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What metabolomics teaches us about wine shelf life
No full textThe metabolomics era started about 22 years ago, and wine was one of the first foodstuff subjects of analysis and investigation by this technique. Wine, which is most likely the richest food in terms of number of metabolites, was an excellent chemical model solution for chemists to explore the potentialities of this new technique, which enable untargeted study. Since then, metabolomics techniques were applied in several oenological studies shedding light on numerous questions from vine to glass. In fact, metabolomics techniques helped us to gain knowledge on the chemical modifications taking place during the wine aging and shelf life, which has a paramount importance since wine is one of the few foods that aging may improve its sensorial character and economical value. Recently, the combination of well-designed experiments, high-resolution mass spectrometers and modern informatic tools opened new roads for better understating how primary and secondary metabolites are modified during aging, and we learned new reactions taking place or followed in detailed reactions which were not very clear. This talk will provide a snapshot of recent publications regarding the behaviour of wine’s metabolome during shelf life
Study of the Chilean Cabernet Sauvignon wines metabolomic fingerprint
No full textChile is one the biggest exporters and producers of wine with an annually production of 12 million of hectoliters [1]. The vineyards in Chile covers a surface of 135.907 hectares including diverse valleys from Elqui to Malleco. The special geography of Chile can provide diverse climatic influences for the viticulture valleys ruled by the Andes mountains range in the east and Coastal range in the west. The north of Chile is very hot and dry, whereas in the south are colder and wet. Chilean wine production is focalized in Maule, O’Higgins and Metropolitan region. The 65.8% of Chilean wines with appellation of origin produced are red wines and the 28.7% of this production are Cabernet Sauvignon wines [2], thus mean is the more exported and commercialized Chilean wine. With the purpose to study the metabolomic fingerprint of the Chilean Cabernet Sauvignon, 50 wine samples were produced by grapes of different geographic origin (Maule, Colchagua, Maipo, Bío-Bío, Curicó, Cachapoal, Limarí and Valparaiso) and were analyzed by an untargeted LC-MS protocol [4]. In order to exclude the impact of the winemaking, the same standardized winemaking protocol was applied to all the samples. The analysis of the data is focused on the investigation of the behavior of a) the metabolomic fingerprint with a holistic way, and b) specific metabolites known for their importance in wine quality. Between the studied metabolites, were several anthocyanins derived by the grapes or produced during the winemaking
Introduction to FAIR principles about data, metadata and protocols in metabolomics
No full textIn 2016, a consortium of scientists (cheminformaticians, bioinformaticians, biologists, data scientists, computer scientists and representatives from data archives and publishers congregated) with the intention to provide guidelines to improve the findability , accessibility , interoperability and reusability of the digital assets, published the ‘FAIR Guiding Principles for scientific data management and stewardship’(Wilkinson et al., 2016). FAIR Guidelines are based on 15 Principles divided in 4 categories and cover Data, Metadata and Protocols.
Fondazione Edmund Mach (FEM) has a long experience in food, grape and wine metabolomics, while over the last years it’s Metabolomic platform shared several data using public repositories. This presentation will discuss FEM experiences, by reporting the workflow and the tools used from the experimental design to the data sharing, in order to respect the FAIR guidelines. In detail, will be discussed: a) the meta-data collection and organization; b) the instrumental parameters and set ups; c) the various protocol needed; d) the ontologies; e) the metabolites ID; f) the informatic tools; and g) the repositories.
Reference:
Wilkinson et al. The FAIR Guiding Principles for scientific data management and stewardship. Scientific Data, 3, 160018 (2016)
What did we learn the last years about the sulfonation of the proanthocyanidins in wine?
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Kinetic investigations of the Gewürztraminer volatile organic compounds and color at different temperatures and pHs
No full textGewürztraminer is a well-known wine famous for its aroma profile, which is characterized by rose petals, cloves, lychees, and other tropical fruit notes. It is cultivated worldwide, including the Trentino Alto Adige region located in northern Italy, especially in the Tramin zone, and it has long been studied trying to understand what the most characterizing volatile aroma components are [1-4]. The terpenes (geraniol, cis rose oxide, citronellol, and linalool) are between the major responsible for the characteristic floral aroma of this cultivar’s grapes and wines. Throughout the winemaking and storage, acid-catalysed rearrangements take place producing cyclic and hydroxylated forms of the above terpenes, which generally have minor perception thresholds and so the wine’s floral aroma character decreases [5]. It has been demonstrated that the temperature and pH strongly influence these reactions, however their kinetics are not studied in detail. The first aim of this work was to develop and validate a fast, modern, sensitive, selective, robust, and comprehensive protocol for the quantification of primary, secondary, and tertiary wine volatile compounds by using solid-phase extraction (SPE) cartridges for the sample preparation and a fast GC-MS/MS for analysis [1]. Second aim was to apply this protocol and study the kinetics of the reactions occurring on the Gewürztraminer wine volatile compounds during its storage at various temperatures and pHs. In parallel also the colour of the wines was monitored by using the CIELAB method. The produced method gave us the possibility to measure 64 aroma compounds, with big importance in wine science, by using fewer organic solvents, having short chromatographic run, and increasing specificity and sensitivity due to the MRM MS-mode used. The results of the second part of the study, demonstrated the behaviour of volatile aroma compounds, with their absolute concentrations. The investigated reactions included the degradation of the linear terpenes (linalool, geraniol, nerol, etc), the ethyl esters of fatty acids and volatile phenols on the one hand; and the formation of the cyclic terpenes (1,4-cineole, 1,8-cineole, terpineol, etc), the norisoprenoids (e.g. TDN and safranal) and the diprotic organic acids esters on the other hand. In conclusion, we developed a modern protocol for the analysis of the wine aroma compounds and we underlined some key characteristics that a winemaker should take in consideration in the Gewürztraminer production and aging/storage. References 1. Carlin, S.; Lotti, C.; Correggi, L.; Mattivi, F.; Arapitsas, P.; Vrhovsek, U. “Measurement of the effect of accelerated aging on the aromatic compounds of Gewürztraminer and Teroldego wines, using a new SPE-GC-MS /MS protocol” Metabolites 2022, 12(2), 180. 2. Versini, G. Sull’aroma Del Vino “Traminer Aromatico” o “Gewürztraminer.” VIGNEVINI 1985, 12, 57–65. 3. Guth, H. Identification of Character Impact Odorants of Different White Wine Varieties. J. Agric. Food Chem. 1997, 45, 3022–3026. 4. Román, T.; Tonidandel, T.; Larcher, R.; Celotti, E.; Nicolini, G. Importance of Polyfunctional Thiols on Semi-Industrial Gewürztraminer Wines and the Correlation to Technological Treatments. Eur. Food Res. Technol. 2018, 244, 379–386. 5. Slaghenaufi, D.; Ugliano, M. “Norisoprenoids, Sesquiterpenes and Terpenoids Content of Valpolicella Wines During Aging: Investigating Aroma Potential in Relationship to Evolution of Tobacco and Balsamic Aroma in Aged Wine.” Front. Chem. 2018, 6
D-wines: use of LC-MS metabolomic space to discriminate Italian mono-varietal red wines
No full textStudying wine metabolome through multiple targeted methods is complicated and limitative; since grapes,
yeasts, bacteria, oxygen, enological techniques and wine aging collaborate to deliver one of the richest metabolomic fingerprint. Therefore, untargeted metabolomics, that developed and evolved as a consequence of
the need to obtain a comprehensive characterization of the organic molecules in any biological sample, is the
current methodology offering the best coverage of wine metabolome. Taking into account the large genetic
diversity, the diversity of the climate and of the agronomical practices, and the wide winemaking culture
characterizing the Italian wines, the metabolomic untargeted approach appears as an appropriate analytical
tool to study such metabolic space.
According to the national project D-Wines, 110 single-cultivar red wines from the 2016 vintage were collected directly from wineries across different regions of Italy: Sangiovese from Tuscany and Romagna, Nebbiolo from Piemont, Aglianico from Campania, Nerello Mascalese from Sicily, Primitivo from Apulia, Raboso
and Corvina from Veneto, Cannonau from Sardinia, Teroldego from Trentino, Sagrantino from Umbria, and
Montepulciano from Abruzzo. The wines were analyzed according to a well-defined RP-UPLC-HRMSQTOF-MS protocol.
The results of the data analysis, after their validation: a) confirmed untargeted LC-MS-based metabolomics as a powerful authenticity tool; b) provided indications about the similarity between the cultivars,
clustering the wines in three major groups (Primitivo – Nebbiolo, Corvina, Raboso, Sangiovese – Teroldego, Sagrantino, Cannonau, Nerello, Aglianico, Montepulciano); c) furnished a rich list of putative markers
characterizing each cultivar, where Primitivo, Teroldego and Nebbiolo had the maximum number of unique
putative markers; d) revealed that the putative markers were not only phenolic metabolites; and e) pointed
out rt/mz chromatographic sections helpful to distinguish each cultivar from the others.
This study, together with other D-Wines analytical results, is directed to understand the diversity of Italian
red wines and to characterize them in term of metabolic space coverage/variability and taste and in consequence comprehend better their quality.
Acknowledgements: MIUR project N. 20157RN44Y. A. Curioni, A. Gambuti, V. Gerbi, S. Giacosa, G.P. Parpinello, D. Perenzoni, P. Piombino, A. Rinaldi, S. Río Segade, B. Simonato, G. Tornielli, S. Vincenz
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