Metabolites

Article

20 pages, 15032 KiB

Open AccessEditor’s ChoiceArticle

Multi-Omics Profiling Reveals Glycerolipid Metabolism-Associated Molecular Subtypes and Identifies ALDH2 as a Prognostic Biomarker in Pancreatic Cancer

by Jifeng Liu, Shurong Ma, Dawei Deng, Yao Yang, Junchen Li, Yunshu Zhang, Peiyuan Yin and Dong Shang

Metabolites 2025, 15(3), 207; https://doi.org/10.3390/metabo15030207 - 18 Mar 2025

Cited by 1 | Viewed by 937

Abstract

Background: The reprogramming of lipid metabolism, especially glycerolipid metabolism (GLM), plays a key role in cancer progression and response to therapy. However, the role and molecular characterization of GLM in pancreatic cancer (PC) remain unclear. Methods: A pan-cancer analysis of glycerolipid [...] Read more.

Background: The reprogramming of lipid metabolism, especially glycerolipid metabolism (GLM), plays a key role in cancer progression and response to therapy. However, the role and molecular characterization of GLM in pancreatic cancer (PC) remain unclear. Methods: A pan-cancer analysis of glycerolipid metabolism-related genes (GMRGs) was first conducted to assess copy-number variants, single-nucleotide variations, methylation, and mRNA expression. Subsequently, GLM in PC was characterized using lipidomics, single-cell RNA sequencing (scRNA-seq), and spatial transcriptomic analysis. A cluster analysis based on bulk RNA sequencing data from 930 PC samples identified GLM-associated subtypes, which were then analyzed for differences in prognosis, biological function, immune microenvironment, and drug sensitivity. To prioritize prognostically relevant GMRGs in PC, we employed a random forest (RF) algorithm to rank their importance across 930 PC samples. Finally, the key biomarker of PC was validated using PCR and immunohistochemistry. Results: Pan-cancer analysis identified molecular features of GMRGs in cancers, while scRNA-seq, spatial transcriptomics, and lipidomics highlighted GLM heterogeneity in PC. Two GLM-associated subtypes with significant prognostic, biofunctional, immune microenvironmental, and drug sensitivity differences were identified in 930 PC samples. Finally, ALDH2 was identified as a novel prognostic biomarker in PC and validated in a large number of datasets and clinical samples. Conclusions: This study highlights the crucial role of GLM in PC and defines a new PC subtype and prognostic biomarker. These findings establish a novel avenue for studying prognostic prediction and precision medicine in PC patients. Full article

(This article belongs to the Special Issue New Analytical Techniques and Applications of Metabolomics and Lipidomics)

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21 pages, 5553 KiB

Open AccessEditor’s ChoiceArticle

Identification of Bioactive Metabolites of Capirona macrophylla by Metabolomic Analysis, Molecular Docking, and In Vitro Antiparasitic Assays

by Joseph Evaristo, Elise de Laia, Bruna Tavares, Esdras Mendonça, Larissa Grisostenes, Caroline Rodrigues, Welington do Nascimento, Carolina Garcia, Sheila Guterres, Fábio Nogueira, Fernando Zanchi and Geisa Evaristo

Metabolites 2025, 15(3), 157; https://doi.org/10.3390/metabo15030157 - 26 Feb 2025

Cited by 1 | Viewed by 1148

Abstract

Capirona 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 [...] Read more.

Capirona 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. Full article

(This article belongs to the Special Issue Advanced Metabolic Profiling via Gas Chromatography–Mass Spectrometry and Liquid Chromatography–Mass Spectrometry)

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22 pages, 5013 KiB

Open AccessEditor’s ChoiceArticle

Polar Metabolite Profiles Distinguish Between Early and Severe Sub-Maintenance Nutritional States of Wild Bighorn Sheep

by Galen O’Shea-Stone, Brian Tripet, Jennifer Thomson, Robert Garrott and Valérie Copié

Metabolites 2025, 15(3), 154; https://doi.org/10.3390/metabo15030154 - 24 Feb 2025

Viewed by 990

Abstract

Background: 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 [...] Read more.

Background: 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. Full article

(This article belongs to the Section Animal Metabolism)

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17 pages, 7353 KiB

Open AccessEditor’s ChoiceArticle

Multifluid Metabolomics Identifies Novel Biomarkers for Irritable Bowel Syndrome

by Daniel Kirk, Panayiotis Louca, Ilias Attaye, Xinyuan Zhang, Kari E. Wong, Gregory A. Michelotti, Mario Falchi, Ana M. Valdes, Frances M. K. Williams and Cristina Menni

Metabolites 2025, 15(2), 121; https://doi.org/10.3390/metabo15020121 - 12 Feb 2025

Cited by 2 | Viewed by 1612

Abstract

Background/Objectives: Irritable bowel syndrome (IBS) is a complex disorder affecting 10% of the global population, but the underlying mechanisms remain poorly understood. By integrating multifluid metabolomics, we aimed to identify metabolite markers of IBS in a large population-based cohort. Methods: We [...] Read more.

Background/Objectives: Irritable bowel syndrome (IBS) is a complex disorder affecting 10% of the global population, but the underlying mechanisms remain poorly understood. By integrating multifluid metabolomics, we aimed to identify metabolite markers of IBS in a large population-based cohort. Methods: We included individuals from TwinsUK with and without IBS, ascertained using the Rome III criteria, and analysed serum (232 cases, 1707 controls), urine (185 cases, 1341 controls), and stool (186 cases, 1284 controls) metabolites (Metabolon Inc.). Results: After adjusting for covariates, and multiple testing, 44 unique metabolites (25 novel) were associated with IBS, including lipids, amino acids, and xenobiotics. Androsterone sulphate, a sulfated steroid hormone precursor, was associated with lower odds of IBS in both urine (0.69 [95% confidence interval = 0.56–0.85], p = 2.34 × 10⁻⁴) and serum (0.75 [0.63–0.90], p = 1.54 × 10⁻³. Moreover, suberate (C8-DC) was associated with higher odds of IBS in serum (1.36 [1.15–1.61]; p = 1.84 × 10⁻⁴) and lower odds of IBS in stool (0.76 [0.63–0.91]; p = 2.30 × 10⁻³). On the contrary, 32 metabolites appeared to be fluid-specific, including indole, 13-HODE + 9-HODE, pterin, bilirubin (E,Z or Z,Z), and urolithin. The remaining 10 metabolites were associated with IBS in one fluid with suggestive evidence (p < 0.05) in another fluid. Finally, we identified androgenic signalling, dicarboxylates, haemoglobin, and porphyrin metabolism to be significantly over-represented in individuals with IBS compared to controls. Conclusions: Our results highlight the utility of a multi-fluid approach in IBS research, revealing distinct metabolic signatures across biofluids. Full article

(This article belongs to the Special Issue Advances in Metabolomics and Multi-Omics Integration)

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31 pages, 5603 KiB

Open AccessEditor’s ChoiceArticle

Oregano Young Plants Cultured at Low Temperature Reveal an Enhanced Healing Effect of Their Extracts: Anatomical, Physiological and Cytotoxicity Approach

by Aikaterina L. Stefi, Maria Chalkiadaki, Katerina Dimitriou, Konstantina Mitsigiorgi, Dimitrios Gkikas, Danae Papageorgiou, Georgia C. Ntroumpogianni, Dido Vassilacopoulou, Maria Halabalaki and Nikolaos S. Christodoulakis

Metabolites 2025, 15(2), 103; https://doi.org/10.3390/metabo15020103 - 7 Feb 2025

Viewed by 1481

Abstract

Background: The germination and early development of Origanum vulgare L. subsp. hirtum (Link) Ietswaart (Greek oregano) were studied to assess the plant’s response to different temperatures. Methods: After germination, seedlings were cultivated in control (25 °C) and cold (15 °C) chambers with standard [...] Read more.

Background: The germination and early development of Origanum vulgare L. subsp. hirtum (Link) Ietswaart (Greek oregano) were studied to assess the plant’s response to different temperatures. Methods: After germination, seedlings were cultivated in control (25 °C) and cold (15 °C) chambers with standard growth parameters. Comparative analyses of plant morphology and leaf anatomy were conducted to identify structural modifications induced by different temperatures. Physiological evaluations, including photosynthetic pigment measurements, phenolic content, and antioxidant activity, were performed to assess differences between the plants grown under the two temperature conditions. Methanolic extracts from the leaves were tested for cytotoxicity on MCF-7 breast adenocarcinoma cells and SH-SY5Y neuroblastoma cells, as well as on nine microbial strains. Additionally, biomarkers from the leaves affected by temperature changes were determined using LC-HRMS/MS analysis. Results: Comparative analyses revealed distinct structural and physiological modifications under cold conditions. The methanolic extracts from plants grown at 15 °C exhibited notably higher cytotoxic activity in both cell lines but demonstrated no activity against microbial strains. The results highlight the influence of low temperature on enhancing the bioactive properties of Greek oregano. Conclusions: The findings provide valuable insights into the environmental adaptability of oregano, demonstrating the impact of low temperature on its bioactive properties. The therapeutic potential of methanolic extracts cultured at 15 °C is imprinted in cytotoxicity in SH-SY5Y and MCF-7 cells and the absence of any activity against microbial strains. Full article

(This article belongs to the Special Issue Advances in Secondary Metabolites: Phytochemical Analysis and Bioactivity Assays)

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22 pages, 1356 KiB

Open AccessEditor’s ChoiceArticle

A New, Validated GC-PICI-MS Method for the Quantification of 32 Lipid Fatty Acids via Base-Catalyzed Transmethylation and the Isotope-Coded Derivatization of Internal Standards

by Petr Vodrážka, Lucie Řimnáčová, Petra Berková, Jan Vojtíšek, Miroslav Verner, Martin Moos and Petr Šimek

Metabolites 2025, 15(2), 104; https://doi.org/10.3390/metabo15020104 - 7 Feb 2025

Viewed by 1058

Abstract

Background: Fatty acids (FAs) represent a ubiquitous class of nonpolar alkyl carboxylate metabolites with diverse biological functions. Nutrition, metabolism, and endogenous and exogenous stress influence the overall FA metabolic status and transport via the bloodstream. FAs esterified in lipids are of particular interest, [...] Read more.

Background: Fatty acids (FAs) represent a ubiquitous class of nonpolar alkyl carboxylate metabolites with diverse biological functions. Nutrition, metabolism, and endogenous and exogenous stress influence the overall FA metabolic status and transport via the bloodstream. FAs esterified in lipids are of particular interest, as they represent promising biomarkers of pathological diseases and nutritional status. Methods: Here, we report a validated gas chromatographic-mass spectrometric (GC-MS) method for the quantitative analysis of 32 FAs exclusively bound in esterified lipids. The developed sample preparation protocol comprises three steps using only 5 µL of human serum for Folch extraction, sodium methoxide-catalyzed transesterification in tert-butyl methyl ether, and re-extraction in isooctane prior to a quantitative GC-MS analysis with positive ion chemical ionization (PICI) and selected ion monitoring (SIM). Results: The base-catalyzed transmethylation step was studied for 14 lipid classes and was found to be efficient under mild conditions for all major esterified lipids but not for free FAs, lipid amides, or sphingolipids. To minimize matrix effects and instrument bias, internal fatty acid trideuteromethyl esters (D3-FAME) standards were prepared through isotope-coded derivatization with D3-labeled methylchloroformate/methanol medium mixed with each transmethylated serum extract for the assay. The method was validated according to FDA guidelines and evaluated by analyzing NIST SRM 2378 Serum 1 and sera from three healthy donors. Conclusions: The measured quantitative FA values are consistent with the reference data of SRM 2378, and they demonstrate the application potential of the described method for general FA analysis in esterified lipids as a novel complementary tool for lipidomics, as well as for the analysis of membrane FAs in dry blood spots and red blood cells. Full article

(This article belongs to the Section Lipid Metabolism)

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16 pages, 6875 KiB

Open AccessEditor’s ChoiceArticle

Metabolomic-Based Assessment of Earthworm (Eisenia fetida) Exposure to Different Petroleum Fractions in Soils

by Meiyu Liu, Mutian Wang, Xiaowen Fu, Fanyong Song, Fangyuan Zhou, Tianyuan Li and Jianing Wang

Metabolites 2025, 15(2), 97; https://doi.org/10.3390/metabo15020097 - 5 Feb 2025

Viewed by 1246

Abstract

Background/Objectives: Petroleum contamination in soil exerts toxic effects on earthworms (Eisenia fetida) through non-polar narcotic mechanisms. However, the specific toxicities of individual petroleum components remain insufficiently understood. Methods: This study investigates the effects of four petroleum components—saturated hydrocarbons, aromatic hydrocarbons, resins, [...] Read more.

Background/Objectives: Petroleum contamination in soil exerts toxic effects on earthworms (Eisenia fetida) through non-polar narcotic mechanisms. However, the specific toxicities of individual petroleum components remain insufficiently understood. Methods: This study investigates the effects of four petroleum components—saturated hydrocarbons, aromatic hydrocarbons, resins, and asphaltenes—on earthworms in artificially contaminated soil, utilizing a combination of biochemical biomarker analysis and metabolomics to uncover the underlying molecular mechanisms. Results: The results revealed that aromatic hydrocarbons are the most toxic fraction, with EC50 concentrations significantly lower than those of other petroleum fractions. All tested fractions triggered notable metabolic disturbances and immune responses in earthworms after 7 days of exposure, as evidenced by significant changes in metabolite abundance within critical pathways such as arginine synthesis, a-linolenic acid metabolism, and the pentose phosphate pathway. According to the KEGG pathway analysis, saturated hydrocarbon fractions induced marked changes in glycerophospholipid metabolism, and arginine and proline metabolism pathways, contributing to the stabilization of the protein structure and membrane integrity. Aromatic hydrocarbon fractions disrupted the arachidonic acid metabolic pathway, leading to increased myotube production and enhanced immune defense mechanisms. The TCA cycle and riboflavin metabolic pathway were significantly altered during exposure to the colloidal fraction, affecting energy production and cellular respiration. The asphaltene fraction significantly impacted glycolysis, accelerating energy cycling to meet stress-induced increases in energy demands. Conclusions: Aromatic hydrocarbons accounted for the highest level of toxicity among the four components in petroleum-contaminated soils. However, the contributions of other fractions to overall toxicity should not be ignored, as each fraction uniquely affects key metabolic pathways and biological functions. These findings emphasize the importance of monitoring metabolic perturbations caused by petroleum components in non-target organisms such as earthworms. They also reveal the specificity of the toxic metabolic effects of different petroleum components on earthworms. Full article

(This article belongs to the Section Environmental Metabolomics)

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18 pages, 2363 KiB

Open AccessEditor’s ChoiceArticle

Metabolites and Free Fatty Acids in Japanese Black Beef During Wet Aging

by Shuji Ueda, Yuka Yoshida, Yuka Tateoka, Biniam Kebede, Masakazu Shinohara, Hiroki Nakanishi, Itsuko Fukuda and Yasuhito Shirai

Metabolites 2025, 15(2), 94; https://doi.org/10.3390/metabo15020094 - 3 Feb 2025

Cited by 2 | Viewed by 1930

Abstract

Background: Japanese Black beef is known for its high intramuscular fat content, an important factor in its distinctive Wagyu aroma. Wet aging, which involves vacuum-packing meat and storing it at low temperatures, enhances flavor, texture, and tenderness and is essential for maintaining and [...] Read more.

Background: Japanese Black beef is known for its high intramuscular fat content, an important factor in its distinctive Wagyu aroma. Wet aging, which involves vacuum-packing meat and storing it at low temperatures, enhances flavor, texture, and tenderness and is essential for maintaining and improving meat quality. In this study, changes in metabolites and lipid profiles were investigated during the wet aging of Japanese Black and Holstein beef. Methods/Results: Gas chromatography–mass spectrometry identified 113 metabolites in Japanese Black beef and 94 in Holstein beef, with significant increases in metabolites like aspartic acid and maleic acid over the aging period. Regarding lipid composition, total free fatty acids significantly increased with wet aging, with Japanese Black beef showing significantly higher concentrations of oleic and linoleic acids than Holstein beef. Additionally, lipid analysis by liquid chromatography–mass spectrometry revealed a reduction in specific phospholipids, particularly lysophosphatidylcholine (LPC) and lysophosphatidylethanolamine (LPE), with notable decreases in LPC (18:1), LPC (18:2), LPE (18:1), and LPE (18:2). Conclusions: These results suggest that wet aging influences the stability of membrane lipids, facilitating the degradation of phospholipids into free fatty acids, and improving the flavor of Japanese Black beef. Full article

(This article belongs to the Special Issue The Digital Revolution in Livestock Production and Metabolism: Foodomics for a Viable Future and Beyond)

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15 pages, 1801 KiB

Open AccessEditor’s ChoiceArticle

Is N1-Methylnicotinamide a Good Organic Cation Transporter 2 (OCT2) Biomarker?

by Anoud Sameer Ailabouni, Gautam Vijaywargi, Sandhya Subash, Dilip Kumar Singh, Zsuzsanna Gaborik and Bhagwat Prasad

Metabolites 2025, 15(2), 80; https://doi.org/10.3390/metabo15020080 - 29 Jan 2025

Cited by 1 | Viewed by 1338

Abstract

Background/Objectives: The impact of potential precipitant drugs on plasma or urinary exposure of endogenous biomarkers is emerging as an alternative approach to evaluating drug–drug interaction (DDI) liability. N1-Methylnicotinamide (NMN) has been proposed as a potential biomarker for renal organic cation transporter 2 [...] Read more.

Background/Objectives: The impact of potential precipitant drugs on plasma or urinary exposure of endogenous biomarkers is emerging as an alternative approach to evaluating drug–drug interaction (DDI) liability. N1-Methylnicotinamide (NMN) has been proposed as a potential biomarker for renal organic cation transporter 2 (OCT2). NMN is synthesized in the liver from nicotinamide by nicotinamide N-methyltransferase (NNMT) and is subsequently metabolized by aldehyde oxidase (AO). Multiple clinical studies have shown a reduction in NMN plasma concentration following the administration of OCT inhibitors such as cimetidine, trimethoprim, and pyrimethamine, which contrasts with their inhibition of NMN renal clearance by OCT2. We hypothesized that OCT1-mediated NMN release from hepatocytes is inhibited by the administration of OCT inhibitors. Methods: Re-analysis of the reported NMN pharmacokinetics with and without OCT inhibitor exposure was performed. We assessed the effect of cimetidine on NMN uptake in OCT1-HEK293 cells and evaluated the potential confounding effects of cimetidine on enzymes involved in NMN formation and metabolism. Results: A re-analysis of previous NMN pharmacokinetic DDI data suggests that NMN plasma systemic exposure decreased by 17–41% during the first 4 h following different OCT inhibitor administration except dolutegravir. Our findings indicate that NMN uptake was significantly higher (by 2.5-fold) in OCT1-HEK293 cells compared to mock cells, suggesting that NMN is a substrate of OCT1. Additionally, our results revealed that cimetidine does not inhibit NNMT and AO activity. Conclusions: Our findings emphasize the limitations of using NMN as an OCT2 biomarker and reveal potential mechanisms behind the reduction in NMN plasma levels associated with OCT inhibitors. Instead, our data suggest that NMN could be tested further as a potential biomarker for OCT1 activity. Full article

(This article belongs to the Special Issue The Role of Metabolites in Translational and Clinical Pharmacology)

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15 pages, 1672 KiB

Open AccessEditor’s ChoiceArticle

Colostrum-Derived Melatonin Plus PEG Microspheres Modulate the Oxidative Metabolism of Human Colostrum Phagocytes

by Caroline G. Silva, Viviane F. Luz, Victor L. Nunes, Ana B. M. Verzoto, Aron C. de M. Cotrim, Wagner B. dos Santos, Eduardo L. França and Adenilda C. Honorio-França

Metabolites 2025, 15(1), 57; https://doi.org/10.3390/metabo15010057 - 16 Jan 2025

Cited by 3 | Viewed by 917

Abstract

Background/Objectives: Exogenous melatonin adsorbed onto PEG microspheres can modulate the functional activity of phagocytes in colostrum, but no data are available on the activity of melatonin found in colostrum. Therefore, the objective of this study was to extract melatonin from human colostrum, develop [...] Read more.

Background/Objectives: Exogenous melatonin adsorbed onto PEG microspheres can modulate the functional activity of phagocytes in colostrum, but no data are available on the activity of melatonin found in colostrum. Therefore, the objective of this study was to extract melatonin from human colostrum, develop and characterize PEG microspheres with the extracted melatonin adsorbed onto them, and evaluate the effects of this system on the oxidative metabolism of colostrum phagocytes. Methods: Thirty colostrum samples were collected; ten were used for melatonin extraction, while twenty were used to obtain phagocytes. Melatonin was extracted from the colostrum supernatant through affinity chromatography and quantified by ELISA. The polyethylene glycol microspheres produced were analyzed using fluorescence microscopy and flow cytometry. Oxidative metabolism was assessed by measuring the release of the superoxide anion and superoxide enzymes. A control was conducted using commercial melatonin. Results: The fluorescence microscopy and flow cytometry analyses demonstrated that PEG microspheres can adsorb melatonin. There was an increase in superoxide release in phagocytes incubated with colostrum-derived or synthetic melatonin. When exposed to bacteria, colostrum phagocytes treated with colostrum melatonin adsorbed to PEG microspheres exhibited increased superoxide, accompanied by a decrease in the release of superoxide dismutase (SOD) and a lower SOD-to-superoxide ratio. In contrast, synthetic melatonin reduced the release of superoxide and increased the release of the enzyme and the SOD-to-superoxide ratio. Conclusions: These data highlight the importance of melatonin on cellular metabolism and suggest that colostrum-derived melatonin may be a more effective option for controlling oxidative metabolism, particularly during infectious processes. Full article

(This article belongs to the Section Cell Metabolism)

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16 pages, 5126 KiB

Open AccessEditor’s ChoiceArticle

Chemical Diversity of UK-Grown Tea Explored Using Metabolomics and Machine Learning

by Amanda J. Lloyd, Alina Warren-Walker, Jasen Finch, Jo Harper, Kathryn Bennet, Alison Watson, Laura Lyons, Pilar Martinez Martin, Thomas Wilson and Manfred Beckmann

Metabolites 2025, 15(1), 52; https://doi.org/10.3390/metabo15010052 - 15 Jan 2025

Cited by 4 | Viewed by 1260

Abstract

Background/Objectives: Dartmoor Estate Tea plantation in Devon, UK, is renowned for its unique microclimate and varied soil conditions, which contribute to the distinctive flavours and chemical profiles of tea. The chemical diversity of fresh leaf samples from various garden locations was explored within [...] Read more.

Background/Objectives: Dartmoor Estate Tea plantation in Devon, UK, is renowned for its unique microclimate and varied soil conditions, which contribute to the distinctive flavours and chemical profiles of tea. The chemical diversity of fresh leaf samples from various garden locations was explored within the plantation. Methods: Fresh leaf, which differed by location, cultivar, time of day, and variety, was analysed using Flow Infusion Electrospray Ionisation Mass Spectrometry (FIE-MS). Results: Random forest classification revealed no significant differences between Georgian N2 cultivar garden locations. However, a significant degree of variability was observed within four tri-clonal variants (Tocklai Variety) with TV9 exhibiting greater similarity to the Georgian N2 cultivar compared to TV8 and TV11, while TV11 was found to be most like TV1. The intraclass variability in leaf composition was similar between the varieties. We explored the metabolic changes over the day in one variant (Camellia assamica Masters), yielding a model with a significant R² value of 0.617 (p < 0.01, 3000 permutations). Starch and sucrose metabolism was found to be significant where the abundance of these chemical features increased throughout the day and then began to decrease at night. Conclusions: This research highlights the complex interplay of cultivars, geographical location, and temporal factors on the chemical composition of tea. It provides insightful data on the metabolic pathways influencing tea cultivation and production and underscores the importance of these variables in determining the final chemical profile and organoleptic characteristics of tea products. Full article

(This article belongs to the Section Plant Metabolism)

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28 pages, 10002 KiB

Open AccessEditor’s ChoiceArticle

Silymarin as a Therapeutic Agent for Hepatocellular Carcinoma: A Multi-Approach Computational Study

by Ouided Benslama, Sabrina Lekmine, Hamza Moussa, Hichem Tahraoui, Mohammad Shamsul Ola, Jie Zhang and Abdeltif Amrane

Metabolites 2025, 15(1), 53; https://doi.org/10.3390/metabo15010053 - 15 Jan 2025

Cited by 2 | Viewed by 1593

Abstract

Background: Hepatocellular carcinoma (HCC) is a prevalent and lethal form of liver cancer with limited treatment options. Silymarin, a flavonoid complex derived from milk thistle, has shown promise in liver disease treatment due to its antioxidant, anti-inflammatory, and anticancer properties. This study aims [...] Read more.

Background: Hepatocellular carcinoma (HCC) is a prevalent and lethal form of liver cancer with limited treatment options. Silymarin, a flavonoid complex derived from milk thistle, has shown promise in liver disease treatment due to its antioxidant, anti-inflammatory, and anticancer properties. This study aims to explore the therapeutic potential of silymarin in HCC through a comprehensive in silico approach. Methods: This study employed a network pharmacology approach to identify key molecular targets of silymarin in HCC. The Genecards and Metascape databases were used for target identification and functional annotation. Molecular docking analysis was conducted on the primary silymarin components against VEGFA and SRC proteins, which are critical in HCC progression. MD simulations followed to assess the stability and interactions of the docked complexes. Results: Network pharmacology analysis identified several key molecular targets and pathways implicated in HCC. The molecular docking results revealed strong binding affinities of silymarin components to VEGFA and SRC, with Silybin A and Isosilybin B showing the highest affinities. MD simulations confirmed the stability of these interactions, indicating potential inhibitory effects on HCC progression. Conclusions: This study provides a comprehensive in silico evaluation of silymarin’s therapeutic potential in HCC. The findings suggest that silymarin, particularly its components Silybin A and Isosilybin B, may effectively target VEGFA and SRC proteins, offering a promising avenue for HCC treatment. Further experimental validation is warranted to confirm these findings and facilitate the development of silymarin-based therapeutics for HCC. Full article

(This article belongs to the Special Issue Metabolism of Bioactives and Natural Products)

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13 pages, 1625 KiB

Open AccessEditor’s ChoiceArticle

MetaboLabPy—An Open-Source Software Package for Metabolomics NMR Data Processing and Metabolic Tracer Data Analysis

by Christian Ludwig

Metabolites 2025, 15(1), 48; https://doi.org/10.3390/metabo15010048 - 14 Jan 2025

Cited by 1 | Viewed by 1497

Abstract

Introduction: NMR spectroscopy is a powerful technique for studying metabolism, either in metabolomics settings or through tracing with stable isotope-enriched metabolic precursors. MetaboLabPy (version 0.9.66) is a free and open-source software package used to process 1D- and 2D-NMR spectra. The software implements a [...] Read more.

Introduction: NMR spectroscopy is a powerful technique for studying metabolism, either in metabolomics settings or through tracing with stable isotope-enriched metabolic precursors. MetaboLabPy (version 0.9.66) is a free and open-source software package used to process 1D- and 2D-NMR spectra. The software implements a complete workflow for NMR data pre-processing to prepare a series of 1D-NMR spectra for multi-variate statistical data analysis. This includes a choice of algorithms for automated phase correction, segmental alignment, spectral scaling, variance stabilisation, export to various software platforms, and analysis of metabolic tracing data. The software has an integrated help system with tutorials that demonstrate standard workflows and explain the capabilities of MetaboLabPy. Materials and Methods: The software is implemented in Python and uses numerous Python toolboxes, such as numpy, scipy, pandas, etc. The software is implemented in three different packages: metabolabpy, qtmetabolabpy, and metabolabpytools. The metabolabpy package contains classes to handle NMR data and all the numerical routines necessary to process and pre-process 1D NMR data and perform multiplet analysis on 2D-¹H, ¹³C HSQC NMR data. The qtmetabolabpy package contains routines related to the graphical user interface. Results: PySide6 is used to produce a modern and user-friendly graphical user interface. The metabolabpytools package contains routines which are not specific to just handling NMR data, for example, routines to derive isotopomer distributions from the combination of NMR multiplet and GC-MS data. A deep-learning approach for the latter is currently under development. MetaboLabPy is available via the Python Package Index or via GitHub. Full article

(This article belongs to the Special Issue Open-Source Software in Metabolomics)

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19 pages, 4057 KiB

Open AccessEditor’s ChoiceArticle

A Comprehensive Machine Learning Approach for COVID-19 Target Discovery in the Small-Molecule Metabolome

by Md. Shaheenur Islam Sumon, Md Sakib Abrar Hossain, Haya Al-Sulaiti, Hadi M. Yassine and Muhammad E. H. Chowdhury

Metabolites 2025, 15(1), 44; https://doi.org/10.3390/metabo15010044 - 11 Jan 2025

Cited by 1 | Viewed by 1270

Abstract

Background/Objectives: Respiratory viruses, including Influenza, RSV, and COVID-19, cause various respiratory infections. Distinguishing these viruses relies on diagnostic methods such as PCR testing. Challenges stem from overlapping symptoms and the emergence of new strains. Advanced diagnostics are crucial for accurate detection and effective [...] Read more.

Background/Objectives: Respiratory viruses, including Influenza, RSV, and COVID-19, cause various respiratory infections. Distinguishing these viruses relies on diagnostic methods such as PCR testing. Challenges stem from overlapping symptoms and the emergence of new strains. Advanced diagnostics are crucial for accurate detection and effective management. This study leveraged nasopharyngeal metabolome data to predict respiratory virus scenarios including control vs. RSV, control vs. Influenza A, control vs. COVID-19, control vs. all respiratory viruses, and COVID-19 vs. Influenza A/RSV. Method: We proposed a stacking-based ensemble technique, integrating the top three best-performing ML models from the initial results to enhance prediction accuracy by leveraging the strengths of multiple base learners. Key techniques such as feature ranking, standard scaling, and SMOTE were used to address class imbalances, thus enhancing model robustness. SHAP analysis identified crucial metabolites influencing positive predictions, thereby providing valuable insights into diagnostic markers. Results: Our approach not only outperformed existing methods but also revealed top dominant features for predicting COVID-19, including Lysophosphatidylcholine acyl C18:2, Kynurenine, Phenylalanine, Valine, Tyrosine, and Aspartic Acid (Asp). Conclusions: This study demonstrates the effectiveness of leveraging nasopharyngeal metabolome data and stacking-based ensemble techniques for predicting respiratory virus scenarios. The proposed approach enhances prediction accuracy, provides insights into key diagnostic markers, and offers a robust framework for managing respiratory infections. Full article

(This article belongs to the Special Issue Metabolomics and Machine Learning for Improved Diagnostics and as a Tool to Accelerate Drug Development)

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15 pages, 697 KiB

Open AccessEditor’s ChoiceArticle

Pharmacometabolomics Enables Real-World Drug Metabolism Sciences

by Fleur B. Nijdam, Marieke A. J. Hof, Hans Blokzijl, Stephan J. L. Bakker, Eelko Hak, Gérard Hopfgartner, Frank Klont and on behalf of the TransplantLines Investigators

Metabolites 2025, 15(1), 39; https://doi.org/10.3390/metabo15010039 - 10 Jan 2025

Cited by 1 | Viewed by 1372

Abstract

Background/Objectives: Pharmacogenomics (PGx) has revolutionized personalized medicine, notably by predicting drug responses through the study of the metabolic genotype of drug-metabolizing enzymes. However, these genotypes rely heavily on the availability and completeness of drug metabolism information and do not account for (all) [...] Read more.

Background/Objectives: Pharmacogenomics (PGx) has revolutionized personalized medicine, notably by predicting drug responses through the study of the metabolic genotype of drug-metabolizing enzymes. However, these genotypes rely heavily on the availability and completeness of drug metabolism information and do not account for (all) “phenoconversion” factors, like drug–drug interactions and comorbidities. To address these limitations, a more phenotypic approach would be desirable, for which pharmacometabolomics (PMx) could be useful by studying and elucidating drug metabolism in patient samples, such as blood and urine. Methods: This study explored the potential of PMx to analyze real-world drug metabolite profiles of the extensively studied drug cyclosporine (CsA) using 24-h urine samples from 732 kidney and 350 liver transplant recipients included in the TransplantLines Biobank and Cohort Study (NCT identifier NCT03272841). Detected metabolites were matched with existing information on CsA metabolism gathered through a comprehensive literature review, aiming to confirm previously reported metabolites and identify potentially unreported ones. Results: Our analyses confirmed the urinary presence of CsA and six known metabolites. Additionally, we detected three known metabolites not previously reported in urine and identified one unreported metabolite, potentially suggesting the involvement of glutathione conjugation. Lastly, the observed metabolic patterns showed no notable differences between kidney and liver transplant recipients. Conclusions: Our findings demonstrate the potential of PMx to enhance the understanding of drug metabolism, even for well-studied compounds such as CsA. Moreover, this study highlights the value of PMx in real-world drug metabolism research and its potential to complement PGx in advancing personalized medicine. Full article

(This article belongs to the Section Pharmacology and Drug Metabolism)

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13 pages, 2980 KiB

Open AccessEditor’s ChoiceArticle

Untargeted Metabolomics Reveals the Metabolic Characteristics and Biomarkers of Antioxidant Properties of Gardeniae Fructus from Different Geographical Origins in China

by Wu Jiang, Lingling Jiang, Xiaoli Yin, Shuhui Zhang, Xiaojing Duan, Jiadong Chen, Yingying Liu, Hong Zheng and Zhengming Tao

Metabolites 2025, 15(1), 38; https://doi.org/10.3390/metabo15010038 - 10 Jan 2025

Cited by 2 | Viewed by 1045

Abstract

Background/Objectives: Gardeniae Fructus (GF) has been widely used as both food and medicinal purposes for thousands of years, but their antioxidant properties and potential metabolite biomarkers remain unclear. Methods: The purposes of this study were to examine antioxidant activities of 21 GF [...] Read more.

Background/Objectives: Gardeniae Fructus (GF) has been widely used as both food and medicinal purposes for thousands of years, but their antioxidant properties and potential metabolite biomarkers remain unclear. Methods: The purposes of this study were to examine antioxidant activities of 21 GF varieties from different geographical origins in China and identify potential biomarkers of antioxidant properties using an untargeted LC–MS-based metabolomics approach. Results: The results demonstrate that metabolomics had the ability to trace the geographical origins of GF. We found that antioxidant activities varied with different varieties of GF, which was dependent on their chemical compositions. The key chemical categories were obtained as the primary contributors of the antioxidant activity, including prenol lipids, flavonoids, coumarins and derivatives, as well as steroids and steroid derivatives. In addition, adouetine Y, coagulin R 3-glucoside and epicatechin 3-glucoside were identified as potential biomarkers for the antioxidant activity of GF. Conclusions: Therefore, our study sheds light on the metabolic characteristics and biomarkers of the antioxidant properties of GF, contributing to the selection and cultivation of a high antioxidant variety. Full article

(This article belongs to the Special Issue Analysis of Specialized Metabolites in Natural Products)

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11 pages, 3050 KiB

Open AccessEditor’s ChoiceArticle

Docosahexaenoic and Eicosapentaenoic Acid Supplementation Could Attenuate Negative Effects of Maternal Metabolic Syndrome on Liver Lipid Metabolism and Liver Betacellulin Expression in Male and Female Rat Offspring

by Tomislav Mašek, Petra Roškarić, Sunčica Sertić and Kristina Starčević

Metabolites 2025, 15(1), 32; https://doi.org/10.3390/metabo15010032 - 9 Jan 2025

Viewed by 1031

Abstract

Background/Objectives: This study investigated the effects of maternal metabolic syndrome during pregnancy on hepatic fatty acid metabolism and betacellulin expression in rat offspring. A rat model of maternal metabolic syndrome was created with a high-fructose diet (15% fructose in drinking water for [...] Read more.

Background/Objectives: This study investigated the effects of maternal metabolic syndrome during pregnancy on hepatic fatty acid metabolism and betacellulin expression in rat offspring. A rat model of maternal metabolic syndrome was created with a high-fructose diet (15% fructose in drinking water for six months). Methods: The females with metabolic syndrome were divided into the CON group, the HF group, which received fructose in drinking water, and the HF-DHA group, which received fructose in water and increased amounts of DHA (docosahexaenoic acid) and EPA (eicosapentaenoic acid) in the diet (2.5% fish oil in the diet). The male and female offspring were killed at birth and their liver tissue was analyzed for the fatty acid profile and expression of Δ-9-desaturase and betacellulin. Results: When the rat offspring were exposed in utero to maternal fatty acids altered by the high-fructose diet, this resulted in a similarly altered fatty acid profile in the liver, with the most significant changes being Δ-9 desaturation and a dramatic increase in monounsaturated fatty acids. The offspring also showed an overexpression of hepatic betacellulin. Supplementation with DHA and EPA increased the DHA content and normalized the fatty acid composition of oleic acid, saturated fatty acids, linoleic acid and n3-docosapentaenoic acid in the offspring of mothers on a high-fructose diet. In addition, the DHA/EPA supplementation of fructose-fed mothers normalized hepatic Δ-9-desaturase and betacellulin overexpression in the offspring, suggesting that DHA/EPA supplementation affects not only the fatty acid content but also the liver function. Conclusions: The changes observed in this study suggest that DHA/EPA supplementation may modulate the effects of maternal programming on disorders of the lipid metabolism in the offspring. Full article

(This article belongs to the Special Issue Fat and Glucose Metabolism)

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17 pages, 867 KiB

Open AccessEditor’s ChoiceArticle

DisCo P-ad: Distance-Correlation-Based p-Value Adjustment Enhances Multiple Testing Corrections for Metabolomics

by Debmalya Nandy, Debashis Ghosh and Katerina Kechris

Metabolites 2025, 15(1), 28; https://doi.org/10.3390/metabo15010028 - 8 Jan 2025

Viewed by 1229

Abstract

Background: Due to scientific advancements in high-throughput data production technologies, omics studies, such as genomics and metabolomics, often give rise to numerous measurements per sample/subject containing several noisy variables that potentially cloud the true signals relevant to the desired study outcome(s). Therefore, correcting [...] Read more.

Background: Due to scientific advancements in high-throughput data production technologies, omics studies, such as genomics and metabolomics, often give rise to numerous measurements per sample/subject containing several noisy variables that potentially cloud the true signals relevant to the desired study outcome(s). Therefore, correcting for multiple testing is critical while performing any statistical test of significance to minimize the chances of false or missed discoveries. Such correction practice is commonplace in genome-wide association studies (GWAS) but is also becoming increasingly relevant to metabolome-wide association studies (MWAS). However, many existing procedures may be too conservative or too lenient, only assume a linear association between the features, or have not been evaluated on metabolomics data. Methods: One such multiple testing correction strategy is to estimate the number of statistically independent tests, called the effective number of tests, based on the eigen-analysis of the correlation matrix between the features. This effective number is then used for a subsequent single-step adjustment to obtain the pointwise significance level. We propose a modification to the p-value adjustment based on a more general measure of association between two predictors, the distance correlation, with a specific focus on MWAS. Results: We assessed common GWAS p-value adjustment procedures and one tailored for MWAS, which rely on eigen-analysis of the Pearson’s correlation matrix. Our study, including varying sample size-to-feature ratios, response types, and metabolite groupings, highlights the superior performance of the distance correlation. Conclusion: We propose the distance-correlation-based p-value adjustment (DisCo P-ad) as a novel modification that can enhance existing eigen-analysis-based multiple testing correction procedures by increasing power or reducing false positives. While our focus is on metabolomics, DisCo P-ad can also readily be applied to other high-dimensional omics studies. Full article

(This article belongs to the Section Bioinformatics and Data Analysis)

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40 pages, 3770 KiB

Open AccessEditor’s ChoiceArticle

Impact of Ketogenic and Mediterranean Diets on Gut Microbiota Profile and Clinical Outcomes in Drug-Naïve Patients with Diabesity: A 12-Month Pilot Study

by Vanessa Palmas, Andrea Deledda, Vitor Heidrich, Giuseppina Sanna, Giulia Cambarau, Michele Fosci, Lorenzo Puglia, Enrico Antonio Cappai, Alessio Lai, Andrea Loviselli, Aldo Manzin and Fernanda Velluzzi

Metabolites 2025, 15(1), 22; https://doi.org/10.3390/metabo15010022 - 6 Jan 2025

Cited by 2 | Viewed by 9966

Abstract

Background/Objectives: Managing type 2 diabetes mellitus (T2DM) and obesity requires a multidimensional, patient-centered approach including nutritional interventions (NIs) and physical activity. Changes in the gut microbiota (GM) have been linked to obesity and the metabolic alterations typical of T2DM and obesity, and [...] Read more.

Background/Objectives: Managing type 2 diabetes mellitus (T2DM) and obesity requires a multidimensional, patient-centered approach including nutritional interventions (NIs) and physical activity. Changes in the gut microbiota (GM) have been linked to obesity and the metabolic alterations typical of T2DM and obesity, and they are strongly influenced by diet. However, few studies have evaluated the effects on the GM of a very-low-calorie ketogenic diet (VLCKD) in patients with T2DM, especially in the mid-term and long-term. This longitudinal study is aimed at evaluating the mid-term and long-term impact of the VLCKD and Mediterranean diet (MD) on the GM and on the anthropometric, metabolic, and lifestyle parameters of 11 patients with T2DM and obesity (diabesity). This study extends previously published results evaluating the short-term (three months) impact of these NIs on the same patients. Methods: At baseline, patients were randomly assigned to either a VLCKD (KETO group) or a Mediterranean diet (MEDI group). After two months, the KETO group gradually shifted to a Mediterranean diet (VLCKD-MD), according to current VLCKD guidelines. From the fourth month until the end of the study both groups followed a similar MD. Previous published results showed that VLCKD had a more beneficial impact than MD on several variables for 3 months of NI. In this study, the analyses were extended until six (T6) and twelve months (T12) of NI by comparing data prospectively and against baseline (T0). The GM analysis was performed through next-generation sequencing. Results: Improvements in anthropometric and metabolic parameters were more pronounced in the KETO group at T6, particularly for body mass index (−5.8 vs. −1.7 kg/m²; p = 0.006) and waist circumference (−15.9 vs. −5.2 cm; p = 0.011). At T6, a significant improvement in HbA1c (6.7% vs. 5.5% p = 0.02) and triglyceride (158 vs. 95 mg/dL p = 0.04) values compared to T0 was observed only in the KETO group, which maintained the results achieved at T3. The VLCKD-MD had a more beneficial impact than the MD on the GM phenotype. A substantial positive modulatory effect was observed especially up to the sixth month of the NI in KETO due to the progressive increase in bacterial markers of human health. After the sixth month, most markers of human health decreased, though they were still increased compared with baseline. Among them, the Verrucomicrobiota phylum was identified as the main biomarker in the KETO group, together with its members Verrucomicrobiae, Akkermansiaceae, Verrucomicrobiales, and Akkermansia at T6 compared with baseline. Conclusions: Both dietary approaches ameliorated health status, but VLCKD, in support of the MD, has shown greater improvements on anthropometric and metabolic parameters, as well as on GM profile, especially up to T6 of NI. Full article

(This article belongs to the Special Issue Impact of Macronutrients on Metabolism)

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13 pages, 1086 KiB

Open AccessEditor’s ChoiceArticle

The Validation of a Novel, Sex-Specific LDL-Cholesterol Equation and the Friedewald, Sampson-NIH, and Extended-Martin–Hopkins Equations Against Direct Measurement in Korean Adults

by Hyun Suk Yang, Soo-Nyung Kim, Seungho Lee and Mina Hur

Metabolites 2025, 15(1), 18; https://doi.org/10.3390/metabo15010018 - 5 Jan 2025

Viewed by 1161

Abstract

Background/Objectives: The currently established equations for calculating low-density lipoprotein cholesterol (LDLc) do not reflect the sex-specific differences in lipid metabolism. We aimed to develop a sex-specific LDLc equation (SSLE) and validate it with three established equations (Friedewald, Sampson-NIH, and ext-Martin–Hopkins) against direct [...] Read more.

Background/Objectives: The currently established equations for calculating low-density lipoprotein cholesterol (LDLc) do not reflect the sex-specific differences in lipid metabolism. We aimed to develop a sex-specific LDLc equation (SSLE) and validate it with three established equations (Friedewald, Sampson-NIH, and ext-Martin–Hopkins) against direct LDLc measurement in Korean adults. Methods: This study included 23,757 subjects (51% male; median age, 51 years) from the 2009–2022 Korean National Health and Nutrition Examination Survey. We developed the SSLE through multiple linear regression incorporating total cholesterol (TC), high-density lipoprotein cholesterol (HDLc), triglycerides (TG), and sex. The validation metrics included Bland–Altman analysis for mean absolute percentage error (MAPE) and agreement of the categorization based on the NCEP ATP-III guidelines, assessed by sex and lipid subgroups. Results: The derived SSLE equation was as follows: for TG < 200 mg/dL, LDLc = 0.963 × TC − 0.881 × HDLc − 0.111 × TG + 0.982 × Sex − 6.958; for TG ≥ 200 mg/dL, LDLc = 0.884 × TC − 0.646 × HDLc − 0.126 × TG + 3.742 × Sex − 3.214 (male = 1, female = 0). The MAPE was similar between males and females for the SSLE (4.6% for both) and ext-Martin–Hopkins (5.0% vs. 4.9%) but higher in males for the Sampson-NIH (5.4% vs. 4.9%) and Friedewald (7.6% vs. 5.7%). In the TG ≥ 400 mg/dL group, the MAPE increased progressively: SSLE (10.2%), ext-Martin–Hopkins (12.0%), Sampson-NIH (12.7%), and Friedewald (27.4%). In the LDLc < 70 mg/dL group, the MAPE was as follows: SSLE (8.0%), Sampson-NIH (8.6%), ext-Martin–Hopkins (9.7%), and Friedewald (12.8%). At TG 200–400 mg/dL, the SSLE revealed very good agreement (κ = 0.801) versus good agreement for other equations (ext-Martin–Hopkins κ = 0.794, Sampson-NIH κ = 0.782, Friedewald κ = 0.696). Conclusions: The novel SSLE demonstrated superior accuracy and agreement in Korean adults. Further validation studies across different ethnic populations are warranted. Full article

(This article belongs to the Special Issue Lipid Biomarkers and Cardiometabolic Diseases—2nd Edition)

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15 pages, 1699 KiB

Open AccessEditor’s ChoiceArticle

Evaluating Metabolic Profiling of Human Milk Using Biocrates MxP^® QUANT 500 Assay

by Daniela Hampel, Setareh Shahab-Ferdows, Gilberto Kac and Lindsay H. Allen

Metabolites 2025, 15(1), 14; https://doi.org/10.3390/metabo15010014 - 3 Jan 2025

Cited by 1 | Viewed by 1468

Abstract

Background/Objectives: Metabolic profiling of human milk (HM) is indispensable for elucidating mother-milk-infant relationships. Methods: We evaluated the Biocrates MxP^® Quant 500 assay for HM-targeted metabolomics (106 small molecules, 524 lipids) and analyzed in a feasibility test HM from apparently healthy Brazilian mothers [...] Read more.

Background/Objectives: Metabolic profiling of human milk (HM) is indispensable for elucidating mother-milk-infant relationships. Methods: We evaluated the Biocrates MxP^® Quant 500 assay for HM-targeted metabolomics (106 small molecules, 524 lipids) and analyzed in a feasibility test HM from apparently healthy Brazilian mothers (A: 2–8, B: 28–50, C: 88–119 days postpartum, n_total = 25). Results: Of the 630 possible signatures detectable with this assay, 506 were above the limits of detection in an HM-pool (10 µL) used for assay evaluation, 12 of them above the upper limit of quantitation. Analyzing five different HM-pool volumes (2–20 µL) revealed acceptable linearity for 458 metabolites. Intraday accuracy of 80–120% was attained by 469 metabolites after spiking and for 342 after a 1:2 dilution. Analyzing HM from Brazilian mothers revealed significantly lower concentrations in colostrum vs. mature milk for many flow-injection analyses (FIA) and only a few LC-MS metabolites, including triglycerides, sphingomyelins, and phosphatidylcholines. Higher concentrations at the later lactation stages were found predominantly for amino acids and related compounds. Conclusions: The MxP Quant^® 500 assay is a useful tool for HM metabolic profiling, minimizing analytical bias between matrices, and enhancing our ability to study milk as a biological system. Full article

(This article belongs to the Special Issue Advanced Metabolic Profiling via Gas Chromatography–Mass Spectrometry and Liquid Chromatography–Mass Spectrometry)

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20 pages, 3377 KiB

Open AccessEditor’s ChoiceArticle

Metabolomic Insights into the Allelopathic Effects of Ailanthus altissima (Mill.) Swingle Volatile Organic Compounds on the Germination Process of Bidens pilosa (L.)

by Leonardo Bruno, Diana M. Mircea and Fabrizio Araniti

Metabolites 2025, 15(1), 12; https://doi.org/10.3390/metabo15010012 - 3 Jan 2025

Cited by 2 | Viewed by 1164

Abstract

Background/Objectives: This study explores the allelopathic effects of volatile organic compounds (VOCs) emitted by the invasive species Ailanthus altissima (Mill.) Swingle on the seed germination of Bidens pilosa. A. altissima is known for releasing allelopathic VOCs that suppress the growth of neighbouring [...] Read more.

Background/Objectives: This study explores the allelopathic effects of volatile organic compounds (VOCs) emitted by the invasive species Ailanthus altissima (Mill.) Swingle on the seed germination of Bidens pilosa. A. altissima is known for releasing allelopathic VOCs that suppress the growth of neighbouring plants, contributing to its invasive potential. Methods: To examine these effects, we exposed B. pilosa seeds to varying concentrations of A. altissima VOCs, assessing germination rates and metabolic changes through untargeted metabolomics. Results: Our findings revealed that VOCs from A. altissima significantly inhibited the germination speed and overall germination rates of B. pilosa in a dose-dependent manner. Metabolomic profiling showed disruptions in energy and amino acid metabolism pathways, specifically involving delayed breakdown of starch and key metabolites, indicating inhibition of critical metabolic processes during early germination stages. This metabolic delay likely impairs B. pilosa’s establishment and competitiveness, enhancing A. altissima’s ecological dominance. Conclusions: The results underscore the potential of VOC-based allelopathy as a mechanism of plant invasion, offering insights into the role of VOCs in interspecies plant competition and ecosystem dynamics. Full article

(This article belongs to the Special Issue Plant Biotic and Abiotic Stress Responses and Tolerance: Phytohormonal and Metabolic Insights)

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17 pages, 2872 KiB

Open AccessEditor’s ChoiceArticle

Serum Uric Acid and Bone Health in Middle-Aged and Elderly Hypertensive Patients: A Potential U-Shaped Association and Implications for Future Fracture Risk

by Shuaiwei Song, Xintian Cai, Junli Hu, Qing Zhu, Di Shen, Huimin Ma, Yingying Zhang, Rui Ma, Pan Zhou, Wenbo Yang, Jing Hong and Nanfang Li

Metabolites 2025, 15(1), 15; https://doi.org/10.3390/metabo15010015 - 3 Jan 2025

Cited by 7 | Viewed by 1405

Abstract

Background: The influence of serum uric acid (SUA) on bone metabolism, as suggested by previous studies, remains a contentious issue. SUA plays a complex role in bone health and hypertension, making it challenging to discern its impact on the skeletal status of middle-aged [...] Read more.

Background: The influence of serum uric acid (SUA) on bone metabolism, as suggested by previous studies, remains a contentious issue. SUA plays a complex role in bone health and hypertension, making it challenging to discern its impact on the skeletal status of middle-aged and elderly hypertensive patients. This study aims to elucidate the effects of SUA on bone health, with a particular focus on its association with osteoporosis and the risk of fractures. Methods: Multiple linear regression analyzed SUA levels against bone mineral density (BMD) and future fracture risk. Additionally, multivariate logistic regression was used to examine the association between SUA and osteoporosis. Dose–response relationship analysis was conducted using generalized smooth curve fitting (GSCF) and restricted cubic spline (RCS) methods. Results: With the exception of the total femur region, SUA and BMD showed a positive connection. GSCF analysis revealed an inverted U-shaped relationship between SUA and BMD, alongside a U-shaped trend with FRAX scores. Moreover, RCS analysis indicated a U-shaped relationship between osteoporosis risk and SUA levels, with higher risks identified in the first and third tertiles compared to the second tertile. Conclusions: In individuals with middle-aged and older hypertension, SUA is substantially linked to bone health. The identification of an inverted U-shaped relationship with BMD and U-shaped relationships with FRAX scores and osteoporosis risk highlights the nuanced influence of SUA. These findings suggest that both low and high SUA levels may adversely affect bone health, emphasizing the need for further research. Full article

(This article belongs to the Special Issue Nutrition and Metabolic Changes in Aging and Age-Related Diseases)

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21 pages, 2010 KiB

Open AccessEditor’s ChoiceArticle

Longitudinal Metabolomics Data Analysis Informed by Mechanistic Models

by Lu Li, Huub Hoefsloot, Barbara M. Bakker, David Horner, Morten A. Rasmussen, Age K. Smilde and Evrim Acar

Metabolites 2025, 15(1), 2; https://doi.org/10.3390/metabo15010002 - 24 Dec 2024

Cited by 2 | Viewed by 1196

Abstract

Background: Metabolomics measurements are noisy, often characterized by a small sample size and missing entries. While data-driven methods have shown promise in terms of analyzing metabolomics data, e.g., revealing biomarkers of various phenotypes, metabolomics data analysis can significantly benefit from incorporating prior [...] Read more.

Background: Metabolomics measurements are noisy, often characterized by a small sample size and missing entries. While data-driven methods have shown promise in terms of analyzing metabolomics data, e.g., revealing biomarkers of various phenotypes, metabolomics data analysis can significantly benefit from incorporating prior information about metabolic mechanisms. This paper introduces a novel data analysis approach to incorporate mechanistic models in metabolomics data analysis. Methods: We arranged time-resolved metabolomics measurements of plasma samples collected during a meal challenge test from the COPSAC₂₀₀₀ cohort as a third-order tensor: subjects by metabolites by time samples. Simulated challenge test data generated using a human whole-body metabolic model were also arranged as a third-order tensor: virtual subjects by metabolites by time samples. Real and simulated data sets were coupled in the metabolites mode and jointly analyzed using coupled tensor factorizations to reveal the underlying patterns. Results: Our experiments demonstrated that the joint analysis of simulated and real data had better performance in terms of pattern discovery, achieving higher correlations with a BMI (body mass index)-related phenotype compared to the analysis of only real data in males, while in females, the performance was comparable. We also demonstrated the advantages of such a joint analysis approach in the presence of incomplete measurements and its limitations in the presence of wrong prior information. Conclusions: The joint analysis of real measurements and simulated data (generated using a mechanistic model) through coupled tensor factorizations guides real data analysis with prior information encapsulated in mechanistic models and reveals interpretable patterns. Full article

(This article belongs to the Special Issue Metabolomics in Human Diseases and Health)

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25 pages, 11702 KiB

Open AccessEditor’s ChoiceArticle

Gallic Acid: A Potent Metabolite Targeting Shikimate Kinase in Acinetobacter baumannii

by Mansour S. Alturki, Abdulaziz H. Al Khzem, Mohamed S. Gomaa, Nada Tawfeeq, Marwah H. Alhamadah, Futun M. Alshehri, Raghad Alzahrani, Hanin Alghamdi, Thankhoe A. Rants’o, Khaled A. G. Ayil, Abdulaziz K. Al Mouslem and Mohammed Almaghrabi

Metabolites 2024, 14(12), 727; https://doi.org/10.3390/metabo14120727 - 23 Dec 2024

Cited by 1 | Viewed by 1855

Abstract

Background/Objectives: Acinetobacter baumannii is a highly multidrug-resistant pathogen resistant to almost all classes of antibiotics; new therapeutic strategies against this infectious agent are urgently needed. Shikimate kinase is an enzyme belonging to the shikimate pathway and has become a potential target for [...] Read more.

Background/Objectives: Acinetobacter baumannii is a highly multidrug-resistant pathogen resistant to almost all classes of antibiotics; new therapeutic strategies against this infectious agent are urgently needed. Shikimate kinase is an enzyme belonging to the shikimate pathway and has become a potential target for drug development. This work describes the search for Food and Drug Administration (FDA)-approved drugs and natural compounds, including gallic acid, that could be repurposed as selective shikimate kinase inhibitors by integrated computational and experimental approaches. Methods: Approaches to drug design using structure-based and ligand-based methodology, in-silico screening, molecular docking, and molecular dynamics for the study of both binding affinity and stability. Experimental Validation Determination of minimum inhibitory concentration (MIC) and minimum bactericidal concentration (MBC) on Acinetobacter baumannii and Enterococcus faecalis. Results/Conclusions: Among them, gallic acid, obtained from plants, proved to be the most promising compound that showed sufficient binding with shikimate kinase through computational studies. Gallic acid showed very good activity against Acinetobacter baumannii and Enterococcus faecalis in the MIC and MBC assay, respectively. Gallic acid exhibited better activity against Acinetobacter baumannii due to the overexpression of shikimate kinase. Gallic acid has emerged as a potential therapeutic candidate drug against A. baumannii infection and, therefore, as a strategy against the appearance of multidrug-resistant microorganisms. This study not only identifies a novel repurposing opportunity for gallic acid but also provides a comprehensive computational and experimental framework for accelerating antimicrobial drug discovery against multidrug-resistant pathogens. Full article

(This article belongs to the Special Issue Novel Approaches for Metabolomics in Drugs and Biomarkers Discovery: 2nd Edition)

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15 pages, 3111 KiB

Open AccessEditor’s ChoiceArticle

Analysis of Immunosuppression and Antioxidant Damage in Diploid and Triploid Crucian Carp (Carassius auratus) Induced by Saline-Alkaline Environmental Stress: From Metabolomic Insight

by Fangying Yuan, Xiaofeng Wei, Dongping Li, Xiaofeng Jin, Jing Wang and Yanchun Sun

Metabolites 2024, 14(12), 721; https://doi.org/10.3390/metabo14120721 - 21 Dec 2024

Cited by 1 | Viewed by 1025

Abstract

Objectives: The salinization of the water environment worldwide is increasing, which has brought great challenges to the sustainability of fish farming of aquatic animals. Methods: Three NaHCO₃ concentration groups (0 mmol/L, 20 mmol/L, and 60 mmol/L) were set up in this study [...] Read more.

Objectives: The salinization of the water environment worldwide is increasing, which has brought great challenges to the sustainability of fish farming of aquatic animals. Methods: Three NaHCO₃ concentration groups (0 mmol/L, 20 mmol/L, and 60 mmol/L) were set up in this study to investigate growth and metabolic differences between diploid and triploid crucian carp under saline-alkaline stresses. Purpose: This study utilized UPLC-QTOF/MS metabolomics to analyze significant metabolites and metabolic pathways in the serum of diploid and triploid crucian carp, exposing them to different NaHCO₃ concentrations in saline-alkaline habitats, elucidating the mechanism of their metabolic differences. Results: Results revealed that in the CA20 group, diploid and triploid crucian carp shared 69 differential metabolites, primarily enriched in pathways such as sphingolipid metabolism, glycerophospholipid metabolism, and linoleic acid metabolism. In the CA60 group, 46 differentially metabolites (DMs) were identified, mainly enriched in pathways such as linoleic acid metabolism, unsaturated fatty acid biosynthesis and sphingolipid metabolism. Conclusions: The analysis indicated that under different carbonate-saline-alkaline concentrations, diploid and triploid crucian carp primarily enriched in metabolic pathways such as glycerophospholipid metabolism, sphingolipid metabolism, and unsaturated fatty acid biosynthesis. With increasing carbonate-alkaline concentrations, hemolytic phospholipids associated with cell apoptosis were significantly upregulated and sphingolipid metabolism related to inflammation was more significantly enriched in triploid crucian carp, indicating that triploid crucian carp exhibited significant sensitivity to high carbonate-saline-alkaline stress and poorer carbonate-saline-alkaline tolerance. The results of this study provided a scientific theoretical basis for the later cultivation and aquaculture research of saline-alkaline-tolerant fish species. Full article

(This article belongs to the Special Issue Metabolic Physiology Under Environmental Coercion)

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13 pages, 2660 KiB

Open AccessEditor’s ChoiceArticle

Cyperus rotundus Extract and Its Active Metabolite α-Cyperone Alleviates Paclitaxel-Induced Neuropathic Pain via the Modulation of the Norepinephrine Pathway

by Keun-Tae Park, Insuk Sim, Jae-Chul Lee, Young-Ho Jin and Woojin Kim

Metabolites 2024, 14(12), 719; https://doi.org/10.3390/metabo14120719 - 20 Dec 2024

Cited by 1 | Viewed by 1501

Abstract

Background: Paclitaxel is a widely used anticancer drug for ovarian, lung, breast, and stomach cancers; however, its clinical use is often limited by the side effects of peripheral neuropathy. This study evaluated the effects of Cyperus rotundus (C. rotundus) extract and [...] Read more.

Background: Paclitaxel is a widely used anticancer drug for ovarian, lung, breast, and stomach cancers; however, its clinical use is often limited by the side effects of peripheral neuropathy. This study evaluated the effects of Cyperus rotundus (C. rotundus) extract and its active metabolite, α-cyperone, on paclitaxel-induced neuropathic pain. Methods: The oral administration of C. rotundus extract at doses of 500 mg/kg and intraperitoneal administration of α-cyperone at doses of 480 and 800 μg/kg prevented both the development of cold and mechanical pain. Results: The gene and protein expressions of tyrosine hydroxylase and noradrenergic receptors (α1- and α2-adrenergic), which were upregulated by paclitaxel, were significantly downregulated in the C. rotundus extract-treated group. In the locus coeruleus region of the mouse brain, C. rotundus extract administration also reduced the elevated expression of tyrosine hydroxylase induced by paclitaxel. The concentration of α-cyperone in C. rotundus extract was quantified using high-performance liquid chromatography (HPLC). In the group treated with α-cyperone, at levels corresponding to its content in C. rotundus, both cold and mechanical allodynia were effectively prevented. Conclusions: This study suggests that α-cyperone shows potential as a preventive agent for paclitaxel-induced neuropathic pain. Full article

(This article belongs to the Section Plant Metabolism)

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16 pages, 2393 KiB

Open AccessEditor’s ChoiceArticle

Chemical Diversity of Mediterranean Seagrasses Volatilome

by Salomé Coquin, Elena Ormeno, Vanina Pasqualini, Briac Monnier, Gérald Culioli, Caroline Lecareux, Catherine Fernandez and Amélie Saunier

Metabolites 2024, 14(12), 705; https://doi.org/10.3390/metabo14120705 - 14 Dec 2024

Cited by 4 | Viewed by 1098

Abstract

Background/Objectives: Biogenic volatile organic compounds (BVOCs), extensively studied in terrestrial plants with global emissions around 1 PgC yr⁻¹, are also produced by marine organisms. However, benthic species, especially seagrasses, are understudied despite their global distribution (177,000–600,000 km²). This study [...] Read more.

Background/Objectives: Biogenic volatile organic compounds (BVOCs), extensively studied in terrestrial plants with global emissions around 1 PgC yr⁻¹, are also produced by marine organisms. However, benthic species, especially seagrasses, are understudied despite their global distribution (177,000–600,000 km²). This study aims to examine BVOC emissions from key Mediterranean seagrass species (Cymodocea nodosa, Posidonia oceanica, Zostera noltei, and Zostera marina) in marine and coastal lagoon environments. Methods: BVOCs were collected using headspace solid-phase microextraction (HS-SPME) using divinylbenzene/carboxen/polydimethylsiloxane (DVB/CAR/PDMS) fibers and analyzed by gas chromatography–mass spectrometry (GC-MS). Results: An important chemical diversity was found with a total of 92 volatile compounds (61 for Z. noltei, 59 for C. nodosa, 55 for P. oceanica, and 51 for Z. marina), from different biosynthetic pathways (e.g., terpenoids, benzenoids, and fatty acid derivatives) and with several types of chemical functions (e.g., alkanes, esters, aldehydes, and ketones) or heteroatoms (e.g., sulfur). No differences in chemical richness or diversity of compounds were observed between species. The four species shared 29 compounds enabling us to establish a specific chemical footprint for Mediterranean marine plants, including compounds like benzaldehyde, benzeneacetaldehyde, 8-heptadecene, heneicosane, heptadecane, nonadecane, octadecane, pentadecane, tetradecane, and tridecanal. PLS-DA and Heatmap show that the four species presented significantly different chemical profiles. The major compounds per species in relative abundance were isopropyl myristate for C. nodosa (25.6%), DMS for P. oceanica (39.3%), pentadecane for Z. marina (42.9%), and heptadecane for Z. noltei (46%). Conclusions: These results highlight the potential of BVOCs’ emission from seagrass ecosystems and reveal species-specific chemical markers. Full article

(This article belongs to the Special Issue Unlocking Nature's Toolbox: Advances in Plant Metabolites Identification)

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15 pages, 1109 KiB

Open AccessEditor’s ChoiceArticle

Using Serum Metabolomic Signatures to Investigate Effects of Acupuncture on Pain-Fatigue-Sleep Disturbance in Breast Cancer Survivors

by Hongjin Li, Ardith Z. Doorenbos, Yinglin Xia, Jun Sun, Hannah Choi, Richard E. Harris, Shuang Gao, Katy Sullivan and Judith M. Schlaeger

Metabolites 2024, 14(12), 698; https://doi.org/10.3390/metabo14120698 - 10 Dec 2024

Cited by 2 | Viewed by 1368

Abstract

Background/Objectives: Acupuncture is an efficacious integrative therapy for treating pain, fatigue, and sleep disturbance (the psychoneurological symptom cluster) in breast cancer survivors. However, the mechanisms underlying its effects remain unclear, and related metabolomics studies are limited. This study aimed to examine serum metabolite [...] Read more.

Background/Objectives: Acupuncture is an efficacious integrative therapy for treating pain, fatigue, and sleep disturbance (the psychoneurological symptom cluster) in breast cancer survivors. However, the mechanisms underlying its effects remain unclear, and related metabolomics studies are limited. This study aimed to examine serum metabolite changes after acupuncture and their relationships to symptom improvement. Methods: Forty-two breast cancer survivors experiencing pain, fatigue, and sleep disturbance participated in a single-arm acupuncture trial. They received a 10-session acupuncture intervention over 5 weeks. Fasting blood samples and symptom surveys were collected before and after the acupuncture intervention, and untargeted metabolomics profiling was conducted on serum samples. Mixed-effects models adjusting for covariates (age, race, body mass index, and antidepressant use) were applied for analysis. Results: After acupuncture, there was a significant reduction in the psychoneurological symptom cluster (mean reduction = −6.2, p < 0.001).Bonferroni correction was applied to 40 independent metabolite clusters (α = 0.00125); cysteine-glutathione disulfide (p = 0.0006) significantly increased, and retinal (p = 0.0002) and cis-urocanate (p = 0.0005) were significantly decreased. Dimethyl sulfone (p = 0.00139) showed a trend towards reduction after acupuncture and its change (p = 0.04, β =1.97) was positively associated with reduction in the psychoneurological symptom cluster. Also, increased lauroylcarnitine (p = 0.0009) and decreased cytosine (p = 0.0008) can modulate the therapeutic effects of acupuncture. Conclusions: Acupuncture demonstrates beneficial effects on the psychoneurological symptom cluster in breast cancer survivors. Dimethyl sulfone may be a promising mediator in the relationship between acupuncture and psychoneurological symptoms, while acylcarnitine metabolism may modulate the therapeutic effect of acupuncture. Full article

(This article belongs to the Special Issue Investigation of the Metabolic Mechanisms Underlying Breast Cancer: Navigating from Diagnosis to Survivorship)

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14 pages, 7233 KiB

Open AccessEditor’s ChoiceArticle

Non-Targeted Metabolomics Analysis Reveals Metabolite Profiles Change During Whey Fermentation with Kluyveromyces marxianus

by Yansong Gao, Lei Gao, You Kang, Ge Yang, Zijian Zhao, Yujuan Zhao and Shengyu Li

Metabolites 2024, 14(12), 694; https://doi.org/10.3390/metabo14120694 - 9 Dec 2024

Cited by 1 | Viewed by 1531

Abstract

Background: Whey fermentation could produce bioactive substances with immunomodulatory effects, metabolic syndrome modulation, and antioxidant properties, thereby imparting functional characteristics to products and facilitating the development of novel foods with health-promoting potential. Methods: A non-targeted metabolomics approach using liquid chromatography–mass spectrometry (LC-MS) was [...] Read more.

Background: Whey fermentation could produce bioactive substances with immunomodulatory effects, metabolic syndrome modulation, and antioxidant properties, thereby imparting functional characteristics to products and facilitating the development of novel foods with health-promoting potential. Methods: A non-targeted metabolomics approach using liquid chromatography–mass spectrometry (LC-MS) was employed to investigate changes in the metabolite profiles of whey fermented by Kluyveromyces marxianus strain KM812 over varying fermentation durations. Results: The findings demonstrated a progressive enrichment of metabolites over time. A total of 151 differential metabolites were identified and categorized primarily into amino acids, peptides, and analogues, fatty acids and conjugates, and carbohydrates and conjugates, as well as benzoic acids and derivatives. The highest relative content of whey metabolites was observed at 48 h of fermentation, with a cumulative increase of 1.45-fold, 1.49-fold, 3.39-fold, and 1.24-fold for peptides and amino acids, peptides, and analogues, fatty acids and conjugates, and carbohydrates and conjugates, respectively. Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis revealed associations with 23 specific metabolites and delineated 9 metabolic pathways, predominantly involved in amino acid and lipid metabolism. Conclusions: Based on the above, KM812 could effectively degrade macromolecular substances in whey into small molecules such as L-isoleucine, ornithine, betaine, α-linolenic acid, and palmitoleic acid, thereby influencing the nutritional and functional properties of whey. In-depth analysis of the metabolic products in KM812-fermented whey could provide a theoretical basis for the development of functional foods derived from small molecules in the future. Full article

(This article belongs to the Section Food Metabolomics)

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14 pages, 8565 KiB

Open AccessEditor’s ChoiceArticle

Role of Milk Intake in Modulating Serum Lipid Profiles and Gut Metabolites

by Ting Xu, Chang Zhang, Yufeng Yang, Liang Huang, Qingyou Liu, Ling Li, Qingkun Zeng and Zhipeng Li

Metabolites 2024, 14(12), 688; https://doi.org/10.3390/metabo14120688 - 7 Dec 2024

Viewed by 1180

Abstract

Background/Objectives: Milk is one of the main sources of nutrition in people’s daily diet, but the fat in milk raises health concerns in consumers. Here, we aimed to elucidate the impact of Buffalo milk and Holstein cow milk consumption on blood lipid health [...] Read more.

Background/Objectives: Milk is one of the main sources of nutrition in people’s daily diet, but the fat in milk raises health concerns in consumers. Here, we aimed to elucidate the impact of Buffalo milk and Holstein cow milk consumption on blood lipid health through metabolomics analysis. Methods: Golden hamsters were administered Murrah Buffalo milk (BM) or Holstein cow milk (HM), and the body weight and serum lipid indicators were tested and recorded. The hamsters receiving equal amounts of physiological saline were used as the negative control (NC). Serum and fecal samples were collected, and LC-MS was used to identify the metabolites in the samples. Results: The results showed that both the BM and HM groups exhibited a significant reduction in body weight compared to that of the NC group from day 9, and the serum TG, TC, and LDL-C levels were significantly lower than those of the NC group. Further analysis identified 564 and 567 metabolites in the serum and fecal samples shared in the BM and HM groups and significantly different from those in the NC group, which were mainly enriched in the pathways related to lipid metabolism, such as fatty acid biosynthesis, arachidonic acid metabolism, and primary bile acid biosynthesis. Correlation analysis further suggested that milk intake can increase the levels of Muramic Acid, Oleoyl Ethanolamide, Seratrodast, Chenodeoxycholic Acid, Docosahexaenoic Acid Ethyl Ester, and Deoxycholic Acid in the serum and gut microbiota, which may affect TG, TC, HDL-C, and LDL-C in the serum, and thereby benefit the body’s lipid health. Conclusions: The results further confirmed that milk intake has a beneficial effect on blood lipid health by altering multiple metabolites in the serum and the gut. This study provides novel evidence that milk consumption is beneficial to health and is a reference for guiding people to a healthy diet. Full article

(This article belongs to the Special Issue Nutritional and Metabolic Influences on Animal Growth and Reproduction)

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9 pages, 1324 KiB

Open AccessEditor’s ChoiceArticle

The Role of Beta-Hydroxybutyrate in Mitigating the Inflammatory and Metabolic Consequences of Uric Acid

by Nicole P. Remund, John G. Larsen, Marley J. Shin, Cali E. Warren, Isabelle L. Palmer, Iris J. Kim, Elijah T. Cooper-Leavitt, Derek M. Clarke, Colson G. Beus, Richard J. Johnson, Juan A. Arroyo, Paul R. Reynolds and Benjamin T. Bikman

Metabolites 2024, 14(12), 679; https://doi.org/10.3390/metabo14120679 - 4 Dec 2024

Cited by 3 | Viewed by 5771

Abstract

Background: Uric acid (UA), a metabolite of purine and fructose metabolism, is linked to inflammation and metabolic disorders, including gout and cardiovascular disease. Its pro-inflammatory effects are largely driven by the activation of the nucleotide-binding oligomerization domain-like receptor family pyrin domain-containing 3 (NLRP3) [...] Read more.

Background: Uric acid (UA), a metabolite of purine and fructose metabolism, is linked to inflammation and metabolic disorders, including gout and cardiovascular disease. Its pro-inflammatory effects are largely driven by the activation of the nucleotide-binding oligomerization domain-like receptor family pyrin domain-containing 3 (NLRP3) inflammasome, leading to increased cytokine production. Beta-hydroxybutyrate (BHB), a ketone produced during fasting or carbohydrate restriction, has been shown to reduce inflammation. This study explores the role of BHB in mitigating the inflammatory and metabolic effects of elevated uric acid levels. Methods: We utilized a murine muscle cell culture treated with UA and BHB. Results: Muscle cells treated with UA had increased production of pro-inflammatory cytokines and reduced cell viability. Co-treatment with BHB reversed these effects, improving cell survival and reducing cytokine levels. Additionally, uric acid impaired mitochondrial function and increased oxidative stress, which were mitigated by BHB. Furthermore, uric acid disrupted insulin signaling, but BHB co-treatment restored insulin sensitivity. Conclusions: These findings suggest that BHB holds therapeutic potential by counteracting the inflammatory and metabolic disruptions caused by elevated uric acid, making it a promising target for conditions such as hyperuricemia and metabolic syndrome. Full article

(This article belongs to the Special Issue Exploring Uric Acid and Beyond)

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13 pages, 2027 KiB

Open AccessEditor’s ChoiceArticle

Antihypertensive Effect of Perla and Esmeralda Barley (Hordeum vulgare L.) Sprouts in an Induction Model with L-NAME In Vivo

by Abigail García-Castro, Alma D. Román-Gutiérrez, Fabiola A. Guzmán-Ortiz and Raquel Cariño-Cortés

Metabolites 2024, 14(12), 678; https://doi.org/10.3390/metabo14120678 - 3 Dec 2024

Viewed by 3939

Abstract

Background: Hypertension is one of the leading causes of premature death worldwide. Despite advances in conventional treatments, there remains a significant need for more effective and natural alternatives to control hypertension. In this context, sprouted barley extracts have emerged as a potential therapeutic [...] Read more.

Background: Hypertension is one of the leading causes of premature death worldwide. Despite advances in conventional treatments, there remains a significant need for more effective and natural alternatives to control hypertension. In this context, sprouted barley extracts have emerged as a potential therapeutic option. This study presents the evaluation of the bioactive properties of extracts from two varieties of barley germinated for different periods (3, 5, and 7 days), focusing on their potential to regulate blood pressure mechanisms. Objectives/Methods: The main objective was to assess the effects of these extracts on blood pressure regulation in N(ω)-Nitro-L-Arginine Methyl Ester (L-NAME)-induced hypertensive rats. Renal (creatinine, urea, uric acid, and total protein) and endothelial (NOx levels) function, angiotensin-converting enzyme (ACE) I and II activity, and histopathological effects on heart and kidney tissues were evaluated. Results: In particular, Esmeralda barley extract demonstrated 83% inhibition of ACE activity in vitro. Furthermore, the combined administration of sprouted barley extract (SBE) and captopril significantly reduced blood pressure and ACE I and II activity by 22%, 81%, and 76%, respectively, after 3, 5, and 7 days of germination. The treatment also led to reductions in protein, creatinine, uric acid, and urea levels by 3%, 38%, 42%, and 48%, respectively, along with a 66% increase in plasma NO concentrations. Conclusions: This study highlights the bioactive properties of barley extracts with different germination times, emphasizing their potential health benefits as a more effective alternative to conventional antihypertensive therapies. Full article

(This article belongs to the Special Issue Plants and Plant-Based Foods for Metabolic Disease Prevention)

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18 pages, 7658 KiB

Open AccessEditor’s ChoiceArticle

Comprehensive Blood Metabolome and Exposome Analysis, Annotation, and Interpretation in E-Waste Workers

by Zhiqiang Pang, Charles Viau, Julius N. Fobil, Niladri Basu and Jianguo Xia

Metabolites 2024, 14(12), 671; https://doi.org/10.3390/metabo14120671 - 2 Dec 2024

Cited by 1 | Viewed by 1312

Abstract

Background: Electronic and electrical waste (e-waste) production has emerged to be of global environmental public health concern. E-waste workers, who are frequently exposed to hazardous chemicals through occupational activities, face considerable health risks. Methods: To investigate the metabolic and exposomic changes in these [...] Read more.

Background: Electronic and electrical waste (e-waste) production has emerged to be of global environmental public health concern. E-waste workers, who are frequently exposed to hazardous chemicals through occupational activities, face considerable health risks. Methods: To investigate the metabolic and exposomic changes in these workers, we analyzed whole blood samples from 100 male e-waste workers and 49 controls from the GEOHealth II project (2017–2018 in Accra, Ghana) using LC-MS/MS. A specialized computational workflow was established for exposomics data analysis, incorporating two curated reference libraries for metabolome and exposome profiling. Two feature detection algorithms, asari and centWave, were applied. Results: In comparison to centWave, asari showed better sensitivity in detecting MS features, particularly at trace levels. Principal component analysis demonstrated distinct metabolic profiles between e-waste workers and controls, revealing significant disruptions in key metabolic pathways, including steroid hormone biosynthesis, drug metabolism, bile acid biosynthesis, vitamin metabolism, and prostaglandin biosynthesis. Correlation analyses linked metal exposures to alterations in hundreds to thousands of metabolic features. Functional enrichment analysis highlighted significant perturbations in pathways related to liver function, vitamin metabolism, linoleate metabolism, and dynorphin signaling, with the latter being observed for the first time in e-waste workers. Conclusions: This study provides new insights into the biological impact of prolonged metal exposure in e-waste workers. Full article

(This article belongs to the Special Issue Method Development in Metabolomics and Exposomics)

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16 pages, 3208 KiB

Open AccessEditor’s ChoiceArticle

Essential Oils from Papaver rhoeas and Their Metabolomic Profiling

by Valeria Cavalloro, Francesco Saverio Robustelli della Cuna, Alberto Malovini, Carla Villa, Cristina Sottani, Matteo Balestra, Francesco Bracco, Emanuela Martino and Simona Collina

Metabolites 2024, 14(12), 664; https://doi.org/10.3390/metabo14120664 - 1 Dec 2024

Cited by 1 | Viewed by 895

Abstract

Background/Objectives: Essential oils (EOs) have been exploited by humans for centuries, but many sources remain poorly investigated, mainly due to the low yields associated with conventional extraction. Recently, new techniques have been developed, like solvent-free microwave extraction (SFME), able to enhance efficiency [...] Read more.

Background/Objectives: Essential oils (EOs) have been exploited by humans for centuries, but many sources remain poorly investigated, mainly due to the low yields associated with conventional extraction. Recently, new techniques have been developed, like solvent-free microwave extraction (SFME), able to enhance efficiency and sustainability. The use of Papaver rhoeas L. in traditional medicine has led researchers to investigate non-volatile fractions, but there are little data available on EOs. Methods: In the present work, we prepared EOs from the petals and leaves of P. rhoeas by SFME. GC/MS analysis of EOs revealed the presence of 106 compounds belonging to 13 different classes. Isomers of the different alkenes were identified thanks to an alkylthiolation reaction. Results: The results highlighted a predominance of saturated and unsaturated hydrocarbons, alcohols, and esters that might suggest a specific relationship with pollinators. Each population has been compared using PCA, heatmap, and barplot tools, highlighting differences in terms of composition by both comparing leaves and flowers and hill and lowland samples. Furthermore, cantharidin, a metabolite usually produced by insects, was detected in the flowers, possible present for attractiveness purposes. Conclusions: These results could contribute to ensuring a better understanding of the pollination process and of the biological activities of EOs from P. rhoeas. Full article

(This article belongs to the Special Issue Secondary Metabolites and Their Activities: From the Identification to the Biological Investigation)

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13 pages, 2396 KiB

Open AccessEditor’s ChoiceArticle

Exploration of Freshness Identification Method for Refrigerated Vegetables Based on Metabolomics

by Zixuan Meng, Haichao Zhang, Jing Wang, Lianfeng Ai and Weijun Kang

Metabolites 2024, 14(12), 665; https://doi.org/10.3390/metabo14120665 - 1 Dec 2024

Cited by 2 | Viewed by 1169

Abstract

Background: The rapid development of refrigerated transportation technology for fresh vegetables has extended their shelf life. Some vegetables may appear undamaged on the surface, but their freshness may have decreased, often resulting in the phenomenon of passing off inferior vegetables as good. [...] Read more.

Background: The rapid development of refrigerated transportation technology for fresh vegetables has extended their shelf life. Some vegetables may appear undamaged on the surface, but their freshness may have decreased, often resulting in the phenomenon of passing off inferior vegetables as good. It is very important to establish a detection method for identifying and assessing the freshness of vegetables. Methods: Therefore, based on metabolomics methods, this study innovatively employed UHPLC-Q-Exactive Orbitrap MS and GC–MS techniques to investigate the metabolites in the refrigerated storage of four vegetables, namely chard (Beta vulgaris var. cicla L), lettuce (Lactuca sativa var. ramose Hort.), crown daisy (Glebionis coronaria (L.) Cass. ex Spach), and tomato (Solanum lycopersicum L.), exploring key biomarkers for assessing their freshness. UPLC-TQ MS was used for the quantitative analysis of key metabolites. Results: The results showed that arginine biosynthesis and the metabolism of alanine, aspartate, and glutamate are key pathways in vegetable metabolism. Four key metabolites were selected from chard, five from lettuce, three from crown daisy, and five from tomato. Conclusions: Comparing the content of substances such as alanine and arginine can help infer the freshness and nutritional value of the vegetables, providing important references for detecting spoilage, determining storage time, and improving transportation conditions. This research holds significant relevance for the vegetable transportation industry. Full article

(This article belongs to the Special Issue New Analytical Techniques and Applications of Metabolomics and Lipidomics)

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14 pages, 2796 KiB

Open AccessEditor’s ChoiceArticle

Metabolic Aging as an Increased Risk for Chronic Obstructive Pulmonary Disease

by Claire J. Guo, Suneeta Godbole, Wassim W. Labaki, Katherine A. Pratte, Jeffrey L. Curtis, Robert Paine, Eric Hoffman, Meilan Han, Jill Ohar, Christopher Cooper, Katerina J. Kechris, Dawn L. DeMeo and Russell P. Bowler

Metabolites 2024, 14(12), 647; https://doi.org/10.3390/metabo14120647 - 21 Nov 2024

Viewed by 1889

Abstract

Background/Objectives: Both aging and chronic obstructive pulmonary disease (COPD) are strongly associated with changes in the metabolome; however, it is unknown whether there are common aging/COPD metabolomic signatures and if accelerated aging is associated with COPD. Methods: Plasma from 5704 subjects from the [...] Read more.

Background/Objectives: Both aging and chronic obstructive pulmonary disease (COPD) are strongly associated with changes in the metabolome; however, it is unknown whether there are common aging/COPD metabolomic signatures and if accelerated aging is associated with COPD. Methods: Plasma from 5704 subjects from the Genetic Epidemiology of COPD study (COPDGene) and 2449 subjects from Subpopulations and intermediate outcome measures in COPD study (SPIROMICS) were profiled using the Metabolon global metabolomics platform (1013 annotated metabolites). Post-bronchodilator spirometry measures of airflow obstruction (forced expiratory volume at one second (FEV₁)/forced vital capacity (FVC) < 0.7) were used to define COPD. Elastic net regression was trained on never and former smokers with normal spirometry and no emphysema to create a metabolomic age score which was validated in SPIROMICS subjects. Results: Our metabolic age score was strongly associated with chronic age in the validation cohort (correlation coefficient = 0.8). COPD subjects with accelerated aging (>7 years difference between metabolic and actual age) had more severe disease compared with those who had decelerated aging (<−7 years difference between metabolic and actual age). COPD and aging metabolites were shared more than expected (p < 0.001), with amino acid and glutathione metabolism among pathways overrepresented. Conclusions: These findings suggest a common mechanism between aging and COPD and that COPD is associated with accelerated metabolic aging. Full article

(This article belongs to the Section Endocrinology and Clinical Metabolic Research)

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19 pages, 14796 KiB

Open AccessEditor’s ChoiceArticle

Effects of Ammonia Stress on Liver Tissue Structure, Enzyme Activities, and Metabolome of Juvenile Largemouth Bass Micropterus salmoides

by Decheng Pu, Zhengxi Wang, Jishu Zheng, Peiyuan Li, Xiuli Wei, Dongsheng Li, Lihong Gao, Lin Zhou and Yu Wang

Metabolites 2024, 14(12), 649; https://doi.org/10.3390/metabo14120649 - 21 Nov 2024

Cited by 1 | Viewed by 1278

Abstract

Background: Ammonia, a ubiquitous contaminant in aquatic ecosystems, poses multifaceted threats to fish species at elevated concentrations. Methods: In order to investigate the toxic effects of chronic ammonia stress on the liver of juvenile Micropterus salmoides, the present experiment was conducted to [...] Read more.

Background: Ammonia, a ubiquitous contaminant in aquatic ecosystems, poses multifaceted threats to fish species at elevated concentrations. Methods: In order to investigate the toxic effects of chronic ammonia stress on the liver of juvenile Micropterus salmoides, the present experiment was conducted to investigate the differences in changes in liver tissue structure, enzyme activities, and metabolomes after 28 days of ammonia exposure (0, 4, 8, and 16 mg/L). Results: The findings revealed that ammonia exposure induced significant oxidative stress in the liver, manifesting in decreased activities of antioxidant enzymes SOD and GSH-Px, elevated levels of GSH, GST, and MDA, and heightened activities of immune enzymes LZM, ALP, and ACP. An increase in ammonia concentration exacerbated liver tissue damage. Metabolome analysis further unveiled perturbations in liver metabolites of Micropterus salmoides exposed to ammonia, with Ala-His emerging as a potentially pivotal functional substance under chronic stress. Specifically, the 4 mg/L group responded to ammonia toxicity by augmenting GSH and L-Carnosine levels, the 8 mg/L group detoxified via upregulation of L-Glutamine, and the 16 mg/L group mitigated toxicity through the urea synthesis pathway. Conclusions: This research offers preliminary insights into the toxicological responses of Micropterus salmoides under chronic ammonia stress. It is suggested that the duration of ammonia concentration exceeding 4 mg/L in high-density aquaculture should not exceed 7 days. Full article

(This article belongs to the Section Environmental Metabolomics)

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21 pages, 6832 KiB

Open AccessEditor’s ChoiceArticle

Identification of Spatial Specific Lipid Metabolic Signatures in Long-Standing Diabetic Kidney Disease

by Yiran Zhang, Hai-Long Piao and Di Chen

Metabolites 2024, 14(11), 641; https://doi.org/10.3390/metabo14110641 - 20 Nov 2024

Cited by 2 | Viewed by 1430

Abstract

Background: Diabetic kidney disease (DKD) is a major complication of diabetes leading to kidney failure. Methods: This study investigates lipid metabolism profiles of long-standing DKD (LDKD, diabetes duration > 10 years) by integrative analysis of available single-cell RNA sequencing and spatial multi-omics data [...] Read more.

Background: Diabetic kidney disease (DKD) is a major complication of diabetes leading to kidney failure. Methods: This study investigates lipid metabolism profiles of long-standing DKD (LDKD, diabetes duration > 10 years) by integrative analysis of available single-cell RNA sequencing and spatial multi-omics data (focusing on spatial continuity samples) from the Kidney Precision Medicine Project. Results: Two injured cell types, an injured thick ascending limb (iTAL) and an injured proximal tubule (iPT), were identified and significantly elevated in LDKD samples. Both iTAL and iPT exhibit increased lipid metabolic and biosynthetic activities and decreased lipid and fatty acid oxidative processes compared to TAL/PT cells. Notably, compared to PT, iPT shows significant upregulation of specific injury and fibrosis-related genes, including FSHR and BMP7. Meanwhile, comparing iTAL to TAL, inflammatory-related genes such as ANXA3 and IGFBP2 are significantly upregulated. Furthermore, spatial metabolomics analysis reveals regionally distributed clusters in the kidney and notably differentially expressed lipid metabolites, such as triglycerides, glycerophospholipids, and sphingolipids, particularly pronounced in the inner medullary regions. Conclusions: These findings provide an integrative description of the lipid metabolism landscape in LDKD, highlighting injury-associated cellular processes and potential molecular mechanisms. Full article

(This article belongs to the Special Issue New Analytical Techniques and Applications of Metabolomics and Lipidomics)

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13 pages, 1635 KiB

Open AccessEditor’s ChoiceArticle

Modulation of Urea Transport Attenuates TLR2-Mediated Microglial Activation and Upregulates Microglial Metabolism In Vitro

by Najlaa A. Al-Thani, Dylan Zinck, Gavin S. Stewart and Derek A. Costello

Metabolites 2024, 14(11), 634; https://doi.org/10.3390/metabo14110634 - 17 Nov 2024

Cited by 4 | Viewed by 1505

Abstract

Background: Alzheimer’s disease (AD) is a neurodegenerative disorder traditionally characterised by the presence of amyloid beta (Aβ) plaques and neurofibrillary tau tangles in the brain. However, emerging research has highlighted additional metabolic hallmarks of AD pathology. These include the metabolic reprogramming of microglia [...] Read more.

Background: Alzheimer’s disease (AD) is a neurodegenerative disorder traditionally characterised by the presence of amyloid beta (Aβ) plaques and neurofibrillary tau tangles in the brain. However, emerging research has highlighted additional metabolic hallmarks of AD pathology. These include the metabolic reprogramming of microglia in favour of glycolysis over oxidative phosphorylation. This shift is attributed to an ‘M1′-like pro-inflammatory phenotype, which exacerbates neuroinflammation and contributes to neuronal damage. The urea cycle also presents as an altered metabolic pathway in AD, due to elevated urea levels and altered expression of urea cycle enzymes, metabolites, and transporters in the brain. However, to date, these changes remain largely unexplored. Methods: This study focuses on understanding the effects of extracellular urea and urea transporter-B (UT-B) inhibition on inflammatory changes in lipoteichoic acid (LTA)-stimulated BV2 microglia and on the viability of SH-SY5Y neuronal cells under oxidative stress and neurotoxic conditions. Results: In BV2 microglia, UT-B inhibition demonstrated a notable anti-inflammatory effect by reducing the formation of nitric oxide (NO) and the expression of tumour necrosis factor α (TNFα) and CCL2 in response to stimulation with the toll-like receptor (TLR)2 agonist, lipoteichoic acid (LTA). This was accompanied by a reduction in extracellular urea and upregulation of UT-B expression. The application of exogenous urea was also shown to mediate the inflammatory profile of BV2 cells in a similar manner but had only a modest impact on UT-B expression. While exposure to LTA alone did not alter the microglial metabolic profile, inhibition of UT-B upregulated the expression of genes associated with both glycolysis and fatty acid oxidation. Conversely, neither increased extracellular urea nor UT-B inhibition had a significant impact on cell viability or cytotoxicity in SH-SY5Y neurones exposed to oxidative stressors tert-butyl hydroperoxide (t-BHP) and 6-hydroxydopamine (6-OHDA). Conclusions: This study further highlights the involvement of urea transport in regulating the neuroinflammation associated with AD. Moreover, we reveal a novel role for UT-B in maintaining microglial metabolic homeostasis. Taken together, these findings contribute supporting evidence to the regulation of UT-B as a therapeutic target for intervention into neuroinflammatory and neurodegenerative disease. Full article

(This article belongs to the Section Cell Metabolism)

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21 pages, 3268 KiB

Open AccessEditor’s ChoiceArticle

Comparison of Free Flavonoids and the Polyphenol Content in the Bran of a Newly Developed Sorghum Variety and Two Commercially Available Sorghum Varieties

by Mariely Cristine Dos Santos, Naoki Tanaka, Shigemitsu Kasuga, Kazuhiro Tanabe, Chihiro Hayashi, Masahiro Mizuno and Yoshihiko Amano

Metabolites 2024, 14(11), 628; https://doi.org/10.3390/metabo14110628 - 15 Nov 2024

Cited by 1 | Viewed by 1101

Abstract

Background/Objectives: Sorghum bicolor is a source of many bioactive components, such as polyphenols. Those components are present mainly in its bran, often removed in industrial processes through decortication. In that sense, this work aimed to analyze the polyphenol content, especially free flavonoids, [...] Read more.

Background/Objectives: Sorghum bicolor is a source of many bioactive components, such as polyphenols. Those components are present mainly in its bran, often removed in industrial processes through decortication. In that sense, this work aimed to analyze the polyphenol content, especially free flavonoids, from the bran of a newly developed variety compared to other commercially available varieties. Methods: The samples were white sorghum TDN^® Sorgho, red sorghum Mini Sorgho, and the newly developed red sorghum RILN-156. First, decortication was conducted to obtain the bran samples, which were triturated and then sieved. The use of colorimetric methods allowed the general quantification of the polyphenolic components. First, the polyphenol content was extracted using 70% methanol. Then, the samples’ total phenolic content, total flavonoid content, total tannin content, total anthocyanin content, and antioxidant potential were determined. To analyze the different components and identify the free flavonoids, an untargeted metabolomics analysis (with liquid chromatography coupled with mass spectrometer (LC/MS) and capillary electrophoresis coupled with a mass spectrometer (CE/MS)) was performed. Results: The results have shown that apart from anthocyanin and tannin, the newly developed variety, RILN-156, presented the highest concentration of polyphenolic content, including a higher antioxidant capacity. The exploratory analysis identified 19 flavonoids within the samples, with galangin and daidzein being the most abundant ones. Conclusions: These results show a promising finding for using this newly developed sorghum variety (RILN-156) industrially and further investigating its health benefits. They also elucidate the differences between colored sorghum within themselves and with white sorghum varieties. Full article

(This article belongs to the Section Plant Metabolism)

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17 pages, 2798 KiB

Open AccessEditor’s ChoiceArticle

A Comprehensive LC–MS Metabolomics Assay for Quantitative Analysis of Serum and Plasma

by Lun Zhang, Jiamin Zheng, Mathew Johnson, Rupasri Mandal, Meryl Cruz, Miriam Martínez-Huélamo, Cristina Andres-Lacueva and David S. Wishart

Metabolites 2024, 14(11), 622; https://doi.org/10.3390/metabo14110622 - 14 Nov 2024

Cited by 4 | Viewed by 3876

Abstract

Background/Objectives: Targeted metabolomics is often criticized for the limited metabolite coverage that it offers. Indeed, most targeted assays developed or used by researchers measure fewer than 200 metabolites. In an effort to both expand the coverage and improve the accuracy of metabolite quantification [...] Read more.

Background/Objectives: Targeted metabolomics is often criticized for the limited metabolite coverage that it offers. Indeed, most targeted assays developed or used by researchers measure fewer than 200 metabolites. In an effort to both expand the coverage and improve the accuracy of metabolite quantification in targeted metabolomics, we decided to develop a comprehensive liquid chromatography–tandem mass spectrometry (LC–MS/MS) assay that could quantitatively measure more than 700 metabolites in serum or plasma. Methods: The developed assay makes use of chemical derivatization followed by reverse phase LC–MS/MS and/or direct flow injection MS (DFI–MS) in both positive and negative ionization modes to separate metabolites. Multiple reaction monitoring (MRM), in combination with isotopic standards and multi-point calibration curves, is used to detect and absolutely quantify the targeted metabolites. The assay has been adapted to a 96-well plate format to enable automated, high-throughput sample analysis. Results: The assay (called MEGA) is able to detect and quantify 721 metabolites in serum/plasma, covering 20 metabolite classes and many commonly used clinical biomarkers. The limits of detection were determined to range from 1.4 nM to 10 mM, recovery rates were from 80% to 120%, and quantitative precision was within 20%. LC–MS/MS metabolite concentrations of the NIST^® SRM^®1950 plasma standard were found to be within 15% of NMR quantified levels. The MEGA assay was further validated in a large dietary intervention study. Conclusions: The MEGA assay should make comprehensive quantitative metabolomics much more affordable, accessible, automatable, and applicable to large-scale clinical studies. Full article

(This article belongs to the Special Issue Method Development in Metabolomics and Exposomics)

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13 pages, 2892 KiB

Open AccessEditor’s ChoiceArticle

Analysis of In Vivo Plant Volatiles Using Active Sampling and TD-GC×GC-TOFMS

by Sheri A. Schmidt, Ewenet Yemane Mesfin, Chaminda De Silva Weeraddana, A. Paulina de la Mata, Alejandro C. Costamagna and James J. Harynuk

Metabolites 2024, 14(11), 623; https://doi.org/10.3390/metabo14110623 - 14 Nov 2024

Cited by 1 | Viewed by 1375

Abstract

Background: Plants constantly produce primary and secondary metabolites, and a significant fraction of these are volatile organic compounds (VOCs). Factors including the life stage of the plant, temperature, environment, and stress influence the abundance and types of VOCs emitted. The analysis of VOCs [...] Read more.

Background: Plants constantly produce primary and secondary metabolites, and a significant fraction of these are volatile organic compounds (VOCs). Factors including the life stage of the plant, temperature, environment, and stress influence the abundance and types of VOCs emitted. The analysis of VOCs released by plants during different stages or with different conditions provides insight into plant metabolism and stress responses. Collecting the VOC profiles of plants in vivo makes it possible to obtain a representative sample of the entire plant volatilome under controlled conditions with minimal invasiveness. In addition, in vivo sampling can also be used to compare the impacts of different environmental conditions or stressors on plants, i.e., the presence/absence of a pest or amount of nitrogen in soil. Methods: In this study, an in vivo plant sampling technique is introduced and validated using active sampling and thermal desorption (TD) tubes with comprehensive two-dimensional gas chromatography coupled to a time-of-flight mass spectrometer (TD-GC×GC-TOFMS). The purpose of this work is to highlight a novel technique to analyze headspace secondary plant metabolites with a minimal invasiveness. Results: It was concluded that in vivo active sampling onto TD tubes provides a wider global coverage of compounds and larger peak areas when compared to extraction by solid-phase microextraction (SPME). Additionally, the Horwitz ratio of active sampling onto TD tubes was 0.893, demonstrating this technique to be a reliable and reproducible method. Lastly, a variety of plants were sampled to assess the versatility of this technique across various plant species with different sizes and volatile profiles. Hundreds of compounds were measured with this analysis, including terpenes, aldehydes, ketones, terpenoids, and alcohols. Conclusions: This novel in vivo active sampling method provides an additional technique for extracting and analyzing volatile secondary plant metabolites. Full article

(This article belongs to the Special Issue Method Development in Metabolomics and Exposomics)

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12 pages, 9300 KiB

Open AccessEditor’s ChoiceArticle

Phenolic Metabolites Protocatechuic Acid and Vanillic Acid Improve Nitric Oxide Bioavailability via the Akt-eNOS Pathway in Response to TNF-α Induced Oxidative Stress and Inflammation in Endothelial Cells

by Joseph Festa, Aamir Hussain, Zakia Al-Hareth, Stephen J. Bailey, Harprit Singh and Mariasole Da Boit

Metabolites 2024, 14(11), 613; https://doi.org/10.3390/metabo14110613 - 11 Nov 2024

Cited by 2 | Viewed by 1252

Abstract

Background/Objectives: Reduced nitric oxide (NO) bioavailability secondary to excess-superoxide-driven oxidative stress is central to endothelial dysfunction. Previous studies suggest that phenolic metabolites may improve NO bioavailability, yet limited research is available in response to an inflammatory mediator. Therefore, we assessed the effects [...] Read more.

Background/Objectives: Reduced nitric oxide (NO) bioavailability secondary to excess-superoxide-driven oxidative stress is central to endothelial dysfunction. Previous studies suggest that phenolic metabolites may improve NO bioavailability, yet limited research is available in response to an inflammatory mediator. Therefore, we assessed the effects of cyanidin-3-glucoside (C3G) and its phenolic metabolites protocatechuic acid (PCA) and vanillic acid (VA) on NO bioavailability in a TNF-α induced inflammatory environment. Methods: Primary human umbilical vein endothelial cells (HUVECs) were supplemented with either C3G, PCA, or VA at 1 μM for 24 h before being stimulated with TNF-α 20 ng/mL for an additional 24 h. Measurements included cell viability, apoptosis, reactive oxygen species (ROS), nitrite concentrations, and endothelial nitric oxide synthase (eNOS) and Akt at the mRNA and protein level. Results: Phenolic metabolites did not increase the eNOS expression or nitrite levels in the unstimulated environment; rather, the metabolites mediated NO bioavailability in response to TNF-α induced oxidative stress, with increased viability, eNOS mRNA, phosphorylation, and nitrite levels. Conclusions: Phenolic metabolites, in the presence of TNF-α, can improve NO bioavailability at physiologically relevant concentrations via the Akt-eNOS pathway. This demonstrates that the induction of inflammation is a prerequisite for phenolic metabolites to promote protective properties in endothelial cells by activating the Akt-eNOS pathway. Full article

(This article belongs to the Section Cell Metabolism)

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14 pages, 1597 KiB

Open AccessEditor’s ChoiceArticle

Schinus terebinthifolia Raddi—Untargeted Metabolomics Approach to Investigate the Chemical Variation in Volatile and Non-Volatile Compounds

by Mara Junqueira Carneiro, Guilherme Perez Pinheiro, Elisa Ribeiro Miranda Antunes, Leandro Wang Hantao, Thomas Moritz and Alexandra Christine Helena Frankland Sawaya

Metabolites 2024, 14(11), 612; https://doi.org/10.3390/metabo14110612 - 11 Nov 2024

Viewed by 1317

Abstract

Context: Schinus terebinthifolia Raddi is used in Brazilian folk medicine due to the wound healing and antiseptic properties of its bark, and its fruit are used as a condiment. However, the aerial parts of this plant have been studied and present some bioactive [...] Read more.

Context: Schinus terebinthifolia Raddi is used in Brazilian folk medicine due to the wound healing and antiseptic properties of its bark, and its fruit are used as a condiment. However, the aerial parts of this plant have been studied and present some bioactive compounds as well. Objectives: The aim of this study was to investigate the variation in volatile and non-volatile composition of S. terebinthifolia leaves using untargeted metabolomics. Material and Methods: The leaves of four trees were collected over one year; ethanolic extracts were analyzed by UHPLC-MS and fresh leaves were analyzed by GC-MS using HS-SPME. The data were processed using online software. Results: The results suggest seasonality interfered little with the chemical composition of leaves. On the other hand, the sex of the plant clearly determined the chemical composition of both volatile and non-volatile compounds. Discussion and conclusions: Chemical variability between plants with male and female flowers is fundamental information for the standardized use of its leaves. Compounds with important biological activities were putatively identified, confirming the potential use of S. terebinthifolia leaves as a source of bioactive compounds, reducing waste and increasing economic gains for local farmers throughout the year. Full article

(This article belongs to the Special Issue Analysis of Specialized Metabolites in Natural Products)

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16 pages, 2250 KiB

Open AccessEditor’s ChoiceArticle

MS2Lipid: A Lipid Subclass Prediction Program Using Machine Learning and Curated Tandem Mass Spectral Data

by Nami Sakamoto, Takaki Oka, Yuki Matsuzawa, Kozo Nishida, Jayashankar Jayaprakash, Aya Hori, Makoto Arita and Hiroshi Tsugawa

Metabolites 2024, 14(11), 602; https://doi.org/10.3390/metabo14110602 - 7 Nov 2024

Cited by 2 | Viewed by 1699

Abstract

Background: Untargeted lipidomics using collision-induced dissociation-based tandem mass spectrometry (CID-MS/MS) is essential for biological and clinical applications. However, annotation confidence still relies on manual curation by analytical chemists, despite the development of various software tools for automatic spectral processing based on rule-based [...] Read more.

Background: Untargeted lipidomics using collision-induced dissociation-based tandem mass spectrometry (CID-MS/MS) is essential for biological and clinical applications. However, annotation confidence still relies on manual curation by analytical chemists, despite the development of various software tools for automatic spectral processing based on rule-based fragment annotations. Methods: In this study, we present a novel machine learning model, MS2Lipid, for the prediction of known lipid subclasses from MS/MS queries, providing an orthogonal approach to existing lipidomics software programs in determining the lipid subclass of ion features. We designed a new descriptor, MCH (mode of carbon and hydrogen), to increase the specificity of lipid subclass prediction in nominal mass resolution MS data. Results: The model, trained with 6760 and 6862 manually curated MS/MS spectra for the positive and negative ion modes, respectively, classified queries into one or several of 97 lipid subclasses, achieving an accuracy of 97.4% in the test set. The program was further validated using various datasets from different instruments and curators, with the average accuracy exceeding 87.2%. Using an integrated approach with molecular spectral networking, we demonstrated the utility of MS2Lipid by annotating microbiota-derived esterified bile acids, whose abundance was significantly increased in fecal samples of obese patients in a human cohort study. This suggests that the machine learning model provides an independent criterion for lipid subclass classification, enhancing the annotation of lipid metabolites within known lipid classes. Conclusions: MS2Lipid is a highly accurate machine learning model that enhances lipid subclass annotation from MS/MS data and provides an independent criterion. Full article

(This article belongs to the Special Issue Metabolomics and Bioinformatics Approaches to Studying Human Gut Microbiota-Derived Metabolites)

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13 pages, 2623 KiB

Open AccessEditor’s ChoiceArticle

Metabolomics of Papanicolaou Tests for the Discovery of Ovarian Cancer Biomarkers

by Samyukta Sah, Elisabeth M. Schwiebert, Samuel G. Moore, Ying Liu, David A. Gaul, Kristin L. M. Boylan, Amy P. N. Skubitz and Facundo M. Fernández

Metabolites 2024, 14(11), 600; https://doi.org/10.3390/metabo14110600 - 7 Nov 2024

Viewed by 1523

Abstract

Background: Ovarian cancer (OC) remains one of the most lethal cancers among women due to most cases going undiagnosed until later stages. The early detection and treatment of this malignancy provides the best prognosis, but the lack of an accurate and sensitive [...] Read more.

Background: Ovarian cancer (OC) remains one of the most lethal cancers among women due to most cases going undiagnosed until later stages. The early detection and treatment of this malignancy provides the best prognosis, but the lack of an accurate and sensitive screening tool combined with ambiguous symptoms hinders these diagnoses. In contrast, screening for cervical cancer via Papanicolaou (Pap) tests is a widespread practice that greatly reduces the cancer’s mortality rates. Interestingly, previous studies show evidence of OC cells in Pap tests, suggesting that proteins, and potentially lipids, shed from ovarian tumors end up in the cervix. The goal of this study is to evaluate the practicality of using Pap tests as biospecimens for OC-screening-related metabolomics. Methods: To evaluate the effectiveness of using residual Pap test samples as biospecimens for potential metabolomics work, 29 Pap test samples, collected from women over the age of 50 with normal cytology and no visible blood contamination, were first obtained from the University of Minnesota, with IRB approval. These samples were centrifuged to recover the cell pellets from the supernatants. The cell pellets underwent a biphasic extraction, followed by an RP-LC-MS analysis, while the supernatants underwent two separate extractions and analyses, including RP-LC-MS and HILIC-LC-MS. Non-targeted features were detected in the range of 220–1000 m/z to determine the sensitivity and scope of the various extraction and analytical workflows, as well as evaluating residual Pap test samples as viable metabolomics biospecimens. Results: The biphasic extraction and subsequent RP-LC-MS analysis of the isolated cell pellets from all 29 samples yielded informative, exploratory data, highlighting the potential of using residual Pap test samples as biospecimens for metabolomics, specifically lipidomics, studies. Each sample was analyzed in both the positive and negative ion mode, yielding the detection of 7318 in the positive ion mode and 3733 in the negative ion mode. Using multiple reference libraries, 22.85% and 36.19% of these features were annotated in the positive and negative ion mode, respectively. Among these detected features, 453 unique lipids, representative of 20 different lipid subclasses, were annotated in all 29 samples. Of the various lipid subclasses represented from the detected lipids, ceramides, triacylglycerols, hexosylceramides, and phosphatidylcholines contributed to over half (53.3%) of the detected lipids at 16.2%, 13.0%, 12.8%, and 11.3%, respectively. Conclusions: The detection of these 453 common lipids across all patients establishes a relative lipidome baseline for women over the age of 50 with normal cervical cytology. This exploratory study is the first investigation to utilize residual Pap test samples as biospecimens in a metabolomics/lipidomics workflow. Full article

(This article belongs to the Special Issue Method Development in Metabolomics and Exposomics)

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17 pages, 2954 KiB

Open AccessEditor’s ChoiceArticle

Integrated Metabolomic and Transcriptomic Analysis of Nitraria Berries Indicate the Role of Flavonoids in Adaptation to High Altitude

by Qing Zhao, Jie Zhang, Yanhong Li, Zufan Yang, Qian Wang and Qiangqiang Jia

Metabolites 2024, 14(11), 591; https://doi.org/10.3390/metabo14110591 - 1 Nov 2024

Cited by 2 | Viewed by 1276

Abstract

Background: Plants of Nitraria, belonging to the Zygophyllaceae family, are not only widely distributed at an altitude of about 1000 m but also at an altitude of about 3000 m, which is a rare phenomenon. However, little is known about the effect [...] Read more.

Background: Plants of Nitraria, belonging to the Zygophyllaceae family, are not only widely distributed at an altitude of about 1000 m but also at an altitude of about 3000 m, which is a rare phenomenon. However, little is known about the effect of altitude on the accumulation of metabolites in plants of Nitraria. Furthermore, the mechanism of the high–altitude adaptation of Nitraria has yet to be fully elucidated. Methods: In this study, metabolomics and transcriptomics were used to investigate the differential accumulation of metabolites of Nitraria berries and the regulatory mechanisms in different altitudes. Results: As a result, the biosynthesis of flavonoids is the most significant metabolic pathway in the process of adaptation to high altitude, and 5 Cyanidins, 1 Pelargonidin, 3 Petunidins, 1 Peonidin, and 4 Delphinidins are highly accumulated in high–altitude Nitraria. The results of transcriptomics showed that the structural genes C4H (2), F3H, 4CL (2), DFR (2), UFGT (2), and FLS (2) were highly expressed in high–altitude Nitraria. A network metabolism map of flavonoids was constructed, and the accumulation of differential metabolites and the expression of structural genes were analyzed for correlation. Conclusions: In summary, this study preliminarily offers a new understanding of metabolic differences and regulation mechanisms in plants of Nitraria from different altitudes. Full article

(This article belongs to the Section Plant Metabolism)

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15 pages, 1886 KiB

Open AccessEditor’s ChoiceArticle

Predicting the Pathway Involvement of All Pathway and Associated Compound Entries Defined in the Kyoto Encyclopedia of Genes and Genomes

by Erik D. Huckvale and Hunter N. B. Moseley

Metabolites 2024, 14(11), 582; https://doi.org/10.3390/metabo14110582 - 27 Oct 2024

Cited by 2 | Viewed by 1100

Abstract

Background/Objectives: Predicting the biochemical pathway involvement of a compound could facilitate the interpretation of biological and biomedical research. Prior prediction approaches have largely focused on metabolism, training machine learning models to solely predict based on metabolic pathways. However, there are many other [...] Read more.

Background/Objectives: Predicting the biochemical pathway involvement of a compound could facilitate the interpretation of biological and biomedical research. Prior prediction approaches have largely focused on metabolism, training machine learning models to solely predict based on metabolic pathways. However, there are many other types of pathways in cells and organisms that are of interest to biologists. Methods: While several publications have made use of the metabolites and metabolic pathways available in the Kyoto Encyclopedia of Genes and Genomes (KEGG), we downloaded all the compound entries with pathway annotations available in the KEGG. From these data, we constructed a dataset where each entry contained features representing compounds combined with features representing pathways, followed by a binary label indicating whether the given compound is associated with the given pathway. We trained multi-layer perceptron binary classifiers on variations of this dataset. Results: The models trained on 6485 KEGG compounds and 502 pathways scored an overall mean Matthews correlation coefficient (MCC) performance of 0.847, a median MCC of 0.848, and a standard deviation of 0.0098. Conclusions: This performance on all 502 KEGG pathways represents a roughly 6% improvement over the performance of models trained on only the 184 KEGG metabolic pathways, which had a mean MCC of 0.800 and a standard deviation of 0.021. These results demonstrate the capability to effectively predict biochemical pathways in general, in addition to those specifically related to metabolism. Moreover, the improvement in the performance demonstrates additional transfer learning with the inclusion of non-metabolic pathways. Full article

(This article belongs to the Special Issue Machine Learning Applications in Metabolomics Analysis)

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17 pages, 7552 KiB

Open AccessEditor’s ChoiceArticle

Metabolomics Reveal Key Metabolic Pathway Responses to Anxiety State Regulated by Serotonin in Portunus trituberculatus

by Wei Zhai, Yuanyuan Fu, Lei Liu, Xinlian Huang and Sixiang Wang

Metabolites 2024, 14(10), 568; https://doi.org/10.3390/metabo14100568 - 21 Oct 2024

Cited by 1 | Viewed by 1831

Abstract

Background: Anxiety refers to the pathological persistence and intensification of emotional responses to danger, affecting health from psychological and physical aspects. Serotonin is an important neurotransmitter involved in the onset of anxiety. Methods and Results: To explore the biological changes in the formation [...] Read more.

Background: Anxiety refers to the pathological persistence and intensification of emotional responses to danger, affecting health from psychological and physical aspects. Serotonin is an important neurotransmitter involved in the onset of anxiety. Methods and Results: To explore the biological changes in the formation of anxiety in crustaceans under the regulation of serotonin, we applied the open field-like test method for assessing anxiety states of larval Portunus trituberculatus, a highly aggressive crustacean species with a more simple neural structure compared with rodents and mammals. Compared with the control group, serotonin treatment resulted in a significant decrease in the time spent by the larvae in the central zone, suggesting anxiety-like behavior. Clonazepam treatment reversed this result and provided further evidence that the behavior of larval P. trituberculatus displayed anxiety. Moreover, a non-targeted metabolomic analysis found a significant alteration in the metabolites involved in tryptophan metabolism pathways associated with anxiety, including L-kynurenine, N-acetyl serotonin, and serotonin. These metabolites are involved in the serotonin pathway, the kynurenine pathway, and other pathways that affect anxiety through tryptophan metabolism. There were no significant differences in tryptophan metabolism levels between the control and clonazepam treatment groups. Conclusions: Our results demonstrate the possible existence of anxiety-like behavior in the larvae of P. trituberculatus from two perspectives. Being a species with a simpler neural structure than that of mammals, the larvae of P. trituberculatus offer a convenient model for studying the mechanisms of anxiety in crustaceans. Full article

(This article belongs to the Special Issue Meeting the Challenge of Metabolomics Analysis by Using Multidimensional Gas Chromatography with Mass Spectrometry)

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