PubMed

Metabolites. 2025 Mar 13;15(3):198. doi: 10.3390/metabo15030198.ABSTRACTCardiovascular diseases are a leading cause of death worldwide, and the process of cardiac remodeling lies at the core of most of these diseases. Sustained cardiac remodeling almost unavoidably ends in progressive muscle dysfunction, heart failure, and ultimately death. Therefore, in order to attenuate cardiac remodeling and reduce mortality, different therapies have been used, but it is important to identify adjuvant factors that can help to modulate this process. One of these factors is the inclusion of affordable foods in the diet with potential cardioprotective properties. Orange juice intake has been associated with several beneficial metabolic changes, which may influence cardiac remodeling induced by cardiovascular diseases. Current opinion highlights how the metabolites and metabolic pathways modulated by orange juice consumption could potentially attenuate cardiac remodeling. It was observed that orange juice intake significantly modulates phospholipids, energy metabolism, endocannabinoid signaling, amino acids, and gut microbiota diversity, improving insulin resistance, dyslipidemia, and metabolic syndrome. Specifically, modulation of phosphatidylethanolamine (PE) metabolism and activation of PPARα and PPARγ receptors, associated with improved energy metabolism, mitochondrial function, and oxidative stress, showed protective effects on the heart. Furthermore, orange juice intake positively impacted gut microbiota diversity and led to an increase in beneficial bacterial populations, correlated with improved metabolic syndrome. These findings suggest that orange juice may act as a metabolic modulator, with potential therapeutic implications for cardiac remodeling associated with cardiovascular diseases.PMID:40137162 | DOI:10.3390/metabo15030198

Metabolites. 2025 Mar 11;15(3):193. doi: 10.3390/metabo15030193.ABSTRACTBackground/Objectives: Metabolomic studies of different parasite-derived biomolecules, such as lipids, are needed to broaden the discovery of novel targets and overcome anthelmintic resistance. Lipids are involved in diverse functions in biological systems, including parasitic helminths, but little is known about their role in the biology of these organisms and their impact on host-parasite interactions. This study aimed to characterize the lipid profile secreted by Haemonchus contortus, the major parasitic nematodes of farm ruminants. Methods: H. contortus adult worms were recovered from infected sheep and cultured ex vivo. Parasite medium was collected at different time points and samples were subjected to an untargeted global lipidomic analysis. Lipids were extracted and subjected to Liquid Chromatography-Mass Spectrometry (LC-MS/MS). Annotated lipids were normalized and subjected to statistical analysis. Lipid clusters' fold change (FC) and individual lipid features were compared at different time points. Lipids were also analyzed by structural composition and saturation bonding. Results: A total of 1057 H. contortus lipid features were annotated, including glycerophospholipids, fatty acyls, sphingolipids, glycerolipids, and sterols. Most of these compounds were unsaturated lipids. We found significant FC differences in the lipid profile in a time-dependent manner. Conclusions: We predict that many lipids found in our study act as signaling molecules for nematodes' physiological functions, such as adaptation to nutrient changes, life span and mating, and as modulators on the host immune responses.PMID:40137157 | DOI:10.3390/metabo15030193

Metabolites. 2025 Mar 11;15(3):192. doi: 10.3390/metabo15030192.ABSTRACTBACKGROUND: The metabolome of COVID-19 patients has been studied sparsely, with most research focusing on a limited number of plasma metabolites or small cohorts. This is the first study to test saliva metabolites in COVID-19 patients in a comprehensive way, revealing patterns significantly linked to disease and severity, highlighting saliva's potential as a non-invasive tool for pathogenesis or diagnostic studies.METHODS: We included 30 asymptomatic subjects with no prior COVID-19 infection or vaccination, 102 patients with mild SARS-CoV-2 infection, and 61 hospitalized patients with confirmed SARS-CoV-2 status. Saliva samples were analyzed using hydrophilic interaction liquid chromatography-mass spectrometry (HILIC-MS/MS) in positive and negative ionization modes.RESULTS: Significant differences in metabolites were identified in COVID-19 patients, with distinct patterns associated with disease severity. Dipeptides such as Val-Glu and Met-Gln were highly elevated in moderate cases, suggesting specific protease activity related to SARS-CoV-2. Acetylated amino acids like N-acetylserine and N-acetylhistidine increased in severe cases. Bacterial metabolites, including muramic acid and indole-3-carboxaldehyde, were higher in mild-moderate cases, indicating that oral microbiota differs according to disease severity. In severe cases, polyamines and organ-damage-related metabolites, such as N-acetylspermine and 3-methylcytidine, were significantly increased. Interestingly, most metabolites that were reduced in moderate cases were elevated in severe cases.CONCLUSIONS: Saliva metabolomics offers insightful information that is potentially useful in studying COVID-19 severity and for diagnosis.PMID:40137156 | DOI:10.3390/metabo15030192

Metabolites. 2025 Mar 11;15(3):189. doi: 10.3390/metabo15030189.ABSTRACTPinellia ternata (Thunb.) Breit is a widely used medicinal herb in Traditional Chinese Medicine (TCM). Still, its sustainable cultivation is threatened by continuous cropping obstacles, which disrupt soil ecosystems, reduce yield, and degrade quality. Objectives: This study explores the potential of microbial inoculants to mitigate these challenges through integrated metabolomic and transcriptomic analyses. Methods: Soil samples from fields with and without continuous cropping issues were used to compare the effects of microbial inoculants on the secondary metabolism and gene expression of P. ternata. Results and Discussion: Metabolomic profiling identified 20,969 metabolites, with significant changes in lipid-like molecules (22.2%), organic acids (9.1%), and phenylpropanoids (7.0%) under microbial treatment. Notable increases in phenylalanine and caffeic acid levels were observed in microbial-inoculated plants. Correspondingly, transcriptomic analysis revealed the upregulation of phenylalanine ammonia-lyase (PAL) and other stress-related genes, confirming the metabolic shifts. Clustering and machine learning analyses highlighted the critical roles of metabolites and genes in enhancing plant resilience. Microbial inoculants improved secondary metabolite production. Implications: These findings provide valuable insights into the mechanisms of microbial-plant interactions and establish a sustainable approach for cultivating P. ternata, addressing the challenges of continuous cropping while improving crop productivity and quality.PMID:40137154 | DOI:10.3390/metabo15030189

Metabolites. 2025 Mar 11;15(3):188. doi: 10.3390/metabo15030188.ABSTRACTObjectives: Ziziphi spinosae semen (ZSS), an edible and medicinal substance, was easily infested by Plodia interpunctella (P. interpunctella) during storage. However, there was no identification method for insect-infested ZSS based on its chemical composition. Therefore, the characteristic compounds in ZSS before and after being infested by P. interpunctella were discovered based on the comparison of volatile organic compounds (VOCs), untargeted metabolomics, and other quality characters. Methods: Color, total flavonoid content (TFC), and main active compound content were measured to explore the change of physicochemical properties in ZSS after being infested by P. interpunctella. Non-targeted metabolomic techniques, including ultra-performance liquid chromatography-mass spectrometry (UPLC-MS) and headspace solid-phase microextraction-gas chromatography-mass spectrometry (HS-SPME-GC-MS) were used to assess molecular-level alterations. Results: The color changed significantly. The TFC and main active compounds of spinosin, jujuboside A, jujuboside B, and betulinic acid were decreased significantly. A total of nine VOCs and twenty-one metabolites were screened out that could be used to identify whether ZSS was infested. And some metabolites, such as uric acid, gluconic acid, hypoxanthine, and xanthine, were discovered as characteristic compounds in ZSS after being infested by P. interpunctella. Conclusions: The study provided the basis and reference for the identification of insect-infested ZSS and offered an example for the identification of other insect-infested edible and medicinal materials.PMID:40137152 | DOI:10.3390/metabo15030188

Metabolites. 2025 Mar 6;15(3):179. doi: 10.3390/metabo15030179.ABSTRACTBackground/Objectives: Prenatal depression (PND) poses a significant threat to the health of both the mother and the developing fetus. Despite its increasing prevalence, the pathophysiology of PND is not yet fully elucidated. Methods: In this study, we aimed to investigate the fecal metabolites and gut microbiota in PND patients compared to healthy controls and to explore potential correlations between these factors. Results: Through untargeted metabolomics analysis, we identified 75 significantly altered metabolites in PND patients, of which 27 were structurally annotated and implicated key pathways, such as linoleic acid metabolism and phenylalanine, tyrosine, and tryptophan biosynthesis. Notably, two Clostridia-associated enterobacteria, unclassified_c_Clostridia and unclassified_f_Lachnospiraceae, which were enriched in the PND group, were significantly positively correlated with tyrosine and negatively correlated with multiple sulfated neurosteroids. Conclusions: Our findings underscore a robust association between gut microbiota dysbiosis and metabolic disturbances in PND, with specific alterations noted in tyrosine metabolism, sulfated neurosteroid homeostasis, and linoleic acid pathways. These dysregulated metabolites-tyrosine, sulfated neurosteroids, and linoleic acid-may serve as potential diagnostic biomarkers and therapeutic targets. Moreover, their interplay provides new insights into the pathophysiological mechanisms of PND, particularly highlighting the role of gut-brain axis signaling in neuroendocrine dysregulation and inflammatory responses. However, further large-scale studies and animal models are required to validate these findings and explore detailed mechanistic pathways.PMID:40137144 | DOI:10.3390/metabo15030179

Metabolites. 2025 Mar 5;15(3):177. doi: 10.3390/metabo15030177.ABSTRACTBackground/Objectives:Euphorbia neriifolia is a succulent plant from the therapeutically rich family of Euphorbia comprising 2000 species globally. E. neriifolia is used in Indigenous Guyanese asthma therapy. Methods: To investigate E. neriifolia's therapeutic potential, traditionally heated leaf, simple leaf, and latex extracts were evaluated for phytohormones and therapeutic compounds. Full scan, data-dependent acquisition, and parallel reaction monitoring modes via liquid chromatography Orbitrap mass spectrometry were used for screening. Results: Pathway analysis of putative features from all extracts revealed a bias towards the phenylpropanoid, terpenoid, and flavonoid biosynthetic pathways. A total of 850 compounds were annotated using various bioinformatics tools, ranging from confidence levels 1 to 3. Lipids and lipid-like molecules (34.35%), benzenoids (10.24%), organic acids and derivatives (12%), organoheterocyclic compounds (12%), and phenylpropanoids and polyketides (10.35%) dominated the contribution of compounds among the 13 superclasses. Semi-targeted screening revealed 14 out of 16 literature-relevant therapeutic metabolites detected, with greater upregulation in traditional heated extracts. Targeted screening of 39 phytohormones resulted in 25 being detected and quantified. Simple leaf extract displayed 4.4 and 45 times greater phytohormone levels than traditional heated leaf and latex extracts, respectively. Simple leaf extracts had the greatest nucleotide and riboside cytokinin and acidic phytohormone levels. In contrast, traditional heated extracts exhibited the highest free base and glucoside cytokinin levels and uniquely contained methylthiolated and aromatic cytokinins while lacking acidic phytohormones. Latex samples had trace gibberellic acid levels, the lowest free base, riboside, and nucleotide levels, with absences of aromatic, glucoside, or methylthiolated cytokinin forms. Conclusions: In addition to metabolites with possible therapeutic value for asthma treatment, we present the first look at cytokinin phytohormones in the species and Euphorbia genus alongside metabolite screening to present a comprehensive assessment of heated leaf extract used in Indigenous Guyanese asthma therapy.PMID:40137143 | DOI:10.3390/metabo15030177

Metabolites. 2025 Mar 4;15(3):175. doi: 10.3390/metabo15030175.ABSTRACTBACKGROUND/OBJECTIVES: Epilepsy is a common chronic and recurrent neurological disorder that poses a threat to human health, and Acorus tatarinowii Schott (ATS), a traditional Chinese medicine, is used to treat it. This study aimed to determine its effects on plasma metabolites. Moreover, the possible mechanism of its intervention in epilepsy was preliminarily explored, combined with network pharmacology.METHODS: An epileptic model of rats was established using pentylenetetrazol. The potential targets and pathways of ATS were predicted by network pharmacology. Ultra Performance Liquid Chromatography-Quadrupole-Time of Flight Mass Spectrometrynce Liquid Chromatography-Quadrupole-Time of Flight Mass Spectrometryance Liquid Chromatography-Quadrupole-Time of Flight Mass Spectrometry and statistical analyses were used to profile plasma metabolites and identify ATS's effects on epilepsy.RESULTS: Kyoto Encyclopedia of Genes and Genomes enrichment analysis revealed that ATS was involved in regulating multiple signaling pathways, mainly including the neuroactive ligand-receptor interaction and GABAerGamma-aminobutyrate transaminaseAminobutyrate Transaminaseapse signaling pathway. ATS treatment restored 19 metabolites in epiGamma-aminobutyrate transaminaseminobutyrate Transaminase rats, affecting lysine, histidine, and purine metabolism. GABA-T was found as a new key target for treating epilepsy with ATS. The IC50 of ATS for inhibiting GABA-T activity was 57.9 μg/mL. Through metabolomic analysis, we detected changes in the levels of certain metabolites related to the GABAergic system. These metabolite changes can be correlated with the targets and pathways predicted by network pharmacology. One of the limitations of this study is that the correlation analysis between altered metabolites and seizure severity remains unfinished, which restricts a more in-depth exploration of the underlying biological mechanisms. In the future, our research will focus on conducting a more in-depth exploration of the correlation analysis between altered metabolites and seizure severity.CONCLUSIONS: These results improved our understanding of epilepsy and ATS treatment, potentially leading to better therapies. The identification of key metabolites and their associated pathways in this study offers potential novel therapeutic targets for epilepsy. By modulating these metabolites, future therapies could be designed to better manage the disorder. Moreover, the insights from network pharmacology can guide the development of more effective antiepileptic drugs, paving the way for improved clinical outcomes for patients.PMID:40137140 | DOI:10.3390/metabo15030175

Metabolites. 2025 Mar 3;15(3):174. doi: 10.3390/metabo15030174.ABSTRACTBackground/Objectives: Metabolomics has recently emerged as a key tool in the biological sciences, offering insights into metabolic pathways and processes. Over the last decade, network-based machine learning approaches have gained significant popularity and application across various fields. While several studies have utilized metabolomics profiles for sample classification, many network-based machine learning approaches remain unexplored for metabolomic-based classification tasks. This study aims to compare the performance of various network-based machine learning approaches, including recently developed methods, in metabolomics-based classification. Methods: A standard data preprocessing procedure was applied to 17 metabolomic datasets, and Bayesian neural network (BNN), convolutional neural network (CNN), feedforward neural network (FNN), Kolmogorov-Arnold network (KAN), and spiking neural network (SNN) were evaluated on each dataset. The datasets varied widely in size, mass spectrometry method, and response variable. Results: With respect to AUC on test data, BNN, CNN, FNN, KAN, and SNN were the top-performing models in 4, 1, 5, 3, and 4 of the 17 datasets, respectively. Regarding F1-score, the top-performing models were BNN (3 datasets), CNN (3 datasets), FNN (4 datasets), KAN (4 datasets), and SNN (3 datasets). For accuracy, BNN, CNN, FNN, KAN, and SNN performed best in 4, 1, 4, 4, and 4 datasets, respectively. Conclusions: No network-based modeling approach consistently outperformed others across the metrics of AUC, F1-score, or accuracy. Our results indicate that while no single network-based modeling approach is superior for metabolomics-based classification tasks, BNN, KAN, and SNN may be underappreciated and underutilized relative to the more commonly used CNN and FNN.PMID:40137139 | DOI:10.3390/metabo15030174

Metabolites. 2025 Mar 3;15(3):173. doi: 10.3390/metabo15030173.ABSTRACTBackground: Osteoporosis is frequently observed in patients with chronic pancreatitis, and both conditions are closely associated with systemic metabolic disorders. However, the underlying mechanisms linking chronic pancreatitis and osteoporosis remain unclear. Methods: In this study, we utilized high-performance liquid chromatography-mass spectrometry (HPLC-MS) to conduct metabolomics and lipidomics analyses on pancreatic, serum, and other tissues from a mouse model of chronic pancreatitis-induced osteoporosis (CP-OP), with the aim to elucidate the metabolism-related pathogenic mechanisms of CP-OP. Results: We identified over 405 metabolites and 445 lipids, and our findings revealed that several metabolites involving the tricarboxylic acid (TCA) cycle, as well as triacylglycerols and diacylglycerols with higher saturation, were significantly increased in the CP-OP model. In contrast, triglycerides with higher unsaturation were decreased. Differential pathways were enriched in n-3 long-chain polyunsaturated fatty acid metabolism in both pancreatic and bone tissues, and these pathways exhibited positive correlations with bone-related parameters. Furthermore, the modulation of these polyunsaturated fatty acids by Qingyi granules demonstrated significant therapeutic effects on CP-OP, as validated in mouse models. Conclusions: Through the metabolomics approach, we uncovered that disorders in polyunsaturated fatty acids play a critical role in the pathogenesis of CP-OP. This study not only enhances our understanding of the pathogenesis of CP-OP but also highlights the therapeutic potential of targeting polyunsaturated fatty acids as a future intervention strategy for osteoporosis treatment.PMID:40137138 | DOI:10.3390/metabo15030173

Metabolites. 2025 Mar 3;15(3):172. doi: 10.3390/metabo15030172.ABSTRACTBACKGROUND: Cuscuta australis R. Br. is a parasitic herbaceous plant that obtains nutrients by forming specialized structures called haustoria to invade host plants.METHODS: In this study, we elucidated the differences in the gene expression regulation and metabolic characteristics between Cuscuta australis and Glycine max (Glycine max (L.) Merr. Var Williams) through comprehensive transcriptomic and metabolomic analyses.RESULTS: The results demonstrated significant differences in the gene expression and metabolic features between the haustorium and the distal stem segments. The differentially expressed genes absorbed by Cuscuta australis from the soybean host influence amino acid metabolism, and the expression of the S-adenosylmethionine decarboxylase gene may affect the production of 5'-methylthioadenosine. A high expression of the chalcone synthase enzyme could lead to an increased daidzein content. Many Glycine max genes were also integrated into Cuscuta australis within the haustorium.CONCLUSIONS: This study systematically analyzed, for the first time, the significant differences in gene expression and metabolic characteristics between the haustoria and distal stem segments of Cuscuta. It also explored the nutrient absorption mechanisms of the host plant. Additionally, the research discovered that Cuscuta can absorb a substantial amount of host genes and adapt to its parasitic lifestyle through differential gene expression and metabolic changes. These findings provide important insights into the parasitic mechanisms of Cuscuta australis and lay the foundation for the development of effective control strategies.PMID:40137137 | DOI:10.3390/metabo15030172

Metabolites. 2025 Mar 3;15(3):171. doi: 10.3390/metabo15030171.ABSTRACTPlant metabolomics is pivotal in understanding plant defense mechanisms against environmental stresses [...].PMID:40137136 | DOI:10.3390/metabo15030171

Metabolites. 2025 Mar 2;15(3):170. doi: 10.3390/metabo15030170.ABSTRACTBackground: Significant sex differences exist in atrial fibrillation (AF). Better understanding of its underlying mechanism would help AF management. This study aimed to investigate the contribution of circulating metabolites to sex differences in AF and the association between them. Methods: A total of 108 patients with AF were enrolled. Untargeted metabolomics were performed in plasma samples of male and female patients. Correlation analysis with clinical characteristics and Mendelian randomization were used to identify sex-specific metabolites associated with AF, which was further validated in additional patients. Transcriptomics data of the left atrium were used to investigate the molecular alteration of the left atrium responding to identified sex-specific circulating metabolites. The effect of selected sex-specific metabolites on cardiomyocytes was further investigated. Results: A total of 60 annotated metabolites were found with different levels between male and female patients. Among these sex-specific metabolites, three metabolites, 7-Methylguanosine, succinic acid, and N-Undecylbenzenesulfonic acid, were positively related to the left atrial remodeling. Additionally, succinic acid was significantly associated with increased risk of AF (OR = 1.26; 95% CI: 1.13 to 1.40; p < 0.001). And, SUCLA2, the gene of succinic acid metabolism, was significantly increased in the left atrium of male patients (fold change = 1.53; p = 0.008). Treatment with succinic acid led to cardiomyocyte hypertrophy and mitochondrial dysfunction. Conclusions: This study highlights sex differences in circulating metabolites in patients with AF and identifies the associations between sex-specific metabolites and AF. succinic acid, which is much higher in male patients, contributes to the process of AF.PMID:40137135 | DOI:10.3390/metabo15030170

Metabolites. 2025 Mar 1;15(3):161. doi: 10.3390/metabo15030161.ABSTRACTBackground/Objectives: Pathway annotations of non-macromolecular (relatively small) biomolecules facilitate biological and biomedical interpretation of metabolomics datasets. However, low pathway annotation levels of detected biomolecules hinder this type of interpretation. Thus, predicting the pathway involvement of detected but unannotated biomolecules has a high potential to improve metabolomics data analysis and omics integration. Past publications have only made use of the Kyoto Encyclopedia of Genes and Genomes-derived datasets to develop machine learning models to predict pathway involvement. However, to our knowledge, the Reactome knowledgebase has not been utilized to develop these types of predictive models. Methods: We created a dataset ready for machine learning using chemical representations of all pathway-annotated compounds available from the Reactome knowledgebase. Next, we trained and evaluated a multilayer perceptron binary classifier using combined metabolite-pathway paired feature vectors engineered from this new dataset. Results: While models trained on a prior corresponding KEGG dataset with 502 pathways scored a mean Matthew's correlation coefficient (MCC) of 0.847 and a 0.0098 standard deviation, the models trained on the Reactome dataset with 3985 pathways demonstrated improved performance with a mean MCC of 0.916, but with a higher standard deviation of 0.0149. Conclusions: These results indicate that the pathways in Reactome can also be effectively predicted, greatly increasing the number of human-defined pathways available for prediction.PMID:40137126 | DOI:10.3390/metabo15030161

Metabolites. 2025 Feb 26;15(3):157. doi: 10.3390/metabo15030157.ABSTRACTCapirona macrophylla is a Rubiaceae known as "mulateiro". Ethnobotanical extracts have been used for skin treatment and in the management of leishmaniasis and malaria.OBJECTIVES: The metabolites in aqueous extracts from wood bark, leaves, and stems were identified, and their in silico docking and in vitro cellular efficacy against Leishmania amazonensis and Plasmodium falciparum were evaluated.METHODS: The extracts were analyzed by UHPLC/HRMSn using untargeted metabolomics approach with MSDial, MSFinder, and GNPS software for metabolite identification and spectra clustering. The most abundant metabolites underwent molecular docking using AutoDock via PyRx, targeting the dihydroorotate dehydrogenase from Leishmania and P. falciparum, and evaluated through molecular dynamics simulations using Gromacs. In vitro biological assays were conducted on 60 HPLC-fractions against these parasites.RESULTS: Metabolomics analysis identified 5100 metabolites in ESI+ and 2839 in ESI- spectra among the "mulateiro" samples. GNPS clustering highlighted large clusters of quercetin and chlorogenic acid groups. The most abundant metabolites were isofraxidin, scopoletin, 5(S)-5-carboxystrictosidine, loliolide, quercetin, quinic acid, caffeoylquinic acid (and isomers), chlorogenic acid, neochlorogenic acid, tryptophan, N-acetyltryptophan, epicatechin, procyanidin, and kaempferol-3-O-robinoside-7-O-rhamnoside. Molecular docking pointed to 3,4-dicaffeoylquinic acid and kaempferol as promising inhibitors. The in vitro assays yielded four active HPLC-fractions against L. amazonensis with IC50 values ranging from 175.2 μg/mL to 194.8 μg/mL, and fraction G29 showed an IC50 of 119.8 μg/mL against P. falciparum.CONCLUSIONS: The ethnobotanical use of "mulateiro" wood bark tea as an antimalarial and antileishmanial agent was confirmed through in vitro assays. We speculate that these activities are attributed to linoleic acids and quinic acids.PMID:40137122 | DOI:10.3390/metabo15030157

Metabolites. 2025 Feb 24;15(3):154. doi: 10.3390/metabo15030154.ABSTRACTBackground: Understanding the metabolic adaptations of wild bighorn sheep (Ovis c. canadensis) to nutritional stress is crucial for their conservation. Methods: This study employed 1H nuclear magnetic resonance (NMR) metabolomics to investigate the biochemical responses of these animals to varying sub-maintenance nutritional states. Serum samples from 388 wild bighorn sheep collected between 2014 and 2017 from December (early sub-maintenance) through March (severe sub-maintenance) across Wyoming and Montana were analyzed. Multivariate statistics and machine learning analyses were employed to identify characteristic metabolic patterns and metabolic interactions between early and severe sub-maintenance nutritional states. Results: Significant differences were observed in the levels of 15 of the 49 quantified metabolites, including formate, thymine, glucose, choline, and others, pointing to disruptions in one-carbon, amino acid, and central carbon metabolic pathways. These metabolites may serve as indicators of critical physiological processes such as nutritional intake, immune function, energy metabolism, and protein catabolism, which are essential for understanding how wild bighorn sheep adapt to nutritional stress. Conclusions: This study has generated valuable insights into molecular networks underlying the metabolic resilience of wild bighorn sheep, highlighting the potential for using specific biochemical markers to evaluate nutritional and energetic states in free-ranging ungulates. These insights may help wildlife managers and ecologists compare populations across different times in seasonal cycles, providing information to assess the adequacy of seasonal ranges and support conservation efforts. This research strengthens our understanding of metabolic adaptations to environmental stressors in wild ruminants, offering a foundation for improving management practices to maintain healthy bighorn sheep populations.PMID:40137119 | DOI:10.3390/metabo15030154

Metabolites. 2025 Feb 24;15(3):153. doi: 10.3390/metabo15030153.ABSTRACTBACKGROUND: Aromatase inhibitors-related musculoskeletal syndrome (AIMSS) is a common side effect experienced by early breast cancer patients undergoing endocrine therapy. This condition can result in medication discontinuation and a diminished quality of life. The objective of this study was to characterize AIMSS, investigate its pathogenesis, and identify potential biomarkers at both the protein and metabolic levels.METHODS: We collected peripheral blood samples from 60 women diagnosed with breast cancer undergoing aromatase inhibitor therapy, of whom 30 had AIMSS and 30 did not. The samples were analyzed using four-dimensional data-independent acquisition (DIA)-based proteomics and untargeted metabolomics, employing liquid chromatography-mass spectrometry (LC-MS) on the latest platform.RESULTS: The mean age of participants was 49.2 (11.3) years in the AIMSS group and 50.1 (11.5) years in the non-AIMSS group. There were no statistically significant differences between the two groups in terms of age, BMI, education level, clinical stage, and treatment. In total, we identified 3473 proteins and 1247 metabolites in the samples. The chemokine signaling pathway (p = 0.015), cytokine-cytokine receptor interaction (p = 0.015), complement and coagulation cascades (p = 0.004), neuroactive ligand-receptor interaction (p = 0.004), and the estrogen signaling pathway (p = 0.004) were significant enriched in differentially expressed proteins (DEPs). GnRH secretion (p < 0.001), sphingolipid signaling pathways (p < 0.001), endocrine resistance (p < 0.001), the estrogen signaling pathway (p = 0.001), endocrine and other factor-regulated calcium reabsorption (p = 0.001), dopaminergic synapse (p = 0.003), regulation of lipolysis in adipocytes (p = 0.004), biosynthesis of cofactors (p = 0.004), thyroid hormone synthesis (p = 0.008), aldosterone synthesis and secretion (p = 0.001), taurine and hypotaurine metabolism (p = 0.011), ovarian steroidogenesis (p = 0.011), and the cAMP signaling pathway (p = 0.011) were significantly enriched in differentially expressed metabolites (DEMs). Complement C3 (p = 0.004), platelet factor 4 (p = 0.015), KRT10 (p = 0.004), KRT14 (p = 0.004), beta-estradiol (p = 0.019), testosterone (p = 0.023), sphingosine (p < 0.001), and 1-stearoyl-2-arachidonoyl-sn-glycerol (p = 0.039) could be the monitoring and therapeutic targets for AIMSS.CONCLUSIONS: This study offered new insights into the mechanisms underlying musculoskeletal symptoms associated with aromatase inhibitors. It also highlighted potential biomarkers for predicting and addressing these symptoms in breast cancer patients, paving the way for improved intervention strategies.PMID:40137118 | DOI:10.3390/metabo15030153

Metabolites. 2025 Feb 23;15(3):152. doi: 10.3390/metabo15030152.ABSTRACTBackground: Wild boletes are famous for their exceptional flavor and nutritional value. Due to their susceptibility to decay and spoilage, dry storage is a common method for processing and preservation. However, few studies have reported on the alterations of metabolites of boletes resulting from different drying methods. This paper aims to investigate the metabolic changes in two species of boletes, Butyriboletus roseoflavus and Lanmaoa asiatica, subjected to three drying methods: hot-air drying, microwave drying, and freeze drying. Method and Result: Nuclear magnetic resonance (NMR) metabolomics was utilized for multivariate data analysis. In total, 27 metabolites were identified from the two species of boletes, including amino acids such as glutamate and leucine, sugars like glucose and sucrose, and alkaloids like choline. Among these, 17 metabolites were classified as differential metabolites, comprising 12 amino acids, 4 sugars, and 1 alkaloid. Differential metabolites were quantified by quantitative NMR (qNMR), and these metabolites were subsequently analyzed using the Kyoto Encyclopedia of Genes and Genomes (KEGG) database for pathway enrichment analysis. KEGG pathway analysis revealed that the different drying methods resulted in significantly distinct metabolic pathways for these differential metabolites, resulting in the enrichment of amino acid metabolism and starch and sucrose metabolism pathways. Conclusions: This metabolomics study elucidates the differences in metabolite composition and abundance between the two species of boletes, providing a theoretical foundation for selecting appropriate drying methods for their preservation.PMID:40137117 | DOI:10.3390/metabo15030152

Metabolites. 2025 Feb 21;15(3):146. doi: 10.3390/metabo15030146.ABSTRACTGut microbial metabolism of dietary flavonoids leads to a diverse array of bioactive products that are closely associated with human health. Combining enzyme promiscuity prediction, metabolomics, and in vitro model systems, we identified a chalcone-synthase-like bacterial polyketide synthase that can initiate the metabolism of naringenin by catalyzing the C-ring cleavage. This was validated using a mutant strain of the model organism Bacillus subtilis (ATCC 23857). Our prediction-validation methodology could be used to systematically characterize the products of gut bacterial flavonoid metabolism and identify the responsible enzymes and species. In vitro experiments with Caco-2 cells revealed that naringenin and its bacterial metabolites differentially engage the aryl hydrocarbon receptor (AhR) and orphan nuclear receptor 4A (NR4A). These results suggest that metabolism by gut bacterial species could directly impact the profile of bioactive flavonoids and influence inflammatory responses in the intestine. These results are significant for understanding gut-microbiota-dependent physiological effects of dietary flavonoids.PMID:40137111 | DOI:10.3390/metabo15030146

Metabolites. 2025 Feb 21;15(3):145. doi: 10.3390/metabo15030145.ABSTRACTBackground/Objectives: Effectiveness of modified atmosphere (MA) packaging for the preservation of the freshness of vegetable soybeans was confirmed by using metabolomics combined with convolutional neural networks (CNNs). Methods: Stored under a low O2, high CO2 environment, the vegetable soybeans' freshness was tracked through changes in hue angle on the surface of the crops and metabolite levels compared to those stored under normoxia. Results: MA packaging slowed respiration and reduced pectin decomposition, succinic acid oxidation, and fatty acid consumption, all linked to freshness maintenance. Using 62 key metabolite concentrations as inputs, CNNs classified vegetable soybean freshness into seven categories with 92.9% accuracy, outperforming traditional linear discriminant analysis by 14.3%. Conclusions: These findings demonstrate MA packaging's effectiveness in extending freshness of vegetable soybeans by monitoring specific metabolic changes. This will contribute to the advancement of research aimed at elucidating the relationship between freshness and metabolism in horticultural crops.PMID:40137110 | DOI:10.3390/metabo15030145