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Colorectal cancer (CRC) ranks as the third most frequently diagnosed cancer and the second leading cause of cancer-related deaths. The current endoscopic-based or stool-based diagnostic techniques are either highly invasive or lack sufficient sensitivity. Thus, there is a need for less invasive and more sensitive screening approaches. We, therefore, conducted a study on 64 human serum samples representing three different groups (adenocarcinoma, adenoma, and control) using cutting-edge GC×GC-LR/HR-TOFMS (comprehensive two-dimensional gas chromatography coupled with low/high-resolution time-of-flight mass spectrometry). We analyzed samples with two different specifically tailored sample preparation approaches for lipidomics (fatty acids) (25 μL serum) and metabolomics (50 μL serum). In-depth chemometric screening with supervised and unsupervised approaches and metabolic pathway analysis were applied to both datasets. A lipidomics study revealed that specific PUFA (ω-3) molecules are inversely associated with increased odds of CRC, while some PUFA (ω-6) analytes show a positive correlation. The metabolomics approach revealed downregulation of amino acids (alanine, glutamate, methionine, threonine, tyrosine, and valine) and myo-inositol in CRC, while 3-hydroxybutyrate levels were increased. This unique study provides comprehensive insight into molecular-level changes associated with CRC and allows for a comparison of the efficiency of two different analytical approaches for CRC screening using same serum samples and single instrumentation.

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.

Coffee, one of the most popular beverages in the world, attracts consumers by its rich aroma and the stimulating effect of caffeine. Increasing consumers prefer decaffeinated coffee to regular coffee due to health concerns. There are some main decaffeination methods commonly used by commercial coffee producers for decades. However, a certain amount of the aroma precursors can be removed together with caffeine, which could cause a thin taste of decaffeinated coffee. To understand the difference between regular and decaffeinated coffee from the volatile composition point of view, headspace solid-phase microextraction two-dimensional gas chromatography time-of-flight mass spectrometry (HS-SPME-GC×GC-TOFMS) was employed to examine the headspace volatiles of eight pairs of regular and decaffeinated coffees in this study. Using the key aroma-related volatiles, decaffeinated coffee was significantly separated from regular coffee by principal component analysis (PCA). Using feature-selection tools (univariate analysis: t -test and multivariate analysis: partial least squares-discriminant analysis (PLS-DA)), a group of pyrazines was observed to be significantly different between regular coffee and decaffeinated coffee. Pyrazines were more enriched in the regular coffee, which was due to the reduction of sucrose during the decaffeination process. The reduction of pyrazines led to a lack of nutty, roasted, chocolate, earthy, and musty aroma in the decaffeinated coffee. For the non-targeted analysis, the random forest (RF) classification algorithm was used to select the most important features that could enable a distinct classification between the two coffee types. In total, 20 discriminatory features were identified. The results suggested that pyrazine-derived compounds were a strong marker for the regular coffee group whereas furan-derived compounds were a strong marker for the decaffeinated coffee samples.

Hindgut homogenates of the termite Reticulitermes santonensis were incubated with carboxymethyl cellulose (CMC), crystalline celluloses or xylan substrates. Hydrolysates were analyzed with matrix-assisted laser desorption/ionization coupled to time-of-flight mass spectrometry (MALDI-TOF MS). The method was first set up using acid hydrolysis analysis to characterize non-enzymatic profiles. Commercial enzymes of Trichoderma reesei or T. longibrachiatum were also tested to validate the enzymatic hydrolysis analysis. For CMC hydrolysis, data processing and visual display were optimized to obtain comprehensive profiles and allow rapid comparison and evaluation of enzymatic selectivity, according to the number of substituents of each hydrolysis product. Oligosaccharides with degrees of polymerization (DPs) ranging from three to 12 were measured from CMC and the enzymatic selectivity was demonstrated. Neutral and acidic xylo-oligosaccharides with DPs ranging from three to 11 were measured from xylan substrate. These results are of interest for lignocellulose biomass valorization and demonstrated the potential of termites and their symbiotic microbiota as a source of interesting enzymes for oligosaccharides production.

A single fraction of essential oil can often contain hundreds of compounds. Despite of the technical improvements and the enhanced selectivity currently offered by the state-of-the-art gas chromatography (GC) and mass spectrometry (MS) instruments, the complexity of essential oils is frequently underestimated. Comprehensive two-dimensional GC coupled to time-of-flight MS (GC×GC-TOFMS) was used to improve the chemical characterization of ylang-ylang essential oil fractions recently reported in a previous one-dimensional (1D) GC study. Based on both, the enhanced chromatographic separation and the mass spectral deconvolution, 161 individual compounds were identified and labeled as potentially characteristic analytes found in both low and high boiling fractions issued from distillation of mature ylang-ylang flowers. Compared to the most recent full GC-MS characterization, this represents 75 new compounds, essentially consisting of terpenes, terpenoid esters, and alcohols.