Search Results (51)

In line with the recommended European policy for a zero-waste crop supply chain, a lab-pilot optimisation process to valorise the by-products of industrially produced rapeseed meal (RM) was performed. Three batches of RM were first processed into ethanol-wash solutes (EWS) and then optimised (OEWS) by an ultrasound-assisted (UA) treatment. After direct analysis in real time–high resolution mass spectrometry (DART-HRMS) analysis, data were processed applying a partial least square–discriminant analysis (PLS-DA), which retrieved the 15 most discriminative ions able to characterise the biochemical changes during the ethanol-washing and UA optimisation process. The metabolomic fingerprinting of EWS and OEWS generated an accurate and well-defined 3D spatial clusterisation based on a restricted pool of informative bioactive compounds. A significantly higher relative abundance of sinapic, azelaic, and vernolic acids and a lower incidence of the oleic and palmitic fatty acids were detected in OEWS. DART-HRMS generated a vast amount of biochemical information in one single run, also demonstrating that its association with an untargeted multivariate statistical approach would be a valuable tool for revealing specific functional biomarkers. This would eventually enhance the circular and effective use of rapeseed residuals coming from this plant’s oilseed industry. Full article

Demonstrating the authenticity and traceability of quality wines based on parameters that reflect their composition and provenance contributes to protecting wine authenticity and to increasing consumer confidence in moderate wine consumption, which is associated with numerous health-promoting properties. A wine’s phenolic fingerprint is increasingly used to assess its authenticity, even though wine phenolic composition is influenced by genetic and environmental factors, as well as vineyard management and enological practices, and storage conditions. This study presents a comprehensive analysis of the bioactive characteristics (total polyphenols—TPs, total flavonoids—TFs, antioxidant activity—AA, and total anthocyanins—TAs) by spectrophotometric analysis and phenolic compound profile (by UHPLC-HRMS analysis) of 19 white and 21 red wines with a Protected Designation of Origin (PDO) from four vineyards located in the wine-growing region of Oltenia, Romania. Multivariate statistical analysis, specifically principal component analysis and heat map analysis, applied to analytical data, enables the discrimination of wines based on grape variety and terroir, and across four consecutive vintages (2019–2022). The phenolic profiles of the wines obtained under standardized winemaking conditions depend on the climatic data specific to each harvest year (temperature, precipitation, duration of sun exposure during grape berry phenological stages, and ripening). The phenolic biomarkers of red wines, such as epicatechin, catechin, gallic, caffeic, t-ferulic acids, t-resveratrol and hesperidin, represent specific biomarkers of warmer and sunnier harvest years with lower precipitation, as observed in the 2021 harvest year. Additionally, our results contribute to the identification of specific phenolic biomarkers for geographical and varietal discrimination, as well as to the promotion of high-quality wines produced in a renowned wine-growing region of Romania. Full article

Fusarium fungi are widespread pathogens of food crops, primarily associated with the formation of mycotoxins. Therefore, effective mitigation strategies for these toxicogenic microorganisms are required. In this study, the potential of pulsed electric field (PEF) as an advanced technology of increasing use in the food processing industry was investigated to minimize the viability of Fusarium pathogens and to characterize the PEF-induced changes at the metabolomic level. Spores of four Fusarium species (Fusarium culmorum, Fusarium graminearum, Fusarium poae, and Fusarium sporotrichioides) were treated with PEF and cultured on potato dextrose agar (PDA) plates. The viability of the Fusarium species was assessed by counting the colony-forming units, and changes in the mycotoxin content and metabolomic fingerprints were evaluated by using UHPLC-HRMS/MS instrumental analysis. For metabolomic data processing and compound identification, the MS-DIAL (v. 4.80)–MS-CleanR–MS-Finder (v. 3.52) software platform was used. As we found out, both fungal viability and the ability to produce mycotoxins significantly decreased after the PEF treatment for all of the species tested. The metabolomes of the treated and untreated fungi showed statistically significant differences, and PEF-associated biomarkers from the classes oxidized fatty acid derivatives, cyclic hexapeptides, macrolides, pyranocoumarins, carbazoles, and guanidines were identified. Full article

Schizophrenia (SCH) is a major mental illness that causes impaired cognitive function and long-term disability, so the requirements for reliable biomarkers for early diagnosis and therapy of SCH are essential. The objective of this work was an untargeted lipidomic study of serum samples from a Serbian cohort including 30 schizophrenia (SCH) patients and 31 non-psychiatric control (C) individuals by applying liquid chromatography (LC) coupled with high-resolution mass spectrometry (HRMS) and chemometric analyses. Principal component analysis (PCA) of all samples indicated no clear separation between SCH and C groups but indicated clear gender separation in the C group. Multivariate statistical analyses (PCA and orthogonal partial least squares discriminant analysis (OPLS-DA)) of gender-differentiated SCH and C groups established forty-nine differential lipids in the differentiation of male SCH (SCH-M) patients and male controls (C-M), while sixty putative biomarkers were identified in the differentiation of female SCH patients (SCH-F) and female controls (C-F). Lipidomic study of gender-differentiated groups, between SCH-M and C-M and between SCH-F and C-F groups, confirmed that lipids metabolism was altered and the content of the majority of the most affected lipid classes, glycerophospholipids (GP), sphingolipids (SP), glycerolipids (GL) and fatty acids (FA), was decreased compared to controls. From differential lipid metabolites with higher content in both SCH-M and SCH-F patients groups compared to their non-psychiatric controls, there were four common lipid molecules: ceramides Cer 34:2, and Cer 34:1, lysophosphatidylcholine LPC 16:0 and triacylglycerol TG 48:2. Significant alteration of lipids metabolism confirmed the importance of metabolic pathways in the pathogenesis of schizophrenia. Full article

To comply with a more circular and environmentally friendly European common agricultural policy, while also valorising sunflower by-products, an ultrasound assisted extraction (UAE) was tested to optimise ethanol-wash solutes (EWS). Furthermore, the capabilities of DART-HRMS as a rapid and cost-effective tool for determining the biochemical changes after valorisation of these defatted sunflower EWS were investigated. Three batches of EWS were doubly processed into optimised EWS (OEWS) samples, which were analysed via DART-HRMS. Then, the metabolic profiles were submitted to a univariate analysis followed by a partial least square discriminant analysis (PLS-DA) allowing the identification of the 15 most informative ions. The assessment of the metabolomic fingerprinting characterising EWS and OEWS resulted in an accurate and well-defined spatial clusterization based on the retrieved pool of informative ions. The outcomes highlighted a significantly higher relative abundance of phenolipid hydroxycinnamoyl-glyceric acid and a lower incidence of free fatty acids and diglycerides due to the ultrasound treatment. These resulting biochemical changes might turn OEWS into a natural antioxidant supplement useful for controlling lipid oxidation and to prolong the shelf-life of foods and feeds. A standardised processing leading to a selective concentration of the desirable bioactive compounds is also advisable. Full article

Coffee consumption is expected to steadily rise in the next few years, with an increasing incidence of Coffea canephora on the market. To date, consumers are demanding high-quality and healthy beverages produced in an environmentally respectful manner. The study aimed to determine the optimal combination of acrylamide formation, sensory quality, and energy efficiency for blockchain-driven environmental accounting during the roasting process of C. canephora of different cups and market quality. Coffee was roasted in a professional 5 kg drum roaster at three speeds (fast, intermediate, and slow) and profiles, resulting in a medium roast degree. The quantification of acrylamide complied with the European legal benchmark across all roasting speeds, enabling a qualified panel to perform a sensory analysis of coffees in an espresso brew, including aroma and taste attributes. The chemical fingerprint of coffee was initially investigated through an untargeted metabolomics approach based on high-resolution mass spectrometry (UHPLC-Q-Orbitrap-HRMS). An ANOVA Multiblock Orthogonal Partial Least Squares analysis (AMOPLS) applied to metabolomics data enabled an accurate discrimination of coffee samples based on coffee market quality and roasting speed. Notably, their interaction was identified as a statistically significant discriminant factor (Residual Structure Ratio p-value = 0.01), with the highest contribution to the model (Relative Sum of Squares = 32.6%). The majority of metabolites detected through the VIP² approach belong to the lipid and lipid-like molecules chemical class, highlighting their pivotal role in defining the signature of C. canephora coffee. Regarding energy efficiency, the consumption recorded by the natural gas meter at the fast, intermediate, and slow speeds did not show significant differences. The roaster and gas valve employed may influence the efficacy of the “Energy Calculator” of the roasting program “Artisan” (v. 2.10.4), requiring an appropriate configuration. The optimized program resulted in a mean underestimation of real methane consumption by 0.207 kWh (SD 0.124), making it a promising tool for carbon emission calculation in coffee roasting. Moreover, further investigations will be performed to build a multi-omics approach by integrating the UHPLC-Q-Orbitrap-HRMS database with the volatilomic analysis performed by the GCxGC-MS technique to reveal the potential network between the chemical profile and the sensory characteristics of the samples. Full article

Raw milk cheeses harbor complex microbial communities. Some of these microorganisms are technologically essential, but undesirable microorganisms can also be present. While most of the microbial dynamics and cross-talking studies involving interaction between food-derived bacteria have been carried out on agar plates in laboratory-controlled conditions, the present study evaluated the modulation of the resident microbiota and the changes of metabolite production directly in ripening raw milk cheese inoculated with Listeria innocua strains. Using a proxy of the pathogenic Listeria monocytogenes, we aimed to establish the key microbiota players and chemical signals that characterize Latteria raw milk cheese over 60 days of ripening time. The microbiota of both the control and Listeria-inoculated cheeses was analyzed using 16S rRNA targeted amplicon sequencing, while direct analysis in real time mass spectrometry (DART-HRMS) was applied to investigate the differences in the metabolic profiles of the cheeses. The diversity analysis showed the same microbial diversity trend in both the control cheese and the inoculated cheese, while the taxonomic analysis highlighted the most representative genera of bacteria in both the control and inoculated cheese: Lactobacillus and Streptococcus. On the other hand, the metabolic fingerprints revealed that the complex interactions between resident microbiota and L. innocua were governed by continuously changing chemical signals. Changes in the amounts of small organic acids, hydroxyl fatty acids, and antimicrobial compounds, including pyroglutamic acid, hydroxy-isocaproic acid, malic acid, phenyllactic acid, and lactic acid, were observed over time in the L. innocua-inoculated cheese. In cheese that was inoculated with L. innocua, Streptococcus was significantly correlated with the volatile compounds carboxylbenzaldheyde and cyclohexanecarboxylic acid, while Lactobacillus was positively correlated with some volatile and flavor compounds (cyclohexanecarboxylic acid, pyroxidal acid, aminobenzoic acid, and vanillic acid). Therefore, we determined the metabolic markers that characterize a raw milk cheese inoculated with L. innocua, the changes in these markers with the ripening time, and the positive correlation of flavor and volatile compounds with the resident microbiota. This multi-omics approach could suggest innovative food safety strategies based on the enhanced management of undesirable microorganisms by means of strain selection in raw matrices and the addition of specific antimicrobial metabolites to prevent the growth of undesirable microorganisms. Full article

Torin1, a selective kinase inhibitor targeting the mammalian target of rapamycin (mTOR), remains widely used in autophagy research due to its potent autophagy-inducing abilities, regardless of its unspecific properties. Recognizing the impact of mTOR inhibition on metabolism, our objective was to develop a reliable and thorough untargeted metabolomics workflow to study torin1-induced metabolic changes in mouse embryonic fibroblast (MEF) cells. Crucially, our quality assurance and quality control (QA/QC) protocols were designed to increase confidence in the reported findings by reducing the likelihood of false positives, including a validation experiment replicating all experimental steps from sample preparation to data analysis. This study investigated the metabolic fingerprint of torin1 exposure by using liquid chromatography—high resolution mass spectrometry (LC-HRMS)-based untargeted metabolomics platforms. Our workflow identified 67 altered metabolites after torin1 exposure, combining univariate and multivariate statistics and the implementation of a validation experiment. In particular, intracellular ceramides, diglycerides, phosphatidylcholines, phosphatidylethanolamines, glutathione, and 5′-methylthioadenosine were downregulated. Lyso-phosphatidylcholines, lyso-phosphatidylethanolamines, glycerophosphocholine, triglycerides, inosine, and hypoxanthine were upregulated. Further biochemical pathway analyses provided deeper insights into the reported changes. Ultimately, our study provides a valuable workflow that can be implemented for future investigations into the effects of other compounds, including more specific autophagy modulators. Full article

The profile of secondary metabolites present in the apple cuticular layer is not only characteristic of a particular apple cultivar; it also dynamically reflects various external factors in the growing environment. In this study, the possibility of authenticating apple samples by analyzing their cuticular layer extracts was investigated. Ultra-high-performance liquid chromatography coupled with high-resolution tandem mass spectrometry (UHPLC-HRMS/MS) was employed for obtaining metabolomic fingerprints. A total of 274 authentic apple samples from four cultivars harvested in the Czech Republic and Poland between 2020 and 2022 were analyzed. The complex data generated, processed using univariate and multivariate statistical methods, enabled the building of classification models to distinguish apple cultivars as well as their geographical origin. The models showed very good performance in discriminating Czech and Polish samples for three out of four cultivars: “Gala”, “Golden Delicious” and “Idared”. Moreover, the validity of the models was tested over several harvest seasons. In addition to metabolites of the triterpene biosynthetic pathway, the diagnostic markers were mainly wax esters. “Jonagold”, which is known to be susceptible to mutations, was the only cultivar for which an unambiguous classification of geographical origin was not possible. Full article

Piper aduncum L. is widely distributed in tropical regions and the ethnobotanical uses of this species encompass medicinal applications for the treatment of respiratory, antimicrobial, and gynecological diseases. Chemical studies reveal a diverse array of secondary metabolites, including terpenes, flavonoids, and prenylated compounds. Extracts from P. aduncum have shown antibacterial, antifungal, and larvicidal activities. Our study explores the activity of extracts and partitions against Mycobacterium tuberculosis H37Rv, as well as the chemical diversity of the bioactive partition. This marks the first investigation of the bioactive partition of P. aduncum from agroecological cultivation. The ethyl acetate partition from the ethanolic leaf extract (PAEPL) was found to be the most active. PAEPL was subjected to column chromatography using Sephadex LH-20 and the obtained fractions were analyzed using UHPLC-HRMS/MS. The MS/MS data from the fractions were submitted to the online GNPS platform for the generation of the molecular network, which displayed 1714 nodes and 167 clusters. Compounds were identified via manual inspection and different libraries, allowing the annotation of 83 compounds, including flavonoids, benzoic acid derivatives, glycosides, free fatty acids, and glycerol-esterified fatty acids. This study provides the first chemical fingerprint of an antimycobacterial sample from P. aduncum cultivated in an agroecological system. Full article

Objective: To compare the effect of fermentation on the chemical constituents of Gastrodia Tuder Halimasch Powder (GTHP), to establish its fingerprinting and multicomponent content determination, and to provide a basis for the processing, handling, and clinical application of this herb. Methods: Ultra-high-performance liquid chromatography-quadrupole-Orbitrap high-resolution mass spectrometry (UHPLC-Q-Orbitrap HRMS) was used to conduct a preliminary analysis of the chemical constituents in GTHP before and after fermentation. High-performance liquid chromatography (HPLC) was used to determine some major differential components of GTHP and establish fingerprints. Cluster analysis (CA), and principal component analysis (PCA) were employed for comprehensive evaluation. Results: Seventy-nine compounds were identified, including flavonoids, organic acids, nucleosides, terpenoids, and others. The CA and PCA results showed that ten samples were divided into three groups. Through standard control and HPLC analysis, 10 compounds were identified from 22 peaks, namely uracil, guanosine, adenosine, 5-hydroxymethylfurfural (5-HMF), daidzin, genistin, glycitein, daidzein, genistein, and ergosterol. After fermentation, GTHP exhibited significantly higher contents of uracil, guanosine, adenosine, 5-hydroxymethylfurfural, and ergosterol and significantly lower genistein and daidzein contents. Conclusions: The UHPLC-Q-Orbitrap HRMS and HPLC methods can effectively identify a variety of chemical components before and after the fermentation of GTHP. This study provides a valuable reference for further research on the rational clinical application and quality control improvement of GTHP. Full article

Nowadays, the quality of natural products is an issue of great interest in our society due to the increase in adulteration cases in recent decades. Coffee, one of the most popular beverages worldwide, is a food product that is easily adulterated. To prevent fraudulent practices, it is necessary to develop feasible methodologies to authenticate and guarantee not only the coffee’s origin but also its variety, as well as its roasting degree. In the present study, a C18 reversed-phase liquid chromatography (LC) technique coupled to high-resolution mass spectrometry (HRMS) was applied to address the characterization and classification of Arabica and Robusta coffee samples from different production regions using chemometrics. The proposed non-targeted LC-HRMS method using electrospray ionization in negative mode was applied to the analysis of 306 coffee samples belonging to different groups depending on the variety (Arabica and Robusta), the growing region (e.g., Ethiopia, Colombia, Nicaragua, Indonesia, India, Uganda, Brazil, Cambodia and Vietnam), and the roasting degree. Analytes were recovered with hot water as the extracting solvent (coffee brewing). The data obtained were considered the source of potential descriptors to be exploited for the characterization and classification of the samples using principal component analysis (PCA) and partial least squares–discriminant analysis (PLS-DA). In addition, different adulteration cases, involving nearby production regions and different varieties, were evaluated by pairs (e.g., Vietnam Arabica—Vietnam Robusta, Vietnam Arabica—Cambodia and Vietnam Robusta—Cambodia). The coffee adulteration studies carried out with partial least squares (PLS) regression demonstrated the good capability of the proposed methodology to quantify adulterant levels down to 15%, accomplishing calibration and prediction errors below 2.7% and 11.6%, respectively. Full article

Oil-bearing Rosa rugosa are popular in the essential oil and perfume markets. The similar botanical characteristics between high-oil-yield or low-oil-yield cultivars are confusing and it is hard for farmers or breeders to identify the high-oil-yield cultivar by phenotype difference. High-resolution melting (HRM) analysis of simple sequence repeats (SSRs) can construct accurate DNA fingerprints quickly, which was shown to be effective for identification of closely related cultivars of R. rugosa. Optimization of HRM-SSR indicated that the 10 µL HRM reaction mixture containing 20 ng of genomic DNA of R. rugosa and 0.75 µL of 10 µmol/L of each primer with an annealing temperature of 64 °C was a robust SSR genotyping protocol. Using this protocol, 9 polymorphic SSR markers with 3–9 genotypes among the 19 R. rugosa cultivars were identified. The top three polymorphic makers SSR9, SSR12 and SSR19 constructed a fingerprint of all cultivars, and the rare insertion in the flanking sequences of the repeat motif of SSR19 generated three characteristic genotypes of three high-oil-yield cultivars. These results may be economical and practical for the identification of high-oil-yield R. rugosa and be helpful for the selection and breeding of oil-bearing roses. Full article

Nuclear and cytoplasmic DNA barcoding regions are useful for plant identification, breeding, and phylogenesis. In this study, the genetic diversity of 17 Diplotaxis species, was investigated with 5 barcode markers. The allelic variation was based on the sequences of chloroplast DNA markers including the spacer between trnL and trnF and tRNA-Phe gene (trnL-F), the rubisco (rbcl), the maturase K (matk), as well as the internal transcribed spacer (ITS) region of the nuclear ribosomal DNA. A highly polymorphic marker (HRM500) derived from a comparison of cytoplasmic genome sequences in Brassicaceae, was also included. Subsequently, a real-time PCR method coupled with HRM analysis was implemented to better resolve taxonomic relationships and identify assays suitable for species identification. Integration of the five barcode regions revealed a grouping of the species according to the common chromosomal set number. Clusters including species with n = 11 (D. duveryrieriana or cretacea, D. tenuifolia, D. simplex and D. acris), n = 8 (D. ibicensis, D. brevisiliqua and D. ilorcitana), and n = 9 (D. brachycarpa, D. virgata, D. assurgens, and D. berthautii) chromosomes were identified. Both phylogenetic analysis and the genetic structure of the collection identified D. siifolia as the most distant species. Previous studies emphasized this species’ extremely high glucosinolate content, particularly for glucobrassicin. High-resolution melting analysis showed specific curve patterns useful for the discrimination of the species, thus determining ITS1 as the best barcode for fingerprinting. Findings demonstrate that the approach used in this study is effective for taxa investigations and genetic diversity studies. Full article

(1) Background: Citrus honey constitutes a unique monofloral honey characterized by a distinctive aroma and unique taste. The non-targeted chemical analysis can provide pivotal information on chemical markers that differentiate honey based on its geographical and botanical origin. (2) Methods: Within the PRIMA project “PLANT-B”, a metabolomics workflow was established to unveil potential chemical markers of orange blossom honey produced in case study areas of Egypt, Italy, and Greece. In some of these areas, aromatic medicinal plants were cultivated to enhance biodiversity and attract pollinators. The non-targeted chemical analysis and metabolomics were conducted using ultra-high-performance liquid chromatography high-resolution mass spectrometry (UHPLC-HRMS). (3) Results: Forty compounds were disclosed as potential chemical markers, enabling the differentiation of the three orange blossom honeys according to geographical origin. Italian honey showed a preponderance of flavonoids, while in Greek honey, terpenoids and iridoids were more abundant than flavonoids, except for hesperidin. In Egyptian honey, suberic acid and a fatty acid ester derivative emerged as chemical markers. New, for honey, furan derivatives were identified using GC-MS in Greek samples. (4) Conclusions: The application of UHPLC-HRMS metabolomics combined with an elaborate melissopalynological analysis managed to unveil several potential markers of Mediterranean citrus honey potentially associated with citrus crop varieties and the local indigenous flora. Full article