Comprehensive metabolic profiling of dioxin-like compounds exposure in laying hens: Implications for toxicity assessment.

The evaluation of toxicity related to polychlorinated dibenzo-p-dioxins and furans (PCDD/Fs) and dioxin-like polychlorinated biphenyls (DL-PCBs) is crucial for a comprehensive risk assessment in real-world exposure scenarios. This study employed a controlled feeding experiment to investigate the metabolic effects of dioxin-like compounds (DLCs) on laying hens via feed exposure. Diets enriched with two concentrations (1.17 and 5.13 pg toxic equivalents (TEQ)/g dry weight (dw)) were administered over 14 days, followed by 28 days of clean feed. Metabolomics analyses of blood samples revealed significant metabolic variations between PCDD/Fs and DL-PCBs exposed groups and controls, reflecting the induced metabolic disruption. Distinct changes were observed in sphingosine, palmitoleic acid, linoleate, linolenic acid, taurocholic acid, indole acrylic acid, and dibutyl phthalate levels, implying possible connections between PCDD/Fs and DL-PCBs toxic effects and energy-neuronal imbalances, along with lipid accumulation and anomalous amino acid metabolism, impacting taurine metabolism. Moreover, we identified three differential endogenous metabolites-L-tryptophan, indole-3-acetaldehyde, and indole acrylic acid-as potential ligands for the aryl hydrocarbon receptor (AhR), suggesting their role in mediating PCDD/Fs and DL-PCBs toxicity. This comprehensive investigation provides novel insights into the metabolic alterations induced by PCDD/Fs and DL-PCBs in laying hens, thereby enhancing our ability to assess risks associated with their exposure in human populations.

Metabolic profiling of pea (Pisum sativum) cultivars in changing environments: Implications for nutritional quality in animal feed.

Field pea seeds have long been recognized as valuable feed ingredients for animal diets, due to their high-quality protein and starch digestibility. However, the chemical composition of pea cultivars can vary across different growing locations, consequently impacting their nutrient profiles. This study employs untargeted metabolomics in conjunction with the quantification of fatty acids and amino acids to explore the influence of three different growing locations in Spain (namely Andalusia, Aragon and Asturias), on the nutritional characteristics of seeds of various pea cultivars. Significant interactions between cultivar and environment were observed, with 121 metabolites distinguishing pea profiles. Lipids, lipid-like molecules, phenylpropanoids, polyketides, carbohydrates, and amino acids were the most affected metabolites. Fatty acid profiles varied across locations, with higher C16:0, C18:0, and 18:1 n-9 concentration in Aragón, while C18:2 n-6 predominated in Asturias and C18:3 n-3 in Andalusia. Amino acid content was also location-dependent, with higher levels in Asturias. These findings underscore the impact of environmental factors on pea metabolite profiles and emphasize the importance of selecting pea cultivars based on specific locations and animal requirements. Enhanced collaboration between research and industry is crucial for optimizing pea cultivation for animal feed production.

Metabolic profiles and protein expression responses of Pacific oyster (Crassostrea gigas) to polystyrene microplastic stress.

The underlying toxicity mechanisms of microplastics on oysters have rarely been explored. To fill this gap, the present study investigated the metabolic profile and protein expression responses of oysters to microplastic stress through metabolomics and biochemical analyses. Oysters were exposed to microplastics for 21 days, and the results indicated that the microplastics induced oxidative stress, with a significant decrease in SOD activity in the 0.1 mg/L exposure group. Metabolomics revealed that exposure to microplastics disturbed many metabolic pathways, such as amino acid metabolism, lipid metabolism, biosynthesis of amino acids, aminoacyl-tRNA biosynthesis, and that different concentrations of microplastics induced diverse metabolomic profiles in oysters. Overall, the current study provides new reference data and insights for assessing food safety and consumer health risks caused by microplastic contamination.

Seasonal variation in non-volatile flavor substances of fresh tea leaves (Camellia sinensis) by integrated lipidomics and metabolomics using UHPLC-Q-Exactive mass spectrometry.

Harvest season exerts great influence on tea quality. Herein, the variations in non-volatile flavor substances in spring and summer fresh tea leaves of four varieties were comprehensively investigated by integrating UHPLC-Q-Exactive based lipidomics and metabolomics. A total of 327 lipids and 99 metabolites were detected, among which, 221 and 58 molecules were significantly differential. The molecular species of phospholipids, glycolipids and acylglycerolipids showed most prominent and structure-dependent seasonal changes, relating to polar head, unsaturation and total acyl length. Particularly, spring tea contained higher amount in aroma precursors of highly unsaturated glycolipids and phosphatidic acids. The contents of umami-enhancing amino acids and phenolic acids, e.g., theanine, theogallin and gallotannins, were increased in spring. Besides, catechins, theaflavins, theasinensins and flavone/flavonol glycosides showed diverse changes. These phytochemical differences covered key aroma precursors, tastants and colorants, and may confer superior flavor of black tea processed using spring leaves, which was verified by sensory evaluation.

Modular, Scalable, and Customizable LC-HRMS for Exposomics.

In this chapter, we describe a multi-purpose, reversed-phase liquid chromatography-high-resolution mass spectrometry (LC-HRMS) workflow for acquiring high-quality, non-targeted exposomics data utilizing data-dependent acquisition (DDA) combined with the use of toxicant inclusion lists for semi-targeted analysis. In addition, we describe expected retention times for >160 highly diverse xenobiotics in human plasma and serum samples. The method described is intended to serve as a generic LC-HRMS exposomics workflow for research and educational purposes. Moreover, it may be employed as a primer, allowing for further adaptations according to specialized research needs, e.g., by including reference and/or internal standards, by expanding to data-independent acquisition (DIA), or by modifying the list of compounds prioritized in fragmentation experiments (MS2).

(Pre)Clinical Metabolomics Analysis.

Metabolomics is the scientific field with the eager goal to comprehensively analyze the entirety of all small molecules of a biological system, i.e., the metabolome. Over the last few years, metabolomics has matured to become an analytical cornerstone of life science research across diverse fields, from fundamental biochemical applications to preclinical studies, including biomarker discovery and drug development. In this chapter, we provide an introduction to (pre)clinical metabolomics. We define key metabolomics aspects and provide the basis to thoroughly understand the relevance of this field in a biological and clinical context. We present and explain state-of-the-art analytical technologies devoted to metabolomic analysis as well as emerging technologies, discussing both strengths and weaknesses. Given the ever-increasing demand for handling complex datasets, the role of bioinformatics approaches in the context of metabolomic analysis is also illustrated.

Global Metabolomics Using LC-MS for Clinical Applications.

Metabolomics can be used for a multitude of purposes, including monitoring of treatment effects and for increasing the knowledge of the pathophysiology of a wide range of diseases. Global (commonly referred to as "untargeted") metabolomics is hypothesis-generating and provides the opportunity to discover new biomarkers. Being versatile and having a high degree of selectivity and sensitivity, liquid chromatography-mass spectrometry (LC-MS) is the most common technique applied for metabolomics. We here present our global metabolomics LC-electrospray ionization-MS/MS method. The sample preparation procedures for plasma, serum, dried blood spots, urine, and cerebrospinal fluid are simple and nonspecific to reduce the risk of analyte loss. The method is based on reversed-phase chromatography using a diphenyl column. The high-resolution Q Exactive Orbitrap MS with data-dependent acquisition provides MS/MS spectra of a wide range of analytes. Our method covers a large part of the metabolome regarding hydrophobicity and compound class.

Stable Isotope Tracing Experiments Using LC-MS.

Metabolomics has emerged as a pivotal field in understanding cellular function, particularly in the context of disease. In numerous diseases, including cancer, alterations in metabolism play an essential role in disease progression and drug response. Hence, unraveling the metabolic rewiring is of importance to find novel diagnostic and therapeutic strategies. Isotope tracing is a powerful technique for delving deeper into the metabolic wiring of cells. By tracking an isotopically labeled substrate through biochemical reactions in the cell, this technique provides a dynamic understanding of cellular metabolism. This chapter outlines a robust isotope tracing protocol utilizing high-resolution mass spectrometry coupled to liquid chromatography in cell culture-based models. We cover essential aspects of experimental design and analyses, providing a valuable resource for researchers aiming to employ isotopic tracing.

Distinguishing Artifactual Fatty Acid Dimers from Fatty Acid Esters of Hydroxy Fatty Acids in Untargeted LC-MS Pipelines.

Untargeted metabolomics is a powerful profiling tool for the discovery of possible biomarkers of disease onset and progression. Analytical pipelines applying liquid chromatography (LC) and mass spectrometry (MS)-based methods are widely used to survey a broad range of metabolites within various metabolic pathways, including organic acids, amino acids, nucleosides, and lipids. Accurate and complete identification of putative metabolites is an ongoing challenge in untargeted metabolomics studies. Highly sensitive instrumentation can result in the detection of adduct and fragment ions that form reproducibly and contain identifiable ions that are difficult to distinguish from metabolic pathway intermediates, which may result in false-positive identification. At concentrations as low as 10 µM, free fatty acids have been found to form homo- and heterodimers in untargeted metabolomics pipelines that resemble the lipid class fatty acid esters of hydroxy fatty acids (FAHFAs), resulting in misidentification. This chapter details a protocol for LC-MS-based untargeted metabolomics using hydrophilic interaction chromatography (HILIC) that specifically aids in distinguishing artifactual fatty acid dimers from endogenous FAHFAs.

Prostaglandin Metabolites Analysis in Urine by LC-MS/MS.

The analysis of prostaglandin urinary metabolites is valuable for assessing physiological processes and identifying disease biomarkers. These metabolites, derived from the breakdown of prostaglandins, offer a noninvasive means to gauge prostaglandin production and its potential impact on various biological functions. We report an efficient LC-MS method of four commonly analyzed prostaglandin urinary metabolites including tetranor-PGEM (derived from PGE2), tetranor-PGDM, 11ß-PGF2α, and 2,3-dinor-11ß-PGF2α (derived from PGD2). Each metabolite possesses distinct characteristics and clinical applications, collectively contributing to our understanding of prostaglandin-mediated pathways.

NMR-Based Analysis of Cellular Central Energy Metabolism and Exchange Rates.

Cell cultures are widely used in studies to gain mechanistic insights of metabolic processes. The foundation of these studies lies on the quantification of intracellular and extracellular metabolites, and nuclear magnetic resonance (NMR) is one of the key analytical platforms used to this aim. Among the factors influencing the quality of the produced data are the sampling procedures as well as the acquisition and processing of spectroscopic data. Here we provide our workflow for obtaining quantitative metabolic data from adherent mammalian cells using NMR spectroscopy. The described protocol is compatible with other analytical methods like LC- or GC-MS-based lipidomics and untargeted metabolomics from the same sample. We also show how the collected extracellular data can be used to extract exchange flux rates, particularly useful for flux analysis studies and metabolic engineering of human-induced pluripotent stem cells.

CE-MS-Based Clinical Metabolomics of Human Plasma.

Capillary electrophoresis coupled to mass spectrometry (CE-MS) has emerged as a powerful analytical technique with significant implications for clinical research and diagnostics. The integration of information from CE and MS strengthens confidence in the identification of compounds present in clinical samples. The ability of CE to separate molecules based on their electrophoretic mobility coupled to MS enables the accurate identification and quantification of analytes, even in complex biological matrices such as human plasma.Here, we present a detailed protocol for an untargeted metabolomics study using CE-MS and its application in a study on human plasma from patients suffering Long COVID syndrome. The protocol ranges from sample preparation to biological interpretation, detailing a workflow enabling the analysis of cationic and anionic compounds, metabolite identification, and data processing.

Extracting Knowledge from MS Clinical Metabolomic Data: Processing and Analysis Strategies.

Assessing potential alterations of metabolic pathways using large-scale approaches plays today a central role in clinical research. Because several thousands of mass features can be measured for each sample with separation techniques hyphenated to mass spectrometry (MS) detection, adapted strategies have to be implemented to detect altered pathways and help to elucidate the mechanisms of pathologies. These procedures include peak detection, sample alignment, normalization, statistical analysis, and metabolite annotation. Interestingly, considerable advances have been made over the last years in terms of analytics, bioinformatics, and chemometrics to help massive and complex metabolomic data to be more adequately handled with automated processing and data analysis workflows. Recent developments and remaining challenges related to MS signal processing, metabolite annotation, and biomarker discovery based on statistical models are illustrated in this chapter in light of their application to clinical research.

Quantitative Blood Serum IVDr NMR Spectroscopy in Clinical Metabolomics of Cancer, Neurodegeneration, and Internal Medicine.

Despite more than two decades of metabolomics having joined the "omics" scenery, to date only a few novel blood metabolite biomarkers have found their way into the clinic. This is changing now by massive large-scale population metabolic phenotyping for both healthy and disease cohorts. Here, nuclear magnetic resonance (NMR) spectroscopy is a method of choice, as typical blood serum markers can be easily quantified and by knowledge of precise reference concentrations, more and more NMR-amenable biomarkers are established, moving NMR from research to clinical application. Besides customized approaches, to date two major commercial platforms have evolved based on either 600 MHz (14.1 Tesla) or 500 MHz (11.7 Tesla) high-field NMR systems. This chapter provides an introduction into the field of quantitative in vitro diagnostics research (IVDr) NMR at 600 MHz and its application within clinical research of cancer, neurodegeneration, and internal medicine.

Application of a Computational Metabolomics Workflow for the Diagnosis of Inborn Errors of Metabolism in a Laboratory Setting.

Inborn errors of metabolism constitute a set of hereditary diseases that impose severe medical and physical challenges in the affected individual, in particular, for the pediatric patient population. Timely diagnosis is crucial for these patients, as any delay could result in irreversible health damage, underscoring the importance of early initiation of personalized treatment. Current routine diagnostic screening for inborn errors of metabolism relies on various targeted analyses of established biomarkers. However, this approach is time-consuming, focuses on a limited number of tests (based on clinical information) with a relatively small number of biomarkers, and does not facilitate the identification of new markers. In contrast, untargeted metabolomics-based screening offers a more efficient diagnostic solution, by assessing thousands of metabolites across multiple metabolic pathways in a single test. This not only saves time but also conserves resources for clinicians, the diagnostic laboratory, and for patients.This chapter describes the computational workflow of our "Next Generation Metabolic Screening" approach, which is a metabolomics-based method that is currently applied at the Translational Metabolic Laboratory of the Radboud University Medical Center (the Netherlands) for the diagnosis of inborn errors of metabolism.

In Situ Isotope Tracing at Single-Cell Resolution Using Mass Spectrometry Imaging.

Mass spectrometry imaging (MSI) allows for label-free spatial molecular interrogation of tissues. With advances in the field over recent years, the spatial resolution at which MSI data can be recorded has reached the single-cell level. This makes MSI complementary to other single-cell omics technologies. As metabolism is a highly dynamic process, capturing the metabolic turnover adds a valuable layer of information. Here, we describe how to set up in situ stable isotope tracing followed by MSI-enabled spatial metabolomics to perform dynamic metabolomics at the single-cell level.

NMR-Based Stable Isotope Tracing of Cancer Metabolism.

NMR is widely used for metabolite profiling (metabolomics, metabonomics) particularly of various readily obtainable biofluids such as plasma and urine. It is especially valuable for stable isotope tracer studies to track metabolic pathways under control or perturbed conditions in a wide range of cell models as well as animal models and human subjects. NMR has unique properties for utilizing stable isotopes to edit or simplify otherwise complex spectra acquired in vitro and in vivo, while quantifying the level of enrichment at specific atomic positions in various metabolites (i.e., isotopomer distribution analysis).In this protocol, we give an overview with specific protocols for NMR-based stable isotope-resolved metabolomics, or SIRM, with a workflow from administration of isotope-enriched precursors, via sample preparation through to NMR data collection and reduction. We focus on indirect detection of common NMR-active stable isotopes including 13C, 15N, 31P, and 2H, using a variety of 1H-based two-dimensional experiments. We also include the application and analyses of multiplex tracer experiments.

Metabolomic and gut-microbial responses of earthworms exposed to microcystins and nano zero-valent iron in soil.

The earthworm-based vermiremediation facilitated with benign chemicals such as nano zero-valent iron (nZVI) is a promising approach for the remediation of a variety of soil contaminants including cyanotoxins. As the most toxic cyanotoxin, microcystin-LR (MC-LR) enter soil via runoff, irrigated surface water and sewage, and the application of cyanobacterial biofertilizers as part of the sustainable agricultural practice. Earthworms in such remediation systems must sustain the potential risk from both nZVI and MC-LR. In the present study, earthworms (Eisenia fetida) were exposed up to 14 days to MC-LR and nZVI (individually and in mixture), and the toxicity was investigated at both the organismal and metabolic levels, including growth, tissue damage, oxidative stress, metabolic response and gut microbiota. Results showed that co-exposure of MC-LR and nZVI is less potent to earthworms than that of separate exposure. Histological observations in the co-exposure group revealed only minor epidermal brokenness, and KEGG enrichment analysis showed that co-exposure induced earthworms to regulate glutathione biosynthesis for detoxification and reduced adverse effects from MC-LR. The combined use of nZVI promoted the growth and reproduction of soil and earthworm gut bacteria (e.g., Sphingobacterium and Acinetobacter) responsible for the degradation of MC-LR, which might explain the observed antagonism between nZVI and MC-LR in earthworm microcosm. Our study suggests the beneficial use of nZVI to detoxify pollutants in earthworm-based vermiremediation systems where freshwater containing cyanobacterial blooms is frequently used to irrigate soil and supply water for the growth and metabolism of earthworms.

Seasonal variations and sensory profiles of oolong tea: Insights from metabolic analysis of Tieguanyin cultivar.

The impact of seasonal variations on the quality of oolong tea products remains a subject of ongoing exploration. This study delves into the intricate relationships between seasonality, metabolites, and sensory characteristics in finished oolong tea products. Metabolomic data from 266 Tieguanyin oolong tea products harvested in both spring and autumn, along with corresponding sensory evaluations, were acquired. Using OPLS-DA and PLS-DA models with UPLC-QToF/MS data, our findings showed that seasonal effects were notably more pronounced in light-scented Tieguanyin products (lightly-roasted) compared to strong-scented products (moderately-roasted). Furthermore, over half of the identified key seasonal discriminant metabolites happened to be crucial for determining the sensory grade. The study marks the first-time recognition of triterpene saponins as critical factors in determining both the harvest season and the sensory grade of oolong tea. These insights deepen our understanding of the interplays between seasonal variations, metabolites, and sensory attributes in oolong tea products.

Targeted/untargeted metabolomics and antioxidant properties distinguish Citrus reticulata 'Chachi' from Citrus reticulata Blanco.

Dried citrus peel (DCP), also called "Chen Pi", has edible and medicinal value. However, the specific differences among various sources remain unknown. Herein, we collected six DCP species, namely, one Citrus reticulata 'Chachi' (CZG) and five Citrus reticulata Blanco (CRB). Targeted high-performance liquid chromatography and untargeted ultra-high-performance liquid chromatography-tandem mass spectrometry were employed to comprehensively compare the phenolic compounds and metabolites in DCP. Interestingly, 13 different phenolic compounds were noted in DCP. The total phenolic compound content in all CRB samples (58.86-127.65 mg/g) was higher than that of CZG (39.47 mg/g). Untargeted metabolomic revealed 1495 compounds, with 115 differentially expressed metabolites for CRBs and CZG, particularly flavonoids (38), terpenoids (15), and phenolic acids and derivatives (9). Lastly, antioxidant assays revealed that all CRB samples exhibited higher antioxidant activities compared with CZG. Therefore, our study results provide a theoretical basis for the high-value utilization of citrus peels and their metabolites.