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In this review, we consider and discuss the affinity and complementarity between a generic sample preparation technique and the comprehensive two-dimensional gas chromatography process. From the initial technical development focus (e.g., on the GC×GC and solid-phase microextraction techniques), the trend is inevitably shifting toward more applied challenges, and therefore, the preparation of the sample should be carefully considered in any GC×GC separation for an overreaching research. We highlight recent biomedical, food, and plant applications (2016-July 2020), and specifically those in which the combination of tailored sample preparation methods and GC×GC-MS has proven to be beneficial in the challenging aspects of non-targeted analysis. Specifically on the sample preparation, we report on gas-phase, solid-phase, and liquid-phase extractions, and derivatization procedures that have been used to extract and prepare volatile and semi-volatile metabolites for the successive GC×GC analysis. Moreover, we also present a milestone section reporting the early works that pioneered the combination of sample preparation techniques with GC×GC for non-targeted analysis.

Headspace gas chromatography is frequently used for aroma profiling thanks to its ability to naturally exploit the volatility of aroma compounds, and also to provide chemical information on sample composition. Its main advantages rely on simplicity, no use of solvent, amenability to automation, and the cleanliness of the extract. In the present contribution, the most effective sampling (dynamic extraction), separation (multidimensional gas chromatography), and detection (mass spectrometry) techniques for untargeted analysis are exploited in combination, showing their potential in unraveling aroma profiles in fruit beers. To complete the overall analytical process, a neat workflow for data analysis is discussed and used for the successful characterization and identification of five different beer flavors (berries, cherry, banana, apple, and peach). From the technical viewpoint, the coupling of purge-and-trap, comprehensive two-dimensional gas chromatography, and mass spectrometry makes the global methodology unique, and it is for the first time discussed. A (low-)flow modulation approach allowed for the full transfer into the second dimension with mass-spectrometry compatible flow (< 7 mL/min), avoiding the need of splitting before detection and making the overall method sensitive (1.2-5.2-fold higher signal to noise ratio compared to unmodulated gas chromatography conditions) and selective.

In the host, pathogenic microorganisms have developed stress responses to cope with constantly changing environments. Stress responses are directly related to changes in several metabolomic pathways, which could hamper microorganisms' unequivocal identification. We evaluated the effect of various in vitro stress conditions (acidic, basic, oxidative, ethanolic, and saline conditions) on the metabolism of Staphylococcus aureus, Bacillus cereus, and Pseudomonas aeruginosa, which are common lung pathogens. The metabolite profiles of the bacteria were analyzed using liquid chromatography coupled to triple quadrupole and quadrupole time-of-flight mass spectrometry. The advantages of targeted and untargeted analysis combined with univariate and multivariate statistical analysis (principal component analysis, hierarchical cluster analysis, partial least square discriminant analysis, random forest) were combined to unequivocally identify bacterial species. In normal in vitro conditions, the targeted methodology, based on the analysis of primary metabolites, enabled the rapid and efficient discrimination of the three bacteria. In changing in vitro conditions and specifically in presence of the various stressors, the untargeted methodology proved to be more valuable for the global and accurate differentiation of the three bacteria, also considering the type of stress environment within each species. In addition, species-specific metabolites (i.e., fatty acids, polysaccharides, peptides, and nucleotide bases derivatives) were putatively identified. Good intra-day repeatability and inter-day repeatability (< 10% RSD and < 15% RSD, respectively) were obtained for the targeted and the untargeted methods. This untargeted approach highlights its importance in unusual (and less known) bacterial growth environments, being a powerful tool for infectious disease diagnosis, where the accurate classification of microorganisms is sought.

Species of Mycobacteriaceae cause disease in animals and humans, including tuberculosis and leprosy. Individuals infected with organisms in the Mycobacterium tuberculosis complex (MTBC) or non-tuberculous mycobacteria (NTM) may present identical symptoms, however the treatment for each can be different. Although the NTM infection is considered less vital due to the chronicity of the disease and the infrequency of occurrence in healthy populations, diagnosis and differentiation among Mycobacterium species currently require culture isolation, which can take several weeks. The use of volatile organic compounds (VOCs) is a promising approach for species identification and in recent years has shown promise for use in the rapid analysis of both in vitro cultures as well as ex vivo diagnosis using breath or sputum. The aim of this contribution is to analyze VOCs in the culture headspace of seven different species of mycobacteria and to define the volatilome profiles that are discriminant for each species. For the pre-concentration of VOCs, solid-phase micro-extraction (SPME) was employed and samples were subsequently analyzed using gas chromatography–quadrupole mass spectrometry (GC-qMS). A machine learning approach was applied for the selection of the 13 discriminatory features, which might represent clinically translatable bacterial biomarkers.

The present research reports on the development of a methodology to unravel the complex phytochemistry of cannabis. Specifically, cannabis inflorescences were considered and stir bar sorptive extraction (SBSE) was used for the preconcentration of the metabolites. Analytes were thermally desorbed into a comprehensive two-dimensional (2D) gas chromatography (GC × GC) system coupled with low- and high-resolution mass spectrometry (MS). Particular attention was devoted to the optimization of the extraction conditions, to extend the analytes' coverage, and the chromatographic separation, to obtain a robust data set for further untargeted analysis. Monoterpenes, sesquiterpenes, hydrocarbons, cannabinoids, other terpenoids, and fatty acids were considered to optimize the extraction conditions. The response of selected ions for each chemical class, delimited in specific 2D chromatographic regions, enabled an accurate and fast evaluation of the extraction variables (i.e., time, temperature, solvent, salt addition), which were then selected to have a wide analyte selection and good reproducibility. Under optimized SBSE conditions, eight different cannabis inflorescences and a quality control sample were analyzed and processed following an untargeted and unsupervised approach. Principal component analysis on all detected metabolites revealed chemical differences among the sample types which could be associated with the plant subspecies. With the same SBSE-GC × GC-MS methodology, a quantitative targeted analysis was performed on three common cannabinoids, namely, Δ9-tetrahydrocannabinol, cannabidiol, and cannabinol. The method was validated, giving correlation factors over 0.98 and

Gas chromatography (GC) coupled with electron ionization (EI) mass spectrometry (MS) is a well-established technique for the analysis of volatile and semi-volatile compounds. The main advantage is the highly repeatable fragmentation of the compounds into the ion source, generating intense and diagnostic fragmentation when the ionization is performed at 70 eV; this is considered the standard ionization condition and has been used for creating many established databases, which are of great support in the analyte identification process. However, such an intense fragmentation often causes the loss of the molecular ion or more diagnostic ions, which can be detrimental for the identification of homologous series or isomers, as for instance fatty acids. To obtain this information chemical or soft ionization can be used, but dedicated ion sources and conditions are required. In this work, we explored different ionization voltages in GC-EI-MS to preserve the intensity of the molecular ion using a conventional quadrupole MS. Twenty, 30, 50, and 70 eV were tested using a mixture of fatty acid methyl esters standards. Intensity and repeatability of the most informative ions were compared. Twenty and 70 eV were then used to analyze the fatty acid composition of six different strains of mycobacteria. Two approaches were used for elaborating the data: (1) a single average spectrum of the entire chromatogram was derived, which can be considered (in terms of concept) as a direct EI-MS analysis; (2) the actual chromatographic separation of the compounds was considered after automatic alignment. The results obtained are discussed herein. Graphical abstract ᅟ.

We present a QR code paper microfluidic colorimetric assay that can exploit the hardware and software on mobile devices, and circumvent sample preparation by directly targeting volatile biomarkers. Our platform is a printable microarray of well-defined reaction regions, which outputs an instant diagnosis by directing the user to a URL containing their test result, while simultaneously storing epidemiological data for remote access and bioinformatics. To assist in the rapid identification of Escherichia coli in bloodstream infections, we employed an existing colorimetric reagent (p-dimethylaminocinnamaldehyde) and adapted its use to detect volatile indole, a biomarker produced by E. coli. Our assay was able to quantitatively detect indole in the headspace of E. coli culture after 12 h of growth (27.0 ± 3.1 ppm), assisting in species-level identification hours earlier than existing methods. Results were confirmed with headspace solid-phase microextraction (HS-SPME) two-dimensional gas chromatography time-of-flight mass spectrometry (GC×GC-ToFMS), which estimated indole concentration in E. coli culture to average 32.3 ± 5.2 ppm after 12 h of growth. This QR paper microfluidic platform represents a novel development in both telemedicine and diagnostics using volatile biomarkers. We envision that our QR code platform can be extended to other colorimetric assays for real-time diagnostics in low-resource environments.

In the present research, the potential of breath analysis by comprehensive two-dimensional gas chromatography coupled to mass spectrometry (GC×GC-MS) was investigated for the discrimination between healthy and infected mice. A pilot study employing a total of 16 animals was used to develop a method for breath analysis in a murine model for studying Mycobacterium tuberculosis complex (MTBC) using the M. bovis bacillus Calmette-Guérin. Breath was collected in Tedlar bags and concentrated onto thermal desorption tubes for subsequent analysis by GC×GC-MS. Immunological test and bacterial cell count in bronchoalveolar lavage fluid and mice lung homogenate confirmed the presence of bacteria in the infected group. From the GC×GC-MS analysis, 23 molecules were found to mainly drive the separation between control and infected mice and their tentative identification is provided.This study shows that the overall used methodology is able to differentiate breath between healthy and infected animals, and the information herein can be used to further develop the mouse breath model to study MTBC pathogenesis, evaluate pre-clinical drug regimen efficacy, and to further develop the concept of breath-based diagnostics.

Untargeted metabolomics study of volatile organic compounds produced by different cell cultures is a field that has gained increasing attention over the years. Solid-phase microextraction has been the sampling technique of choice for most of the applications mainly due to its simplicity to implement. However, a careful optimization of the analytical conditions is necessary to obtain the best performances, which are highly matrix-dependent. In this work, five different solid-phase microextraction fibers were compared for the analysis of the volatiles produced by cell culture infected with the human respiratory syncytial virus. A central composite design was applied to determine the best time-temperature combination to maximize the extraction efficiency and the salting-out effect was evaluated as well. The linearity of the optimized method, along with limits of detection and quantification and repeatability was assessed. Finally, the effect of i) different normalization techniques (i.e. z-score and probabilistic quotient normalization), ii) data transformation (i.e. in logarithmic scale), and iii) different feature selection algorithms (i.e. Fisher ratio and random forest) on the capability of discriminating between infected and not-infected cell culture was evaluated.

Microorganisms catabolize carbon-containing compounds in their environment during growth, releasing a subset of metabolic byproducts as volatile compounds. However, the relationship between growth media and the production of volatile compounds has been largely unexplored to-date. To assess the core and media-specific components of the Klebsiella pneumoniae volatile metabolome via growth in four in vitro culture media. Headspace volatiles produced by cultures of K. pneumoniae after growth to stationary phase in four rich media (brain heart infusion broth, lysogeny broth, Mueller-Hinton broth, and tryptic soy broth) were analyzed using comprehensive two-dimensional gas chromatography time-of-flight mass spectrometry (GC×GC-TOFMS). Differences in the composition of headspace volatiles as a function of growth media were assessed using hierarchical clustering analysis (HCA) and principal component analysis (PCA). A total of 365 volatile compounds were associated with the growth of K. pneumoniae across all media, of which 36 (10%) were common to all growth media, and 148 (41%) were specific to a single medium. In addition, utilizing all K. pneumoniae-associated volatile compounds, strains clustered as a function of growth media, demonstrating the importance of media in determining the metabolic profile of this organism. K. pneumoniae produces a core suite of volatile compounds across all growth media studied, although the volatile metabolic signature of this organism is fundamentally media-dependent.

Polychlorodibenzo-p-dioxins (PCDDs), polychloro-dibenzofurans (PCDFs), dioxin-like (DL), and non dioxin-like (NDL) polychlorinated biphenyls (PCBs) are currently regulated in food and feed within the European territory (EU 2017/644-771). The confirmatory methods of analysis for checking compliance with maximum levels (MLs) for these involve either the historically-established GC-magnetic sector high-resolution mass spectrometry (GC-HRMS) and, more recently, GC-triple quadrupole mass spectrometry operating in tandem mode (GC-QQQMS/MS). In this study, the performance of a novel triple quadrupole GC-QQQMS/MS system equipped with a programable temperature vaporization (PTV) injector was evaluated for the analysis of regulated PCDD/Fs and PCBs in food and feed. The MS analyzer was equipped with a titanium ionization chamber and a new short collision cell capable to accumulate and eject ions by means of very narrow pulses that allow to minimize the noise and to adapt accumulation times for sensitive multiple reaction monitoring (MRM). The analytical capability of the system was confronted by the strict requirements (selectivity, reproducibility, linearity, quant/qual MRM transitions, accuracy, robustness) set by the EU Regulation for a range of standards, quality control (QC) and food/feed samples. In this respect, the approach showed high precision (1.9&ndash, 15% relative standard deviation (RSD) at low pg/&micro, L) and accuracy (&gt, 80%, except for one hexa-CDD). The quantitative results were also compared to the most used GC-HRMS. In this case, comparable results in terms of single congener concentration basis and total toxic equivalent (TEQ) basis for PCDD/Fs and DL-PCBs were obtained for the QC samples analyzed.

In this pilot study, volatile molecules produced by cultures of Mycobacterium tuberculosis were evaluated to determine whether they could be used to discriminate between uninfected and M. tuberculosis-infected macaques. Thirty seven of the culture biomarkers were detectable in macaque breath and were shown to discriminate between uninfected and infected animals with an area under the curve (AUC) of 87%. An AUC of 98% was achieved when using the top 38 discriminatory molecules detectable in breath. We report two newly discovered volatile biomarkers, not previously associated with M. tuberculosis, that were selected in both our in vitro and in vivo discriminatory biomarker suites: 4-(1,1-dimethylpropyl) phenol and 4-ethyl-2,2,6,6-tetramethylheptane. Additionally, we report the detection of heptanal, a previously identified M. tuberculosis breath biomarker in humans, as an in vitro culture biomarker that was detected in every macaque breath sample analyzed, though not part of the in vivo discriminatory suite. This pilot study suggests that molecules from the headspace of M. tuberculosis culture show potential to translate as breath biomarkers for macaques infected with the same strain.