PubMed

Metabolomics. 2025 May 17;21(3):68. doi: 10.1007/s11306-025-02258-8.ABSTRACTBACKGROUND: While anthracyclines, commonly used in cancer treatment, are well known to cause cardiotoxicity, no validated biomarkers currently exist that can predict the early development of doxorubicin-induced cardiotoxicity (DIC). Therefore, identifying early biomarkers of DIC is urgently needed. Metabolomics approaches have been used to elucidate this relationship and identified related metabolite markers. However, differences in pre-clinical model systems make it challenging to draw definitive conclusions from the discoveries and translate findings into clinical applications.AIM OF REVIEW: A systematic literature search on metabolomics studies of DIC was conducted with the goal to identify and compare study results reported using in vitro models, animal models, and studies from clinical patients. Metabolites identified across all studies were pooled to uncover biologically meaningful patterns that are significantly enriched in the data. Finally, pooled metabolites perturbed by DIC were mapped to metabolic pathways to explore potential pathological implications.RESULTS: We reviewed 28 studies published between 2000 and 2024 that utilized metabolomics approaches to investigate DIC. The included studies used a variety of analytical techniques, including LC-MS, GC-MS, and NMR. The analysis revealed that metabolites such as inosine, phenylalanine, arginine, and tryptophan were commonly perturbed across all study models, with carnitine metabolism and purine and pyrimidine metabolism being the most affected pathways. Metabolite Set Enrichment Analysis (MSEA) using MetaboAnalyst identified the arginine biosynthesis, citrate cycle, and alanine, aspartate, and glutamate metabolism pathways as significantly enriched.CONCLUSION: These findings underscore the potential of metabolomics in identifying early biomarkers for DIC, providing a foundation for future studies aimed at preventing cardiotoxicity and improving treatment strategies for cancer patients receiving DOX-containing therapies.KEY SCIENTIFIC CONCEPTS OF REVIEW: Altogether, metabolomics studies suggest metabolic alterations in DIC, albeit little overlap between studies especially with animal and human studies. Attempts at intercepting these pathways have shown that intervention in DIC may be possible. Future research should focus on developing precise cardiotoxicity models that incorporate cancer metabolism, as these will be crucial in bridging the gap between laboratories (in vitro and animal models) and clinical studies to identify subclinical biomarkers in the early stage of DIC that can effectively identify new targets for interventions to reduce lethal cardiovascular disease risk.PMID:40381141 | DOI:10.1007/s11306-025-02258-8

Trop Anim Health Prod. 2025 May 17;57(5):224. doi: 10.1007/s11250-025-04467-8.ABSTRACTThis study aimed to evaluate the effects of parity and body condition score at calving on the metabolic profile of high-producing Holstein × Gyr cows during the transition period. Cows were divided into groups according to the parity: primiparous (n = 20), biparous (n = 20), multiparous (n = 20); and according to the BCS at calving: high (HBCS; > 3.5; n = 20), normal (NBCS; 3.0 - 3.5; n = 21), and low (LBCS; < 3.0; n = 15). BCS, serum non- esterified fatty acids (NEFA), beta-hydroxybutirate (BHB), cholesterol, total protein (TP), albumin, blood urea nitrogen (BUN), total calcium (Ca), phosphorus (P), magnesium (Mg), aspartateaminotransferase (AST), gamma-glutamyltransferase (GGT), and plasma glucose levels were measured on -21, -7, 0, 7, 21, and 42 days relative to parturition. Differences between parity groups were observed for most metabolites; however, these differences occurred at a few time points and were more frequent at 7 and 21 days in milk (DIM). At 21 DIM, primiparous cows had lower BCS, BHB, cholesterol, and TP values and intermediate NEFA and Mg values. Multiparous cows exhibited lower Ca values at calving than primiparous cows. Differences between groups according to BCS at calving were observed mainly at parturition and during early lactation. HBCS cows had significantly differences in NEFA values than LBCS cows at calving and in BHB values than LBCS cows at calving and at 7 and 21 DIM. Subclinical hypocalcemia at calving was the main imbalance (53.1%) mainly affecting multiparous cows. It can be concluded that well-nourished high-producing Holstein × Gyr cows are metabolically balanced, and that parity and BCS at calving do not significantly impact the metabolic profile of Holstein x Gyr cows.PMID:40381111 | DOI:10.1007/s11250-025-04467-8

Metabolomics. 2025 May 17;21(3):69. doi: 10.1007/s11306-025-02266-8.ABSTRACTINTRODUCTION: Sea lamprey (Petromyzon marinus) is a unique vertebrate model to examine how liver metabolomes support different reproductive functions. Juvenile sea lamprey prey on other fish species by attaching to their body and feeding on their blood and body fluids. Once reaching adulthood, they cease feeding, migrate to spawning streams and begin their final sexual maturation. During these processes, the male livers produce large quantities of bile acid pheromone precursors to be modified and released via gills, whereas the female livers synthesize vast amounts of vitellogenin (yolk lipophosphoprotein) to be transported to the ovary.OBJECTIVE: We aim to test the hypothesis that the liver metabolic pathways exhibit dramatic changes during sexual maturation of sea lampreys that support their reproductive strategies.METHODS: Liver tissues from prespermiating (PSM) and spermiating (SM) males, and preovulatory (POF) and ovulatory (OF) females were homogenized, extracted and analyzed using the Thermo Q-exactive Orbitrap UPLC/MS/MS. Progenesis QI, Compound Discoverer, and Metaboanalyst were used for alignment, peak picking, deconvolution, and annotation. Data were subjected to analyses such as PCA and PLS-DA, using the SIMCA® software. The glycogen and triglyceride content in liver were also examined to determine levels of stored energy.RESULTS: Overall, we found upregulations of amino acid and fatty acid metabolisms in mature male sea lamprey compared to the immature ones. Although the metabolic differences were comparatively subdued in the sexually immature males and females, amino acid regulation was slightly higher in females.CONCLUSION: We conclude that the metabolic dynamics in sea lamprey livers are consistent with their reproductive strategies.PMID:40381064 | DOI:10.1007/s11306-025-02266-8

J Agric Food Chem. 2025 May 17. doi: 10.1021/acs.jafc.4c11778. Online ahead of print.ABSTRACTDecabromodiphenyl ethane (DBDPE), an emerging ubiquitous contaminant, enters the food chain through crop bioaccumulation, threatening food safety. This study investigated the bioaccumulation, toxicity, and tolerance mechanisms of DBDPE in sugar beet. The results showed that DBDPE was absorbed by roots and transported to leaves in a constant proportion, with greater toxicity in leaves than in roots. Physiological analyses revealed that DBDPE induced chloroplastic dysfunction and oxidative stress in a concentration-dependent manner. The antioxidant system in response to DBDPE varied with exposure levels. Integrated transcriptomic, proteomic, and metabolomic analyses revealed that remodeling of jasmonic acid (JA) biosynthesis and consequent activation of JA signaling were critical for DBDPE tolerance. Exogenous JA and JA-Ile (active JA) maintained photosynthetic activity by protecting chloroplasts and mitigated oxidative damage by enhancing antioxidant system activity, thereby improving DBDPE tolerance. This study provides an insight into the development of effective mitigation strategies against DBDPE toxicity in crops.PMID:40380918 | DOI:10.1021/acs.jafc.4c11778

Carcinogenesis. 2025 May 17:bgaf024. doi: 10.1093/carcin/bgaf024. Online ahead of print.ABSTRACTCancer stem cells (CSCs) are the initiating cells of tumorigenesis, metastasis, and recurrence and play a crucial role in androgen deprivation therapy resistance, yet how sphingolipid metabolism promotes CSC maintenance remains exclusive. Here, we conducted gene expression profiling of sphere-derived castration-resistant prostate cancer stem cells (PCSCs) and identified enhanced sphingolipid de novo biosynthesis with upregulated DEGS2 expression in PCSCs. Silencing of DEGS2 significantly suppressed prostate cancer stem-like traits, cell growth, clonogenicity, and metastasis, while ectopic overexpression of DEGS2 showed the opposite effects. Mechanistically, DEGS2-synthesized phytoceramide activates PI3K-AKT signaling pathway to promote cancer stem-like characteristics, and activation of AKT reversed DEGS2-depletion-inhibited cancer stem-like properties. Clinically, prostate cancer tissues expressed higher levels of DEGS2 compared with adjacent normal tissue, and DEGS2 expression exhibits strong correlations with SOX2, CD133 and Snail expression in primary prostate carcinomas. Collectively, our data illustrate that DEGS2 dictates prostate cancer stem-like properties via the PI3K-AKT pathway, and disruption of this pathway provides potential therapeutic strategies for prostate cancer.PMID:40380873 | DOI:10.1093/carcin/bgaf024

Gut Pathog. 2025 May 16;17(1):30. doi: 10.1186/s13099-025-00706-3.ABSTRACTBACKGROUND: The impact of the fecal multidrug-resistant organism (MDRO) carriage on the gut microbiota, metabolite alterations, and cirrhosis-related complications remains unclear.METHODS: Eighty-eight patients with cirrhosis and 22 healthy volunteers were analyzed for plasma metabolites, fecal MDROs, and microbiota composition. The fecal bacterial and fungal composition was assessed using 16S ribosomal RNA and internal transcribed spacer sequencing, whereas plasma metabolomic analysis was evaluated via untargeted liquid chromatography-mass spectrometry. Predictors of cirrhosis-related outcomes, risk factors for MDRO carriage, and microbiota-metabolite correlations were analyzed.RESULTS: Fecal MDRO carriage was detected in 33% of patients with cirrhosis. MDRO carriers had a higher risk of hepatic encephalopathy (HE) compared to non-carriers (20.7% vs. 3.2%, p = 0.008). Patients carrying MDROs had higher plasma lipopolysaccharide (LPS) levels, and both elevated LPS and MDRO carriage independently predicted HE occurrence within 1 year. Compared with non-carriers, MDRO carriers had higher fecal bacterial and fungal burdens and exhibited different gut microbiota compositions, characterized by increased Streptococcus salivarius and enrichment of Saccharomycetes and Candida albicans. Thirty-one metabolites differed significantly among healthy controls, and patients with cirrhosis, with and without MDRO carriage. Six metabolites were significantly correlated with specific microbial taxa in MDRO carriers. Isoaustin, a fungal-derived metabolite, was significantly elevated in MDRO carriers with HE.CONCLUSIONS: Fecal MDRO carriage was associated with endotoxemia, altered gut microbiota, metabolic changes, and a higher risk of HE. It's worthy to monitor fecal MDRO colonization in cirrhosis.PMID:40380209 | DOI:10.1186/s13099-025-00706-3

J Transl Med. 2025 May 16;23(1):549. doi: 10.1186/s12967-025-06552-w.ABSTRACTINTRODUCTION: Gastrointestinal disorders (GIDs) affect nearly 40% of the global population, with gut microbiome-metabolome interactions playing a crucial role in gastric cancer (GC), colorectal cancer (CRC), and inflammatory bowel disease (IBD). This study aims to investigate how microbial and metabolic alterations contribute to disease development and assess whether biomarkers identified in one disease could potentially be used to predict another, highlighting cross-disease applicability.METHODS: Microbiome and metabolome datasets from Erawijantari et al. (GC: n = 42, Healthy: n = 54), Franzosa et al. (IBD: n = 164, Healthy: n = 56), and Yachida et al. (CRC: n = 150, Healthy: n = 127) were subjected to three machine learning algorithms, eXtreme gradient boosting (XGBoost), Random Forest, and Least Absolute Shrinkage and Selection Operator (LASSO). Feature selection identified microbial and metabolite biomarkers unique to each disease and shared across conditions. A microbial community (MICOM) model simulated gut microbial growth and metabolite fluxes, revealing metabolic differences between healthy and diseased states. Finally, network analysis uncovered metabolite clusters associated with disease traits.RESULTS: Combined machine learning models demonstrated strong predictive performance, with Random Forest achieving the highest Area Under the Curve(AUC) scores for GC(0.94[0.83-1.00]), CRC (0.75[0.62-0.86]), and IBD (0.93[0.86-0.98]). These models were then employed for cross-disease analysis, revealing that models trained on GC data successfully predicted IBD biomarkers, while CRC models predicted GC biomarkers with optimal performance scores.CONCLUSION: These findings emphasize the potential of microbial and metabolic profiling in cross-disease characterization particularly for GIDs, advancing biomarker discovery for improved diagnostics and targeted therapies.PMID:40380167 | DOI:10.1186/s12967-025-06552-w

BMC Musculoskelet Disord. 2025 May 16;26(1):487. doi: 10.1186/s12891-025-08725-6.ABSTRACTIn the context of global aging, osteoporosis has emerged as a significant public health concern, with a relatively high prevalence observed in plateau regions. This study aimed to investigate the effects and underlying mechanisms of high-fat diet (HFD) and hypoxic conditions on bone metabolism in mice. The mice were subjected to different dietary regimens (a HFD versus a normal diet) and placed in a hypoxic environment. This study explored relevant mechanisms through comprehensive assessments, including body and bone morphological indices, pathological examinations, biochemical analyses, evaluation of gut microbiota diversity, and metabolomics approaches. The results indicated that, compared with those in the control group, the body weight, Lee's index, body mass index (BMI), and body fat percentage of the HFD-fed group were significantly greater. Additionally, the femoral microstructure was compromised, bone metabolic markers were disrupted, inflammatory responses were heightened, gut microbiota diversity was altered, and specific intestinal metabolites such as Anserine were downregulated, whereas L-carnosine was upregulated. Spearman correlation analysis and network visualization elucidated the multifactorial influence mechanism of a HFD on bone metabolism under hypoxic conditions. These factors interconnect to form a complex network that drives osteoporosis development. Notably, L-carnosine occupies a central position within this network, serving as a key hub for interactions among various factors. Under the dual stressors of hypoxia and a HFD, this network becomes imbalanced, leading to bone metabolic disorders and osteoporosis. This study provides insights into the multifactorial mechanisms of osteoporosis induced by a HFD and hypoxia in mice, offering a foundation for subsequent research and preventive strategies for osteoporosis in plateau areas.PMID:40380162 | DOI:10.1186/s12891-025-08725-6

Arch Toxicol. 2025 May 16. doi: 10.1007/s00204-025-04074-4. Online ahead of print.ABSTRACTImproved prediction of drug-induced structural cardiotoxicity is required to reduce attrition driven by cardiac safety concerns in drug discovery. Omics measurements are well suited to this need, offering the potential to discover molecular signatures associated with toxicological endpoints. In addition, untargeted metabolomics can simultaneously measure xenobiotic fate within the test system. We present an extensive metabolomics study to discover a predictive metabolic signature of drug-induced structural cardiotoxicity. A human-relevant in vitro cardiac model, cardiac microtissues, were exposed to twelve xenobiotics (eight clinically labelled structural cardiotoxins and four non-cardiotoxic pharmaceuticals), each at two concentrations, for 6, 24, and 48 h. The measurements were made by direct-infusion and liquid-chromatography mass spectrometry from intracellular polar and lipid extracts, and spent culture medium, respectively. Data were used to quantify levels, and reveal the metabolic fate of the xenobiotics, and to simultaneously explore their effects on the cardiac microtissues. Xenobiotic quantification revealed free concentrations to be typically lower than nominal values, whilst discovery of xenobiotic-related features evidenced the biotransformation capacity of the microtissues. Both common and condition-specific effects of the xenobiotics on the intracellular metabolome, lipidome, and metabolic footprint were discovered. Moreover, metabolic signatures with capacity to predict structural cardiotoxicity were revealed. These included features representing several ceramides, energy metabolism intermediates, e.g. creatine, purine-related metabolites, and markers of oxidative stress, e.g. glutathione.PMID:40379885 | DOI:10.1007/s00204-025-04074-4

Sci Rep. 2025 May 16;15(1):17035. doi: 10.1038/s41598-025-01634-7.ABSTRACTAdvancements in large-scale analysis of metabolites in human peripheral blood samples revealed the links between metabolite concentrations and genetic variations. This field is known as metabolome-genome-wide association study (MGWAS). Although MGWAS is a powerful tool, it has some limitations, particularly in terms of the number of metabolites that can be measured. Whether the observed associations are directly due to genetic variation or indirectly due to changes in unmeasured metabolites is unclear. To address this, we used simulations of metabolic pathway models to investigate the influence of genetic variants on metabolite concentrations and enhance the interpretation of MGWAS results. By systematically adjusting the enzyme reaction rates to simulate genetic variants, we observed changes in the metabolite levels. Our simulations accurately represented most of the variant-metabolite pairs identified by MGWAS with significant p-values, thereby demonstrating the potential of our approach. Furthermore, our simulations revealed additional marked fluctuations in metabolite levels that the MGWAS did not detect, suggesting that some variant-metabolite pairs might become more significant with larger sample sizes. We also categorized the enzymes into three types based on their impact on metabolite concentrations, highlighting enzymes with minimal impact. This indicated that genetic variations in these enzymes may have limited biological significance. Our study not only validates key MGWAS findings, but also provides a systematic framework for understanding enzyme-metabolite relationships. This approach offers valuable insights for future experimental studies and potential therapeutic interventions.PMID:40379784 | DOI:10.1038/s41598-025-01634-7

Sci Rep. 2025 May 16;15(1):17090. doi: 10.1038/s41598-025-01895-2.ABSTRACTTo study the differences in the urine metabolome between pediatric patients with severe Mycoplasma pneumoniae pneumonia (SMPP) and those with general Mycoplasma pneumoniae pneumonia (GMPP) via non-targeted metabolomics method, and potential biomarkers were explored through machine learning (ML) algorithms. The urine metabonomics data of 48 children with SMPP and 85 children with GMPP were collected via high performance liquid chromatography‒mass spectrometry (HPLC-MS/MS). The differential metabolites between the two groups were obtained via principal component analysis (PCA) and partial least squares-discriminant analysis (PLS-DA), and the significant metabolic pathways were screened via enrichment analysis. Potential biomarkers were identified using the random forest algorithm, and their relationships with clinical indicators were subsequently analyzed. A total of 136 significantly differential metabolites were identified in the urine samples from SMPP and GMPP. Of these, 68 metabolites were upregulated, and 68 were downregulated, predominantly belonging to the amino acid group. A total of 6 differential metabolic pathways were enriched, including Galactose metabolism, Pantothenate and CoA biosynthesis, Cysteine and methionine metabolism, Biotin metabolism, Glycine, serine and threonine metabolism, Arginine biosynthesis. Three significant potential biomarkers were identified through machine learning: 3-Hydroxyanthranilic acid (3-HAA), L-Kynurenine, and 16(R)-HETE. The area under the receiver operating characteristic curve (AUC) for this three-metabolite panel was 0.9142. There are great differences in the urine metabolome between SMPP and GMPP children, with multiple metabolic pathways being abnormally expressed. Three metabolites have been identified as potential biomarkers for the early detection of SMPP.PMID:40379752 | DOI:10.1038/s41598-025-01895-2

Sci Rep. 2025 May 16;15(1):17051. doi: 10.1038/s41598-025-02429-6.ABSTRACTMultiple pesticide residues in agricultural products and environments, especially those with synergistic toxicity, pose a potential risk to human health. We observed a remarkable increase in serum biochemical parameters related to rat liver function when rat liver was exposed to the binary mixture of emamectin benzoate and cyantraniliprole. The present study aimed to investigate the toxicity interactions and underlying mechanisms of the binary mixture by using an L-02 cell model and metabolomics analysis. Cytotoxicity tests have shown that binary mixtures of emamectin benzoate and cyantraniliprole produced either additive or synergistic toxic effect on the cell viability of the human hepatic epithelial cell line L-02. The interaction within the binary mixtures resulted in the production of excessive reactive oxygen species (ROS) and malondialdehyde, as well as overexpression of antioxidant enzyme activities. The synergism was driven by aggravated production of ROS, leading to an imbalance in mitochondrial oxidation and energy metabolism, suggesting the possible use of ROS as an effective toxicity endpoint. Based on the benchmark dose calculated to determine the combined toxicity threshold, the model-averaged estimates of the benchmark dose lower confidence limits (4.74-9.58 mmol/L) of the binary mixtures at concentration ratios of 3:15, 3:45, 4:15, and 4:45 were 20% more toxic than their individual active ingredients. These findings have important implications for risk assessments of pesticide residue in food and highlight the need to consider concentration ratios and oxidative stress endpoints in such assessments.PMID:40379747 | DOI:10.1038/s41598-025-02429-6

Sci Rep. 2025 May 16;15(1):17109. doi: 10.1038/s41598-025-01743-3.ABSTRACTThis study was conducted to evaluate the effects of wet-fermented brewer's grains (WFBG) on liver metabolism in pullets. A total of 120 female 84-d-old pullets (575.2 ± 4.3 g) were randomly allocated into 2 treatments (0% and 20% WFBG) with 6 replicates per group and 10 birds per replicate in this 28-d experiment. Birds fed 20% WFBG had higher (P < 0.05) superoxide dismutase (SOD) level and lower (P < 0.05) malondialdehyde (MDA) content in the liver compared with the control group. In total, 324 liver differentially-expressed metabolites (DEMs) including 208 up-regulated DEMs and 116 down-regulated DEMs were identified and considered to be related with WFBG. Pathway analysis revealed that these DEMs were mainly involved in 64 metabolic pathways including metabolic pathways metabolism, glycerophospholipid (GP) metabolism, linoleic acid (LA) metabolism, arachidonic acid metabolism (ARA), and alpha-linolenic acid metabolism. Furthermore, untargeted metabolomic analyses uncovered 18 common up-regulated DEMs and 8 common down-regulated DEMs in GP, LA and ARA metabolism in the 20% WFBG group (P < 0.05), such as lysophosphatidylcholine (LPC(18:0/0:0), LPC(0:0/20:4)), lysophosphatidylethanolamine (LPE(22:6/0:0)), and 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphocholine. Overall, the inclusion of 20% WFBG in the diets of pullets led to alterations in liver metabolism.PMID:40379717 | DOI:10.1038/s41598-025-01743-3

Sci Rep. 2025 May 16;15(1):17021. doi: 10.1038/s41598-025-01082-3.ABSTRACTA heat stress (HS) cattle research design was implemented to study HS effects on the three different "omics features" methylations, gene expressions and metabolic pattern from a direct perspective in pregnant cows and from an indirect time-lagged intergenerational perspective in offspring (the respective F1 and as F1 offspring before calving). In this regard, a total number of 88 German Holstein dairy cows and their 93 female calves were blood sampled for DNA and RNA extraction and for metabolic phenotyping, and allocated to HS and respective control groups (the cows (dams) as well as their calves) according to a temperature-humidity threshold of 60. Separate principal component analyses for all "omics-tiers" revealed clear separations of HS from respective control groups, as well as dam-offspring separations according to gene expressions and metabolic pattern. The GO enrichment analyses based on the differentially expressed genes contributed to the detection of 10 significantly overrepresented biological processes in heat stressed dams, and of 95 overrepresented biological processes due to indirect maternal heat stress in calves. With regard to direct HS in dams and the first PCs of the different "omics" features, the correlation coefficient was 0.45 between methylation and gene expression data, 0.62 between expression and metabolites, and 0.38 between methylation and metabolite data. The separation of HS from the control group was very obvious when using the average and weighted average of the first and second components from the three multi-omics datasets. The present study provides extended insights into the complex genetic and physiological mechanisms of HS response in dam and calf groups from different generations, contributing to a deeper understanding of the interplay of prompt and time lagged HS effects between different omics-tiers.PMID:40379708 | DOI:10.1038/s41598-025-01082-3

Nat Commun. 2025 May 16;16(1):4567. doi: 10.1038/s41467-025-59755-6.ABSTRACTGlycosphingolipids (GSLs) are important targets in immune, infectious, lysosomal storage diseases, cancer, and neurodegenerative diseases. Circulatory GSLs profiling in clinical samples is restricted by the lack of mid- and high-throughput analytical methods and deep coverage of long-chain sialylated glycosphingolipidome. We present a 4-dimensional (4D)-glycosphingolipidomics platform for routine glycosphingolipidome profiling encompassing: extraction and fractionation of sialylated GSLs with 3 to 15 monosaccharides, neutral GSLs and sulfatides; µL-flow reversed-phase LC-TIMS-PASEF MS analysis; semi-quantification strategy adapted for fractionated glycosphingolipidome, and referential CCS, RT, and m/z values for GSLs annotation. 4D-glycosphingolipidomics of human serum reveals a high structural heterogeneity, amounting to 376 GSLs: 159 GSLs of ganglio- and neolacto-series, 145 neutral GSLs and 72 sulfatides. Here we demonstrate the platform's utility for clinical profiling of Parkinson's disease (PD) sera. 41 neolacto- and ganglio-species discriminate PD patients from controls and 14 GSLs differentiate sex subgroups, laying the foundation for further functional GSL studies with PD.PMID:40379659 | DOI:10.1038/s41467-025-59755-6

Nat Commun. 2025 May 16;16(1):4582. doi: 10.1038/s41467-025-59878-w.ABSTRACTSingle-cell metabolomics reveals cell heterogeneity and elucidates intracellular molecular mechanisms. However, general concentration measurement of metabolites can only provide a static delineation of metabolomics, lacking the metabolic activity information of biological pathways. Herein, we develop a universal system for dynamic metabolomics by stable isotope tracing at the single-cell level. This system comprises a high-throughput single-cell data acquisition platform and an untargeted isotope tracing data processing platform, providing an integrated workflow for dynamic metabolomics of single cells. This system enables the global activity profiling and flow analysis of interlaced metabolic networks at the single-cell level and reveals heterogeneous metabolic activities among single cells. The significance of activity profiling is underscored by a 2-deoxyglucose inhibition model, demonstrating delicate metabolic alteration within single cells which cannot reflected by concentration analysis. Significantly, the system combined with a neural network model enables the metabolomic profiling of direct co-cultured tumor cells and macrophages. This reveals intricate cell-cell interaction mechanisms within the tumor microenvironment and firstly identifies versatile polarization subtypes of tumor-associated macrophages based on their metabolic signatures, which is in line with the renewed diversity atlas of macrophages from single-cell RNA-sequencing. The developed system facilitates a comprehensive understanding single-cell metabolomics from both static and dynamic perspectives.PMID:40379657 | DOI:10.1038/s41467-025-59878-w

Nat Commun. 2025 May 16;16(1):4566. doi: 10.1038/s41467-025-59683-5.ABSTRACTImproving annotation accuracy, coverage, speed and depth of lipid profiles remains a significant challenge in traditional lipid annotation. We introduce LipidIN, an advanced framework designed for flash platform-independent annotation. LipidIN features a 168.5-million lipid fragmentation hierarchical library that encompasses all potential chain compositions and carbon-carbon double bond locations. The expeditious querying module achieves speeds exceeding one hundred billion queries per second across all mass spectral libraries. The lipid categories intelligence model is developed using three relative retention time rules, reducing false positive annotations and predicting unannotated lipids with a 5.7% estimated false discovery rate, covering 8923 lipids cross various species. More importantly, LipidIN integrates a Wide-spectrum Modeling Yield network for regenerating lipid fragment fingerprints to further improve accuracy and coverage with a 20% estimated recall boosting. We further demonstrate the utility of LipidIN in multiple tasks for lipid annotation and biomarker discovery in clinical cohorts.PMID:40379655 | DOI:10.1038/s41467-025-59683-5

Cell Death Dis. 2025 May 16;16(1):391. doi: 10.1038/s41419-025-07707-9.ABSTRACTHepatocellular carcinoma (HCC) is one of the most prevalent malignant tumors of the digestive system, and its prevalence is currently increasing. The current study aims to elucidate the mechanism by which membrane-associated RING-CH8 (MARCH8) impedes the progression of HCC. MARCH8 was identified as a distinct prognostic marker for recurrence-free survival (RFS) and overall survival (OS) in patients with HCC. This study shows that MARCH8 hinders lipid deposition by suppressing the expression of key enzymes for the de novo synthesis of fatty acids (FAs) via RNA sequencing, untargeted metabolomics, and a series of in vivo and in vitro experiments. Further experimental validation demonstrated that MARCH8 was a novel E3 ligase of sterol regulatory element binding protein 1 (SREBP1). And, it primarily promoted the degradation of SREBP1, thereby suppressing the expression of key enzymes involved in the de novo synthesis of FAs. In conclusion, this study has identified MARCH8 as a key "switch" that can be targeted to prevent de novo FA synthesis in HCC cells. This finding may have substantial implications for discovering innovative therapeutic strategies for HCC.PMID:40379644 | DOI:10.1038/s41419-025-07707-9

Exp Eye Res. 2025 May 14:110414. doi: 10.1016/j.exer.2025.110414. Online ahead of print.ABSTRACTThis study employed a multiomic approach to investigate retinal tissue damage following direct ocular exposure (DOE) to vesicants (VSs)-namely, nitrogen mustard (NM) and lewisite (Lew). We explored both the acute and chronic stages of retinal injury by assessing functional, structural, and molecular changes. C57BL/6 mice were used to measure scotopic and photopic electroretinograms (ERGs) and to analyze TUNEL-positive retinal cells. Global retinal proteomics was conducted to identify common and unique signaling pathways. In addition, we performed targeted metabolomic and lipidomic analyses of retinal tissue to uncover significant metabolic changes. Our results demonstrated remarkable declines in ERG amplitudes at 2 and 4 weeks post-exposure, accompanied by an increase in TUNEL+ retinal cells in response to DOE to both VSs. Our proteomic analysis revealed chronic oxidative stress, mitochondrial dysfunction, elevated RXR signaling, and increased levels of 28 proteins. Moreover, we observed a decline in the KEGG phototransduction pathways, along with the downregulation of photoreceptor-specific proteins, in response to both VSs. Consistent with the proteomic findings, targeted metabolomics identified a decline in phototransduction and steroid hormone biosynthesis, along with increases in D-amino acid and purine metabolism, as well as lysine degradation. These changes were associated with a GSSG/GSH ratio of 2.6, confirming the proteomic data on oxidative stress. Furthermore, lipidomic analysis revealed an increase in oxidative lipid levels, accompanied by a 3.4-fold increase in phosphatidylserine (PS), suggesting apoptotic cell death and a reduction in fatty acids (FAs). In conclusion, exposure to both VSs induced progressive retinal damage, altering major metabolic pathways and dysregulating lipid metabolism. Future studies should focus on identifying the responses of individual neuronal cell types to DOE to VSs to develop cell-specific countermeasures.PMID:40379201 | DOI:10.1016/j.exer.2025.110414

Environ Res. 2025 May 14:121820. doi: 10.1016/j.envres.2025.121820. Online ahead of print.NO ABSTRACTPMID:40378997 | DOI:10.1016/j.envres.2025.121820