Urinary metabolic fingerprinting of mice with diet-induced metabolic derangements by parallel dual secondary column-dual detection two-dimensional comprehensive gas chromatography

Chemical fingerprinting strategies based on comprehensive two-dimensional gas chromatography combined with gas chromatography-olfactometry to capture the unique signature of Piemonte peppermint essential oil (Mentha x piperita var Italo-Mitcham)

Accurate, reliable, and informative mapping of untargeted and targeted components across many samples is here performed by combining off-line GC-Olfactometry (GC-O) and comprehensive two-dimensional gas chromatography (GC×GC) coupled to time-of-flight mass spectrometry with variable ionization energy (TOF MS featuring Tandem Ionization™). In particular, untargeted and targeted (UT) features patterns are processed by chromatographic fingerprinting, giving differential priority to potent odorants' retention-times regions. Distinguishing peppermint essential oil (EO) from Piedmont (Italy - Mentha × piperita L. var. Italo-Mitcham - Menta di Pancalieri EO), with its unique sensory fingerprint (i.e., freshness and long-lasting sweetness), from high-quality peppermint EOs produced in other areas poses a great challenge. Chromatographic UT fingerprinting provided a great chemical dimensionality by mapping more than 350 peak-regions at 70 eV and 135 at 12 eV. From them, 95 components were identified and responses compared to available literature. Then, potent odorants, detected by GC-O using the aroma extraction dilution analysis (AEDA), were tracked over the chromatographic space and tentatively identified. With the highest flavor dilution (FD), 1,8-cineole (eucalyptus, fresh, camphoraceous); menthone (minty, herbaceous); and menthofuran (minty, musty, petroleum-like) were highlighted. Responsible for creamy and coumarinic notes were the diasteroisomers of (3,6)-dimethyl-4,5,6,7-tetrahydrobenzo[b]-furan-2(3H)-one (i.e., menthofurolactones), detected in higher relative abundance in Pancalieri EOs. By prioritizing the investigation of volatiles on higher LogFD retention regions, including 131 untargeted/targeted features, Pancalieri EOs were separately clustered from United States samples. Besides pre-targeted analytes, additional untargeted features were post-processed for identification within marker chemicals. Myrtenyl methyl ether, ethyl 3-methyl butanoate, propyl-2-methylbutanoate, and (E)-2-hexenal were putatively identified. Of the "unknown - knowns" with diagnostic roles, all metadata were collected including low energy spectra at 12 eV, which were found to be highly complementary to 70 eV spectra.

Exploring extra dimensions to capture saliva metabolite fingerprints from metabolically healthy and unhealthy obese patients by comprehensive two-dimensional gas chromatography featuring Tandem Ionization mass spectrometry

This study examines the information potential of comprehensive two-dimensional gas chromatography combined with time-of-flight mass spectrometry (GC×GC-TOF MS) and variable ionization energy (i.e., Tandem Ionization™) to study changes in saliva metabolic signatures from a small group of obese individuals. The study presents a proof of concept for an effective exploitation of the complementary nature of tandem ionization data. Samples are taken from two sub-populations of severely obese (BMI > 40 kg/m²) patients, named metabolically healthy obese (MHO) and metabolically unhealthy obese (MUO). Untargeted fingerprinting, based on pattern recognition by template matching, is applied on single data streams and on fused data, obtained by combining raw signals from the two ionization energies (12 and 70 eV). Results indicate that at lower energy (i.e., 12 eV), the total signal intensity is one order of magnitude lower compared to the reference signal at 70 eV, but the ranges of variations for 2D peak responses is larger, extending the dynamic range. Fused data combine benefits from 70 eV and 12 eV resulting in more comprehensive coverage by sample fingerprints. Multivariate statistics, principal component analysis (PCA), and partial least squares discriminant analysis (PLS-DA) show quite good patient clustering, with total explained variance by the first two principal components (PCs) that increases from 54% at 70 eV to 59% at 12 eV and up to 71% for fused data. With PLS-DA, discriminant components are highlighted and putatively identified by comparing retention data and 70 eV spectral signatures. Within the most informative analytes, lactose is present in higher relative amount in saliva from MHO patients, whereas N-acetyl-D-glucosamine, urea, glucuronic acid γ-lactone, 2-deoxyribose, N-acetylneuraminic acid methyl ester, and 5-aminovaleric acid are more abundant in MUO patients. Visual feature fingerprinting is combined with pattern recognition algorithms to highlight metabolite variations between composite per-class images obtained by combining raw data from individuals belonging to different classes, i.e., MUO vs. MHO.

Graphical abstract

Sedentariness and Urinary Metabolite Profile in Type 2 Diabetic Patients, a Cross-Sectional Study

Recent findings indicate a significant association between sedentary (SED)-time and type 2 diabetes mellitus (T2DM). The aim of this study was to investigate whether different levels of SED-time could impact on biochemical and physiological processes occurring in sedentary and physically inactive T2DM patients. In particular, patients from the “Italian Diabetes and Exercise Study (IDES)_2 trial belonging to the first and fourth quartile of SED-time were compared. Urine samples were analyzed by comprehensive two-dimensional gas chromatography (GC × GC) with parallel detection by mass spectrometry and flame ionization detection (GC × 2GC-MS/FID). This platform enables accurate profiling and fingerprinting of urinary metabolites while maximizing the overall information capacity, quantitation reliability, and response linearity. Moreover, using advanced pattern recognition, the fingerprinting process was extended to untargeted and targeted features, revealing diagnostic urinary fingerprints between groups. Quantitative metabolomics was then applied to analytes of relevance for robust comparisons. Increased levels of glycine, L-valine, L-threonine, L-phenylalanine, L-leucine, L-alanine, succinic acid, 2-ketoglutaric acid, xylitol, and ribitol were revealed in samples from less sedentary women. In conclusion, SED-time is associated with changes in urine metabolome signatures. These preliminary results suggest that reducing SED-time could be a strategy to improve the health status of a large proportion of diabetic patients.

Towards personalised molecular feedback for weight loss

Background

Numerous diets, apps and websites help guide and monitor dietary behaviour with the goal of losing weight, yet dieting success is highly dependent on personal preferences and circumstances. To enable a more quantitative approach to dieting, we developed an integrated platform that allows tracking of life-style information alongside molecular biofeedback measurements (lactate and insulin).

Methods

To facilitate weight loss, participants (≥18 years) omitted one main meal from the usual three-meal routine. Daily caloric intake was restricted to ~1200KCal with one optional snack ≤250KCal. A mobile health platform (personalhealth.warwick.ac.uk) was developed and used to maintain diaries of food intake, weight, urine collection and volume. A survey was conducted to understand participants’ willingness to collect samples, motivation for taking part in the study and reasons for dropout.

Results

Meal skipping resulted in weight loss after a 24 h period in contrast to 3-meal control days regardless of the meal that was skipped, breakfast, lunch or dinner (p < 0.001). Common reasons for engagement were interest in losing weight and personal metabolic profile. Total insulin and lactate values varied significantly between healthy and obese individuals at p = 0.01 and 0.05 respectively.

Conclusion

In a proof of concept study with a meal-skipping diet, we show that insulin and lactate values in urine correlate with weight loss, making these molecules potential candidates for quantitative feedback on food intake behaviour to people dieting.

Electronic supplementary material

The online version of this article (10.1186/s40608-019-0237-5) contains supplementary material, which is available to authorized users.

Comprehensive comparative compositional study of the vapour phase of cigarette mainstream tobacco smoke and tobacco heating product aerosol

A simple direct sample collection/dilution and introduction method was developed using quartz wool and Tenax/sulficarb sorbents for thermal desorption and comprehensive two-dimensional gas chromatography (TD-GC × GC) analyses of volatile organic compounds from vapour phase (VP) fractions of aerosol produced by tobacco heating products (THP1.0) and 3R4F mainstream tobacco smoke (MTS). Analyses were carried out using flame ionisation detection (FID) for semi-quantification and both low and high resolution time-of-flight mass spectrometry (LR/HR-TOFMS) for qualitative comparison and peak assignment. Qualitative analysis was carried out by combining identification data based on linear retention indices (LRIs) with a match window of ±10 index units, mass spectral forward and reverse library searches (from LR and HRTOFMS spectra) with a match factor threshold of >700 (both forward and reverse), and accurate mass values of ± 3 ppm for increased confidence in peak identification. Using this comprehensive approach of data mining, a total of 79 out of 85 compounds and a total of 198 out of 202 compounds were identified in THP1.0 aerosol and in 3R4F MTS, respectively. Among the identified analytes, a set of 35 compounds was found in both VP sample types. Semi-quantitative analyses were carried out using a chemical class-based external calibration method. Acyclic, alicyclic, aromatic hydrocarbons and ketones appeared to be prominent in 3R4F MTS VP, whereas larger amounts of aldehydes, ketones, heterocyclic hydrocarbons and esters were present in THP1.0 aerosol VP. The results demontsrate the capability and versatility of the method for the characterization and comparison of complex aerosol samples and highlighted the relative chemical simplicity of THP1.0 aerosol in comparison to MTS.

Comprehensive Chemical Fingerprinting of High-Quality Cocoa at Early Stages of Processing: Effectiveness of Combined Untargeted and Targeted Approaches for Classification and Discrimination

This study investigates chemical information of volatile fractions of high-quality cocoa (Theobroma cacao L. Malvaceae) from different origins (Mexico, Ecuador, Venezuela, Columbia, Java, Trinidad, and Sao Tomè) produced for fine chocolate. This study explores the evolution of the entire pattern of volatiles in relation to cocoa processing (raw, roasted, steamed, and ground beans). Advanced chemical fingerprinting (e.g., combined untargeted and targeted fingerprinting) with comprehensive two-dimensional gas chromatography coupled with mass spectrometry allows advanced pattern recognition for classification, discrimination, and sensory-quality characterization. The entire data set is analyzed for 595 reliable two-dimensional peak regions, including 130 known analytes and 13 potent odorants. Multivariate analysis with unsupervised exploration (principal component analysis) and simple supervised discrimination methods (Fisher ratios and linear regression trees) reveal informative patterns of similarities and differences and identify characteristic compounds related to sample origin and manufacturing step.

Cultivable gut bacteria provide a pathway for adaptation of Chrysolina herbacea to Mentha aquatica volatiles

BACKGROUND

A chemical cross-talk between plants and insects is required in order to achieve a successful co-adaptation. In response to herbivory, plants produce specific compounds, and feeding insects respond adequately7 to molecules produced by plants. Here we show the role of the gut microbial community of the mint beetle Chrysolina herbacea in the chemical cross-talk with Mentha aquatica (or watermint).

RESULTS

By using two-dimensional gas chromatography-mass spectrometry we first evaluated the chemical patterns of both M. aquatica leaf and frass volatiles extracted by C. herbacea males and females feeding on plants, and observed marked differences between males and females volatiles. The sex-specific chemical pattern of the frass paralleled with sex-specific distribution of cultivable gut bacteria. Indeed, all isolated gut bacteria from females belonged to either α- or γ-Proteobacteria, whilst those from males were γ-Proteobacteria or Firmicutes. We then demonstrated that five Serratia marcescens strains from females possessed antibacterial activity against bacteria from males belonging to Firmicutes suggesting competition by production of antimicrobial compounds. By in vitro experiments, we lastly showed that the microbial communities from the two sexes were associated to specific metabolic patterns with respect to their ability to biotransform M. aquatica terpenoids, and metabolize them into an array of compounds with possible pheromone activity.

CONCLUSIONS

Our data suggest that cultivable gut bacteria of Chrysolina herbacea males and females influence the volatile blend of herbivory induced Mentha aquatica volatiles in a sex-specific way.

Effectiveness of Global, Low-Degree Polynomial Transformations for GCxGC Data Alignment

As columns age and differ between systems, retention times for comprehensive two-dimensional gas chromatography (GCxGC) may vary between runs. To properly analyze GCxGC chromatograms, it often is desirable to align the retention times of chromatographic features, such as analyte peaks, between chromatograms. Previous work by the authors has shown that global, low-degree polynomial transformation functions, namely affine, second-degree polynomial, and third-degree polynomial, are effective for aligning pairs of two-dimensional chromatograms acquired with dual second columns and detectors (GC×2GC). This work assesses the experimental performance of these global methods on more general GCxGC chromatogram pairs and compares their performance to that of a recent, robust, local alignment algorithm for GCxGC data [ Gros Anal. Chem. 2012 , 84 , 9033 ]. Measuring performance with the root-mean-square (RMS) residual differences in retention times for matched peaks suggests that global, low-degree polynomial transformations outperform the local algorithm given a sufficiently large set of alignment points, and are able to improve misalignment by over 95% based on a lower-bound benchmark of inherent variability. However, with small sets of alignment points, the local method demonstrated lower error rates (although with greater computational overhead). For GCxGC chromatogram pairs with only slight initial misalignment, none of the global or local methods performed well. In some cases with initial misalignment near the inherent variability of the system, these methods worsened alignment, suggesting that it may be better not to perform alignment in such cases.

Urine and serum metabolite profiling of rats fed a high-fat diet and the anti-obesity effects of caffeine consumption

In this study, we investigated the clinical changes induced by a high fat diet (HFD) and caffeine consumption in a rat model. The mean body weight of the HFD with caffeine (HFDC)-fed rat was decreased compared to that of the HFD-fed rat without caffeine. The levels of cholesterol, triglycerides (TGs), and free fatty acid, as well as the size of adipose tissue altered by HFD, were improved by caffeine consumption. To investigate the metabolites that affected the change of the clinical factors, the urine and serum of rats fed a normal diet (ND), HFD, and HFDC were analyzed using ultra performance liquid chromatography quadruple time-of-flight mass spectrometry (UPLC-Q-TOF-MS), gas chromatography (GC-TOF-MS), and linear trap quadruple mass spectrometry (LTQ-XL-MS) combined with multivariate analysis. A total of 68 and 52 metabolites were found to be different in urine and serum, respectively. After being fed caffeine, some glucuronide-conjugated compounds, lysoPCs, CEs, DGs, TGs, taurine, and hippuric acid were altered compared to the HFD group. In this study, caffeine might potentially inhibit HFD-induced obesity and we suggest possible biomarker candidates using MS-based metabolite profiling.