Comparison of data processing strategies using commercial vs. open-source software in GC-Orbitrap-HRMS untargeted metabolomics analysis for food authentication: thyme geographical differentiation and marker identification as a case study.

Untargeted analysis of gas chromatography-high-resolution mass spectrometry (GC-HRMS) data is a key and time-consuming challenge for identifying metabolite markers in food authentication applications. Few studies have been performed to evaluate the capability of untargeted data processing tools for feature extraction, metabolite annotation, and marker selection from untargeted GC-HRMS data since most of them are focused on liquid chromatography (LC) analysis. In this framework, this study provides a comprehensive evaluation of data analysis tools for GC-Orbitrap-HRMS plant metabolomics data, including the open-source MS-DIAL software and commercial Compound Discoverer™ software (designed for Orbitrap data processing), applied for the geographical discrimination and search for thyme markers (Spanish vs. Polish differentiation) as the case study. Both approaches showed that the feature detection process is highly affected by unknown metabolites (Levels 4-5 of identification confidence), background signals, and duplicate features that must be carefully assessed before further multivariate data analysis for reliable putative identification of markers. As a result, Compound Discoverer™ and MS-DIAL putatively annotated 52 and 115 compounds at Level 2, respectively. Further multivariate data analysis allowed the identification of differential compounds, showing that the putative identification of markers, especially in challenging untargeted analysis, heavily depends on the data processing parameters, including available databases used during compound annotation. Overall, this method comparison pointed out both approaches as good options for untargeted analysis of GC-Orbitrap-HRMS data, and it is presented as a useful guide for users to implement these data processing approaches in food authenticity applications depending on their availability.

Exploring the bioaccessibility of polyphenols and glucosinolates from Brassicaceae microgreens by combining metabolomics profiling and computational chemometrics.

Microgreens constitute natural-based foods with health-promoting properties mediated by the accumulation of glucosinolates (GLs) and phenolic compounds (PCs), although their bioaccessibility may limit their nutritional potential. This work subjected eight Brassicaceae microgreens to in vitro gastrointestinal digestion and large intestine fermentation before the metabolomics profiling of PCs and GLs. The application of multivariate statistics effectively discriminated among species and their interaction with in vitro digestion phases. The flavonoids associated with arugula and the aliphatic GLs related to red cabbage and cauliflower were identified as discriminant markers among microgreen species. The multi-omics integration along in vitro digestion and fermentation predicted bioaccessible markers, featuring potential candidates that may eventually be responsible for these functional foods' nutritional properties. This combined analytical and computational framework provided a promising platform to predict the nutritional metabolome-wide outcome of functional food consumption, as in the case of microgreens.

The addition of polysaccharide gums to Aronia melanocarpa purees modulates the bioaccessibility of phenolic compounds and gut microbiota: A multiomics data fusion approach following in vitro digestion and fermentation.

This study aimed to determine how the addition of gellan, guar, locust bean, and xanthan gums affected the polyphenol profile of Aronia melanocarpa puree and the human gut microbiota after in vitro gastrointestinal digestion and large intestine fermentation. The different gums distinctively affected the content and bioaccessibility of phenolics in Aronia puree, as outlined by untargeted metabolomics. The addition of locust bean gum increased the levels of low-molecular-weight phenolics and phenolic acids after digestion. Gellan and guar gums enhanced phenolic acids' bioaccessibility after fermentation. Interactions between digestion products and fecal bacteria altered the composition of the microbiota, with the greatest impact of xanthan. Locust bean gum promoted the accumulation of different taxa with health-promoting properties. Our findings shed light on the added-value properties of commercial gums as food additives, promoting a distinctive increase of polyphenol bioaccessibility and shifting the gut microbiota distribution, depending on their composition and structural features.

Untargeted 1H NMR-based metabolomics and multi-technique data fusion: A promising combined approach for geographical and processing authentication of thyme by multivariate statistical analysis.

Thyme is a culinary herb highly susceptible to increasing mislabeling occurring in the spice industry. In this study, proton nuclear magnetic resonance spectroscopy (1H NMR) combined with multivariate statistics was successfully applied with two authenticity purposes: (1) tracing thyme metabolic differences among three relevant geographical regions (Morocco, Spain, and Poland), and (2) assessing the influence of sterilization processing on the metabolic fingerprint. Multivariate data analysis provided six and seven key geographical and processing markers, respectively, including thymol, organic acids, chlorogenic acid, and some carbohydrates (e.g., sucrose). Additionally, for the first time, a mid-level data fusion approach was tested for thyme authenticity combining three complementary and synergic analytical platforms: gas and liquid chromatography coupled with high-resolution mass spectrometry, and 1H NMR spectroscopy, providing a comprehensive metabolomics insight into the origin and processing effects on thyme fingerprinting, and opening the path to new metabolomics approaches for quality control in the spice industry.

UHPLC-QTOF-HRMS metabolomics insight on the origin and processing authentication of thyme by comprehensive fingerprinting and chemometrics.

The metabolic composition of thyme, one of the most used aromatic herbs, is influenced by environmental and post-harvest processing factors, presenting the possibility of exploiting thyme fingerprint to assess its authenticity. In this study, a comprehensive UHPLC-QTOF-HRMS fingerprinting approach was applied with a dual objective: (1) tracing thyme from three regions of production (Spain, Morocco, and Poland) and (2) evaluating the metabolic differences in response to processing, considering sterilized thyme samples. Multivariate statistics reveal 37 and 33 key origin and processing differentiation compounds, respectively. The findings highlighted the remarkable "terroir" influence on thyme fingerprint, noticing flavonoids, amino acids, and peptides among the most discriminant chemical classes. Thyme sterilization led to an overall metabolite enrichment, most likely due to the facilitated compound accessibility as a result of processing. The findings provide a comprehensive metabolomics insight into the origin and processing effect on thyme composition for product traceability and quality assessment.

An untargeted strategy based on UHPLC-QTOF-HRMS metabolomics to identify markers revealing the terroir and processing effect on thyme phenolic profiling.

Thyme is one of Europe's most consumed aromatic herbs and represents a matrix susceptible to intentional mislabelling and food frauds. In this study, a phenolic profiling approach based on UHPLC-QTOF-HRMS untargeted metabolomics was used to trace its geographical origin, as well as to assess the effect of post-harvest processing by comparing sterilized vs non-sterilized thyme. Both unsupervised and supervised statistics led to reliable sample clustering, high-quality model parameters, as well as the identification of a total of 45 differential compounds (markers) for discrimination purposes. The phenolic signature was markedly affected by environmental conditions related to the region of production, leading to an overall higher abundance of flavonoids in Moroccan thyme (from Fez), flavanols in Polish one (from Lublin), and tyrosols and other phenolics in thyme cultivated in Spain (from Castilla-La Mancha). The processing was also shown to play an important role in phenolic profiling, noticing not only the decrease of thermolabile phenolics (such as flavonoids) but also the enhancement of other phenolic subfamilies in response to sterilization. This study opens the path to novel metabolomics-based strategies to support the integrity of thyme and possibly other spices, scarcely studied so far.

Fingerprinting based on gas chromatography-Orbitrap high-resolution mass spectrometry and chemometrics to reveal geographical origin, processing, and volatile markers for thyme authentication.

Thyme is an aromatic herb traditionally used for food purposes due to its organoleptic characteristics and medicinal properties, which is highly susceptible to food fraud. In this study, GC-HRMS-based fingerprinting was applied for the first time to determine the geographical traceability of thyme based on different origins (Spain, Poland, and Morocco), as well as to assess its processing by comparing sterilized vs. non-sterilized thyme. Unsupervised chemometric methods (PCA and HCA) revealed a predominant influence of the geographical origin on thyme fingerprints rather than processing effects. Supervised PLS-DA and OPLS-DA were used for discrimination purposes, revealing high predictive ability for further samples (100%), and allowing the identification of differential compounds (markers). A total of 24 markers were putatively identified (13 metabolites were confirmed) belonging to different classes: monoterpenoids, diterpenoids, sesquiterpenoids, alkenylbenzenes, and other miscellaneous compounds. This study outlines the potential of combining untargeted analysis by GC-HRMS with chemometrics for thyme authenticity and traceability.

Persistent organic pollutants (PCBs and PCDD/Fs), PAHs, and plasticizers in spices, herbs, and tea - A review of chromatographic methods from the last decade (2010-2020).

Edible and highly demanded plant-derived products such as herbs, spices, and tea may be subjected to exogenous contamination of well-known chemical hazards such as persistent organic pollutants (POPs), and emerging ones such as plasticizers, affecting negatively the safety of these food commodities. This fact has led to the increasing analysis of exogenous compounds including priority POPs such as polychlorinated dibenzo-p-dioxins (PCDDs) and polychlorinated dibenzofurans (PCDFs), and polychlorinated biphenyls (PCBs), as well as highly persistent polycyclic aromatic hydrocarbons (PAHs). Currently, plasticizer residues are also considered an emerging issue because of the extensive use in food packaging and potential migration into foodstuffs. In this review, the studies published from 2010 to 2020 were discussed, including the main extraction methods applied for these contaminants from herbs, spices, and tea, and it was revealed the trend toward the use of less solvent-consuming and time-effective methods. Chromatographic methods were also described, which were mainly combined with detection techniques such as classical or mass spectrometry (MS) detection. Finally, a comprehensive overview of the occurrence of these selected exogenous compounds was presented in the studied matrices, showing that their monitoring should be further investigated to ensure food safety of highly consumed condiments and tea.

Application of an innovative metabolomics approach to discriminate geographical origin and processing of black pepper by untargeted UHPLC-Q-Orbitrap-HRMS analysis and mid-level data fusion.

An untargeted metabolomics approach based on ultra-high performance liquid chromatography coupled to high-resolution mass spectrometry (UHPLC-HRMS) fingerprinting was applied to investigate the metabolic differences of black pepper among three geographical origins (Sri Lanka, Vietnam, and Brazil) and two post-harvest processing (sterilized and non-sterilized spice). Principal component analysis (PCA) was employed to assess the overall clustering of samples, whereas supervised orthogonal partial least squares discriminant analysis (OPLS-DA) was effectively used for discrimination purposes. OPLS-DA models were fully validated (R2Y and Q2 values > 0.5) and the variable importance in projection (VIP) approach was employed to provide valuable data about differential metabolites with high discrimination potential (8 markers were putatively identified). For origin differentiation, three markers were highlighted with VIP values > 1.5 (i.e. reynosin, artabsinolide D, and tatridin B). Fatty acid derivates were the most frequent markers within the metabolites annotated for processing discrimination (e.g. 10,16-dihydroxyhexadecanoic acid and 9-hydroperoxy-10E-octadecenoic acid). Additionally, different combinations of mid-level data fusion of chromatographic-mass spectrometric techniques (UHPLC and gas chromatography coupled to HRMS) and proton nuclear magnetic resonance spectroscopy (1H NMR) were evaluated for the first time for geographical and processing discrimination of black pepper. The NMR-UHPLC-GC mid-level fused model was preferred among the tested fusion approaches since good sample clustering and no misclassification were achieved. Enhanced correct classification rate was achieved by mid-level data fusion compared with the findings obtained for one of the individual techniques (1H NMR fingerprinting) (from 92% to 100% of samples correctly classified). This study opens the path to new metabolomics approaches for black pepper authentication and quality control.

Feasibility of Applying Untargeted Metabolomics with GC-Orbitrap-HRMS and Chemometrics for Authentication of Black Pepper (Piper nigrum L.) and Identification of Geographical and Processing Markers.

Black pepper is one of the most consumed spices all over the world. Due to its high demand and nutritional value, a metabolomics approach based on GC-Orbitrap-HRMS fingerprinting and chemometrics was applied to assess its geographical traceability and processing authenticity. GC-HRMS-based fingerprints were obtained using a simple ultrasound-assisted extraction method, which may be easily implemented in routine activities of quality control. Unsupervised methods, such as principal component analysis (PCA), were performed for sample overview according to the investigated origins (Brazil, Vietnam, and Sri Lanka) and processing (sterilized vs nonsterilized samples). Further orthogonal partial least squares discriminant analysis (OPLS-DA) models were validated by cross- and external validation, providing satisfactory performance for geographical and processing authentication, as well as excellent predictive ability for further samples. Furthermore, reliable putative identification of 12 key metabolites (markers) was performed, highlighting the feasibility of combining untargeted GC-HRMS analysis with chemometrics for quality control of black pepper.

A new strategy based on gas chromatography-high resolution mass spectrometry (GC-HRMS-Q-Orbitrap) for the determination of alkenylbenzenes in pepper and its varieties.

Alkenylbenzenes are natural toxins with genotoxic and carcinogenic effects in rodents, which are highly present in condiments frequently consumed. The aim of this study was the development of the first multi-analyte method for the determination of eight alkenylbenzenes (eugenol, methyl eugenol, acetyl eugenol, trans-isoeugenol, safrole, estragole, myristicin and trans-anethole) in different pepper varieties by gas chromatography coupled to high-resolution mass spectrometry (GC-HRMS-Q-Orbitrap) in combination with a simple ultrasound-assisted extraction method (UAE). The method was successfully validated, and it was applied for studying the presence of these analytes in peppers as well as to elucidate the effects of the berries' maturity and the geographical origin on alkenylbenzene contents. The analysis of the pepper samples showed that eugenol (10.5-120 mg/kg), trans-anethole (10.7-42.7 mg/kg) and estragole (2.2-45.7 mg/kg) tended to be the most detected alkenylbenzenes at high levels, whereas trans-isoeugenol (0.69-3.6 mg/kg) and safrole (0.20-3.0 mg/kg) were minor components. Estragole (PubChem CID: 8815); trans-anethole (PubChem CID: 637563); Myristicin (PubChem CID: 4276); Safrole (PubChem CID: 5144); Eugenol (PubChem CID: 3314); Methyl eugenol (PubChem CID: 7127); Acetyl eugenol (PubChem CID: 7136); trans-Isoeugenol (PubChem CID: 853433); Caffeine (PubChem CID: 2519); Dicyclohexylmethanol (PubChem CID: 78197).