Validated Ultra-High-Performance Liquid Chromatography Hybrid High-Resolution Mass Spectrometry and Laser-Assisted Rapid Evaporative Ionization Mass Spectrometry for Salivary Metabolomics.

Whereas urine and blood are typically targeted in clinical research, saliva represents an interesting alternative because its intrinsic metabolome is chemically diverse and reflective for various biological processes. Moreover, saliva collection is easy and noninvasive, which is especially valuable for cohorts in which sample collection is challenging, for example, infants and children. With this rationale, we established a validated ultra-high-performance liquid chromatography high-resolution mass spectrometry (UHPLC-HRMS) method for salivary metabolic profiling and fingerprinting. Hereby, 450 µL of saliva was centrifuged and passed over a 0.45-µm polyamide membrane filter, after which the extract was subjected to chromatographic analysis (HSS T3 column) and Q-Exactive Orbitrap-MS. For the majority of the profiled metabolites, good linearity (R2 ≥ 0.99) and precision (coefficient of variance ≤ 15%) was achieved. The fingerprinting performance was evaluated based on the complete metabolome (11 385 components), whereby 76.8% was found compliant with the criteria for precision (coefficient of variance ≤ 30%) and 82.7% with linearity (R2 ≥ 0.99). In addition, the method was proven fit-for-purpose for a cohort of 140 adolescents (6-16 years, stratified according to weight), yielding relevant profiles (45 obesity-related metabolites) and discriminative fingerprints (Q2 of 0.784 for supervised discriminant analysis). Alternatively, laser-assisted rapid evaporative ionization mass spectrometry (LA-REIMS) was established for rapid fingerprinting of saliva, thereby using a Nd:YAG laser and Xevo G2-XS QToF-MS. With an acquisition time of 0.5 min per sample, LA-REIMS offers unique opportunities for point-of-care applications. In conclusion, this work presents a platform of UHPLC-HRMS and LA-REIMS, complementing each other to perform salivary metabolomics.

Holistic Lipidomics of the Human Gut Phenotype Using Validated Ultra-High-Performance Liquid Chromatography Coupled to Hybrid Orbitrap Mass Spectrometry.

As lipids are assigned a plethora of biological functions, it is evident that dysregulated lipid metabolism signifies a key element in many pathological conditions. With this rationale, this study presents a validated lipidomics platform to map the fecal lipidome, which integrates unique information about host-gut microbiome interactions, gastrointestinal functionality, and dietary patterns. This particular method accomplished coverage across all eight lipid categories: fatty acyls, glycerolipids, phosphoglycerolipids, polyketides, prenols, saccharolipids, sphingolipids, and sterols. Generic extraction of freeze-dried feces was achieved by solid-liquid extraction using methanol and methyl tert-butyl ether. Extracted components were separated by liquid chromatography, whereby the selected ethylene-bridged hybrid phenyl ultra-high-performance liquid chromatography stationary phase allowed fast separation of both individual lipid species and categories. Detection was achieved by high-resolution full-scan Q-Exactive Orbitrap mass spectrometry and covered a broad m/z scan range (67-2300 Da). Method validation was performed in a targeted fashion to evaluate the analytical performance across all lipid categories, revealing excellent linearity (R2 ≥ 0.9921), acceptable repeatability (coefficients of variance ≤15.6%), and stable recovery (coefficients of variance ≤11.9%). Method suitability for untargeted fingerprinting was verified, demonstrating adequate linearity (R2 ≥ 0.90) for 75.3% and acceptable repeatability (coefficients of variance ≤30%) for 84.5% of about 9000 endogenous fecal compounds. Eventually, the potential of fecal lipidomics was exemplified within a clinical context of type 2 diabetes, thereby revealing significant perturbations [orthogonal partial least-squares discriminant analysis Q2(Y) of 0.728] in the fecal lipidome between participants with normal blood glucose levels (n = 26) and those with type 2 diabetes (n = 17).

Unraveling biomarkers of exposure for tenuazonic acid through urinary metabolomics.

Mycotoxins are secondary metabolites produced by fungi such as Aspergillus, Alternaria, and Penicillium, affecting nearly 80% of global food crops. Tenuazonic acid (TeA) is the major mycotoxin produced by Alternaria alternata, a prevalent pathogen affecting plants, fruits, and vegetables. TeA is notably prevalent in European diets, however, TeA biomarkers of exposure and metabolites remain unknown. This research aims to bridge this knowledge-gap by gaining insights about human TeA exposure and metabolization. Nine subjects were divided into two groups. The first group received a single bolus of TeA at the Threshold of Toxicological Concern (TTC) to investigate the presence of TeA urinary biomarkers, while the second group served as a control. Sixty-nine urinary samples were prepared and analyzed using UPLC-Xevo TQ-XS for TeA quantification and UPLC-Orbitrap Exploris for polar metabolome acquisition. TeA was rapidly excreted during the first 13 h and the fraction extracted was 0.39 ± 0.22. The polar metabolome compounds effectively discriminating the two groups were filtered using Orthogonal Partial Least Squares-Discriminant Analysis and subsequently annotated (n = 122) at confidence level 4. Finally, the urinary metabolome was compared to in silico predicted TeA metabolites. Nine metabolites, including oxidized, N-alkylated, desaturated, glucuronidated, and sulfonated forms of TeA were detected.

Point-of-care applicable metabotyping using biofluid-specific electrospun MetaSAMPs directly amenable to ambient LA-REIMS.

In recent years, ambient ionization mass spectrometry (AIMS) including laser ablation rapid evaporation IMS, has enabled direct biofluid metabolome analysis. AIMS procedures are, however, still hampered by both analytical, i.e., matrix effects, and practical, i.e., sample transport stability, drawbacks that impede metabolome coverage. In this study, we aimed at developing biofluid-specific metabolome sampling membranes (MetaSAMPs) that offer a directly applicable and stabilizing substrate for AIMS. Customized rectal, salivary, and urinary MetaSAMPs consisting of electrospun (nano)fibrous membranes of blended hydrophilic (polyvinylpyrrolidone and polyacrylonitrile) and lipophilic (polystyrene) polymers supported metabolite absorption, adsorption, and desorption. Moreover, MetaSAMP demonstrated superior metabolome coverage and transport stability compared to crude biofluid analysis and was successfully validated in two pediatric cohorts (MetaBEAse, n = 234 and OPERA, n = 101). By integrating anthropometric and (patho)physiological with MetaSAMP-AIMS metabolome data, we obtained substantial weight-driven predictions and clinical correlations. In conclusion, MetaSAMP holds great clinical application potential for on-the-spot metabolic health stratification.

A multi-omics study to boost continuous bolaform sophorolipid production.

Biodegradable and biobased surface active agents are renewable and environmentally friendly alternatives to petroleum derived or oleochemical surfactants. However, they are accompanied by relatively high production costs. In this study, the aim was to reduce the production costs for an innovative type of microbial biosurfactant: bolaform sophorolipids, produced by the yeast Starmerella bombicola ΔsbleΔat. A novel continuous retentostat set-up was performed whereby continuous broth microfiltration retained the biomass in the bioreactor while performing an in situ product separation of bolaform sophorolipids. Although a mean volumetric productivity of 0.56 g L-1 h-1 was achieved, it was not possible to maintain this productivity, which collapsed to almost 0 g L-1 h-1. Therefore, two process adaptations were evaluated, a sequential batch strategy and a phosphate limitation alleviation strategy. The sequential batch set-up restored the mean volumetric productivity to 0.66 g L-1 h-1 for an additional 132 h but was again followed by a productivity decline. A similar result was obtained with the phosphate limitation alleviation strategy where a mean volumetric productivity of 0.54 g L-1 h-1 was reached, but a productivity decline was also observed. Whole genome variant analysis uncovered no evidence for genomic variations for up to 1306 h of retentostat cultivation. Untargeted metabolomics analysis identified 8-hydroxyguanosine, a biomarker for oxidative RNA damage, as a key metabolite correlating with high bolaform sophorolipid productivity. This study showcases the application of a retentostat to increase bolaform sophorolipid productivity and lays the basis of a multi-omics platform for in depth investigation of microbial biosurfactant production with S. bombicola.

Discovery of urinary biomarkers to discriminate between exogenous and semi-endogenous thiouracil in cattle: A parallel-like randomized design.

In the European Union, the use of thyreostats for animal fattening purposes has been banned and monitoring plans have been established to detect potential abuse. However, this is not always straightforward as thyreostats such as thiouracil may also have a semi-endogenous origin. Therefore, this study aimed at defining urinary metabolites, which may aid in defining the origin of detected thiouracil. Hereto, a parallel-like randomized in vivo study was conducted in which calves (n = 8) and cows (n = 8) were subjected to either a control treatment, rapeseed-enriched diet to induce semi-endogenous formation, or thiouracil treatment. Urine samples (n = 330) were assessed through metabolic fingerprinting, employing liquid-chromatography and Q-ExactiveTM Orbitrap mass spectrometry. Urinary fingerprints comprised up to 40,000 features whereby multivariate discriminant analysis was able to point out significant metabolome differences between treatments (Q2(Y) ≥ 0.873). Using the validated models, a total of twelve metabolites (including thiouracil) were assigned marker potential. Combining these markers into age-dependent biomarker panels rendered a tool by which sample classification could be improved in comparison with thiouracil-based thresholds, and this during on-going thiouracil treatment (specificities ≥ 95.2% and sensitivities ≥ 85.7%), post-treatment (sensitivities ≥ 80% for ≥ 24 h after last administration), and simulated low-dose thiouracil treatment (exogenous thiouracil below 30 ng µL-1). Moreover, the metabolic relevance of revealed markers was supported by the suggested identities, for which a structural link with thiouracil could be determined in most cases. The proposed biomarker panels may contribute to a more justified decision-making in monitoring thiouracil abuse.