Identification Of Metabolites Research Articles

Biodegradation of the strobilurin fungicide pyraclostrobin by Burkholderia sp. Pyr-1: Characteristics, degradation pathway, water remediation, and toxicity assessment

Pyraclostrobin, a widely used fungicide, poses significant risks to both the environment and human health. However, research on the microbial degradation process of pyraclostrobin was scarce. Here, a pyraclostrobin-degrading strain, identified as Burkholderia sp. Pyr-1, was isolated from activated sludge. Pyraclostrobin was efficiently degraded by strain Pyr-1, and completely eliminated within 6 d in the presence of glucose. Additionally, pyraclostrobin degradation was significantly enhanced by the addition of divalent metal cations (Mn2+ and Cu2+). The degradation pathway involving ether bond and N–O bond cleavage was proposed by metabolite identification. The sodium alginate-immobilized strain Pyr-1 had a higher pyraclostrobin removal rate from contaminated lake water than the free cells. Moreover, the toxicity evaluation demonstrated that the metabolite 1-(4-chlorophenyl)-1H-pyrazol-3-ol significantly more effectively inhibited Chlorella ellipsoidea than pyraclostrobin, while its degradation products by strain Pyr-1 alleviated the growth inhibition of C. ellipsoidea, which confirmed that the low-toxic metabolites were generated from pyraclostrobin by strain Pyr-1. The study provides a potential strain Pyr-1 for the bioremediation in pyraclostrobin-contaminated aquatic environments.

Identification and characterization of the in-vivo metabolites of the novel soluble epoxide hydrolase inhibitor EC5026 using liquid chromatography quadrupole time of flight mass spectrometry

EC5026 is a novel soluble epoxide hydrolase inhibitor being developed clinically to treat neuropathic pain and inflammation. In the current study, we employed the LC-ESI-Q-TOF-MS/MS technique to identify four in-vivo phase-I metabolites of EC5026 in rat model, out of which three were found to be novel. The identified metabolites include aliphatic hydroxylation, di-hydroxylation, terminal desaturation, and carboxylation. No phase-II metabolites were found. The pharmacokinetic profile of identified metabolites was established after a single oral dose of EC5026 to Wistar rats. The Tmax of the drug and metabolites were found to be in the range of 1–2 hours and 4–12 hours, respectively. The major metabolites M1 and M2 were found to have more than 2-fold (263.87% AUC) and equivalent exposure (96.33% AUC) compared to the parent drug, respectively. Further, the docking study revealed that the mono-hydroxylated and terminally desaturated metabolites possess better binding affinity than the parent drug. Therefore, these metabolites may hold sEH inhibition potential and can be followed through future research.

Pharmacokinetics, mass balance, and metabolism of [14C]envonalkib (TQ-B3139), a novel ALK tyrosine kinase inhibitor, in healthy Chinese subjects.

Envonalkib (TQ-B3139) is a novel, potent anaplastic lymphoma kinase (ALK) tyrosine kinase inhibitor used to treat ALK-positive non-small cell lung cancer. This phase I mass balance study investigated the pharmacokinetics, metabolism, and excretion of 14C-radiolabeled envonalkib in healthy Chinese male subjects. A single oral dose of 600mg (150µCi) [14C]envonalkib was administered to healthy male subjects under fasted state. Samples of blood, urine and feces were collected for quantitative determination of total radioactivity and unchanged envonalkib, and the metabolites identification. After dosing, the median Tmax of radioactivity was 4h and the mean t1/2 was 65.2h in plasma. The exposure of total radioactivity was much higher than that of unchanged envonalkib in plasma. The mean total recovery of the radiolabeled dose was 93.93% over 504h post-dose, with 15.23% in urine and 78.71% in feces. Envonalkib underwent extensive metabolism and a total of 15 metabolites were identified in plasma, urine, and feces. Unchanged envonalkib and its major metabolite M315 were the main components in plasma, accounting for 20.37% and 33.33% of total plasma radioactivity. In urine, O-dealkylation metabolite M315 was the major component accounted for 7.98% of dose. In feces, 16.01% of dose was excreted as cysteine conjugate M434-1. Envonalkib was well tolerated and there were no serious adverse events observed in the study. Envonalkib was extensively metabolized prior to excretion and eliminated primarily as metabolites via feces.

Identification of New Ketamine Metabolites and Their Detailed Distribution in the Mammalian Brain.

Ketamine is a common anesthetic used in human and veterinary medicine. This drug has recently received increased medical and scientific attention due to its indications for neurological diseases. Despite being applied for decades, ketamine's entire metabolism and pharmacological profile have not been elucidated yet. Therefore, insights into the metabolism and brain distribution are important toward identification of neurological effects. Herein, we have investigated ketamine and its metabolites in the pig brain, cerebrospinal fluid, and plasma using mass spectrometric and metabolomics analysis. We discovered previously unknown metabolites and validated their chemical structures. Our comprehensive analysis of the brain distribution of ketamine and 30 metabolites describes significant regional differences detected mainly for phase II metabolites. Elevated levels of these metabolites were identified in brain regions linked to clearance through the cerebrospinal fluid. This study provides the foundation for multidisciplinary studies of ketamine metabolism and the elucidation of neurological effects by ketamine.

Identification of metabolites produced by six gut commensal Bacteroidales strains using non-targeted LC-MS/MS metabolite profiling

As the most abundant gram-negative bacterial order in the gastrointestinal tract, Bacteroidales bacteria have been extensively studied for their contribution to various aspects of gut health. These bacteria are renowned for their involvement in immunomodulation and their remarkable capacity to break down complex carbohydrates and fibers. However, the human gut microbiota is known to produce many metabolites that ultimately mediate important microbe-host and microbe-microbe interactions. To gain further insights into the metabolites produced by the gut commensal strains of this order, we examined the metabolite composition of their bacterial cell cultures in the stationary phase. Based on their abundance in the gastrointestinal tract and their relevance in health and disease, we selected a total of six bacterial strains from the relevant genera Bacteroides, Phocaeicola, Parabacteroides, and Segatella. We grew these strains in modified Gifu anaerobic medium (mGAM) supplemented with mucin, which resembles the gut microbiota’s natural environment. Liquid chromatography-tandem mass spectrometry (LC-MS/MS)-based metabolite profiling revealed 179 annotated metabolites that had significantly differential abundances between the studied bacterial strains and the control growth medium. Most of them belonged to classes such as amino acids and derivatives, organic acids, and nucleot(s)ides. Of particular interest, Segatella copri DSM 18205 (previously referred to as Prevotella copri) produced substantial quantities of the bioactive metabolites phenylethylamine, tyramine, tryptamine, and ornithine. Parabacteroides merdae CL03T12C32 stood out due to its ability to produce cadaverine, histamine, acetylputrescine, and deoxycarnitine. In addition, we found that strains of the genera Bacteroides, Phocaeicola, and Parabacteroides accumulated considerable amounts of proline-hydroxyproline, a collagen-derived bioactive dipeptide. Collectively, these findings offer a more detailed comprehension of the metabolic potential of these Bacteroidales strains, contributing to a better understanding of their role within the human gut microbiome in health and disease.

Development and validation of a versatile non-invasive urinary steroidomics method for wildlife biomonitoring

Wildlife conservation is often challenged by a lack of knowledge about the reproduction biology and adaptability of endangered species. Although monitoring steroids and related molecules can increase this knowledge, the applicability of current techniques (e.g. immunoassays) is hampered by species-specific steroid metabolism and the requisite to avoid invasive sampling. This study presents a validated steroidomics method for the (un)targeted screening of a wide range of sex and stress steroids and related molecules in urine using ultra-high performance liquid chromatography coupled to high-resolution mass spectrometry (UHPLC-HRMS). In total, 50 steroids (conjugated and non-conjugated androgens, estrogens, progestogens and glucocorticoids) and 6 prostaglandins could be uniquely detected. A total of 45 out of 56 compounds demonstrated a detection limit below 0.01 ng μL−1. Excellent linearity (R2 > 0.99), precision (CV < 20 %), and recovery (80–120 %) were observed for 46, 41, and 39 compounds, respectively. Untargeted screening of pooled giant panda and human samples yielded 9691 and 8366 features with CV < 30 %, from which 84.1 % and 83.0 %, respectively, also demonstrated excellent linearity (R2 > 0.90). The biological validity of the method was investigated on male and female giant panda urine (n = 20), as well as pooled human samples (n = 10). A total of 24 different steroids were detected with clear qualitative and quantitative differences between human and giant panda samples. Furthermore, expected differences were revealed between female giant panda samples from different reproductive phases. In contrast to traditional biomonitoring techniques, the developed steroidomics method was able to screen a wide range of compounds and provide information on the putative identities of metabolites potentially important for reproductive monitoring in giant pandas. These results illustrate the advancements steroidomics brings to the field of wildlife biomonitoring in the pursuit to better understand the biology of endangered species.

Urinary metabolic characterization of advanced tuberculous meningitis cases in a South African paediatric population.

Tuberculous meningitis (TBM) is a severe form of tuberculosis with high neuro-morbidity and mortality, especially among the paediatric population (aged ≤12years). Little is known of the associated metabolic changes. This study aimed to identify characteristic metabolic markers that differentiate severe cases of paediatric TBM from controls, through non-invasive urine collection. Urine samples selected for this study were from two paediatric groups. Group 1: controls (n = 44): children without meningitis, no neurological symptoms and from the same geographical region as group 2. Group 2: TBM cases (n = 13): collected from paediatric patients that were admitted to Tygerberg Hospital in South Africa on the suspicion of TBM, mostly severely ill; with a later confirmation of TBM. Untargeted 1H NMR-based metabolomics data of urine were generated, followed by statistical analyses via MetaboAnalyst (v5.0), and the identification of important metabolites. Twenty nine urinary metabolites were identified as characteristic of advanced TBM and categorized in terms of six dysregulated metabolic pathways: 1) upregulated tryptophan catabolism linked to an altered vitamin B metabolism; 2) perturbation of amino acid metabolism; 3) increased energy production-metabolic burst; 4) disrupted gut microbiota metabolism; 5) ketoacidosis; 6) increased nitrogen excretion. We also provide original biological insights into this biosignature of urinary metabolites that can be used to characterize paediatric TBM patients in a South African cohort.

Degradation of pyrene by Xanthobacteraceae bacterium strain S3 isolated from the rhizosphere sediment of Vallisneria natans: active conditions, metabolite identification, and proposed pathways.

Polycyclic aromatic hydrocarbons (PAHs) were typical environmental contaminants that accumulated continuously in sediment. Microbial degradation is the main way of PAH degradation in the natural environment. Therefore, expanding the available pool of microbial resources and investigating the molecular degrading mechanisms of PAHs are critical to the efficient control of PAH-polluted sites. Here, a strain (identified as Xanthobacteraceae bacterium) with the ability to degrade pyrene was screened from the rhizosphere sediment of Vallisneria natans. Response surface analysis showed that the strain could degrade pyrene at pH 5-7, NaCl addition 0-1.5%, and temperature 25-40°C, and the maximum pyrene degradation (~ 95.4%) was obtained under the optimum conditions (pH 7.0, temperature 28.5°C, and NaCl-free addition) after 72h. Also, it was observed that the effect of temperature on the degradation ratio was the most significant. Furthermore, eighteen metabolites were identified by mass spectrometry, among which (2Z)-2-hydroxy-3-(4-oxo-4H-phenalen-3-yl) prop-2-enoic acid, 7-(carboxymethyl)-8-formyl-1-naphthyl acetic acid, phthalic acid, naphthalene-1,2-diol, and phenol were the main metabolites. And the degradation pathway of pyrene was proposed, suggesting that pyrene undergoes initial ortho-cleavage under the catalysis of metapyrocatechase to form (2Z)-2-hydroxy-3-(4-oxo-4H-phenalen-3-yl) prop-2-enoic acid. Subsequently, this intermediate was progressively oxidized and degraded to phthalic acid or phenol, which could enter the tricarboxylic acid cycle. Furthermore, the pyrene biodegradation by the strain followed the first-order kinetic model and the degradation rate changed from fast to slow, with the rate remaining mostly slow in the later stages. The slow biodegradation rate was probably caused by a significant amount of phenol accumulation in the initial stage of degradation, which resulted in a decrease in bacterial activity or death.

In Silico Analysis of Novel Bacterial Metabolites with Anticancer Activities.

Resistance to anticancer therapeutics is a major global concern. Thus, new anticancer agents should be aimed against novel protein targets to effectively mitigate the increased resistance. This study evaluated the potential of secondary metabolites from a bacterial endophyte, as new anticancer agents, against a novel protein target, fibroblast growth factor. In silico genomic characterization of the Bacillus sp. strain MHSD_37 was used to identify potential genes involved in encoding secondary metabolites with biological activity. The strain was also exposed to stress and liquid chromatography-mass spectrometry used for the identification and annotation of secondary metabolites of oligopeptide class with anticancer activity. Selected metabolites were evaluated for their anticancer activity through molecular docking and Absorption, Distribution, Metabolism, Excretion and Toxicity (ADMET) properties analysis. Phylogenetic analysis revealed that strain MHSD_37 shared close evolutionary relationships with Bacillus at the species level, with no identified relationships at the sub-species level. Both in silico genomic characterization and spectrometry analysis identified secondary metabolites with potential anticancer activity. Molecular docking analysis illustrated that the metabolites formed complexes with the target protein, fibroblast growth factor, which were stabilized by hydrogen bonds. Moreover, the ADMET analysis showed that the metabolites passed the toxicity test for use as a potential drug. Thereby, Bacillus sp. strain MHSD_37 is a potential novel strain with oligopeptide metabolites that can be used as new anticancer agents against novel protein targets.

Prediction of metabolites associated with somatic mutations in cancers by using genome-scale metabolic models and mutation data

BackgroundOncometabolites, often generated as a result of a gene mutation, show pro-oncogenic function when abnormally accumulated in cancer cells. Identification of such mutation-associated metabolites will facilitate developing treatment strategies for cancers, but is challenging due to the large number of metabolites in a cell and the presence of multiple genes associated with cancer development.ResultsHere we report the development of a computational workflow that predicts metabolite-gene-pathway sets. Metabolite-gene-pathway sets present metabolites and metabolic pathways significantly associated with specific somatic mutations in cancers. The computational workflow uses both cancer patient-specific genome-scale metabolic models (GEMs) and mutation data to generate metabolite-gene-pathway sets. A GEM is a computational model that predicts reaction fluxes at a genome scale and can be constructed in a cell-specific manner by using omics data. The computational workflow is first validated by comparing the resulting metabolite-gene pairs with multi-omics data (i.e., mutation data, RNA-seq data, and metabolome data) from acute myeloid leukemia and renal cell carcinoma samples collected in this study. The computational workflow is further validated by evaluating the metabolite-gene-pathway sets predicted for 18 cancer types, by using RNA-seq data publicly available, in comparison with the reported studies. Therapeutic potential of the resulting metabolite-gene-pathway sets is also discussed.ConclusionsValidation of the metabolite-gene-pathway set-predicting computational workflow indicates that a decent number of metabolites and metabolic pathways appear to be significantly associated with specific somatic mutations. The computational workflow and the resulting metabolite-gene-pathway sets will help identify novel oncometabolites and also suggest cancer treatment strategies.

Metabolite markers for three synthetic tryptamines N-ethyl-N-propyltryptamine, 4-hydroxy-N-ethyl-N-propyltryptamine, and 5-methoxy-N-ethyl-N-propyltryptamine.

N-Ethyl-N-propyltryptamine (EPT), 4-hydroxy-N-ethyl-N-propyltryptamine (4-OH-EPT), and 5-methoxy-N-ethyl-N-propyltryptamine (5-MeO-EPT) are new psychoactive substances classified as tryptamines, sold online. Many tryptamines metabolize rapidly, and identifying the appropriate metabolites to reveal intake is essential. While the metabolism of 4-OH-EPT and 5-MeO-EPT are not previously described, EPT is known to form metabolites by indole ring hydroxylation among others. Based on general knowledge of metabolic patterns, 5-MeO-EPT is also expected to form ring hydroxylated EPT (5-OH-EPT). In the present study, the aim was to characterize the major metabolites of EPT, 4-OH-EPT, and 5-MeO-EPT, to provide markers for substance identification in forensic casework. The tryptamines were incubated with pooled human liver microsomes at 37°C for up to 4 h. The generated metabolites were separated and detected by ultra-high performance liquid chromatography-quadrupole time-of-flight mass spectrometry analysis. The major in vitro EPT metabolites were formed by hydroxylation, N-dealkylation, and carbonylation. In comparison, 4-OH-EPT metabolism was dominated by double bond formation, N-dealkylation, hydroxylation, and carbonylation in vitro and hydroxylation or carbonylation combined with double bond loss, carbonylation, N-dealkylation, and hydroxylation in vivo. 5-MeO-EPT was metabolized by O-demethylation, hydroxylation, and N-dealkylation in vitro. The usefulness of the characterized metabolites in forensic casework was demonstrated by identification of unique metabolites for 4-OH-EPT in a human postmortem blood sample with suspected EPT or 4-OH-EPT intoxication.

Exploring Individual Variability in Drug-Induced Liver Injury (DILI) Responses through Metabolomic Analysis.

Drug-induced liver injury (DILI) is a serious adverse hepatic event presenting diagnostic and prognostic challenges. The clinical categorization of DILI into hepatocellular, cholestatic, or mixed phenotype is based on serum alanine aminotransferase (ALT) and alkaline phosphatase (ALP) values; however, this classification may not capture the full spectrum of DILI subtypes. With this aim, we explored the utility of assessing changes in the plasma metabolomic profiles of 79 DILI patients assessed by the RUCAM (Roussel Uclaf Causality Assessment Method) score to better characterize this condition and compare results obtained with the standard clinical characterization. Through the identification of various metabolites in the plasma (including free and conjugated bile acids and glycerophospholipids), and the integration of this information into predictive models, we were able to evaluate the extent of the hepatocellular or cholestatic phenotype and to assign a numeric value with the contribution of each specific DILI sub-phenotype into the patient's general condition. Additionally, our results showed that metabolomic analysis enabled the monitoring of DILI variability responses to the same drug, the transitions between sub-phenotypes during disease progression, and identified a spectrum of residual DILI metabolic features, which can be overlooked using standard clinical diagnosis during patient follow-up.

Bifidobacterium alleviate metabolic disorders via converting methionine to 5'-methylthioadenosine.

Dietary patterns and corresponding gut microbiota profiles are associated with various health conditions. A diet rich in polyphenols, primarily plant-based, has been shown to promote the growth of probiotic bacteria in the gastrointestinal tract, subsequently reducing the risk of metabolic disorders in the host. The beneficial effects of these bacteria are largely due to the specific metabolites they produce, such as short-chain fatty acids and membrane proteins. In this study, we employed a metabolomics-guided bioactive metabolite identification platform that included bioactivity testing using in vitro and in vivo assays to discover a bioactive metabolite produced from probiotic bacteria. Through this approach, we identified 5'-methylthioadenosine (MTA) as a probiotic bacterial-derived metabolite with anti-obesity properties. Furthermore, our findings indicate that MTA administration has several regulatory impacts on liver functions, including modulating fatty acid synthesis and glucose metabolism. The present study elucidates the intricate interplay between dietary habits, gut microbiota, and their resultant metabolites.

An Integrated Hepatocyte Stability Assay for Simultaneous Metabolic Stability Assessment and Metabolite Profiling.

The determination of metabolic stability is critical for drug discovery programs, allowing for the optimization of chemical entities and compound prioritization. As such, it is common to perform high-volume in vitro metabolic stability experiments early in the lead optimization process to understand metabolic liabilities. Additional metabolite identification experiments are subsequently performed for a more comprehensive understanding of the metabolic clearance routes to aid medicinal chemists in the structural design of compounds. Collectively, these experiments require extensive sample preparation and a substantial amount of time and resources. To overcome the challenges, a high-throughput integrated assay for simultaneous hepatocyte metabolic stability assessment and metabolite profiling was developed. This assay platform consists of four parts: 1) an automated liquid-handling system for sample preparation and incubation, 2) a liquid chromatography and high-resolution mass spectrometry-based system to simultaneously monitor the parent compound depletion and metabolite formation, 3) an automated data analysis and report system for hepatic clearance assessment; and 4) streamlined autobatch processing for software-based metabolite profiling. The assay platform was evaluated using eight control compounds with various metabolic rates and biotransformation routes in hepatocytes across three species. Multiple sample preparation and data analysis steps were evaluated and validated for accuracy, repeatability, and metabolite coverage. The combined utility of an automated liquid-handling instrument, a high-resolution mass spectrometer, and multiple streamlined data processing software improves the process of these highly demanding screening assays and allows for simultaneous determination of metabolic stability and metabolite profiles for more efficient lead optimization during early drug discovery. SIGNIFICANCE STATEMENT: Metabolic stability assessment and metabolite profiling are pivotal in drug discovery to fully comprehend metabolic liabilities for chemical entity optimization and lead selection. Process of these assays can be repetitive and resource demanding. Here, we developed an integrated hepatocyte stability assay that combines automation, high-resolution mass spectrometers, and batch-processing software to improve and combine the workflow of these assays. The integrated approach allows simultaneous metabolic stability assessment and metabolite profiling, significantly accelerating screening and lead optimization in a resource-effective manner.

Iodine-131 intervention in hyperthyroidism with hepatic insufficiency: Metabolomic evaluation

Hyperthyroidism, often accompanied by hepatic insufficiency (HI), poses significant clinical challenges, highlighting the necessity for identifying optimal treatment strategies and early diagnostic biomarkers to improve patient outcomes. This study aimed to determine the optimal iodine-131 (131I) intervention dose for alleviating hyperthyroidism with HI and to identify serum metabolic biomarkers for early diagnosis using UPLC-Q/TOF-MS technology. A mouse model for early 131I intervention was established to monitor changes in physiological response, body weight, fur condition, thyroid, and liver function. Metabolite identification was achieved through UPLC-Q/TOF-MS and further analyzed via MetaboAnalyst. Six biomarkers were identified and subjected to ROC analysis. Early intervention with 80 μCi 131I per gram of thyroid tissue effectively controlled hyperthyroidism and improved liver function. Metabolomics analysis uncovered 63 differentially abundant metabolites, six of which (L-kynurenine, Taurochenodesoxycholic acid, Glycocholic acid, Phytosphingosine, Tryptamine, and Betaine) were identified as early warning biomarkers. Post-intervention, these biomarkers progressively returned to normal levels. This study demonstrates the efficacy of UPLC-Q/TOF-MS in identifying metabolic biomarkers for early diagnosis of hyperthyroidism with HI and highlights the therapeutic potential of early 131I intervention in normalizing these biomarkers.

Metabolomics-driven investigation of plant defense response against pest and pathogen attack.

The advancement of metabolomics has assisted in the identification of various bewildering characteristics of the biological system. Metabolomics is a standard approach, facilitating crucial aspects of system biology with absolute quantification of metabolites using minimum samples, based on liquid/gas chromatography, mass spectrometry and nuclear magnetic resonance. The metabolome profiling has narrowed the wide gaps of missing information and has enhanced the understanding of a wide spectrum of plant-environment interactions by highlighting the complex pathways regulating biochemical reactions and cellular physiology under a particular set of conditions. This high throughput technique also plays a prominent role in combined analyses of plant metabolomics and other omics datasets. Plant metabolomics has opened a wide paradigm of opportunities for developing stress-tolerant plants, ensuring better food quality and quantity. However, despite advantageous methods and databases, the technique has a few limitations, such as ineffective 3D capturing of metabolites, low comprehensiveness, and lack of cell-based sampling. In the future, an expansion of plant-pathogen and plant-pest response towards the metabolite architecture is necessary to understand the intricacies of plant defence against invaders, elucidation of metabolic pathway operational during defence and developing a direct correlation between metabolites and biotic stresses. Our aim is to provide an overview of metabolomics and its utilities for the identification of biomarkers or key metabolites associated with biotic stress, devising improved diagnostic methods to efficiently assess pest and pathogen attack and generating improved crop varieties with the help of combined application of analytical and molecular tools.

Non-targeted metabolomics for the identification of plasma metabolites associated with organic anion transporting polypeptide 1B1 function.

Our aim was to evaluate biomarkers for organic anion transporting polypeptide 1B1 (OATP1B1) function using a hypothesis-free metabolomics approach. We analyzed fasting plasma samples from 356 healthy volunteers using non-targeted metabolite profiling by liquid chromatography high-resolution mass spectrometry. Based on SLCO1B1 genotypes, we stratified the volunteers to poor, decreased, normal, increased, and highly increased OATP1B1 function groups. Linear regression analysis, and random forest (RF) and gradient boosted decision tree (GBDT) regressors were used to investigate associations of plasma metabolite features with OATP1B1 function. Of the 9152 molecular features found, 39 associated with OATP1B1 function either in the linear regression analysis (p < 10-5) or the RF or GBDT regressors (Gini impurity decrease > 0.01). Linear regression analysis showed the strongest associations with two features identified as glycodeoxycholate 3-O-glucuronide (GDCA-3G; p = 1.2 × 10-20 for negative and p = 1.7 × 10-19 for positive electrospray ionization) and one identified as glycochenodeoxycholate 3-O-glucuronide (GCDCA-3G; p = 2.7 × 10-16). In both the RF and GBDT models, the GCDCA-3G feature showed the strongest association with OATP1B1 function, with Gini impurity decreases of 0.40 and 0.17. In RF, this was followed by one GDCA-3G feature, an unidentified feature with a molecular weight of 809.3521, and the second GDCA-3G feature. In GBDT, the second and third strongest associations were observed with the GDCA-3G features. Of the other associated features, we identified with confidence two representing lysophosphatidylethanolamine 22:5. In addition, one feature was putatively identified as pregnanolone sulfate and one as pregnenolone sulfate. These results confirm GCDCA-3G and GDCA-3G as robust OATP1B1 biomarkers in human plasma.

Identification of a host metabolite with both antiviral and anti-inflammatory properties that protects against influenza virus-driven morbidity and mortality

Identification of a host metabolite with both antiviral and anti-inflammatory properties that protects against influenza virus-driven morbidity and mortality

Studies on Secondary Metabolites and In vitro and In silico Anticholinesterases Activities of the Sea Urchin Echinometra mathaei Crude Venoms from the Persian Gulf-Bushehr

Background: Echinoderms are a unique source of amazing secondary metabolites with a wide spectrum of biological activities. Several species of sea urchins contain various toxins and biologically active metabolites. One of the most attractive approaches to treat Alzheimer's disease is searching for effective marine natural products with cholinesterase inhibitory activities. Objective: The current study is designed to investigate the in vitro and in silico acetylcholinesterase and butyrylcholinesterase inhibitory activities of the Persian Gulf echinoderm sea urchin Echinometra mathaei venom and related chemical compounds. Methods: The experiments for LD50, total protein, protein bands, in vitro cholinesterase inhibitory activities, the identity of secondary metabolites, and the in silico evaluations, respectively, were performed by Spearman-Karber, Lowry, SDS-PAGE, Ellman's spectroscopic, GC-MS, and docking methods. Results: The LD50 (IV rat) of the spine, gonad, and coelomic fluid from sea urchin samples were 2.231 ± 0.09, 1.03 ± 0.05, and 1.12 ± 0.13 mg/ml, respectively. The SDS-PAGE and total protein studies showed that at least a portion of the venom is protein in nature. GC-MS analysis of the identified samples revealed 12, 23, and 21 compounds with different chemical types, including alkaloids, terpenes, and steroids, respectively. According to the results, all samples act as significant inhibitors of both enzymes. In silico data for the identified compounds also confirmed the experimental results. Conclusion: The alkaloid compound 6H-Indolo[3,2,1-de] [1,5] naphthyridine-6-one,1,2,3a,4,5- hexahydro-8-hydroxy-3-methyl (C7) had the highest affinity for both enzymes. Further research is needed to determine whether C7 could be a therapeutic candidate for Alzheimer's disease.

Analyses of plasma metabolites using a high performance four-channel CIL LC-MS method and identification of metabolites associated with enteric methane emissions in beef cattle.

Reducing enteric methane (one greenhouse gas) emissions from beef cattle not only can be beneficial in reducing global warming, but also improve efficiency of nutrient utilization in the production system. However, direct measurement of enteric methane emissions on individual cattle is difficult and expensive. The objective of this study was to detect plasma metabolites that are associated with enteric methane emissions in beef cattle. Average enteric methane emissions (CH4) per day (AVG_DAILYCH4) for each individual cattle were measured using the GreenFeed emission monitoring (GEM) unit system, and beef cattle with divergent AVG_DAILYCH4 from Angus (n = 10 for the low CH4 group and 9 for the high CH4 group), Charolais (n = 10 for low and 10 for = high), and Kinsella Composite (n = 10 for low and 10 for high) populations were used for plasma metabolite quantification and metabolite-CH4 association analyses. Blood samples of these cattle were collected near the end of the GEM system tests and a high performance four-channel chemical isotope labeling (CIL) liquid chromatography (LC) mass spectrometer (MS) method was applied to identify and quantify concentrations of metabolites. The four-channel CIL LC-MS method detected 4235 metabolites, of which 1105 were found to be significantly associated with AVG_DAILYCH4 by a t-test, while 1305 were significantly associated with AVG_DAILYCH4 by a regression analysis at p<0.05. Both the results of the t-test and regression analysis revealed that metabolites that were associated with enteric methane emissions in beef cattle were largely breed-specific whereas 4.29% to 6.39% CH4 associated metabolites were common across the three breed populations and 11.07% to 19.08% were common between two breed populations. Pathway analyses of the CH4 associated metabolites identified top enriched molecular processes for each breed population, including arginine and proline metabolism, arginine biosynthesis, butanoate metabolism, and glutathione metabolism for Angus; beta-alanine metabolism, pyruvate metabolism, glycolysis / gluconeogenesis, and citrate cycle (TCA cycle) for Charolais; phenylalanine, tyrosine and tryptophan biosynthesis, phenylalanine metabolism, arginine biosynthesis, and arginine and proline metabolism for Kinsella Composite. The detected CH4 associated metabolites and enriched molecular processes will help understand biological mechanisms of enteric methane emissions in beef cattle. The detected CH4 associated plasma metabolites will also provide valuable resources to further characterize the metabolites and verify their utility as biomarkers for selection of cattle with reduced methane emissions.