Benefits of Ion Mobility Separation in GC-APCI-HRMS Screening: From the Construction of a CCS Library to the Application to Real-World Samples.

The performance of gas chromatography (GC) combined with the improved identification properties of ion mobility separation coupled to high-resolution mass spectrometry (IMS-HRMS) is presented as a promising approach for the monitoring of (semi)volatile compounds in complex matrices. The soft ionization promoted by an atmospheric pressure chemical ionization (APCI) source designed for GC preserves the molecular and/or quasi-molecular ion information enabling a rapid, sensitive, and efficient wide-scope screening. Additionally, ion mobility separation (IMS) separates species of interest from coeluting matrix interferences and/or resolves isomers based on their charge, shape, and size, making IMS-derived collision cross section (CCS) a robust and matrix-independent parameter comparable between instruments. In this way, GC-APCI-IMS-HRMS becomes a powerful approach for both target and suspect screening due to the improvements in (tentative) identifications. In this work, mobility data for 264 relevant multiclass organic pollutants in environmental and food-safety fields were collected by coupling GC-APCI with IMS-HRMS, generating CCS information for molecular ion and/or protonated molecules and some in-source fragments. The identification power of GC-APCI-IMS-HRMS for the studied compounds was assessed in complex-matrix samples, including fish feed extracts, surface waters, and different fruit and vegetable samples.

Untargeted metabolomics unravels distinct gut microbial metabolites derived from plant-based and animal-origin proteins using in vitro modeling.

The popularity of plant-based meat alternatives (PBMAs) has sparked a contentious debate about their influence on intestinal homeostasis compared to traditional animal-based meats. This study aims to explore the changes in gut microbial metabolites (GMMs) induced by the gut microbiota on different digested patties: beef meat and pea-protein PBMA. After digesting in vitro, untargeted metabolomics revealed 32 annotated metabolites, such as carnitine and acylcarnitines correlated with beef meat, and 45 annotated metabolites, like triterpenoids and lignans, linked to our PBMA. Secondly, (un)targeted approaches highlighted differences in GMM patterns during colonic fermentations. Our findings underscore significant differences in amino acids and their derivatives. Beef protein fermentation resulted in higher production of methyl-histidine, gamma-glutamyl amino acids, indoles, isobutyric and isovaleric acids. In contrast, PBMAs exhibit a significant release of N-acyl amino acids and unique dipeptides, like phenylalanine-arginine. This research offers valuable insights into how PBMAs and animal-based proteins differently modulate intestinal microenvironments.

Identification and quantification of flavor compounds in smoked tuna fish based on GC-Orbitrap volatolomics approach.

Cold smoking enhances the appeal of fish products, offering consumers a smooth texture and a delicate smoky flavor. This study aims to explore variations in the volatile profile from different exposure times during cold smoking processing (light, moderate, and full-cure) in tune samples. An innovative untargeted analytical approach, headspace solid-phase microextraction combined with gas chromatography and a hybrid quadrupole-orbitrap mass analyzer, was employed to identify 86 volatiles associated with the cold smoking process. Most of these compounds, including phenols, furan derivates, aldehydes, cyclic ketones, and different aromatic species, were found to contribute to the smoke odor. The development of a QuEChERS-based extraction and clean-up method facilitated the quantification of 25 relevant smoky markers across all smoking degrees, revealing significant concentration differences after 15 h of smoking. This research sheds light on the dynamics of cold smoking impact and its on the flavor profile and safety quality of processed fish products.

Discovery of Food Intake Biomarkers Using Metabolomics.

Due to the high impact of diet exposure on health, it is crucial the generation of robust data of regular dietary intake, hence improving the accuracy of dietary assessment. The metabolites derived from individual food or group of food have great potential to become biomarkers of food intake (BFIs) and provide more objective food consumption measurements.Herein, it is presented an untargeted metabolomic workflow for the discovery BFIs in blood and urine samples, from the study design to the biomarker identification. Samples are analyzed by liquid chromatography coupled to high-resolution mass spectrometry (LC-HRMS). A wide variety of compounds are covered by separate analyses of medium to nonpolar molecules and polar metabolites based on two LC separations as well as both positive and negative electrospray ionization. The main steps of data treatment of the comprehensive data sets and statistical analysis are described, as well as the principal considerations for the BFI identification.

LC-IMS-HRMS for identification of biomarkers in untargeted metabolomics: The effects of pterostilbene and resveratrol consumption in liver steatosis, animal model.

Untargeted metabolomics with the combination of ion mobility separation coupled to high resolution mass spectrometry (IMS-HRMS) was applied to investigate the impact of resveratrol and pterostilbene supplementation on the metabolic fingerprint of the Wistar rats liver with induced liver steatosis. RP-LC and HILIC in both ionisation modes were employed to analyse the liver samples (n = 40) from Wistar rats fed with a high-fat and high-fructose diet, supplemented or not with resveratrol and pterostilbene. After univariate and multivariate statistical analysis, 34 metabolites were highlighted in the different diets and elucidated. Despite the structural similarity, different alterations in liver metabolism were observed by the supplementations. Resveratrol treatment was characterised by the alteration in metabolism of 17 lysophospholipids, while pterostilbene affected some vitamins and derivatives, among others. IMS has demonstrated great potential in the elucidation process thanks to the additional structural descriptor the CCS (Å2), providing more confidence in the identification.