PubMed

bioRxiv. 2024 Jan 30:2024.01.26.577518. doi: 10.1101/2024.01.26.577518. Preprint.ABSTRACTQuantitative trait loci (QTL) denote regions of DNA whose variation is associated with variations in quantitative traits. QTL discovery is a powerful approach to understand how changes in molecular and clinical phenotypes may be related to DNA sequence changes. However, QTL discovery analysis encompasses multiple analytical steps and the processing of multiple input files, which can be laborious, error prone, and hard to reproduce if performed manually. In order to facilitate and automate large-scale QTL analysis, we developed the yQTL Pipeline, where the 'y' indicates the dependent quantitative variable being modeled. Prior to genome-wide association test, the pipeline supports the calculation or the direct input of pre-defined genome-wide principal components and genetic relationship matrix when applicable. User-specified covariates can also be provided. Depending on whether familial relatedness exists among the subjects, genome-wide association tests will be performed using either a linear mixed-effect model or a linear model. Using the workflow management tool Nextflow, the pipeline parallelizes the analysis steps to optimize run-time and ensure results reproducibility. In addition, a user-friendly R Shiny App is developed to facilitate result visualization. Upon uploading the result file, it can generate Manhattan plots of user-selected phenotype traits and trait-QTL connection networks based on user-specified p-value thresholds. We applied the yQTL Pipeline to analyze metabolomics profiles of blood serum from the New England Centenarians Study (NECS) participants. A total of 9.1M SNPs and 1,052 metabolites across 194 participants were analyzed. Using a p-value cutoff 5e-8, we found 14,983 mQTLs cumulatively associated with 312 metabolites. The built-in parallelization of our pipeline reduced the run time from ~90 min to ~26 min. Visualization using the R Shiny App revealed multiple mQTLs shared across multiple metabolites. The yQTL Pipeline is available with documentation on GitHub at https://github.com/montilab/yQTL-Pipeline.PMID:38370654 | PMC:PMC10874520 | DOI:10.1101/2024.01.26.577518

Front Pharmacol. 2024 Jan 29;15:1353325. doi: 10.3389/fphar.2024.1353325. eCollection 2024.ABSTRACTIntroduction: Zhusha Anshen Wan (ZSASW) is a traditional Chinese medicine compound mainly composed of mineral drugs. In clinical practice, ZSASW did not show the toxicity of administering equal doses of cinnabar alone, suggesting that the four combination herbs in ZSASW can alleviate the damage of cinnabar. The effect of each herb on reducing the toxicity of cinnabar has not been fully explained. Methods: In our study, we utilized a metabonomics approach based on high-resolution 1H nuclear magnetic resonance spectroscopy to investigate the reduction of toxicity by each herb in ZSASW. Liver, kidney and intestinal histopathology examinations and biochemical analysis of the serum were also performed. Results: Partial least squares-discriminant analysis (PLS-DA) was conducted to distinct different metabolic profiles in the urine and serum from the rats. Liver and kidney histopathology examinations, as well as analysis of serum clinical chemistry analysis, were also carried out. The metabolic profiles of the urine and serum of the rats in the CGU (treated with cinnabar and Glycyrrhiza uralensis Fisch) and CCC (treated with cinnabar and Coptis chinensis French) groups were remarkably similar to those of the control group, while those of the CRG (treated with cinnabar and Rehmannia glutinosa Libosch) and CAS (treated with cinnabar and Angelica sinensis) groups were close to those of the cinnabar group. The metabolic profiles of the urine and serum of the rats in the CGU and CCC groups were remarkably similar to those of the control group, while those of the CRG and CAS groups were close to those of the cinnabar group. Changes in endogenous metabolites associated with toxicity were identified. Rehmannia glutinosa, Rhizoma Coptidis and Glycyrrhiza uralensis Fisch could maintain the dynamic balance of the intestinal flora. These results were also verified by liver, kidney and intestinal histopathology examinations and biochemical analysis of the serum. The results suggested that Discussion: The metabolic mechanism of single drug detoxification in compound prescriptions has been elucidated. Coptis chinensis and Glycyrrhiza uralensis serve as the primary detoxification agents within ZSASW for mitigating liver, kidney, and intestinal damage caused by cinnabar. Detoxification can be observed through changes in the levels of various endogenous metabolites and related metabolic pathways.PMID:38370476 | PMC:PMC10871036 | DOI:10.3389/fphar.2024.1353325

Front Endocrinol (Lausanne). 2024 Feb 2;15:1313597. doi: 10.3389/fendo.2024.1313597. eCollection 2024.ABSTRACTBACKGROUND: Metformin is a drug with a long history of providing benefits in diabetes management and beyond. The mechanisms of action of metformin are complex, and continue to be actively debated and investigated. The aim of this study is to identify metabolic signatures associated with metformin treatment, which may explain the pleiotropic mechanisms by which metformin works, and could lead to an improved treatment and expanded use.METHODS: This is a cross-sectional study, in which clinical and metabolomic data for 146 patients with type 2 diabetes were retrieved from Qatar Biobank. Patients were categorized into: Metformin-treated, treatment naïve, and non-metformin treated. Orthogonal partial least square discriminate analysis and linear models were used to analyze differences in the level of metabolites between the metformin treated group with each of the other two groups.RESULTS: Patients on metformin therapy showed, among other metabolites, a significant increase in 3-hydroxyoctanoate and 3-hydroxydecanoate, which may have substantial effects on metabolism.CONCLUSIONS: This is the first study to report an association between 3-hydroxy medium chain fatty acids with metformin therapy in patients with type 2 diabetes. This opens up new directions towards repurposing metformin by comprehensively understanding the role of these metabolites.PMID:38370354 | PMC:PMC10869496 | DOI:10.3389/fendo.2024.1313597

Food Chem X. 2024 Feb 6;21:101173. doi: 10.1016/j.fochx.2024.101173. eCollection 2024 Mar 30.ABSTRACTTo better understand the effect of oxygen levels in the storage environment on peanut protein oxidation and explore the mechanism, the functional properties and the oxidation degree of peanut proteins extracted from peanuts under conventional storage (CS), nitrogen modified atmosphere storage (NS, hypoxic) and re-aeration storage (RS) were investigated. Metabolomics and proteomics were employed to analyze peanut's response to hypoxic/re-aeration storage environment. The results showed that NS retarded the decline of the functional properties and the oxidation of peanut proteins, while the process were accelerated after re-aeration. That was the result of the metabolic changes of peanuts under different storage environments. The omics results presented the decreased (NS)/increased (RS) levels of the antioxidant-related proteins acetaldehyde dehydrogenase and glutathione S-transferase, and the inhibition (NS)/activation (RS) of metabolic pathways such as the TCA cycle and the pentose phosphate pathway. This study provided a reference for the re-aeration storage of other agricultural products.PMID:38370304 | PMC:PMC10869743 | DOI:10.1016/j.fochx.2024.101173

Expert Rev Mol Diagn. 2024 Feb 19:1-13. doi: 10.1080/14737159.2024.2316755. Online ahead of print.ABSTRACTBACKGROUND: Breathomics is an emerging area focusing on monitoring and diagnosing pulmonary diseases, especially lung cancer. This research aims to employ metabolomic methods to create a breathprint in human-expelled air to rapidly identify lung cancer and its stages.RESEARCH DESIGN AND METHODS: An electronic nose (e-nose) system with five metal oxide semiconductor (MOS) gas sensors, a microcontroller, and machine learning algorithms was designed and developed for this application. The volunteers in this study include 114 patients with lung cancer and 147 healthy controls to understand the clinical potential of the e-nose system to detect lung cancer and its stages.RESULTS: In the training phase, in discriminating lung cancer from controls, the XGBoost classifier model with 10-fold cross-validation gave an accuracy of 91.67%. In the validation phase, the XGBoost classifier model correctly identified 35 out of 42 patients with lung cancer samples and 44 out of 51 healthy control samples providing an overall sensitivity of 83.33% and specificity of 86.27%.CONCLUSIONS: These results indicate that the exhaled breath VOC analysis method may be developed as a new diagnostic tool for lung cancer detection. The advantages of e-nose based diagnostics, such as an easy and painless method of sampling, and low-cost procedures, will make it an excellent diagnostic method in the future.PMID:38369930 | DOI:10.1080/14737159.2024.2316755

Sheng Wu Gong Cheng Xue Bao. 2024 Feb 25;40(2):542-561. doi: 10.13345/j.cjb.230371.ABSTRACTThe leaves and roots of Sarcandra glabra (thunb) nakai have different therapeutic effects in some clinical applications. In order to explore the tissue specific distribution differences of terpenoids in the leaves and roots of S. glabra, and to analyze the molecular mechanism of the formation of their pharmacodynamic quality differences. In this study, liquid chromatography-mass spectrometry (LC-MS) and Illumina HiSeqTM high-throughput sequencing techniques were respectively used to obtain the metabolome and transcriptome data of the leaves and roots of S. glabra. The metabolomics analysis showed that there were 50 differential terpenoids metabolites between the leaves and roots, including farnesylcysteine, d-glyceraldehyde 3-phosphate, and (R)-5-phosphomevalonate. The transcriptomics analysis indicated that there were 57 differentially expressed metabolic enzyme coding genes, including ACTC, HMGCR, MVK, DXS, and KS. Moreover, there were seven transcription factors, including MYB, C2H2, AP2/ERF-ERF, which were predicted to participate in regulating the differences in terpenoid synthesis and accumulation between the leaves and roots of S. glabra. qRT-PCR results demonstrated that the expression changes of eight randomly selected enzyme genes involved in terpene synthesis between the leaves and roots of S. glabra, which were consistent with the transcriptome sequencing results. This study will help to elucidate the molecular mechanisms underlying the clinical efficacy differences between the leaves and roots of S. glabra, and facilitate the extraction, utilization, and resource development of S. glabra.PMID:38369840 | DOI:10.13345/j.cjb.230371

Development. 2024 Feb 15;151(4):dev202020. doi: 10.1242/dev.202020. Epub 2024 Feb 19.ABSTRACTMalrotation of the intestine is a prevalent birth anomaly, the etiology of which remains poorly understood. Here, we show that late-stage exposure of Xenopus embryos to atrazine, a widely used herbicide that targets electron transport chain (ETC) reactions, elicits intestinal malrotation at high frequency. Interestingly, atrazine specifically inhibits the cellular morphogenetic events required for gut tube elongation, including cell rearrangement, differentiation and proliferation; insufficient gut lengthening consequently reorients the direction of intestine rotation. Transcriptome analyses of atrazine-exposed intestines reveal misexpression of genes associated with glycolysis and oxidative stress, and metabolomics shows that atrazine depletes key glycolytic and tricarboxylic acid cycle metabolites. Moreover, cellular bioenergetics assays indicate that atrazine blocks a crucial developmental transition from glycolytic ATP production toward oxidative phosphorylation. Atrazine-induced defects are phenocopied by rotenone, a known ETC Complex I inhibitor, accompanied by elevated reactive oxygen species, and rescued by antioxidant supplementation, suggesting that malrotation may be at least partly attributable to redox imbalance. These studies reveal roles for metabolism in gut morphogenesis and implicate defective gut tube elongation and/or metabolic perturbations in the etiology of intestinal malrotation.PMID:38369735 | DOI:10.1242/dev.202020

Sci Rep. 2024 Feb 19;14(1):4037. doi: 10.1038/s41598-024-54717-2.ABSTRACTGut microbiota and their metabolic products might play important roles in regulating the pathogenesis of autism spectrum disorder (ASD). The purpose of this study was to characterize gut microbiota and serum amino acid metabolome profiles in children with ASD. A non-randomized controlled study was carried out to analyze the alterations in the intestinal microbiota and their metabolites in patients with ASD (n = 30) compared with neurotypical controls (NC) (n = 30) by metagenomic sequencing to define the gut microbiota community and liquid chromatography/mass spectrometry (LC/MS) analysis to characterize the metabolite profiles. Compared with children in the NC group, those in the ASD group showed lower richness, higher evenness, and an altered microbial community structure. At the class level, Deinococci and Holophagae were significantly lower in children with ASD compared with TD. At the phylum level, Deinococcus-Thermus was significantly lower in children with ASD compared with TD. In addition, the functional properties (such as galactose metabolism) displayed significant differences between the ASD and NC groups. Five dominant altered species were identified and analyzed (LDA score > 2.0, P < 0.05), including Subdoligranulum, Faecalibacterium_praushitzii, Faecalibacterium, Veillonellaceae, and Rumminococcaceae. The peptides/nickel transport system was the main metabolic pathway involved in the differential species in the ASD group. Decreased ornithine levels and elevated valine levels may increase the risk of ASD through a metabolic pathway known as the nickel transport system. The microbial metabolism in diverse environments was negatively correlated with phascolarctobacterium succinatutens. Our study provides novel insights into compositional and functional alterations in the gut microbiome and metabolite profiles in ASD and the underlying mechanisms between metabolite and ASD.PMID:38369656 | DOI:10.1038/s41598-024-54717-2

Biotechnol Biofuels Bioprod. 2024 Feb 18;17(1):27. doi: 10.1186/s13068-024-02476-7.ABSTRACTBACKGROUND: The demand for melatonin is increasing due to its health-promoting bioactivities such as antioxidant and sleep benefits. Although melatonin is present in various organisms, its low content and high extraction cost make it unsustainable. Biosynthesis is a promising alternative method for melatonin production. However, the ectopic production of melatonin in microorganisms is very difficult due to the low or insoluble expression of melatonin synthesis genes. Hence, we aim to explore the biosynthesis of melatonin using Escherichia coli as a cell factory and ways to simultaneously coordinated express genes from different melatonin synthesis pathways.RESULTS: In this study, the mXcP4H gene from Xanthomonas campestris, as well as the HsAADC, HsAANAT and HIOMT genes from human melatonin synthesis pathway were optimized and introduced into E. coli via a multi-monocistronic vector. The obtained strain BL7992 successfully synthesized 1.13 mg/L melatonin by utilizing L-tryptophan (L-Trp) as a substrate in a shake flask. It was determined that the rate-limiting enzyme for melatonin synthesis is the arylalkylamine N-acetyltransferase, which is encoded by the HsAANAT gene. Targeted metabolomics analysis of L-Trp revealed that the majority of L-Trp flowed to the indole pathway in BL7992, and knockout of the tnaA gene may be beneficial for increasing melatonin production.CONCLUSIONS: A metabolic engineering approach was adopted and melatonin was successfully synthesized from low-cost L-Trp in E. coli. This study provides a rapid and economical strategy for the synthesis of melatonin.PMID:38369525 | DOI:10.1186/s13068-024-02476-7

J Dairy Sci. 2024 Feb 16:S0022-0302(24)00489-2. doi: 10.3168/jds.2023-24147. Online ahead of print.ABSTRACTThrough its influence on the gut microbiota, feeding of Saccharomyces cerevisiae fermentation products (SCFP) has been a successful strategy to enhance the health of dairy cows during periods of physiological stresses. Although production and metabolic outcomes from feeding SCFP are well-known, combined impacts on the ruminal microbiota and metabolome during gut barrier challenges remain unclear. To address this gap in knowledge, multiparous Holstein cows (97.1 ± 7.6 DIM; n = 8/group) fed a control diet (CON) or CON plus 19 g/d SCFP for 9 wk were subjected to a feed restriction (FR) challenge for 5 d, during which they were fed 40% of their ad-libitum intake from the 7 d before FR. DNA extracted from ruminal fluid was subjected to PacBio Full-Length 16S rRNA gene sequencing, RT-PCR of 12 major ruminal bacteria, and metabolomics analysis of up to 189 metabolites via GC-MS. High-quality amplicon sequence analyses were performed with Targeted Amplicon Diversity Analysis (TADA), MicrobiomeAnalyst, PICRUSt2, and STAMP software, while metabolomics data were analyzed via MetaboAnalyst 5.0. Ruminal fluid metabolites from the SCFP group exhibited a greater α diversity Chao 1 (P = 0.03) and Shannon indices (P = 0.05), and the PLS-DA analysis clearly discriminated metabolite profiles between dietary groups. The abundance of CPla_4_termite_group, Candidatus_Saccharimonas, Oribacterium, and Pirellula genus in cows fed SCFP was greater. In the SCFP group, concentrations of ethanolamine, 2-amino-4,6-dihydroxypyrimidine, glyoxylic acid, serine, threonine, cytosine, stearic acid, and pyrrole-2-carboxylic acid were greater in ruminal fluid. Both Fretibacterium and Succinivibrio abundance were positively correlated with metabolites across various biological processes: gamma-aminobutyric acid, galactose, butane-2,3-diol, fructose, 5-amino pentanoic acid, β-aminoisobutyric acid, ornithine, malonic acid, 3-hydroxy-3-methylbutyric acid, hexanoic acid, heptanoic acid, cadaverine, glycolic acid, β-alanine, 2-hydroxybutyric acid, methyl alanine, and alanine. In the SCFP group, compared with CON, the mean proportion of 14 predicted pathways based on metabolomics data was greater, while 10 predicted pathways were lower. Integrating metabolites and upregulated predicted enzymes (NADP+-dependent glucose-6-phosphate dehydrogenase, 6-phosphogluconate dehydrogenase, serine: glyoxylate aminotransferase, and D-glycerate 3-kinase) indicated that the pentose phosphate pathway and photorespiration pathway were most upregulated by SCFP. Overall, SCFP during FR led to alterations in ruminal microbiota composition and key metabolic pathways. Among those, there was a shift from the tricarboxylic acid (TCA) cycle to the glyoxylate cycle and nitrogenous base production was enhanced.PMID:38369118 | DOI:10.3168/jds.2023-24147

J Dairy Sci. 2024 Feb 16:S0022-0302(24)00484-3. doi: 10.3168/jds.2023-23984. Online ahead of print.ABSTRACTEstimating feed efficiency (FE) in dairy sheep is challenging due to the high cost of systems that measure individual feed intake. Identifying proxies that can serve as effective predictors of FE could make it possible to introduce FE into breeding programs. Here, 39 Assaf ewes in first lactation were evaluated regarding their FE by 2 metrics, residual feed intake (RFI) and feed conversion ratio (FCR). The ewes were classified into high, medium and low groups for each metric. Milk samples of the 39 ewes were subjected to untargeted metabolomics analysis. The complete milk metabolomic signature was used to discriminate the FE groups using partial least squares discriminant analysis. A total of 41 and 26 features were selected as the most relevant features for the discrimination of RFI and FCR groups, respectively. The predictive ability when utilizing the complete milk metabolomic signature and the reduced data sets were investigated using 4 machine-learning algorithms and a multivariate regression method. The Orthogonal Partial Least Square algorithm outperformed other ML algorithms for the FCR prediction in the scenarios using the complete milk metabolite signature (r2 = 0.62 ± 0.06) and the 26 selected features (0.62 ± 0.15). Regarding RFI predictions, the scenarios using the 41 selected features outperformed the scenario with the complete milk metabolite signature, where the Multilayer feedforward artificial neural network (r2 = 0.18 ± 0.14) and extreme gradient boosting (r2 = 0.17 ± 0.15) outperformed other algorithms. The functionality of the selected metabolites implied that the metabolism of glucose, galactose, fructose, sphingolipids, amino acids, insulin, and thyroid hormones was at play. Compared with the use of traditional methods, practical applications of these biomarkers might simplify and reduce costs in selecting feed-efficient ewes.PMID:38369116 | DOI:10.3168/jds.2023-23984

Environ Pollut. 2024 Feb 16:123595. doi: 10.1016/j.envpol.2024.123595. Online ahead of print.ABSTRACTThe zirconium metal-organic framework UiO-66-NH2 has garnered considerable attention for their potentials of removing environmental contaminants from water. The production and application of UiO-66-NH2 make their releases into the aquatic environment inevitable. Nevertheless, little information is available regarding its potential risk to the environment and aquatic organisms, thus limiting the evaluation of its safe and sustainable use. In this study, the ecotoxicity of UiO-66-NH2 was evaluated, specifically its impacts on growth, extracellular organic matter release, and metabolomic changes of the model phytoplankton Microcystis aeruginosa (M. aeruginosa). UiO-66-NH2 exhibited moderate effects on algal physiology including growth, viability, and photosynthetic system. At concentrations below 20 mg/L, UiO-66-NH2 induced negligible inhibition of algal growth, algal viability, and photosynthesis. In contrast, UiO-66-NH2 boosted the release of extracellular organic matter even at concentration as low as 0.02 mg/L. These findings indicated that, while no evident damage to algal cells was observed, UiO-66-NH2 was hazardous to the aquatic environment as it stimulated the release of algal toxins. Moreover, UiO-66-NH2 entered algal cells rather than adhering to the surface of M. aeruginosa as observed by the fluorescence imaging. Based on metabolic analysis, UiO-66-NH2 influenced the cyanobacteria mainly through interference with purine metabolism and ABC transporter. This study sheds light on the potential threat UiO-66-NH2 posing to microalgae, and has potential implications for its safe utilization in the environmental field.PMID:38369089 | DOI:10.1016/j.envpol.2024.123595

EBioMedicine. 2024 Feb 17;101:105008. doi: 10.1016/j.ebiom.2024.105008. Online ahead of print.ABSTRACTGestational diabetes mellitus (GDM) is one of the most common metabolic complications during pregnancy, threatening both maternal and fetal health. Prediction and diagnosis of GDM is not unified. Finding effective biomarkers for GDM is particularly important for achieving early prediction, accurate diagnosis and timely intervention. Urine, due to its accessibility in large quantities, noninvasive collection and easy preparation, has become a good sample for biomarker identification. In recent years, a number of studies using metabolomics and proteomics approaches have identified differential expressed urine metabolites and proteins in GDM patients. In this review, we summarized these potential urine biomarkers for GDM prediction and diagnosis and elucidated their role in development of GDM.PMID:38368766 | DOI:10.1016/j.ebiom.2024.105008

Arch Toxicol. 2024 Feb 18. doi: 10.1007/s00204-024-03680-y. Online ahead of print.ABSTRACTWhile grouping/read-across is widely used to fill data gaps, chemical registration dossiers are often rejected due to weak category justifications based on structural similarity only. Metabolomics provides a route to robust chemical categories via evidence of shared molecular effects across source and target substances. To gain international acceptance, this approach must demonstrate high reliability, and best-practice guidance is required. The MetAbolomics ring Trial for CHemical groupING (MATCHING), comprising six industrial, government and academic ring-trial partners, evaluated inter-laboratory reproducibility and worked towards best-practice. An independent team selected eight substances (WY-14643, 4-chloro-3-nitroaniline, 17α-methyl-testosterone, trenbolone, aniline, dichlorprop-p, 2-chloroaniline, fenofibrate); ring-trial partners were blinded to their identities and modes-of-action. Plasma samples were derived from 28-day rat tests (two doses per substance), aliquoted, and distributed to partners. Each partner applied their preferred liquid chromatography-mass spectrometry (LC-MS) metabolomics workflows to acquire, process, quality assess, statistically analyze and report their grouping results to the European Chemicals Agency, to ensure the blinding conditions of the ring trial. Five of six partners, whose metabolomics datasets passed quality control, correctly identified the grouping of eight test substances into three categories, for both male and female rats. Strikingly, this was achieved even though a range of metabolomics approaches were used. Through assessing intrastudy quality-control samples, the sixth partner observed high technical variation and was unable to group the substances. By comparing workflows, we conclude that some heterogeneity in metabolomics methods is not detrimental to consistent grouping, and that assessing data quality prior to grouping is essential. We recommend development of international guidance for quality-control acceptance criteria. This study demonstrates the reliability of metabolomics for chemical grouping and works towards best-practice.PMID:38368582 | DOI:10.1007/s00204-024-03680-y

Sci Rep. 2024 Feb 17;14(1):3968. doi: 10.1038/s41598-024-54279-3.ABSTRACTHorseshoe crabs are among the most studied invertebrates due to their unique, innate immune system and biological processes. The metabolomics study was conducted on lipopolysaccharide (LPS)-stimulated and non-stimulated hemocytes isolated from the Malaysian Tachypleus gigas and Carcinoscorpius rotundicauda. LC-TOF-MS, multivariate analyses, principal component analysis (PCA), and partial least squares-discriminant analysis (PLS-DA) were included in this study to profile the metabolites. A total of 37 metabolites were identified to be differentially abundant and were selected based on VIP > 1. However, of the 37 putative metabolites, only 23 were found to be significant with ANOVA at p < 0.05. The metabolites were identified using several databases, and the literature review of the metabolites was reported in the manuscript. Thus, this study has provided further insights into the putative metabolites' presence in the hemocytes of horseshoe crabs that are stimulated and non-stimulated with LPS and their abundance in each species. Several putative metabolites showed they have medicinal values from previous studies.PMID:38368470 | DOI:10.1038/s41598-024-54279-3

Leukemia. 2024 Feb 17. doi: 10.1038/s41375-024-02168-z. Online ahead of print.NO ABSTRACTPMID:38368441 | DOI:10.1038/s41375-024-02168-z

Arch Toxicol. 2024 Feb 18. doi: 10.1007/s00204-024-03683-9. Online ahead of print.ABSTRACTDimethyl fumarate (DMF) is an old drug used for psoriasis treatment that has recently been repurposed to treat relapse-remitting multiple sclerosis, mostly due to its neuro- and immunomodulatory actions. However, mining of a pharmacovigilance database recently ranked DMF as the second pharmaceutical most associated with cognitive adverse events. To our best knowledge, the signaling mechanisms underlying its therapeutic and neurotoxic outcomes remain mostly undisclosed. This work thus represents the first-hand assessment of DMF-induced metabolic changes in undifferentiated SH-SY5Y human neuroblastoma cells, through an untargeted metabolomic approach using gas chromatography-mass spectrometry (GC-MS). The endometabolome was analyzed following 24 h and 96 h of exposure to two pharmacologically relevant DMF concentrations (0.1 and 10 μM). None of these conditions significantly reduced metabolic activity (MTT reduction assay). Our data showed that 24 h-exposure to DMF at both concentrations tested mainly affected metabolic pathways involved in mitochondrial activity (e.g., citric acid cycle, de novo triacylglycerol biosynthesis), and the synthesis of catecholamines and serotonin by changing the levels of their respective precursors, namely phenylalanine (0.68-fold decrease for 10 μM DMF vs vehicle), and tryptophan (1.36-fold increase for 0.1 μM DMF vs vehicle). Interestingly, taurine, whose levels can be modulated via Nrf2 signaling (DMF's primary target), emerged as a key mediator of DMF's neuronal action, displaying a 3.86-fold increase and 0.27-fold decrease for 10 μM DMF at 24 h and 96 h, respectively. A 96 h-exposure to DMF seemed to mainly trigger pathways associated with glucose production (e.g., gluconeogenesis, glucose-alanine cycle, malate-aspartate shuttle), possibly related to the metabolism of DMF into monomethyl fumarate and its further conversion into glucose via activation of the citric acid cycle. Overall, our data contribute to improving the understanding of the events associated with neuronal exposure to DMF.PMID:38368281 | DOI:10.1007/s00204-024-03683-9

J Biosci Bioeng. 2024 Feb 16:S1389-1723(24)00033-1. doi: 10.1016/j.jbiosc.2024.01.013. Online ahead of print.ABSTRACTFermented seasonings have pleasant flavors that stimulate our appetite. Their flavoring properties change depending on factors such as their materials and fermented conditions. Therefore, a comparative analysis of their flavor is important when evaluating their quality. However, seasonings contain high levels of various matrices such as sugars, proteins, lipids, and ethanol, making it difficult to extract aroma compounds efficiently from them. In this study, we verified a high-efficient and high-throughput volatile flavor analysis of fermented seasonings by solvent-assisted stir bar solid extraction (SA-SBSE) with reverse extraction. We applied SA-SBSE to Japanese fermented seasonings, soy sauce, miso (fermented beans), and mirin (sweet rice wine) and compared their profiles with those from other common extraction methods, headspace gas-solid-phase microextraction (HS-SPME), liquid extraction with solvent-assisted flavor evaporation (LE-SAFE), and conventional SBSE (C-SBSE). The aroma properties and profiles of extracts from SA-SBSE were close to those of the original sample, being similar to that of LE-SAFE. In addition, potent aroma compounds in each sample were extracted by SA-SBSE and LE-SAFE, which were far superior to those by C-SBSE. For quantification, SA-SBSE extracts showed a good standard curve by the standard addition method. We could quantify maltol, one of the most common potent aroma compounds in all samples, for various commercial samples by such high-throughput analysis.PMID:38368121 | DOI:10.1016/j.jbiosc.2024.01.013

Carbohydr Polym. 2024 Apr 15;330:121805. doi: 10.1016/j.carbpol.2024.121805. Epub 2024 Jan 13.ABSTRACTThis study explores the structural modification of glucomannan extracted from Artemisia sphaerocephala Krasch seeds (60S) to assess the impact of acetyl groups on its prebiotic characteristics. The structural changes were examined, with a focus on the degree of acetyl group substitution (DS). Both deacetylation and acetylation had limited influence on the molecular properties of 60S. Despite these modifications, the apparent viscosity of all samples remained consistently low. In vitro fermentation experiments revealed that Escherichia-Shigella decreased as DS increased, while Bacteroides ovatus was enriched. Acetylation had no significant impact on the utilization rate of 60S but led to a reduction in the production of propionic acid. Furthermore, untargeted metabolomics analysis confirmed the changes in propionic acid levels. Notably, metabolites such as N-acetyl-L-tyrosine, γ-muricholic acid, and taurocholate were upregulated by acetylated derivatives. Overall, acetyl groups are speculated to play a pivotal role in the prebiotic properties of 60S.PMID:38368082 | DOI:10.1016/j.carbpol.2024.121805

Free Radic Biol Med. 2024 Feb 15:S0891-5849(24)00098-4. doi: 10.1016/j.freeradbiomed.2024.02.016. Online ahead of print.ABSTRACTUlcerative colitis (UC) is a chronic gastrointestinal disease that can be managed with 5-aminosalicylic acid (5-ASA), the standard treatment for UC. However, the effectiveness of 5-ASA is not always optimal. Our study revealed that despite 5-ASA treatment, cells continued to experience excessive ferroptosis, which may hinder mucosal healing in UC and limit the success of this treatment approach in achieving disease remission. We found that combining 5-ASA with the ferroptosis inhibitor Fer-1 led to a significant inhibition of ferroptosis in macrophages present in the colon tissue, along with an increase in the proportion of M2 macrophages, suggesting that targeting ferroptosis in M2 macrophages could be a potential therapeutic strategy for alleviating UC. Our study also demonstrated that M2 macrophages are more susceptible to ferroptosis compared to M1 macrophages, and this susceptibility is associated with the activated arachidonic acid (AA) metabolism pathway mediated by ERK-cPLA2-ACSL4. Additionally, we found that the expression of cPLA2 gene pla2g4a was increased in the colon of UC patients compared to healthy controls. Furthermore, targeted metabolomics analysis revealed that the combination treatment group, as opposed to the 5-ASA treatment group, exhibited the ability to modulate AA metabolism. Overall, our findings emphasize the importance of addressing macrophage ferroptosis in order to enhance macrophage anti-inflammation, improve mucosal healing, and achieve better therapeutic outcomes for patients with UC.PMID:38367927 | DOI:10.1016/j.freeradbiomed.2024.02.016