PubMed

Metabolomics. 2024 Feb 23;20(2):25. doi: 10.1007/s11306-024-02094-2.ABSTRACTINTRODUCTION: Human African trypanosomiasis, commonly known as sleeping sickness, is a vector-borne parasitic disease prevalent in sub-Saharan Africa and transmitted by the tsetse fly. Suramin, a medication with a long history of clinical use, has demonstrated varied modes of action against Trypanosoma brucei. This study employs a comprehensive workflow to investigate the metabolic effects of suramin on T. brucei, utilizing a multimodal metabolomics approach.OBJECTIVES: The primary aim of this study is to comprehensively analyze the metabolic impact of suramin on T. brucei using a combined liquid chromatography-mass spectrometry (LC-MS) and nuclear magnetic resonance spectroscopy (NMR) approach. Statistical analyses, encompassing multivariate analysis and pathway enrichment analysis, are applied to elucidate significant variations and metabolic changes resulting from suramin treatment.METHODS: A detailed methodology involving the integration of high-resolution data from LC-MS and NMR techniques is presented. The study conducts a thorough analysis of metabolite profiles in both suramin-treated and control T. brucei brucei samples. Statistical techniques, including ANOVA-simultaneous component analysis (ASCA), principal component analysis (PCA), ANOVA 2 analysis, and bootstrap tests, are employed to discern the effects of suramin treatment on the metabolomics outcomes.RESULTS: Our investigation reveals substantial differences in metabolic profiles between the control and suramin-treated groups. ASCA and PCA analysis confirm distinct separation between these groups in both MS-negative and NMR analyses. Furthermore, ANOVA 2 analysis and bootstrap tests confirmed the significance of treatment, time, and interaction effects on the metabolomics outcomes. Functional analysis of the data from LC-MS highlighted the impact of treatment on amino-acid, and amino-sugar and nucleotide-sugar metabolism, while time effects were observed on carbon intermediary metabolism (notably glycolysis and di- and tricarboxylic acids of the succinate production pathway and tricarboxylic acid (TCA) cycle).CONCLUSION: Through the integration of LC-MS and NMR techniques coupled with advanced statistical analyses, this study identifies distinctive metabolic signatures and pathways associated with suramin treatment in T. brucei. These findings contribute to a deeper understanding of the pharmacological impact of suramin and have the potential to inform the development of more efficacious therapeutic strategies against African trypanosomiasis.PMID:38393408 | DOI:10.1007/s11306-024-02094-2

Toxics. 2024 Feb 4;12(2):128. doi: 10.3390/toxics12020128.ABSTRACTSmoking is an established risk factor for various pathologies including lung cancer. Electronic cigarettes (e-cigs) and heated tobacco products (HTPs) have appeared on the market in recent years, but their safety or, conversely, their toxicity has not yet been demonstrated. This study aimed to compare the metabolome of human lung epithelial cells exposed to emissions of e-cigs, HTPs, or 3R4F cigarettes in order to highlight potential early markers of toxicity. BEAS-2B cells were cultured at the air-liquid interface and exposed to short-term emissions from e-cigs set up at low or medium power, HTPs, or 3R4F cigarettes. Untargeted metabolomic analyses were performed using liquid chromatography coupled with mass spectrometry. Compared to unexposed cells, both 3R4F cigarette and HTP emissions affected the profiles of exogenous compounds, one of which is carcinogenic, as well as those of endogenous metabolites from various pathways including oxidative stress, energy metabolism, and lipid metabolism. However, these effects were observed at lower doses for cigarettes (2 and 4 puffs) than for HTPs (60 and 120 puffs). No difference was observed after e-cig exposure, regardless of the power conditions. These results suggest a lower acute toxicity of e-cig emissions compared to cigarettes and HTPs in BEAS-2B cells. The pathways deregulated by HTP emissions are also described to be altered in respiratory diseases, emphasizing that the toxicity of HTPs should not be underestimated.PMID:38393223 | DOI:10.3390/toxics12020128

Toxins (Basel). 2024 Jan 23;16(2):62. doi: 10.3390/toxins16020062.ABSTRACTIn the original publication [...].PMID:38393190 | DOI:10.3390/toxins16020062

Toxins (Basel). 2024 Feb 17;16(2):110. doi: 10.3390/toxins16020110.ABSTRACTCommon bloom-forming cyanobacteria produce complex strain-specific mixtures of secondary metabolites. The beneficial and toxic properties of these metabolite mixtures have attracted both research and public health interest. The advancement of mass spectrometry-based platforms and metabolomics data processing has accelerated the identification of new metabolites and feature dereplication from microbial sources. The objective of this study was to use metabolomics data processing to decipher the intracellular cyanopeptide diversity of six Planktothrix strains collected from Canadian lakes. Data-dependent acquisition experiments were used to collect a non-targeted high-resolution mass spectrometry dataset. Principal component analysis and factor loadings were used to visualize cyanopeptide variation between strains and identified features contributing to the observed variation. GNPS molecular networking was subsequently used to show the diversity of cyanopeptides produced by the Planktothrix strains. Each strain produced a unique mixture of cyanopeptides, and a total of 225 cyanopeptides were detected. Planktothrix sp. CPCC 735 produced the most (n = 68) cyanopeptides, and P. rubescens CPCC 732 produced the fewest (n = 27). Microcystins and anabaenopeptins were detected from all strains. Cyanopeptolins, microviridins and aeruginosins were detected from five, four and two strains, respectively. Cyanopeptolin (n = 80) and anabaenopeptin (n = 61) diversity was the greatest, whereas microcystins (n = 21) were the least diverse. Interestingly, three of the P. rubescens strains had different cyanopeptide profiles, despite being collected from the same lake at the same time. This study highlights the diversity of cyanopeptides produced by Planktothrix and further hints at the underestimated cyanopeptide diversity from subpopulations of chemotypic cyanobacteria in freshwater lakes.PMID:38393188 | DOI:10.3390/toxins16020110

Toxins (Basel). 2024 Feb 10;16(2):99. doi: 10.3390/toxins16020099.ABSTRACTFusarium is a genus that mostly consists of plant pathogenic fungi which are able to produce a broad range of toxic secondary metabolites. In this study, we focus on a type A trichothecene-producing isolate (15-39) of Fusarium sporotrichioides from Lower Austria. We assessed the secondary metabolite profile and optimized the toxin production conditions on autoclaved rice and found that in addition to large amounts of T-2 and HT-2 toxins, this strain was able to produce HT-2-glucoside. The optimal conditions for the production of T-2 toxin, HT-2 toxin, and HT-2-glucoside on autoclaved rice were incubation at 12 °C under constant light for four weeks, darkness at 30 °C for two weeks, and constant light for three weeks at 20 °C, respectively. The HT-2-glucoside was purified, and the structure elucidation by NMR revealed a mixture of two alpha-glucosides, presumably HT-2-3-O-alpha-glucoside and HT-2-4-O-alpha-glucoside. The efforts to separate the two compounds by HPLC were unsuccessful. No hydrolysis was observed with two the alpha-glucosidases or with human salivary amylase and Saccharomyces cerevisiae maltase. We propose that the two HT-2-alpha-glucosides are not formed by a glucosyltransferase as they are in plants, but by a trans-glycosylating alpha-glucosidase expressed by the fungus on the starch-containing rice medium.PMID:38393177 | DOI:10.3390/toxins16020099

Mar Drugs. 2024 Jan 27;22(2):66. doi: 10.3390/md22020066.ABSTRACTCo-cultivation, coupled with the OSMAC approach, is considered an efficient method for expanding microbial chemical diversity through the activation of cryptic biosynthetic gene clusters (BGCs). As part of our project aiming to discover new fungal metabolites for crop protection, we previously reported five polyketides, the macrolides dendrodolides E (1) and N (2), the azaphilones spiciferinone (3) and 8α-hydroxy-spiciferinone (4), and the bis-naphtho-γ-pyrone cephalochromin (5) from the solid Potato Dextrose Agar (PDA) co-culture of two marine sediment-derived fungi, Plenodomus influorescens and Pyrenochaeta nobilis. However, some of the purified metabolites could not be tested due to their minute quantities. Here we cultivated these fungi (both axenic and co-cultures) in liquid regime using three different media, Potato Dextrose Broth (PDB), Sabouraud Dextrose Broth (SDB), and Czapek-Dox Broth (CDB), with or without shaking. The aim was to determine the most ideal co-cultivation conditions to enhance the titers of the previously isolated compounds and to produce extracts with stronger anti-phytopathogenic activity as a basis for future upscaled fermentation. Comparative metabolomics by UPLC-MS/MS-based molecular networking and manual dereplication was employed for chemical profiling and compound annotations. Liquid co-cultivation in PDB under shaking led to the strongest activity against the phytopathogen Phytophthora infestans. Except for compound 1, all target compounds were detected in the co-culture in PDB. Compounds 2 and 5 were produced in lower titers, whereas the azaphilones (3 and 4) were overexpressed in PDB compared to PDA. Notably, liquid PDB co-cultures contained meroterpenoids and depside clusters that were absent in the solid PDA co-cultures. This study demonstrates the importance of culture regime in BGC regulation and chemical diversity of fungal strains in co-culture studies.PMID:38393037 | DOI:10.3390/md22020066

Metabolites. 2024 Feb 16;14(2):128. doi: 10.3390/metabo14020128.ABSTRACTHuman breastmilk is an invaluable nutritional and pharmacological resource with a highly diverse metabolite profile, which can directly affect the metabolism of infants. Application of metabolomics can discriminate the complex relationship between such nutrients and infant health. As the most common biological fluid in metabolomic study, infant urinary metabolomics may provide the physiological impacts of different nutritional resources, namely human breastmilk and formulated milk. In this study, we aimed to identify possible differences in the urine metabolome of 30 infants (1-14 days after birth) fed with breast milk (n = 15) or formulated milk (n = 15). From metabolomic analysis with gas chromatography-mass spectrometry, 163 metabolites from single mass spectrometry (GC-MS), and 383 metabolites from tandem mass spectrometry (GC-MS/MS) were confirmed in urinary samples. Various multivariate statistical analysis were performed to discriminate the differences originating from physiological/nutritional variables, including human breastmilk/formulate milk feeding, sex, and duration of feeding. Both unsupervised and supervised discriminant analyses indicated that feeding resources (human breastmilk/formulated milk) gave marginal but significant differences in urinary metabolomes, while other factors (sex, duration of feeding) did not show notable discrimination between groups. According to the biomarker analyses, several organic acid and amino acids showed statistically significant differences between different feeding resources, such as 2-hydroxyhippurate.PMID:38393020 | DOI:10.3390/metabo14020128

Metabolites. 2024 Feb 15;14(2):125. doi: 10.3390/metabo14020125.ABSTRACTLiquid chromatography-high-resolution mass spectrometry (LC-HRMS), as applied to untargeted metabolomics, enables the simultaneous detection of thousands of small molecules, generating complex datasets. Alignment is a crucial step in data processing pipelines, whereby LC-MS features derived from common ions are assembled into a unified matrix amenable to further analysis. Variability in the analytical factors that influence liquid chromatography separations complicates data alignment. This is prominent when aligning data acquired in different laboratories, generated using non-identical instruments, or between batches from large-scale studies. Previously, we developed metabCombiner for aligning disparately acquired LC-MS metabolomics datasets. Here, we report significant upgrades to metabCombiner that enable the stepwise alignment of multiple untargeted LC-MS metabolomics datasets, facilitating inter-laboratory reproducibility studies. To accomplish this, a "primary" feature list is used as a template for matching compounds in "target" feature lists. We demonstrate this workflow by aligning four lipidomics datasets from core laboratories generated using each institution's in-house LC-MS instrumentation and methods. We also introduce batchCombine, an application of the metabCombiner framework for aligning experiments composed of multiple batches. metabCombiner is available as an R package on Github and Bioconductor, along with a new online version implemented as an R Shiny App.PMID:38393017 | DOI:10.3390/metabo14020125

Metabolites. 2024 Feb 11;14(2):120. doi: 10.3390/metabo14020120.ABSTRACTColored rice is richer in nutrients and contains more nutrients and bioactive substances than ordinary white rice. Moderate consumption of black (purple) rice has a variety of physiological effects, such as antioxidant effects, blood lipid regulation, and blood sugar control. Therefore, we utilized nontargeted metabolomics, quantitative assays for flavonoid and phenolic compounds, and physiological and biochemical data to explore the correlations between metabolites and the development of antioxidant characteristics in pigmented rice seeds. The findings indicated that, among Yangjinnuo 818 (YJN818), Hongnuo (HN), Yangchannuo 1 hao (YCN1H), and Yangzi 6 hao (YZ6H), YZ6H exhibited the highest PAL activity, which was 2.13, 3.08, and 3.25 times greater than those of YJN818, HN, and YCN1H, respectively. YZ6H likewise exhibited the highest flavonoid content, which was 3.8, 7.06, and 35.54 times greater than those of YJN818, HN, and YCN1H, respectively. YZ6H also had the highest total antioxidant capacity, which was 2.42, 3.76, and 3.77 times greater than those of YJN818, HN, and YCN1H, respectively. Thus, purple rice grains have stronger antioxidant properties than other colored rice grains. Receiver operating characteristic (ROC) curve analysis revealed that trans-3,3',4',5,5',7-hexahydroxyflavanone, phorizin, and trilobatin in the YZ6H, HN, and YCN1H comparison groups all had area under the curve (AUC) values of 1. Phlorizin, trans-3,3',4',5,5',7-hexahydroxyflavanone, and trilobatin were recognized as indices of antioxidant capability in colored rice in this research. This research adds to the understanding of antioxidant compounds in pigmented rice, which can increase the nutritional value of rice and promote the overall well-being of individuals. This type of information is of immense importance in maintaining a balanced and healthy diet.PMID:38393012 | DOI:10.3390/metabo14020120

Metabolites. 2024 Feb 10;14(2):118. doi: 10.3390/metabo14020118.ABSTRACTScientific workflows facilitate the automation of data analysis tasks by integrating various software and tools executed in a particular order. To enable transparency and reusability in workflows, it is essential to implement the FAIR principles. Here, we describe our experiences implementing the FAIR principles for metabolomics workflows using the Metabolome Annotation Workflow (MAW) as a case study. MAW is specified using the Common Workflow Language (CWL), allowing for the subsequent execution of the workflow on different workflow engines. MAW is registered using a CWL description on WorkflowHub. During the submission process on WorkflowHub, a CWL description is used for packaging MAW using the Workflow RO-Crate profile, which includes metadata in Bioschemas. Researchers can use this narrative discussion as a guideline to commence using FAIR practices for their bioinformatics or cheminformatics workflows while incorporating necessary amendments specific to their research area.PMID:38393009 | DOI:10.3390/metabo14020118

Metabolites. 2024 Feb 10;14(2):116. doi: 10.3390/metabo14020116.ABSTRACTIt is well recognized that patients with severe obesity exhibit remarkable heterogeneity in response to different types of weight-loss interventions. Those who undergo Roux-en-Y gastric bypass (RYGB) usually exhibit more favorable glycemic outcomes than those who receive adjustable gastric banding (BAND) or intensive medical intervention (IMI). The molecular mechanisms behind these observations, however, remain largely unknown. To identify the plasma metabolites associated with differential glycemic outcomes induced by weight-loss intervention, we studied 75 patients with severe obesity (25 each in RYGB, BAND, or IMI). Using untargeted metabolomics, we repeatedly measured 364 metabolites in plasma samples at baseline and 1-year after intervention. Linear regression was used to examine whether baseline metabolites or changes in metabolites are associated with differential glycemic outcomes in response to different types of weight-loss intervention, adjusting for sex, baseline age, and BMI as well as weight loss. Network analyses were performed to identify differential metabolic pathways involved in the observed associations. After correction for multiple testing (q < 0.05), 33 (RYGB vs. IMI) and 28 (RYGB vs. BAND) baseline metabolites were associated with changes in fasting plasma glucose (FPG) or glycated hemoglobin (HbA1c). Longitudinal changes in 38 (RYGB vs. IMI) and 38 metabolites (RYGB vs. BAND) were significantly associated with changes in FPG or HbA1c. The identified metabolites are enriched in pathways involved in the biosynthesis of aminoacyl-tRNA and branched-chain amino acids. Weight-loss intervention evokes extensive changes in plasma metabolites, and the altered metabolome may underlie the differential glycemic outcomes in response to different types of weight-loss intervention, independent of weight loss itself.PMID:38393008 | DOI:10.3390/metabo14020116

Metabolites. 2024 Feb 9;14(2):115. doi: 10.3390/metabo14020115.ABSTRACTA competitive volleyball game is a highly metabolic and physically demanding event for professional players. This study aimed to investigate whether a single game at the end of a preseason promotes changes in the biochemical markers of physical exercise responses and the metabolomic profile of professional volleyball players. This cross-sectional study included 13 male Brazilian professional volleyball players. Food intake, body composition, heart rate, physical movement variables, and blood biochemical indicators were evaluated. For non-target metabolomic analysis, serum samples were subjected to 500 MHz Nuclear Magnetic Resonance. Data analysis showed no significant difference in the biochemical indicators after the game (p > 0.05). The level of metabolites present in the groups of the main components (β-hydroxybutyrate, arginine/lysine, isoleucine, leucine, and valine) had decreased after the game. However, formic acid and histidine levels increased. Among the compounds not part of the main components, hypoxanthine and tyrosine increased, whereas low-density lipoprotein and very low-density lipoprotein levels decreased. After the game, the metabolomic profiles of players showed significant negative variations in essential amino acids (leucine, valine, and isoleucine). These decreases might be influenced by athlete diet and reduced glycogen storage due to lower carbohydrate intake, potentially impacting serum-essential amino acid levels via oxidation in skeletal muscle. The study provides insights for developing metabolic compensation strategies in athletes.PMID:38393007 | DOI:10.3390/metabo14020115

Metabolites. 2024 Feb 7;14(2):112. doi: 10.3390/metabo14020112.ABSTRACTSpecialized metabolites are produced via discrete metabolic pathways. These small molecules play significant roles in plant growth and development, as well as defense against environmental stresses. These include damping off or seedling blight at a post-emergence stage. Targeted metabolomics was followed to gain insights into metabolome changes characteristic of different developmental stages of sorghum seedlings. Metabolites were extracted from leaves at seven time points post-germination and analyzed using ultra-high performance liquid chromatography coupled to mass spectrometry. Multivariate statistical analysis combined with chemometric tools, such as principal component analysis, hierarchical clustering analysis, and orthogonal partial least squares-discriminant analysis, were applied for data exploration and to reduce data dimensionality as well as for the selection of potential discriminant biomarkers. Changes in metabolome patterns of the seedlings were analyzed in the early, middle, and late stages of growth (7, 14, and 29 days post-germination). The metabolite classes were amino acids, organic acids, lipids, cyanogenic glycosides, hormones, hydroxycinnamic acid derivatives, and flavonoids, with the latter representing the largest class of metabolites. In general, the metabolite content showed an increase with the progression of the plant growth stages. Most of the differential metabolites were derived from tryptophan and phenylalanine, which contribute to innate immune defenses as well as growth. Quantitative analysis identified a correlation of apigenin flavone derivatives with growth stage. Data-driven investigations of these metabolomes provided new insights into the developmental dynamics that occur in seedlings to limit post-germination mortality.PMID:38393004 | DOI:10.3390/metabo14020112

Metabolites. 2024 Feb 6;14(2):110. doi: 10.3390/metabo14020110.ABSTRACTDepressive disorder is a multifactorial disease that is based on dysfunctions in mental and biological processes. The search for biomarkers can improve its diagnosis, personalize therapy, and lead to a deep understanding of the biochemical processes underlying depression. The purpose of this work was a metabolomic analysis of blood serum to classify patients with depressive disorders and healthy individuals using Compound Discoverer software. Using high-resolution mass spectrometry, blood plasma samples from 60 people were analyzed, of which 30 were included in a comparison group (healthy donors), and 30 were patients with a depressive episode (F32.11) and recurrent depressive disorder (F33.11). Differences between patient and control groups were identified using the built-in utilities in Compound Discoverer software. Compounds were identified by their accurate mass and fragment patterns using the mzCloud database and tentatively identified by their exact mass using the ChemSpider search engine and the KEGG, ChEBI, FDA UNII-NLM, Human Metabolome and LipidMAPS databases. We identified 18 metabolites that could divide patients with depressive disorders from healthy donors. Of these, only two compounds were tentatively identified using the mzCloud database (betaine and piperine) based on their fragmentation spectra. For three compounds ((4S,5S,8S,10R)-4,5,8-trihydroxy-10-methyl-3,4,5,8,9,10-hexahydro-2H-oxecin-2-one, (2E,4E)-N-(2-hydroxy-2-methylpropyl)-2,4-tetradecadienamide and 17α-methyl-androstan-3-hydroxyimine-17β-ol), matches were found in the mzCloud database but with low score, which could not serve as reliable evidence of their structure. Another 13 compounds were identified by their exact mass in the ChemSpider database, 9 (g-butyrobetaine, 6-diazonio-5-oxo-L-norleucine, 11-aminoundecanoic acid, methyl N-acetyl-2-diazonionorleucinate, glycyl-glycyl-argininal, dilaurylmethylamine, 12-ketodeoxycholic acid, dicetylamine, 1-linoleoyl-2-hydroxy-sn-glycero-3-PC) had only molecular formulas proposed, and 4 were unidentified. Thus, the use of Compound Discoverer software alone was not sufficient to identify all revealed metabolites. Nevertheless, the combination of the found metabolites made it possible to divide patients with depressive disorders from healthy donors.PMID:38393002 | DOI:10.3390/metabo14020110

Metabolites. 2024 Feb 6;14(2):109. doi: 10.3390/metabo14020109.ABSTRACTUterine cancer is the most prevalent gynecologic malignancy in women worldwide. Endometrial cancer (EC) has an 81% five-year survival rate, depending on disease stage and time of diagnosis. While endometrial cancer is largely treatable when detected early, no established screening techniques are available in clinical practice. As a result, one of the most significant issues in the medical field is the development of novel ways for early cancer identification, which could boost treatment success rates. Liquid chromatography-high-resolution mass spectrometry (LC-HRMS)-based metabolomics was employed to explore the metabolomic markers and pathways unique to this cancer type and link them to the benign endometrial hyperplasia that may progress to cancer in 5% to 25% of patients. The study involved 59 postmenopausal participants, 20 with EC type 1, 20 with benign hyperplasia, and 19 healthy participants. Metabolite distribution changes were analyzed, and 338 of these features were dysregulated and significant. The first two main components, PC1 and PC2, were responsible for 11.5% and 12.2% of the total metabolites, respectively. Compared with the control group (CO), EC samples had 203 differentially expressed metabolites (180 upregulated and 23 downregulated); in hyperplasia (HP), 157 metabolites were dysregulated (127 upregulated and 30 downregulated) compared to the CO group while 21 metabolites exhibited differential regulation (16 upregulated and 5 downregulated) in EC plasma samples compared to the HP group. Hyperplasia samples exhibited similar metabolic changes to those reported in cancer, except for alterations in triglyceride levels, 7a,12 b-dihydroxy-5b-Cholan-24-oic acid, and Hept-2-enedioyl carnitine levels. The metabolites N-heptanoyl glycine and -(Methylthio)-2,3-isopentyl phosphate and formimino glutamic acid can be specific markers for hyperplasia conditions and dimethyl phosphatidyl ethanolamine and 8-isoprostaglandin E2 can be specific markers for EC conditions. Metabolic activities rely on mitochondrial oxidative phosphorylation for energy generation. The changes in metabolites identified in our study indicate that endometrial cancer cells adopt alternative strategies to increase energy production to meet the energy demand, thereby supporting proliferation.PMID:38393001 | DOI:10.3390/metabo14020109

Metabolites. 2024 Feb 2;14(2):105. doi: 10.3390/metabo14020105.ABSTRACTMetabolomic biomarkers hold promise in aiding the diagnosis and prognostication of traumatic brain injury. In Canada, over 165,000 individuals annually suffer from a traumatic brain injury (TBI), making it one of the most prevalent neurological conditions. In this pilot investigation, we examined blood-derived biomarkers as proxy measures that can provide an objective approach to TBI diagnosis and monitoring. Using a 1H nuclear magnetic resonance (NMR)-based quantitative metabolic profiling approach, this study determined whether (1) blood-derived metabolites change during recovery in male participants with mild to severe TBI; (2) biological pathway analysis reflects mechanisms that mediate neural damage/repair throughout TBI recovery; and (3) changes in metabolites correlate to initial injury severity. Eight male participants with mild to severe TBI (with intracranial lesions) provided morning blood samples within 1-4 days and again 6 months post-TBI. Following NMR analysis, the samples were subjected to multivariate statistical and machine learning-based analyses. Statistical modelling displayed metabolic changes during recovery through group separation, and eight significant metabolic pathways were affected by TBI. Metabolic changes were correlated to injury severity. L-alanine (R= -0.63, p < 0.01) displayed a negative relationship with the Glasgow Coma Scale. This study provides pilot data to support the feasibility of using blood-derived metabolites to better understand changes in biochemistry following TBI.PMID:38392997 | DOI:10.3390/metabo14020105

Metabolites. 2024 Feb 1;14(2):102. doi: 10.3390/metabo14020102.ABSTRACTFertilizers are widely used to improve the quality of fruits and vegetables. However, the overuse of fertilizers has become an issue because it causes environmental problems and negatively affects productivity and fruit quality. In this study, we examined the effects of nitrogen, phosphorus, and potassium (NPK) fertilizer levels on the metabolism of cucumber fruit in low- and high-nutrient soils using mass-spectrometry-based metabolomics approaches. Cucumber metabolite content was notably different depending on the initial soil nutrient status. Most amino acids and phenylpropanoids were abundant in the cucumbers raised in low-nutrient soil, whereas organic acids, some amino acids (aspartate, glutamate, and ornithine), and carbohydrates were comparatively higher in fruits from high-nutrient soil. The fertilizer supply resulted in an alteration in the metabolite profile, while no change in fruit yield was observed in either low- or high-nutrient soils. Fertilizer treatment perturbed the metabolite contents in cucumbers from low-nutrient soil. In contrast, treatment with higher concentrations of fertilizer in high-nutrient soil increased phenylpropanoid content in the cucumbers, while most metabolites decreased. In conclusion, fertilization levels should be carefully determined, considering culture conditions such as the original soil status, to increase product yield and fruit quality and avoid environmental problems.PMID:38392994 | DOI:10.3390/metabo14020102

Metabolites. 2024 Jan 31;14(2):98. doi: 10.3390/metabo14020098.ABSTRACTMetabolomics is emerging as a powerful systems biology approach for improving preclinical drug safety assessment. This review discusses current applications and future trends of metabolomics in toxicology and drug development. Metabolomics can elucidate adverse outcome pathways by detecting endogenous biochemical alterations underlying toxicity mechanisms. Furthermore, metabolomics enables better characterization of human environmental exposures and their influence on disease pathogenesis. Metabolomics approaches are being increasingly incorporated into toxicology studies and safety pharmacology evaluations to gain mechanistic insights and identify early biomarkers of toxicity. However, realizing the full potential of metabolomics in regulatory decision making requires a robust demonstration of reliability through quality assurance practices, reference materials, and interlaboratory studies. Overall, metabolomics shows great promise in strengthening the mechanistic understanding of toxicity, enhancing routine safety screening, and transforming exposure and risk assessment paradigms. Integration of metabolomics with computational, in vitro, and personalized medicine innovations will shape future applications in predictive toxicology.PMID:38392990 | DOI:10.3390/metabo14020098

Metabolites. 2024 Jan 30;14(2):97. doi: 10.3390/metabo14020097.ABSTRACTAstragali Radix, derived from the roots of Astragalus mongholicus, is a traditional Chinese medicine containing flavonoids and saponins as its key ingredients. With a shortage in the wild sources of the herbal plant, it is especially important to explore a cultivation mode for A. mongholicus for medicinal purposes. Cutting, a physical environmental stress method, was used in this study with the objective of improving the quality of this herbal legume. We found that cutting of the top 1/3 of the aboveground part of A. mongholicus during the fruiting period resulted in a significant increase in the content of flavonoids and saponins, as well as in root growth, including length, diameter, and dry weight. Furthermore, the leaves were sampled and analyzed using a combined transcriptome and metabolome analysis approach at five different time points after the treatment. Sixteen differentially expressed unigenes (DEGs) involved in the biosynthesis of flavonoids were identified; these were found to stimulate the synthesis of flavonoids such as formononetin and calycosin-7-O-β-D-glucoside. Moreover, we identified 10 DEGs that were associated with the biosynthesis of saponins, including astragaloside IV and soyasaponin I, and found that they only regulated the mevalonic acid (MVA) pathway. These findings provide new insights into cultivating high-quality A. mongholicus, which could potentially alleviate the scarcity of this valuable medicinal plant.PMID:38392989 | DOI:10.3390/metabo14020097

Metabolites. 2024 Jan 29;14(2):95. doi: 10.3390/metabo14020095.ABSTRACTEfficient cold-chain delivery is essential for maintaining a sustainable global food supply. This study used metabolomic analysis to examine meat quality changes during the "wet aging" of crossbred Wagyu beef during cold storage. The longissimus thoracic (Loin) and adductor muscles (Round) of hybrid Wagyu beef, a cross between the Japanese Black and Holstein-Friesian breeds, were packaged in vacuum film and refrigerated for up to 40 days. Sensory evaluation indicated an increase in the umami and kokumi taste owing to wet aging. Comprehensive analysis using gas chromatography-mass spectrometry identified metabolite changes during wet aging. In the Loin, 94 metabolites increased, and 24 decreased; in the Round, 91 increased and 18 decreased. Metabolites contributing to the umami taste of the meat showed different profiles during wet aging. Glutamic acid increased in a cold storage-dependent manner, whereas creatinine and inosinic acid degraded rapidly even during cold storage. In terms of lipids, wet aging led to an increase in free fatty acids. In particular, linoleic acid, a polyunsaturated fatty acid, increased significantly among the free fatty acids. These results provide new insight into the effects of wet aging on Wagyu-type beef, emphasizing the role of free amino acids, organic acids, and free fatty acids generated during cold storage.PMID:38392987 | DOI:10.3390/metabo14020095