Metabolomics最新文献

{"title":"Impact of matched samples on domain harmonization in cross-cohort NMR metabolomics.","authors":"A Ottas, L Goldoni, A Armirotti, S Decherchi","doi":"10.1007/s11306-026-02543-0","DOIUrl":"10.1007/s11306-026-02543-0","url":null,"abstract":"<p><strong>Introduction: </strong>Machine learning models trained on metabolomics data frequently show reduced performance when applied to independent cohorts because of domain shifts introduced by differences in analytical platforms, sample handling, storage conditions, and metabolite quantification procedures. Robust approaches for harmonizing metabolomics datasets across cohorts are therefore needed to improve model transferability and reproducibility.</p><p><strong>Objectives: </strong>To evaluate the impact of matched samples on domain harmonization and cross-cohort prediction performance in NMR metabolomics data, and to compare multiple harmonization strategies for improving model generalization across independently acquired datasets.</p><p><strong>Methods: </strong>A machine-learning framework was developed to classify ICD-10 code I50.9 (unspecified heart failure) using plasma NMR metabolomics data from the Estonian Biobank. Models were trained on a source dataset comprising 12,000 samples measured at Nightingale Health and evaluated on an independently measured destination dataset of 295 samples acquired on a different NMR platform. Harmonization approaches included within-domain normalization, Optimal Transport, Bridge mapping, and Empirical Bayes correction. The effect of matched samples was assessed using up to 108 duplicated biospecimens measured in both datasets. Additional validation was performed using independently generated human gestational diabetes and mouse diabetes metabolomics datasets from Metabolomics Workbench.</p><p><strong>Results: </strong>Domain harmonization generally improved cross-cohort prediction compared with unaligned data, particularly when matched samples were available. Predictive performance increased as the number of matched samples used for calibration increased, although gains varied across methods. Nevertheless, simple within-domain normalization consistently provided strong performance and often matched or exceeded more complex alignment approaches. External validation using fully unmatched human and mouse metabolomics datasets demonstrated that harmonization strategies improved classification performance relative to raw data, supporting the broader applicability of the framework.</p><p><strong>Conclusion: </strong>Matched samples substantially enhance domain harmonization and improve the transferability of metabolomics prediction models across analytical platforms and cohorts. However, robust normalization remains a strong baseline, and the benefits of more sophisticated alignment methods depend on the availability and representativeness of matched reference samples. These findings provide practical guidance for developing reproducible cross-cohort metabolomics machine-learning models while preserving biologically relevant signals.</p>","PeriodicalId":18506,"journal":{"name":"Metabolomics","volume":"22 6","pages":""},"PeriodicalIF":3.5,"publicationDate":"2026-10-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13675295/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149207316","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Environmental drivers of metabolomic profiles within and between cryptic lineages of Montastraea cavernosa, the great star coral.","authors":"Dominique N Gallery, Evelyn A Abbott, Lisa A Rose, Alexa K Huzar, Karim D Primov, Camille P Brown, Payton L Bryant, Brian E Sedio, Mikhail V Matz","doi":"10.1007/s11306-026-02545-y","DOIUrl":"https://doi.org/10.1007/s11306-026-02545-y","url":null,"abstract":"<p><strong>Introduction: </strong>Reef restoration practitioners aim to preserve coral genetic diversity by protecting reefs and cultivating diverse genotypes in coral nurseries. However, cryptic genetic lineages in most corals complicate restoration strategies, as the role of between-lineage genetic divergence remains unclear regarding adaptation. In Montastraea cavernosa, researchers have identified cryptic lineages, some strongly segregated by depth.</p><p><strong>Objectives: </strong>We aimed to quantify lineage-specific responses to the environment that explain the genetic and ecological divergence between the two lineages.</p><p><strong>Methods: </strong>We conducted a ten-week reciprocal transplantation experiment using two cryptic lineages restricted to shallow water (< 10 m depth), with one lineage more common on nearshore reefs and the other on offshore reefs. Following transplantation, we analyzed the corals' growth and metabolomic response to transplantation.</p><p><strong>Results: </strong>Surprisingly, the strongest response was not lineage-specific. Instead, both lineages exhibited significant and similar changes in growth and metabolomic profiles, depending on the final habitat they were transplanted to.</p><p><strong>Conclusion: </strong>These results suggest that cryptic lineages employ similar mechanisms of adaptation and acclimatization to environmental challenges at the metabolite level, despite their genetic distinction.</p>","PeriodicalId":18506,"journal":{"name":"Metabolomics","volume":"22 6","pages":""},"PeriodicalIF":3.5,"publicationDate":"2026-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13653957/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149170555","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Metabolic basis of post-infectious sequelae after Ebola virus disease.","authors":"Anna C Sanford, Nell G Bond, Samuel Ficenec, Charlotte Osterman, Payton Farkas, Emily Engel, Bronwyn Gunn, Donald S Grant, Robert Samuels, Kevin J Zwezdaryk, John S Schieffelin","doi":"10.1007/s11306-026-02544-z","DOIUrl":"10.1007/s11306-026-02544-z","url":null,"abstract":"<p><strong>Introduction: </strong>Ebola virus disease (EVD) survivors often present with clinical sequelae after acute disease resolution, called post-Ebola syndrome (PES). Why some survivors develop these sequelae and others do not is poorly defined. Altered metabolism has been noted in acute EVD but has not been studied in PES. Here, we identified distinct metabolic pathways in EVD survivors with PES compared to asymptomatic survivors and potential biomarkers of PES.</p><p><strong>Objectives: </strong>The purpose of this study was to determine if EVD survivors with PES demonstrated differential metabolism compared to asymptomatic EVD survivors.</p><p><strong>Methods: </strong>Plasma was collected from EVD survivors in Sierra Leone as part of an ongoing cohort study. Untargeted metabolomics (LC-MS/MS) was performed on survivors with and without sequelae as well as household contacts. Univariate, multivariate, biomarker and pathway analyses were performed in MetaboAnalyst. Spearman's R correlation was performed using JMP.</p><p><strong>Results: </strong>We identified differential expression of metabolites involved in multiple metabolic pathways in EVD survivors with PES compared to asymptomatic survivors. These pathways include the tricarboxylic acid cycle as well as amino acid, nucleotide, and short chain fatty acid metabolism. Several of these pathways are associated with immune dysfunction. The identified metabolites have potential use as biomarkers of PES.</p><p><strong>Conclusion: </strong>EVD survivors with PES exhibit differing metabolism compared to asymptomatic EVD survivors in several pathways. Other studies have linked these pathways to immune dysfunction and chronic viral infection, however further immunometabolic studies of EVD survivors with PES are needed.</p>","PeriodicalId":18506,"journal":{"name":"Metabolomics","volume":"22 6","pages":""},"PeriodicalIF":3.5,"publicationDate":"2026-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13653831/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149170559","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Metabolic profiling of retinal organoids reveals conserved core metabolites and alterations in glycolytic and amino acid metabolism.","authors":"Pragati Gupta, Claudia Wiesner, Focke Ziemssen, Jeroen Klevering, Purva Kulkarini, Zohreh Hosseinzadeh","doi":"10.1007/s11306-026-02523-4","DOIUrl":"https://doi.org/10.1007/s11306-026-02523-4","url":null,"abstract":"<p><strong>Introduction: </strong>Retinal organoids have emerged as powerful models of retinal development and disease; however, the extent to which they recapitulate the metabolic landscape of the native retina remains largely unknown.</p><p><strong>Objectives: </strong>This study aimed to compare the metabolomic profiles of mouse retina and mouse embryonic stem cell-derived retinal organoids and to evaluate metabolic changes during organoid maturation.</p><p><strong>Methods: </strong>Untargeted gas chromatography mass spectrometry based metabolomic profiling was performed on intracellular metabolites from mouse retina at postnatal day 3 and mouse retinal organoids (MROs) at differentiation day 28, together with conditioned media collected during organoid maturation.</p><p><strong>Results: </strong>Across mouse retina and retinal organoids, 166 annotated compounds were included in the analysis . Of these, 148 were shared between the two sample types. Using a bidirectional fold-change threshold, differential analysis showed that mouse retinal organoids preserved a substantial metabolic signature shared with mouse retina. However, selective differences were observed in the abundance of glycolysis-associated metabolites and pentose phosphate intermediates including glucose-6-phosphate and ribulose-5-phosphate, as well as tricarboxylic acid-cycle-associated metabolites including citric acid, fumaric acid and oxalic acid. Pathway enrichment analysis identified significant alterations in alanine, aspartate, and glutamate metabolism. Media analysis further revealed stage-dependent changes in extracellular glutamate and glycine abundance during organoid maturation.</p><p><strong>Conclusion: </strong>MRO retains major components of retinal metabolic organization while exhibiting features suggestive of incomplete metabolic maturation compared with native retina. These findings provide valuable insight into MRO metabolic fidelity and guide future optimization strategies.</p>","PeriodicalId":18506,"journal":{"name":"Metabolomics","volume":"22 6","pages":""},"PeriodicalIF":3.5,"publicationDate":"2026-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13653828/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149166305","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Multi-reflecting time-of-flight mass spectrometry enables high-accuracy metabolite identification in a demonstration study using serum samples from COVID-19 patients.","authors":"Adam King, Eleanor Matthews, Garth Maker, Robert Trengove, Shaufa Shareef, Stephen Fowler, Timothy Felton, Angela Simpson, Martin Palmer, Lee A Gethings, Robert S Plumb, E N Clare Mills","doi":"10.1007/s11306-026-02539-w","DOIUrl":"10.1007/s11306-026-02539-w","url":null,"abstract":"<p><strong>Introduction: </strong>Accurate metabolite identification remains a major challenge in untargeted metabolomics due to overlapping signals, isomeric compounds, and insufficient mass resolution. The multi-reflecting time-of-flight (MRT) platform provides mass resolution exceeding 200,000 Full Width at Half Maximum and sub-ppm mass accuracy, enabling detailed isotopic fine structure analysis.</p><p><strong>Objectives: </strong>The performance of the MRT platforms in identifying lipids and metabolites was evaluated using selected serum samples from a group of hospitalized COVID-19 patients.</p><p><strong>Methods: </strong>Lipids and polar metabolites were extracted from human serum samples from the Manchester Asthma, Allergy and Thoracic Surgery Biobank and analysed using the MRT platform with data-independent acquisition.</p><p><strong>Results: </strong>The MRT platform facilitated the resolution of overlapping lipid species and improved annotation confidence. In a pilot cohort (n = 8), metabolomic differences associated with disease severity were observed, alongside annotation of clinically relevant metabolites including sulphated bile acids and retained iohexol associated with renal dysfunction.</p><p><strong>Conclusions: </strong>These findings demonstrate that MRT platform enhances confidence in metabolite identification and supports high-throughput metabolomics, offering significant potential for biomarker discovery in clinical studies.</p>","PeriodicalId":18506,"journal":{"name":"Metabolomics","volume":"22 5","pages":""},"PeriodicalIF":3.5,"publicationDate":"2026-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13633998/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149111848","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Metabonaut: an open educational resource for learning reproducible, script-based untargeted LC-MS/MS metabolomics.","authors":"Philippine Louail, Marilyn De Graeve, Alexandru Mahmoud, Daniel Marques de Sá E Silva, Kozo Nishida, Vilhelm Suksi, Anna Tagliaferri, Gabriele Tomè, Vinicius Verri Hernandes, Johannes Rainer","doi":"10.1007/s11306-026-02538-x","DOIUrl":"10.1007/s11306-026-02538-x","url":null,"abstract":"<p><strong>Background: </strong>Two decades after the Metabolomics Standards Initiative, public deposition of raw LC-MS/MS data into archives such as MetaboLights, Metabolomics Workbench, GNPS and MassBank has matured, but the analyses that turn raw files into reported feature tables remain difficult to share, audit and reuse. The FAIR principles, originally formulated for data, later extended to research software and to workflows, make a strong case that this gap matters; we adopt that view and ask how an educational resource can help researchers cross it.</p><p><strong>Aim of review: </strong>This is an educational review where we describe the principles of FAIR and reproducible analysis as they apply to untargeted LC-MS metabolomics, and we show how those principles are realised in Metabonaut, an open educational resource built on top of the R for Mass Spectrometry/Bioconductor ecosystem. Metabonaut provides executable example workflows from raw mzML files to annotated feature tables, demonstrates interoperability across programming languages, and is built with and for the community.</p><p><strong>Key scientific concepts of review: </strong>After a brief tour of the underlying software ecosystem and of literate programming, the review discusses three topics, each through one or more Metabonaut vignettes: visual inspection and quality control, reuse of public archives at scale, and cross-language interoperability. Together, they teach how to carry FAIR practice from data to analysis: making the analysis itself, and not only the data it consumes, shareable, auditable and reusable. The source code of Metabonaut and links to pre-rendered workflow documents are available at https://github.com/RforMassSpectrometry/Metabonaut .</p>","PeriodicalId":18506,"journal":{"name":"Metabolomics","volume":"22 5","pages":""},"PeriodicalIF":3.5,"publicationDate":"2026-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13634014/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149111871","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Metabolomic biomarkers and metabolic remodelling in genetically characterised hypertrophic cardiomyopathy: a systematic review.","authors":"Ammar Hariz Ahmad Razmy, Normala Abd Latip, Sharaniza Ab-Rahim, Siti Hamimah Sheikh Abdul Kadir","doi":"10.1007/s11306-026-02526-1","DOIUrl":"10.1007/s11306-026-02526-1","url":null,"abstract":"<p><strong>Introduction: </strong>Hypertrophic cardiomyopathy (HCM) is the most common inherited cardiomyopathy and a major cause of heart failure, malignant arrhythmias and sudden cardiac death. Although pathogenic variants in sarcomeric genes such as MYBPC3, MYH7, TNNT2, and TNNI3 are well-recognised contributors to the disease, the mechanisms linking these mutations to the heterogeneous phenotypes remain poorly understood. Increasing evidence suggests that HCM is fundamentally associated with disturbances in myocardial energetics and metabolic remodelling.</p><p><strong>Objectives: </strong>This systematic review aimed to synthesise metabolomic evidence from genetically characterised HCM cohorts, with three specific objectives: (1) to characterise the metabolic pathways dysregulated in HCM, (2) to determine whether distinct metabolic signatures are associated with specific sarcomeric gene variants and (3) to evaluate the diagnostic, prognostic, and therapeutic relevance of identified metabolite biomarkers in HCM management. By explicitly examining whether genotype-specific metabolomic signatures exist in the current literature, this review addresses a question of direct relevance to precision medicine approaches in HCM.</p><p><strong>Methods: </strong>A systematic search of PubMed, Scopus and Web of Science identified 14 eligible studies comprising 1511 participants.</p><p><strong>Results: </strong>Most studies employed liquid chromatography-mass spectrometry (LCMS) based metabolomics using plasma or myocardial tissue samples. Across studies, recurrent metabolic alterations were observed in pathways related to fatty acid oxidation, branched-chain amino acid (BCAA) metabolism, ketone body utilisation, tricarboxylic acid (TCA) cycle intermediates and lipid metabolism. Circulating acyl carnitines, amino acids, and eicosanoid metabolites were among the most frequently reported biomarkers associated with disease presence or severity. Myocardial tissue analyses demonstrated impaired mitochondrial energetics, reductions in high-energy phosphate metabolites, and shifts toward alternative metabolic substrates.</p><p><strong>Conclusion: </strong>No distinct genotype-specific metabolic signature was identified across studies; the metabolic remodelling pattern reflected phenotypic severity rather than the causal variants. While metabolomics shows potential in improving disease characterisation and biomarker discovery, further longitudinal and externally validated studies are required before clinical translation.</p>","PeriodicalId":18506,"journal":{"name":"Metabolomics","volume":"22 5","pages":""},"PeriodicalIF":3.5,"publicationDate":"2026-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13633945/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149111859","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The chemical blueprint of Trichoderma for next-generation microbial biostimulants.","authors":"Thuso Mudau, Lerato Pertunia Tshehlane, Keabetswe Tebogo Ncube, Fidele Tugizimana","doi":"10.1007/s11306-026-02531-4","DOIUrl":"10.1007/s11306-026-02531-4","url":null,"abstract":"<p><strong>Introduction: </strong>Microbial biostimulants comprise beneficial microorganisms, such as Bacillus and Trichoderma, that enhance plant growth, nutrient uptake, and stress tolerance through biological mechanisms. The combined use of Bacillus and Trichoderma is increasingly recognised as an important strategy for enhanced crop productivity and sustainable agriculture. However, the compatibility of microorganisms is constrained by their distinct ecological niche and metabolic activities, which may limit the stability of consortia.</p><p><strong>Objectives: </strong>To characterize the biochemical landscape of Trichoderma strains and evaluate their metabolic compatibility with the Bacillus consortium.</p><p><strong>Methods: </strong>Metabolites were extracted from each Trichoderma strain using LC-MS grade quality methanol. The methanolic extracts were analysed on a UPLC-MS system. Principal component analysis and orthogonal partial least squares discriminant analysis were performed to assess sample clustering and overall metabolic variation among Trichoderma strains. Feature-based molecular networking was used for metabolite annotation of Trichoderma's chemical space. Functional analysis was used to map annotated metabolites in the metabolic pathways of Trichoderma strains.</p><p><strong>Results: </strong>The findings revealed distinct metabolic markers, including primary and secondary metabolites. The sphingolipid metabolism was significantly impacted, among others. The in vitro studies revealed a positive interaction with no evidence of antagonism between Trichoderma strains and the Bacillus consortium.</p><p><strong>Conclusion: </strong>The major constraint of biostimulant application is the lack of standardisation in product composition. Therefore, these findings provide insights into the molecular composition and functional dynamics of microbial networks. Such knowledge is crucial and essential for the development of cutting-edge innovations in the field of biostimulants.</p>","PeriodicalId":18506,"journal":{"name":"Metabolomics","volume":"22 5","pages":""},"PeriodicalIF":3.5,"publicationDate":"2026-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13633993/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149111885","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Synergistic lipase inhibition by Garcinia parvifolia metabolites: a ¹H NMR-based metabolomic deciphering of ligand interactions.","authors":"Ahmad Iqbal Noordin, Fazleen Izzany Abu Bakar, Fiffy Hanisdah Saikim, Santad Wichienchot, Azizul Isha, Mohd Fadzelly Abu Bakar","doi":"10.1007/s11306-026-02536-z","DOIUrl":"10.1007/s11306-026-02536-z","url":null,"abstract":"<p><strong>Introduction: </strong>The rising prevalence of obesity and metabolic disorders has intensified the demand for sustainable, plant-based functional ingredients for weight management. Garcinia parvifolia, an underutilized tropical fruit native to Malaysian Borneo, represents a promising natural source of anti-obesity compounds.</p><p><strong>Objectives: </strong>This study aimed to decipher the complex, ligand interactions responsible for pancreatic lipase inhibition in G. parvifolia using a multi-disciplinary metabolomics-driven approach.</p><p><strong>Methods: </strong>Extracts of varying polarities (70% ethanol, acetone, chloroform, and hexane) were analyzed using ¹H NMR-based metabolomics, in vitro p-nitrophenyl butyrate (p-NPB) lipase assays, and in silico molecular docking.</p><p><strong>Results: </strong>The results demonstrated that solvent polarity critically dictates chemical diversity, with the 70% ethanol extract yielding the highest metabolite abundance and the strongest lipase inhibitory activity (IC₅₀ = 85.3 µg/mL). Multivariate data analyses, including Principal Component Analysis (PCA) and Partial Least Squares (PLS), revealed that this bioactivity is not driven by a single isolated compound, but rather by a synergistic combination of polar phenolic and aromatic metabolites, alongside supportive amino and organic acids. Molecular docking validated the inhibitory potential of key annotated metabolites, demonstrating that compounds such as catechin, β-sitosterol, and β-caryophyllene interact with the enzyme via reversible hydrogen bonding, van der Waals forces, and hydrophobic interactions, exhibiting binding affinities of - 6.09, - 6.34, and - 5.19 kcal/mol, respectively.</p><p><strong>Conclusion: </strong>These findings establish G. parvifolia as a viable, sustainable, and multi-targeted plant-based alternative to synthetic fat blockers. Its integration into functional foods and anti-obesity nutraceutical formulations offers significant potential for advancing preventive and personalized nutrition.</p>","PeriodicalId":18506,"journal":{"name":"Metabolomics","volume":"22 5","pages":""},"PeriodicalIF":3.5,"publicationDate":"2026-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13633999/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149111844","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Metabolome analyses of the rumen, feces and blood reveal separate and simultaneous impacts of increased dietary concentrate and hindgut starch flow in Holstein cows.","authors":"Ezequias Castillo-Lopez, Markus Aigensberger, Rana Muhammad Atif, Patrick Biber, Thomas Hartinger, Sabina Raykova, Alejandra Guerrero-Lavin, Nicole Reisinger, Heidi E Schwartz-Zimmermann, Franz Berthiller, Qendrim Zebeli","doi":"10.1007/s11306-026-02519-0","DOIUrl":"10.1007/s11306-026-02519-0","url":null,"abstract":"<p><strong>Introduction: </strong>The combined effects of increased dietary concentrate and hindgut starch supply on the cow metabolome remain poorly understood.</p><p><strong>Objective: </strong>To evaluate the impacts of high concentrate feeding and the impacts of increased hindgut starch supply on the metabolome of rumen, feces and blood of Holstein cows.</p><p><strong>Methods: </strong>Either a 40% (Control) or a 65% concentrate diet (High) was fed. In addition, cows were abomasally infused with either water or starch (3 kg/day). Metabolomic analysis of rumen, feces and blood were performed with HPLC-MS/MS and anion exchange chromatography coupled to high-resolution mass spectrometry.</p><p><strong>Results: </strong>Ruminal pH duration < 5.8 was 69 and 249 min/day for Control and High, respectively; fecal pH was 6.58 and 6.33 for water- or starch-infused cows, respectively. Independent of abomasal starch infusion, High increased ruminal concentration of several amino acids, nucleosides, and lipid-related metabolites, and enriched metabolic pathways for purine metabolism, urea cycle and amino acid metabolism. In feces, both High and abomasal starch infusion increased metabolites related to fatty acid and nitrogen metabolism, and enriched pathways for bile acid biosynthesis, amino acid metabolism, α-linolenic acid and biotin metabolism. In blood, Control enriched metabolic pathways for amino sugar metabolism, aspartate metabolism, fatty acid biosynthesis and malate-aspartate shuttle, regardless of abomasal starch infusion.</p><p><strong>Conclusion: </strong>High enhanced metabolic pathways mainly for ruminal nitrogen metabolism. Both High and abomasal starch infusion influenced fecal metabolic pathways; whereby, the increased ethanolamine suggests its potential as a biomarker for gut acidosis. Compared to abomasal starch infusion, High had greater impacts on the blood metabolome.</p>","PeriodicalId":18506,"journal":{"name":"Metabolomics","volume":"22 5","pages":""},"PeriodicalIF":3.5,"publicationDate":"2026-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13633985/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149111862","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}