Distinct Metabolites Research Articles

Unraveling the Mechanism of Xiaochaihu Granules in Alleviating Yeast-Induced Fever Based on Network Analysis and Experimental Validation.

Xiaochaihu granules (XCHG) are extensively used to treat fever. Nevertheless, the underlying mechanism remains elusive. This study aimed to explore the potential of XCHG in mitigating yeast-induced fever and the underlying metabolic pathways. The chemical composition of XCHG was ascertained using ultra-fast liquid chromatography/quadrupole-time-of-flight tandem mass spectrometry (UFLC-Q-TOF-MS/MS), followed by integrated network analysis to predict potential targets. We then conducted experimental validation using pharmacological assays and metabolomics analysis in a yeast-induced mouse fever model. The study identified 133 compounds in XCHG, resulting in the development of a comprehensive network of herb-compound-biological functional modules. Subsequently, molecular dynamic (MD) simulations confirmed the stability of the complexes, including γ-aminobutyric acid B receptor 2 (GABBR2)-saikosaponin C, prostaglandin endoperoxide synthases (PTGS2)-lobetyolin, and NF-κB inhibitor IκBα (NFKBIA)-glycyrrhizic acid. Animal experiments demonstrated that XCHG reduced yeast-induced elevation in NFKBIA's downstream regulators [interleukin (IL)-1β and IL-8], inhibited PTGS2 activity, and consequently decreased prostaglandin E2 (PGE2) levels. XCHG also downregulated the levels of 5-hydroxytryptamine (5-HT), γ-aminobutyric acid (GABA), corticotropin releasing hormone (CRH), and adrenocorticotrophin (ACTH). These corroborated the network analysis results indicating XCHG's effectiveness against fever in targeting NFKBIA, PTGS2, and GABBR2. The hypothalamus metabolomics analysis identified 14 distinct metabolites as potential antipyretic biomarkers of XCHG. In conclusion, our findings suggest that XCHG alleviates yeast-induced fever by regulating inflammation/immune responses, neuromodulation, and metabolism modules, providing a scientific basis for the anti-inflammatory and antipyretic properties of XCHG.

Gastrointestinal microbiota and metabolites possibly contribute to distinct pathogenicity of SARS-CoV-2 proto or its variants in rhesus monkeys

ABSTRACT Gastrointestinal (GI) infection is evidenced with involvement in COVID-19 pathogenesis caused by SARS-CoV-2. However, the correlation between GI microbiota and the distinct pathogenicity of SARS-CoV-2 Proto and its emerging variants remains unclear. In this study, we aimed to determine if GI microbiota impacted COVID-19 pathogenesis and if the effect varied between SARS-CoV-2 Proto and its variants. We performed an integrative analysis of histopathology, microbiomics, and transcriptomics on the GI tract fragments from rhesus monkeys infected with SARS-CoV-2 proto or its variants. Based on the degree of pathological damage and microbiota profile in the GI tract, five of SARS-CoV-2 strains were classified into two distinct clusters, namely, the clusters of Alpha, Beta and Delta (ABD), and Proto and Omicron (PO). Notably, the abundance of potentially pathogenic microorganisms increased in ABD but not in the PO-infected rhesus monkeys. Specifically, the high abundance of UCG-002, UCG-005, and Treponema in ABD virus-infected animals positively correlated with interleukin, integrins, and antiviral genes. Overall, this study revealed that infection-induced alteration of GI microbiota and metabolites could increase the systemic burdens of inflammation or pathological injury in infected animals, especially in those infected with ABD viruses. Distinct GI microbiota and metabolite profiles may be responsible for the differential pathological phenotypes of PO and ABD virus-infected animals. These findings improve our understanding the roles of the GI microbiota in SARS-CoV-2 infection and provide important information for the precise prevention, control, and treatment of COVID-19.

Changes and Significance of Central Carbon Metabolism before and after Metformin Treatment of Type 2 Diabetes Based on Mass Spectrometry.

An imbalance in energy metabolism serves as a causal factor for type 2 diabetes (T2D). Although metformin has been known to ameliorate the overall energy metabolism imbalance, but the direct correlation between metformin and central carbon metabolism (CCM) has not been thoroughly investigated. In this study, we employed a high-performance ion chromatography-tandem mass spectrometry (HPIC-MS/MS) technique to examine the alterations and significance of CCM both before and after metformin treatment for T2D. We recruited 29 participants, comprising 10 individuals recently diagnosed with T2D (T2D group). Among these, 10 patients underwent a 4-6-week treatment with metformin (MET group). Additionally, we included 9 healthy subjects (CON group). Employing HPIC-MS/MS, we quantitatively analyzed 56 metabolites across 18 biologically relevant metabolic pathways associated with CCM. Univariate and multivariate statistical analyses were utilized to identify differential metabolites. Subsequently, correlation analyses and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were conducted on the identified differential metabolites. We identified seven distinct metabolites in individuals with T2D (p < 0.05). Notably, cyclic 3',5'-Adenosine MonoPhosphate (AMP), Glucose 6-phosphate, L-lactic acid, Maleic acid, and Malic acid exhibited a reversal to normal levels following metformin treatment. Furthermore, Malic acid demonstrated a positive correlation with L-lactic acid (r = 0.94, p < 0.05), as did succinic acid with malic acid (r = 0.81, p < 0.05), L-lactic acid with succinic acid (r = 0.78, p < 0.05), and L-lactic acid with glucose-6-phosphate (r = 0.72, p < 0.05). These metabolites were notably enriched in pyruvate metabolism (p = 0.005), tricarboxylic acid cycle (TCA) (p = 0.007), propanoate metabolism (p = 0.007), and glycolysis or gluconeogenesis (p = 0.009), respectively. We employed HPIC-MS/MS to uncover alterations in CCM among individuals recently diagnosed with T2D before and after metformin treatment. The findings suggest that metformin may ameliorate the energy metabolism imbalance in T2D by reducing intermediates within the CCM pathway.

Mechanistic insight into biotransformation of novel triazine-based flame retardant 1,3,5-tris(2,3-dibromopropyl)-1,3,5-triazinane-2,4,6-trione by human cytochrome P450s

The escalating focus on the environmental occurrence and toxicology of emerging pollutants underscores the imperative need for a profound exploration of their metabolic transformations mediated by human CYP450 enzymes. Such investigations have the potential to unravel the intricate metabolite profiles, substantially altering the toxicological outcomes. In this study, we integrated the computational simulations with in vitro metabolism experiments to investigate the metabolic activity and mechanism of an emerging pollutant, 1,3,5-tris(2,3-dibromopropyl)-1,3,5-triazinane-2,4,6-trione (TDBP-TAZTO), catalyzed by human CYP450s. The results highlight the important contributions of CYP2E1, 3A4 and 2C9 to the biotransformation of TDBP-TAZTO, leading to the identification of four distinct metabolites. The effective binding conformations governing biotransformation reactions of TDBP-TAZTO within active CYP450s are unveiled. Structural instability of primary hydroxyTDBP-TAZTO products suggests three potential outcomes: (1) generation of an alcohol metabolite through successive debromination and reduction reactions, (2) formation of a dihydroxylated metabolite through secondary hydroxylation by CYP450, and (3) production of an N-dealkylated metabolite via decomposition and isomerization reactions in the aqueous environment. The formation of a desaturated debrominated metabolite may arise from H-abstraction and barrier-free Br release during the primary oxidation, potentially competing with the generation of hydroxyTDBP-TAZTO. These findings provide detailed mechanistic insight into TDBP-TAZTO biotransformation by CYP450s, which can enrich our understanding of the metabolic fate and associated health risk of this chemical.

Metabolic changes and isoflavone biotransformation in natto for improved nutritional distribution and bioavailability

We used LC-MS to identify the metabolic changes in soybean fermented by Bacillus subtilis DC-15 to comprehend the biochemical alterations. Total 650 distinct metabolites were observed, with amino acids, dipeptides, fatty acids, small molecule sugars, and isoflavones having the largest abundances. Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis revealed that the primary metabolic pathways involved during the fermentation of soybeans were related to amino acid metabolism, including beta-alanine metabolism, phenylalanine metabolism, glycine, serine, and threonine metabolism. In the gastric phase, the maximum amount of soy isoflavones was successfully converted from its glycoside form (50.04 μg/mL) to the aglycone form (104.07 μg/mL). The distribution of protein and lipid particles in natto during various stages of digestion showed changes from aggregated particles to more scattered particles. For the future development and enhancement of fermented soybean products, our metabolomic data can shed light on activated biochemical pathways and changes in metabolic pattern.

Isolation of Secondary Metabolites From Marine Actinobacterium of Microbispora sp.T3S11 and Their Antibacterial Activities.

Introduction Marine actinobacteria are promising sources of novel bioactive compounds due to their distinct ecological niches and diverse secondary metabolite production capabilities. Among these,Microbisporasp. T3S11 is notable for its unique spore chain structure, which allows for both morphological and genetic identification. Despite its potential, little is understood about the secondary metabolites produced by this strain. In this study, we hope to fill this gap by extracting and analyzing the antibacterial activities of secondary metabolites fromMicrobisporasp. T3S11, which will be the first time its bioactive compound profile is investigated. Aim To evaluate the antibacterial activity of secondary metabolites isolated from the marine actinobacteriumMicrobisporasp. T3S11. Materials and methods The antibacterial assays were carried out on agar plates containing the appropriate media for each pathogen. Sterile filter paper disks were impregnated with secondary metabolites extracted fromMicrobisporasp. T3S11 and placed on the surface of agar plates inoculated with the appropriate pathogens. Similarly, disks containing tetracycline were used as a positive control. The plates were then incubated at the appropriate temperature for each pathogen, and the zones of inhibition around the disks were measured to determine the extracted metabolites' antibacterial activity. Result Secondary metabolites had antimicrobial activity againstStreptococcus mutans,Klebsiella pneumonia, and methicillin-resistantStaphylococcus aureus(MRSA). The inhibition ofS. mutanswas 7.5 mm and 8.5 mm at 75 μg/mL and 100 μg/mL, respectively.Klebsiella pneumoniazones measured 7 mm and 7.5 mm, while MRSA zones measured 7.6 mm and 8.5 mm at the same concentrations. Tetracycline, the standard antibiotic, had larger inhibition zones: 22 mm forS. mutansandKlebsiella pneumoniaand 16 mm for MRSA, indicating variable susceptibility. Conclusion We conclude that the secondary metabolites extracted fromMicrobisporasp. T3S11exhibits high antibacterial activity. This could be attributed to the presence of various active compounds.

Abstract 5541: The unique metabolite landscape of the aged microenvironment dictates melanoma migratory and invasive capacity

Abstract Metastatic burden and organ failure are the root causes of mortality in patients with advanced melanoma; however, little is known of the metabolic drivers that enable organ colonization and the formation of overt metastases. Recent studies have drawn attention to the importance of metabolism in the survival and colonization of cancer cells. In melanoma, there have been studies focusing on the invasive capabilities of cells; however, not much is known regarding metabolic plasticity in melanoma migratory, invasive and ultimately metastatic capabilities.We have previously shown changes in the lipid landscape of the aged microenvironment promotes melanoma resistance to targeted therapy. Here, we find a distinct metabolite landscape in the aged microenvironment elevates melanoma metastatic capacity. We utilized a panel of well characterized melanoma models and tested their invasiveness and motility under different metabolite levels modeled after the aged microenvironment. Transcriptomic and proteomic analysis identifies distinct signatures that explain the migratory and invasive differences in cells cultured in varying metabolic environments. We hypothesize that different nutrient availabilities melanoma cells are exposed to during the metastatic phase affect the migratory and invasive capacity of the cell. We tested this by performing 3D migration assays, organoids and transwell assays of cells grown in media with varying nutrient levels. Further analysis is currently underway to better understand the mechanisms in which these metabolic differences facilitate cell migration, invasion and eventually colonization. This work has important implications for our understanding of the metabolic determinants of melanoma migration and metastatic colonization, and we hypothesize restraining tumor metabolic plasticity is vital to prevent and treat metastases in melanoma. Citation Format: Gretchen Marie Alicea, Payal Patel, Meihan Wei, Vito Rebecca, Denis Wirtz. The unique metabolite landscape of the aged microenvironment dictates melanoma migratory and invasive capacity [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 5541.

Metabolomics distinguishes different grades of Scrophularia ningpoensis hemsl: Towards a biomarker discovery and quality evaluation

In managing unique complexities associated with Chinese medicinal quality assessment, metabolomics serves as an innovative tool. This study proposes an analytical approach to assess differing qualities of Scrophularia ningpoensis （S. ningpoensis）Hemsl by identifying potential biomarker metabolites and their activity with the corresponding secondary metabolites. The methodology includes four steps; first, a GC-MS based metabolomics exploration of the Scrophularia ningpoensis Hemsl. Second, a multivariate statistical analysis (PCA, PLS-DA, OPLS-DA) for quality assessment and biomarker identification. Third, the application of ROC analysis and pathway analysis based on identified biomarkers. Finally, validation of the associated active ingredients by HPLC. The analysis showed distinct metabolite profiles across varying grades of S. ningpoensis Hemsl, establishing a grading dependency relationship. Select biomarkers (gluconic Acid, d-xylulose, sucrose, etc.) demonstrated robust grading performances. Further, the Pentose Phosphate Pathway, deemed as most influential in grading, was tied to the synthesis of key constituents (iridoids, phenylpropanoids). HPLC validation tests affirm a decreasing trend in harpagoside and cinnamic acid levels between first and third-grade samples. In conclusion, this GC-MS based metabolomics combined HPLC method offers a sound approach to assess and distinguish quality variations in S. ningpoensis Hemsl samples.

Altered neopterin and IDO in kynurenine metabolism based on LC-MS/MS metabolomics study: Novel therapeutic checkpoints for type 2 diabetes mellitus

BackgroundThis study assessed the alternations of kynurenine pathway (KP) and neopterin in type 2 diabetes mellitus (T2DM) and explored possible differential metabolites. MethodsA fresh residual sera panel was collected from 80 healthy control (HC) individuals and 72 T2DM patients. Metabolites/ratios of interest including tryptophan (TRP), kynurenine (KYN), 5-hydroxytryptamine (5HT), kynurenic acid (KA), xanthurenic acid (XA), neopterin (NEO), KA/KYN ratio and KYN/TRP ratio were determined using a targeted liquid chromatography-tandem mass spectrometry (LC-MS/MS) metabolomics approach, and the difference between groups was assessed. Supervised orthogonal partial least squares-discriminant analysis and differential metabolite screening with fold change (FC) were performed to identify distinct biomarkers. The diagnostic performance of KP metabolites in T2DM was evaluated. ResultsSignificant decreases of TRP, 5HT, KA, XA, and KA/KYN and increases of KYN/TRP and NEO in T2DM compared to HC group were observed (P < 0.05). The KP metabolites panel significantly changed between T2DM and HC groups (Q2: 0.925, P < 0.005). 5HT (FC: 0.63, P < 0.01) and NEO (FC: 3.27, P < 0.01) were proven to be distinct differential metabolites. A combined testing of fasting plasma glucose and KYN/TRP showed good value in the prediction of T2DM (AUC: 0.904, 95% CI 0.843–0.947). ConclusionsThe targeted LC-MS/MS metabolomics study is a powerful tool for evaluating the status of T2DM. This study facilitated the application of KP metabolomics into future clinical practice. 5HT and NEO are promising biomarkers in T2DM. KYN/TRP was highly associated with the development of T2DM and may serve as a potential treatment target.

Abstract P179: Association Between Serum Metabolites and Carotid Atherosclerosis Among Japanese Men

Background: Complex metabolic pathways may exist for atherosclerosis. We examined metabolomic signatures that reflect mechanistic pathways associated with carotid atherosclerosis in apparently healthy men. Methods: A cross-sectional study was conducted in 675 Japanese men (46-83 years) from the SESSA Study (2010-2014). A total of 468 serum metabolites were quantified by liquid chromatography mass spectrometry. The mean intima-media thickness (IMT) and total number of plaques from carotid arteries were measured using B-mode ultrasound. All metabolites were standardized prior to the analysis. We used partial least square regression and variable importance projection (VIP) method to extract the principal metabolites most associated with the mean IMT and total number of plaques. We used a multivariable linear model for the log-mean IMT and a multivariable Poisson model for the total number of plaques to assess the association between individual extracted serum metabolites and carotid measures. Each metabolite multivariable model adjusted for age, body mass index, smoking and drinking status, medications for hypertension, diabetes and dyslipidemia, and systolic blood pressure, high- and low-density lipoprotein cholesterols and hemoglobin A1c. We used false discovery rate adjusted p-values to control for multiple testing. Results: The average mean IMT and total number of plaques were 0.80 mm (SD: 0.16) and 2.06 (range: 0-14), respectively. There were 191 metabolites with a VIP value of one or higher for mean IMT. None of these metabolites was significantly associated with the log-mean IMT. On the other hand, there were 209 metabolites with a VIP value of one or higher for the total number of plaques. Among them, SulfoHexCer(d18:2/24:0(OH)) and SulfoHexCer(d18:2/16:0(OH)) had an inverse association with the total number of plaques (Figure 1). Conclusion: We identified distinct metabolites associated with the total number of plaques. The results suggest an important role of sphingolipids in carotid plaque formation.

Abstract MP26: Dietary Patterns, Metabolome Profile and Risk of Type 2 Diabetes

Background: Plasma metabolites have been associated with type 2 diabetes (T2D) risk and may reflect metabolic homeostasis as a result of the interplay among diet, genetics, and the gut microbiome. Hypothesis: We hypothesized that specific multi-metabolite signatures can characterize the adherence and metabolic response to various dietary patterns and are associated with incident T2D. Methods: We analyzed 20578 participants in the Nurses’ Health studies and Health Professional Follow-up Study (NHS/HPFS), Hispanic Community Health Study/Study of Latinos, and Women’s Health Initiative, whose blood metabolome were profiled by liquid chromatography-mass spectrometry. We applied elastic net regression to develop (n=1206 in a NHS/HPFS lifestyle sub-study) and validate (in the remaining samples) metabolic signatures for 3 dietary recommendation-based diets (a Mediterranean diet - AMED, a healthy eating index - AHEI, and an anti-hypertensive diet - DASH), 3 plant-based diets (PDIs), and 2 mechanism-based diets (proinflammatory [EDIP] and insulinemic [EDIH] diets). We tested associations between the dietary metabolic signatures and incident T2D in 14060 initially T2D-free participants (1832 cases in up to 22 years of follow-up). In sub-samples, we further examined genetic and microbial factors (shotgun sequencing) associated with metabolic signatures. Results: We identified 8 metabolic signatures, each consisted of 37-66 metabolites and was robustly correlated with the corresponding dietary pattern index in all validation cohorts ( r =0.11-0.38; P &lt; 8.06 х10 -9 ). We noted shared and distinct metabolites cross metabolic signatures of various dietary patterns. In multivariable-analyses, metabolic signatures of healthful diets (i.e., AMED, AHEI, DASH, healthful PDI) were associated with a lower T2D risk (hazard ratio [HR]: 0.82-0.90; P &lt; 3х10 -6 ), whereas metabolic signatures of unhealthful diets (e.g., EDIP and EDIH) were associated with a higher T2D risk (HR: 1.23-1.26; P &lt; 2х10 -15 ). The metabolic signatures mediated 26%-56% of the associations between their corresponding dietary patterns and T2D risk ( P &lt; 0.01). Further, a proportion of variation in the dietary metabolic signatures was explained by genetic variants (9.9% for EDIP to 34.5% for PDI) and gut microbial diversity (0.2% for PDI to 14.9% for EDIP). Dietary metabolic signatures were associated with 7 genetic loci including those involved in fatty acid and energy metabolism (e.g., FADS1/2 and CERS4 , P &lt; 5х10 -8 ), and the abundance of 39 gut bacterial species (FDR &lt;0.05). Conclusions: We identified metabolic signatures that characterized the adherence and metabolic responses (related to genetics and gut microbiome) to various dietary patterns, and were associated with T2D risk, in ethnically diverse populations. Metabolomic profiling may facilitate personalized nutritional interventions for T2D prevention.

Hepatic insulin resistance and muscle insulin resistance are characterized by distinct postprandial plasma metabolite profiles: a cross-sectional study

BackgroundTissue-specific insulin resistance (IR) predominantly in muscle (muscle IR) or liver (liver IR) has previously been linked to distinct fasting metabolite profiles, but postprandial metabolite profiles have not been investigated in tissue-specific IR yet. Given the importance of postprandial metabolic impairments in the pathophysiology of cardiometabolic diseases, we compared postprandial plasma metabolite profiles in response to a high-fat mixed meal between individuals with predominant muscle IR or liver IR.MethodsThis cross-sectional study included data from 214 women and men with BMI 25–40 kg/m2, aged 40–75 years, and with predominant muscle IR or liver IR. Tissue-specific IR was assessed using the muscle insulin sensitivity index (MISI) and hepatic insulin resistance index (HIRI), which were calculated from the glucose and insulin responses during a 7-point oral glucose tolerance test. Plasma samples were collected before (T = 0) and after (T = 30, 60, 120, 240 min) consumption of a high-fat mixed meal and 247 metabolite measures, including lipoproteins, cholesterol, triacylglycerol (TAG), ketone bodies, and amino acids, were quantified using nuclear magnetic resonance spectroscopy. Differences in postprandial plasma metabolite iAUCs between muscle and liver IR were tested using ANCOVA with adjustment for age, sex, center, BMI, and waist-to-hip ratio. P-values were adjusted for a false discovery rate (FDR) of 0.05 using the Benjamini–Hochberg method.ResultsSixty-eight postprandial metabolite iAUCs were significantly different between liver and muscle IR. Liver IR was characterized by greater plasma iAUCs of large VLDL (p = 0.004), very large VLDL (p = 0.002), and medium-sized LDL particles (p = 0.026), and by greater iAUCs of TAG in small VLDL (p = 0.025), large VLDL (p = 0.003), very large VLDL (p = 0.002), all LDL subclasses (all p < 0.05), and small HDL particles (p = 0.011), compared to muscle IR. In liver IR, the postprandial plasma fatty acid (FA) profile consisted of a higher percentage of saturated FA (p = 0.013), and a lower percentage of polyunsaturated FA (p = 0.008), compared to muscle IR.ConclusionPeople with muscle IR or liver IR have distinct postprandial plasma metabolite profiles, with more unfavorable postprandial metabolite responses in those with liver IR compared to muscle IR.

Comparative UHPLC-MS/MS-based untargeted metabolomics analysis, antioxidant, and anti-diabetic activities of six walnut cultivars

Walnuts are important stone fruits that are commonly consumed as food or used in food products. However, most studies have focused on specific compounds found in walnuts. Therefore, this study aimed to compare untargeted UHPLC-MS/MS metabolite profiles and determine the antioxidant and antidiabetic properties of six walnut cultivars. A total of 135 metabolites belonging to fourteen different classes were identified including amino acids, lipids, carboxylic acids and amides, phenyl alcohols and aldehydes, ketones, flavonoids, oxygenated hydrocarbons, glycosides, phenolic acids, hydrocarbons, sugar alcohols and acids, and vitamins. The main classes of metabolites were amino acids, lipids, oxygenated hydrocarbons, carboxylic acids and amides, phospholipids, and phenolic acids. The six cultivars were divided into two groups based on PCA, and PLS-DA score with significant differences in the number of distinct metabolites between the two groups. Hierarchical cluster analysis further confirmed these groups by comparing the similarities and differences of all metabolites in the six cultivars. Pathway enrichment analysis revealed that the most prominent metabolic pathways in walnuts were related to amino acids, followed by flavonoids and vitamins. The antioxidant and antidiabetic effects of walnuts varied significantly among the cultivars. Group A, which had higher levels of upregulated metabolites, showed greater IC50 values for ABTS, and DPPH scavenging, as well as α-glucosidase activities. On the other hand, walnuts 4, 5, and 6 in group B had more downregulated metabolites and higher IC50 values for α-amylase inhibition. These findings suggest that walnuts contain key metabolites with antioxidant and antidiabetic properties, which occur at cultivar-dependent levels.

Screening Metabolic Biomarkers in KRAS Mutated Mouse Acinar and Human Pancreatic Cancer Cells via Single-Cell Mass Spectrometry.

Pancreatic cancer is a highly aggressive and rapidly progressing disease, often diagnosed in advanced stages due to the absence of early noticeable symptoms. The KRAS mutation is a hallmark of pancreatic cancer, yet the underlying mechanisms driving pancreatic carcinogenesis remain elusive. Cancer cells display significant metabolic heterogeneity, which is relevant to the pathogenesis of cancer. Population measurements may obscure information about the metabolic heterogeneity among cancer cells. Therefore, it is crucial to analyze metabolites at the single-cell level to gain a more comprehensive understanding of metabolic heterogeneity. In this study, we employed a 3D-printed ionization source for metabolite analysis in both mice and human pancreatic cancer cells at the single-cell level. Using advanced machine learning algorithms and mass spectral feature selection, we successfully identified 23 distinct metabolites that are statistically significantly different in KRAS mutant human pancreatic cancer cells and mouse acinar cells bearing the oncogenic KRAS mutation. These metabolites encompass a variety of chemical classes, including organic nitrogen compounds, organic acids and derivatives, organoheterocyclic compounds, benzenoids, and lipids. These findings shed light on the metabolic remodeling associated with KRAS-driven pancreatic cancer initiation and indicate that the identified metabolites hold promise as potential diagnostic markers for early detection in pancreatic cancer patients.

Accumulation mechanism of metabolite markers identified by machine learning between Qingyuan and Xiushui counties in Polygonatum cyrtonema Hua

Polygonatum cyrtonema Hua is a traditional Chinese medicinal plant acclaimed for its therapeutic potential in diabetes and various chronic diseases. Its rhizomes are the main functional parts rich in secondary metabolites, such as flavonoids and saponins. But their quality varies by region, posing challenges for industrial and medicinal application of P. cyrtonema. In this study, 482 metabolites were identified in P. cyrtonema rhizome from Qingyuan and Xiushui counties. Cluster analysis showed that samples between these two regions had distinct secondary metabolite profiles. Machine learning methods, specifically support vector machine-recursive feature elimination and random forest, were utilized to further identify metabolite markers including flavonoids, phenolic acids, and lignans. Comparative transcriptomics and weighted gene co-expression analysis were performed to uncover potential candidate genes including CHI, UGT1, and PcOMT10/11/12/13 associated with these compounds. Functional assays using tobacco transient expression system revealed that PcOMT10/11/12/13 indeed impacted metabolic fluxes of the phenylpropanoid pathway and phenylpropanoid-related metabolites such as chrysoeriol-6,8-di-C-glucoside, syringaresinol-4'-O-glucopyranosid, and 1-O-Sinapoyl-D-glucose. These findings identified metabolite markers between these two regions and provided valuable genetic insights for engineering the biosynthesis of these compounds.

Plasma metabolites and risk of seven cancers: a two-sample Mendelian randomization study among European descendants

BackgroundWhile circulating metabolites have been increasingly linked to cancer risk, the causality underlying these associations remains largely uninterrogated.MethodsWe conducted a comprehensive 2-sample Mendelian randomization (MR) study to evaluate the potential causal relationship between 913 plasma metabolites and the risk of seven cancers among European-ancestry individuals. Data on variant-metabolite associations were obtained from a genome-wide association study (GWAS) of plasma metabolites among 14,296 subjects. Data on variant-cancer associations were gathered from large-scale GWAS consortia for breast (N = 266,081), colorectal (N = 185,616), lung (N = 85,716), ovarian (N = 63,347), prostate (N = 140,306), renal cell (N = 31,190), and testicular germ cell (N = 28,135) cancers. MR analyses were performed with the inverse variance-weighted (IVW) method as the primary strategy to identify significant associations at Bonferroni-corrected P < 0.05 for each cancer type separately. Significant associations were subjected to additional scrutiny via weighted median MR, Egger regression, MR-Pleiotropy RESidual Sum and Outlier (MR-PRESSO), and reverse MR analyses. Replication analyses were performed using an independent dataset from a plasma metabolite GWAS including 8,129 participants of European ancestry.ResultsWe identified 94 significant associations, suggesting putative causal associations between 66 distinct plasma metabolites and the risk of seven cancers. Remarkably, 68.2% (45) of these metabolites were each associated with the risk of a specific cancer. Among the 66 metabolites, O-methylcatechol sulfate and 4-vinylphenol sulfate demonstrated the most pronounced positive and negative associations with cancer risk, respectively. Genetically proxied plasma levels of these two metabolites were significantly associated with the risk of lung cancer and renal cell cancer, with an odds ratio and 95% confidence interval of 2.81 (2.33–3.37) and 0.49 (0.40–0.61), respectively. None of these 94 associations was biased by weak instruments, horizontal pleiotropy, or reverse causation. Further, 64 of these 94 were eligible for replication analyses, and 54 (84.4%) showed P < 0.05 with association patterns consistent with those shown in primary analyses.ConclusionsOur study unveils plausible causal relationships between 66 plasma metabolites and cancer risk, expanding our understanding of the role of circulating metabolites in cancer genetics and etiology. These findings hold promise for enhancing cancer risk assessment and prevention strategies, meriting further exploration.

Phytochemical Profiling for Leaf, Stem, Roots, and Seeds of Withania somnifera (L.) Dunal

Background: Withania somnifera (L.) Dunal, belonging to the Solanaceae family and commonly known as Ashwagandha, is a traditional Ayurvedic herb renowned for its adaptogenic properties. It plays a significant role in various classical Ayurvedic formulations and proprietary medicines. Traditionally, the roots of the plant are utilized over the aerial parts, such as leaves and stems. In recent years, a global increase in the use of Ashwagandha roots has been spurred by several modern pharmacological studies supporting its benefits. Methods: This study examined different parts of the herb, including leaves, stems, roots, and seeds, using methods like phytochemical analysis, thin layer chromatography (TLC) analysis, high-performance thin layer chromatography (HPTLC) phytochemical profiling, UV-visible spectral analysis, and 1H nuclear magnetic resonance (NMR) profiling. Results: The findings indicated that phytosterols, triterpenoids, and alkaloids were predominantly found in the leaves and stems, with lower concentrations in the roots and seeds. Ethanol extracts were particularly rich in total flavonoids, whereas aqueous extracts contained higher levels of phenolic compounds. High-performance thin layer chromatography fingerprinting varied for each part of the herb, effectively separating pigment-based components such as chlorophyll at 366 nm in the aerial parts. The 1H NMR spectra showed distinct metabolite profiles for each part of the plant. Conclusions: The analytical methods proposed in this study offer enhanced quality control and evaluation for the medicinal use of W. somnifera roots and its aerial components.

Glycogen deficiency enhances carbon partitioning into glutamate for an alternative extracellular metabolic sink in cyanobacteria

Glycogen serves as a metabolic sink in cyanobacteria. Glycogen deficiency causes the extracellular release of distinctive metabolites such as pyruvate and 2-oxoglutarate upon nitrogen depletion; however, the mechanism has not been fully elucidated. This study aimed to elucidate the mechanism of carbon partitioning in glycogen-deficient cyanobacteria. Extracellular and intracellular metabolites in a glycogen-deficient ΔglgC mutant of Synechococcus elongatus PCC 7942 were comprehensively analyzed. In the presence of a nitrogen source, the ΔglgC mutant released extracellular glutamate rather than pyruvate and 2-oxoglutarate, whereas its intracellular glutamate level was lower than that in the wild-type strain. The de novo synthesis of glutamate increased in the ΔglgC mutant, suggesting that glycogen deficiency enhanced carbon partitioning into glutamate and extracellular excretion through an unidentified transport system. This study proposes a model in which glutamate serves as the prime extracellular metabolic sink alternative to glycogen when nitrogen is available.

Decoding the metabolomic responses of Caragana tibetica to livestock grazing in fragile ecosystems.

The population of Caragana tibetica, situated on the edge of the typical grassland-to-desert transition in the Mu Us Sandy Land, plays a vital ecological role in maintaining stability within the regional fragile ecosystem. Despite the consistent growth of C. tibetica following animal grazing, the biological mechanisms underlying its compensatory growth in response to livestock consumption remain unclear. Analyzing 48 metabolomic profiles from C. tibetica, our study reveals that the grazing process induces significant changes in the metabolic pathways of C. tibetica branches. Differential metabolites show correlations with soluble protein content, catalase, peroxidase, superoxide dismutase, malondialdehyde, and proline levels. Moreover, machine learning models built on these differential metabolites accurately predict the intensity of C. tibetica grazing (with an accuracy of 83.3%). The content of various metabolites, indicative of plant stress responses, including Enterolactone, Narceine, and Folcepri, exhibits significant variations in response to varying grazing intensities (P<0.05). Our investigation reveals that elevated grazing intensity intensifies the stress response in C. tibetica, triggering heightened antioxidative defenses and stress-induced biochemical activities. Distinctive metabolites play a pivotal role in responding to stress, facilitating the plant's adaptation to environmental challenges and fostering regeneration.

Antioxidant and anti-inflammatory activities of the methanol extract from the bran of the colored wheat, 'Ariheuk'

In vitro antioxidant and anti-inflammatory activities were investigated using a 70% acidic methanol extract of the colored wheat bran, 'Ariheuk.' Active metabolites were identified via metabolomic analysis using multivariate statistical comparisons. The 'Ariheuk' bran extract (ABE) contained a higher total anthocyanin content (0.19 mg C3G/g) than the general wheat bran extract (GBE) (0.01 mg C3G/g). ABE exhibited stronger antioxidant and anti-inflammatory activities than GBE. The mechanism underlying the anti-inflammatory effects of ABE was explored by assessing the expression of inducible nitric oxide synthase (iNOS) and cyclooxygenase 2 (COX-2) in RAW 264.7 cells stimulated with lipopolysaccharide (LPS). The crude ABE extract was also partially fractionated into three subfractions (ABE-F1, ABE-F2, and ABE-F3) using preparative liquid chromatography (Prep-LC) to identify the active metabolites. The total anthocyanin content was highest in ABE-F3 (1.91 ± 0.06 mg C3G/g). Among the subfractions, ABE-F2 exhibited the highest antioxidant and anti-inflammatory activities. Several distinct metabolites contributing to the activities of ABE-F2 were identified, including various cyanidin and peonidin derivatives and apigenin derivatives, such as corymboside and schaftoside.