Metabolites最新文献

Background/Objectives: Circulating inflammatory cytokines and tissue sensitivity are both elevated following heat stress-induced intrauterine growth restriction (IUGR). Cytokines disrupt myoblast function and muscle growth, and thus we hypothesized that suppressing inflammatory tone in IUGR-born lambs by supplementing anti-inflammatory nutraceuticals would improve early postnatal growth. Methods: IUGR lambs produced by maternal heat stress were supplemented daily with 42 mg/kg oral omega-3 polyunsaturated fatty acid (ω-3 PUFA) Ca²⁺ salts or placebo from birth to 28 days of age. Results: By day 28, the 21% lighter bodyweights for IUGR lambs were fully resolved by ω-3 PUFA due to the complete recovery of average daily gain. Subcutaneous fat deposition and visceral organ growth were modestly diminished in IUGR-born lambs, but skeletal muscle mass was more markedly restricted. This coincided with 63% less muscle AdipoR2 but 27% greater circulating adiponectin. ω-3 PUFA reduced or eliminated deficits in subcutaneous fat, visceral organs, and five of the six individual muscles assessed, which corresponded with rescue of myoblast populations and AdipoR2 content. In turn, asymmetric growth restriction was resolved at one month of age. Conclusions: These findings show that targeting heightened inflammatory tone during the neonatal period in IUGR-born offspring can recover early growth in skeletal muscle and other soft tissues.

Background: Pulmonary neuroendocrine cells (PNECs) are rare airway sensory cells implicated in amplifying allergic inflammation, yet due to their scarcity, the contribution of PNECs to the metabolic programs and responses of the airway epithelium remains poorly defined. Using a newly developed PNEC-enriched human airway epithelial model (ePNEC), we investigated the influence of PNECs on neuroendocrine and immune-modulatory metabolite production in response to the common aeroallergen of the house dust mite (HDM). Methods: Human bronchial epithelial cells (HBECs) and ePNEC cultures were differentiated at the air-liquid interface. Global untargeted metabolomics was performed to quantify metabolite abundance at baseline and following stimulation with HDMs. Differential expression, overlap significance, metabolite class enrichment, and pathway analyses were used to define PNEC-specific metabolic programs. Results: Principal component analysis (PCA) demonstrated strong baseline separation between ePNECs and HBECs, with HDMs inducing additional within-cell-type shifts. ePNECs displayed broader and more pronounced metabolite changes than HBECs. Baseline differences were largely preserved following allergen exposure, with significant overlap in both up- and down-regulated metabolites. ePNECs exhibited enriched neurotransmitter-linked metabolites-including serotonin, L-noradrenaline, dopamine, and histamine-at baseline and after HDM exposure. Amino acid-centered metabolism dominated the dataset, with enhanced histidine and tryptophan pathway activity in ePNECs. Pathway analysis revealed significant enrichment of phenylalanine, tyrosine, tryptophan, glutathione, and arginine-proline metabolism in ePNECs, whereas HBECs showed no significant pathway-level enrichment after HDM exposure. Conclusions: Human ePNECs engage a distinct, neuroactive metabolic program that is amplified upon HDM exposure. These findings provide a metabolic framework for how PNECs shape epithelial and neuroimmune responses to inhaled allergens.

Background/Objectives: Per- and polyfluoroalkyl substances (PFAS) are persistent environmental pollutants that accumulate in humans through everyday exposure pathways, raising concern about long-term metabolic health effects in exposed populations. This study aimed to characterize PFAS-associated serum metabolic alterations in a Flemish population residing within a 3 km radius of a PFAS production facility using untargeted metabolomics and lipidomics. Methods: A cohort of 82 adults was stratified into high-exposure (n = 41, median total PFAS = 162.0 ng/mL) and low-exposure (n = 41, median total PFAS = 7.2 ng/mL) groups. Serum metabolic profiling was performed using four liquid chromatography-high-resolution mass spectrometry (LC-HRMS)-based platforms. Univariate and multivariate statistics were conducted to identify metabolites that were differentially expressed between both exposure groups. Results: The analysis revealed 38 altered metabolites. Overall, high PFAS exposure was characterized by upregulation of phosphatidylglycerols (PG), phosphatidylinositols, phosphatidylethanolamines (PE), and triacylglycerols (TG) and downregulation of sphingomyelins, with differential regulation of ceramides, hexosylceramides (HexCer), and phosphatidylcholines. Glycerophospholipid metabolism as well as sphingolipid metabolism pathways were identified as perturbed. Seven lipids and one amino acid showed weak-to-strong correlations (|r|= 0.23-0.61) with PFAS levels. A panel of five metabolites was selected to explore whether they collectively form a potential metabolic signature associated with PFAS exposure. This panel, including L-aspartic acid, PG 18:0_18:2, HexCer (d18:1/14:0), PE 16:0_18:3, and TG 16:0_20:5_22:6, showed moderate discrimination between residents with high and low PFAS levels (area under the curve, AUC = 0.753). Conclusions: This study identifies coordinated lipid metabolic changes associated with PFAS exposure and highlights a small, exploratory metabolite panel that may provide complementary insight into the biological effects of PFAS.

Introduction: The availability of toxicokinetic data is critical for detecting and monitoring the intake of psychoactive substances. Timely characterization of novel psychoactive substances (NPS) is particularly important to assess their abuse potential and inform public health responses. Methods: Toxicometabolomics offers a powerful approach to characterize xenobiotic metabolism through high-resolution profiling of biochemical transformations. It thus allows the finding of exogenous biomarkers, such as new drug metabolites, and endogenous biomarkers, which could be indications of acute drug ingestions or sample manipulation, as well as offering information on the mode of action of drugs. In this study, we applied a liquid chromatography-high-resolution mass spectrometry workflow to investigate the toxicometabolomics of two N1-sulfonated N,N-dimethyltryptamine derivatives with potential for both therapeutic use and recreational abuse. Results: Zebrafish (Danio rerio), an increasingly valuable model for preclinical pharmacology and toxicology studies, along with pooled human liver S9 fractions were used to elucidate metabolic pathways and identify key phase I and phase II biotransformations. Furthermore, untargeted metabolomics revealed significant downregulation of L-threonine associated with compound exposure. Conclusions: These findings advance the current understanding of tryptamine metabolism and underscore the utility of toxicometabolomics in the analytical evaluation of NPS.

Background: Obesity is one of the most prevalent metabolic disorders worldwide, and its long-term management remains challenging due to the limited efficacy and adverse effects of current pharmacological treatments. Accordingly, there is growing interest in safe and effective anti-obesity strategies based on natural compounds. This study aimed to evaluate the anti-obesity effects of HT099, an extract derived from Prunus persica (peach blossom), and to investigate molecular changes associated with its metabolic effects in a high-fat diet (HFD)-induced obesity mouse model. Methods: Male C57BL/6N mice were fed an HFD and orally administered HT099 (50 or 100 mg/kg) or the positive control orlistat (40 mg/kg) for 12 weeks. Body weight, adipose tissue accumulation, food efficiency ratio, glucose tolerance, serum lipid profiles, and hepatic gene expression related to lipid metabolism were evaluated. Results: HT099 supplementation significantly attenuated body weight gain and reduced white adipose tissue accumulation while improving food efficiency ratio. HT099 also ameliorated HFD-induced glucose intolerance and favorably modulated serum lipid profiles, including reduced triglyceride levels, increased HDL-cholesterol levels, and improved non-HDL cholesterol indices. At the molecular level, HT099 administration was associated with an increased hepatic AMPKα1 mRNA expression and decreased expression of adipogenic and lipogenic genes, including C/EBPα, PPARγ, FAS, and SREBP-1c. Conclusions: These findings indicate that HT099 exerts anti-obesity effects in HFD-induced obese mice, accompanied by improvements in lipid and glucose metabolism and changes in adipogenesis- and lipogenesis-related gene expression. Collectively, the results support the potential of HT099 as a natural bioactive agent for obesity management.

Background: Metabolic reprogramming is a hallmark of cancer and supports tumor growth and adaptation within the tumor microenvironment (TME). The complexity of this reprogramming manifests as both distinct variations across cancer types and spatial heterogeneity within individual tumors. The specificity of these metabolic alterations, whether to cancer type, spatial niche, or as shared features, remains unclear, highlighting a critical gap in our systematic, pan-cancer understanding of metabolic reprogramming.

Methods: We integrated bulk metabolomics and spatial metabolomics to investigate pan-cancer metabolic features and used blood-based metabolomics and spatial transcriptomics data to validate key findings. Metabolic differences were compared between tumor and normal tissues across multiple cancer types at the bulk level to identify metabolic modules shared across cancers or specific to individual cancer types. A two-step clustering framework was applied to identify both local and global TME-associated spatial metabolic modules of spatial metabolomics data from various tumor tissue slices.

Results: We have identified a spectrum of metabolic features, including those specific to individual cancer types or spatial architectures and others shared across cancers, with some features emerging only at bulk-level and others uniquely discernible through spatial metabolomics. Integrative analyses also identified 19 metabolites consistently altered in both bulk and spatial data, especially carnitine species, which also showed concordant changes in blood samples and spatial associations with genes involved in fatty acid metabolism.

Conclusions: This pan-cancer, multi-scale integrative analysis highlights substantial metabolic heterogeneity within the TME and across cancer types and identifies metabolites with consistent alterations across analytical layers, providing candidate features for future studies of tumor metabolism and potential metabolic biomarkers.

Background/objectives: Plants alter metabolites of their fruits during the ripening process, leading to improved nutritional properties and taste. In addition, metabolite compositions continue to change on the shelf after harvest. However, the dynamics of these important processes are species-specific and so this study aimed to contrast the ripening dynamics of ten different fruit species simultaneously.

Methods: Plant material was collected from the fruits of apple, banana, blueberry, kiwifruit, pear, plum, peach, strawberry, raspberry, and tomato at three different stages: unripe, fully ripe, and overripe fruits. Comparative metabolome analysis by GCMS was performed to identify differentially abundant metabolites across the species of this study and to examine their dynamics across ripening and post-harvest storage. These results were complemented by elemental compositions derived from a literature search.

Results: In a first, this study demonstrated that both baseline metabolite abundances and their dynamics across ripening clustered species vary largely according to their phylogeny. Comparisons across ripe fruit identified differences in nutritional properties, highlighting species such as banana to be of especially high nutritional value and blueberry and peach to be prominent sources of antioxidants. Comparing the ripening dynamics of all species identified common patterns, such as the conversion of organic acids to sugars and cell wall dynamics, although species-specific responses were also acknowledged, in particular, kiwi and the Rosaceae berries, which may explain differences in post-harvest shelf-life.

Conclusions: The observed inter- and intra-specific variation in nutritionally relevant metabolites and elements serves as a reference for both producers and consumers and emphasizes that consuming a variety of fruits, not only across species but also across cultivars within a species, can maximize the intake of beneficial phytonutrients, sugars, amino acids, and antioxidants.

Background/Objectives: Cardiovascular involvement drives morbidity and mortality in systemic lupus erythematosus (SLE). Echocardiography has limited predictive value for long-term outcomes, and subclinical right ventricular (RV) remodeling is poorly characterized. Metabolic dysregulation may influence immune activation and myocardial injury. This study investigates whether baseline metabolomic profiles are associated with longitudinal RV changes and disease progression in SLE. Methods: In this prospective, single-center study, patients with established SLE and no known cardiac disease underwent baseline clinical assessment, plasma metabolomic profiling, and advanced echocardiography, including 3D RV analysis. Echocardiography was repeated after 6 years. Metabolomics was performed using NMR spectroscopy and GC-MS. Disease progression was assessed via the SLICC/ACR damage index (SDI), defining clinical stability as ΔSDI = 0 and worsening as ΔSDI ≥ 1. Results: Twenty-five patients completed the follow-up (88% female; mean age 51 ± 13 years). Despite normal echocardiographic values, subtle but significant RV changes were observed, remaining within reference ranges, including mild declines in fractional area change and septal longitudinal strain (p < 0.05). Clinically worsened patients showed reduced TAPSE, while stable patients had slight increases (p < 0.05). Multivariate metabolomic analysis distinguished stable from worsened patients (R²Y = 0.772; Q² = 0.483), primarily driven by higher 2-aminoheptanedioic acid values in those with progression (p < 0.05), along with trends toward higher fumarate and lower fructose and glucopyranose. Conclusions: Baseline metabolomic and advanced echocardiographic profiling may identify SLE patients at risk of disease progression. Longitudinal echocardiography enables monitoring of subtle RV changes, supporting personalized surveillance to detect early subclinical trajectories before overt dysfunction develops.

Background/Objectives: This study was based on the joint analysis of transcriptome and metabolome to explore the key genes and metabolic pathways of gardenia single flower petal number variation and to explore the possible mechanism of floral organ variation. Methods: Five, six, and seven petals of single-flower gardenia were selected as test materials for transcriptome and metabolome determination to excavate the key genes in regulating petal number in gardenia. Results: Metabolomic analysis identified triethylamine, succinic acid, succinylaldehyde, 2-phenylethanol, and o-xylene as the top five differentially expressed metabolites affecting petal number variation in gardenia. In the KEGG enrichment analysis, gardenia five, six, and seven DEGs were mainly enriched in amphetamine biosynthesis, the biosynthesis of plant secondary metabolites; transcriptome results showed that the identified differential transcription factors mainly come from NAC, ERF, C2H2, MYB, and MADS-box gene families; the expression of GjMADS50, GjMADS59, and GjERF28 changed with the increase in petal number. The commonality between gardenia five, six, and seven flowers exceeded the difference, and the expression pattern of MADS-box and ERF gene family members was the upregulation of GjERF28, GjERF39, and GjMADS67 and downregulation of GjMADS50, GjMADS59, and GjMADS60. Conclusions: We propose that ERF transcription factors may determine the initial number of petal primordia by mediating gibberellin biosynthesis or signaling, thereby coordinately regulating floral meristem activity and specific metabolic states.

Background/objectives: Fig (Ficus carica L.) seed oil represents an underexplored by-product with considerable nutraceutical potential. However, systematic evaluation of genotype × environment (G × E) interactions affecting its biochemical composition remains limited. This study assessed compositional variability across fig varieties, identified metabolic trade-offs, and developed rapid authentication protocols using FTIR-ATR spectroscopy to support predictive G × E models and marker-assisted selection.

Methods: Thirty-seven fig varieties were evaluated across two consecutive harvest years (2023-2024) in Morocco. Conventional biochemical analyses measured total phenolic content (TPC), total flavonoid content (TFC), DPPH and ABTS antioxidant activities, and oil yield. FTIR-ATR spectroscopy characterized spectral variations, with ANOVA assessing effects of year, variety, and G × E interactions. Principal Component Analysis (PCA) discriminated genotypes and years.

Results: TPC varied substantially (16.5-115.1 mg GAE/100 g oil), declining 36% from 2023 (48.7 ± 16.6 mg GAE/100 g) to 2024 (31.2 ± 16.6 mg GAE/100 g; F = 1372.84, p < 0.001), with TFC showing parallel trends (15.6 vs. 11.8 mg QCE/100 g). DPPH activity increased 34% in 2024 (58.5% vs. 43.7%), while ABTS activity decreased 18.6% from 32.34 ± 14.28% to 26.31 ± 6.10% (p < 0.001). Oil yield decreased from 26.7% to 21.2% and negatively correlated with phenolic accumulation (r = -0.49, p < 0.001). FTIR-ATR identified diagnostic peaks (e.g., 3012, 2928 cm^-1), with significant G × E effects (p < 0.001). PCA captured 75.4-84.5% variance, discriminating genotypes and years. Stable high-value cultivars included 'Dottato Perguerolles', 'VCR 276/49', and 'Ferqouch Jmel'.

Conclusions: Genotypic differences and year-to-year environmental conditions significantly influence fig seed oil composition. The observed negative correlation between oil yield and phenolic content indicates a trade-off between lipid biosynthesis and secondary metabolism. FTIR-ATR spectroscopy coupled with multivariate analysis enables reliable variety discrimination and year differentiation, supporting the development of stable cultivars for nutraceutical applications.