Nitrogen-fixing bacteria promote growth and bioactive components accumulation of Astragalus mongholicus by regulating plant metabolism and rhizosphere microbiota.

BACKGROUND: The excessive application of chemical fertilizers in the cultivation of Astragalus mongholicus Bunge results in a reduction in the quality of the medicinal plant and compromises the sustainable productivity of the soil. PGPB inoculant is a hot topic in ecological agriculture research. In the cultivation of Astragalus mongholicus, the screened nitrogen-fixing bacteria can promote plant growth, however, whether it can promote the accumulation of main bioactive components remains unknown. In this study, mixed inoculants containing 5 strains of growth promoting bacteria (Rhizobium T16 , Sinorhizobium T21 , Bacillus J1 , Bacillus G4 and Arthrobacter J2) were used in the field experiment. The metabolic substances in the root tissues of Astragalus mongholicus were identified during the harvest period by non-targeted metabolomics method, and the differential metabolites between groups were identified by statistical analysis. Meanwhile, high-throughput sequencing was performed to analyze the changes of rhizosphere soil and endophytic microbial community structure after mixed microbial treatment. RESULTS: The results of non-targeted metabolism indicated a significant increase in the levels of 26 metabolites after treatment including 13 flavonoids, 3 saponins and 10 other components. The contents of three plant hormones (abscisic acid, salicylic acid and spermidine) also increased after treatment, which presumed to play an important role in regulating plant growth and metabolism. Studies on endosphere and rhizosphere bacterial communities showed that Rhzobiaceae, Micromonosporaceae, and Hypomicrobiaceae in endophytic, and Oxalobactereae in rhizosphere were significantly increased after treatment. These findings suggest their potential importance in plant growth promotion and secondary metabolism regulation. CONCLUSIONS: This finding provides a basis for developing nitrogen-fixing bacteria fertilizer and improving the ecological planting efficiency of Astragalus mongholicus.

Isopsoralen Improves Glucocorticoid-induced Osteoporosis by Regulating Purine Metabolism and Promoting cGMP/PKG Pathway-mediated Osteoblast Differentiation.

BACKGROUND: The effects of Isopsoralen (ISO) in promoting osteoblast differentiation and inhibiting osteoclast formation are well-established, but the mechanism underlying ISO's improvement of Glucocorticoid- Induced Osteoporosis (GIOP) by regulating metabolism remains unclear. METHODS: This study aims to elucidate the mechanism of ISO treatment for GIOP through non-targeted metabolomics based on ISO's efficacy in GIOP. Initially, we established a GIOP female mouse model and assessed ISO's therapeutic effects using micro-CT detection, biomechanical testing, serum calcium (Ca), and phosphorus (P) level detection, along with histological analyses using hematoxylin and eosin (HE), Masson, and tartrate-resistant acidic phosphatase (TRAP) staining. Subsequently, non-targeted metabolomics was employed to investigate ISO's impact on serum metabolites in GIOP mice. RT-qPCR and Western blot analyses were conducted to measure the levels of enzymes associated with these metabolites. Building on the metabolomic results, we explored the effects of ISO on the cyclic Guanosine Monophosphate (cGMP)/Protein Kinase G (PKG) pathway and its role in mediating osteoblast differentiation. RESULTS: Our findings demonstrate that ISO intervention effectively enhances the bone microarchitecture and strength of GIOP mice. It mitigates pathological damage, such as structural damage in bone trabeculae, reduced collagen fibers, and increased osteoclasts, while improving serum Ca and P levels in GIOP mice. Non-- targeted metabolomics revealed purine metabolism as a common pathway between the Control and GIOP groups, as well as between the ISO high-dose (ISOH) group and the GIOP group. ISO intervention upregulated inosine and adenosine levels, downregulated guanosine monophosphate levels, increased Adenosine Deaminase (ADA) expression, and decreased cGMP-specific 3',5'-cyclic phosphodiesterase (PDE5) expression. Additionally, ISO intervention elevated serum cGMP levels, upregulated PKGI and PKGII expression in bone tissues, as well as the expression of Runt-related transcription factor 2 (Runx2) and Osterix, and increased serum Alkaline Phosphatase (ALP) activity. CONCLUSION: In summary, ISO was able to enhance the bone microstructure and bone strength of GIOP mice and improve their Ca, P, and ALP levels, which may be related to ISO's regulation of purine metabolism and promotion of osteoblast differentiation mediated by the cGMP/PKG pathway. This suggests that ISO is a potential drug for treating GIOP. However, further research is still needed to explore the specific targets and clinical applications of ISO.

Finding the best predictive model for hypertensive depression in older adults based on machine learning and metabolomics research.

Objective: Depression is a common comorbidity in hypertensive older adults, yet depression is more difficult to diagnose correctly. Our goal is to find predictive models of depression in hypertensive patients using a combination of various machine learning (ML) methods and metabolomics. Methods: Methods We recruited 379 elderly people aged ≥65 years from the Chinese community. Plasma samples were collected and assayed by gas chromatography/liquid chromatography-mass spectrometry (GC/LC-MS). Orthogonal partial least squares discriminant analysis (OPLS-DA), volcano diagrams and thermograms were used to distinguish metabolites. The attribute discriminators CfsSubsetEval combined with search method BestFirst in WEKA software was used to find the best predicted metabolite combinations, and then 24 classification methods with 10-fold cross-validation were used for prediction. Results: 34 individuals were considered hypertensive combined with depression according to our criteria, and 34 subjects with hypertension only were matched according to age and sex. 19 metabolites by GC-MS and 65 metabolites by LC-MS contributed significantly to the differentiation between the depressed and non-depressed cohorts, with a VIP value of more than 1 and a P value of less than 0.05. There were multiple metabolic pathway alterations. The metabolite combinations screened with WEKA for optimal diagnostic value included 12 metabolites. The machine learning methods with AUC values greater than 0.9 were bayesNet and random forests, and their other evaluation measures are also better. Conclusion: Altered metabolites and metabolic pathways are present in older adults with hypertension combined with depression. Methods using metabolomics and machine learning performed quite well in predicting depression in hypertensive older adults, contributing to further clinical research.

Potential nutritional and functional matters in yeast culture prepared by soybean meal fermentation.

BACKGROUND: Yeast culture (YC) is a product fermented on a specific medium, which is a type of postbiotic of anaerobic solid-state fermentation. Although YC has positive effects on the animal growth and health, it contains a variety of beneficial metabolites as dark matter, which have not been quantified. In the present study, liquid chromatography-tandem mass spectrometry is employed to identify the unknown metabolites. Following their identification, the important chemicals are quantified using HPLC-diode array detection methods. RESULTS: Non-targeted metabolomics studies showed that 670 metabolites in total were identified in YC, of which 23 metabolites significantly increased, including organic acids, amino acids, nucleosides and purines, isoflavones, and other substances. The chemical quantitative analysis showed that the contents of succinic acid, aminobutyric acid, glutamine, purine and daidzein increased by 84.42%, 51.07%, 100%, 68.85% and 4.60%, respectively. CONCLUSION: Therefore, the use of non-targeted metabolomics combined with chemical quantitative analysis to reveal the nutritional and functional substances of YC could help to elucidate the postbiotic mechanism and provide theoretical support for the regulation of the directional accumulation of beneficial metabolites. © 2024 Society of Chemical Industry.

Recent Advancement in NMR Based Plant Metabolomics: Techniques, Tools, and Analytical Approaches.

Plant metabolomics, a rapidly advancing field within plant biology, is dedicated to comprehensively exploring the intricate array of small molecules in plant systems. This entails precisely gathering comprehensive chemical data, detecting numerous metabolites, and ensuring accurate molecular identification. Nuclear magnetic resonance (NMR) spectroscopy, with its detailed chemical insights, is crucial in obtaining metabolite profiles. Its widespread application spans various research disciplines, aiding in comprehending chemical reactions, kinetics, and molecule characterization. Biotechnological advancements have further expanded NMR's utility in metabolomics, particularly in identifying disease biomarkers across diverse fields such as agriculture, medicine, and pharmacology. This review covers the stages of NMR-based metabolomics, including historical aspects and limitations, with sample preparation, data acquisition, spectral processing, analysis, and their application parts.

Widely Targeted Metabolomic Analysis Reveals the Improvement in Panax notoginseng Triterpenoids Triggered by Arbuscular Mycorrhizal Fungi via UPLC-ESI-MS/MS.

Panax notoginseng is a highly valued perennial medicinal herb in China and is widely used in clinical treatments. The main purpose of this study was to elucidate the changes in the composition of P. notoginseng saponins (PNSs), which are the main bioactive substances, triggered by arbuscular mycorrhizal fungi (AMF) via ultrahigh-performance liquid chromatography-electrospray ionization-tandem mass spectrometry (UPLC-ESI-MS/MS). A total of 202 putative terpenoid metabolites were detected, of which 150 triterpene glycosides were identified, accounting for 74.26% of the total. Correlation analysis, principal component analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS-DA) of the metabolites revealed that the samples treated with AMF (group Ce) could be clearly separated from the CK samples. In total, 49 differential terpene metabolites were identified between the Ce and CK groups, of which 38 and 11 metabolites were upregulated and downregulated, respectively, and most of the upregulated differentially abundant metabolites were mainly triterpene glycosides. The relative abundances of the two major notoginsenosides (MNs), ginsenosides Rd and Re, and 13 rare notoginsenosides (RNs), significantly increased. The differential saponins, especially RNs, were more easily clustered into one branch and had a high positive correlation. It could be concluded that the biosynthesis and accumulation of some RNs share the same pathways as those triggered by AMF. This study provides a new way to obtain more notoginsenoside resources, particularly RNs, and sheds new light on the scientization and rationalization of the use of AMF agents in the ecological planting of medicinal plants.

First Data on the (Poly)phenolic Profiling of Farmacista Honorati Persimmon Fruit (Diospyros kaki Thunb.) at Commercial Harvest and after Treatments for Astringency Removal.

This study aims to provide the first report on the soluble and polyphenolic profiles of "Farmacista Honorati" (FH) persimmons, which is a marketed cultivar with no existing data on its nutraceutical value. Total soluble tannins (TSTs) and major soluble (poly)phenols in FH fruits before and after post-harvest commercial treatments with carbon dioxide and ethylene were analyzed. Fruits at commercial harvest had a TST content of 1022 ± 286 mg GAL/100 g d.w. Whereas, after deastringency treatments, an 85% and 83% reduction were observed for carbon dioxide- and ethylene-treated fruits, respectively. Carbon dioxide treatment resulted in the insolubilization of tannins around comparable values in most fruit cultivars, despite the variable soluble tannin content in untreated fruit. By targeted metabolomic profiling, nineteen (poly)phenolic substances were quantified in the investigated untreated and treated fruits. Gallic acid (99 mg/100 g d.w.), (+)-catechin (1.8 mg/100 g d.w.), ellagic acid (1.2 mg/100 g d.w.), and (-)-epicatechin (1.1 mg/100 g d.w.) were the predominant compounds in the untreated FH samples. After the application of post-harvest treatments, a non-nutraceutical relevant decrease of 8-19% in the targeted (poly)phenolic content was generally observed. Ethylene induced the most significant reduction in the individual (poly)phenolic compounds in the FH fruits.

Hybrid Explainable Artificial Intelligence Models for Targeted Metabolomics Analysis of Diabetic Retinopathy.

BACKGROUND: Diabetic retinopathy (DR) is a prevalent microvascular complication of diabetes mellitus, and early detection is crucial for effective management. Metabolomics profiling has emerged as a promising approach for identifying potential biomarkers associated with DR progression. This study aimed to develop a hybrid explainable artificial intelligence (XAI) model for targeted metabolomics analysis of patients with DR, utilizing a focused approach to identify specific metabolites exhibiting varying concentrations among individuals without DR (NDR), those with non-proliferative DR (NPDR), and individuals with proliferative DR (PDR) who have type 2 diabetes mellitus (T2DM). METHODS: A total of 317 T2DM patients, including 143 NDR, 123 NPDR, and 51 PDR cases, were included in the study. Serum samples underwent targeted metabolomics analysis using liquid chromatography and mass spectrometry. Several machine learning models, including Support Vector Machines (SVC), Random Forest (RF), Decision Tree (DT), Logistic Regression (LR), and Multilayer Perceptrons (MLP), were implemented as solo models and in a two-stage ensemble hybrid approach. The models were trained and validated using 10-fold cross-validation. SHapley Additive exPlanations (SHAP) were employed to interpret the contributions of each feature to the model predictions. Statistical analyses were conducted using the Shapiro-Wilk test for normality, the Kruskal-Wallis H test for group differences, and the Mann-Whitney U test with Bonferroni correction for post-hoc comparisons. RESULTS: The hybrid SVC + MLP model achieved the highest performance, with an accuracy of 89.58%, a precision of 87.18%, an F1-score of 88.20%, and an F-beta score of 87.55%. SHAP analysis revealed that glucose, glycine, and age were consistently important features across all DR classes, while creatinine and various phosphatidylcholines exhibited higher importance in the PDR class, suggesting their potential as biomarkers for severe DR. CONCLUSION: The hybrid XAI models, particularly the SVC + MLP ensemble, demonstrated superior performance in predicting DR progression compared to solo models. The application of SHAP facilitates the interpretation of feature importance, providing valuable insights into the metabolic and physiological markers associated with different stages of DR. These findings highlight the potential of hybrid XAI models combined with explainable techniques for early detection, targeted interventions, and personalized treatment strategies in DR management.

Widely targeted metabolomics reveals the phytoconstituent changes in Platostoma palustre leaves and stems at different growth stages.

Platostoma palustre (Blume) A. J. Paton is an important edible and medicinal plant. To gain a comprehensive and clear understanding of the variation patterns of metabolites in P. palustre, we employed the UPLC-MS platform along with widely targeted metabolomics techniques to analyze the metabolites in the stems and leaves of P. palustre at different stages. Our results revealed a total of 1228 detected metabolites, including 241 phenolic acids, 203 flavonoids, 152 lipids, 128 terpenes, 106 amino acids, 79 organic acids, 74 saccharides, 66 alkaloids, 44 lignans, etc. As the growth time increased, the differential metabolites (DAMs) mainly enriched in P. palustre leaves were terpenoids, phenolic acids, and lipids, while the DAMs primarily enriched in stems were terpenoids. Compared to stems, there were more differential flavonoids in leaves, and saccharides and flavonoids were significantly enriched in leaves during the S1 and S2 stages. Additionally, we identified 13, 10, and 23 potential markers in leaf, stem, and leaf vs. stem comparison groups. KEGG enrichment analysis revealed that arginine biosynthesis was the common differential metabolic pathway in different growth stages and tissues. Overall, this study comprehensively analyzed the metabolic profile information of P. palustre, serving as a solid foundation for its further development and utilization.

Selenium-enriched yeast, a selenium supplement, improves the rheological properties and processability of dough: From the view of yeast metabolism and gluten alteration.

This study investigated the effect mechanism of selenium (Se)-enriched yeast on the rheological properties of dough from the perspective of yeast metabolism and gluten alteration. As the yeast Se content increased, the gas production rate of Se-enriched yeast slowed down, and dough viscoelasticity decreased. The maximum creep of Se-enriched dough increased by 29%, while the final creep increased by 54%, resulting in a softer dough. Non-targeted metabolomics analyses showed that Se inhibited yeast energy metabolism and promoted the synthesis of stress-resistance related components. Glutathione, glycerol, and linoleic acid contributed to the rheological property changes of the dough. The fractions and molecular weight distribution of protein demonstrated that the increase in yeast Se content resulted in the depolymerization of gluten. The intermolecular interactions, fluorescence spectrum and disulfide bond analysis showed that the disruption of intermolecular disulfide bond induced by Se-enriched yeast metabolites played an important role in the depolymerization of gluten.

Characterization of the gut microbiota and fecal metabolome in the osteosarcoma mouse model.

Previous studies have reported the correlation between gut microbiota (GM), GM-derived metabolites, and various intestinal and extra-intestinal cancers. However, limited studies have investigated the correlation between GM, GM-derived metabolites, and osteosarcoma (OS). This study successfully established a female BALB/c nude mouse model of OS. Mice (n = 14) were divided into the following two groups (n = 7/group): OS group named OG, injected with Saos-2 OS cells; normal control group named NCG, injected with Matrigel. The GM composition and metabolites were characterized using 16S rDNA sequencing and untargeted metabolomics, respectively. Bioinformatics analysis revealed that amino acid metabolism was dysregulated in OS. The abundances of bone metabolism-related genera Alloprevotella, Rikenellaceae_RC9_gut_group, and Muribaculum were correlated with amino acid metabolism, especially histidine metabolism. These findings suggest the correlation between GM, GM-derived metabolites, and OS pathogenesis. Clinical significance: The currently used standard therapeutic strategies for OS, including surgery, chemotherapy, and radiation, are not efficacious. The findings of this study provided novel insights for developing therapeutic, diagnostic, and prognostic strategies for OS.

Assessing a respiratory toxic infectious bronchitis virus (IBV) strain: isolation, identification, pathogenicity, and immunological failure insights.

Infectious bronchitis virus (IBV) is caused by avian coronavirus and poses a global economic threat to the poultry industry. In 2023, a highly pathogenic IBV strain, IBV/CN/GD20230501, was isolated and identified from chickens vaccinated with IBV-M41 in Guangdong, China. This study comprehensively investigated the biological characteristics of the isolated IBV strain, including its genotype, whole genome sequence analysis of its S1 gene, pathogenicity, host immune response, and serum non-targeted metabolomics. Through the analysis of the S1 gene sequence, serum neutralization tests, and comparative genomics, it was proven that IBV/CN/GD20230501 belongs to the GI-I type of strain and is serotype II. One alanine residue in the S1 subunit of the isolated strain was mutated into serine, and some mutations were observed in the ORF1ab gene and the terminal region of the genome. Animal challenge experiments using the EID50 and TCID50 calculations showed that IBV/CN/GD20230501 possesses strong respiratory pathogenicity, with early and long-term shedding of viruses and rapid viral spread. Antibody detection indicated that chickens infected with IBV/CN/GD20230501 exhibited delayed expression of early innate immune genes, while those infected with M41 showed rapid gene induction and effective viral control. Metabolomics analysis demonstrated that this virus infection led to differential expression of 291 ions in chicken serum, mainly affecting the citric acid cycle (tricarboxylic acid cycle).IMPORTANCEThis study identified an infectious bronchitis virus (IBV) strain isolated from vaccinated chickens in an immunized population that had certain sequence differences compared to IBV-M41, resulting in significantly enhanced pathogenicity and host defense. This strain has the potential to replace M41 as a more suitable challenge model for drug research. The non-targeted metabolomics analysis highlighting the citric acid cycle provides a new avenue for studying this highly virulent strain.

To explore the mechanism of acupoint application in the treatment of primary dysmenorrhea by 16S rDNA sequencing and metabolomics.

Graphene-based warm uterus acupoint paste (GWUAP) is an emerging non-drug alternative therapy for the treatment of primary dysmenorrhea (PD), but the underlying mechanism is still unclear. SD female rats were randomly divided into control group, model group and treatment group to explore the mechanism of GWUAP in the treatment of PD. Combined with 16S rDNA and fecal metabolomics, the diversity of microbiota and metabolites in each group was comprehensively evaluated. In this study, GWUAP reduced the torsion score of PD model rats, improved the pathological morphology of uterine tissue, reduced the pathological damage score of uterine tissue, and reversed the expression levels of inflammatory factors, pain factors and sex hormones. The 16 S rDNA sequencing of fecal samples showed that the abundance of Lactobacillus in the intestinal flora of the model group decreased and the abundance of Romboutsia increased, while the abundance of Lactobacillus in the intestinal flora of the treatment group increased and the abundance of Romboutsia decreased, which improved the imbalance of flora diversity in PD rats. In addition, 32 metabolites related to therapeutic effects were identified by metabolomics of fecal samples. Moreover, there is a close correlation between fecal microbiota and metabolites. Therefore, the mechanism of GWUAP in the treatment of PD remains to be further studied.

A new chemical derivatization reagent sulfonyl piperazinyl for the quantification of fatty acids using LC-MS/MS.

In our previous study, a chemical derivatization reagent named 5-(dimethylamino) naphthalene-1-sulfonyl piperazine (Dns-PP) was developed to enhance the chromatographic retention and the mass spectrometric response of free fatty acids (FFAs) in reversed-phase liquid chromatography coupled with electrospray ionization-mass spectrometry (RPLC-ESI-MS). However, Dns-PP exhibited strong preferences for long-chain FFAs, with limited improvement for short- or medium-chain FFAs. In this study, a new series of labeling reagents targeting FFAs were designed, synthesized, and evaluated. Among these reagents, Tmt-PP (N2, N2, N4, N4-tetramethyl-6-(4-(piperazin-1-ylsulfonyl) phenyl)-1,3,5-triazine-2,4-diamine) exhibited the best MS response and was selected for further evaluations. We compared Tmt-PP with Dns-PP and four commonly used carboxyl labeling reagents from existing studies, demonstrating the advantages of Tmt-PP. Further comparisons between Tmt-PP and Dns-PP in measuring FFAs from biological samples revealed that Tmt-PP labeling enhanced the MS response for about 80 % (30/38) of the measured FFAs, particularly for short- and medium-chain FFAs. Moreover, Tmt-PP labeling significantly improved the chromatographic retention of short-chain FFAs. To ensure accurate quantification, we developed a stable isotope-labeled Tmt-PP (i.e., d12-Tmt-PP) to react with chemical standards and serve as one-to-one internal standards (IS). The method was validated for accuracy, precision, sensitivity, linearity, stability, extraction efficiency, as well as matrix effect. Overall, this study introduced a new chemical derivatization reagent Tmt-PP (d12-Tmt-PP), providing a sensitive and accurate option for quantifying FFAs in biological samples.

Metabolomics of repetitive myocardial stunning in chronic multivessel coronary artery stenosis: Effect of non-selective and selective ß1-receptor blockers.

Chronic coronary artery stenosis can lead to regional myocardial dysfunction in the absence of myocardial infarction by repetitive stunning, hibernation or both. The molecular mechanisms underlying repetitive stunning-associated myocardial dysfunction are not clear. We used non-targeted metabolomics to elucidate responses to chronically stunned myocardium in a canine model with and without ß-adrenergic blockade treatment. After development of left ventricular systolic dysfunction induced by ameroid constrictors on the coronary arteries, animals were randomized to 3 months of placebo, metoprolol or carvedilol. We compared these two ß-blockers with their different ß-adrenergic selectivities on myocardial function, perfusion and metabolic pathways involved in tissue undergoing chronic stunning. Control animals underwent sham surgery. Dysfunction in stunned myocardium was associated with reduced fatty acid oxidation and enhanced ketogenic amino acid metabolism, together with alterations in mitochondrial membrane phospholipid composition. These changes were consistent with impaired mitochondrial function and were linked to reduced nitric oxide and peroxisome proliferator-activated receptor signalling, resulting in a decline in adenosine monophosphate-activated protein kinase. Mitochondrial changes were ameliorated by carvedilol more than metoprolol, and improvement was linked to nitric oxide and possibly hydrogen sulphide signalling. In summary, repetitive myocardial stunning commonly seen in chronic multivessel coronary artery disease is associated with adverse metabolic remodelling linked to mitochondrial dysfunction and specific signalling pathways. These changes are reversed by ß-blockers, with the non-selective inhibitor having a more favourable impact. This is the first investigation to demonstrate that ß-blockade-associated improvement of ventricular function in chronic myocardial stunning is associated with restoration of mitochondrial function. KEY POINTS: The mechanisms responsible for the metabolic changes associated with repetitive myocardial stunning seen in chronic multivessel coronary artery disease have not been fully investigated. In a canine model of repetitive myocardial stunning, we showed that carvedilol, a non-selective ß-receptor blocker, ameliorated adverse metabolic remodelling compared to metoprolol, a selective ß1-receptor blocker, by improving nitric oxide synthase and adenosine monophosphate protein kinase function, enhancing calcium/calmodulin-dependent protein kinase, probably increasing hydrogen sulphide, and suppressing cyclic-adenosine monophosphate signalling. Mitochondrial fatty acid oxidation alterations were ameliorated by carvedilol to a larger extent than metoprolol; this improvement was linked to nitric oxide and possibly hydrogen sulphide signalling. Both ß-blockers improved the cardiac energy imbalance by reducing metabolites in ketogenic amino acid and nucleotide metabolism. These results elucidated why metabolic remodelling with carvedilol is preferable to metoprolol when treating chronic ischaemic left ventricular systolic dysfunction caused by repetitive myocardial stunning.

Terpinen-4-ol Improves Lipopolysaccharide-Induced Macrophage Inflammation by Regulating Glutamine Metabolism.

Terpinen-4-ol (T-4-O) is an important component of tea tree oil and has anti-inflammatory effects. Currently, there are very few studies on the mechanisms by which T-4-O improves lipopolysaccharide (LPS)-induced macrophage inflammation. In this study, LPS-stimulated mouse RAW264.7 macrophages were used as a model to analyze the effects of T-4-O on macrophage inflammatory factors and related metabolic pathways in an inflammatory environment. The results showed that T-4-O significantly decreased the expression levels of inflammatory cytokines induced by LPS. Cellular metabolism results showed that T-4-O significantly decreased the ratio of the extracellular acidification rate and oxygen consumption rate. Non-targeted metabolomics results showed that T-4-O mainly affected glutamine and glutamate metabolism and glycine, serine, and threonine metabolic pathways. qPCR results showed that T-4-O increased the transcript levels of GLS and GDH and promoted glutamine catabolism. Western blotting results showed that T-4-O inhibited the mTOR and IκB, thereby decreasing NF-κB activity. The overall results showed that T-4-O inhibited mTOR phosphorylation to promote glutamine metabolism and increased cell oxidative phosphorylation levels, thereby inhibiting the expression of LPS-induced inflammatory cytokines.

Impact of three different peak picking software tools on the quality of untargeted metabolomics data.

Data quality and control parameters are becoming more important in metabolomics. For peak picking, open-source or commercial solutions are used. Other publications consider different software solutions or data acquisition types for peak picking, a combination, including proposed and new quality parameters for the process of peak picking, does not exist. This study tries to examine the performance of three different software in terms of reproducibility and quality of their output while also considering new quality parameters to gain a better understanding of resulting feature lists in metabolomics data. We saw best recovery of spiked analytes in MS-DIAL. Reproducibility over multiple projects was good among all software. The total number of features found was consistent for DDA and full scan acquisition in MS-DIAL but full scan data leading to considerably more features in MZmine and Progenesis Qi. Feature linearity proved to be a good quality parameter. Features in MS-DIAL and MZmine, showed good linearity while Progenesis Qi produced large variation, especially in full scan data. Peak width proved to be a very powerful filtering criteria revealing many features in MZmine and Progenesis Qi to be of questionable peak width. Additionally, full scan data appears to produce a disproportionally higher number of short features. This parameter is not yet available in MS-DIAL. Finally, the manual classification of true positive features proved MS-DIAL to perform significantly better in DDA data (62 % true positive) than the two other software in either mode. We showed that currently popular solutions MS-DIAL and MZmine perform well in targeted analysis of spiked analytes as well as in classic untargeted analysis. The commercially available solution Progenesis Qi does not hold any advantage over the two in terms of quality parameters, of which we proposed peak width as a new parameter and showed that already proposed parameters such as feature linearity in samples of increasing concentration are advisable to use.

Changes in the Non-targeted Metabolomic Profile of Three-year-old Toddlers with Elevated Exposure to Polycyclic Aromatic Hydrocarbons.

Objective: To investigate changes in the urinary metabolite profiles of children exposed to polycyclic aromatic hydrocarbons (PAHs) during critical brain development and explore their potential link with the intestinal microbiota. Methods: Liquid chromatography-tandem mass spectrometry was used to determine ten hydroxyl metabolites of PAHs (OH-PAHs) in 36-month-old children. Subsequently, 37 children were categorized into low- and high-exposure groups based on the sum of the ten OH-PAHs. Ultra-high-performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry was used to identify non-targeted metabolites in the urine samples. Furthermore, fecal flora abundance was assessed by 16S rRNA gene sequencing using Illumina MiSeq. Results: The concentrations of 21 metabolites were significantly higher in the high exposure group than in the low exposure group (variable importance for projection > 1, P < 0.05). Most of these metabolites were positively correlated with the hydroxyl metabolites of naphthalene, fluorine, and phenanthrene ( r = 0.336-0.531). The identified differential metabolites primarily belonged to pathways associated with inflammation or proinflammatory states, including amino acid, lipid, and nucleotide metabolism. Additionally, these distinct metabolites were significantly associated with specific intestinal flora abundances ( r = 0.34-0.55), which were mainly involved in neurodevelopment. Conclusion: Higher PAH exposure in young children affected metabolic homeostasis, particularly that of certain gut microbiota-derived metabolites. Further investigation is needed to explore the potential influence of PAHs on the gut microbiota and their possible association with neurodevelopmental outcomes.

Metabolic signatures of metabolic dysfunction-associated steatotic liver disease in severely obese patients.

BACKROUND: Metabolic dysfunction-associated steatotic liver disease (MASLD) can lead to liver fibrosis, cirrhosis, and hepatocellular carcinoma. Still, most patients with MASLD die from cardiovascular diseases indicating metabolic alterations related to both liver and cardiovascular pathology. AIMS AND METHODS: The aim of this study was to assess biologic pathways behind MASLD progression from steatosis to metabolic dysfunction-associated steatohepatitis (MASH) using non-targeted liquid chromatography-mass spectrometry analysis in 106 severely obese individuals (78 women, mean age 47.7 7 ± 9.2 years, body mass index 41.8 ± 4.3 kg/m²) undergoing laparoscopic Roux-en-Y gastric bypass. RESULTS: We identified several metabolites that are associated with MASLD progression. Most importantly, we observed a decrease of lysophosphatidylcholines LPC(18:2), LPC(18:3), and LPC(20:3) and increase of xanthine when comparing those with steatosis to those with MASH. We found that indole propionic acid and threonine were negatively correlated to fibrosis, but not with the metabolic disturbances associated with cardiovascular risk. Xanthine, ketoleucine, and tryptophan were positively correlated to lobular inflammation and ballooning but also with insulin resistance, and dyslipidemia, respectively. The results did not change when taking into account the most important genetic risk factors of MASLD. CONCLUSIONS: Our findings suggest that there are several separate biological pathways, some of them independent of insulin resistance and dyslipidemia, associating with MASLD.

Distinct Gut Microbiota and Arachidonic Acid Metabolism in Obesity-Prone and Obesity-Resistant Mice with a High-Fat Diet.

An imbalance of energy intake and expenditure is commonly considered as the fundamental cause of obesity. However, individual variations in susceptibility to obesity do indeed exist in both humans and animals, even among those with the same living environments and dietary intakes. To further explore the potential influencing factors of these individual variations, male C57BL/6J mice were used for the development of obesity-prone and obesity-resistant mice models and were fed high-fat diets for 16 weeks. Compared to the obesity-prone mice, the obesity-resistant group showed a lower body weight, liver weight, adipose accumulation and pro-inflammatory cytokine levels. 16S rRNA sequencing, which was conducted for fecal microbiota analysis, found that the fecal microbiome's structural composition and biodiversity had changed in the two groups. The genera Allobaculumbiota, SMB53, Desulfovibrio and Clostridium increased in the obesity-prone mice, and the genera Streptococcus, Odoribacter and Leuconostoc were enriched in the obesity-resistant mice. Using widely targeted metabolomics analysis, 166 differential metabolites were found, especially those products involved in arachidonic acid (AA) metabolism, which were significantly reduced in the obesity-resistant mice. Moreover, KEGG pathway analysis exhibited that AA metabolism was the most enriched pathway. Significantly altered bacteria and obesity-related parameters, as well as AA metabolites, exhibited strong correlations. Overall, the phenotypes of the obesity-prone and obesity-resistant mice were linked to gut microbiota and AA metabolism, providing new insight for developing an in-depth understanding of the driving force of obesity resistance and a scientific reference for the targeted prevention and treatment of obesity.