Metabolites

18 pages, 1022 KiB

Open AccessArticle

Double-Weighted Bayesian Model Combination for Metabolomics Data Description and Prediction

by Jacopo Troisi, Martina Lombardi, Alessio Trotta, Vera Abenante, Andrea Ingenito, Nicole Palmieri, Sean M. Richards, Steven J. K. Symes and Pierpaolo Cavallo

Metabolites 2025, 15(4), 214; https://doi.org/10.3390/metabo15040214 - 21 Mar 2025

Abstract

Background/Objectives: This study presents a novel double-weighted Bayesian Ensemble Machine Learning (DW-EML) model aimed at improving the classification and prediction of metabolomics data. This discipline, which involves the comprehensive analysis of metabolites in a biological system, provides valuable insights into complex biological processes [...] Read more.

Background/Objectives: This study presents a novel double-weighted Bayesian Ensemble Machine Learning (DW-EML) model aimed at improving the classification and prediction of metabolomics data. This discipline, which involves the comprehensive analysis of metabolites in a biological system, provides valuable insights into complex biological processes and disease states. As metabolomics assumes an increasingly prominent role in the diagnosis of human diseases and in precision medicine, there is a pressing need for more robust artificial intelligence tools that can offer enhanced reliability and accuracy in medical applications. The proposed DW-EML model addresses this by integrating multiple classifiers within a double-weighted voting scheme, which assigns weights based on the cross-validation accuracy and classification confidence, ensuring a more reliable prediction framework. Methods: The model was applied to publicly available datasets derived from studies on critical illness in children, chronic typhoid carriage, and early detection of ovarian cancer. Results: The results demonstrate that the DW-EML approach outperformed methods traditionally used in metabolomics, such as the Partial Least Squares Discriminant Analysis in terms of accuracy and predictive power. Conclusions: The DW-EML model is a promising tool for metabolomic data analysis, offering enhanced robustness and reliability for diagnostic and prognostic applications and potentially contributing to the advancement of personalized and precision medicine. Full article

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

25 pages, 1151 KiB

Open AccessSystematic Review

Intestinal Metabolome for Diagnosing and Prognosing Autism Spectrum Disorder in Children: A Systematic Review

by Andrés Suárez-Jaramillo, Sara G. Cifuentes, Manuel Baldeón and Paúl Cárdenas

Metabolites 2025, 15(4), 213; https://doi.org/10.3390/metabo15040213 - 21 Mar 2025

Abstract

Background/Objectives: Currently, the diagnosis of autism spectrum disorder (ASD) relies on behavioral observations, frequently causing delays in early identification. Prognostic markers are essential for customizing therapy and monitoring progress. However, there are currently no recognized biomarkers for ASD. The current systematic review [...] Read more.

Background/Objectives: Currently, the diagnosis of autism spectrum disorder (ASD) relies on behavioral observations, frequently causing delays in early identification. Prognostic markers are essential for customizing therapy and monitoring progress. However, there are currently no recognized biomarkers for ASD. The current systematic review aims to analyze studies on the intestinal metabolome in children (both autistic and non-autistic) to identify potential metabolites for diagnostic and prognostic purposes. Methods: We searched Medline, Scopus, Embase, and Web of Science for relevant publications. Results: We identified 11 studies examining the gut metabolome that distinguished between autistic and non-autistic children. These studies also revealed connections between gut metabolites, developmental scores, and symptoms. The substances identified were associated with metabolic pathways such as amino acids, vitamins, lipids, oxidative stress, glycans, xenobiotics, and nucleotides. Conclusions: These findings suggest metabolic changes that may be linked to the causes or development of autism. Although these observations came from a few reports, only high-quality studies were included in this review. Further research is essential to confirm the identified substances as biomarkers. Full article

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19 pages, 2396 KiB

Open AccessArticle

Valorizing Agro-Industrial By-Products for Sustainable Cultivation of Chlorella sorokiniana: Enhancing Biomass, Lipid Accumulation, Metabolites, and Antimicrobial Potential

by Elia Lio, Carlo Esposito, Jacopo Paini, Stefano Gandolfi, Francesco Secundo and Gianluca Ottolina

Metabolites 2025, 15(3), 212; https://doi.org/10.3390/metabo15030212 - 20 Mar 2025

Abstract

Background/Objectives: Mixotrophic cultivation of microalgae using agro-industrial by-products as supplements offers a sustainable strategy to enhance biomass production and bioactive compound synthesis. This study aimed to evaluate the effects of different agro-industrial by-products—orange peel extract, Cladophora glomerata macroalgal hydrolysate, and solid-state fungal fermentation [...] Read more.

Background/Objectives: Mixotrophic cultivation of microalgae using agro-industrial by-products as supplements offers a sustainable strategy to enhance biomass production and bioactive compound synthesis. This study aimed to evaluate the effects of different agro-industrial by-products—orange peel extract, Cladophora glomerata macroalgal hydrolysate, and solid-state fungal fermentation hydrolysate—on the growth and bioactivity of Chlorella sorokiniana. Methods: Microalgae were cultivated under mixotrophic conditions with different agro-industrial by-products as organic carbon sources. Biomass accumulation was monitored through dry weight measurements. Lipid extraction was carried out using dimethyl carbonate. The antimicrobial activity of the extracted compounds was assessed against Escherichia coli, Bacillus megaterium, and Bacillus subtilis by determining the minimal inhibitconcentrations. Results: Orange peel extract supplementation resulted in the highest biomass production. It increased dry weight by 13.86-fold compared to autotrophic conditions. Cladophora glomerata macroalgal hydrolysate followed with a 5.79-fold increase, and solid-state fungal fermentation hydrolysate showed a 4.14-fold increase. The lipophilic fraction extracted from microalgal biomass showed high yields. Orange peel extract supplementation achieved the highest extraction yield (274.36 mg/g DW). Antimicrobial activity varied based on the supplement used: biomass cultivated with orange peel extract exhibited superior activity against E. coli, whereas Cladophora glomerata macroalgal hydrolysate biomass demonstrated potent activity against B. subtilis (MIC: 5.67 g/mL). Conclusions: These findings underscore the potential of agro-industrial by-products for enhancing microalgal biomass and metabolite production. The observed antimicrobial properties highlight the application of microalgal-derived compounds in sustainable bioprocesses, supporting their use in pharmaceutical and biotechnological applications. Full article

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

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19 pages, 1291 KiB

Open AccessReview

Diet-Induced Proteomic and Metabolomic Signatures in Chronic Kidney Disease: A Precision Nutrition Approach

by Sandra Cabała and Agnieszka Herosimczyk

Metabolites 2025, 15(3), 211; https://doi.org/10.3390/metabo15030211 - 20 Mar 2025

Abstract

Background: Diet is a key modifiable factor that can either support renal health or accelerate the onset and progression of chronic kidney disease (CKD). Recent advances in multiomics, particularly proteomics and metabolomics, significantly enhanced our understanding of the molecular mechanisms linking diet to [...] Read more.

Background: Diet is a key modifiable factor that can either support renal health or accelerate the onset and progression of chronic kidney disease (CKD). Recent advances in multiomics, particularly proteomics and metabolomics, significantly enhanced our understanding of the molecular mechanisms linking diet to CKD risk. Proteomics offers a comprehensive analysis of protein expression, structure, and interactions, revealing how dietary components regulate cellular processes and signaling pathways. Meanwhile, metabolomics provides a detailed profile of low-molecular-weight compounds, including endogenous metabolites and diet-derived molecules, offering insights into the metabolic states that influence kidney function. Methods: We have conducted a narrative review of key papers from databases such as PubMed, Scopus, and Web of Science to explore the potential of proteomic and metabolomic analysis in identifying molecular signatures associated with diet in human and animal biological samples, such as blood plasma, urine, and in kidney tissues. These signatures help elucidate how specific foods, food groups, and overall dietary patterns may either contribute to or mitigate CKD risk. Results: Recent studies the impact of high-fat diets on protein expression involved in energy metabolism, inflammation, and fibrosis, identifying early biomarkers of kidney injury. Metabolic, including disruptions in in fatty acid metabolism, glucose regulation, and amino acid pathways, have been recognized as key indicators of CKD risk. Additionally, several studies explore specific metabolites found in biological fluids and renal tissue in response to protein-rich foods, assessing their potential roles in a progressive loss of kidney function. Emerging evidence also suggests that dietary interventions targeting the gut microbiota may help alleviate inflammation, oxidative stress, and toxin accumulation in chronic kidney disease. Notably, recent findings highlight metabolomic signatures linked to beneficial shifts in gut microbial metabolism, particularly in the context of prebiotic supplementation. Conclusions: By integrating proteomics and metabolomics, future research can refine precision nutrition strategies, helping mitigate CKD progression. Expanding large-scale studies and clinical trials will be essential in translating these molecular insights into actionable dietary guidelines. Full article

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

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30 pages, 4051 KiB

Open AccessReview

Diverse Physiological Roles of Kynurenine Pathway Metabolites: Updated Implications for Health and Disease

by Yuechang Wang, Yonggang Zhang, Wei Wang, Yanmin Zhang, Xueqian Dong and Yang Liu

Metabolites 2025, 15(3), 210; https://doi.org/10.3390/metabo15030210 - 20 Mar 2025

Abstract

Tryptophan is an essential amino acid critical for human health. It plays a pivotal role in numerous physiological and biochemical processes through its metabolism. The kynurenine (KYN) pathway serves as the principal metabolic route for tryptophan, producing bioactive metabolites, including KYN, quinolinic acid, [...] Read more.

Tryptophan is an essential amino acid critical for human health. It plays a pivotal role in numerous physiological and biochemical processes through its metabolism. The kynurenine (KYN) pathway serves as the principal metabolic route for tryptophan, producing bioactive metabolites, including KYN, quinolinic acid, and 3-hydroxykynurenine. Numerous studies are actively investigating the relationship between tryptophan metabolism and physiological functions. These studies are highlighting the interactions among metabolites that may exert synergistic or antagonistic effects, such as neuroprotective or neurotoxic, and pro-oxidative or antioxidant activities. Minor disruptions in the homeostasis of these metabolites can result in immune dysregulation, contributing to a spectrum of diseases. These diseases include neurological disorders, mental illnesses, cardiovascular conditions, autoimmune diseases, and chronic kidney disease. Therefore, understanding the physiological roles of the KYN pathway metabolites is essential for elucidating the contribution of tryptophan metabolism to health regulation. The present review emphasizes the physiological roles of KYN pathway metabolites and their mechanisms in disease development, aiming to establish a theoretical basis for leveraging dietary nutrients to enhance human health. Full article

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

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17 pages, 995 KiB

Open AccessArticle

A Pilot Study: Maternal Undernutrition Programs Energy Metabolism and Alters Metabolic Profile and Morphological Characteristics of Skeletal Muscle in Postnatal Beef Cattle

by Daichi Nishino, Taketo Haginouchi, Takeshi Shimogiri, Susumu Muroya, Kenji Kawabata, Saki Urasoko, Ichiro Oshima, Shinobu Yasuo and Takafumi Gotoh

Metabolites 2025, 15(3), 209; https://doi.org/10.3390/metabo15030209 - 19 Mar 2025

Abstract

Objectives: This study investigated the long-term effects of maternal undernutrition on overall muscle metabolism, growth performance, and muscle characteristics in postnatal offspring of Wagyu (Japanese Black) cattle. Methods: Wagyu cows were divided into nutrient-adequate (control, CNT; n = 4, 120% of [...] Read more.

Objectives: This study investigated the long-term effects of maternal undernutrition on overall muscle metabolism, growth performance, and muscle characteristics in postnatal offspring of Wagyu (Japanese Black) cattle. Methods: Wagyu cows were divided into nutrient-adequate (control, CNT; n = 4, 120% of requirements) and nutrient-restricted groups (NR; n = 4; 60% of requirements), and treated from day 35 of gestation until parturition. Diets were delivered on the basis of crude protein requirements, meeting 100% and 80% of dry matter requirements in CNT and NR groups, respectively. All offspring were provided with the same diet from birth to 300 days of age (d). Longissimus thoracis muscle (LM) samples were collected from the postnatal offspring. Results: The NR offspring had lower birth body weight, but their body weight caught up before weaning. These offspring showed enhanced efficiency in nutrient utilization during the post-weaning growth period. Comprehensive analyses of metabolites and transcripts revealed the accumulation of proteinogenic amino acid, asparagine, in NR offspring LM at 300 d, while the abundance of nicotinamide adenine dinucleotide (NADH) and succinate were reduced. These changes were accompanied by decreased gene expression of nicotinamide phosphoribosyltransferase (NAMPT), NADH: ubiquinone oxidoreductase subunit A12 (NDUFA12), and NADH dehydrogenase subunit 5 (ND5), which are essential for mitochondrial energy production. Additionally, NR offspring LM exhibited decreased abundance of neurotransmitter, along with a higher proportion of slow-oxidative myofibers and a lower proportion of fast-oxidative myofibers at 300 d. Conclusions: Offspring from nutrient-restricted cows might suppress muscle energy production, primarily in the mitochondria, and conserve energy expenditure for muscle protein synthesis. These findings suggest that maternal undernutrition programs a thrifty metabolism in offspring muscle, with long-term effects. Full article

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

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32 pages, 3207 KiB

Open AccessReview

Metabolomics in Parkinson’s Disease and Correlation with Disease State

by Elena A. Ostrakhovitch, Kenjiro Ono and Tritia R. Yamasaki

Metabolites 2025, 15(3), 208; https://doi.org/10.3390/metabo15030208 - 18 Mar 2025

Abstract

Changes in the level of metabolites, small molecules that are intermediates produced by metabolism or catabolism, are associated with developing diseases. Metabolite signatures in body fluids such as plasma, cerebrospinal fluid, urine, and saliva are associated with Parkinson’s disease. Here, we discuss alteration [...] Read more.

Changes in the level of metabolites, small molecules that are intermediates produced by metabolism or catabolism, are associated with developing diseases. Metabolite signatures in body fluids such as plasma, cerebrospinal fluid, urine, and saliva are associated with Parkinson’s disease. Here, we discuss alteration of metabolites in the TCA cycle, pentose phosphate pathway, kynurenic network, and redox system. We also summarize the efforts of many research groups to differentiate between metabolite profiles that characterize PD motor progression and dyskinesia, gait and balance, and non-motor symptoms such as depression and cognitive decline. Understanding how changes in metabolites lead to progression in PD may allow for the identification of individuals at the earliest stage of the disease and the development of new therapeutic strategies. Full article

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

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20 pages, 15032 KiB

Open AccessArticle

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

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

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

Abstract

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

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

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

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25 pages, 610 KiB

Open AccessReview

Cardiometabolic Risk in Psoriatic Arthritis: A Hidden Burden of Inflammation and Metabolic Dysregulation

by Mislav Radić, Andrej Belančić, Hana Đogaš, Marijana Vučković, Yusuf Ziya Sener, Seher Sener, Almir Fajkić and Josipa Radić

Metabolites 2025, 15(3), 206; https://doi.org/10.3390/metabo15030206 - 18 Mar 2025

Abstract

Psoriatic arthritis (PsA) is a chronic inflammatory disease that extends beyond musculoskeletal and dermatologic involvement to elevate cardiometabolic risk. Emerging evidence highlights the critical role of systemic inflammation in metabolic dysregulation, accelerating insulin resistance, dyslipidemia, and oxidative stress, all of which contribute to [...] Read more.

Psoriatic arthritis (PsA) is a chronic inflammatory disease that extends beyond musculoskeletal and dermatologic involvement to elevate cardiometabolic risk. Emerging evidence highlights the critical role of systemic inflammation in metabolic dysregulation, accelerating insulin resistance, dyslipidemia, and oxidative stress, all of which contribute to the increased burden of cardiovascular disease in PsA. This review explores the intricate interplay between inflammatory mediators—such as tumor necrosis factor-alpha (TNF-α), interleukin-6 (IL-6), and interleukin-17 (IL-17),—adipokine imbalances, and lipid metabolism abnormalities, all of which foster endothelial dysfunction and atherosclerosis. The dysregulation of adipokines, including leptin, adiponectin, and resistin, further perpetuates inflammatory cascades, exacerbating cardiovascular risk. Additionally, the metabolic alterations seen in PsA, particularly insulin resistance and lipid dysfunction, not only contribute to cardiovascular comorbidities but also impact disease severity and therapeutic response. Understanding these mechanistic links is imperative for refining risk stratification strategies and tailoring interventions. By integrating targeted immunomodulatory therapies with metabolic and cardiovascular risk management, a more comprehensive approach to PsA treatment can be achieved. Future research must focus on elucidating shared inflammatory and metabolic pathways, enabling the development of innovative therapeutic strategies to mitigate both systemic inflammation and cardiometabolic complications in PsA. Full article

(This article belongs to the Special Issue Research on Biomarkers for Cardiometabolic Risk in Metabolic Syndrome)

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14 pages, 2223 KiB

Open AccessArticle

Targeted Detection of 76 Carnitine Indicators Combined with a Machine Learning Algorithm Based on HPLC-MS/MS in the Diagnosis of Rheumatoid Arthritis

by Rui Zhang, Juan Wang, Xiaonan Zhai, Yuanbing Guo, Lei Zhou, Xiaoyan Hao, Liu Yang, Ruiqing Xing, Juanjuan Hu, Jiawei Gao, Fengjuan Wang, Jun Yang and Jiayun Liu

Metabolites 2025, 15(3), 205; https://doi.org/10.3390/metabo15030205 - 18 Mar 2025

Abstract

Background/Objectives: Early diagnosis and treatment of rheumatoid arthritis (RA) are essential to reducing disability. However, the diagnostic criteria remain unclear, relying on clinical symptoms and blood markers. Methods: Using high-performance liquid chromatography–mass spectrometry (HPLC-MS/MS) targeted detection, we evaluated 76 carnitine indicators (55 carnitines [...] Read more.

Background/Objectives: Early diagnosis and treatment of rheumatoid arthritis (RA) are essential to reducing disability. However, the diagnostic criteria remain unclear, relying on clinical symptoms and blood markers. Methods: Using high-performance liquid chromatography–mass spectrometry (HPLC-MS/MS) targeted detection, we evaluated 76 carnitine indicators (55 carnitines and 21 corresponding ratios) in the serum of patients with RA to investigate the role of carnitine in RA. A total of 359 patients (207 patients with RA and 152 healthy controls) were included in the study. Screening involved three methods and integrated 76 carnitine indicators and 128 clinical indicators to identify candidate markers to establish a theoretical basis for RA diagnosis and new therapeutic targets. The diagnostic model derived from the screened markers was validated using three machine learning algorithms. Results: The model was refined using eight candidate indicators (C0, C10:1, LYMPH, platelet distribution width, anti-keratin antibody, glucose, urobilinogen, and erythrocyte sedimentation rate (ESR)). The receiver operating characteristic curve, sensitivity, specificity, and accuracy of the V8 model obtained from the training set were >0.948, 79.46%, 92.99%, and 89.18%, whereas those of the test set were >0.925, 78.89%, 89.22%, and 85.87%, respectively. Twenty-four carnitines were identified as risk factors of RA, with three significantly correlating with ESR, four with anti-cyclic citrullinated peptide antibody activity, two with C-reactive protein, five with immunoglobulin-G, eight with immunoglobulin-A levels, and eleven with immunoglobulin-M levels. Conclusions: Carnitine is integral in the progression of RA. The diagnostic model developed shows excellent diagnostic capacity, improving early detection and enabling timely intervention to minimize disability associated with RA. Full article

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

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25 pages, 1841 KiB

Open AccessArticle

Cytokine-Based Insights into Bloodstream Infections and Bacterial Gram Typing in ICU COVID-19 Patients

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

Metabolites 2025, 15(3), 204; https://doi.org/10.3390/metabo15030204 - 16 Mar 2025

Abstract

Background: Timely and accurate identification of bloodstream infections (BSIs) in intensive care unit (ICU) patients remains a key challenge, particularly in COVID-19 settings, where immune dysregulation can obscure early clinical signs. Methods: Cytokine profiling was evaluated to discriminate between ICU patients with and [...] Read more.

Background: Timely and accurate identification of bloodstream infections (BSIs) in intensive care unit (ICU) patients remains a key challenge, particularly in COVID-19 settings, where immune dysregulation can obscure early clinical signs. Methods: Cytokine profiling was evaluated to discriminate between ICU patients with and without BSIs, and, among those with confirmed BSIs, to further stratify bacterial infections by Gram type. Serum samples from 45 ICU COVID-19 patients were analyzed using a 21-cytokine panel, with feature selection applied to identify candidate markers. Results: A machine learning workflow identified key features, achieving robust performance metrics with AUC values up to 0.97 for BSI classification and 0.98 for Gram typing. Conclusions: In contrast to traditional approaches that focus on individual cytokines or simple ratios, the present analysis employed programmatically generated ratios between pro-inflammatory and anti-inflammatory cytokines, refined through feature selection. Although further validation in larger and more diverse cohorts is warranted, these findings underscore the potential of advanced cytokine-based diagnostics to enhance precision medicine in infection management. Full article

(This article belongs to the Special Issue Towards Clinical Interpretation of Metabolomic Data)

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29 pages, 3828 KiB

Open AccessReview

Pyruvate Kinase M1/2 Proteoformics for Accurate Insights into Energy Metabolism Abnormity to Promote the Overall Management of Ovarian Cancer Towards Predictive, Preventive, and Personalized Medicine Approaches

by Yan Wang, Nuo Xu, Marie Louise Ndzie Noah, Liang Chen and Xianquan Zhan

Metabolites 2025, 15(3), 203; https://doi.org/10.3390/metabo15030203 - 16 Mar 2025

Abstract

Ovarian cancer (OC) is a global health problem that frequently presents at advanced stages, is predisposed to recurrence, readily develops resistance to platinum-based drugs, and has a low survival rate. Predictive, preventive, and personalized medicine (PPPM/3PM) offers an integrated solution with the use [...] Read more.

Ovarian cancer (OC) is a global health problem that frequently presents at advanced stages, is predisposed to recurrence, readily develops resistance to platinum-based drugs, and has a low survival rate. Predictive, preventive, and personalized medicine (PPPM/3PM) offers an integrated solution with the use of genetic, proteomic, and metabolic biomarkers to identify high-risk individuals for early detection. Metabolic reprogramming is one of the key strategies employed by tumor cells to adapt to the microenvironment and support unlimited proliferation. Pyruvate kinases M1 and M2 (PKM1/2) are encoded by the PKM gene, a pivotal enzyme in the last step of the glycolytic pathway, which is at the crossroads of aerobic oxidation and the Warburg effect to serve as a potential regulator of glucose metabolism and influence cellular energy production and metabolic reprogramming. Commonly, the ratio of PKM1-to-PKM2 is changed in tumors compared to normal controls, and PKM2 is highly expressed in OC to induce a high glycolysis rate and participate in the malignant invasion and metastatic characteristics of cancer cells with epithelial/mesenchymal transition (EMT). PKM2 inhibitors suppress the migration and growth of OC cells by interfering with the Warburg effect. Proteoforms are the final structural and functional forms of a gene/protein, and the canonical protein PKM contains all proteoforms encoded by the same PKM gene. The complexity of PKM can be elucidated by proteoformics. The OC-specific PKM proteoform might represent a specific target for therapeutic interventions against OC. In the framework of PPPM/3PM, the OC-specific PKM proteoform might be the early warning and prognosis biomarker. It is important to clarify the molecular mechanisms of PKM proteoforms in cancer metabolism. This review analyzes the expression, function, and molecular mechanisms of PKM proteoforms in OC, which help identify specific biomarkers for OC. Full article

(This article belongs to the Special Issue Mitochondrial Metabolism in Health and Disease: A Clinical Perspective)

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14 pages, 4319 KiB

Open AccessArticle

Effect of Antifreeze Glycopeptides on the Quality and Microstructure of Frozen Lamb Meatballs

by Rong Dong, Shengkun Yan, Guoqiang Wang and Pei Wang

Metabolites 2025, 15(3), 202; https://doi.org/10.3390/metabo15030202 - 13 Mar 2025

Abstract

This study explored the protective effects of antifreeze glycopeptide and alginate on the quality of −18 °C frozen lamb meatballs across various storage periods. Methods: Measurements of volatile salt nitrogen (TVB-N), thiobarbituric acid (TBARS), water retention, water distribution, microstructure, and metabolite changes were [...] Read more.

This study explored the protective effects of antifreeze glycopeptide and alginate on the quality of −18 °C frozen lamb meatballs across various storage periods. Methods: Measurements of volatile salt nitrogen (TVB-N), thiobarbituric acid (TBARS), water retention, water distribution, microstructure, and metabolite changes were taken in the lamb meatballs. Results: The results showed that the addition of antifreeze glycopeptides (AFGs) significantly preserved the quality characteristics of lamb meatballs. In particular, the 0.30% antifreeze glycopeptide demonstrated the strongest protective effect on water retention and metabolites during freezing. The ice crystal area within the microstructure of lamb meatballs with added antifreeze glycopeptides was markedly reduced compared to the others after 14 days of freezing (p < 0.05). Additionally, AFGs lessened the lipid oxidation reaction and prolonged the oxidation time of lamb after 28 days of freezing. Conclusion: In summary, AFGs beneficially affected the quality of frozen lamb meatballs and are a potential, safe, and efficient cryoprotectant. Full article

(This article belongs to the Section Food Metabolomics)

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59 pages, 2893 KiB

Open AccessReview

Nanomedicines Targeting Metabolic Pathways in the Tumor Microenvironment: Future Perspectives and the Role of AI

by Shuai Fan, Wenyu Wang, Wenbo Che, Yicheng Xu, Chuan Jin, Lei Dong and Qin Xia

Metabolites 2025, 15(3), 201; https://doi.org/10.3390/metabo15030201 - 13 Mar 2025

Abstract

Background: Tumor cells engage in continuous self-replication by utilizing a large number of resources and capabilities, typically within an aberrant metabolic regulatory network to meet their own demands. This metabolic dysregulation leads to the formation of the tumor microenvironment (TME) in most solid [...] Read more.

Background: Tumor cells engage in continuous self-replication by utilizing a large number of resources and capabilities, typically within an aberrant metabolic regulatory network to meet their own demands. This metabolic dysregulation leads to the formation of the tumor microenvironment (TME) in most solid tumors. Nanomedicines, due to their unique physicochemical properties, can achieve passive targeting in certain solid tumors through the enhanced permeability and retention (EPR) effect, or active targeting through deliberate design optimization, resulting in accumulation within the TME. The use of nanomedicines to target critical metabolic pathways in tumors holds significant promise. However, the design of nanomedicines requires the careful selection of relevant drugs and materials, taking into account multiple factors. The traditional trial-and-error process is relatively inefficient. Artificial intelligence (AI) can integrate big data to evaluate the accumulation and delivery efficiency of nanomedicines, thereby assisting in the design of nanodrugs. Methods: We have conducted a detailed review of key papers from databases, such as ScienceDirect, Scopus, Wiley, Web of Science, and PubMed, focusing on tumor metabolic reprogramming, the mechanisms of action of nanomedicines, the development of nanomedicines targeting tumor metabolism, and the application of AI in empowering nanomedicines. We have integrated the relevant content to present the current status of research on nanomedicines targeting tumor metabolism and potential future directions in this field. Results: Nanomedicines possess excellent TME targeting properties, which can be utilized to disrupt key metabolic pathways in tumor cells, including glycolysis, lipid metabolism, amino acid metabolism, and nucleotide metabolism. This disruption leads to the selective killing of tumor cells and disturbance of the TME. Extensive research has demonstrated that AI-driven methodologies have revolutionized nanomedicine development, while concurrently enabling the precise identification of critical molecular regulators involved in oncogenic metabolic reprogramming pathways, thereby catalyzing transformative innovations in targeted cancer therapeutics. Conclusions: The development of nanomedicines targeting tumor metabolic pathways holds great promise. Additionally, AI will accelerate the discovery of metabolism-related targets, empower the design and optimization of nanomedicines, and help minimize their toxicity, thereby providing a new paradigm for future nanomedicine development. Full article

(This article belongs to the Special Issue Drug Metabolism and New Drug Development for Cancers)

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20 pages, 7736 KiB

Open AccessArticle

Predicting the Rate Structure of an Evolved Metabolic Network

by Friedrich Srienc and John Barrett

Metabolites 2025, 15(3), 200; https://doi.org/10.3390/metabo15030200 - 13 Mar 2025

Abstract

Background: When glucose molecules are metabolized by a biological cell, the molecules are constrained to flow along distinct reaction trajectories, which are defined by the cell’s underlying metabolic network. Methods: Using the computational technique of Elementary Mode Analysis, the entire set [...] Read more.

Background: When glucose molecules are metabolized by a biological cell, the molecules are constrained to flow along distinct reaction trajectories, which are defined by the cell’s underlying metabolic network. Methods: Using the computational technique of Elementary Mode Analysis, the entire set of all possible trajectories can be enumerated, effectively allowing metabolism to be viewed in a discretized space. Results: With the resulting set of Elementary Flux Modes (EMs), macroscopic fluxes, (of both mass and energy) that cross the cell envelope can be computed by a simple, linear combination of the individual EM trajectories. The challenge in this approach is that the usage probability of each EM is unknown. But, because the analytical framework we have adopted allows metabolism to be viewed in a discrete space, we can use the mathematics of statistical thermodynamics to derive the usage probabilities when the system entropy is maximized. The resulting probabilities, which obey a Boltzmann-type distribution, predict a rate structure for the metabolic network that is in remarkable agreement with experimentally measured rates of adaptively evolved E. coli strains. Conclusions: Thus, in principle, the intracellular dynamic properties of such bacteria can be predicted, using only the knowledge of the DNA sequence, to reconstruct the metabolic reaction network, and the measurement of the specific glucose uptake rate. Full article

(This article belongs to the Special Issue Recent Developments and Emerging Trends in Metabolic Modelling and Metabolomics)

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14 pages, 2223 KiB

Open AccessArticle

Metal Ion Reduction, Chelation, and Cytotoxicity of Selected Bicyclic Monoterpenes and Their Binary Mixtures

by Karolina Wojtunik-Kulesza, Marcela Dubiel and Katarzyna Klimek

Metabolites 2025, 15(3), 199; https://doi.org/10.3390/metabo15030199 - 13 Mar 2025

Abstract

Background/Objectives: Bicyclic monoterpenes are one of the most common groups of secondary plant metabolites found in Nature. Their wide spectrum of biological activity can be used in the prevention and in the treatment of various diseases, including so-called ‘diseases of civilization’. Their [...] Read more.

Background/Objectives: Bicyclic monoterpenes are one of the most common groups of secondary plant metabolites found in Nature. Their wide spectrum of biological activity can be used in the prevention and in the treatment of various diseases, including so-called ‘diseases of civilization’. Their potential for synergistic interactions may influence the biological activities of more complex mixtures. Methods: This study investigated the ability of selected bicyclic monoterpenes and their binary mixtures to reduce Fe(III) and Cu(II) and chelate Fe(II) and assessed their cytotoxic activity against BJ and HepG2 cell lines. Results: The obtained results did not reveal synergistic interactions towards the biological activities, but binary mixtures proved to be safe in relation to the tested cell lines. Among the tested single monoterpenes, the most effective were 3-carene and β-pinene, with the latter exhibiting the greatest ability to decrease cell viability (CC₅₀ for BJ and HepG2 cells was about 1.08 and 1.85 mM, respectively). Conclusions: The results revealed that both single compounds and binary mixtures demonstrate the ability to reduce selected metal ions and chelate Fe(II) ions. Synergistic interactions were not observed, but an increase in the activity of selected binary mixtures was recorded. Based on cell culture experiments, the monoterpenes and their binary mixtures can be considered safe at a concentration lower than 1 mM and close to 0.313 mM, respectively. Full article

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

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16 pages, 670 KiB

Open AccessOpinion

The Therapeutic Potential of Orange Juice in Cardiac Remodeling: A Metabolomics Approach

by Priscila Portugal dos Santos, Anderson Seiji Soares Fujimori, Bertha Furlan Polegato and Marina Politi Okoshi

Metabolites 2025, 15(3), 198; https://doi.org/10.3390/metabo15030198 - 13 Mar 2025

Abstract

Cardiovascular diseases are a leading cause of death worldwide, and the process of cardiac remodeling lies at the core of most of these diseases. Sustained cardiac remodeling almost unavoidably ends in progressive muscle dysfunction, heart failure, and ultimately death. Therefore, in order to [...] Read more.

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

(This article belongs to the Section Advances in Metabolomics)

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Graphical abstract

15 pages, 1618 KiB

Open AccessArticle

Executive Functions and Long-Term Metabolic Control in Adults with Phenylketonuria (PKU)

by Anne Tomm, Alena G. Thiele, Carmen Rohde, Haiko Schlögl, Wieland Kiess and Skadi Beblo

Metabolites 2025, 15(3), 197; https://doi.org/10.3390/metabo15030197 - 12 Mar 2025

Abstract

Background/Objectives: Phenylketonuria (PKU) is a rare inherited metabolic disorder caused by phenylalanine hydroxylase deficiency, resulting in highly elevated blood phenylalanine (Phe) concentrations, leading to neurotoxic effects. Despite advancements in treatment, adult patients with PKU may experience impairments in executive functions (EFs). This study [...] Read more.

Background/Objectives: Phenylketonuria (PKU) is a rare inherited metabolic disorder caused by phenylalanine hydroxylase deficiency, resulting in highly elevated blood phenylalanine (Phe) concentrations, leading to neurotoxic effects. Despite advancements in treatment, adult patients with PKU may experience impairments in executive functions (EFs). This study investigates the influence of metabolic control across different life stages on EFs and sociodemographic outcomes in adult PKU. Methods: We conducted a monocentric study with 36 early-diagnosed and treated PKU patients (mean age: 34.8 years). EFs were assessed using the Test Battery for Attentional Performance (TAP) and the Tower of London (TL-D). Metabolic data were extracted from medical records, focusing on childhood and adulthood metabolic control, including Phe fluctuations. Sociodemographic data were collected via questionnaires. Statistical analyses explored relationships between EFs, metabolic control, and sociodemographic data. Results: EFs in the cohort were within the lower average range. Significant negative correlations could be observed between EF performance and dried blood Phe concentrations during childhood (ages 0–10 years) as well as current Phe concentrations and Phe variation. Elevated childhood Phe concentrations were associated with lower educational attainment. Sociodemographic characteristics, such as employment status and living arrangements, aligned with those of the general population. Conclusions: Optimal cognitive development in PKU requires good metabolic control, particularly in early childhood. In adulthood, while dietary restrictions may be relaxed, maintaining low and stable Phe concentrations is crucial for EFs. Consistent monitoring and tailored therapeutic approaches throughout life seem essential for optimizing metabolic and neurocognitive outcome in PKU. Full article

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

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14 pages, 2048 KiB

Open AccessArticle

Apolipoproteins in Psoriasis: The Effect of Acitretin Treatment and UVB Phototherapy

by Hanna Myśliwiec, Dorota Kozłowska, Katarzyna Hodun, Bartłomiej Łukaszuk, Agnieszka Owczarczyk-Saczonek, Adrian Chabowski and Iwona Flisiak

Metabolites 2025, 15(3), 196; https://doi.org/10.3390/metabo15030196 - 12 Mar 2025

Abstract

Background: Psoriasis is a chronic, multi-system inflammatory disease frequently associated with metabolic syndrome and lipid disturbances. Apolipoproteins, as essential regulators of lipid metabolism, may play a critical role in these metabolic abnormalities, potentially influencing disease severity and systemic inflammation. The aim of this [...] Read more.

Background: Psoriasis is a chronic, multi-system inflammatory disease frequently associated with metabolic syndrome and lipid disturbances. Apolipoproteins, as essential regulators of lipid metabolism, may play a critical role in these metabolic abnormalities, potentially influencing disease severity and systemic inflammation. The aim of this study was to compare serum concentrations of chosen apolipoproteins in patients with psoriasis before and after treatment with acitretin or narrowband UVB (NB-UVB). Methods: This study was conducted on 39 patients with psoriasis. The concentration of nine apolipoproteins and C-reactive protein was quantified using the Bio-Plex Immunoassay Kit. Results: The serum concentrations of ApoA2, ApoC1, ApoD, ApoE, and ApoJ were higher in the acitretin group compared to the NB-UVB group before treatment, while the ApoA1/ApoA2 ratio was lower. We also observed a negative association between the Psoriasis Area and Severity Index (PASI) and ApoA1/ApoA2 ratio in the patients before the treatment. Conclusions: The results of this study confirm the presence of metabolic disturbances in psoriatic patients. The treatment with NB-UVB or acitretin did not cause any significant changes in the apolipoproteins profile. Thus, we found no detrimental impact of acitretin on the apolipoproteins profile, despite the observed rise in total cholesterol concentration after the treatment. Further research is needed to explore whether specific therapeutic approaches can modify these disturbances and potentially improve long-term cardiovascular outcomes in this population. Full article

(This article belongs to the Special Issue Psoriasis and Metabolic Syndrome)

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