Identification Of Metabolites Research Articles

Artificial Intelligence in the Identification of Key Metabolites Associated with Diabetic Kidney Disease

Artificial Intelligence in the Identification of Key Metabolites Associated with Diabetic Kidney Disease

Plant Metabolomics: The Future of Anticancer Drug Discovery.

Drug development from medicinal plants constitutes an important strategy for finding natural anticancer therapies. While several plant secondary metabolites with potential antitumor activities have been identified, well-defined mechanisms of action remained uncovered. In fact, studies of medicinal plants have often focused on the genome, transcriptome, and proteome, dismissing the relevance of the metabolome for discovering effective plant-based drugs. Metabolomics has gained huge interest in cancer research as it facilitates the identification of potential anticancer metabolites and uncovers the metabolomic alterations that occur in cancer cells in response to treatment. This holds great promise for investigating the mode of action of target metabolites. Although metabolomics has made significant contributions to drug discovery, research in this area is still ongoing. In this review, we emphasize the significance of plant metabolomics in anticancer research, which continues to be a potential technique for the development of anticancer drugs in spite of all the challenges encountered. As well, we provide insights into the essential elements required for performing effective metabolomics analyses.

Bioactive Compounds and Valorization of Coffee By-Products from the Origin: A Circular Economy Model from Local Practices in Zongolica, Mexico.

The by-products of green coffee processing are rich in compounds that can be recycled for their possible use in the production of beverages, fertilizers and weed control in production areas. The objective of this work was to identify the organic and inorganic bioactive compounds of green coffee and the coffee by-products related to the production of origin, such as dried cascara (skin-pulp), parchment and silverskin (unroasted), in order to investigate the role their biomolecules may have in reuse through practices and local knowledge, not yet valued. The metabolomic profile by HPLC-ESI-HRMS of the aqueous extract of the dried cascara highlighted 93 non-volatile molecules, the highest number reported for dried cascara. They belong to groups of organic acids (12), alkaloids (5), sugars (5), fatty acids (2), diglycerides (1), amino acids (18), phospholipids (7), vitamins (5), phenolic acids (11), flavonoids (8), chlorogenic acids (17), flavones (1) and terpenes (1). For the first time, we report the use of direct analysis in real-time mass spectrometry (DART-MS) for the identification of metabolites in aqueous extracts of dried cascara, parchment, silverskin and green coffee. The DART analysis mainly showed the presence of caffeine and chlorogenic acids in all the extracts; additionally, sugar adducts and antioxidant compounds such as polyphenols were detected. The mineral content (K, Ca, P, S, Mg and Cl) by EDS spectrometry in the by-products and green coffee showed a relatively high content of K in the dried cascara and green coffee, while Ca was detected in double quantity in the silverskin. These metabolomic and mineral profile data allow enhancement of the link between the quality of green coffee and its by-products and the traditional local practices in the crop-growing area. This consolidates the community's experience in reusing by-products, thereby minimizing the impact on the environment and generating additional income for coffee growers' work, in accordance with the principles of circular economy and bioeconomy.

Identification of volatile and flavor metabolites in three varieties of broccoli sprouts

Broccoli sprouts are promising functional food sources and their taste and flavor play a pivotal role in the acceptance of consumers. In this study, the flavor profiles of three varieties of broccoli sprouts, namely Bi Lv, You Xiu, and Lv Hua, were comprehensively characterized using HS-SPME-GC/MS analysis. A total of 364 volatile and flavor components across 15 chemical classes were successfully identified. The results revealed a majority of volatile metabolites exhibiting upregulation during the germination process, leading to an enhancement in taste intensity after germination, particularly for umami and sweet tastes, which was associated with an increase in associated amino acids and sugar content. Although the total glucosinolate content in broccoli sprouts has decreased compared to seeds, it remains the primary contributor to the bitterness of broccoli sprouts. The present study elaborated on the flavor contribution of broccoli sprouts, supporting the cultivation and consumption of them as a nutritious food.

Metabolite Profiling and Identification of Sweet/Bitter Taste Compounds in the Growth of Cyclocarya Paliurus Leaves Using Multiplatform Metabolomics.

Cyclocarya paliurus tea, also known as "sweet tea", an herbal tea with Cyclocarya paliurus leaves as raw material, is famous for its unique nutritional benefits and flavor. However, due to the unique "bittersweet" of Cyclocarya paliurus tea, it is still unable to fully satisfy consumers' high-quality taste experience and satisfaction. Therefore, this study aimed to explore metabolites in Cyclocarya paliurus leaves during their growth period, particularly composition and variation of sweet and bitter taste compounds, by combining multi-platform metabolomics analysis with an electronic tongue system and molecular docking simulation technology. The results indicated that there were significant differences in the contents of total phenols, flavonoids, polysaccharides, and saponins in C. paliurus leaves in different growing months. A total of 575 secondary metabolites were identified as potential active metabolites related to sweet/bitter taste using nontargeted metabolomics based on UHPLC-MS/MS analysis. Moreover, molecular docking technology was utilized to study interactions between the candidate metabolites and the sweet receptors T1R2/T1R3 and the bitter receptors T2R4/T2R14. Six key compounds with high sweetness and low bitterness were successfully identified by using computational simulation analysis, including cis-anethole, gluconic acid, beta-D-Sedoheptulose, asparagine, proline, and citrulline, which may serve as candidates for taste modification in Cyclocarya paliurus leaves. These findings provide a new perspective for understanding the sweet and bitter taste characteristics that contribute to the distinctive sensory quality of Cyclocarya paliurus leaves.

Untargeted Metabolomic Biomarker Discovery for the Detection of Ectopic Pregnancy.

Ectopic pregnancy (EP) is the leading cause of maternal morbidity and mortality in the first trimester. Using an untargeted metabolomic approach, we sought to identify putative plasma biomarkers using tandem liquid chromatography-mass spectrometry for the detection of tubal EP. This case-control study included the prospective recruitment of 50 tubal EP cases and 50 early intrauterine pregnancy controls. To avoid over-fitting, logistic regression models were developed in a randomly selected discovery group (30 cases vs. 30 controls) and validated in the test group (20 cases vs. 20 controls). In total, 585 mass spectral features were detected, of which 221 molecular features were significantly altered in EP plasma (p < 0.05). Molecular networking and metabolite identification was employed using the Global Natural Products Social Molecular Networking (GNPS) database, which identified 97 metabolites at a high confidence level. Top significant metabolites include subclasses of sphingolipids, carnitines, glycerophosphocholines, and tryptophan metabolism. The top regression model, consisting of D-erythro-sphingosine and oleoyl-carnitine, was validated in a test group and achieved an area under receiving operating curve (AUC) (95% CI) = 0.962 (0.910-1) with a sensitivity of 100% and specificity of 95.9%. Metabolite alterations indicate alterations related to inflammation and abnormal placentation in EP. The validation of these metabolite biomarkers in the future could potentially result in improved early diagnosis.

Role of grass endophytic fungi as a natural resource of bioactive metabolites.

Grass endophytic fungi have garnered increasing attention as a prolific source of bioactive metabolites with potential application across various fields, including pharmaceticals agriculture and industry. This review paper aims to synthesize knowledge on the diversity, isolation, and bioactivity of metabolites produced by grass endophytic fungi. Additionally, this approach aids in the conservation of rare and endangered plant species. Advanced analytical techniques such as high-performance liquid chromatography, liquid chromatograpy-mass spectrometry and gas chromatography are discussed as critical tools for metabolite identification and characterization. The review also highlights significant bioactive metabolites discovered to date, emphasizing their antimicrobial, antioxidant, and insecticidal activities and plant growth regulation properties. Besides address the challenges and future prospects in harnessing grass endophytic fungi for sustainable biotenological applications. By consolidating recent advancements and identifying agaps in the current research, this paper provides a comprehensive overview of the potential grass endophytic fungi as a valuable resource for novel bioactive compounds.

Contemporary Update on Clinical and Experimental Prostate Cancer Biomarkers: A Multi-Omics-Focused Approach to Detection and Risk Stratification.

Prostate cancer remains a significant health challenge, being the most prevalent non-cutaneous cancer in men worldwide. This review discusses the critical advancements in biomarker discovery using single-omics and multi-omics approaches. Multi-omics, integrating genomic, transcriptomic, proteomic, metabolomic, and epigenomic data, offers a comprehensive understanding of the molecular heterogeneity of prostate cancer, leading to the identification of novel biomarkers and therapeutic targets. This holistic approach not only enhances the specificity and sensitivity of prostate cancer detection but also supports the development of personalized treatment strategies. Key studies highlighted include the identification of novel genes, genetic mutations, peptides, metabolites, and potential biomarkers through multi-omics analyses, which have shown promise in improving prostate cancer management. The integration of multi-omics in clinical practice can potentially revolutionize prostate cancer prognosis and treatment, paving the way for precision medicine. This review underscores the importance of continued research and the application of multi-omics to overcome current challenges in prostate cancer diagnosis and therapy.

Identification and Replication of Urine Metabolites Associated With Short-Term and Habitual Intake of Sweet and Fatty Snacks in European Children and Adolescents

BackgroundIntake of sweet and fatty snacks may partly contribute to the occurrence of obesity and other health conditions in childhood. Traditional dietary assessment methods may be limited in accurately assessing the intake of sweet and fatty snacks in children. Metabolite biomarkers may aid the objective assessment of children’s food intake and support establishing diet–disease relationships. ObjectivesThe present study aimed to identify biomarkers of sweet and fatty snack intake in 2 independent cohorts of European children. MethodsWe used data from the IDEFICS/I.Family cohort from baseline (2007/2008) and 2 follow-up examination waves (2009/2010 and 2013/2014). In total, 1788 urine samples from 599 children were analyzed for untargeted metabolomics using high-resolution liquid chromatography-mass spectrometry. Short-term dietary intake was assessed by 24-h dietary recalls, and habitual dietary intake was calculated with the National Cancer Institute method. Data from the Dortmund Nutritional and Anthropometric Longitudinal Designed (DONALD) cohort of 24-h urine samples (n = 567) and 3-d weighted dietary records were used for external replication of results. Multivariate modeling with unbiased variable selection in R algorithms and linear mixed models were used to identify novel biomarkers. Metabolite features significantly associated with dietary intake were then annotated. ResultsIn total, 66 metabolites were discovered and found to be statistically significant for chocolate candy; cakes, puddings, and cookies; candy and sweets; ice cream; and crisps. Most of the features (n = 62) could not be annotated. Short-term and habitual chocolate intake were positively associated with theobromine, xanthosine, and cyclo(L-prolyl-L-valyl). These results were replicated in the DONALD cohort. Short-term candy and sweet intake was negatively associated with octenoylcarnitine. ConclusionsOf the potential metabolite biomarkers of sweet and fatty snacks in children, 3 biomarkers of chocolate intake, namely theobromine, xanthosine, and cyclo(L-prolyl-L-valyl), are externally replicated. However, these potential biomarkers require further validation in children.

Metabolit Sekunder dan Uji Bioaktivitas Sitotoksik Ekstrak Buah Sumpit (Brucea javanica (L.) Merr) terhadap Artemia salina Leach

Research carried out with the title of Secondary Metabolite Identification and bioactivity Fruit Extract Sumpit (Brucea javanica (L) Merr) to the shrimp larvae Artemia salina Leach. This study aims to identifying classes of secondary metabolites as well as test the bioactivity of secondary metabolites sumpit. Identifikasi fruit extracts performed to test the Chopsticks fruit extracts and fractions against reagent, while the bioactivity test was conducted using Brine Shrimp Lethality Test (BSLT). Data were analyzed using the method of Reed and Muench to get Lethality Concrentation value 50% (LC50). The results showed that the fruit extract Sumpit contain the alkaloid class of secondary metabolites, karatenoid, saponins, tannins, phenolic compounds, steroids, and terpenoids. Sumpit fruit bioactivity test results had LC50 values of the methanol extract of 3.10 ppm, n-hexane fraction of 2.09 ppm, 0.79 ppm ethyl acetate fraction and n-butanol fractions of 0.74 ppm.

Immunomodulatory Mechanisms of Tea Leaf Polysaccharide in Mice with Cyclophosphamide-Induced Immunosuppression Based on Gut Flora and Metabolomics.

Tea polysaccharides (TPSs) are receiving increasing attention because of their diverse pharmacological and biological activities. Here, we explored the immunoregulatory mechanisms of TPSs from fresh tea leaves in a mouse model of cyclophosphamide (CTX)-induced immunosuppression in terms of gut microbiota and metabolites. We observed that TPSs significantly increased the body weight and alleviated CTX-induced thymus atrophy in the immunosuppressed mice; they also increased the plasma levels of immunoglobulins A and M, interleukin (IL) 1β, IL-6, inducible nitric oxide synthase, and tumor necrosis factor α. Furthermore, we conducted 16S rDNA sequencing of cecal contents, resulting in the acquisition of 5008 high-quality bacterial 16S rDNA gene reads from the sequencing of mouse fecal samples. By analyzing the data, we found that TPSs regulated the gut microbiota structure and diversity and alleviated the CTX-induced dysregulation of gut microbiota. The colonic contents of mice were subjected to analysis using the UPLC-Q-TOF/MS/MS technique for the purpose of untargeted metabolomics. In the course of our metabolite identification analysis, we identified a total of 2685 metabolites in positive ion mode and 1655 metabolites in negative ion mode. The analysis of these metabolites indicated that TPSs improved CTX-induced metabolic disorders by regulating the levels of metabolites related to tryptophan, arginine, and proline metabolism. In conclusion, TPSs can alleviate CTX-induced immunosuppression by regulating the structural composition of gut microbiota, indicating the applicability of TPSs as novel innate immune modulators in health foods or medicines.

Targeting TRIM26: Unveiling an Oncogene and Identification of Plant Metabolites as a Potential Therapeutics for Breast Cancer.

Breast cancer is the major cause of cancer-related mortality and frequent malignancies among women worldwide. The TRIM (Tripartite Motif) protein family is a broad and diverse set of proteins that contain a conserved structural motif known as the tripartite motif, which comprises of three different domains, B-box domain, Coiled-coil domain and RBR (Ring-finger, B-box, and coiled-coil) domain. TRIM proteins are involved in regulating cancer growth and metastasis. However, TRIM proteins are still unexplored in cancer cell regulation. In this study, by using a cancer database expression of all TRIM proteins was determined in breast cancer. Out of 77 TRIM genes, 16 genes were upregulated in breast cancer. Here, the upregulated TRIM26 gene's role is not yet explored in breast cancer. Indeed, TRIM26 is upregulated in 21 cancer types out of 33 cancer types. To investigate the role of TRIM26 in breast cancer, siRNA-mediated gene silencing was carried out in MCF-7 and MDA-MB 231 breast cancer cells. Reduced expression of TRIM 26 decreased cancer cell proliferation, migration and invasion with simultaneous reduction of various proliferative, cell cycle and mesenchymal markers and upregulation of epithelial markers. Further, docking studies found potential novel plant metabolites. Thus, targeting TRIM26 may provide a novel therapeutic approach for breast cancer treatment.

Squirting Cucumber, Ecballium elaterium (L.) A. Ritch: An Update of Its Chemical and Pharmacological Profile.

Ecballium elaterium, also known as squirting cucumber, is a plant which is widespread in temperate regions of Europe, Africa and Asia. The plant is considered to be one of the oldest used drugs. In the last decades, E. elaterium has been widely studied as a source of triterpene metabolites named cucurbitacins, often found as glycosylated derivatives, used by the plant as defensive agents. Such metabolites exhibit several biological activities, including cytotoxic, anti-inflammatory, and anti-cancer. Interestingly, the bioactive properties of E. elaterium extracts have been investigated in dozens of studies, especially by testing the apolar fractions, including the essential oils, extracted from leaves and fruits. The purpose of this review is to provide an overview of the chemical profile of different parts of the plants (leaves, flowers, and seeds) analyzing the methods used for structure elucidation and identification of single metabolites. The pharmacological studies on the isolated compounds are also reported, to highlight their potential as good candidates for drug discovery.

UHPLC-Q-TOF-MS/MS identification of metabolites in cereal beverage ‘Borde’ and its anti-obesity efficacy in Caenorhabditis elegans model

This research explores the remarkable impact of fermented cereals such as sorghum, maize, and wheat with Pediococcus acidilactici WS07, a strain isolated from Ethiopia's traditional borde beverage. The fermented cereal extracts were thoroughly evaluated for antioxidant activity, inhibition of pancreatic lipase and α-glucosidase, metabolite identification through UHPLC-Q-TOF-MS/MS, and in vivo efficacy using the C. elegans model. The results revealed significant enhancements in the bioactive compounds of fermented cereals, demonstrating promising directions for obesity prevention strategies. Notably, the fermented sorghum extracts improved lipase (88.23 %) and α-glucosidase (85.62 %) inhibitory activities compared to its unfermented counterparts. The antioxidant properties of all fermented samples were confirmed through improved DPPH (67.77–71.86 %) and ABTS (59.91–65.49 %) scavenging activities. Fermentation also led to a notable increase in polyphenols and flavonoids, with detailed metabolite analysis revealing a dynamic shift in the composition of these bioactive compounds. Additionally, C. elegans indicates that fermented extracts extend lifespan, reduce lipid accumulation, and lower triglycerides, highlighting their potential as functional foods for health enhancement and obesity management. This study not only underscores the efficacy of P. acidilactici WS07 fermentation in transforming cereals into nutrient-rich functional foods but also provides insight into how microbial fermentation can unlock the health-promoting potential of traditional diets.

Systematic synthesis and identification of monolignol pathway metabolites.

Monolignol serves as the building blocks to constitute lignin, the second abundant polymer on Earth. Despite two decades of diligent efforts, complete identification of all metabolites in the currently proposed monolignol biosynthesis pathway has proven elusive. This limitation also hampers their potential application. One of the primary obstacles is the challenge of assembling a collection of all molecules, because many are commercially unavailable or prohibitively costly. In this study, we established systematic pipelines to synthesize all 24 molecules through the conversions between functional groups on a core structure followed by the application to other core structures. We successfully identified all of them in Populus trichocarpa and Eucalyptus grandis, two representative species respectively from malpighiales and myrtales in angiosperms. Knowledge about monolignol metabolite chemosynthesis and identification will form the foundation for future studies.

Omega 3 Fatty Acids Attenuate the Acute Kidney Injury to CKD Transition and Renal Fibrosis: Identification of Antifibrotic Metabolites.

AKI is an established risk factor for developing CKD. Recently, the renoprotective effect of omega-3 polyunsaturated fatty acids (ω3PUFAs) has attracted attention. This study aimed to evaluate the effect of ω3PUFAs on the transition of AKI to CKD, and to identify fatty acid active metabolites in renal tissue. Two mice models of AKI to CKD (7-week, male) and unilateral ureteral obstruction (UUO)-induced renal fibrosis (11-week, male) were fed linseed oil, rich in ω3PUFAs (Lin group), or with soybean oil, low in ω3PUFAs (Soy group). Renal fatty acids and metabolites composition in mice were measured by liquid chromatography-mass spectrometry. Rat renal fibroblast cells (NRK-49F cells) were used for in vitro study. At day 14 after 35 min bilateral renal ischemia reperfusion (IR), significant increase in survival was observed in the Lin group compared to the Soy group. Using the 30 min bilateral renal IR model (AKI to CKD model), the Lin group showed attenuated renal tissue damage and fibrosis. In addition, the antifibrotic effect of Lin group was also observed in UUO renal fibrosis model. In the two mice models, levels of eicosapentaenoic acid (EPA) and its metabolites were significantly elevated in renal tissue of mice fed with Lin. Cultured NRK-49F incubated with EPA and its metabolites 18-hydroxyeicosapentaenoic acid (18-HEPE), 17,18-epoxyeicosatetraenoic acid (17,18-EpETE) and 17,18-dihydroxyeicosatetraenoic acid (17,18-diHETE) displayed suppressed TGF-β1-stimulated α-smooth muscle actin protein expression. These effects were suppressed in the presence of an inhibitor of a cytochrome P450 involved in EPA metabolism. This observation suggests that the EPA metabolites have antifibrotic effects. ω3PUFAs prevents AKI to CKD and renal fibrosis. Moreover, the EPA metabolites 18-HEPE, 17,18-EpETE and 17,18-diHETE were found to have antifibrotic effects.

Advancing the Prediction of MS/MS Spectra Using Machine Learning.

Tandem mass spectrometry (MS/MS) is an important tool for the identification of small molecules and metabolites where resultant spectra are most commonly identified by matching them with spectra in MS/MS reference libraries. While popular, this strategy is limited by the contents of existing reference libraries. In response to this limitation, various methods are being developed for the in silico generation of spectra to augment existing libraries. Recently, machine learning and deep learning techniques have been applied to predict spectra with greater speed and accuracy. Here, we investigate the challenges these algorithms face in achieving fast and accurate predictions on a wide range of small molecules. The challenges are often amplified by the use of generic machine learning benchmarking tactics, which lead to misleading accuracy scores. Curating data sets, only predicting spectra for sufficiently high collision energies, and working more closely with experimental mass spectrometrists are recommended strategies to improve overall prediction accuracy in this nuanced field.

Pharmaceutical metabolite identification in lettuce (Lactuca sativa) and earthworms (Eisenia fetida) using liquid chromatography coupled to high-resolution mass spectrometry and in silico spectral library.

Pharmaceuticals released into the aquatic and soil environments can be absorbed by plants and soil organisms, potentially leading to the formation of unknown metabolites that may negatively affect these organisms or contaminate the food chain. The aim of this study was to identify pharmaceutical metabolites through a triplet approach for metabolite structure prediction (software-based predictions, literature review, and known common metabolic pathways), followed by generating in silico mass spectral libraries and applying various mass spectrometry modes for untargeted LC-qTOF analysis. Therefore, Eisenia fetida and Lactuca sativa were exposed to a pharmaceutical mixture (atenolol, enrofloxacin, erythromycin, ketoprofen, sulfametoxazole, tetracycline) under hydroponic and soil conditions at environmentally relevant concentrations. Samples collected at different time points were extracted using QuEChERS and analyzed with LC-qTOF in data-dependent (DDA) and data-independent (DIA) acquisition modes, applying both positive and negative electrospray ionization. The triplet approach for metabolite structure prediction yielded a total of 3762 pharmaceutical metabolites, and anin silico mass spectral library was created based on these predicted metabolites. This approach resulted in the identification of 26 statistically significant metabolites (p < 0.05), with DDA + and DDA - outperforming DIA modes by successfully detecting 56/67 sample type:metabolite combinations. Lettuce roots had the highest metabolite count (26), followed by leaves (6) and earthworms (2). Despite the lower metabolite count, earthworms showed the highest peak intensities, closely followed by roots, with leaves displaying the lowest intensities. Common metabolic reactions observed included hydroxylation, decarboxylation, acetylation, and glucosidation, with ketoprofen-related metabolites being the most prevalent, totaling 12 distinct metabolites. In conclusion, we developed a high-throughput workflow combining open-source software with LC-HRMS for identifying unknown metabolites across various sample types.

Metabolic Stability and Metabolite Identification of CYP450 Probe Substrates in Ferret Hepatocytes.

Ferrets exhibit similar lung physiology to humans and display similar clinical signs following influenza infection, making them a valuable model for studying high susceptibility and infection patterns. However, the metabolic fate of several common human CYP450 probe substrates in ferrets is still unknown and has not been studied. The purpose of this study was to investigate the metabolism of nine human CYP450 probe substrates in ferret hepatocytes and explore their metabolic rate differences between ferrets and other species. Nine substrates were individually incubated in ferret hepatocytes for up to 120 min. At each time point, 30 μL mixtures were extracted for stability analysis using LC-MS/MS methods. After a 120-minute incubation period, 400 μL of the mixtures were extracted for metabolite identification using UHPLC-QExactive Plus. The metabolic clearance was determined as follows: diclofenac > taxol > chlorzoxazone > dextromethorphan > midazolam > omeprazole > bupropion > phenacetin > testosterone. Seven metabolites were identified from phenacetin. Deethylation was found to be the major pathway, and the major metabolite was matched with acetaminophen as probed with the CYP1A2 enzyme. Six metabolites were identified from diclofenac. Glucuronidation was the primary pathway, and a metabolite was found to match 4-OH-diclofenac as probed with the CYP2C9 enzyme. Twenty-two metabolites were identified from omeprazole. The major metabolic pathways included mono-oxygenation and sulfoxide to thioether conversion. No metabolite was found to match with the 5-OH-omeprazole as probed with the CYP2C19 enzyme. Twenty-two metabolites were identified from dextromethorphan. Demethylation was found to be the major metabolic pathway, and one demethylation metabolite was matched with dextrorphan as probed with CYP2D6. Fourteen metabolites were identified from midazolam. Mono-oxygenation was found to be the primary metabolic pathway, and one of the mono-oxygenation metabolites was matched with 1-OH-midazolam as probed with the CYP3A4 enzyme. Eight metabolites were identified from testosterone. Mono-oxygenation and glucuronidation were identified as the major metabolic pathways. One mono-oxygenation was matched with 6-β-testosterone as probed with CYP3A4 enzyme. Six metabolites were identified from taxol. Hydrolysis and mono-oxygenation were the top two metabolic pathways. No metabolite was matched with 6-α-OH-taxol as probed with the CYP2C8 enzyme. Ten metabolites were identified from bupropion. Mono-oxygenation and hydrogenation were identified as the top two metabolic pathways. No mono-oxygenation metabolite was matched with hydroxy-bupropion as probed with the CYP2B6 enzyme. Nine metabolites were identified from chlorzoxazone. Monooxygenation and sulfation were the top two metabolic pathways. One mono-oxygenation metabolite was matched with 6-OH-chlorzoxazone as probed with the CYP2E1 enzyme. Nine human CYP probe substrates were clearly metabolized in ferret hepatocytes, demonstrating substrate-dependent metabolic rates in ferret hepatocytes and species-dependent metabolic rates in mouse, rat, dog, monkey, and human hepatocytes. Except for 6-a-5-OH-omeprazole, 6-α-OH-taxol, and hydroxy-bupropion, specific metabolites of other six probe substrates in ferret hepatocytes were detected and identified as probed with six human CYP enzymes, respectively.

Identification of a chlorosalicylic acid decarboxylase (CsaD) involved in decarboxylation of 3,6-DCSA from an anaerobic dicamba-degrading sludge.

3,6-Dichlorosalicylic acid (3,6-DCSA) is the demethylation metabolite of herbicide 3,6-dichloro-2-methoxy benzoic acid (dicamba). Previous studies have shown that anaerobic sludge further transformed 3,6-DCSA through decarboxylation and dechlorination. However, the anaerobe, enzyme, and gene involved in the anaerobic degradation of 3,6-DCSA are still unknown. In this study, an anaerobic sludge that efficiently degraded dicamba was enriched, and a 3,6-DCSA decarboxylase, designated chlorosalicylic acid decarboxylase (CsaD), was partially purified and identified from the anaerobic sludge. Metagenomic analysis showed that the csaD gene was located in a gene cluster of metagenome-assembled genome 8 (MAG8). MAG8 belonged to an uncultured order, OPB41, in the class Coriobacteriia of the phylum Actinobacteria, and its abundance increased approximately once during the enrichment process. CsaD was a non-oxidative decarboxylase in the amidohydrolase 2 family catalyzing the decarboxylation of 3,6-DCSA and 6-chlorosalicylic acid (6-CSA). Its affinity and catalytic efficiency for 3,6-DCSA were significantly higher than those for 6-CSA. This study provides new insights into the anaerobic catabolism of herbicide dicamba.IMPORTANCEDicamba, an important hormone herbicide, easily migrates to anoxic habitats such as sediment, ground water, and deep soil. Thus, the anaerobic catabolism of dicamba is of importance. Anaerobic bacteria or sludge demethylated dicamba to 3,6-DCSA, and in a previous study, based on metabolite identification, it was proposed that 3,6-DCSA be further degraded via two pathways: decarboxylation to 2,5-dichlorophenol, then dechlorination to 3-chlorophenol (3-CP); or dechlorination to 6-CSA, then decarboxylation to 3-CP. However, there was no physiological and genetic validation for the pathway. In this study, CsaD catalyzed the decarboxylation of both 3,6-DCSA and 6-CSA, providing enzyme-level evidence for the anaerobic catabolism of 3,6-DCSA through the two pathways. CsaD was located in MAG8, which belonged to an uncultured anaerobic actinomycetes order, OPB41, indicating that anaerobic actinomycetes in OPB41 was involved in the decarboxylation of 3,6-DCSA. This study provides a basis for understanding the anaerobic catabolism of dicamba and the demethylation product, 3,6-DCSA.