Comprehensive two-dimensional gas chromatography with time-of-flight mass spectrometry combined with solid phase microextraction as a powerful tool for quantification of ethyl carbamate in fortified wines. The case study of Madeira wine

An analytical methodology based on headspace solid phase microextraction (HS-SPME) combined with comprehensive two-dimensional gas chromatography—time-of-flight mass spectrometry (GC × GC–ToFMS) was developed for the identification and quantification of the toxic contaminant ethyl carbamate (EC) directly in fortified wines. The method performance was assessed for dry/medium dry and sweet/medium sweet model wines, and for quantification purposes, calibration plots were performed for both matrices using the ion extraction chromatography (IEC) mode (m/z 62). Good linearity was obtained with a regression coefficient (r2) higher than 0.981. A good precision was attained (R.S.D. <20%) and low detection limits (LOD) were achieved for dry (4.31 μg/L) and sweet (2.75 μg/L) model wines. The quantification limits (LOQ) and recovery for dry wines were 14.38 μg/L and 88.6%, whereas for sweet wines were 9.16 μg/L and 99.4%, respectively. The higher performance was attainted with sweet model wine, as increasing of glucose content improves the volatile compound in headspace, and a better linearity, recovery and precision were achieved. The analytical methodology was applied to analyse 20 fortified Madeira wines including different types of wine (dry, medium dry, sweet, and medium sweet) obtained from several harvests in Madeira Island (Portugal). The EC levels ranged from 54.1 μg/L (medium dry) to 162.5 μg/L (medium sweet).

Investigation of urinary volatile organic metabolites as potential cancer biomarkers by solid-phase microextraction in combination with gas chromatography-mass spectrometry

BACKGROUND: Non-invasive diagnostic strategies aimed at identifying biomarkers of cancer are of great interest for early cancer detection. Urine is potentially a rich source of volatile organic metabolites (VOMs) that can be used as potential cancer biomarkers. Our aim was to develop a generally reliable, rapid, sensitive, and robust analytical method for screening large numbers of urine samples, resulting in a broad spectrum of native VOMs, as a tool to evaluate the potential of these metabolites in the early diagnosis of cancer. METHODS: To investigate urinary volatile metabolites as potential cancer biomarkers, urine samples from 33 cancer patients (oncological group: 14 leukaemia, 12 colorectal and 7 lymphoma) and 21 healthy (control group, cancer-free) individuals were qualitatively and quantitatively analysed. Dynamic solid-phase microextraction in headspace mode (dHS-SPME) using a carboxenpolydimethylsiloxane (CAR/PDMS) sorbent in combination with GC-qMS-based metabolomics was applied to isolate and identify the volatile metabolites. This method provides a potential non-invasive method for early cancer diagnosis as a first approach. To fulfil this objective, three important dHS-SPME experimental parameters that influence extraction efficiency (fibre coating, extraction time and temperature of sampling) were optimised using a univariate optimisation design. The highest extraction efficiency was obtained when sampling was performed at 501C for 60min using samples with high ionic strengths (17% sodium chloride, wv 1) and under agitation. RESULTS: A total of 82 volatile metabolites belonging to distinct chemical classes were identified in the control and oncological groups. Benzene derivatives, terpenoids and phenols were the most common classes for the oncological group, whereas ketones and sulphur compounds were the main classes that were isolated from the urine headspace of healthy subjects. The results demonstrate that compound concentrations were dramatically different between cancer patients and healthy volunteers. The positive rates of 16 patients among the 82 identified were found to be statistically different (Po0.05). A significant increase in the peak area of 2-methyl3-phenyl-2-propenal, p-cymene, anisole, 4-methyl-phenol and 1,2-dihydro-1,1,6-trimethyl-naphthalene in cancer patients was observed. On average, statistically significant lower abundances of dimethyl disulphide were found in cancer patients. CONCLUSIONS: Gas chromatographic peak areas were submitted to multivariate analysis (principal component analysis and supervised linear discriminant analysis) to visualise clusters within cases and to detect the volatile metabolites that are able to differentiate cancer patients from healthy individuals. Very good discrimination within cancer groups and between cancer and control groups was achieved.

Dynamic headspace solid-phase microextraction combined with one-dimensional gas chromatography–mass spectrometry as a powerful tool to differentiate banana cultivars based on their volatile metabolite profile

In this study the effect of the cultivar on the volatile profile of five different banana varieties was evaluated and determined by dynamic headspace solid-phase microextraction (dHS-SPME) combined with one-dimensional gas chromatography–mass spectrometry (1D-GC–qMS). This approach allowed the definition of a volatile metabolite profile to each banana variety and can be used as pertinent criteria of differentiation. The investigated banana varieties (Dwarf Cavendish, Prata, Maçã, Ouro and Platano) have certified botanical origin and belong to the Musaceae family, the most common genomic group cultivated in Madeira Island (Portugal). The influence of dHS-SPME experimental factors, namely, fibre coating, extraction time and extraction temperature, on the equilibrium headspace analysis was investigated and optimised using univariate optimisation design. A total of 68 volatile organic metabolites (VOMs) were tentatively identified and used to profile the volatile composition in different banana cultivars, thus emphasising the sensitivity and applicability of SPME for establishment of the volatile metabolomic pattern of plant secondary metabolites. Ethyl esters were found to comprise the largest chemical class accounting 80.9%, 86.5%, 51.2%, 90.1% and 6.1% of total peak area for Dwarf Cavendish, Prata, Ouro, Maçã and Platano volatile fraction, respectively. Gas chromatographic peak areas were submitted to multivariate statistical analysis (principal component and stepwise linear discriminant analysis) in order to visualise clusters within samples and to detect the volatile metabolites able to differentiate banana cultivars. The application of the multivariate analysis on the VOMs data set resulted in predictive abilities of 90% as evaluated by the cross-validation procedure.

Effectiveness of high-throughput miniaturized sorbent- and solid phase microextraction techniques combined with gas chromatography–mass spectrometry analysis for a rapid screening of volatile and semi-volatile composition of wines: a comparative study

In this study the feasibility of different extraction procedures was evaluated in order to test their potential for the extraction of the volatile (VOCs) and semi-volatile constituents (SVOCs) from wines. In this sense, and before they could be analysed by gas chromatography–quadrupole first stage masss spectrometry (GC–qMS), three different high-throughput miniaturized (ad)sorptive extraction techniques, based on solid phase extraction (SPE), microextraction by packed sorbents (MEPS) and solid phase microextraction (SPME), were studied for the first time together, for the extraction step. To achieve the most complete volatile and semi-volatile signature, distinct SPE (LiChrolut EN, Poropak Q, Styrene-Divinylbenzene and Amberlite XAD-2) and MEPS (C2, C8, C18, Silica and M1 (mixed C8-SCX)) sorbent materials, and different SPME fibre coatings (PA, PDMS, PEG, DVB/CAR/PDMS, PDMS/DVB, and CAR/PDMS), were tested and compared. All the extraction techniques were followed by GC–qMS analysis, which allowed the identification of up to 103 VOCs and SVOCs, distributed by distinct chemical families: higher alcohols, esters, fatty acids, carbonyl compounds and furan compounds. Mass spectra, standard compounds and retention index were used for identification purposes. SPE technique, using LiChrolut EN as sorbent (SPELiChrolut EN), was the most efficient method allowing for the identification of 78 VOCs and SVOCs, 63 and 19 more than MEPS and SPME techniques, respectively. In MEPS technique the best results in terms of number of extractable/identified compounds and total peak areas of volatile and semi-volatile fraction, were obtained by using C8 resin whereas DVB/CAR/PDMS was revealed the most efficient SPME coating to extract VOCs and SVOCs from Bual wine. Diethyl malate (18.8 ± 3.2%) was the main component found in wine SPELiChrolut EN extracts followed by ethyl succinate (13.5 ± 5.3%), 3-methyl-1-butanol (13.2 ± 1.7%), and 2-phenylethanol (11.2 ± 9.9%), while in SPMEDVB/CAR/PDMS technique 3-methyl-1-butanol (43.3 ± 0.6%) followed by diethyl succinate (18.9 ± 1.6%), and 2-furfural (10.4 ± 0.4%), are the major compounds. The major VOCs and SVOCs isolated by MEPSC8 were 3-methyl-1-butanol (26.8 ± 0.6%, from wine total volatile fraction), diethyl succinate (24.9 ± 0.8%), and diethyl malate (16.3 ± 0.9%). Regardless of the extraction technique, the highest extraction efficiency corresponds to esters and higher alcohols and the lowest to fatty acids. Despite some drawbacks associated with the SPE procedure such as the use of organic solvents, the time-consuming and tedious sampling procedure, it was observed that SPELiChrolut EN, revealed to be the most effective technique allowing the extraction of a higher number of compounds (78) rather than the other extraction techniques studied.

Allergic asthma exhaled breath metabolome: a challenge for comprehensive two-dimensional gas chromatography

Allergic asthma represents an important public health issue, most common in the paediatric population, characterized by airway inflammation that may lead to changes in volatiles secreted via the lungs. Thus, exhaled breath has potential to be a matrix with relevant metabolomic information to characterize this disease. Progress in biochemistry, health sciences and related areas depends on instrumental advances, and a high throughput and sensitive equipment such as comprehensive two-dimensional gas chromatography–time of flight mass spectrometry (GC × GC–ToFMS) was considered. GC × GC–ToFMS application in the analysis of the exhaled breath of 32 children with allergic asthma, from which 10 had also allergic rhinitis, and 27 control children allowed the identification of several hundreds of compounds belonging to different chemical families. Multivariate analysis, using Partial Least Squares-Discriminant Analysis in tandem with Monte Carlo Cross Validation was performed to assess the predictive power and to help the interpretation of recovered compounds possibly linked to oxidative stress, inflammation processes or other cellular processes that may characterize asthma. The results suggest that the model is robust, considering the high classification rate, sensitivity, and specificity. A pattern of six compounds belonging to the alkanes characterized the asthmatic population: nonane, 2,2,4,6,6-pentamethylheptane, decane, 3,6-dimethyldecane, dodecane, and tetradecane. To explore future clinical applications, and considering the future role of molecular-based methodologies, a compound set was established to rapid access of information from exhaled breath, reducing the time of data processing, and thus, becoming more expedite method for the clinical purposes.