Metabolites

15 pages, 1353 KiB

Open AccessEditor’s ChoiceArticle

Amino Acid Profile Alterations in Phenylketonuria: Implications for Clinical Practice

by Eliza Matuszewska, Joanna Matysiak, Łukasz Kałużny, Dariusz Walkowiak, Szymon Plewa, Monika Duś-Żuchowska, Natalia Rzetecka, Małgorzata Jamka, Agnieszka Klupczyńska-Gabryszak, Marcin Piorunek, Jan Matysiak and Jarosław Walkowiak

Metabolites 2024, 14(7), 397; https://doi.org/10.3390/metabo14070397 - 21 Jul 2024

Cited by 3 | Viewed by 1963

Abstract

Patients with phenylketonuria (PKU) must restrict their intake of phenylalanine, which can also affect the levels of other essential and non-essential amino acids due to inadequate supply. Therefore, our objective was to assess amino acids in serum samples from 20 PKU patients and [...] Read more.

Patients with phenylketonuria (PKU) must restrict their intake of phenylalanine, which can also affect the levels of other essential and non-essential amino acids due to inadequate supply. Therefore, our objective was to assess amino acids in serum samples from 20 PKU patients and compare them with results from 51 healthy subjects. A sample analysis was conducted using liquid chromatography–tandem mass spectrometry. We obtained levels of 28 substances, including amino acids, biogenic amines, carnitine, and acetylcarnitine. Kynurenine (p = 0.000001), tyrosine (p = 0.0002), asparagine (p = 0.001), proline (p = 0.012), and the kynurenine/tryptophan ratio (p < 0.000001) were identified as features that differed between the studied groups, being significantly lower in patients with PKU. Glycine (p = 0.000012), putrescine (p = 0.0055), asymmetric dimethylarginine (p = 0.01), creatinine (p = 0.035) levels, as well as the total level of glucogenic amino acids (p = 0.0018), and the ratios of putrescine/ornithine (p = 0.003) and citrulline/ornithine (p = 0.0043) were significantly higher in the PKU group. In conclusion, the amino acid profiles in patients with PKU differ significantly from those in healthy peers, with potential clinical implications. These findings confirm the importance of metabolic testing in clinical practice and highlight the necessity for adequate dietary monitoring and adjustment. Full article

(This article belongs to the Special Issue New Advancements and Challenges in Clinical Metabolomics for Inborn Errors of Metabolism and Rare Diseases)

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38 pages, 10637 KiB

Open AccessEditor’s ChoiceArticle

A Multiomics, Molecular Atlas of Breast Cancer Survivors

by Brent A. Bauer, Caleb M. Schmidt, Kathryn J. Ruddy, Janet E. Olson, Cem Meydan, Julian C. Schmidt, Sheena Y. Smith, Fergus J. Couch, John C. Earls, Nathan D. Price, Joel T. Dudley, Christopher E. Mason, Bodi Zhang, Stephen M. Phipps and Michael A. Schmidt

Metabolites 2024, 14(7), 396; https://doi.org/10.3390/metabo14070396 - 20 Jul 2024

Viewed by 2219

Abstract

Breast cancer imposes a significant burden globally. While the survival rate is steadily improving, much remains to be elucidated. This observational, single time point, multiomic study utilizing genomics, proteomics, targeted and untargeted metabolomics, and metagenomics in a breast cancer survivor (BCS) and age-matched [...] Read more.

Breast cancer imposes a significant burden globally. While the survival rate is steadily improving, much remains to be elucidated. This observational, single time point, multiomic study utilizing genomics, proteomics, targeted and untargeted metabolomics, and metagenomics in a breast cancer survivor (BCS) and age-matched healthy control cohort (N = 100) provides deep molecular phenotyping of breast cancer survivors. In this study, the BCS cohort had significantly higher polygenic risk scores for breast cancer than the control group. Carnitine and hexanoyl carnitine were significantly different. Several bile acid and fatty acid metabolites were significantly dissimilar, most notably the Omega-3 Index (O3I) (significantly lower in BCS). Proteomic and metagenomic analyses identified group and pathway differences, which warrant further investigation. The database built from this study contributes a wealth of data on breast cancer survivorship where there has been a paucity, affording the ability to identify patterns and novel insights that can drive new hypotheses and inform future research. Expansion of this database in the treatment-naïve, newly diagnosed, controlling for treatment confounders, and through the disease progression, can be leveraged to profile and contextualize breast cancer and breast cancer survivorship, potentially leading to the development of new strategies to combat this disease and improve the quality of life for its victims. Full article

(This article belongs to the Special Issue Cancer Metabolomics 2024)

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14 pages, 3096 KiB

Open AccessEditor’s ChoiceArticle

Tracking Metabolite Variations during the Degradation of Vegetables in Rice Bran Bed with Intact-State Nuclear Magnetic Resonance Spectroscopy

by Kengo Ito, Ryusei Yamamoto and Yasuyo Sekiyama

Metabolites 2024, 14(7), 391; https://doi.org/10.3390/metabo14070391 - 19 Jul 2024

Viewed by 1450

Abstract

Fermentation—a process of compound degradation by microorganisms—is a traditional food processing method utilized worldwide for the long-term preservation of fresh foods. In recent years, fermented foods have gained attention as health foods. Fermentation increases the nutritional value of ingredients, producing complex flavors and [...] Read more.

Fermentation—a process of compound degradation by microorganisms—is a traditional food processing method utilized worldwide for the long-term preservation of fresh foods. In recent years, fermented foods have gained attention as health foods. Fermentation increases the nutritional value of ingredients, producing complex flavors and aromas. To identify unknown components in fermented foods, it is necessary to analyze compounds and conditions nondestructively and comprehensively. We performed intact-state nuclear magnetic resonance (NMR) spectroscopy using intermolecular single quantum coherence (iSQC) to detect the degradation of vegetables directly and nondestructively. We used two types of vegetables and a rice bran bed (nukazuke), which is used for traditional vegetable fermentation in Japan. Major metabolites such as saccharides, organic acids, and amino acids were identified in iSQC-sliced spectra. Comparing NMR signal intensities during degradation revealed the transition of metabolites characteristic of lactic acid fermentation. A pathway-based network analysis showed pathways involved in amino acid metabolism and lactic acid fermentation. Our analytical approach with intact-state NMR spectroscopy using iSQC demonstrated that it may be effective in other experimental systems, allowing for the evaluation of phenomena that have been conventionally overlooked in their true state. Full article

(This article belongs to the Special Issue Emerging Applications of Metabolomics in Fermented Food)

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49 pages, 2291 KiB

Open AccessEditor’s ChoiceReview

The Pleiotropic Effects of Lipid-Modifying Interventions: Exploring Traditional and Emerging Hypolipidemic Therapies

by Dimitris Kounatidis, Nikolaos Tentolouris, Natalia G. Vallianou, Iordanis Mourouzis, Irene Karampela, Theodora Stratigou, Eleni Rebelos, Marina Kouveletsou, Vasileios Stamatopoulos, Eleni Tsaroucha and Maria Dalamaga

Metabolites 2024, 14(7), 388; https://doi.org/10.3390/metabo14070388 - 17 Jul 2024

Cited by 5 | Viewed by 3020

Abstract

Atherosclerotic cardiovascular disease poses a significant global health issue, with dyslipidemia standing out as a major risk factor. In recent decades, lipid-lowering therapies have evolved significantly, with statins emerging as the cornerstone treatment. These interventions play a crucial role in both primary and [...] Read more.

Atherosclerotic cardiovascular disease poses a significant global health issue, with dyslipidemia standing out as a major risk factor. In recent decades, lipid-lowering therapies have evolved significantly, with statins emerging as the cornerstone treatment. These interventions play a crucial role in both primary and secondary prevention by effectively reducing cardiovascular risk through lipid profile enhancements. Beyond their primary lipid-lowering effects, extensive research indicates that these therapies exhibit pleiotropic actions, offering additional health benefits. These include anti-inflammatory properties, improvements in vascular health and glucose metabolism, and potential implications in cancer management. While statins and ezetimibe have been extensively studied, newer lipid-lowering agents also demonstrate similar pleiotropic effects, even in the absence of direct cardiovascular benefits. This narrative review explores the diverse pleiotropic properties of lipid-modifying therapies, emphasizing their non-lipid effects that contribute to reducing cardiovascular burden and exploring emerging benefits for non-cardiovascular conditions. Mechanistic insights into these actions are discussed alongside their potential therapeutic implications Full article

(This article belongs to the Special Issue Lipid Biomarkers and Cardiometabolic Diseases)

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13 pages, 1838 KiB

Open AccessEditor’s ChoiceArticle

Alteration of Fecal Microbiota, Fecal Metabolites, and Serum Metabolites in Dairy Cows with Pre-Retained Placenta

by Tao Zhou, Zhenlong Du, Zhengzhong Luo, Xiaoping Li, Dan Wu, Yixin Huang, Kang Yong, Xueping Yao, Liuhong Shen, Shumin Yu, Zuoting Yan and Suizhong Cao

Metabolites 2024, 14(7), 386; https://doi.org/10.3390/metabo14070386 - 15 Jul 2024

Viewed by 1672

Abstract

Retained placenta (RP) affects lactation and fertility in dairy cows and causes economic losses to the dairy industry. Therefore, screening for early warning of this disease is important. This study used multi omics techniques to reveal the metabolic differences of dairy cows before [...] Read more.

Retained placenta (RP) affects lactation and fertility in dairy cows and causes economic losses to the dairy industry. Therefore, screening for early warning of this disease is important. This study used multi omics techniques to reveal the metabolic differences of dairy cows before RP onset and to find potential warning markers. Fecal samples and serum samples of 90 healthy Holstein cows were collected 7 days pre-calving; 10 healthy and 10 RP cows were enrolled according to normal expulsion of fetal membranes after calving. Fecal samples were subjected to 16S rRNA sequencing and untargeted metabolomics analysis, while plasma was analyzed using targeted metabolomics. Pathogenic bacteria levels increased in the intestines of cows with RP compared to those in healthy cows. Lipid metabolites constituted the largest proportion of differential metabolites between feces and plasma. Six potential warning markers for RP in cows were identified, including two fecal microbiomics markers (Oscillospiraceae UCG-005 and Escherichia-Shigella), one fecal untargeted metabolomics marker (N-acetylmuramic acid), and three plasma targeted metabolomics markers (glycylcholic acid-3 sulfate, 7-ketolithocholic acid, and 12-ketolithocholic acid). These biomarkers can predict RP occurrence in the early perinatal period. These results lay a theoretical foundation for early nutritional intervention and pathogenesis research in dairy cows. Full article

(This article belongs to the Special Issue Metabolites in Ruminant Health)

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39 pages, 1836 KiB

Open AccessEditor’s ChoiceReview

Challenges of Spatially Resolved Metabolism in Cancer Research

by Andrew N. Lane, Richard M. Higashi and Teresa W-M. Fan

Metabolites 2024, 14(7), 383; https://doi.org/10.3390/metabo14070383 - 11 Jul 2024

Cited by 1 | Viewed by 1896

Abstract

Stable isotope-resolved metabolomics comprises a critical set of technologies that can be applied to a wide variety of systems, from isolated cells to whole organisms, to define metabolic pathway usage and responses to perturbations such as drugs or mutations, as well as providing [...] Read more.

Stable isotope-resolved metabolomics comprises a critical set of technologies that can be applied to a wide variety of systems, from isolated cells to whole organisms, to define metabolic pathway usage and responses to perturbations such as drugs or mutations, as well as providing the basis for flux analysis. As the diversity of stable isotope-enriched compounds is very high, and with newer approaches to multiplexing, the coverage of metabolism is now very extensive. However, as the complexity of the model increases, including more kinds of interacting cell types and interorgan communication, the analytical complexity also increases. Further, as studies move further into spatially resolved biology, new technical problems have to be overcome owing to the small number of analytes present in the confines of a single cell or cell compartment. Here, we review the overall goals and solutions made possible by stable isotope tracing and their applications to models of increasing complexity. Finally, we discuss progress and outstanding difficulties in high-resolution spatially resolved tracer-based metabolic studies. Full article

(This article belongs to the Special Issue Isotope-Guided Analytical Strategies for Assessing Metabolic Networks in Cancer)

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14 pages, 7624 KiB

Open AccessEditor’s ChoiceArticle

Non-Alcoholic Fatty Liver Disease Induced by Feeding Medium-Chain Fatty Acids Upregulates Cholesterol and Lipid Homeostatic Genes in Skeletal Muscle of Neonatal Pigs

by Samuel D. Gerrard, Fernando H. Biase, Joseph A. Yonke, Ravi Yadav, Anthony J. Shafron, Nishanth E. Sunny, David E. Gerrard and Samer W. El-Kadi

Metabolites 2024, 14(7), 384; https://doi.org/10.3390/metabo14070384 - 11 Jul 2024

Cited by 1 | Viewed by 1663

Abstract

Non-alcoholic fatty liver disease (NAFLD) is a range of disorders characterized by lipid accumulation in hepatocytes. Although this spectrum of disorders is associated with adult obesity, recent evidence suggests that this condition could also occur independently of obesity, even in children. Previously, we [...] Read more.

Non-alcoholic fatty liver disease (NAFLD) is a range of disorders characterized by lipid accumulation in hepatocytes. Although this spectrum of disorders is associated with adult obesity, recent evidence suggests that this condition could also occur independently of obesity, even in children. Previously, we reported that pigs fed a formula containing medium-chain fatty acids (MCFAs) developed hepatic steatosis and weighed less than those fed an isocaloric formula containing long-chain fatty acids (LCFAs). Our objective was to determine the association between NAFLD and the skeletal muscle transcriptome in response to energy and lipid intake. Neonatal pigs were fed one of three formulas: a control formula (CONT, n = 6) or one of two isocaloric high-energy formulas containing either long (LCFA, n = 6) or medium (MCFA, n = 6) chain fatty acids. Pigs were fed for 22 d, and tissues were collected. Body weight at 20 and 22 d was greater for LCFA-fed pigs than their CONT or MCFA counterparts (p < 0.005). Longissimus dorsi weight was greater for LCFA compared with MCFA, while CONT was intermediate (p < 0.05). Lean gain and protein deposition were greater for LCFA than for CONT and MCFA groups (p < 0.01). Transcriptomic analysis revealed 36 differentially expressed genes (DEGs) between MCFA and LCFA, 53 DEGs between MCFA and CONT, and 52 DEGs between LCFA and CONT (FDR < 0.2). Feeding formula high in MCFAs resulted in lower body and muscle weights. Transcriptomics data suggest that the reduction in growth was associated with a disruption in cholesterol metabolism in skeletal muscles. Full article

(This article belongs to the Special Issue Unlocking the Mysteries of Muscle Metabolism in the Animal Sciences)

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22 pages, 4088 KiB

Open AccessEditor’s ChoiceArticle

Metabolomics and Multi-Omics Determination of Potential Plasma Biomarkers in PRV-1-Infected Atlantic Salmon

by Lada Ivanova, Oscar D. Rangel-Huerta, Haitham Tartor, Maria K. Dahle, Silvio Uhlig and Christiane Kruse Fæste

Metabolites 2024, 14(7), 375; https://doi.org/10.3390/metabo14070375 - 2 Jul 2024

Cited by 2 | Viewed by 2545

Abstract

Metabolomic analysis has been explored to search for disease biomarkers in humans for some time. The application to animal species, including fish, however, is still at the beginning. In the present study, we have used targeted and untargeted metabolomics to identify metabolites in [...] Read more.

Metabolomic analysis has been explored to search for disease biomarkers in humans for some time. The application to animal species, including fish, however, is still at the beginning. In the present study, we have used targeted and untargeted metabolomics to identify metabolites in the plasma of Atlantic salmon (Salmo salar) challenged with Piscine orthoreovirus (PRV-1), aiming to find metabolites associated with the progression of PRV-1 infection into heart and skeletal muscle inflammation (HSMI). The metabolomes of control and PRV-1-infected salmon were compared at three time points during disease development by employing different biostatistical approaches. Targeted metabolomics resulted in the determination of affected metabolites and metabolic pathways, revealing a substantial impact of PRV-1 infection on lipid homeostasis, especially on several (lyso)phosphatidylcholines, ceramides, and triglycerides. Untargeted metabolomics showed a clear separation of the treatment groups at later study time points, mainly due to effects on lipid metabolism pathways. In a subsequent multi-omics approach, we combined both metabolomics datasets with previously reported proteomics data generated from the same salmon plasma samples. Data processing with DIABLO software resulted in the identification of significant metabolites and proteins that were representative of the HSMI development in the salmon. Full article

(This article belongs to the Special Issue Proteomic and Metabolomic Analyses of Fisheries and Aquaculture)

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19 pages, 1928 KiB

Open AccessEditor’s ChoiceArticle

Automated Liquid Handling Extraction and Rapid Quantification of Underivatized Amino Acids and Tryptophan Metabolites from Human Serum and Plasma Using Dual-Column U(H)PLC-MRM-MS and Its Application to Prostate Cancer Study

by Tobias Kipura, Madlen Hotze, Alexa Hofer, Anna-Sophia Egger, Lea E. Timpen, Christiane A. Opitz, Paul A. Townsend, Lee A. Gethings, Kathrin Thedieck and Marcel Kwiatkowski

Metabolites 2024, 14(7), 370; https://doi.org/10.3390/metabo14070370 - 30 Jun 2024

Cited by 4 | Viewed by 2335

Abstract

Amino acids (AAs) and their metabolites are important building blocks, energy sources, and signaling molecules associated with various pathological phenotypes. The quantification of AA and tryptophan (TRP) metabolites in human serum and plasma is therefore of great diagnostic interest. Therefore, robust, reproducible sample [...] Read more.

Amino acids (AAs) and their metabolites are important building blocks, energy sources, and signaling molecules associated with various pathological phenotypes. The quantification of AA and tryptophan (TRP) metabolites in human serum and plasma is therefore of great diagnostic interest. Therefore, robust, reproducible sample extraction and processing workflows as well as rapid, sensitive absolute quantification are required to identify candidate biomarkers and to improve screening methods. We developed a validated semi-automated robotic liquid extraction and processing workflow and a rapid method for absolute quantification of 20 free, underivatized AAs and six TRP metabolites using dual-column U(H)PLC-MRM-MS. The extraction and sample preparation workflow in a 96-well plate was optimized for robust, reproducible high sample throughput allowing for transfer of samples to the U(H)PLC autosampler directly without additional cleanup steps. The U(H)PLC-MRM-MS method, using a mixed-mode reversed-phase anion exchange column with formic acid and a high-strength silica reversed-phase column with difluoro-acetic acid as mobile phase additive, provided absolute quantification with nanomolar lower limits of quantification within 7.9 min. The semi-automated extraction workflow and dual-column U(H)PLC-MRM-MS method was applied to a human prostate cancer study and was shown to discriminate between treatment regimens and to identify metabolites responsible for discriminating between healthy controls and patients on active surveillance. Full article

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

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14 pages, 3930 KiB

Open AccessEditor’s ChoiceArticle

Investigation of Rhizopus oligosporus Metabolites in Fermented Wheat Bran and Its Bio Function in Alleviating Colitis in Mice Model

by Afifah Zahra Agista, Yu-Shan Chien, Takuya Koseki, Hazuki Nagaoka, Takuto Ohnuma, Yusuke Ohsaki, Chiu-Li Yeh, Suh-Ching Yang, Ardiansyah, Slamet Budijanto, Michio Komai and Hitoshi Shirakawa

Metabolites 2024, 14(7), 359; https://doi.org/10.3390/metabo14070359 - 26 Jun 2024

Cited by 1 | Viewed by 2846

Abstract

Wheat bran (WB) is a low-value by-product of the wheat milling industry. Solid-state fermentation with Rhizopus oligosporus is performed to improve WB’s nutritional quality (RH). Twenty-five mice (11-week-old C57BL/6N male mice) were divided into three groups. The first group was fed a control [...] Read more.

Wheat bran (WB) is a low-value by-product of the wheat milling industry. Solid-state fermentation with Rhizopus oligosporus is performed to improve WB’s nutritional quality (RH). Twenty-five mice (11-week-old C57BL/6N male mice) were divided into three groups. The first group was fed a control diet (n = 8), the second group a 10% WB-supplemented diet (n = 8), and the last group had a 10% RH-supplemented diet (n = 9). The diet treatment was administered for 4 days before dextran sodium sulfate (DSS, 3% in drinking water) was administered for 9 days. RH supplementation prevented bodyweight loss and reduced the disease activity index in mice. An increase in the level of SCFAs in mouse intestines was detected post-RH supplementation, suggesting that SCFAs might have contributed to its anti-colitis effect. Metabolome analysis was conducted to explore other bioactive compounds in RH. R. oligosporus fermentation significantly increased the amounts of ergothioneine, arginine, branched-chain amino acids, and adenosine in wheat bran. All of these compounds are known to have antioxidant and anti-inflammatory capacities. These bioactive compounds might also have contributed to the RH’s ability to ameliorate DSS-induced colitis. Full article

(This article belongs to the Special Issue Emerging Applications of Metabolomics in Fermented Food)

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31 pages, 6428 KiB

Open AccessEditor’s ChoiceArticle

Changes in Plasma Free Amino Acid Profile in Endurance Athletes over a 9-Month Training Cycle

by Krzysztof Kusy, Monika Ciekot-Sołtysiak, Jan Matysiak, Agnieszka Klupczyńska-Gabryszak, Szymon Plewa, Ewa Anna Zarębska, Zenon J. Kokot, Paweł Dereziński and Jacek Zieliński

Metabolites 2024, 14(7), 353; https://doi.org/10.3390/metabo14070353 - 23 Jun 2024

Cited by 4 | Viewed by 1731

Abstract

We aimed to evaluate long-term changes in proteinogenic and non-proteinogenic plasma free amino acids (PFAA). Eleven male endurance triathletes participated in a 9-month study. Blood was collected at rest, immediately after exhaustive exercise, and during 30-min recovery, in four consecutive training phases: transition, [...] Read more.

We aimed to evaluate long-term changes in proteinogenic and non-proteinogenic plasma free amino acids (PFAA). Eleven male endurance triathletes participated in a 9-month study. Blood was collected at rest, immediately after exhaustive exercise, and during 30-min recovery, in four consecutive training phases: transition, general, specific, and competition. Twenty proteinogenic and 22 non-proteinogenic PFAAs were assayed using the LC-ESI-MS/MS technique. The structured training modified the patterns of exercise-induced PFAA response, with the competition phase being the most distinct from the others. Branched-chain amino acids (p = 0.002; η² = 0.216), phenylalanine (p = 0.015; η² = 0.153), methionine (p = 0.002; η² = 0.206), and lysine (p = 0.006; η² = 0.196) declined more rapidly between rest and exhaustion in the competition phase. Glutamine (p = 0.008; η² = 0.255), glutamate (p = 0.006; η² = 0.265), tyrosine (p = 0.001; η² = 0.195), cystine (p = 0.042; η² = 0.183), and serine (p < 0.001; η² = 0.346) levels were reduced in the competition phase. Arginine (p = 0.046; η² = 0.138) and aspartate (p = 0.011; η² = 0.171) levels were highest during exercise in the transition phase. During the competition phase, α-aminoadipic acid (p = 0.023; η² = 0.145), β-aminoisobutyric acid (p = 0.007; η² = 0.167), β-alanine (p < 0.001; η² = 0.473), and sarcosine (p = 0.017; η² = 0.150) levels increased, whereas phosphoethanolamine (p = 0.037; η² = 0.189) and taurine (p = 0.008; η² = 0.251) concentrations decreased. Overtraining indicators were not elevated. The altered PFAA profile suggests adaptations within energy metabolic pathways such as the tricarboxylic acid cycle, oxidative phosphorylation, ammonia neutralization, the purine nucleotide cycle, and buffering of intracellular H⁺ ions. The changes seem to reflect normal adaptations. Full article

(This article belongs to the Special Issue Metabolomic Advances in Promoting Exercise-Induced Metabolic Changes)

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17 pages, 3018 KiB

Open AccessEditor’s ChoiceArticle

Disturbances in Muscle Energy Metabolism in Patients with Amyotrophic Lateral Sclerosis

by Petra Parvanovova, Petra Hnilicova, Martin Kolisek, Zuzana Tatarkova, Erika Halasova, Egon Kurca, Simona Holubcikova, Monika Turcanova Koprusakova and Eva Baranovicova

Metabolites 2024, 14(7), 356; https://doi.org/10.3390/metabo14070356 - 23 Jun 2024

Cited by 2 | Viewed by 2049

Abstract

Amyotrophic lateral sclerosis (ALS) is a fatal neuromuscular disease type of motor neuron disorder characterized by degeneration of the upper and lower motor neurons resulting in dysfunction of the somatic muscles of the body. The ALS condition is manifested in progressive skeletal muscle [...] Read more.

Amyotrophic lateral sclerosis (ALS) is a fatal neuromuscular disease type of motor neuron disorder characterized by degeneration of the upper and lower motor neurons resulting in dysfunction of the somatic muscles of the body. The ALS condition is manifested in progressive skeletal muscle atrophy and spasticity. It leads to death, mostly due to respiratory failure. Within the pathophysiology of the disease, muscle energy metabolism seems to be an important part. In our study, we used blood plasma from 25 patients with ALS diagnosed by definitive El Escorial criteria according to ALSFR-R (Revised Amyotrophic Lateral Sclerosis Functional Rating Scale) criteria and 25 age and sex-matched subjects. Aside from standard clinical biochemical parameters, we used the NMR (nuclear magnetic resonance) metabolomics approach to determine relative plasma levels of metabolites. We observed a decrease in total protein level in blood; however, despite accelerated skeletal muscle catabolism characteristic for ALS patients, we did not detect changes in plasma levels of essential amino acids. When focused on alterations in energy metabolism within muscle, compromised creatine uptake was accompanied by decreased plasma creatinine. We did not observe changes in plasma levels of BCAAs (branched chain amino acids; leucine, isoleucine, valine); however, the observed decrease in plasma levels of all three BCKAs (branched chain alpha-keto acids derived from BCAAs) suggests enhanced utilization of BCKAs as energy substrate. Glutamine, found to be increased in blood plasma in ALS patients, besides serving for ammonia detoxification, could also be considered a potential TCA (tricarboxylic acid) cycle contributor in times of decreased pyruvate utilization. When analyzing the data by using a cross-validated Random Forest algorithm, it finished with an AUC of 0.92, oob error of 8%, and an MCC (Matthew’s correlation coefficient) of 0.84 when relative plasma levels of metabolites were used as input variables. Although the discriminatory power of the system used was promising, additional features are needed to create a robust discriminatory model. Full article

(This article belongs to the Special Issue Metabolomics in Neurodegenerative Diseases)

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33 pages, 2349 KiB

Open AccessEditor’s ChoiceReview

Interaction between α-Synuclein and Bioactive Lipids: Neurodegeneration, Disease Biomarkers and Emerging Therapies

by Chiara Sanluca, Paolo Spagnolo, Romina Mancinelli, Maria Ilenia De Bartolo, Marina Fava, Mauro Maccarrone, Simone Carotti, Eugenio Gaudio, Alessandro Leuti and Giorgio Vivacqua

Metabolites 2024, 14(7), 352; https://doi.org/10.3390/metabo14070352 - 22 Jun 2024

Cited by 2 | Viewed by 2585

Abstract

The present review provides a comprehensive examination of the intricate dynamics between α-synuclein, a protein crucially involved in the pathogenesis of several neurodegenerative diseases, including Parkinson’s disease and multiple system atrophy, and endogenously-produced bioactive lipids, which play a pivotal role in neuroinflammation and [...] Read more.

The present review provides a comprehensive examination of the intricate dynamics between α-synuclein, a protein crucially involved in the pathogenesis of several neurodegenerative diseases, including Parkinson’s disease and multiple system atrophy, and endogenously-produced bioactive lipids, which play a pivotal role in neuroinflammation and neurodegeneration. The interaction of α-synuclein with bioactive lipids is emerging as a critical factor in the development and progression of neurodegenerative and neuroinflammatory diseases, offering new insights into disease mechanisms and novel perspectives in the identification of potential biomarkers and therapeutic targets. We delve into the molecular pathways through which α-synuclein interacts with biological membranes and bioactive lipids, influencing the aggregation of α-synuclein and triggering neuroinflammatory responses, highlighting the potential of bioactive lipids as biomarkers for early disease detection and progression monitoring. Moreover, we explore innovative therapeutic strategies aimed at modulating the interaction between α-synuclein and bioactive lipids, including the development of small molecules and nutritional interventions. Finally, the review addresses the significance of the gut-to-brain axis in mediating the effects of bioactive lipids on α-synuclein pathology and discusses the role of altered gut lipid metabolism and microbiota composition in neuroinflammation and neurodegeneration. The present review aims to underscore the potential of targeting α-synuclein-lipid interactions as a multifaceted approach for the detection and treatment of neurodegenerative and neuroinflammatory diseases. Full article

(This article belongs to the Special Issue Bioactive Lipids in Neuroinflammatory Diseases)

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20 pages, 4907 KiB

Open AccessEditor’s ChoiceArticle

Metabolomics Analysis of Rabbit Plasma after Ocular Exposure to Vapors of Sulfur Mustard

by Jihéne Bouhlel, Fanny Caffin, Fanny Gros-Désormeaux, Thierry Douki, Jean-François Benoist, Florence A. Castelli, Emeline Chu-Van, Christophe Piérard, Christophe Junot and François Fenaille

Metabolites 2024, 14(7), 349; https://doi.org/10.3390/metabo14070349 - 21 Jun 2024

Cited by 1 | Viewed by 1490

Abstract

Sulfur mustard (SM) is a highly potent alkylating vesicant agent and remains a relevant threat to both civilians and military personnel. The eyes are the most sensitive organ after airborne SM exposure, causing ocular injuries with no antidote or specific therapeutics available. In [...] Read more.

Sulfur mustard (SM) is a highly potent alkylating vesicant agent and remains a relevant threat to both civilians and military personnel. The eyes are the most sensitive organ after airborne SM exposure, causing ocular injuries with no antidote or specific therapeutics available. In order to identify relevant biomarkers and to obtain a deeper understanding of the underlying biochemical events, we performed an untargeted metabolomics analysis using liquid chromatography coupled to high-resolution mass spectrometry of plasma samples from New Zealand white rabbits ocularly exposed to vapors of SM. Metabolic profiles (332 unique metabolites) from SM-exposed (n = 16) and unexposed rabbits (n = 8) were compared at different time intervals from 1 to 28 days. The observed time-dependent changes in metabolic profiles highlighted the profound dysregulation of the sulfur amino acids, the phenylalanine, the tyrosine and tryptophan pathway, and the polyamine and purine biosynthesis, which could reflect antioxidant and anti-inflammatory activities. Taurine and 3,4-dihydroxy-phenylalanine (Dopa) seem to be specifically related to SM exposure and correspond well with the different phases of ocular damage, while the dysregulation of adenosine, polyamines, and acylcarnitines might be related to ocular neovascularization. Additionally, neither cysteine, N-acetylcysteine, or guanine SM adducts were detected in the plasma of exposed rabbits at any time point. Overall, our study provides an unprecedented view of the plasma metabolic changes post-SM ocular exposure, which may open up the development of potential new treatment strategies. Full article

(This article belongs to the Special Issue Challenges and Opportunities in Application of Mass Spectrometry for Metabolomics and Lipidomics)

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12 pages, 1323 KiB

Open AccessEditor’s ChoiceArticle

Characterization and Metabolism of Drug Products Containing the Cocaine-Like New Psychoactive Substances Indatraline and Troparil

by Sascha K. Manier, Paula Mumber, Josef Zapp, Niels Eckstein and Markus R. Meyer

Metabolites 2024, 14(6), 342; https://doi.org/10.3390/metabo14060342 - 18 Jun 2024

Viewed by 1302

Abstract

With a rising demand of cocaine over the last years, it is likely that unregulated new psychoactive substances with similar effects such as indatraline ((1R,3S)-3-(3,4-dichlorophenyl)-N-methyl-2,3-dihydro-1H-inden-1-amine) and troparil (Methyl (1R,2S,3S,5 [...] Read more.

With a rising demand of cocaine over the last years, it is likely that unregulated new psychoactive substances with similar effects such as indatraline ((1R,3S)-3-(3,4-dichlorophenyl)-N-methyl-2,3-dihydro-1H-inden-1-amine) and troparil (Methyl (1R,2S,3S,5S)-8-methyl-3-phenyl-8-azabicyclo[3.2.1]octane-2-carboxylate) become popular as well. Both substances share a similar pharmacological profile as cocaine, while their potency is higher, and their duration of action is longer. This study investigated their metabolic fate in rat urine and incubations using pooled human liver S9 fraction (pHLS9). Indatraline formed two phase I and four phase II metabolites, with aromatic hydroxylation and glucuronidation being the main metabolic steps. All metabolites were detected in rat urine, while the parent compound was not detectable. Although low in abundance, indatraline metabolites were well identifiable due to their specific isotopic patterns caused by chlorine. Troparil formed four phase I and three phase II metabolites, with demethylation being the main metabolic step. Hydroxylation of the tropane ring, the phenyl ring, and combinations of these steps, as well as glucuronidation, were found. Phase I metabolites were detectable in rat urine and pHLS9, while phase II metabolites were only detectable in rat urine. 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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21 pages, 3035 KiB

Open AccessEditor’s ChoiceArticle

Phenylpropanoid Metabolism in Phaseolus vulgaris during Growth under Severe Drought

by Luis Eduardo Peña Barrena, Lili Mats, Hugh J. Earl and Gale G. Bozzo

Metabolites 2024, 14(6), 319; https://doi.org/10.3390/metabo14060319 - 31 May 2024

Cited by 1 | Viewed by 1619

Abstract

Drought limits the growth and development of Phaseolus vulgaris L. (known as common bean). Common bean plants contain various phenylpropanoids, but it is not known whether the levels of these metabolites are altered by drought. Here, BT6 and BT44, two white bean recombinant [...] Read more.

Drought limits the growth and development of Phaseolus vulgaris L. (known as common bean). Common bean plants contain various phenylpropanoids, but it is not known whether the levels of these metabolites are altered by drought. Here, BT6 and BT44, two white bean recombinant inbred lines (RILs), were cultivated under severe drought. Their respective growth and phenylpropanoid profiles were compared to those of well-irrigated plants. Both RILs accumulated much less biomass in their vegetative parts with severe drought, which was associated with more phaseollin and phaseollinisoflavan in their roots relative to well-irrigated plants. A sustained accumulation of coumestrol was evident in BT44 roots with drought. Transient alterations in the leaf profiles of various phenolic acids occurred in drought-stressed BT6 and BT44 plants, including the respective accumulation of two separate caftaric acid isomers and coutaric acid (isomer 1) relative to well-irrigated plants. A sustained rise in fertaric acid was observed in BT44 with drought stress, whereas the greater amount relative to well-watered plants was transient in BT6. Apart from kaempferol diglucoside (isomer 2), the concentrations of most leaf flavonol glycosides were not altered with drought. Overall, fine tuning of leaf and root phenylpropanoid profiles occurs in white bean plants subjected to severe drought. Full article

(This article belongs to the Special Issue Metabolic Responses of Plants to Abiotic Stress)

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14 pages, 2026 KiB

Open AccessEditor’s ChoiceArticle

Machine Learning Metabolomics Profiling of Dietary Interventions from a Six-Week Randomised Trial

by Afroditi Kouraki, Ana Nogal, Weronika Nocun, Panayiotis Louca, Amrita Vijay, Kari Wong, Gregory A. Michelotti, Cristina Menni and Ana M. Valdes

Metabolites 2024, 14(6), 311; https://doi.org/10.3390/metabo14060311 - 29 May 2024

Cited by 2 | Viewed by 1747

Abstract

Metabolomics can uncover physiological responses to prebiotic fibre and omega-3 fatty acid supplements with known health benefits and identify response-specific metabolites. We profiled 534 stool and 799 serum metabolites in 64 healthy adults following a 6-week randomised trial comparing daily omega-3 versus inulin [...] Read more.

Metabolomics can uncover physiological responses to prebiotic fibre and omega-3 fatty acid supplements with known health benefits and identify response-specific metabolites. We profiled 534 stool and 799 serum metabolites in 64 healthy adults following a 6-week randomised trial comparing daily omega-3 versus inulin supplementation. Elastic net regressions were used to separately identify the serum and stool metabolites whose change in concentration discriminated between the two types of supplementations. Random forest was used to explore the gut microbiome’s contribution to the levels of the identified metabolites from matching stool samples. Changes in serum 3-carboxy-4-methyl-5-propyl-2-furanpropanoate and indoleproprionate levels accurately discriminated between fibre and omega-3 (area under the curve (AUC) = 0.87 [95% confidence interval (CI): 0.63–0.99]), while stool eicosapentaenoate indicated omega-3 supplementation (AUC = 0.86 [95% CI: 0.64–0.98]). Univariate analysis also showed significant increases in indoleproprionate with fibre, 3-carboxy-4-methyl-5-propyl-2-furanpropanoate, and eicosapentaenoate with omega-3. Out of these, only the change in indoleproprionate was partly explained by changes in the gut microbiome composition (AUC = 0.61 [95% CI: 0.58–0.64] and Rho = 0.21 [95% CI: 0.08–0.34]) and positively correlated with the increase in the abundance of the genus Coprococcus (p = 0.005). Changes in three metabolites discriminated between fibre and omega-3 supplementation. The increase in indoleproprionate with fibre was partly explained by shifts in the gut microbiome, particularly Coprococcus, previously linked to better health. Full article

(This article belongs to the Collection Advances in Metabolomics)

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27 pages, 3936 KiB

Open AccessEditor’s ChoiceReview

Is Lipid Metabolism of Value in Cancer Research and Treatment? Part II: Role of Specialized Pro-Resolving Mediators in Inflammation, Infections, and Cancer

by Muhammad Usman Babar, Ala F. Nassar, Xinxin Nie, Tianxiang Zhang, Jianwei He, Jacky Yeung, Paul Norris, Hideki Ogura, Anne Muldoon, Lieping Chen and Stephania Libreros

Metabolites 2024, 14(6), 314; https://doi.org/10.3390/metabo14060314 - 29 May 2024

Cited by 6 | Viewed by 3232

Abstract

Acute inflammation is the body’s first defense in response to pathogens or injury that is partially governed by a novel genus of endogenous lipid mediators that orchestrate the resolution of inflammation, coined specialized pro-resolving mediators (SPMs). SPMs, derived from omega-3-polyunstaturated fatty acids (PUFAs), [...] Read more.

Acute inflammation is the body’s first defense in response to pathogens or injury that is partially governed by a novel genus of endogenous lipid mediators that orchestrate the resolution of inflammation, coined specialized pro-resolving mediators (SPMs). SPMs, derived from omega-3-polyunstaturated fatty acids (PUFAs), include the eicosapentaenoic acid-derived and docosahexaenoic acid-derived Resolvins, Protectins, and Maresins. Herein, we review their biosynthesis, structural characteristics, and therapeutic effectiveness in various diseases such as ischemia, viral infections, periodontitis, neuroinflammatory diseases, cystic fibrosis, lung inflammation, herpes virus, and cancer, especially focusing on therapeutic effectiveness in respiratory inflammation and ischemia-related injuries. Resolvins are sub-nanomolar potent agonists that accelerate the resolution of inflammation by reducing excessive neutrophil infiltration, stimulating macrophage functions including phagocytosis, efferocytosis, and tissue repair. In addition to regulating neutrophils and macrophages, Resolvins control dendritic cell migration and T cell responses, and they also reduce the pro-inflammatory cytokines, proliferation, and metastasis of cancer cells. Importantly, several lines of evidence have demonstrated that Resolvins reduce tumor progression in melanoma, oral squamous cell carcinoma, lung cancer, and liver cancer. In addition, Resolvins enhance tumor cell debris clearance by macrophages in the tumor’s microenvironment. Resolvins, with their unique stereochemical structure, receptors, and biosynthetic pathways, provide a novel therapeutical approach to activating resolution mechanisms during cancer progression. Full article

(This article belongs to the Special Issue Mass Spectrometry-Based Metabolomics and Lipidomics for Biomarker Discovery and Drug Development)

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15 pages, 893 KiB

Open AccessEditor’s ChoiceReview

Elucidating the Role of Lipid-Metabolism-Related Signal Transduction and Inhibitors in Skin Cancer

by Eunjin Kook and Do-Hee Kim

Metabolites 2024, 14(6), 309; https://doi.org/10.3390/metabo14060309 - 28 May 2024

Cited by 2 | Viewed by 2217

Abstract

Lipids, as multifunctional molecules, play a crucial role in a variety of cellular processes. These include regulating membrane glycoprotein functions, controlling membrane trafficking, influencing apoptotic pathways, and affecting drug transport. In addition, lipid metabolites can alter the surrounding microenvironment in ways that might [...] Read more.

Lipids, as multifunctional molecules, play a crucial role in a variety of cellular processes. These include regulating membrane glycoprotein functions, controlling membrane trafficking, influencing apoptotic pathways, and affecting drug transport. In addition, lipid metabolites can alter the surrounding microenvironment in ways that might encourage tumor progression. The reprogramming of lipid metabolism is pivotal in promoting tumorigenesis and cancer progression, with tumors often displaying significant changes in lipid profiles. This review concentrates on the essential factors that drive lipid metabolic reprogramming, which contributes to the advancement and drug resistance in melanoma. Moreover, we discuss recent advances and current therapeutic strategies that employ small-molecule inhibitors to target lipid metabolism in skin cancers, particularly those associated with inflammation and melanoma. Full article

(This article belongs to the Special Issue Advances in Cellular Metabolism and Regulation)

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20 pages, 1202 KiB

Open AccessEditor’s ChoiceArticle

The Metabolomic Profile of Microscopic Colitis Is Affected by Smoking but Not Histopathological Diagnosis, Clinical Course, Symptoms, or Treatment

by Axel Ström, Hans Stenlund and Bodil Ohlsson

Metabolites 2024, 14(6), 303; https://doi.org/10.3390/metabo14060303 - 27 May 2024

Cited by 1 | Viewed by 1448

Abstract

Microscopic colitis (MC) is classified as collagenous colitis (CC) and lymphocytic colitis (LC). Genetic associations between CC and human leucocyte antigens (HLAs) have been found, with smoking being a predisposing external factor. Smoking has a great impact on metabolomics. The aim of this [...] Read more.

Microscopic colitis (MC) is classified as collagenous colitis (CC) and lymphocytic colitis (LC). Genetic associations between CC and human leucocyte antigens (HLAs) have been found, with smoking being a predisposing external factor. Smoking has a great impact on metabolomics. The aim of this explorative study was to analyze global metabolomics in MC and to examine whether the metabolomic profile differed regarding the type and course of MC, the presence of IBS-like symptoms, treatment, and smoking habits. Of the 240 identified women with MC aged ≤73 years, 131 completed the study questionnaire; the Rome III questionnaire; and the Visual Analog Scale for Irritable Bowel Syndrome (VAS-IBS). Blood samples were analyzed by ultra-high-performance liquid chromatograph mass spectrometry (UHLC-MS/UHPLC-MSMS). The women, 63.1 (58.7–67.2) years old, were categorized based on CC (n = 76) and LC (n = 55); one episode or refractory MC; IBS-like symptoms or not; use of corticosteroids or not; and smoking habits. The only metabolomic differences found in the univariate model after adjustment for false discovery rate (FDR) were between smokers and non-smokers. Serotonin was markedly increased in smokers (p < 0.001). No clear patterns appeared when conducting a principal component analysis (PCA). No differences in the metabolomic profile were found depending on the type or clinical course of the disease, neither in the whole MC group nor in the subgroup analysis of CC. Full article

(This article belongs to the Section Advances in Metabolomics)

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14 pages, 1202 KiB

Open AccessEditor’s ChoiceArticle

Discovery of Delirium Biomarkers through Minimally Invasive Serum Molecular Fingerprinting

by Ana Viegas, Rúben Araújo, Luís Ramalhete, Cristiana Von Rekowski, Tiago A. H. Fonseca, Luís Bento and Cecília R. C. Calado

Metabolites 2024, 14(6), 301; https://doi.org/10.3390/metabo14060301 - 26 May 2024

Cited by 2 | Viewed by 1588

Abstract

Delirium presents a significant clinical challenge, primarily due to its profound impact on patient outcomes and the limitations of the current diagnostic methods, which are largely subjective. During the COVID-19 pandemic, this challenge was intensified as the frequency of delirium assessments decreased in [...] Read more.

Delirium presents a significant clinical challenge, primarily due to its profound impact on patient outcomes and the limitations of the current diagnostic methods, which are largely subjective. During the COVID-19 pandemic, this challenge was intensified as the frequency of delirium assessments decreased in Intensive Care Units (ICUs), even as the prevalence of delirium among critically ill patients increased. The present study evaluated how the serum molecular fingerprint, as acquired by Fourier-Transform InfraRed (FTIR) spectroscopy, can enable the development of predictive models for delirium. A preliminary univariate analysis of serum FTIR spectra indicated significantly different bands between 26 ICU patients with delirium and 26 patients without, all of whom were admitted with COVID-19. However, these bands resulted in a poorly performing Naïve-Bayes predictive model. Considering the use of a Fast-Correlation-Based Filter for feature selection, it was possible to define a new set of spectral bands with a wider coverage of molecular functional groups. These bands ensured an excellent Naïve-Bayes predictive model, with an AUC, a sensitivity, and a specificity all exceeding 0.92. These spectral bands, acquired through a minimally invasive analysis and obtained rapidly, economically, and in a high-throughput mode, therefore offer significant potential for managing delirium in critically ill patients. Full article

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

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26 pages, 4637 KiB

Open AccessEditor’s ChoiceArticle

Metabolomic and Physiological Effects of a Cardiorenal Protective Diet Intervention in African American Adults with Chronic Kidney Disease

by Meera J. Patel, Chiamaka Emerenini, Xuan Wang, Teodoro Bottiglieri and Heather Kitzman

Metabolites 2024, 14(6), 300; https://doi.org/10.3390/metabo14060300 - 25 May 2024

Viewed by 1649

Abstract

Chronic kidney disease (CKD) impacts 14% of adults in the United States, and African American (AA) individuals are disproportionately affected, with more than 3 times higher risk of kidney failure as compared to White individuals. This study evaluated the effects of base-producing fruit [...] Read more.

Chronic kidney disease (CKD) impacts 14% of adults in the United States, and African American (AA) individuals are disproportionately affected, with more than 3 times higher risk of kidney failure as compared to White individuals. This study evaluated the effects of base-producing fruit and vegetables (FVs) on cardiorenal outcomes in AA persons with CKD and hypertension (HTN) in a low socioeconomic area. The “Cardiorenal Protective Diet” prospective randomized trial evaluated the effects of a 6-week, community-based FV intervention compared to a waitlist control (WL) in 91 AA adults (age = 58.3 ± 10.1 years, 66% female, 48% income ≤ USD 25K). Biometric and metabolomic variables were collected at baseline and 6 weeks post-intervention. The change in health outcomes for both groups was statistically insignificant (p > 0.05), though small reductions in albumin to creatinine ratio, body mass index, total cholesterol, and systolic blood pressure were observed in the FV group. Metabolomic profiling identified key markers (p < 0.05), including C3, C5, 1-Met-His, kynurenine, PC ae 38:5, and choline, indicating kidney function decline in the WL group. Overall, delivering a directed cardiorenal protective diet intervention improved cardiorenal outcomes in AA adults with CKD and HTN. Additionally, metabolomic profiling may serve as a prognostic technique for the early identification of biomarkers as indicators for worsening CKD and increased CVD risk. Full article

(This article belongs to the Special Issue Nutritional Epidemiology and Metabolic Disorders)

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8 pages, 597 KiB

Open AccessEditor’s ChoiceArticle

Metabolites Associated with Polygenic Risk of Breast Cancer

by Elizabeth Samuels, Jaclyn Parks, Jessica Chu, Treena McDonald, John Spinelli, Rachel A. Murphy and Parveen Bhatti

Metabolites 2024, 14(6), 295; https://doi.org/10.3390/metabo14060295 - 23 May 2024

Viewed by 1425

Abstract

While hundreds of germline genetic variants have been associated with breast cancer risk, the mechanisms underlying the impacts of most of these variants on breast cancer remain uncertain. Metabolomics may offer valuable insights into the mechanisms underlying genetic risks of breast cancer. Among [...] Read more.

While hundreds of germline genetic variants have been associated with breast cancer risk, the mechanisms underlying the impacts of most of these variants on breast cancer remain uncertain. Metabolomics may offer valuable insights into the mechanisms underlying genetic risks of breast cancer. Among 143 cancer-free female participants, we used linear regression analyses to explore associations between the genetic risk of breast cancer, as determined by a previously developed polygenic risk score (PRS) that included 266 single-nucleotide polymorphisms (SNPs), and 223 measures of metabolites obtained from blood samples using nuclear magnetic resonance (NMR). A false discovery rate of 10% was applied to account for multiple comparisons. PRS was statistically significantly associated with 45 metabolite measures. These were primarily measures of very low-density lipoproteins (VLDLs) and high-density lipoproteins (HDLs), including triglycerides, cholesterol, and phospholipids. For example, the strongest effect was observed with the percent ratio of medium VLDL triglycerides to total lipids (0.53 unit increase in mean-standardized ln-transformed percent ratio per unit increase in PRS; q = 0.1). While larger-scale studies are needed to confirm these results, this exploratory study presents biologically plausible findings that are consistent with previously reported associations between lipids and breast cancer risk. If confirmed, these lipids could be targeted for lifestyle and pharmaceutical interventions among women at increased genetic risk of breast cancer. Full article

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

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17 pages, 1844 KiB

Open AccessEditor’s ChoiceArticle

Long-Term Consumption of Purified Water Altered Amino Acid, Fatty Acid and Energy Metabolism in Livers of Rats

by Jia Wang, Zhiqun Qiu, Hui Zeng, Yao Tan, Yujing Huang, Jiaohua Luo and Weiqun Shu

Metabolites 2024, 14(5), 289; https://doi.org/10.3390/metabo14050289 - 19 May 2024

Viewed by 2529

Abstract

The consumption of low-mineral water has been increasing worldwide. Drinking low-mineral water is associated with cardiovascular disease, osteopenia, and certain neurodegenerative diseases. However, the specific mechanism remains unclear. The liver metabolic alterations in rats induced by drinking purified water for 3 months were [...] Read more.

The consumption of low-mineral water has been increasing worldwide. Drinking low-mineral water is associated with cardiovascular disease, osteopenia, and certain neurodegenerative diseases. However, the specific mechanism remains unclear. The liver metabolic alterations in rats induced by drinking purified water for 3 months were investigated with a metabolomics-based strategy. Compared with the tap water group, 74 metabolites were significantly changed in the purified water group (6 increased and 68 decreased), including 29 amino acids, 11 carbohydrates, 10 fatty acids, 7 short chain fatty acids (SCFAs), and 17 other biomolecules. Eight metabolic pathways were significantly changed, namely aminoacyl–tRNA biosynthesis; nitrogen metabolism; alanine, aspartate and glutamate metabolism; arginine and proline metabolism; histidine metabolism; biosynthesis of unsaturated fatty acids; butanoate metabolism; and glycine, serine and threonine metabolism. These changes suggested that consumption of purified water induced negative nitrogen balance, reduced expression of some polyunsaturated fatty acids and SCFAs, and disturbed energy metabolism in rats. These metabolic disturbances may contribute to low-mineral-water-associated health risks. The health risk of consuming low-mineral water requires attention. Full article

(This article belongs to the Section Animal Metabolism)

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15 pages, 1576 KiB

Open AccessEditor’s ChoiceArticle

Accurate Prediction of ¹H NMR Chemical Shifts of Small Molecules Using Machine Learning

by Tanvir Sajed, Zinat Sayeeda, Brian L. Lee, Mark Berjanskii, Fei Wang, Vasuk Gautam and David S. Wishart

Metabolites 2024, 14(5), 290; https://doi.org/10.3390/metabo14050290 - 19 May 2024

Cited by 5 | Viewed by 3540

Abstract

NMR is widely considered the gold standard for organic compound structure determination. As such, NMR is routinely used in organic compound identification, drug metabolite characterization, natural product discovery, and the deconvolution of metabolite mixtures in biofluids (metabolomics and exposomics). In many cases, compound [...] Read more.

NMR is widely considered the gold standard for organic compound structure determination. As such, NMR is routinely used in organic compound identification, drug metabolite characterization, natural product discovery, and the deconvolution of metabolite mixtures in biofluids (metabolomics and exposomics). In many cases, compound identification by NMR is achieved by matching measured NMR spectra to experimentally collected NMR spectral reference libraries. Unfortunately, the number of available experimental NMR reference spectra, especially for metabolomics, medical diagnostics, or drug-related studies, is quite small. This experimental gap could be filled by predicting NMR chemical shifts for known compounds using computational methods such as machine learning (ML). Here, we describe how a deep learning algorithm that is trained on a high-quality, “solvent-aware” experimental dataset can be used to predict ¹H chemical shifts more accurately than any other known method. The new program, called PROSPRE (PROton Shift PREdictor) can accurately (mean absolute error of <0.10 ppm) predict ¹H chemical shifts in water (at neutral pH), chloroform, dimethyl sulfoxide, and methanol from a user-submitted chemical structure. PROSPRE (pronounced “prosper”) has also been used to predict ¹H chemical shifts for >600,000 molecules in many popular metabolomic, drug, and natural product databases. 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, 5213 KiB

Open AccessEditor’s ChoiceArticle

Desorption Electrospray Ionization Mass Spectrometry Imaging Techniques Depict a Reprogramming of Energy and Purine Metabolism in the Core Brain Regions of Chronic Social Defeat Stress Mice

by Yulong Song, Fan Xiao, Jiye Aa and Guangji Wang

Metabolites 2024, 14(5), 284; https://doi.org/10.3390/metabo14050284 - 15 May 2024

Cited by 2 | Viewed by 2118

Abstract

Depression is associated with pathological changes and metabolic abnormalities in multiple brain regions. The simultaneous comprehensive and in situ detection of endogenous molecules in all brain regions is essential for a comprehensive understanding of depression pathology, which is described in this paper. A [...] Read more.

Depression is associated with pathological changes and metabolic abnormalities in multiple brain regions. The simultaneous comprehensive and in situ detection of endogenous molecules in all brain regions is essential for a comprehensive understanding of depression pathology, which is described in this paper. A method based on desorption electrospray ionization mass spectrometry imaging (DESI-MSI) technology was developed to classify mouse brain regions using characteristic lipid molecules and to detect the metabolites in mouse brain tissue samples simultaneously. The results showed that characteristic lipid molecules can be used to clearly distinguish each subdivision of the mouse brain, and the accuracy of this method is higher than that of the conventional staining method. The cerebellar cortex, medial prefrontal cortex, hippocampus, striatum, nucleus accumbens-core, and nucleus accumbens-shell exhibited the most significant differences in the chronic social defeat stress model. An analysis of metabolic pathways revealed that 13 kinds of molecules related to energy metabolism and purine metabolism exhibited significant changes. A DESI-MSI method was developed for the detection of pathological brain sections. We found, for the first time, that there are characteristic changes in the energy metabolism in the cortex and purine metabolism in the striatum, which is highly important for obtaining a deeper and more comprehensive understanding of the pathology of depression and discovering regulatory targets. Full article

(This article belongs to the Special Issue Mass Spectrometry Imaging: Theory, Methods and Applications in Biochemical and Pharmaceutical Research)

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18 pages, 5080 KiB

Open AccessEditor’s ChoiceArticle

Olaris Global Panel (OGP): A Highly Accurate and Reproducible Triple Quadrupole Mass Spectrometry-Based Metabolomics Method for Clinical Biomarker Discovery

by Masoumeh Dorrani, Jifang Zhao, Nihel Bekhti, Alessia Trimigno, Sangil Min, Jongwon Ha, Ahram Han, Elizabeth O’Day and Jurre J. Kamphorst

Metabolites 2024, 14(5), 280; https://doi.org/10.3390/metabo14050280 - 11 May 2024

Viewed by 2447

Abstract

Mass spectrometry (MS)-based clinical metabolomics is very promising for the discovery of new biomarkers and diagnostics. However, poor data accuracy and reproducibility limit its true potential, especially when performing data analysis across multiple sample sets. While high-resolution mass spectrometry has gained considerable popularity [...] Read more.

Mass spectrometry (MS)-based clinical metabolomics is very promising for the discovery of new biomarkers and diagnostics. However, poor data accuracy and reproducibility limit its true potential, especially when performing data analysis across multiple sample sets. While high-resolution mass spectrometry has gained considerable popularity for discovery metabolomics, triple quadrupole (QqQ) instruments offer several benefits for the measurement of known metabolites in clinical samples. These benefits include high sensitivity and a wide dynamic range. Here, we present the Olaris Global Panel (OGP), a HILIC LC-QqQ MS method for the comprehensive analysis of ~250 metabolites from all major metabolic pathways in clinical samples. For the development of this method, multiple HILIC columns and mobile phase conditions were compared, the robustness of the leading LC method assessed, and MS acquisition settings optimized for optimal data quality. Next, the effect of U-¹³C metabolite yeast extract spike-ins was assessed based on data accuracy and precision. The use of these U-¹³C-metabolites as internal standards improved the goodness of fit to a linear calibration curve from r² < 0.75 for raw data to >0.90 for most metabolites across the entire clinical concentration range of urine samples. Median within-batch CVs for all metabolite ratios to internal standards were consistently lower than 7% and less than 10% across batches that were acquired over a six-month period. Finally, the robustness of the OGP method, and its ability to identify biomarkers, was confirmed using a large sample set. 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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21 pages, 2508 KiB

Open AccessEditor’s ChoiceReview

Salivary Metabolites Produced by Oral Microbes in Oral Diseases and Oral Squamous Cell Carcinoma: A Review

by Bina Kashyap and Arja Kullaa

Metabolites 2024, 14(5), 277; https://doi.org/10.3390/metabo14050277 - 10 May 2024

Cited by 10 | Viewed by 2948

Abstract

In recent years, salivary metabolome studies have provided new biological information and salivary biomarkers to diagnose different diseases at early stages. The saliva in the oral cavity is influenced by many factors that are reflected in the salivary metabolite profile. Oral microbes can [...] Read more.

In recent years, salivary metabolome studies have provided new biological information and salivary biomarkers to diagnose different diseases at early stages. The saliva in the oral cavity is influenced by many factors that are reflected in the salivary metabolite profile. Oral microbes can alter the salivary metabolite profile and may express oral inflammation or oral diseases. The released microbial metabolites in the saliva represent the altered biochemical pathways in the oral cavity. This review highlights the oral microbial profile and microbial metabolites released in saliva and its use as a diagnostic biofluid for different oral diseases. The importance of salivary metabolites produced by oral microbes as risk factors for oral diseases and their possible relationship in oral carcinogenesis is discussed. Full article

(This article belongs to the Special Issue Advances in Salivary Metabolomics for Oral and Systemic Diseases)

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16 pages, 1281 KiB

Open AccessEditor’s ChoiceArticle

A Chemical Structure and Machine Learning Approach to Assess the Potential Bioactivity of Endogenous Metabolites and Their Association with Early Childhood Systemic Inflammation

by Mario Lovrić, Tingting Wang, Mads Rønnow Staffe, Iva Šunić, Kristina Časni, Jessica Lasky-Su, Bo Chawes and Morten Arendt Rasmussen

Metabolites 2024, 14(5), 278; https://doi.org/10.3390/metabo14050278 - 10 May 2024

Viewed by 2452

Abstract

Metabolomics has gained much attention due to its potential to reveal molecular disease mechanisms and present viable biomarkers. This work uses a panel of untargeted serum metabolomes from 602 children from the COPSAC2010 mother–child cohort. The annotated part of the metabolome consists of [...] Read more.

Metabolomics has gained much attention due to its potential to reveal molecular disease mechanisms and present viable biomarkers. This work uses a panel of untargeted serum metabolomes from 602 children from the COPSAC2010 mother–child cohort. The annotated part of the metabolome consists of 517 chemical compounds curated using automated procedures. We created a filtering method for the quantified metabolites using predicted quantitative structure–bioactivity relationships for the Tox21 database on nuclear receptors and stress response in cell lines. The metabolites measured in the children’s serums are predicted to affect specific targeted models, known for their significance in inflammation, immune function, and health outcomes. The targets from Tox21 have been used as targets with quantitative structure–activity relationships (QSARs). They were trained for ~7000 structures, saved as models, and then applied to the annotated metabolites to predict their potential bioactivities. The models were selected based on strict accuracy criteria surpassing random effects. After application, 52 metabolites showed potential bioactivity based on structural similarity with known active compounds from the Tox21 set. The filtered compounds were subsequently used and weighted by their bioactive potential to show an association with early childhood hs-CRP levels at six months in a linear model supporting a physiological adverse effect on systemic low-grade inflammation. Full article

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

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15 pages, 2491 KiB

Open AccessEditor’s ChoiceArticle

Mass Spectrometric Analysis of Purine Intermediary Metabolism Indicates Cyanide Induces Purine Catabolism in Rabbits

by Jordan Morningstar, Jangwoen Lee, Sari Mahon, Matthew Brenner and Anjali K. Nath

Metabolites 2024, 14(5), 279; https://doi.org/10.3390/metabo14050279 - 10 May 2024

Cited by 2 | Viewed by 1981

Abstract

Purines are the building blocks of DNA/RNA, energy substrates, and cofactors. Purine metabolites, including ATP, GTP, NADH, and coenzyme A, are essential molecules in diverse biological processes such as energy metabolism, signal transduction, and enzyme activity. When purine levels increase, excess purines are [...] Read more.

Purines are the building blocks of DNA/RNA, energy substrates, and cofactors. Purine metabolites, including ATP, GTP, NADH, and coenzyme A, are essential molecules in diverse biological processes such as energy metabolism, signal transduction, and enzyme activity. When purine levels increase, excess purines are either recycled to synthesize purine metabolites or catabolized to the end product uric acid. Purine catabolism increases during states of low oxygen tension (hypoxia and ischemia), but this metabolic pathway is incompletely understood in the context of histotoxic hypoxia (i.e., inhibition of oxygen utilization despite normal oxygen tension). In rabbits exposed to cyanide—a classical histotoxic hypoxia agent—we demonstrated significant increases in several concordant metabolites in the purine catabolic pathway (including plasma levels of uric acid, xanthosine, xanthine, hypoxanthine, and inosine) via mass spectrometry-based metabolite profiling. Pharmacological inhibition of the purine catabolic pathway with oxypurinol mitigated the deleterious effects of cyanide on skeletal muscle cytochrome c oxidase redox state, measured by non-invasive diffuse optical spectroscopy. Finally, plasma uric acid levels correlated strongly with those of lactic acid, an established clinical biomarker of cyanide exposure, in addition to a tissue biomarker of cyanide exposure (skeletal muscle cytochrome c oxidase redox state). Cumulatively, these findings not only shed light on the in vivo role(s) of cyanide but also have implications in the field of medical countermeasure (MCM) development. Full article

(This article belongs to the Special Issue Preclinical and Clinical Application of Metabolomics in Medicine)

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18 pages, 1373 KiB

Open AccessEditor’s ChoiceArticle

In Vivo and In Vitro Metabolic Fate and Urinary Detectability of Five Deschloroketamine Derivatives Studied by Means of Hyphenated Mass Spectrometry

by Fabian Frankenfeld, Lea Wagmann, Anush Abelian, Jason Wallach, Adeboye Adejare, Simon D. Brandt and Markus R. Meyer

Metabolites 2024, 14(5), 270; https://doi.org/10.3390/metabo14050270 - 8 May 2024

Cited by 1 | Viewed by 1711

Abstract

Ketamine derivatives such as deschloroketamine and deschloro-N-ethyl-ketamine show dissociative and psychoactive properties and their abuse as new psychoactive substances (NPSs) has been reported. Though some information is available on the biotransformation of dissociative NPSs, data on deschloro-N-cyclopropyl-ketamine deschloro-N [...] Read more.

Ketamine derivatives such as deschloroketamine and deschloro-N-ethyl-ketamine show dissociative and psychoactive properties and their abuse as new psychoactive substances (NPSs) has been reported. Though some information is available on the biotransformation of dissociative NPSs, data on deschloro-N-cyclopropyl-ketamine deschloro-N-isopropyl-ketamine and deschloro-N-propyl-ketamine concerning their biotransformation and, thus, urinary detectability are not available. The aims of the presented work were to study the in vivo phase I and II metabolism; in vitro phase I metabolism, using pooled human liver microsomes (pHLMs); and detectability, within a standard urine screening approach (SUSA), of five deschloroketamine derivatives. Metabolism studies were conducted by collecting urine samples from male Wistar rats over a period of 24 h after their administration at 2 mg/kg body weight. The samples were analyzed using liquid chromatography high-resolution tandem mass spectrometry (LC-HRMS/MS) and gas chromatography–mass spectrometry (GC-MS). The compounds were mainly metabolized by N-dealkylation, hydroxylation, multiple oxidations, and combinations of these metabolic reactions, as well as glucuronidation and N-acetylation. In total, 29 phase I and 10 phase II metabolites were detected. For the LC-HRMS/MS SUSA, compound-specific metabolites were identified, and suitable screening targets could be recommended and confirmed in pHLMs for all derivatives except for deschloro-N-cyclopropyl-ketamine. Using the GC-MS-based SUSA approach, only non-specific acetylated N-dealkylation metabolites could be detected. Full article

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

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18 pages, 2333 KiB

Open AccessEditor’s ChoiceArticle

Evaluation of the Metabolite Profile of Fish Oil Omega-3 Fatty Acids (n-3 FAs) in Micellar and Enteric-Coated Forms—A Randomized, Cross-Over Human Study

by Afoke Ibi, Chuck Chang, Yun Chai Kuo, Yiming Zhang, Min Du, Yoon Seok Roh, Roland Gahler, Mary Hardy and Julia Solnier

Metabolites 2024, 14(5), 265; https://doi.org/10.3390/metabo14050265 - 7 May 2024

Cited by 2 | Viewed by 2436

Abstract

This study evaluated the differences in the metabolite profile of three n-3 FA fish oil formulations in 12 healthy participants: (1) standard softgels (STD) providing 600 mg n-3 FA; (2) enteric-coated softgels (ENT) providing 600 mg n-3 FA; (3) a new micellar formulation [...] Read more.

This study evaluated the differences in the metabolite profile of three n-3 FA fish oil formulations in 12 healthy participants: (1) standard softgels (STD) providing 600 mg n-3 FA; (2) enteric-coated softgels (ENT) providing 600 mg n-3 FA; (3) a new micellar formulation (LMF) providing 374 mg n-3 FA. The pharmacokinetics (PKs), such as the area under the plot of plasma concentration (AUC), and the peak blood concentration (C_max) of the different FA metabolites including HDHAs, HETEs, HEPEs, RvD1, RvD5, RvE1, and RvE2, were determined over a total period of 24 h. Blood concentrations of EPA (26,920.0 ± 10,021.0 ng/mL·h) were significantly higher with respect to AUC_0-24 following LMF treatment vs STD and ENT; when measured incrementally, blood concentrations of total n-3 FAs (EPA/DHA/DPA3) up to 11 times higher were observed for LMF vs STD (iAUC _0-24: 16,150.0 ± 5454.0 vs 1498.9 ± 443.0; p ≤ 0.0001). Significant differences in n-3 metabolites including oxylipins were found between STD and LMF with respect to 12-HEPE, 9-HEPE, 12-HETE, and RvD1; 9-HEPE levels were significantly higher following the STD vs. ENT treatment. Furthermore, within the scope of this study, changes in blood lipid levels (i.e., cholesterol, triglycerides, LDL, and HDL) were monitored in participants for up to 120 h post-treatment; a significant decrease in serum triglycerides was detected in participants (~20%) following the LMF treatment; no significant deviations from the baseline were detected for all the other lipid biomarkers in any of the treatment groups. Despite a lower administered dose, LMF provided higher blood concentrations of n-3 FAs and certain anti-inflammatory n-3 metabolites in human participants—potentially leading to better health outcomes. Full article

(This article belongs to the Section Nutrition and Metabolism)

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19 pages, 2911 KiB

Open AccessEditor’s ChoiceArticle

Predicting the Pathway Involvement of Metabolites Based on Combined Metabolite and Pathway Features

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

Metabolites 2024, 14(5), 266; https://doi.org/10.3390/metabo14050266 - 7 May 2024

Cited by 4 | Viewed by 1772

Abstract

A major limitation of most metabolomics datasets is the sparsity of pathway annotations for detected metabolites. It is common for less than half of the identified metabolites in these datasets to have a known metabolic pathway involvement. Trying to address this limitation, machine [...] Read more.

A major limitation of most metabolomics datasets is the sparsity of pathway annotations for detected metabolites. It is common for less than half of the identified metabolites in these datasets to have a known metabolic pathway involvement. Trying to address this limitation, machine learning models have been developed to predict the association of a metabolite with a “pathway category”, as defined by a metabolic knowledge base like KEGG. Past models were implemented as a single binary classifier specific to a single pathway category, requiring a set of binary classifiers for generating the predictions for multiple pathway categories. This past approach multiplied the computational resources necessary for training while diluting the positive entries in the gold standard datasets needed for training. To address these limitations, we propose a generalization of the metabolic pathway prediction problem using a single binary classifier that accepts the features both representing a metabolite and representing a pathway category and then predicts whether the given metabolite is involved in the corresponding pathway category. We demonstrate that this metabolite–pathway features pair approach not only outperforms the combined performance of training separate binary classifiers but demonstrates an order of magnitude improvement in robustness: a Matthews correlation coefficient of 0.784 ± 0.013 versus 0.768 ± 0.154. Full article

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

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14 pages, 869 KiB

Open AccessEditor’s ChoiceReview

Nuclear Magnetic Resonance (NMR) Metabolomics: Current Applications in Equine Health Assessment

by Fulvio Laus, Marilena Bazzano, Andrea Spaterna, Luca Laghi and Andrea Marchegiani

Metabolites 2024, 14(5), 269; https://doi.org/10.3390/metabo14050269 - 7 May 2024

Cited by 1 | Viewed by 2943

Abstract

Metabolomics can allow for the comprehensive identification of metabolites within biological systems, at given time points, in physiological and pathological conditions. In the last few years, metabolomic analysis has gained popularity both in human and in veterinary medicine, showing great potential for novel [...] Read more.

Metabolomics can allow for the comprehensive identification of metabolites within biological systems, at given time points, in physiological and pathological conditions. In the last few years, metabolomic analysis has gained popularity both in human and in veterinary medicine, showing great potential for novel applications in clinical activity. The aim of applying metabolomics in clinical practice is understanding the mechanisms underlying pathological conditions and the influence of certain stimuli (i.e., drugs, nutrition, exercise) on body systems, in the attempt of identifying biomarkers that can help in the diagnosis of diseases. Proton Nuclear Magnetic Resonance spectroscopy (¹H-NMR) is well tailored to be used as an analytical platform for metabolites’ detection at the base of metabolomics studies, due to minimal sample preparation and high reproducibility. In this mini-review article, the scientific production of NMR metabolomic applications to equine medicine is examined. The research works are very different in methodology and difficult to compare. Studies are mainly focused on exercise, reproduction, and nutrition, other than respiratory and musculoskeletal diseases. The available information on this topic is still scant, but a greater collection of data could allow researchers to define new reliable markers to be used in clinical practice for diagnostic and therapeutical purposes. Full article

(This article belongs to the Special Issue Metabolomic Profiling in Equine Medicine and Reproduction)

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18 pages, 5035 KiB

Open AccessEditor’s ChoiceArticle

Depth of Interbreed Difference in Postmortem Bovine Muscle Determined by CE-FT/MS and LC-FT/MS Metabolomics

by Susumu Muroya, Yuta Horiuchi, Kazuki Iguchi, Takuma Higuchi, Shuji Sakamoto, Koichi Ojima and Kazutsugu Matsukawa

Metabolites 2024, 14(5), 261; https://doi.org/10.3390/metabo14050261 - 1 May 2024

Cited by 2 | Viewed by 2286

Abstract

Japanese Brown (JBR) cattle have moderately marbled beef compared to the highly marbled beef of Japanese Black (JBL) cattle; however, their skeletal muscle properties remain poorly characterized. To unveil interbreed metabolic differences over the previous results, we explored the metabolome network changes before [...] Read more.

Japanese Brown (JBR) cattle have moderately marbled beef compared to the highly marbled beef of Japanese Black (JBL) cattle; however, their skeletal muscle properties remain poorly characterized. To unveil interbreed metabolic differences over the previous results, we explored the metabolome network changes before and after postmortem 7-day aging in the trapezius muscle of the two cattle breeds by employing a deep and high-coverage metabolomics approach. Using both capillary electrophoresis (CE) and ultra-high-performance liquid chromatography (UHPLC)–Fourier transform mass spectrometry (FT/MS), we detected 522 and 384 annotated peaks, respectively, across all muscle samples. The CE-based results showed that the cattle were clearly separated by breed and postmortem age in multivariate analyses. The metabolism related to glutathione, glycolysis, vitamin K, taurine, and arachidonic acid was enriched with differentially abundant metabolites in aged muscles, in addition to amino acid (AA) metabolisms. The LC-based results showed that the levels of bile-acid-related metabolites, such as tauroursodeoxycholic acid (TUDCA), were high in fresh JBR muscle and that acylcarnitines were enriched in aged JBR muscle, compared to JBL muscle. Postmortem aging resulted in an increase in fatty acids and a decrease in acylcarnitine in the muscles of both cattle breeds. In addition, metabolite set enrichment analysis revealed that JBR muscle was distinctive in metabolisms related to pyruvate, glycerolipid, cardiolipin, and mitochondrial energy production, whereas the metabolisms related to phosphatidylethanolamine, nucleotide triphosphate, and AAs were characteristic of JBL. This suggests that the interbreed differences in postmortem trapezius muscle are associated with carnitine/acylcarnitine transport, β-oxidation, tricarboxylic acid cycle, and mitochondrial membrane stability, in addition to energy substrate and AA metabolisms. These interbreed differences may characterize beef quality traits such as the flavor intensity and oxidative stability. Full article

(This article belongs to the Special Issue Muscle Metabolic Response and Adaptation to Exercise, Diet, and Environment)

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18 pages, 15365 KiB

Open AccessEditor’s ChoiceArticle

Prediction of Myocardial Infarction Using a Combined Generative Adversarial Network Model and Feature-Enhanced Loss Function

by Shixiang Yu, Siyu Han, Mengya Shi, Makoto Harada, Jianhong Ge, Xuening Li, Xiang Cai, Margit Heier, Gabi Karstenmüller, Karsten Suhre, Christian Gieger, Wolfgang Koenig, Wolfgang Rathmann, Annette Peters and Rui Wang-Sattler

Metabolites 2024, 14(5), 258; https://doi.org/10.3390/metabo14050258 - 30 Apr 2024

Cited by 2 | Viewed by 1776

Abstract

Accurate risk prediction for myocardial infarction (MI) is crucial for preventive strategies, given its significant impact on global mortality and morbidity. Here, we propose a novel deep-learning approach to enhance the prediction of incident MI cases by incorporating metabolomics alongside clinical risk factors. [...] Read more.

Accurate risk prediction for myocardial infarction (MI) is crucial for preventive strategies, given its significant impact on global mortality and morbidity. Here, we propose a novel deep-learning approach to enhance the prediction of incident MI cases by incorporating metabolomics alongside clinical risk factors. We utilized data from the KORA cohort, including the baseline S4 and follow-up F4 studies, consisting of 1454 participants without prior history of MI. The dataset comprised 19 clinical variables and 363 metabolites. Due to the imbalanced nature of the dataset (78 observed MI cases and 1376 non-MI individuals), we employed a generative adversarial network (GAN) model to generate new incident cases, augmenting the dataset and improving feature representation. To predict MI, we further utilized multi-layer perceptron (MLP) models in conjunction with the synthetic minority oversampling technique (SMOTE) and edited nearest neighbor (ENN) methods to address overfitting and underfitting issues, particularly when dealing with imbalanced datasets. To enhance prediction accuracy, we propose a novel GAN for feature-enhanced (GFE) loss function. The GFE loss function resulted in an approximate 2% improvement in prediction accuracy, yielding a final accuracy of 70%. Furthermore, we evaluated the contribution of each clinical variable and metabolite to the predictive model and identified the 10 most significant variables, including glucose tolerance, sex, and physical activity. This is the first study to construct a deep-learning approach for producing 7-year MI predictions using the newly proposed loss function. Our findings demonstrate the promising potential of our technique in identifying novel biomarkers for MI prediction. Full article

(This article belongs to the Special Issue Machine Learning in Metabolic Diseases)

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18 pages, 2004 KiB

Open AccessEditor’s ChoiceArticle

Harnessing Metabolites as Serum Biomarkers for Liver Graft Pathology Prediction Using Machine Learning

by Cristina Baciu, Soumita Ghosh, Sara Naimimohasses, Arya Rahmani, Elisa Pasini, Maryam Naghibzadeh, Amirhossein Azhie and Mamatha Bhat

Metabolites 2024, 14(5), 254; https://doi.org/10.3390/metabo14050254 - 27 Apr 2024

Cited by 1 | Viewed by 1741

Abstract

Graft injury affects over 50% of liver transplant (LT) recipients, but non-invasive biomarkers to diagnose and guide treatment are currently limited. We aimed to develop a biomarker of graft injury by integrating serum metabolomic profiles with clinical variables. Serum from 55 LT recipients [...] Read more.

Graft injury affects over 50% of liver transplant (LT) recipients, but non-invasive biomarkers to diagnose and guide treatment are currently limited. We aimed to develop a biomarker of graft injury by integrating serum metabolomic profiles with clinical variables. Serum from 55 LT recipients with biopsy confirmed metabolic dysfunction-associated steatohepatitis (MASH), T-cell mediated rejection (TCMR) and biliary complications was collected and processed using a combination of LC-MS/MS assay. The metabolomic profiles were integrated with clinical information using a multi-class Machine Learning (ML) classifier. The model’s efficacy was assessed through the Out-of-Bag (OOB) error estimate evaluation. Our ML model yielded an overall accuracy of 79.66% with an OOB estimate of the error rate at 19.75%. The model exhibited a maximum ability to distinguish MASH, with an OOB error estimate of 7.4% compared to 22.2% for biliary and 29.6% for TCMR. The metabolites serine and serotonin emerged as the topmost predictors. When predicting binary outcomes using three models: Biliary (biliary vs. rest), MASH (MASH vs. rest) and TCMR (TCMR vs. rest); the AUCs were 0.882, 0.972 and 0.896, respectively. Our ML tool integrating serum metabolites with clinical variables shows promise as a non-invasive, multi-class serum biomarker of graft pathology. Full article

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

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13 pages, 3523 KiB

Open AccessEditor’s ChoiceArticle

Direct Infusion Mass Spectrometry to Rapidly Map Metabolic Flux of Substrates Labeled with Stable Isotopes

by Nils W. F. Meijer, Susan Zwakenberg, Johan Gerrits, Denise Westland, Arif I. Ardisasmita, Sabine A. Fuchs, Nanda M. Verhoeven-Duif, Judith J. M. Jans and Fried J. T. Zwartkruis

Metabolites 2024, 14(5), 246; https://doi.org/10.3390/metabo14050246 - 25 Apr 2024

Cited by 1 | Viewed by 2293

Abstract

Direct infusion–high-resolution mass spectrometry (DI-HRMS) allows for rapid profiling of complex mixtures of metabolites in blood, cerebrospinal fluid, tissue samples and cultured cells. Here, we present a DI-HRMS method suitable for the rapid determination of metabolic fluxes of isotopically labeled substrates in cultured [...] Read more.

Direct infusion–high-resolution mass spectrometry (DI-HRMS) allows for rapid profiling of complex mixtures of metabolites in blood, cerebrospinal fluid, tissue samples and cultured cells. Here, we present a DI-HRMS method suitable for the rapid determination of metabolic fluxes of isotopically labeled substrates in cultured cells and organoids. We adapted an automated annotation pipeline by selecting labeled adducts that best represent the majority of ¹³C and/or ¹⁵N-labeled glycolytic and tricarboxylic acid cycle intermediates as well as a number of their derivatives. Furthermore, valine, leucine and several of their degradation products were included. We show that DI-HRMS can determine anticipated and unanticipated alterations in metabolic fluxes along these pathways that result from the genetic alteration of single metabolic enzymes, including pyruvate dehydrogenase (PDHA1) and glutaminase (GLS). In addition, it can precisely pinpoint metabolic adaptations to the loss of methylmalonyl-CoA mutase in patient-derived liver organoids. Our results highlight the power of DI-HRMS in combination with stable isotopically labeled compounds as an efficient screening method for fluxomics. Full article

(This article belongs to the Special Issue Advances in Metabolic Profiling of Biological Samples 2nd Edition)

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16 pages, 2107 KiB

Open AccessEditor’s ChoiceArticle

The Metabolic and Lipidomic Fingerprint of Torin1 Exposure in Mouse Embryonic Fibroblasts Using Untargeted Metabolomics

by Rani Robeyns, Angela Sisto, Elias Iturrospe, Katyeny Manuela da Silva, Maria van de Lavoir, Vincent Timmerman, Adrian Covaci, Sigrid Stroobants and Alexander L. N. van Nuijs

Metabolites 2024, 14(5), 248; https://doi.org/10.3390/metabo14050248 - 25 Apr 2024

Viewed by 1919

Abstract

Torin1, a selective kinase inhibitor targeting the mammalian target of rapamycin (mTOR), remains widely used in autophagy research due to its potent autophagy-inducing abilities, regardless of its unspecific properties. Recognizing the impact of mTOR inhibition on metabolism, our objective was to develop a [...] Read more.

Torin1, a selective kinase inhibitor targeting the mammalian target of rapamycin (mTOR), remains widely used in autophagy research due to its potent autophagy-inducing abilities, regardless of its unspecific properties. Recognizing the impact of mTOR inhibition on metabolism, our objective was to develop a reliable and thorough untargeted metabolomics workflow to study torin1-induced metabolic changes in mouse embryonic fibroblast (MEF) cells. Crucially, our quality assurance and quality control (QA/QC) protocols were designed to increase confidence in the reported findings by reducing the likelihood of false positives, including a validation experiment replicating all experimental steps from sample preparation to data analysis. This study investigated the metabolic fingerprint of torin1 exposure by using liquid chromatography—high resolution mass spectrometry (LC-HRMS)-based untargeted metabolomics platforms. Our workflow identified 67 altered metabolites after torin1 exposure, combining univariate and multivariate statistics and the implementation of a validation experiment. In particular, intracellular ceramides, diglycerides, phosphatidylcholines, phosphatidylethanolamines, glutathione, and 5′-methylthioadenosine were downregulated. Lyso-phosphatidylcholines, lyso-phosphatidylethanolamines, glycerophosphocholine, triglycerides, inosine, and hypoxanthine were upregulated. Further biochemical pathway analyses provided deeper insights into the reported changes. Ultimately, our study provides a valuable workflow that can be implemented for future investigations into the effects of other compounds, including more specific autophagy modulators. Full article

(This article belongs to the Special Issue Mass Spectrometry-Based Metabolomics and Lipidomics for Biomarker Discovery and Drug Development)

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17 pages, 2604 KiB

Open AccessEditor’s ChoiceArticle

A Data-Driven Approach to Sugarcane Breeding Programs with Agronomic Characteristics and Amino Acid Constituent Profiling

by Chiaki Ishikawa, Yasuhiro Date, Makoto Umeda, Yusuke Tarumoto, Megumi Okubo, Yasujiro Morimitsu, Yasuaki Tamura, Yoichi Nishiba and Hiroshi Ono

Metabolites 2024, 14(4), 243; https://doi.org/10.3390/metabo14040243 - 21 Apr 2024

Cited by 1 | Viewed by 1934

Abstract

Sugarcane (Saccharum spp. hybrids) and its processed products have supported local industries such as those in the Nansei Islands, Japan. To improve the sugarcane quality and productivity, breeders select better clones by evaluating agronomic characteristics, such as commercially recoverable sugar and cane [...] Read more.

Sugarcane (Saccharum spp. hybrids) and its processed products have supported local industries such as those in the Nansei Islands, Japan. To improve the sugarcane quality and productivity, breeders select better clones by evaluating agronomic characteristics, such as commercially recoverable sugar and cane yield. However, other constituents in sugarcane remain largely unutilized in sugarcane breeding programs. This study aims to establish a data-driven approach to analyze agronomic characteristics from breeding programs. This approach also determines a correlation between agronomic characteristics and free amino acid composition to make breeding programs more efficient. Sugarcane was sampled in clones in the later stage of breeding selection and cultivars from experimental fields on Tanegashima Island. Principal component analysis and hierarchical cluster analysis using agronomic characteristics revealed the diversity and variability of each sample, and the data-driven approach classified cultivars and clones into three groups based on yield type. A comparison of free amino acid constituents between these groups revealed significant differences in amino acids such as asparagine and glutamine. This approach dealing with a large volume of data on agronomic characteristics will be useful for assessing the characteristics of potential clones under selection and accelerating breeding programs. Full article

(This article belongs to the Special Issue Metabolomic Technology in Quality and Safety of Agricultural Products and Foods)

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19 pages, 2039 KiB

Open AccessEditor’s ChoiceArticle

Comparative Lipidomics of Oral Commensal and Opportunistic Bacteria

by Paul L. Wood, Annie Le and Dominic L. Palazzolo

Metabolites 2024, 14(4), 240; https://doi.org/10.3390/metabo14040240 - 20 Apr 2024

Cited by 3 | Viewed by 2300

Abstract

The oral cavity contains a vast array of microbes that contribute to the balance between oral health and disease. In addition, oral bacteria can gain access to the circulation and contribute to other diseases and chronic conditions. There are a limited number of [...] Read more.

The oral cavity contains a vast array of microbes that contribute to the balance between oral health and disease. In addition, oral bacteria can gain access to the circulation and contribute to other diseases and chronic conditions. There are a limited number of publications available regarding the comparative lipidomics of oral bacteria and fungi involved in the construction of oral biofilms, hence our decision to study the lipidomics of representative oral bacteria and a fungus. We performed high-resolution mass spectrometric analyses (<2.0 ppm mass error) of the lipidomes from five Gram-positive commensal bacteria: Streptococcus oralis, Streptococcus intermedius, Streptococcus mitis, Streptococcus sanguinis, and Streptococcus gordonii; five Gram-positive opportunistic bacteria: Streptococcus mutans, Staphylococcus epidermis, Streptococcus acidominimus, Actinomyces viscosus, and Nanosynbacter lyticus; seven Gram-negative opportunistic bacteria: Porphyromonas gingivalis. Prevotella brevis, Proteus vulgaris, Fusobacterium nucleatum, Veillonella parvula, Treponema denticola, and Alkermansia muciniphila; and one fungus: Candida albicans. Our mass spectrometric analytical platform allowed for a detailed evaluation of the many structural modifications made by microbes for the three major lipid scaffolds: glycerol, sphingosine and fatty acyls of hydroxy fatty acids (FAHFAs). Full article

(This article belongs to the Special Issue Lipidomics in Health and Disease)

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15 pages, 1228 KiB

Open AccessEditor’s ChoiceArticle

Vitamin D and Ceramide Metabolomic Profile in Acute Myocardial Infarction

by Melania Gaggini, Federica Marchi, Nataliya Pylypiv, Alessandra Parlanti, Simona Storti, Umberto Paradossi, Sergio Berti and Cristina Vassalle

Metabolites 2024, 14(4), 233; https://doi.org/10.3390/metabo14040233 - 18 Apr 2024

Cited by 2 | Viewed by 1805

Abstract

Sphingolipids (SLs) influence several cellular pathways, while vitamin D exerts many extraskeletal effects in addition to its traditional biological functions, including the modulation of calcium homeostasis and bone health. Moreover, Vitamin D and SLs affect the regulation of each others’ metabolism; hence, this [...] Read more.

Sphingolipids (SLs) influence several cellular pathways, while vitamin D exerts many extraskeletal effects in addition to its traditional biological functions, including the modulation of calcium homeostasis and bone health. Moreover, Vitamin D and SLs affect the regulation of each others’ metabolism; hence, this study aims to evaluate the relationship between the levels of 25(OH)D and ceramides in acute myocardial infarction (AMI). In particular, the blood abundance of eight ceramides and 25(OH)D was evaluated in 134 AMI patients (aged 68.4 ± 12.0 years, 72% males). A significant inverse correlation between 25(OH)D and both Cer(d18:1/16:0) and Cer(d18:1/18:0) was found; indeed, patients with severe hypovitaminosis D (<10 ng/mL) showed the highest levels of the two investigated ceramides. Moreover, diabetic/dyslipidemic patients with suboptimal levels of 25(OH)D (<30 ng/mL) had higher levels of both the ceramides when compared with the rest of the population. On the other hand, 25(OH)D remained an independent determinant for Cer(d18:1/16:0) (STD Coeff −0.18, t-Value −2, p ≤ 0.05) and Cer(d18:1/18:0) (−0.2, −2.2, p < 0.05). In light of these findings, the crosstalk between sphingolipids and vitamin D may unravel additional mechanisms by which these molecules can influence CV risk in AMI. Full article

(This article belongs to the Special Issue Lipid Metabolism and Cardiometabolic Diseases: Latest Advances and Prospects)

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15 pages, 3312 KiB

Open AccessEditor’s ChoiceArticle

Discrimination of Lipogenic or Glucogenic Diet Effects in Early-Lactation Dairy Cows Using Plasma Metabolite Abundances and Ratios in Combination with Machine Learning

by Xiaodan Wang, Sanjeevan Jahagirdar, Wouter Bakker, Carolien Lute, Bas Kemp, Ariette van Knegsel and Edoardo Saccenti

Metabolites 2024, 14(4), 230; https://doi.org/10.3390/metabo14040230 - 17 Apr 2024

Cited by 1 | Viewed by 1658

Abstract

During early lactation, dairy cows have a negative energy balance since their energy demands exceed their energy intake: in this study, we aimed to investigate the association between diet and plasma metabolomics profiles and how these relate to energy unbalance of course in [...] Read more.

During early lactation, dairy cows have a negative energy balance since their energy demands exceed their energy intake: in this study, we aimed to investigate the association between diet and plasma metabolomics profiles and how these relate to energy unbalance of course in the early-lactation stage. Holstein-Friesian cows were randomly assigned to a glucogenic (n = 15) or lipogenic (n = 15) diet in early lactation. Blood was collected in week 2 and week 4 after calving. Plasma metabolite profiles were detected using liquid chromatography–mass spectrometry (LC-MS), and a total of 39 metabolites were identified. Two plasma metabolomic profiles were available every week for each cow. Metabolite abundance and metabolite ratios were used for the analysis using the XGboost algorithm to discriminate between diet treatment and lactation week. Using metabolite ratios resulted in better discrimination performance compared with the metabolite abundances in assigning cows to a lipogenic diet or a glucogenic diet. The quality of the discrimination of performance of lipogenic diet and glucogenic diet effects improved from 0.606 to 0.753 and from 0.696 to 0.842 in week 2 and week 4 (as measured by area under the curve, AUC), when the metabolite abundance ratios were used instead of abundances. The top discriminating ratios for diet were the ratio of arginine to tyrosine and the ratio of aspartic acid to valine in week 2 and week 4, respectively. For cows fed the lipogenic diet, choline and the ratio of creatinine to tryptophan were top features to discriminate cows in week 2 vs. week 4. For cows fed the glucogenic diet, methionine and the ratio of 4-hydroxyproline to choline were top features to discriminate dietary effects in week 2 or week 4. This study shows the added value of using metabolite abundance ratios to discriminate between lipogenic and glucogenic diet and lactation weeks in early-lactation cows when using metabolomics data. The application of this research will help to accurately regulate the nutrition of lactating dairy cows and promote sustainable agricultural development. Full article

(This article belongs to the Collection Advances in Metabolomics)

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41 pages, 14139 KiB

Open AccessEditor’s ChoiceReview

Examining the Pathogenesis of MAFLD and the Medicinal Properties of Natural Products from a Metabolic Perspective

by Yansong Fu, Zhipeng Wang and Hong Qin

Metabolites 2024, 14(4), 218; https://doi.org/10.3390/metabo14040218 - 12 Apr 2024

Cited by 9 | Viewed by 2806

Abstract

Metabolic-associated fatty liver disease (MAFLD), characterized primarily by hepatic steatosis, has become the most prevalent liver disease worldwide, affecting approximately two-fifths of the global population. The pathogenesis of MAFLD is extremely complex, and to date, there are no approved therapeutic drugs for clinical [...] Read more.

Metabolic-associated fatty liver disease (MAFLD), characterized primarily by hepatic steatosis, has become the most prevalent liver disease worldwide, affecting approximately two-fifths of the global population. The pathogenesis of MAFLD is extremely complex, and to date, there are no approved therapeutic drugs for clinical use. Considerable evidence indicates that various metabolic disorders play a pivotal role in the progression of MAFLD, including lipids, carbohydrates, amino acids, and micronutrients. In recent years, the medicinal properties of natural products have attracted widespread attention, and numerous studies have reported their efficacy in ameliorating metabolic disorders and subsequently alleviating MAFLD. This review aims to summarize the metabolic-associated pathological mechanisms of MAFLD, as well as the natural products that regulate metabolic pathways to alleviate MAFLD. Full article

(This article belongs to the Special Issue Advances in Dietary Nutrition Intervention on Metabolic Diseases)

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13 pages, 1058 KiB

Open AccessEditor’s ChoiceArticle

Accumulation of Non-Pathological Liver Fat Is Associated with the Loss of Glyoxalase I Activity in Humans

by Andreas Peter, Erwin Schleicher, Elisabeth Kliemank, Julia Szendroedi, Alfred Königsrainer, Hans-Ulrich Häring, Peter P. Nawroth and Thomas Fleming

Metabolites 2024, 14(4), 209; https://doi.org/10.3390/metabo14040209 - 7 Apr 2024

Cited by 1 | Viewed by 2213

Abstract

The underlying molecular mechanisms for the development of non-alcoholic fatty liver (NAFL) and its progression to advanced liver diseases remain elusive. Glyoxalase 1 (Glo1) loss, leading to elevated methylglyoxal (MG) and dicarbonyl stress, has been implicated in various diseases, including obesity-related conditions. This [...] Read more.

The underlying molecular mechanisms for the development of non-alcoholic fatty liver (NAFL) and its progression to advanced liver diseases remain elusive. Glyoxalase 1 (Glo1) loss, leading to elevated methylglyoxal (MG) and dicarbonyl stress, has been implicated in various diseases, including obesity-related conditions. This study aimed to investigate changes in the glyoxalase system in individuals with non-pathological liver fat. Liver biopsies were obtained from 30 individuals with a narrow range of BMI (24.6–29.8 kg/m²). Whole-body insulin sensitivity was assessed using HOMA-IR. Liver biopsies were analyzed for total triglyceride content, Glo1 and Glo2 mRNA, protein expression, and activity. Liquid chromatography–tandem mass spectrometry determined liver dicarbonyl content and oxidation and glycation biomarkers. Liver Glo1 activity showed an inverse correlation with HOMA-IR and liver triglyceride content, but not BMI. Despite reduced Glo1 activity, no associations were found with elevated liver dicarbonyls or glycation markers. A sex dimorphism was observed in Glo1, with females exhibiting significantly lower liver Glo1 protein expression and activity, and higher liver MG-H1 content compared to males. This study demonstrates that increasing liver fat, even within a non-pathological range, is associated with reduced Glo1 activity. Full article

(This article belongs to the Special Issue Metabolic Syndrome and Non-Alcoholic Liver Disease)

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20 pages, 1583 KiB

Open AccessEditor’s ChoiceArticle

Identifying Predictive Biomarkers of Subclinical Mastitis in Dairy Cows through Urinary Metabotyping

by Grzegorz Zwierzchowski, Klevis Haxhiaj, Roman Wójcik, David S. Wishart and Burim N. Ametaj

Metabolites 2024, 14(4), 205; https://doi.org/10.3390/metabo14040205 - 4 Apr 2024

Cited by 2 | Viewed by 2816

Abstract

Mastitis is a significant infectious disease in dairy cows, resulting in milk yield loss and culling. Early detection of mastitis-prone cows is crucial for implementing effective preventive measures before disease onset. Current diagnosis of subclinical mastitis (SCM) relies on somatic cell count assessment [...] Read more.

Mastitis is a significant infectious disease in dairy cows, resulting in milk yield loss and culling. Early detection of mastitis-prone cows is crucial for implementing effective preventive measures before disease onset. Current diagnosis of subclinical mastitis (SCM) relies on somatic cell count assessment post-calving, lacking predictive capabilities. This study aimed to identify metabolic changes in pre-SCM cows through targeted metabolomic analysis of urine samples collected 8 wks and 4 wks before calving, using mass spectrometry. A nested case-control design was employed, involving a total of 145 multiparous dairy cows, with disease occurrence monitored pre- and postpartum. Among them, 15 disease-free cows served as healthy controls (CON), while 10 cows exclusively had SCM, excluding those with additional diseases. Urinary metabolite profiling revealed multiple alterations in acylcarnitines, amino acids, and organic acids in pre-SCM cows. Metabotyping identified 27 metabolites that distinguished pre-SCM cows from healthy CON cows at both 8 and 4 wks before parturition. However, only four metabolites per week showed significant alterations (p < 0.005). Notably, a panel of four serum metabolites (asymmetric dimethylarginine, proline, leucine, and homovanillate) at 8 wks prepartum, and another panel (asymmetric dimethylarginine, methylmalonate, citrate, and spermidine) at 4 wks prepartum, demonstrated predictive ability as urinary biomarkers for SCM risk (AUC = 0.88; p = 0.02 and AUC = 0.88; p = 0.03, respectively). In conclusion, our findings indicate that metabolite testing can identify cows at risk of SCM as early as 8 and 4 wks before parturition. Validation of the two identified metabolite panels is warranted to implement these predictive biomarkers, facilitate early intervention strategies, and improve dairy cow management to mitigate the impact of SCM. Further research is needed to confirm the efficacy and applicability of these biomarkers in practical farm settings. Full article

(This article belongs to the Section Animal Metabolism)

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14 pages, 1057 KiB

Open AccessEditor’s ChoiceReview

Challenges in the Metabolomics-Based Biomarker Validation Pipeline

by Shenghan Li, Nikita Looby, Vinod Chandran and Vathany Kulasingam

Metabolites 2024, 14(4), 200; https://doi.org/10.3390/metabo14040200 - 3 Apr 2024

Cited by 11 | Viewed by 3175

Abstract

As end-products of the intersection between the genome and environmental influences, metabolites represent a promising approach to the discovery of novel biomarkers for diseases. However, many potential biomarker candidates identified by metabolomics studies fail to progress beyond analytical validation for routine implementation in [...] Read more.

As end-products of the intersection between the genome and environmental influences, metabolites represent a promising approach to the discovery of novel biomarkers for diseases. However, many potential biomarker candidates identified by metabolomics studies fail to progress beyond analytical validation for routine implementation in clinics. Awareness of the challenges present can facilitate the development and advancement of innovative strategies that allow improved and more efficient applications of metabolite-based markers in clinical settings. This minireview provides a comprehensive summary of the pre-analytical factors, required analytical validation studies, and kit development challenges that must be resolved before the successful translation of novel metabolite biomarkers originating from research. We discuss the necessity for strict protocols for sample collection, storage, and the regulatory requirements to be fulfilled for a bioanalytical method to be considered as analytically validated. We focus especially on the blood as a biological matrix and liquid chromatography coupled with tandem mass spectrometry as the analytical platform for biomarker validation. Furthermore, we examine the challenges of developing a commercially viable metabolomics kit for distribution. To bridge the gap between the research lab and clinical implementation and utility of relevant metabolites, the understanding of the translational challenges for a biomarker panel is crucial for more efficient development of metabolomics-based precision medicine. Full article

(This article belongs to the Special Issue Challenges and Opportunities in Application of Mass Spectrometry for Metabolomics and Lipidomics)

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15 pages, 4025 KiB

Open AccessEditor’s ChoiceArticle

Time-Course Metabolomic Analysis: Production of Betaine Structural Analogs by Fungal Fermentation of Seaweed

by Nao Inoue, Keisuke Tsuge, Teruyoshi Yanagita, Akira Oikawa and Koji Nagao

Metabolites 2024, 14(4), 201; https://doi.org/10.3390/metabo14040201 - 3 Apr 2024

Cited by 2 | Viewed by 1793

Abstract

Betaine structural analogs are compounds characterized by the presence of positive and negative charges in a single molecule and have been reported to have physiological properties, such as anti-inflammatory activities. In this study, we performed a metabolomic analysis of metabolite composition changes during [...] Read more.

Betaine structural analogs are compounds characterized by the presence of positive and negative charges in a single molecule and have been reported to have physiological properties, such as anti-inflammatory activities. In this study, we performed a metabolomic analysis of metabolite composition changes during the fermentation of Neopyropia yezoensis, an edible red alga, with Aspergillus oryzae for 72 h. The results indicated that three specific betaine structural analogs (betaine, stachydrine, and carnitine) exhibited significant changes in production by the end of the 72 h fermentation period. Time-course analysis suggested that betaine was generated from the precursor choline at 12–24 h during the late stage of fungal growth, while stachydrine was generated from the precursor-related compound glutamic acid at 48–72 h during the sporulation stage. However, the contribution of the precursor lysine to the increased production of carnitine during the 12–72 h period was unclear. This study provides useful information on the efficient production of betaine structural analogs by the fungal fermentation of seaweed as well as various other food materials. Full article

(This article belongs to the Special Issue Emerging Applications of Metabolomics in Fermented Food)

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15 pages, 1170 KiB

Open AccessEditor’s ChoiceArticle

Grape/Blueberry Anthocyanins and Their Gut-Derived Metabolites Attenuate LPS/Nigericin-Induced Inflammasome Activation by Inhibiting ASC Speck Formation in THP-1 Monocytes

by Inken Behrendt, Isabella Röder, Frank Will, Gabriela Michel, Elvira Friedrich, Daniela Grote, Zoe Martin, Hanna Pauline Dötzer, Mathias Fasshauer, Martin Speckmann and Sabine Kuntz

Metabolites 2024, 14(4), 203; https://doi.org/10.3390/metabo14040203 - 3 Apr 2024

Cited by 2 | Viewed by 1899

Abstract

Inflammasomes are multi-protein complexes, which are formed in response to tissue injury, infections, and metabolic stress. However, aberrant inflammasome activation has been linked to several inflammatory diseases. Anthocyanins have been reported to attenuate NLR family pyrin domain-containing 3 (NLRP3) inflammasome activation, but the [...] Read more.

Inflammasomes are multi-protein complexes, which are formed in response to tissue injury, infections, and metabolic stress. However, aberrant inflammasome activation has been linked to several inflammatory diseases. Anthocyanins have been reported to attenuate NLR family pyrin domain-containing 3 (NLRP3) inflammasome activation, but the influence of grape/blueberry anthocyanins and especially their gut-derived metabolites on NLRP3 inflammasome activation in human monocytes remains unclear. Therefore, human leukemic monocytes (THP-1 cells, Tohoku Hospital Pediatrics-1 cells) were preincubated with different concentrations of grape/blueberry anthocyanins, homovanillyl alcohol, or 2,4,6-trihydroxybenzaldehyde (THBA) before the NLRP3 inflammasome was activated by lipopolysaccharide and/or nigericin. Apoptosis-associated speck-like protein containing a CARD (ASC) speck formation, as well as ASC and NLRP3 protein expression, were determined using flow cytometry. Caspase-1 activity was measured in cultured cells, and pro-inflammatory cytokine secretion was determined using enzyme-linked immunosorbent assays. Anthocyanins and their metabolites had no effect on ASC or NLRP3 protein expression. However, THBA significantly inhibited ASC speck formation in primed and unprimed THP-1 monocytes, while caspase-1 activity was significantly declined by grape/blueberry anthocyanins. Furthermore, reduced inflammasome activation resulted in lower pro-inflammatory cytokine secretion. In conclusion, our results show for the first time that grape/blueberry anthocyanins and their gut-derived metabolites exert anti-inflammatory effects by attenuating NLRP3 inflammasome activation in THP-1 monocytes. Full article

(This article belongs to the Special Issue Role of Gut-Derived Metabolites in Health and Disease)

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26 pages, 3539 KiB

Open AccessEditor’s ChoiceArticle

Lipidome Changes Associated with a Diet-Induced Reduction in Hepatic Fat among Adolescent Boys with Metabolic Dysfunction-Associated Steatotic Liver Disease

by Helaina E. Huneault, Chih-Yu Chen, Catherine C. Cohen, Xueyun Liu, Zachery R. Jarrell, Zhulin He, Karla E. DeSantos, Jean A. Welsh, Kristal M. Maner-Smith, Eric A. Ortlund, Jeffrey B. Schwimmer and Miriam B. Vos

Metabolites 2024, 14(4), 191; https://doi.org/10.3390/metabo14040191 - 28 Mar 2024

Cited by 2 | Viewed by 2607

Abstract

Little is known about lipid changes that occur in the setting of metabolic-dysfunction-associated steatotic liver disease (MASLD) regression. We previously reported improvements in hepatic steatosis, de novo lipogenesis (DNL), and metabolomic profiles associated with oxidative stress, inflammation, and selected lipid metabolism in 40 [...] Read more.

Little is known about lipid changes that occur in the setting of metabolic-dysfunction-associated steatotic liver disease (MASLD) regression. We previously reported improvements in hepatic steatosis, de novo lipogenesis (DNL), and metabolomic profiles associated with oxidative stress, inflammation, and selected lipid metabolism in 40 adolescent boys (11–16 y) with hepatic steatosis ≥5% (98% meeting the definition of MASLD). Participants were randomized to a low-free-sugar diet (LFSD) (n = 20) or usual diet (n = 20) for 8 weeks. Here, we employed untargeted/targeted lipidomics to examine lipid adaptations associated with the LFSD and improvement of hepatic steatosis. Our LC-MS/MS analysis revealed decreased triglycerides (TGs), diacylglycerols (DGs), cholesteryl esters (ChE), lysophosphatidylcholine (LPC), and phosphatidylcholine (PC) species with the diet intervention (p < 0.05). Network analysis demonstrated significantly lower levels of palmitate-enriched TG species post-intervention, mirroring the previously shown reduction in DNL in response to the LFSD. Targeted oxylipins analysis revealed a decrease in the abundance of 8-isoprostane and 14,15-DiHET and an increase in 8,9-DiHET (p < 0.05). Overall, we observed reductions in TGs, DGs, ChE, PC, and LPC species among participants in the LFSD group. These same lipids have been associated with MASLD progression; therefore, our findings may indicate normalization of key biological processes, including lipid metabolism, insulin resistance, and lipotoxicity. Additionally, our targeted oxylipins assay revealed novel changes in eicosanoids, suggesting improvements in oxidative stress. Future studies are needed to elucidate the mechanisms of these findings and prospects of these lipids as biomarkers of MASLD regression. Full article

(This article belongs to the Section Lipid Metabolism)

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