Development and validation of a classification model for boar taint detection in pork fat samples.

This study aims to characterize a complete volatile organic compound profile of pork neck fat for boar taint prediction. The objectives are to identify specific compounds related to boar taint and to develop a classification model. In addition to the well-known androstenone, skatole and indole, 10 other features were found to be discriminant according to untargeted volatolomic analyses were conducted on 129 samples using HS-SPME-GC×GC-TOFMS. To select the odor-positive samples among the 129 analyzed, the selection was made by combining human nose evaluations with the skatole and androstenone concentrations determined using UHPLC-MS/MS. A comparison of the data of the two populations was performed and a statistical model analysis was built on 70 samples out of the total of 129 samples fully positive or fully negative through these two orthogonal methods for tainted prediction. Then, the model was applied to the 59 remaining samples. Finally, 7 samples were classified as tainted.

Lipid Serum Profiling of Boar-Tainted and Untainted Pigs Using GC×GC-TOFMS: An Exploratory Study.

Mass spectrometry (MS)-based techniques, including liquid chromatography coupling, shotgun lipidomics, MS imaging, and ion mobility, are widely used to analyze lipids. However, with enhanced separation capacity and an optimized chemical derivatization approach, comprehensive two-dimensional gas chromatography (GC×GC) can be a powerful tool to investigate some groups of small lipids in the framework of lipidomics. This study describes the optimization of a dedicated two-stage derivatization and extraction process to analyze different saturated and unsaturated fatty acids in plasma by two-dimensional gas chromatography-time-of-flight mass spectrometry (GC×GC-TOFMS) using a full factorial design. The optimized condition has a composite desirability of 0.9159. This optimized sample preparation and chromatographic condition were implemented to differentiate between positive (BT) and negative (UT) boar-tainted pigs based on fatty acid profiling in pig serum using GC×GC-TOFMS. A chemometric screening, including unsupervised (PCA, HCA) and supervised analysis (PLS-DA), as well as univariate analysis (volcano plot), was performed. The results suggested that the concentration of PUFA ω-6 and cholesterol derivatives were significantly increased in BT pigs, whereas SFA and PUFA ω-3 concentrations were increased in UT pigs. The metabolic pathway and quantitative enrichment analysis suggest the significant involvement of linolenic acid metabolism.

A unique data analysis framework and open source benchmark data set for the analysis of comprehensive two-dimensional gas chromatography software.

Comprehensive two-dimensional gas chromatography (GC × GC) is amongst the most powerful separation technologies currently existing. Since its advent in early 1990, it has become an established method which is readily available. However, one of its most challenging aspects, especially in hyphenation with mass spectrometry is the high amount of chemical information it provides for each measurement. The GC × GC community agrees that there, the highest demand for action is found. In response, the number of software packages allowing for in-depth data processing of GC × GC data has risen over the last couple of years. These packages provide sophisticated tools and algorithms allowing for more streamlined data evaluation. However, these tools/algorithms and their respective specific functionalities differ drastically within the available software packages and might result in various levels of findings if not appropriately implemented by the end users. This study focuses on two main objectives. First, to propose a data analysis framework and second to propose an open-source dataset for benchmarking software options and their specificities. Thus, allowing for an unanimous and comprehensive evaluation of GC × GC software. Thereby, the benchmark data includes a set of standard compound measurements and a set of chocolate aroma profiles. On this foundation, eight readily available GC × GC software packages were anonymously investigated for fundamental and advanced functionalities such as retention and detection device derived parameters, revealing differences in the determination of e.g. retention times and mass spectra.

The role of sample preparation in multidimensional gas chromatographic separations for non-targeted analysis with the focus on recent biomedical, food, and plant applications.

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.

A non-targeted data processing workflow for volatile organic compound data acquired using comprehensive two-dimensional gas chromatography with dual channel detection.

There has been an influx of technology for comprehensive two-dimensional gas chromatography analyses in recent years, calling for development of guided workflows and rigorous reporting of processes. This research focuses on the processing method for data collected on a dual channel detection system using flame ionization detection (FID) and quadrupole mass spectrometry (qMS) for the analysis of volatile organic compounds (VOCs). The samples analyzed were kava (Piper methysticum), which has a rich VOC profile that benefits substantially from a multidimensional approach due to enhanced peak capacity. The procedure which was customized here was the data processing workflow from a manual single-sample analysis to an integrated batch workflow that can be applied across studies.•Parameter choice for baseline correction and peak detection were defined when handling batch data.•Elution regions were defined using qMS data to automate compound identification.•Stencils were transformed onto FID data and sequenced for quantitative information.This dataset can be used as a training tool, as all details, methods and results for the workflow have been provided for users to compare with. The focus on data workflow reproducibility in the field of multidimensional chromatography will assist in adoption by users in new application areas.

In-Depth Cannabis Multiclass Metabolite Profiling Using Sorptive Extraction and Multidimensional Gas Chromatography with Low- and High-Resolution Mass Spectrometry.

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 <20% reproducibility (relative standard deviation). The high-resolution MS acquisition allowed for high-confidence identification and post-targeted analysis, confirming the presence of two pesticides, a plasticizer, and a cannabidiol degradation product in some of the samples.

Translation of a One-Dimensional to a Comprehensive Two-Dimensional Gas Chromatography Method with Dual-Channel Detection for Volatile Organic Compound Measurement in Forensic Applications.

After its introduction in the early 1990s, comprehensive two-dimensional gas chromatography (GC×GC) has evolved from a separation science research tool to the central component of many industries. Despite the maturity of the technique, some fields remain reluctant to its use in routine applications. In the case of forensic science, some constraints are the strict requirements enforced in forensic laboratories and the time and effort that must be invested for intralaboratory method validation. Concerns may also arise about whether information could be lost when transitioning to a new technique. This study reports on a method translation from conventional one-dimensional (1D) GC to GC×GC, ensuring the integrity of data as conversion is made. The GC was retrofitted with a reverse fill/flush (RFF) flow modulator and equipped with dual-channel detection using a quadrupole mass spectrometer (qMS) and a flame ionization detector (FID). The parallel use of two detectors, where qMS was applied for qualitative identification and FID for quantification, allowed higher flows and slightly wider peaks to be exploited for the analysis of a volatile organic compound (VOC) reference mixture relevant to forensic VOC profiling. Peak quality assessment and calibration curves using GC-qMS and GC×GC-qMS/FID document the transfer and adaptation of the original method without a loss in data quality. Furthermore, the preprocessing and the data analysis processing steps, including calibration and peak quality assessment for each of the three data sets, are explained in detail. This information provides benchmark data for routine laboratories that want to implement a GC×GC approach into routine workflows.

Advanced method optimization for volatile aroma profiling of beer using two-dimensional gas chromatography time-of-flight mass spectrometry.

The complex mixture of volatile organic compounds (VOCs) present in the headspace of Trappist and craft beers was studied to illustrate the efficiency of thermal desorption (TD) comprehensive two-dimensional gas chromatography time-of-flight mass spectrometry (GC×GC-TOFMS) for highlighting subtle differences between highly complex mixtures of VOCs. Headspace solid-phase microextraction (HS-SPME), multiple (and classical) stir bar sorptive extraction (mSBSE), static headspace (SHS), and dynamic headspace (DHS) were compared for the extraction of a set of 21 representative flavor compounds of beer aroma. A Box-Behnken surface response methodology experimental design optimization (DOE) was used for convex hull calculation (Delaunay's triangulation algorithms) of peak dispersion in the chromatographic space. The predicted value of 0.5 for the ratio between the convex hull and the available space was 10% higher than the experimental value, demonstrating the usefulness of the approach to improve optimization of the GC×GC separation. Chemical variations amongst aligned chromatograms were studied by means of Fisher Ratio (FR) determination and F-distribution threshold filtration at different significance levels (α=0.05 and 0.01) and based on z-score normalized area for data reduction. Statistically significant compounds were highlighted following principal component analysis (PCA) and hierarchical cluster analysis (HCA). The dendrogram structure not only provided clear visual information about similarities between products but also permitted direct identification of the chemicals and their relative weight in clustering. The effective coupling of DHS-TD-GC×GC-TOFMS with PCA and HCA was able to highlight the differences and common typical VOC patterns among 24 samples of different Trappist and selected Canadian craft beers.

A minimally-invasive method for profiling volatile organic compounds within postmortem internal gas reservoirs.

In forensic casework, non-invasive and minimally-invasive methods for postmortem examinations are extremely valuable. Whole body postmortem computed tomography (PMCT) is often used to provide visualization of the internal characteristics of a body prior to more invasive procedures and has also been used to locate gas reservoirs inside the body to assist in determining cause of death. Preliminary studies have demonstrated that exploiting the volatile organic compounds (VOCs) located in these gas reservoirs by comprehensive two-dimensional gas chromatography-high-resolution time-of-flight mass spectrometry (GC×GC-HRTOF-MS) may assist in providing information regarding the postmortem interval. The aim of the current study was to further develop the procedures related to solid-phase microextraction (SPME) and GC×GC-HRTOF-MS analysis of gas reservoirs collected from deceased individuals. SPME fiber extraction parameters, internal standard approach, and sample stability were investigated. Altering the SPME parameters increased the selectivity and sensitivity for the VOC profile, and the use of a mixed deuterated internal standard contributed to data quality. Samples were found to be stable up to 6 weeks but were recommended to be analyzed within 4 weeks due to higher variation observed beyond this point. In addition, 29 VOC markers of interest were identified, and heart and/or abdominal cavity samples were suggested as a possible standardized sampling location for future studies. The data presented in this study will contribute to the long-term goal of producing a routine, accredited method for minimally-invasive VOC analysis in postmortem examinations.

Thermal desorption comprehensive two-dimensional gas chromatography coupled to variable-energy electron ionization time-of-flight mass spectrometry for monitoring subtle changes in volatile organic compound profiles of human blood.

Blood is a matrix with high potential for forensic investigations and human rescue. Its volatile signature can be used in search exercises to locate injured or deceased individuals. Little is known, however, about the volatile organic compound (VOC) profile of blood, except that it is complex and varies while blood ages. In the present study, we used thermal desorption (TD) and comprehensive two-dimensional gas chromatography (GCxGC) coupled to variable-energy electron ionization time-of-flight mass spectrometry (TOFMS) to monitor VOC signatures of human blood. A highly complex reference standard (Century Mix) containing 108 compounds of various chemical functionalities and several homologue series of compounds was used for the purpose of transposing our previously developed cryogenically modulated GCxGC-TOFMS methods into the use of a reverse fill/flush (RFF) flow modulator. The average peak width at half height was 340ms and the average tailing factor was 1.16. Light VOCs (down to C4) were effectively flow modulated and exhibited minimal breakthrough over a large dynamic range spanning four orders of magnitude. Mass spectrometric detection was performed using electron impact ionization (EI) carried out at 70eV and lower energies (12, 14, and 16eV). The use of variable-energy (ve) EI allowed mass spectra to be produced with less fragmentation and an increased presence of structurally significant ions and the molecular ion. This provided additional confidence in peak assignments, especially for closely eluting isomers often observed in the profiling of the headspace of blood. Variable-energy EI TD-GCxGC-TOFMS blood data sets were statistically processed using principal component analyses (PCA) and hierarchical cluster analyses (HCA). These techniques demonstrated that the effect of aging was greater than the inter-individual variation on the blood VOC profile. The combination of retention indices, low and high EI MS spectra served as a strong basis to gain more confidence in analytical identification by excluding identities proposed by mass spectral databases (70eV) for compounds contributing to the separation of blood of different ages.