Metabolomics analysis of (Geo)propolis from Brazilian stingless bees by FIA and UHPLC-HRMS (Orbitrap).

Native stingless bees (Meliponini) from Brazil make (geo)propolis which is largely used in folk medicine, specially by indigenous and quilombos communities and beekeepers´ families but are progressively being recognized for their pharmacological activities. In this study, the ethanolic extracts of (geo)propolis (EEGs) from Melipona marginata, M. quadrifasciata, M. scutellaris, and Tetragonisca angustula were analysed by Flow injection analysis (FIA) and Ultra-high performance liquid chromatography (UHPLC) in a high resolution Orbitrap mass analyser (HRMS) to investigate and compare their chemical profile. Untargeted metabolomic approach based on UHPLC-HRMS experiments, and bioinformatic tools, allowed to annotate 59 compounds from diverse classes such as: flavonoids, phenolic compounds, sugars, terpenoids, and lipids. In addition, using multivariate tools and Flow injection- high resolution mass spectrometry (FIA-HRMS), it was possible to classify samples and identify marker ions related to the bee species or genus and to the geographical origin as a proof of concept.

Identification of Plant Compounds with Mass Spectrometry Imaging (MSI).

The presence and localization of plant metabolites are indicative of physiological processes, e.g., under biotic and abiotic stress conditions. Further, the chemical composition of plant parts is related to their quality as food or for medicinal applications. Mass spectrometry imaging (MSI) has become a popular analytical technique for exploring and visualizing the spatial distribution of plant molecules within a tissue. This review provides a summary of mass spectrometry methods used for mapping and identifying metabolites in plant tissues. We present the benefits and the disadvantages of both vacuum and ambient ionization methods, considering direct and indirect approaches. Finally, we discuss the current limitations in annotating and identifying molecules and perspectives for future investigations.

Tannat grape pomace as an ingredient for potential functional biscuits: bioactive compound identification, in vitro bioactivity, food safety, and sensory evaluation.

Grape pomace, the main by-product of wine process, shows high potential for the development of functional foods, being a natural source of bioactive compounds and dietary fiber. Thus, the present study proposes the development of five potential functional biscuits. The five formulations were achieved by varying the Tannat grape pomace powder (TGP, 10-20% w/w total wet dough) and sweetener sucralose (2-4% w/w total wet dough) content through a factorial design with central points. TGP microbiological and pesticides analysis were performed as a food safety requirement. Identification of bioactive compounds by HPLC-DAD-MS, in vitro bioactivity (total phenol content, antioxidant by ABTS and ORAC-FL, antidiabetic and antiobesity by inhibition of α-glucosidase and pancreatic lipase, respectively) and sensory properties of the biscuits were evaluated. TGP microbiological and pesticides showed values within food safety criteria. Sensory profiles of TGP biscuits were obtained, showing biscuits with 20% TGP good sensory quality (7.3, scale 1-9) in a cluster of 37 out of 101 consumers. TGP addition in biscuits had a significant (p < 0.05) effect on total phenolic content (0.893-1.858 mg GAE/g biscuit) and bioactive properties when compared to controls: 11.467-50.491 and 4.342-50.912 µmol TE/g biscuit for ABTS and ORAC-FL, respectively; inhibition of α-glucosidase and pancreatic lipase, IC50 35.572-64.268 and 7.197-47.135 mg/mL, respectively. HPLC-DAD-MS results showed all the identified phenolic compounds in 20/4% biscuit (TGP/sucralose%) were degraded during baking. Malvidin-3-O-(6'-p-coumaroyl) glucoside, (+)-catechin, malvidin-3-O-glucoside, and (-)-epicatechin were the main phenolic compounds (in descendent order of content) found. The bioactive properties could be attributed to the remaining phenolic compounds in the biscuits. In conclusion, TGP biscuits seemed to be a promising functional food with potential for ameliorating oxidative stress, glucose and fatty acids levels with good sensory quality.

Untargeted-based metabolomics analysis and in vitro/in silico antiviral activity of extracts from Phyllanthus brasiliensis (Aubl.) Poir.

INTRODUCTION: This study describes the molecular profile and the potential antiviral activity of extracts from Phyllanthus brasiliensis, a plant widely found in the Brazilian Amazon. The research aims to shed light on the potential use of this species as a natural antiviral agent. METHODS: The extracts were analysed using liquid chromatography-mass spectrometry (LC-MS) system, a potent analytical technique to discover drug candidates. In the meantime, in vitro antiviral assays were performed against Mayaro, Oropouche, Chikungunya, and Zika viruses. In addition, the antiviral activity of annotated compounds was predicted by in silico methods. RESULTS: Overall, 44 compounds were annotated in this study. The results revealed that P. brasiliensis has a high content of fatty acids, flavones, flavan-3-ols, and lignans. Furthermore, in vitro assays revealed potent antiviral activity against different arboviruses, especially lignan-rich extracts against Zika virus (ZIKV), as follows: methanolic extract from bark (MEB) [effective concentration for 50% of the cells (EC50 ) = 0.80 µg/mL, selectivity index (SI) = 377.59], methanolic extract from the leaf (MEL) (EC50 = 0.84 µg/mL, SI = 297.62), and hydroalcoholic extract from the leaf (HEL) (EC50 = 1.36 µg/mL, SI = 735.29). These results were supported by interesting in silico prediction, where tuberculatin (a lignan) showed a high antiviral activity score. CONCLUSIONS: Phyllanthus brasiliensis extracts contain metabolites that could be a new kick-off point for the discovery of candidates for antiviral drug development, with lignans becoming a promising trend for further virology research.

Lipidomic analysis of geopropolis of Brazilian stingless bees by LC-HRMS.

Stingless bees (Meliponini) represent over than 500 species, found in tropical and sub-tropical regions of the world. They produce geopropolis, a resinous natural product containing bioactive compounds, which is commonly used in folk medicine. In the current study, LC-HRMS and bioinformatic tools were used to carry out for the first time the lipidomic analysis of geopropolis from indigenous Brazilian stingless bees. As a result, 61 compounds of several lipid classes were identified with elevated degree of confidence. Then, we demonstrated that lipids in geopropolis are not restricted to waxes and fatty acids; but fatty amides and amines, phenolic lipids, resorcinols, retinoids, abietanoids, diterpenoids, pentacyclic triterpenoids, prostaglandins, retinoids, and steroids were found. In addition, multivariate analysis, based on the lipidomic profile of extracts, reinforces the assumption that the species of stingless bees, as well as the geographical origin are relevant factors to affect geopropolis composition once that the lipidic profile allowed the discrimination of geopropolis in groups related to the geographical origin, bee specie or bee genus. The lipidic profile also suggest a selective forage habits of T. angustula, which seems to collect resins from more specific vegetal sources regardless geographic origin, while other stingless bees, such as M. marginata and M. quadrifasciata, are less selective and may adapt to collect resins from a wider variety of plants.

Exploring correlations between MS and NMR for compound identification using essential oils: A pilot study.

INTRODUCTION: In this era of 'omics' technology in natural products studies, the complementary aspects of mass spectrometry (MS)- and nuclear magnetic resonance (NMR)-based techniques must be taken into consideration. The advantages of using both analytical platforms are reflected in a higher confidence of results especially when using replicated samples where correlation approaches can be used to statistically link results from MS to NMR. OBJECTIVES: Demonstrate the use of Statistical Total Correlation (STOCSY) for linking results from MS and NMR data to reach higher confidence in compound identification. METHODOLOGY: Essential oil samples of Melaleuca alternifolia and M. rhaphiophylla (Myrtaceae) were used as test objects. Aliquots of 10 samples were collected for GC-MS and NMR data acquisition [proton (1 H)-NMR, and carbon-13 (13 C)-NMR as well as two-dimensional (2D) heteronuclear single quantum correlation (HSQC), heteronuclear multiple-bond correlation (HMBC), and HSQC-total correlated spectroscopy (TOCSY) NMR]. The processed data was imported to Matlab where STOCSY was applied. RESULTS: STOCSY calculations led to the confirmation of the four main constituents of the sample-set. The identification of each was accomplished using; MS spectra, retention time comparison, 13 C-NMR data, and scalar correlations of the 2D NMR spectra. CONCLUSION: This study provides a pipeline for high confidence in compound identification using a set of essential oils samples as test objects for demonstration.