolomic study identified and quantified 15 major primary and secondary metabolites belonging to alkaloids, saponins, flavonoids, sugars, and amino and fatty acids. Principal component analysis (PCA) of the NMR dataset revealed α-glucose, sucrose, and isorhamnetin as markers for fruit and stem and unsaturated fatty acids for predominated seeds. Orthogonal projections to latent structure discriminant analysis (OPLS-DA) revealed trigonelline as a major distinctive metabolite in the immature fruit and isorhamnetin as a major distinct marker in the mature fruit. UPLC-MS/MS analysis using feature-based molecular networks revealed diverse chemical classes viz. steroidal saponins, N-containing metabolites, phenolics, fatty acids, and lipids as the constitutive metabolome in Balanites. Gas chromatography-mass spectroscopy (GC-MS) profiling of primary metabolites led to the detection of 135 peaks belonging to sugars, fatty acids/esters, amino acids, nitrogenous, and organic acids. Monosaccharides were detected at much higher levels in ripe fruit and disaccharides in predominate unripe fruits, whereas B. aegyptiaca vegetative parts (leaves and stem) were rich in amino acids and fatty acids. The antidiabetic compounds, viz, nicotinic acid, and trigonelline, were detected in all parts especially unripe fruit in addition to the sugar alcohol D-pinitol for the first time providing novel evidence for B. aegyptiaca use in diabetes. In vitro cytotoxic activity revealed the potential efficacy of immature fruit and seeds as cytotoxic agents against human prostate cancer (PC3) and human colorectal cancer (HCT-116) cell lines. Collectively, such detailed profiling of parts provides novel evidence for B. aegyptiaca medicinal uses.

Introduction Liverworts are a group of non-vascular plants that possess unique metabolism not found in other plants. Many liverwort metabolites have interesting structural and biochemical characteristics, however the fluctuations of these metabolites in response to stressors is largely unknown. Objectives To investigate the metabolic stress-response of the leafy liverwort Radula complanata. Methods Five phytohormones were applied exogenously to in vitro cultured R. complanata and an untargeted metabolomic analysis was conducted. Compound classification and identification was performed with CANOPUS and SIRIUS while statistical analyses including PCA, ANOVA, and variable selection using BORUTA were conducted to identify metabolic shifts.Results It was found that R. complanata was predominantly composed of carboxylic acids and derivatives, followed by benzene and substituted derivatives, fatty acyls, organooxygen compounds, prenol lipids, and flavonoids. The PCA revealed that samples grouped based on the type of hormone applied, and the variable selection using BORUTA (Random Forest) revealed 71 identified and/or classified features that fluctuated with phytohormone application. The stress-response treatments largely reduced the production of the selected primary metabolites while the growth treatments resulted in increased production of these compounds. 4-(3-Methyl-2-butenyl)-5-phenethylbenzene-1,3-diol was identified as a biomarker for the growth treatments while GDP-hexose was identified as a biomarker for the stress-response treatments. Conclusion Exogenous phytohormone application caused clear metabolic shifts in Radula complanata that deviate from the responses of vascular plants. Further identification of the selected metabolite features can reveal metabolic biomarkers unique to liverworts and provide more insight into liverwort stress responses.

Herbs of the Umbelliferae family are popular spices valued worldwide for their many nutritional and health benefits. Herein, five chief umbelliferous fruits viz., cumin, fennel, anise, coriander and caraway were assessed for its secondary metabolites diversity along with compositional changes incurring upon roasting as analyzed via ultra-high performance liquid chromatography coupled to photodiode array and electrospray ionization mass detectors UHPLC-qToF/MS. A total of 186 metabolites were annotated, according to metabolomics society guidelines, belonging mainly to flavonoids, fatty acids and phenolic acids. Multivariate models viz., PCA, HCA and OPLS-DA were further employed to assess fruits\' heterogeneity in an untargeted manner and determine mechanistic changes in bioactive makeup post roasting viz., glycosidic cleavage, lipid degradation and Maillard reaction. Finally, the fruits\' antioxidant activity showed decline upon roasting and in correlation with its total phenolic content. This study presents the first complete map of umbelliferous fruit metabolome, compositional differences and its roasting effect.

IntroductionThe demand to develop efficient and reliable analytical methods for the quality control of nutraceuticals is on the rise, together with an increase in the legal requirements for safe and consistent levels of its active principles.ObjectiveTo establish a reliable model for the quality control of widely used Senna preparations used as laxatives and assess its phyto-equivalency.MethodsA comparative metabolomics approach via NMR and MS analyses was employed for the comprehensive measurement of metabolites and analyzed using chemometrics.ResultsUnder optimized conditions, 30 metabolites were simultaneously identified and quantified including anthraquinones, bianthrones, acetophenones, flavonoid conjugates, naphthalenes, phenolics, and fatty acids. Principal component analysis (PCA) was used to define relative metabolite differences among Senna preparations. Furthermore, quantitative 1H NMR (qHNMR) was employed to assess absolute metabolites levels in preparations. Results revealed that 6-hydroxy musizin or tinnevellin were correlated with active metabolites levels, suggesting the use of either of these naphthalene glycosides as markers for official Senna drugs authentication.ConclusionThis study provides the first comparative metabolomics approach utilizing NMR and UPLC–MS to reveal for secondary metabolite compositional differences in Senna preparations that could readily be applied as a reliable quality control model for its analysis.

IntroductionThe production of marine drugs in its normal habitats is often low and depends greatly on ecological conditions. Chemical synthesis of marine drugs is not economically feasible owing to their complex structures. Biotechnology application via elicitation represents a promising tool to enhance metabolites yield that has yet to be explored in soft corals.ObjectivesStudy the elicitation impact of salicylic acid (SA) and six analogues in addition to a systemic acquired resistance inducer on secondary metabolites accumulation in the soft coral Sarcophyton ehrenbergi along with the symbiont zooxanthellae and if SA elicitation effect is extended to other coral species S. glaucum and Lobophyton pauciliforum.MethodsPost elicitation in the three corals and zooxanthella, metabolites were extracted and analyzed via UHPLC-MS coupled with chemometric tools.ResultsMultivariate data analysis of the UHPLC-MS data set revealed clear segregation of SA, amino-SA, and acetyl-SA elicited samples. An increased level ca. 6- and 8-fold of the diterpenes viz., sarcophytonolide I, sarcophine and a C28-sterol, was observed in SA and amino-SA groups, respectively. Post elicitation, the level of diepoxy-cembratriene increased 1.5-fold and 2.4-fold in 1 mM SA, and acetyl-SA (aspirin) treatment groups, respectively. S. glaucum and Lobophyton pauciliforum showed a 2-fold increase of diepoxy-cembratriene levels.ConclusionThese results suggest that SA could function as a general and somewhat selective diterpene inducing signaling molecule in soft corals. Structural consideration reveals initial structure–activity relationship (SAR) in SA derivatives that seem important for efficient diterpene and sterol elicitation.

Thousands of articles using metabolomics approaches are published every year. With the increasing amounts of data being produced, mere description of investigations as text in manuscripts is not sufficient to enable re-use anymore: the underlying data needs to be published together with the findings in the literature to maximise the benefit from public and private expenditure and to take advantage of an enormous opportunity to improve scientific reproducibility in metabolomics and cognate disciplines. Reporting recommendations in metabolomics started to emerge about a decade ago and were mostly concerned with inventories of the information that had to be reported in the literature for consistency. In recent years, metabolomics data standards have developed extensively, to include the primary research data, derived results and the experimental description and importantly the metadata in a machine-readable way. This includes vendor independent data standards such as mzML for mass spectrometry and nmrML for NMR raw data that have both enabled the development of advanced data processing algorithms by the scientific community. Standards such as ISA-Tab cover essential metadata, including the experimental design, the applied protocols, association between samples, data files and the experimental factors for further statistical analysis. Altogether, they pave the way for both reproducible research and data reuse, including meta-analyses. Further incentives to prepare standards compliant data sets include new opportunities to publish data sets, but also require a little “arm twisting” in the author guidelines of scientific journals to submit the data sets to public repositories such as the NIH Metabolomics Workbench or MetaboLights at EMBL-EBI. In the present article, we look at standards for data sharing, investigate their impact in metabolomics and give suggestions to improve their adoption.

A methodology that brings together sugar and steroid scaffolds linked by a selenium atom is discussed in this work. A series of 6β and 3α glycoconjugated steroids were achieved by stereoselective nucleophilic substitution of cholesterol, pregnenolone, stigmasterol and sitosterol with different seleno-pyranosides and furanosides.

The anticancer drug cisplatin (CP) is loaded into SBA-15 mesoporous silica (SBA-15|CP) and its release from the nanomaterial is studied. The CP-loaded SBA-15 is tested against four tumor cell lines: mouse malignant melanoma B16F10, human adenocarcinoma HeLa, colon HT-29 and prostate PC3. Most importantly, the superiority of this novel material in comparison to CP arises from the fact that the CP-grafted nanomaterial SBA-15 (→SBA-15|CP) is enhancing cessation of proliferation along with induction of senescence in B16F10 in approximately 3.5 times lower concentration. The control material loaded with therapeutically inactive K2[PtCl4] (→SBA-15|TC) showed no antitumor activity. To a large extent, SBA-15|CP-induced senescence might present a safe approach in tumor treatment. Such cells can be cleared by immune cells resulting in efficient tumor regression. So far only apoptotic agents are being exploited in clinics, thus an understanding of the chemotherapeutic-induced senescence will allow oncologists to explore this essential tumor suppressor mechanism.

Univariate hypotheses tests such as Student’s t test or variance analysis (ANOVA) can help to answer a variety of questions in metabolomics data analysis. The statistical power of these tests depends on the setup of the experiment, the experimental design and the analytical variance of the actual observations. In this paper, we demonstrate how a well-designed pilot study prior to an experiment with the aim to find differences between e.g. several genotypes, can help to determine the variance at multiple levels ranging from biological variance, sample preparation to instrumental variances. Next, we illustrate how these variances can be used to obtain several parameters (e.g. minimum statistically significant effect, number of required replicates and error probabilities) which influence the design of the actual study. In particular, we are going to sketch how technical replicates can improve the performance of a test, when they are correctly used in the statistical analysis, e.g. with a hierarchical model. Finally, we demonstrate the process of evaluating the trade-off between different experimental designs with different replication strategies. The choice of an experimental design beyond the gut feeling can be influenced by factors such as costs, sample availability and the accuracy of of the tests. We use metabolite profiles of the model plant Arabidopsis thaliana measured on an UPLC-ESI/QqTOF-MS as real-world dataset, but the approach is equally applicable to other sample types and measurement methods like NMR based metabolomics.