Pietro Franceschi

LC-MS based global metabolite profiling of grapes: solvent extraction protocol optimisation

Optimal solvent conditions for grape sample preparation were investigated for the purpose of metabolite profiling studies, with the aim of obtaining as many features as possible with the best analytical repeatability. Mixtures of water, methanol and chloroform in different combinations were studied as solvents for the extraction of ground grapes. The experimental design used a two stage study to find the optimum extraction medium. The extracts obtained were further purified using solid phase extraction and analysed using a UPLC full scan TOF MS with both reversed phase and hydrophilic interaction chromatography. The data obtained were processed using data extraction algorithms and advanced statistical software for data mining. The results obtained indicated that a fairly broad optimal area for solvent composition could be identified, containing approximately equal amounts of methanol and chloroform and up to 20% water. Since the water content of the samples was variable, the robustness of the optimal conditions suggests these are appropriate for large scale profiling studies for characterisation of the grape metabolome.

Stability-based biomarker selection.

Biomarker identification, i.e., finding those variables that indicate true differences between two or more populations, is an ever more important topic in the omics sciences. In most cases, the number of variables far exceeds the number of samples, making biomarker identification extremely difficult. We present a strategy based on the stability of putative biomarkers under perturbation of the data, and show that in several cases important gains can be achieved. The strategy is very general and can be applied with all common biomarker identification methods; it also has the advantage that it does not rely on error estimates from crossvalidation, that in this setting tend to be highly variable.

A benchmark spike-in data set for biomarker identification in metabolomics

The development and the validation of innovative approaches for biomarker selection are of paramount importance in many ‐omics technologies. Unfortunately, the actual testing of new methods on real data is difficult, because in real data sets, one can never be sure about the “true” biomarkers. In this paper, we present a publicly available metabolomic ultra performance liquid chromatography–mass spectrometry spike‐in data set for apples. The data set consists of 10 control samples and three spiked sets of the same size, where naturally occurring compounds are added in different concentrations. In this sense, the data set can serve as a test bed to assess the performance of new algorithms and compare them with previously published results.

Regional features of northern Italian sparkling wines, identified using solid-phase micro extraction and comprehensive two-dimensional gas chromatography coupled with time-of-flight mass spectrometry

We carried out comprehensive mapping of volatile compounds in 70 wines, from 48 wineries and 6 vintages, representative of the two main production areas for Italian sparkling wines, by HS-SPME-GCxGC-TOF-MS and multivariate analysis. The final scope was to describe the metabolomics space of these wines, and to verify whether the grape cultivar signature, the pedoclimatic influence of the production area, and the complex technology were measurable in the final product. The wine chromatograms provided a wealth of information, with 1695 compounds being found. A large number of putative markers influenced by the cultivation area was observed. A subset of 196 biomarkers fully discriminated between the two types of sparkling wines investigated. Among the new compounds, safranal and α-isophorone were observed. We showed how correlation-based network analysis could be used as a tool to detect the differences in compound behaviour based on external/environmental influences.

Core Microbiota and Metabolome of Vitis vinifera L. cv. Corvina Grapes and Musts

The composition and changes of the fungal population and of the metabolites present in grapes and in ferments of Vitis vinifera L. cv. Corvina, one of the major components of the Amarone musts, were dissected aiming at the identification of constant characteristics possibly influenced by the productive process. The fungal populations and metabolomic profiles were analyzed in three different vintages. 454-pyrosequencing on the ribosomal ITS1 region has been used to identify the fungal population present in Corvina grapes and fresh must. Samples were also subjected to metabolomics analysis measuring both free volatile compounds and glycosylated aroma precursors through an untargeted approach with comprehensive two-dimensional gas chromatography time-of-flight mass spectrometry. Albeit strongly dependent on the climate, both the mycobiota and metabolome of Corvina grapes and fresh musts show some characteristics recursive in different vintages. Such persistent characteristics are likely determined by the method adopted to produce Amarone or other dry wines made from partially dried grapes. In particular, the harsh conditions imposed by the prolonged withering appear to contribute to the shaping of the fungal populations. The fungal genera and metabolites present in different vintages in V. vinifera L. cv. Corvina grapes and fresh musts represent core components of the peculiar technique of production of Amarone. Their identification allows the in-depth understanding and improved control of the process of production of this economically and culturally relevant wine.

H, C, and O Stable Isotope Ratios of Passito Wine

In this study we investigated the effect of the grape withering process occurring during the production of Italian passito wines on the variability of the (D/H)I, (D/H)II, δ(13)C, and δ(18)O of wine ethanol and the δ(18)O of wine water. The production of PDO Erbaluce di Caluso Passito in five different cellars in Piedmont (Italy) was considered in two successive years. Moreover, samples of 17 different traditional Italian passito wines taken at different stages of maturation were taken into account. We found that the δ(18)O of must and wine water and the δ(18)O of ethanol decrease in the case of passito wines produced in northern and central Italy using postharvest drying of the grapes in dedicated ventilated or unventilated fruit drying rooms (fruttaio), during autumn-winter. For passito wines produced in southern Italy, where the main technique involves withering on the plant (en plein air), δ(18)O tends to increase. The (DH)I of wine ethanol did not change during withering, whereas the (DH)II and δ(13)C values changed slightly, but without any clear trend. Particular attention must be therefore paid in the evaluation of the δ(18)O data of passito wines for fraud detection.

Applying generalized additive models to unravel dynamic changes in anthocyanin biosynthesis in methyl jasmonate elicited grapevine ( Vitis vinifera cv. Gamay) cell cultures

Plant cell cultures represent important model systems to understand metabolism and its modulation by regulatory factors. Even in controlled conditions, cell metabolism is highly dynamic and can be fully characterized only by time course experiments. Here, we show that statistical analysis of this type of data gains power if it moves to approaches able to compare the ‘trends’ of the different metabolites. In particular, we show how generalized additive models can be used to model the time-dependent profile of anthocyanin synthesis in grapevine cell suspension cultures (Vitis vinifera cv. Gamay), following treatment with 100 μm methyl jasmonate. The sampling was performed daily for 20 days of culturing following elicitation at day 5. All samples were analyzed by UPLC-MS/MS for the identification and quantification of fifteen anthocyanin compounds. The models confirmed the separation in the anthocyanin biosynthetic pathway between delphinidin-based and cyanidin-based compounds, showing that methyl jasmonate modulates the anthocyanin concentration profiles. Our results clearly indicate that the combination of high-throughput metabolomics and state of the art statistical modeling is a powerful approach to study plant metabolism. This approach is expected to gain popularity due to the growing availability of low-cost high-throughput ‘omic’ assays.

IsotopicLabelling: an R package for the analysis of MS isotopic patterns of labelled analytes

Motivation: Labelling experiments in biology usually make use of isotopically enriched substrates, with the two most commonly employed isotopes for metabolism being 2H and 13C. At the end of the experiment some metabolites will have incorporated the labelling isotope, to a degree that depends on the metabolic turnover. In order to propose a meaningful biological interpretation, it is necessary to estimate the amount of labelling, and one possible route is to exploit the fact that MS isotopic patterns reflect the isotopic distributions. Results: We developed the IsotopicLabelling R package, a tool able to extract and analyze isotopic patterns from liquid chromatography-mass spectrometry (LC-MS) and gas chromatography-MS (GC-MS) data relative to labelling experiments. This package estimates the isotopic abundance of the employed stable isotope (either 2H or 13C) within a specified list of analytes. Availability and Implementation: The IsotopicLabelling R package is freely available at https://github.com/RuggeroFerrazza/IsotopicLabelling. Contacts: r.ferrazza@unitn.it Supplementary information: Supplementary data are available at Bioinformatics online.

Characterisation and attempted differentiation of European and extra-European olive oils using stable isotope ratio analysis

European law requires a designation of origin for virgin and extra virgin olive oils (at least in terms of EU/non-EU provenance). Stable isotope ratios have been successfully applied to determine the geographical origin of olive oils, but never to distinguish EU and non-EU oils. In this study 2H/1H, 13C/12C and 18O/16O ratios were analysed in bulk olive oils using Isotope Ratio Mass Spectrometry (IRMS) as well as 13C/12C and 2H/1H in the four main fatty acids (linoleic, oleic, palmitic and stearic acids) using IRMS coupled with GC. The isotopic composition of olive oils was successfully used to distinguish samples originating in the two areas. Specifically, when bulk data were combined with fatty acid isotopic data the differentiation power of the method improved clearly. This separation is due to the specific isotopic fingerprint of the individual countries making up the EU and non-EU samples.

ONS: an ontology for a standardized description of interventions and observational studies in nutrition

BackgroundThe multidisciplinary nature of nutrition research is one of its main strengths. At the same time, however, it presents a major obstacle to integrate data analysis, especially for the terminological and semantic interpretations that specific research fields or communities are used to. To date, a proper ontology to structure and formalize the concepts used for the description of nutritional studies is still lacking.ResultsWe have developed the Ontology for Nutritional Studies (ONS) by harmonizing selected pre-existing de facto ontologies with novel health and nutritional terminology classifications. The ONS is the result of a scholarly consensus of 51 research centers in nine European countries. The ontology classes and relations are commonly encountered while conducting, storing, harmonizing, integrating, describing, and searching nutritional studies. The ONS facilitates the description and specification of complex nutritional studies as demonstrated with two application scenarios.ConclusionsThe ONS is the first systematic effort to provide a solid and extensible formal ontology framework for nutritional studies. Integration of new information can be easily achieved by the addition of extra modules (i.e., nutrigenomics, metabolomics, nutrikinetics, and quality appraisal). The ONS provides a unified and standardized terminology for nutritional studies as a resource for nutrition researchers who might not necessarily be familiar with ontologies and standardization concepts.