Simultaneous Quantification of Organic Acids in Tamarillo (Solanum betaceum) and Untargeted Chemotyping Using Methyl Chloroformate Derivatisation and GC-MS

Sixteen organic acids were quantified in peel and pulp of Amber, Laird’s Large and Mulligan cultivars of tamarillo using GC-MS. Fourteen of these compounds had not previously been quantified in tamarillo. An untargeted metabolomics approach was used in parallel to identify and quantify 64 more metabolites relative to the internal standard, indicating abundances of glutamic acid, pro-line, aspartic acid and γ-aminobutyric acid as well as lower concentrations of several other essential fatty acids and amino acids. The main findings were that total organic acid concentration was significantly higher (p < 0.05) in pulp than in peel, with the highest concentration seen in Mulligan pulp (219.7 mg/g DW). Remarkably, after citric acid, the potent bactericide itaconic acid was the second most abundant organic acid. At least 95% of organic acids in tamarillo were one of these two acids, as well as cis-aconitic, malic and 4-toluic acids. Differences between cultivar chemotypes were as substantial as differences between tissues. These results suggest that the bitter flavour of the peel does not result from organic acids. The combination of targeted and untargeted metabolomics techniques for simultaneous qualitative and quantitative investigation of nutrients and flavours is efficient and informative.     

Comparison of Widely Targeted Metabolomics and Untargeted Metabolomics of Wild Ophiocordyceps sinensis

The authors of this paper conducted a comparative metabolomic analysis of Ophiocordyceps sinensis (OS), providing the metabolic profiles of the stroma (OSBSz) and sclerotia (OSBSh) of OS by widely targeted metabolomics and untargeted metabolomics. The results showed that 778 and 1449 metabolites were identified by the widely targeted metabolomics and untargeted metabolomics approaches, respectively. The metabolites in OSBSz and OSBSh are significantly differentiated; 71 and 96 differentially expressed metabolites were identified by the widely targeted metabolomics and untargeted metabolomics approaches, respectively. This suggests that these 71 metabolites (riboflavine, tripdiolide, bromocriptine, lumichrome, tetrahymanol, citrostadienol, etc.) and 96 metabolites (sancycline, vignatic acid B, pirbuterol, rubrophen, epalrestat, etc.) are potential biomarkers. 4-Hydroxybenzaldehyde, arginine, and lumichrome were common differentially expressed metabolites. Using the widely targeted metabolomics approach, the key pathways identified that are involved in creating the differentiation between OSBSz and OSBSh may be nicotinate and nicotinamide metabolism, thiamine metabolism, riboflavin metabolism, glycine, serine, and threonine metabolism, and arginine biosynthesis. The differentially expressed metabolites identified using the untargeted metabolomics approach were mainly involved in arginine biosynthesis, terpenoid backbone biosynthesis, porphyrin and chlorophyll metabolism, and cysteine and methionine metabolism. The purpose of this research was to provide support for the assessment of the differences between the stroma and sclerotia, to furnish a material basis for the evaluation of the physical effects of OS, and to provide a reference for the selection of detection methods for the metabolomics of OS.     

Characterising and correcting batch variation in an automated direct infusion mass spectrometry (DIMS) metabolomics workflow

Direct infusion mass spectrometry (DIMS)-based untargeted metabolomics measures many hundreds of metabolites in a single experiment. While every effort is made to reduce within-experiment analytical variation in untargeted metabolomics, unavoidable sources of measurement error are introduced. This is particularly true for large-scale multi-batch experiments, necessitating the development of robust workflows that minimise batch-to-batch variation. Here, we conducted a purpose-designed, eight-batch DIMS metabolomics study using nanoelectrospray (nESI) Fourier transform ion cyclotron resonance mass spectrometric analyses of mammalian heart extracts. First, we characterised the intrinsic analytical variation of this approach to determine whether our existing workflows are fit for purpose when applied to a multi-batch investigation. Batch-to-batch variation was readily observed across the 7-day experiment, both in terms of its absolute measurement using quality control (QC) and biological replicate samples, as well as its adverse impact on our ability to discover significant metabolic information within the data. Subsequently, we developed and implemented a computational workflow that includes total-ion-current filtering, QC-robust spline batch correction and spectral cleaning, and provide conclusive evidence that this workflow reduces analytical variation and increases the proportion of significant peaks. We report an overall analytical precision of 15.9 %, measured as the median relative standard deviation (RSD) for the technical replicates of the biological samples, across eight batches and 7 days of measurements. When compared against the FDA guidelines for biomarker studies, which specify an RSD of <20 % as an acceptable level of precision, we conclude that our new workflows are fit for purpose for large-scale, high-throughput nESI DIMS metabolomics studies.     

Comparative Evaluation of Different Targeted and Untargeted Analytical Approaches to Assess Greek Extra Virgin Olive Oil Quality and Authentication

Extra virgin olive oil (EVOO) is a key component of the Mediterranean diet, with several health benefits derived from its consumption. Moreover, due to its eminent market position, EVOO has been thoroughly studied over the last several years, aiming at its authentication, but also to reveal the chemical profile inherent to its beneficial properties. In the present work, a comparative study was conducted to assess Greek EVOOs’ quality and authentication utilizing different analytical approaches, both targeted and untargeted. 173 monovarietal EVOOs from three emblematic Greek cultivars (Koroneiki, Kolovi and Adramytiani), obtained during the harvesting years of 2018–2020, were analyzed and quantified as per their fatty acids methyl esters (FAMEs) composition via the official method (EEC) No 2568/91, as well as their bioactive content through liquid chromatography coupled to high resolution mass spectrometry (LC-HRMS) methodology. In addition to FAMEs analysis, EVOO samples were also analyzed via HRMS-untargeted metabolomics and optical spectroscopy techniques (visible absorption, fluorescence and Raman). The data retrieved from all applied techniques were analyzed with Machine Learning methods for the authentication of the EVOOs’ variety. The models’ predictive performance was calculated through test samples, while for further evaluation 30 commercially available EVOO samples were also examined in terms of variety. To the best of our knowledge, this is the first study where different techniques from the fields of standard analysis, spectrometry and optical spectroscopy are applied to the same EVOO samples, providing strong insight into EVOOs chemical profile and a comparative evaluation through the different platforms.     

Understanding the Impact of Key Wine Components on the Use of a Non-Swelling Ion-Exchange Resin for Wine Protein Fining Treatment

The impact of key classes of compounds found in wine on protein removal by the ion-exchange resin, Macro-Prep^® High S, was examined by adsorption isotherm experiments. A model wine system, which contained a prototypical protein Bovine Serum Albumin (BSA), was used. We systematically changed concentrations of individual chemical components to generate and compare adsorption isotherm plots and to quantify adsorption affinity or capacity parameters of Macro-Prep^® High S ion-exchange resin. The pH (hydronium ion concentration), ethanol concentration, and prototypical phenolics and polysaccharide compounds are known to impact interactions with proteins and thus could alter the adsorption affinity and capacity of Macro-Prep^® High S ion-exchange resin. At low equilibrium protein concentrations (< ~0.3 (g BSA)/L) and at high equilibrium protein concentrations in model wines at various pH, the adsorption behavior followed the Langmuir isotherm, most likely due to the resin acting as a monolayer adsorbent. The resulting range of BSA capacity was between 0.15–0.18 (g BSA)/(g Macro-Prep^® High S resin). With the addition of ethanol, catechin, caffeic acid, and polysaccharides, the protein adsorption behavior was observed to differ at higher equilibrium protein concentrations (> ~0.3 (g BSA)/L), likely as a result of Macro-Prep^® acting as an unrestricted multilayer adsorbent at these conditions. These data can be used to inform the design and scale-up of ion-exchange columns for removing proteins from wines.     

Smoked-Derived Volatile Phenol Analysis in Wine by Stir Bar Sorptive Extraction-Gas Chromatography-Mass Spectrometry

Smoke-derived taint has become a significant concern for the U.S. wine industry, particularly on the west coast, and climate change is anticipated to aggravate it. High volatile phenols such as guaiacol, 4-methylguaiacol, 4-ethylguaiacol, 4-ethylphenol, and o-, p-, m-cresols have been suggested to be related to smoke-exposed grape and wine. This paper describes an analytical approach based on ethylene glycol/polydimethylsiloxane (EG/PDMS)-stir bar sorptive extraction-gas chromatography-mass spectrometry (SBSE-GC-MS) to quantify or estimate the concentrations of some smoke-related volatile phenols in wines. Correlation coefficients with R² ≥ 0.990 were obtained. This method can quantify most smoked-related volatile phenols down to 0.5 μg/L in wine in selective ion monitoring mode. Recovery for the targeted volatile phenols ranged from 72.2% to 142.4% in the smoke-tainted wine matrix, except for 4-vinylguaiacol. The standard deviations of the volatile phenols were from 0 to 23% in smoke-tainted wine. The approach provides another tool to evaluate wine smoke exposure and potential smoke taint.     

1H-NMR Metabolomics as a Tool for Winemaking Monitoring

The chemical composition of wine is known to be influenced by multiple factors including some viticulture practices and winemaking processes. ¹H-NMR metabolomics has been successfully applied to the study of wine authenticity. In the present study, ¹H-NMR metabolomics in combination with multivariate analysis was applied to investigate the effects of grape maturity and enzyme and fining treatments on Cabernet Sauvignon wines. A total of forty wine metabolites were quantified. Three different stages of maturity were studied (under-maturity, maturity and over-maturity). Enzyme treatments were carried out using two pectolytic enzymes (E1 and E2). Finally, two proteinaceous fining treatments were compared (vegetable protein, fining F1; pea protein and PVPP, fining F2). The results show a clear difference between the three stages of maturity, with an impact on different classes of metabolites including amino acids, organic acids, sugars, phenolic compounds, alcohols and esters. A clear separation between enzymes E1 and E2 was observed. Both fining agents had a significant effect on metabolite concentrations. The results demonstrate that ¹H-NMR metabolomics provides a fast and robust approach to study the effect of winemaking processes on wine metabolites. These results support the interest to pursue the development of ¹H-NMR metabolomics to investigate the effects of winemaking on wine quality.     

Development of a Wine Metabolomics Approach for the Authenticity Assessment of Selected Greek Red Wines

Wine metabolomics constitutes a powerful discipline towards wine authenticity assessment through the simultaneous exploration of multiple classes of compounds in the wine matrix. Over the last decades, wines from autochthonous Greek grape varieties have become increasingly popular among wine connoisseurs, attracting great interest for their authentication and chemical characterization. In this work, 46 red wine samples from Agiorgitiko and Xinomavro grape varieties were collected from wineries in two important winemaking regions of Greece during two consecutive vintages and analyzed using ultra-high performance liquid chromatography-quadrupole time-of-flight mass spectrometry (UHPLC-QToF-MS). A targeted metabolomics methodology was developed, including the determination and quantification of 28 phenolic compounds from different classes (hydroxycinnamic acids, hydroxybenzoic acids, stilbenes and flavonoids). Moreover, 86 compounds were detected and tentatively identified via a robust suspect screening workflow using an in-house database of 420 wine related compounds. Supervised chemometric techniques were employed to build an accurate and robust model to discriminate between two varieties.     

D-optimal design of an untargeted HS-SPME-GC-TOF metabolite profiling method

In recent times we have seen the development of many "-omics" technologies. One of the youngest is undoubtedly metabolomics, which aims to define the whole chemical fingerprint unique to each specific organism. The development and optimisation of an untargeted high-throughput method capable of investigating the volatile fraction of a biological system represents a crucial step for the success of such holistic approaches, and specific optimisation criteria must be developed in connection with suitable experimental designs. In this paper experimental designs (D-optimal) were applied for the first time as an automatic optimisation tool to an untargeted HS-SPME-GC-TOF method. In this case, optimal conditions correspond to a maximal number of detected features, in order to provide a fingerprint that is as complete as possible. The system under study is the grape berry. Four variables were considered: the type of fibre, extraction time, equilibration time and temperature. The results show that the D-optimal design methodology provides an easily interpretable assessment of experimental settings. This and other specific properties of the D-optimal design, such as the possibility to explicitly exclude certain experimental conditions, make it an extremely suitable strategy for method optimisation in untargeted metabolomics.     

An improved pseudotargeted metabolomics approach using multiple ion monitoring with time-staggered ion lists based on ultra-high performance liquid chromatography/quadrupole time-of-flight mass spectrometry

Pseudotargeted metabolomics is a novel strategy integrating the advantages of both untargeted and targeted methods. The conventional pseudotargeted metabolomics required two MS instruments, i.e., ultra-high performance liquid chromatography/quadrupole-time- of-flight mass spectrometry (UHPLC/Q-TOF MS) and UHPLC/triple quadrupole mass spectrometry (UHPLC/QQQ-MS), which makes method transformation inevitable. Furthermore, the picking of ion pairs from thousands of candidates and the swapping of the data between two instruments are the most labor-intensive steps, which greatly limit its application in metabolomic analysis. In the present study, we proposed an improved pseudotargeted metabolomics method that could be achieved on an UHPLC/Q-TOF/MS instrument operated in the multiple ion monitoring (MIM) mode with time-staggered ion lists (tsMIM). Full scan-based untargeted analysis was applied to extract the target ions. After peak alignment and ion fusion, a stepwise ion picking procedure was used to generate the ion lists for subsequent single MIM and tsMIM. The UHPLC/Q-TOF tsMIM MS-based pseudotargeted approach exhibited better repeatability and a wider linear range than the UHPLC/Q-TOF MS-based untargeted metabolomics method. Compared to the single MIM mode, the tsMIM significantly increased the coverage of the metabolites detected. The newly developed method was successfully applied to discover plasma biomarkers for alcohol-induced liver injury in mice, which indicated its practicability and great potential in future metabolomics studies.     

New insights into the conversion of electropherograms to the effective electrophoretic mobility scale

CE–MS is increasingly gaining momentum as an analytical tool in metabolomics, due to its ability to obtain information about the most polar elements in biological samples. This has been helped by improvements of robustness in peak identification by means of mobility-scale representations of the electropherograms (mobilograms). As a necessary step toward facilitating the use of CE–MS for untargeted metabolomics data, the authors previously developed and introduced ROMANCE, a software automating mobilogram generation for large untargeted datasets through a simple and self-contained user interface. Herein, we introduce a new version of ROMANCE including new features such as compatibility with other types of data (targeted MS data and 2D UV-Vis absorption-like electropherograms), and the much needed additional flexibility in the transformation parameters (including field ramping and the use of secondary markers), more measurement conditions (depending on detection and integration modes), and most importantly tackling the issue of quantitative peak conversion. First, we present a review of the current theoretical framework with regard to peak characterization, and we develop new formulas for multiple marker peak area corrections, for anticipating peak position precision, and for assessing peak shape distortion. Then, the new version of the software is presented and validated experimentally. We contrast the multiple marker mobility transformations with previous results, finding increased peak position precision, and finally we showcase an application to actual untargeted metabolomics data.     

Composition of Pinot Noir Wine from Grapevine Red Blotch Disease-Infected Vines Managed with Exogenous Abscisic Acid Applications

Grapevine red blotch disease (GRBD) has negative effects on grape development and impacts berry ripening. Abscisic acid (ABA) is a plant growth regulator involved in the initiation of berry ripening. Exogenous abscisic acid application was compared to an unsprayed control on GRBD-positive Pinot noir vines during two vintages, and the total monomeric anthocyanin, total phenolics, phenolic composition, and volatile profile were measured in wines. In addition, untargeted metabolites were profiled using high-resolution LC-MS/MS. Results showed that the wine composition varied by vintage year and was not consistent with ABA application. Wines from the ABA treatment had a lower total anthocyanin and total phenolic content in one year. The untargeted high-resolution LC-MS/MS analysis showed a higher abundance of phenolic compounds in ABA wines in 2019, but lower in 2018. The wine volatile compounds of ABA treatments varied by vintage. There were higher levels of free β-damascenone, β-ionone, nerol, and several fermentation-derived esters, acids, and alcohols in ABA wines, but these were not observed in 2019. Lower 3-isobutyl-2-methoxypyrazine (IBMP) was also observed in wines with ABA treatment in 2019. The results demonstrated that ABA application to the fruit zones did not consistently mitigate the adverse impacts of GRBD on Pinot noir wines.     

PLS‐DA for compositional data with application to metabolomics

When quantifying information in metabolomics, the results are often expressed as data carrying only relative information. Vectors of these data have positive components, and the only relevant information is contained in the ratios between their parts; such observations are called compositional data. The aim of the paper is to demonstrate how partial least squares discriminant analysis (PLS‐DA)—the most widely used method in chemometrics for multivariate classification—can be applied to compositional data. Theoretical arguments are provided, and data sets from metabolomics are investigated. The data are related to the diagnosis of inherited metabolic disorders (IMDs). The first example analyzes the significance of the corresponding regression parameters (metabolites) using a small data set resulting from targeted metabolomics, where just a subset of potential markers is selected. The second example—the approach of untargeted metabolomics—was used for the analysis detecting almost 500 metabolites. The significance of the metabolites is investigated by applying PLS‐DA, accommodated according to a compositional approach. The significance of important metabolites (markers of diseases) is more clearly visible with the compositional method in both examples. Also, cross‐validation methods lead to better results in case of using the compositional approach. Copyright © 2014 John Wiley & Sons, Ltd.     

Comparison of a Rapid Light-Induced and Forced Test to Study the Oxidative Stability of White Wines

The oxidation processes of white wines can occur during storage and commercialization due to several factors, and these can negatively affect the color, aroma, and quality of the wine. Wineries should have faster and simpler methods that provide valuable information on oxidation stability of wines and allow fast decision-making procedures, able to trigger suitable technological interventions. Using a portable prototype instrument for light irradiations at different wavelengths and times was considered and evaluated on sensorial, spectrophotometric, and colorimetric parameters of white wines. The sensorial analysis revealed that white and light blue were the most significant, after only 1 h of irradiation. The experimental results showed that hydrogen peroxide could enhance the effect of light treatment, allowing a contemporary evaluation of the oxidation stability of wine against light and chemical stresses. As expected, a good correlation (R² > 0.89) between optical density at 420 nm and b* parameter was highlighted. The synergic effect of light and H₂O₂ was also studied on the hydrolyzable and condensed tannins’ additions to white wine. The proposed methodology could be used to evaluate the oxidative stability of white wines, but also to evaluate the effect of some oenological adjuvants on wine stability.     

Hybrid Electronic Tongue as a Tool for the Monitoring of Wine Fermentation and Storage Process

Hybrid electronic tongue based on potentiometric and voltammetric sensors was applied for the monitoring of wine production process. The sensor array formed by miniaturized ion‐selective electrodes and glassy carbon electrodes provided the analysis of the progress and correctness of wine fermentation and storage process, detection of the presence of disturbing factors and evaluation of the quality of final product. The efficiency of the proposed approach was compared with the monitoring of wine production carried out using standard reference methods. The results indicated that hybrid electronic tongue could be used as simple and reliable analytical tool dedicated to qualitative and quantitative assessment of wine production.     

High-Throughput Analysis of Amino Acids for Protein Quantification in Plant and Animal-Derived Samples Using High Resolution Mass Spectrometry

Current methods for measuring the abundance of proteogenic amino acids in plants require derivatisation, extended run times, very sensitive pH adjustments of the protein hydrolysates, and the use of buffers in the chromatographic phases. Here, we describe a fast liquid chromatography–mass spectrometry (LC–MS) method for the determination of amino acids that requires only three steps: hydrolysis, neutralisation, and sample dilution with a borate buffer solution for pH and retention time stability. The method shows excellent repeatability (repeated consecutive injections) and reproducibility (repeated hydrolysis) in the amino acid content, peak area, and retention time for all the standard amino acids. The chromatographic run time is 20 min with a reproducibility and repeatability of <1% for the retention time and <11% for the peak area of the BSA and quality control (QC) lentil samples. The reproducibility of the total protein levels in the hydrolysis batches 1–4 was <12% for the BSA and the lentil samples. The level of detection on column was below 0.1 µM for most amino acids (mean 0.017 µM).     

A Review of Ladybug Taint in Wine: Origins,Prevention, and Remediation

Ladybug taint (also known as ladybird taint) is a relatively recently recognized fault that has been identified in wines from a wide range of terroirs. Alkyl-methoxypyrazines—particularly 2-isopropyl-3-methoxypyrazine—have been determined as the causal compounds, and these are introduced into grape must during processing, when specific species of vineyard-dwelling Coccinellidae are incorporated into the harvested fruit. Coccinella septempunctata, and especially the invasive Harmonia axyridis, are the beetles implicated, and climate change is facilitating wider dispersal and survivability of H. axyridis in viticultural regions worldwide. Affected wines are typically characterized as possessing excessively green, bell pepper-, and peanut-like aroma and flavor. In this paper, we review a range of vineyard practices that seek to reduce Coccinellidae densities, as well as both “standard” and novel wine treatments aimed at reducing alkyl-methoxypyrazine load. We conclude that while prevention of ladybug taint is preferable, there are several winery interventions that can remediate the quality of wine affected by this taint, although they vary in their relative efficacy and specificity.     

Dried blood spot analysis with liquid chromatography and mass spectrometry: Trends in clinical chemistry

Dried blood spot samples are simple to prepare and transport, enabling safe and accessible diagnostics, both locally and globally. We review dried blood spot samples for clinical analysis, focusing on liquid chromatography-mass spectrometry as a versatile measurement tool for these samples. Dried blood spot samples can provide information for, for example, metabolomics, xenobiotic analysis, and proteomics. Targeted analyses of small molecules are the main application of dried blood spot samples and liquid chromatography-mass spectrometry, but emerging applications include untargeted metabolomics and proteomics. Applications are highly varied, including analyses related to newborn screening, diagnostics and monitoring of disease progression and treatment effects of virtually any disease, as well as studies into the physiology and effects of diet, exercise, xenobiotics, and doping. A range of dried blood spot products and methods are available, and applied liquid chromatography-mass spectrometry instrumentation is varied with regard to liquid chromatography column formats and selectivity. In addition, novel approaches such as on-paper sample preparation (e.g., selective trapping of analytes with paper-immobilized antibodies) are described. We focus on research papers published in the last 5 years.