Exploring the anxiolytic mechanism of Fructus gardeniae based on metabolomics, network pharmacology, and molecular docking.

OBJECTIVE: To explore the effect and anxiolytic mechanism of a natural remedy called Fructus gardeniae (FG). METHODS: The elevated-plus maze (EPM) test was used to confirm the anxiolytic effect of FG. The potential and anxiolytic components, targets, and route processes of FG were investigated using the network pharmacology method in conjunction with metabolomics and molecular docking technologies. RESULTS: FG could greatly enhance the proportion of time and times of opening arms, according to the EPM data. As to the metabolomics findings, a total of 61 distinct metabolites were found, mainly involved in glycine, serine, and threonine metabolism as well as alanine, aspartate, and glutamate metabolism. The primary active ingredients of FG, nicotiflorin, jasminodiol, and crocetin, demonstrated substantial binding affinities with monoamine oxidase A (MAOA), monoamine oxidase A (ACHE), malate dehydrogenase 2 (MDH2), glutamate decarboxylase 2 (GAD2), glutamate decarboxylase 1 (GAD1), and nitric oxide synthase (NOS1), according to the findings of network pharmacology and molecular docking. CONCLUSION: FG exerts an anxiolytic action via targeting MAOA, ACHE, MDH2, GAD2, GAD1, and NOS1, and regulating the metabolism of glycine, serine, and threonine as well as alanine, aspartic acid, and glutamic acid.

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.

Dataset for analysis of metabolic pathways and their reversibility associated with anti-proliferative effect of metformin in liver cancer cells.

Despite epidemiological indications, utility of metformin in liver cancer remains debated and the understanding of the mechanism underlying its anti-cancer effects remains incomplete. Particularly, whether it operates via similar mechanism under glucose-sufficient and glucose- deficient environments or whether these effects are reversible remains unexplored. This metabolomic dataset was collected from liver cancer (HepG2) cells treated with metformin or placebo over a period of 3 h to 48 h as well as from cells recovering after metformin withdrawal. Cells were exposed to placebo or 2.5 mM metformin with or without glucose (5 mM) supplementation. The cells were harvested at 3, 6, 12, 24, and 48 h post-treatment. Cells were also harvested after 24 h of treatment under one of these conditions followed by reversal of glucose and/or metformin exposure status for 48 h. Metabolites from six biological replicates of each experimental group were extracted using chilled monophasic metabolite extraction solvent (Water: Acetonitrile: Isopropanol= 2:3:3) containing homovanillic acid as an internal standard. Samples were derivatized using MOX reagent followed by MSTFA. Untargeted metabolomic profiling of derivatized samples were performed using an Agilent 7890B gas chromatograph coupled to a 5977B single quadrupole mass spectrometer. Analytes were injected through a splitless liner and separated on a HP-5MS ultra-inert column using ultrapure helium as the carrier gas. Peak alignment, annotation, and integration were done using Agilent MassHunter Quantitative analysis software. Multivariate analysis was performed using MetaboAnalyst 5.0. These experiments were performed to unravel the longitudinal evolution of cellular metabolome in response to metformin treatment, its glucose dependence, as well as to examine the reversibility of these changes. The dataset can help to identify glucose-independent pathways involved in anti-cancer effect of metformin. The dataset can be used to design experiments to develop novel therapeutic combinations synergistically acting with metformin to cripple the metabolic fitness of cancer cells. It can also help to develop experiments to test the effect of metformin withdrawal in liver cancer.

Antibacterial activity and mechanism of luteolin isolated from Lophatherum gracile Brongn. against multidrug-resistant Escherichia coli.

Infections caused by multidrug-resistant (MDR) bacteria have become a major challenge for global healthcare systems. The search for antibacterial compounds from plants has received increasing attention in the fight against MDR bacteria. As a medicinal and edible plant, Lophatherum gracile Brongn. (L. gracile) has favorable antibacterial effect. However, the main antibacterial active compound and its antimicrobial mechanism are not clear. Here, our study first identified the key active compound from L. gracile as luteolin. Meanwhile, the antibacterial effect of luteolin was detected by using the broth microdilution method and time-kill curve analysis. Luteolin can also cause morphological structure degeneration and content leakage, cell wall/membrane damage, ATP synthesis reduction, and downregulation of mRNA expression levels of sulfonamide and quinolones resistance genes in multidrug-resistant Escherichia coli (MDR E. coli). Furthermore, untargeted UPLC/Q-TOF-MS-based metabolomics analysis of the bacterial metabolites revealed that luteolin significantly changed riboflavin energy metabolism, bacterial chemotaxis cell process and glycerophospholipid metabolism of MDR E. coli. This study suggests that luteolin could be a potential new food additive or preservative for controlling MDR E. coli infection and spread.

Alterations of mouse gut microbiome in alveolar echinococcosis.

Alveolar echinococcosis (AE) may affect the composition of the host's gut microbiota, potentially disrupting the balance between the gut microbiota and metabolites. Metagenomics and untargeted metabolomics were employed to characterize changes in the gut microbiota and metabolites in mouse models infected with E. multilocularis. Pearson correlation coefficients were calculated to compare the distribution of microbiota and metabolites, revealing synergistic or mutually exclusive relationships. Functional outputs of the gut microbiota were explored using the CAZy database and six enzymes involved in carbohydrate metabolism were identified with statistically significant differential expression between infected and control groups. The resistome was characterized by identifying antibiotic resistance genes annotated in the Comprehensive Antibiotic Resistance Database from the metagenomes of the groups. Firmicutes are the main carrier of ARGs in the host gut with tetQ being most prevalent. Antibiotic efflux, inactivation and target modification were the principal mechanisms of resistance. Comparison and analysis of two sets of antibiotic metabolic pathways allowed the identification of enzyme reactions unique to infected mice. KEGG pathway overview shows phenazine biosynthesis involving phzG to be one of them. In conclusion, infection with AE in mice leads to an overall disruption of gut microbiota and metabolites with the involvement of enzymes related to carbohydrate metabolism. Furthermore, antibiotic-resistance genes may play a role in disease progression, offering potential insights into the relationship between antibiotic use in AE and treatment outcomes.

Integrated proteomic and metabolomic profiling of lymph after trauma-induced hypercoagulopathy and antithrombotic therapy.

BACKGROUND: Routine coagulation tests are not widely accepted diagnostic criteria of trauma-induced hypercoagulopathy (TIH) due to insensitivity. Lymphatic vessels drain approximately 10% of the interstitial fluid into the lymphatic system and form lymph. SUBJECTIVE: The purpose of this study was to identify the potential lymph biomarkers for TIH. METHODS: Eighteen male Sprague-Dawley rats were randomly assigned to the sham (non-fractured rats with sham surgery and vehicle treatment), the VEH (fractured rats with vehicle treatment) and the CLO (fractured rats with clopidogrel treatment) group. Thoracic duct lymph was obtained to perform proteomics and untargeted metabolomics. RESULTS: A total of 1207 proteins and 16,695 metabolites were identified. The top 5 GO terms of lymph proteomics indicated that oxidative stress and innate immunity were closely associated with TIH and antithrombotic therapy. The top 5 GO terms of lymph metabolomics showed that homocystine and lysophosphatidylcholine were the differential expressed metabolites (DEMs) between the sham and VEH groups, while cholic acid, docosahexaenoic acid, N1-Methyl-2-pyridone-5-carboxamide, isoleucine and testosterone are the DEMs between the VEH and CLO group. CONCLUSIONS: This study presents the first proteomic and metabolomic profiling of lymph after TIH and antithrombotic therapy, and predicts the possible lymph biomarkers for TIH.

Untargeted metabolomics revealed the mechanism of aucubin on glucocorticoid-induced osteoporosis in mice through modulating arachidonic acid metabolism.

Glucocorticoid-induced osteoporosis (GIOP) represents the most prevalent form of secondary osteoporosis. Aucubin (AU), a principal active component found in traditional herbal medicines such as Eucommia ulmoides, has been demonstrated to enhance osteoblast differentiation. Nonetheless, the precise therapeutic effects of AU on GIOP and the complex underlying regulatory mechanisms warrant further investigation. We first established a GIOP model in female mice and then assessed the therapeutic effects of AU using micro-CT analysis, biomechanical testing, measurements of serum calcium (Ca) and phosphorus (P) levels, and histological analyses using Hematoxylin and Eosin (HE) and Masson staining. Subsequently, non-targeted metabolomics was employed in order to study the effects of AU on serum metabolites in GIOP mice. The levels of the factors related to these metabolites were quantified using real-time quantitative reverse transcription polymerase chain reaction (RT-qPCR) and western blot analyses. Finally, the effects of AU on osteoblastic and osteoclastic differentiation were examined. We found that AU significantly ameliorated bone microarchitecture and strength in GIOP mice. It mitigated pathological damages such as impairment of trabecular bone structure and reduction in collagen fibers, while concurrently elevating serum levels of Ca and P. Non-targeted metabolomics revealed that Arachidonic acid (AA) metabolism serves as a common pathway between the control and GIOP groups, as well as between the high-dose AU (AUH) and GIOP groups. AU notably upregulates prostaglandin-endoperoxide synthase 2 (PTGS2) and microsomal prostaglandin-E synthase 1 (PTGES) expression and downregulates prostaglandin-H2 D-isomerase (PTGDS) expression. Furthermore, AU treatment increased the expression of runt-related transcription factor 2 (Runx2) and transcription factor Sp7 (Osterix), enhanced serum alkaline phosphatase (ALP) activity, and reduced osteoclast expression. These results indicate that AU is a potential drug for treating GIOP, and its mechanism is related to regulating AA metabolism and promoting osteoblast differentiation. However, the key targets of AU in treating GIOP still need further exploration.

Untargeted metabolomics combined with vitro antioxidant to comprehensively evaluate the effect of sodium sulfite immersion on the holistic quality of mung bean sprouts.

Mung bean sprouts are widely consumed as a seasonal fresh vegetable, renowned for their affordability and richness in antioxidants and bioactive compounds. This study employed ultra-high-performance liquid chromatogram-Q-Exactive HF mass spectrometry (UHPLC-QE-MS) and multivariate statistical analysis to comprehensively evaluate the chemical profile of mung bean sprouts following sulfite immersion. The findings revealed a significant alteration in the overall chemical composition of mung bean sprouts following sodium sulfite immersion. Eleven components, including four sulfur-containing compounds, were identified as characteristic markers distinguishing between non-immersed and sodium sulfite-immersed mung bean sprouts. Esterification and addition reactions were inferred to occur during sodium sulfite immersion, leading to the transformation of flavonoid and saponin sulfates. Commercial samples analysis indicated that sulfur-containing compounds were detectable in 9 of 11 commercial mung bean sprouts. Meanwhile, when sodium sulfite concentration exceeded 3.00 mg/mL and immersion time exceeded 360 min, the contents of total polyphenol and flavonoid were significantly reduced and the antioxidant activity was adversely influenced.

Integrative Metabolomics, Enzymatic Activity, and Gene Expression Analysis Provide Insights into the Metabolic Profile Differences between the Slow-Twitch Muscle and Fast-Twitch Muscle of Pseudocaranx dentex.

The skeletal muscles of teleost fish encompass heterogeneous muscle types, termed slow-twitch muscle (SM) and fast-twitch muscle (FM), characterized by distinct morphological, anatomical, histological, biochemical, and physiological attributes, driving different swimming behaviors. Despite the central role of metabolism in regulating skeletal muscle types and functions, comprehensive metabolomics investigations focusing on the metabolic differences between these muscle types are lacking. To reveal the differences in metabolic characteristics between the SM and FM of teleost, we conducted an untargeted metabolomics analysis using Pseudocaranx dentex as a representative model and identified 411 differential metabolites (DFMs), of which 345 exhibited higher contents in SM and 66 in FM. KEGG enrichment analysis showed that these DFMs were enriched in the metabolic processes of lipids, amino acids, carbohydrates, purines, and vitamins, suggesting that there were significant differences between the SM and FM in multiple metabolic pathways, especially in the metabolism of energy substances. Furthermore, an integrative analysis of metabolite contents, enzymatic activity assays, and gene expression levels involved in ATP-PCr phosphate, anaerobic glycolysis, and aerobic oxidative energy systems was performed to explore the potential regulatory mechanisms of energy metabolism differences. The results unveiled a set of differential metabolites, enzymes, and genes between the SM and FM, providing compelling molecular evidence of the FM achieving a higher anaerobic energy supply capacity through the ATP-PCr phosphate and glycolysis energy systems, while the SM obtains greater energy supply capacity via aerobic oxidation. These findings significantly advance our understanding of the metabolic profiles and related regulatory mechanisms of skeletal muscles, thereby expanding the knowledge of metabolic physiology and ecological adaptation in teleost fish.

Untargeted Metabolomics Analysis Based on LC-QTOF-MS to Investigate the Phenolic Composition of Red and White Wines Elaborated from Sonicated Grapes.

Ultrasounds are considered an emerging technology in the wine industry. Concretely, in 2019, the International Organization of Vine and Wine (OIV) officially approved their use for the treatment of crushed grapes to increase the level of phenolic compound extraction. The main objective of this study was to validate an untargeted metabolomics approach as an analytical tool for identifying novel markers associated with sonication. To do so, the influence of a sonication treatment on the metabolic profile was studied in four typically commercial varietal wines, i.e., two red wines from 'Syrah' and 'Cabernet Sauvignon' grapes and two white wines from 'Macabeo' and 'Airén' grapes. A robust classification and prediction model was created employing supervised techniques such as partial least-squares discriminant analysis (PLS-DA). The findings indicated that the grapes subjected to high-power ultrasound conditions experienced cell wall disruption due to the cavitation phenomenon, resulting in significant changes in various phenolic compounds (including hydroxycinnamic acids and flavonoids) present in these wines compared to wines from non-sonicated grapes. Additionally, new metabolites were tentatively identified through untargeted metabolomics techniques. This study represents the successful application of the untargeted metabolomics approach employing a UHPLC-QTOF system to discern how grape sonication affects bioactive secondary metabolites in wines.

Exploratory Untargeted Metabolomics of Dried Blood Spot Samples from Newborns with Maple Syrup Urine Disease.

Currently, tandem mass spectrometry-based newborn screening (NBS), which examines targeted biomarkers, is the first approach used for the early detection of maple syrup urine disease (MSUD) in newborns, followed by confirmatory genetic mutation tests. However, these diagnostic approaches have limitations, demanding the development of additional tools for the diagnosis/screening of MUSD. Recently, untargeted metabolomics has been used to explore metabolic profiling and discover the potential biomarkers/pathways of inherited metabolic diseases. Thus, we aimed to discover a distinctive metabolic profile and biomarkers/pathways for MSUD newborns using untargeted metabolomics. Herein, untargeted metabolomics was used to analyze dried blood spot (DBS) samples from 22 MSUD and 22 healthy control newborns. Our data identified 210 altered endogenous metabolites in MSUD newborns and new potential MSUD biomarkers, particularly L-alloisoleucine, methionine, and lysoPI. In addition, the most impacted pathways in MSUD newborns were the ascorbate and aldarate pathways and pentose and glucuronate interconversions, suggesting that oxidative and detoxification events may occur in early life. Our approach leads to the identification of new potential biomarkers/pathways that could be used for the early diagnosis/screening of MSUD newborns but require further validation studies. Our untargeted metabolomics findings have undoubtedly added new insights to our understanding of the pathogenicity of MSUD, which helps us select the appropriate early treatments for better health outcomes.

Mechanism of Guigan Longmu Decoction in the Treatment of Arrhythmias Based on Network Pharmacology and Untargeted Metabolomics Assays.

BACKGROUND: Guigan longmu decoction (GGLM), a traditional Chinese medicine compound, has demonstrated efficacy in treating rapid arrhythmia clinically. Nevertheless, its mechanism of action remains elusive. This study aims to elucidate the molecular mechanism underlying the efficacy of GGLM in treating arrhythmia utilizing non-targeted metabolomics, widely-targeted metabolomics, and network pharmacology, subsequently validated through animal experiments. METHODS: Initially, network pharmacology analysis and widely-targeted metabolomics were performed on GGLM. Subsequent to that, rats were administered GGLM intervention, and nontargeted metabolomics assays were utilized to identify metabolites in rat plasma postadministration. The primary signaling pathways, core targets, and key active ingredients of GGLM influencing arrhythmia were identified. Additionally, to validate the therapeutic efficacy of GGLM on arrhythmia rat models, a rat model of rapid arrhythmia was induced via subcutaneous injection of isoproterenol, and alterations in pertinent pathogenic pathways and proteins in the rat model were assessed through qRT-PCR and Western blot following GGLM administration. RESULTS: The results of network pharmacology showed that 99 active ingredients in GGLM acted on 249 targets and 201 signaling pathways, which may be key to treating arrhythmia. Widelytargeted metabolic quantification analysis detected a total of 448 active ingredients in GGLM, while non-targeted metabolomics identified 279 different metabolites and 10 major metabolic pathways in rats. A comprehensive analysis of the above results revealed that the core key active ingredients of GGLM in treating arrhythmia include calycosin, licochalcone B, glabridin, naringenin, medicarpin, formononetin, quercetin, isoliquiritigenin, and resveratrol. These active ingredients mainly act on the relevant molecules and proteins upstream and downstream of the MAPK pathway to delay the onset of arrhythmia. Animal experimental results showed that the heart rate of rats in the model group increased significantly, and the mRNA and protein expression of p38, MAPK, JNK, ERK, NF-kb, IL-1ß, and IL-12 in myocardial tissue also increased significantly. However, after intervention with GGLM, the heart rate of rats in the drug group decreased significantly, while the mRNA and protein expression of p38 MAPK, JNK, ERK1, NF-kb, IL-1ß, and IL-12 in myocardial tissue decreased significantly. CONCLUSION: GGLM, as an adjunctive therapy in traditional Chinese medicine, exhibits favorable therapeutic efficacy against arrhythmia. This can be attributed to the abundant presence of bioactive compounds in the formulation, including verminin, glycyrrhizin B, glabridine, naringenin, ononin, quercetin, isorhamnetin, and kaempferol. The metabolites derived from these active ingredients have the potential to mitigate myocardial inflammation and decelerate heart rate by modulating the expression of proteins associated with the MAPK signaling pathway in vivo.

Optimal transport for automatic alignment of untargeted metabolomic data.

Untargeted metabolomic profiling through liquid chromatography-mass spectrometry (LC-MS) measures a vast array of metabolites within biospecimens, advancing drug development, disease diagnosis, and risk prediction. However, the low throughput of LC-MS poses a major challenge for biomarker discovery, annotation, and experimental comparison, necessitating the merging of multiple datasets. Current data pooling methods encounter practical limitations due to their vulnerability to data variations and hyperparameter dependence. Here, we introduce GromovMatcher, a flexible and user-friendly algorithm that automatically combines LC-MS datasets using optimal transport. By capitalizing on feature intensity correlation structures, GromovMatcher delivers superior alignment accuracy and robustness compared to existing approaches. This algorithm scales to thousands of features requiring minimal hyperparameter tuning. Manually curated datasets for validating alignment algorithms are limited in the field of untargeted metabolomics, and hence we develop a dataset split procedure to generate pairs of validation datasets to test the alignments produced by GromovMatcher and other methods. Applying our method to experimental patient studies of liver and pancreatic cancer, we discover shared metabolic features related to patient alcohol intake, demonstrating how GromovMatcher facilitates the search for biomarkers associated with lifestyle risk factors linked to several cancer types.

Changes of microbial communities and metabolites in the fermentation of persimmon vinegar by bioaugmentation fermentation.

To evaluate the effects of bioaugmentation fermentation inoculated with one ester-producing strain (Wickerhamomyces anomalus ZX-1) and two strains of lactic acid bacteria (Lactobacillus plantarum CGMCC 24035 and Lactobacillus acidophilus R2) for improving the flavor of persimmon vinegar, microbial community, flavor compounds and metabolites were analyzed. The results of microbial diversity analysis showed that bioaugmentation fermentation significantly increased the abundance of Lactobacillus, Saccharomyces, Pichia and Wickerhamomyces, while the abundance of Acetobacter, Apiotrichum, Delftia, Komagataeibacter, Kregervanrija and Aspergillus significantly decreased. After bioaugmentation fermentation, the taste was softer, and the sensory irritancy of acetic acid was significantly reduced. The analysis of HS-SPME-GC-MS and untargeted metabolomics based on LC-MS/MS showed that the contents of citric acid, lactic acid, malic acid, ethyl lactate, methyl acetate, isocitrate, acetoin and 2,3-butanediol were significantly increased. By multivariate analysis, 33 differential metabolites were screened out to construct the correlation between the differential metabolites and microorganisms. Pearson correlation analysis showed that methyl acetate, ethyl lactate, betaine, aconitic acid, acetoin, 2,3-butanediol and isocitrate positively associated with Wickerhamomyces and Lactobacillus. The results confirmed that the quality of persimmon vinegar was improved by bioaugmentation fermentation.

Tongue coating metabolic profiles of intra-oral halitosis patients.

OBJECTIVE: This study focused on the metabolic characteristics of tongue coating in patients with intra-oral halitosis (IOH) to investigate potential diagnostic biomarkers for IOH. METHODS: Oral healthy participants were enrolled in this study. Halitosis was evaluated with an organoleptic assessment, a Halimeter®, and an OralChroma™. Tongue coating samples were collected from 18 halitosis patients and 18 healthy controls. Liquid chromatography-mass spectrometry was conducted to reveal the IOH-related metabolic variations in tongue coating. RESULTS: A total of 2214 metabolites were obtained. Most metabolites were shared between the two groups. A total of 274 upregulated metabolites, such as paramethasone acetate and indole-3-acetic acid, and 43 downregulated metabolites, including deoxyadenosine and valyl-arginine, were detected in the halitosis group. Functional analysis indicated that several metabolic pathways, including arginine biosynthesis, arginine and proline metabolism, histidine metabolism, and lysine degradation were significantly enriched in the IOH group. The least absolute shrinkage and selection operator logistic regression analysis revealed that paramethasone acetate, {1-[2-(4-carbamimidoyl-benzoylamino)-propionyl]-piperidin-4-yloxy}-acetic acid, indole-3-acetic acid, and valyl-arginine were remarkably associated with IOH. CONCLUSIONS: This study revealed the metabolites present in tongue coating and identified effective biomarkers, providing essential insights into the prediction, pathogenesis, and diagnosis of IOH.

Study on the correlation and difference of qualitative information among three types of UPLC-HRMS and potential generalization in metabolites annotation.

The variation of qualitative information among different types of mainstream hyphenated instruments of ultra-performance liquid chromatography coupled to high-resolution mass spectrometry (UPLC-HRMS) makes data sharing and standardization, and further comparison of results consistency in metabolite annotation not easy to attain. In this work, a quantitative study of correlation and difference was first achieved to systematically investigate the variation of retention time (tR), precursor ion (MS1), and product fragment ions (MS2) generated by three typical UPLC-HRMS instruments commonly used in metabolomics area. In terms of the findings of systematic and correlated variation of tR, MS1, and MS2 between different instruments, a computational strategy for integrated metabolite annotation was proposed to reduce the influence of differential ions, which made full use of the characteristic (common) and non-common fragments for scoring assessment. The regular variations of MS2 among three instruments under four collision energy voltages of high, medium, low, and hybrid levels were respectively inspected with three technical replicates at each level. These discoveries could improve general metabolite annotation with a known database and similarity comparison. It should provide the potential for metabolite annotation to generalize qualitative information obtained under different experimental conditions or using instruments from various manufacturers, which is still a big headache in untargeted metabolomics. The mixture of standard compounds and serum samples with the addition of standards were applied to demonstrate the principle and performance of the proposed method. The results showed that it could be an optional strategy for general use in HRMS-based metabolomics to offset the difference in metabolite annotation. It has some potential in untargeted metabolomics.

Untargeted metabolic profiling of high-dose methotrexate toxicity shows alteration in betaine metabolism.

Cardiotoxicity is a well-established adverse effect of several drugs across multiple therapeutic indications. It is particularly prevalent following anticancer therapy. In order to evaluate the changes in cellular metabolism associated with methotrexate cardiotoxicity, we treated Wistar rats with a single high dose of methotrexate (HDMTX), and after five days, the animals were sacrificed. We then analyzed the cardiotoxicity parameters in serum like Cardiac enzymes(CK-MB, Troponin T, ALP), Inflammatory markers (TNF-α and IL-6), oxidative stress markers (NO, NOX-2), histopathology and cardiac tissue with the goal of identifying a metabolic signature of cardiotoxicity using discovery-based metabolomics. The biochemical parameters for cardiac enzymes, oxidative stress and inflammatory markers showed a significant increase in all three categories in rats treated with HDMTX. These findings were mirrored in the histopathological analysis confirming cardiotoxicity due to HDMTX. The results showed a total of 95 metabolites that were found to be significantly (p < 0.05) modulated: either up- or downregulated in the HDMTX-treated group when compared with the control group. Using integrated pathway analysis we found these metabolites were associated with many important cardiac tissue metabolic pathways, such as the malate aspartate shuttle, taurine and hypotaurine metabolism, betaine metabolism, spermidine biosynthesis, and homocysteine degradation. Among them, L-arginine, homocysteine, and betaine were significantly upregulated, suggesting their possible association with cardiac tissue injury. Overall, we provided evidence for using untargeted metabolomics to identify novel metabolites associated with HDMTX cardiac toxicity.

A Novel Dry-Cured Ham Broth-Derived Peptide JHBp2 Effectively Inhibits Salmonella typhimurium In Vitro: Integrated Metabolomic, Proteomic, and Molecular Simulation Analyses.

JHBp2 is a peptide purified from Jinhua ham broth with antibacterial activity against Salmonella typhimurium. Untargeted metabolomics and label-free quantitative proteomics were used to analyze metabolic and protein expression changes in S. typhimurium after JHBp2 treatment. Cell wall and membrane damage results indicate that JHBp2 has membrane-disruptive properties, causing leakage of intracellular nucleic acids and proteins. Metabolomics revealed 516 differentially expressed metabolites, involving cofactor biosynthesis, purine metabolism, ABC transporters, glutathione metabolism, pyrimidine metabolism, etc. Proteomics detected 735 differentially expressed proteins, involving pyruvate metabolism, amino acid biosynthesis, purine metabolism, carbon metabolism, glycolysis/gluconeogenesis, etc. RT-qPCR and proteomics results showed a positive correlation, and molecular docking demonstrated stable binding of JHBp2 to some differentially expressed proteins. In summary, JHBp2 could disrupt the S. typhimurium cell wall and membrane structure, interfere with synthesis of membrane-related proteins, trigger intracellular substance leak, and reduce levels of enzymes and metabolites involved in energy metabolism, amino acid anabolism, and nucleotide anabolism.

Changes in Faecal Microbiota Profile and Plasma Biomarkers following the Administration of an Antioxidant Oleuropein-Rich Leaf Extract in a Rat Model Mimicking Colorectal Cancer.

Oleuropein (OLE), a phenolic compound particularly abundant in the olive leaves, has been reported to have beneficial activities against colorectal cancer (CRC). In vitro studies suggested that these latter could be due to a modulation of the intestinal microbiota. Aiming to evaluate if OLE could affect the intestinal microbiota and the plasma metabolome, an antioxidant oleuropein-rich leaf extract (ORLE) was administered for one week to PIRC rats (F344/NTac-Apcam1137), a genetic model mimicking CRC. ORLE treatment significantly modulated the gut microbiota composition. Plasma metabolomic profiles revealed a significant predictive ability for amino acids, medium-chain fatty acids, and aldehydes. Pathway analysis revealed a significant decrease in phosphatidylcholine accumulation (LogFC = -1.67) in PIRC rats. These results suggest a significant effect of ORLE administration on faecal microbiota profiles and plasma metabolomes, thereby offering new omics-based insights into its protective role in CRC progression.

Metabolomic study on ostracods exposed to environmentally relevant concentrations of five pharmaceuticals selected via a novel approach.

Pharmaceuticals (PhACs) are increasingly detected in aquatic ecosystems, yet their effects on biota remain largely unknown. The environmentally relevant concentrations of many PhACs may not result in individual-level responses, like mortality or growth inhibition, traditional toxicity endpoints. However, this doesn't imply the absence of negative effects on biota. Metabolomics offers a more sensitive approach, detecting responses at molecular and cellular levels and providing mechanistic understanding of adverse effects. We evaluated bioaccumulation and metabolic alterations in a benthic ostracod, Heterocypris incongruens, exposed to a mixture of five PhACs (carbamazepine, tiapride, tolperisone, propranolol and amlodipine) at environmentally relevant concentrations for 7 days using liquid chromatography coupled with mass spectrometry. The selection of PhACs was based, among other factors, on risk quotient values determined using toxicological data available in the literature and concentrations of PhACs quantified in our previous research in the sediments of the Odra River estuary. This represents a novel approach to PhACs selection for metabolomic studies that considers strictly quantitative data. Amlodipine and tolperisone exhibited the highest bioaccumulation. Significant impacts were observed in Alanine, aspartate and glutamate metabolism, Starch and sucrose metabolism, Arginine biosynthesis, Histidine metabolism, Tryptophan metabolism, Glycerophospholipid metabolism, and Glutathione metabolism pathways. Most of the below-individual-level responses were likely nonspecific and related to dysregulation in energy metabolism and oxidative stress response. Additionally, some pharmaceutical-specific responses were also observed. Therefore, untargeted metabolomics can be used to detect metabolic changes resulting from environmentally relevant concentrations of PhACs in aquatic ecosystems and to understand their underlying mechanism.