Identification Of Metabolites Research Articles

Combining Enhanced Resolving Power with Duty Cycle Improvements on a Multi-Reflecting Time-of-Flight Mass Spectrometer.

The combination of enhanced resolving power and improved duty cycle on a multireflecting time-of-flight mass spectrometer is described. Resolving power increases are achieved by extending the effective ion path length from 47 m to greater than 200 m. Path length increases are achieved through containment of ions within the analyzer for up to N = 5 passes using a pulsed deflection electrode. Resolving power was shown to increase from 220,000 to 402,000 (fwhm) at m/z 785 for N = 1 and N = 4 analyzer passes, respectively. Due to the timing of the pulsed deflection electrode, the approach is particularly suited to high resolution analysis over a targeted m/z range. Duty cycle enhancements are achieved for ions of the targeted m/z range via accumulation prior to orthogonal acceleration, providing signal improvements of 2 orders of magnitude. Achieving such high resolving powers at fast scan rates (30 Hz) can yield additional information such as fine isotope structure; when combined with ppb mass measurement accuracy, high confidence in analyte identification can be achieved. The technique is applied for N = 2 analyzer passes, demonstrating fine isotope structure for a typical UHPLC metabolite identification experiment at a 10 Hz acquisition rate. Additionally, mass spectrometry imaging data is acquired using DESI, demonstrating the improved image clarity achieved at >300,000 (fwhm).

LC-MS based metabolomics identification of natural metabolites against Fusarium oxysporum.

Fusarium is a soil-borne pathogen that poses a serious threat to the quality and yield of hundreds of crops worldwide, particularly tobacco production. Using metabolomics technology, we investigated natural metabolites from disease-conducting soil (DCS) and disease-suppressing soil (DSS) of tobacco rhizosphere as fungicides to control tobacco Fusarium wilt (TFW), which is mainly caused by Fusarium oxysporum. Furthermore, the antifungal mechanisms of these natural metabolites were preliminarily elucidated through various assessments, including antifungal activity determination, chemotaxis effect tests, PI staining experiments, and measurements of extracellular conductivity and protein content. Metabolomics results showed that the DCS with three different disease grades (G1, G5 and G9 groups) had significantly higher levels of 15, 14 and 233 differential rhizosphere metabolites (DRMs) and significantly lower levels of 72, 152 and 170 DRMs compared to the DSS (G0 group). According to KEGG pathway analysis, these DRMs were found to be enriched in the caffeine metabolism, biosynthesis of phenylpropanoids, galactose metabolism and tyrosine metabolism, etc. Linustatin, scopoletin and phenylpropiolic acid were picked out from these DRMs and found to have suppressive activity against F. oxysporum through correlation analysis and antifungal experiments. The three DRMs showed strong inhibitory effects on the growth and spore germination of F. oxysporum at concentrations of 0.5 mM or higher in each test period. Furthermore, F. oxysporum showed a phobotaxis effect against these three DRMs at concentrations as low as 0.25 mM. Finally, we found that the three DRMs had an inhibitory effect on F. oxysporum by destroying the integrity of the cell membrane and increasing the membrane permeability of F. oxysporum. This study firstly reports the inhibition activity of phenylpropiolic acid and linustatin on F. oxysporum, providing a practical and environmentally friendly method for biocontrol of TFW by using natural fungicides.

Comprehensive identification of polyphenolic metabolites in aspen knotwood by combination of 2D NMR and HPLC-HRMS.

European aspen (Populus tremula L.) knotwood contains large amounts of polyphenolic metabolites, mainly flavonoids, and can be considered as a promising industrial-scale source of valuable bioactive compounds. Valorization of knotwood extractives requires detailed information on their chemical composition and a relevant analytical methodology. This study proposes combined analytical strategy for non-targeted screening and identification of polyphenolic plant metabolites and is aimed at comprehensive characterization of knotwood extractives. Aspen knotwood acetone extract with determined antioxidant activity was an object of the study. Two-dimensional NMR spectroscopy with Structure Elucidator expert system was used for preliminary search of major components and specific structures. Liquid chromatography-high-resolution mass spectrometry (HPLC-HRMS) with data-dependent MS/MS spectra acquisition was used as a complementary technique providing molecular-level characterization and identification of the detected metabolites. Twenty-eight phenolic metabolites were found and identified. Among them, flavonoids, aromadendrin and naringenin, as well as their glycosylated derivatives (mainly O-glucosides) and methyl ethers, dominated. Taxifolin and its 7-O-glucoside were detected as minor components. Other detected compounds are represented by p-coumaric acid and its rutinoside and small amounts of glycosylated ferulic acid. Nineteen of the detected compounds were discovered in aspen knotwood for the first time. The results were confirmed by preparative isolation of individual compounds and NMR studies. The proposed analytical strategy based on 2D NMR and HPLC-HRMS can be considered a powerful tool in the analysis of plant extractives and allowed for the identification and semi-quantification of a large number of polyphenols in aspen knotwood.

Exploring Metabolomics to Innovate Management Approaches for Fall Armyworm (Spodoptera frugiperda [J.E. Smith]) Infestation in Maize (Zea mays L.).

The Fall armyworm (FAW), Spodoptera frugiperda (J. E. Smith), is a highly destructive lepidopteran pest known for its extensive feeding on maize (Zea mays L.) and other crops, resulting in a substantial reduction in crop yields. Understanding the metabolic response of maize to FAW infestation is essential for effective pest management and crop protection. Metabolomics, a powerful analytical tool, provides insights into the dynamic changes in maize's metabolic profile in response to FAW infestation. This review synthesizes recent advancements in metabolomics research focused on elucidating maize's metabolic responses to FAW and other lepidopteran pests. It discusses the methodologies used in metabolomics studies and highlights significant findings related to the identification of specific metabolites involved in FAW defense mechanisms. Additionally, it explores the roles of various metabolites, including phytohormones, secondary metabolites, and signaling molecules, in mediating plant-FAW interactions. The review also examines potential applications of metabolomics data in developing innovative strategies for integrated pest management and breeding maize cultivars resistant to FAW by identifying key metabolites and associated metabolic pathways involved in plant-FAW interactions. To ensure global food security and maximize the potential of using metabolomics in enhancing maize resistance to FAW infestation, further research integrating metabolomics with other omics techniques and field studies is necessary.

Chemical Composition, Antioxidant Capacity, and Anticancerous Effects against Human Lung Cancer Cells of a Terpenoid-Rich Fraction of Inula viscosa.

Inula viscosa is a widely used plant in traditional Mediterranean and Middle Eastern medicine for various illnesses. I. viscosa has been shown to have anticancer effects against various cancers, but its effects against lung cancer have been under limited investigation. At the same time, I. viscosa is rich in terpenoids whose anti-lung cancer effects have been poorly investigated. This study aimed to examine the potential anticancer properties of methanolic and aqueous extracts of stems and leaves of I. viscosa and its terpenoid-rich fraction against human lung cancer A549 cells. Results showed that the methanolic extracts of I. viscosa had significantly higher polyphenol and flavonoid content and radical scavenging capacity than the aqueous extracts. In addition, leaves methanolic extracts (IVLM) caused the highest reduction in viability of A549 cells among all the extracts. IVLM also reduced the viability of human ovarian SK-OV-3, breast MCF-7, liver HepG2, and colorectal HCT116 cancer cells. A terpenoid-rich I. viscosa fraction (IVL DCM), prepared by liquid-liquid separation of IVLM in dichloromethane (DCM), displayed a substantial reduction in the viability of A549 cells (IC50 = 27.8 ± 1.5 µg/mL at 48 h) and the panel of tested cancerous cell lines but was not cytotoxic to normal human embryonic fibroblasts (HDFn). The assessment of IVL DCM phytochemical constituents using GC-MS analysis revealed 21 metabolites, highlighting an enrichment in terpenoids, such as lupeol and its derivatives, caryophyllene oxide, betulin, and isopulegol, known to exhibit proapoptotic and antimetastatic functions. IVL DCM also showed robust antioxidant capacity and decent polyphenol and flavonoid contents. Furthermore, Western blotting analysis indicated that IVL DCM reduced proliferation (reduction of proliferation marker Ki67 and induction of proliferation inhibitor proteins P21 and P27), contaminant with P38 MAP kinase activation, and induced the intrinsic apoptotic pathway (P53/BCL2/BAX/Caspase3/PARP) in A549 cells. IVL DCM also reduced the migration of A549 cells, potentially by reducing FAK activation. Future identification of anticancer metabolites of IVL DCM, especially terpenoids, is recommended. These data place I. viscosa as a new resource of herbal anticancer agents.

Causality of Genetically Determined Metabolites on Chronic Kidney Disease: A Two-Sample Mendelian Randomization Study In Silico.

Introduction: Chronic kidney disease (CKD) is associated with metabolic disorders. However, the evidence for the causality of circulating metabolites to promote or prevent CKD is still lacking. Methods: The two-sample Mendelian randomization (MR) analysis was conducted to evaluate the latent causal relationship between the genetically proxied 486 blood metabolites and CKD. Genome-wide association study (GWAS) data for exposures were derived from 7824 European GWAS on metabolite levels, which have been extensively utilized in the medical field to elucidate the mechanisms underlying disease onset and progression. The random inverse variance weighted (IVW) is the primary analysis for causality analysis while MR-Egger and weighted median as complementary analyses. For the further identification of metabolites, reverse MR and linkage disequilibrium score regression were performed for further evaluation. The drug target for N-acetylornithine was subsequently supplemented into the analysis, with MR and colocalization analysis being utilized. Key metabolic pathways were identified via MetaboAnalyst 4.0 (https://www.metaboanalyst.ca/) online website. Results: N-acetylornithine was identified as a reliable metabolite that increases the susceptibility to estimated glomerular filtration rate (eGFR) decrease (β = 0.047; 95% confidence interval: -0.068 to -0.026; PIVW = 1.5E-5). The "glyoxylate and dicarboxylate metabolism" pathway showed significant relevance to CKD development (P = 6E-4), whereas the "glycine, serine, and threonine metabolism" pathway was also recognized as associated with CKD by general practitioners (P = 7E-4). Colocalization analysis revealed a robust genetic link between N-acetylornithine and both CKD and eGFR, with 85.1% and 99.4% colocalization rates, respectively. IVW-MR analysis substantiated these findings with a significant positive association for CKD (odds ratio = 1.43, P = 4.7E-5) and a negative correlation with eGFR (b = -0.04, P = 1.13E-31). Conclusions: MR was utilized to explore the potential causal links between 61 genetic serum metabolites and CKD. N-acetylornithine and NAT8 were further explored as a potential therapeutic target for CKD treatment.

A pilot pharmacokinetic and Metabolite identification study of Erinacine A in a Single landrace pig model

Erinacine A has been proven to have the ability to protect nerves and have the benefit of neurohealth. However, the pharmacokinetic and metabolites study of erinacine A in pigs, whose physiology and anatomy are similar to humans, have not been reported. In this study, 5 mg/kg of erinacine A was intravenously administered to the landrace pig. Blood, cerebrospinal fluid, and brain tissue samples were collected and analyzed by HPLC-QQQ/MS and UPLC-QTOF/MS. The results indicated the following pharmacokinetic parameters in plasma samples: with an area under the plasma concentration versus time curve (AUC) were 38.02 ± 0.03 mg∙min/L (AUC0-60) and 43.60 ± 0.06 mg∙min/L (AUC0-∞), clearance (CL) was 0.11 ± 0.00 L/min∙kg, volume of distribution (Vd) was 4.24 ± 0.00 L/kg, and terminal half-life (T1/2β) was 20.85 ± 0.03 min. In the cerebrospinal fluid samples, erinacine A was detected after 15 min and the highest concentration (5.26 ± 0.58 μg/L) was observed at 30 min. In the brain tissue sample, 77.45 ± 0.58 μg/L of erinacine A was found. In the study of metabolites, there were 6 identical metabolites in plasma and brain tissue. To our surprise, erinacine B was found to be the metabolite of erinacine A, and its concentration increased over time as erinacine A was metabolized. In summary, this study is the first to demonstrate that erinacine A can be found in the cerebrospinal fluid of landrace pigs. Additionally, the metabolite identification of erinacine A in landrace pigs is also investigated.

Development of a determination method for quality control markers utilizing metabolic profiling and its application on processed Zingiber officinale Roscoe rhizome.

This study established an Orthogonal Partial Least Squares (OPLS) model combining 1H-NMR and GC-MS data to identify characteristic metabolites in complex extracts. Both in metabolomics studies, and natural product chemistry, the reliable identification of marker metabolites usually requires laborious isolation and purification steps, which remains a bottleneck in many studies. Both ginger (GR) and processed ginger (PGR) are listed in the Japanese pharmacopeia. The plant of origin, the rhizome of Zingiber officinale Roscoe, is differently processed for these crude drugs. Notably, the quality of crude drugs is affected by genetic and environmental factors, making it difficult to maintain a certain quality standard. Therefore, characteristic markers for the quality control of GR and PGR are required. Metabolomic analysis using 1H-NMR was able to discriminate between GR and PGR, but there were unidentified signals that were difficult to distinguish based on NMR data alone. Therefore, we combined 1H-NMR and GC-MS analytical data to identify them by OPLS. As a result, αr-curcumene was found to be a useful marker for these identifications. This new approach enabled rapid identification of characteristic marker compounds and reduced the labor involved in the isolation process.

The prognosis and metabolite changes of NSCLC patients receiving first-line immunotherapy combined chemotherapy in different M1c categories according to 9th edition of TNM classification.

The 9th edition of the TNM Classification for lung cancer delineates M1c into two subcategories: M1c1 (Multiple extrathoracic lesions within a single organ system) and M1c2 (Multiple extrathoracic lesions involving multiple organ systems). Existing research indicates that patients with lung cancer in stage M1c1 exhibit superior overall survival compared to those in stage M1c2. The primary frontline therapy for patients with advanced non-small cell lung cancer (NSCLC), lacking driver gene mutations, involves the use of immune checkpoint inhibitors (ICIs) combined with chemotherapy. Nevertheless, a dearth of evidence exists regarding potential survival disparities between NSCLC patients with M1c1 and M1c2 undergoing first-line immune-chemotherapy, and reliable biomarkers for predicting treatment outcomes are elusive. Serum metabolic profiles may elucidate distinct prognostic mechanisms, necessitating the identification of divergent metabolites in M1c1 and M1c2 undergoing combination therapy. This study seeks to scrutinize survival discrepancies between various metastatic patterns (M1c1 and M1c2) and pinpoint metabolites associated with treatment outcomes in NSCLC patients undergoing first-line ICIs combined with chemotherapy. In this study, 33 NSCLC patients lacking driver gene mutations diagnosed with M1c1, and 22 similarly diagnosed with M1c2 according to the 9th edition of TNM Classification, were enrolled. These patients received first-line PD-1 inhibitor plus chemotherapy. The relationship between metastatic patterns and progression-free survival (PFS) in patients undergoing combination therapy was analyzed using univariate and multivariate Cox regression models. Serum samples were obtained from all patients before treatment initiation for untargeted metabolomics analysis, aiming to identify differential metabolites. In the univariate analysis of PFS, NSCLC patients in M1c1 receiving first-line PD-1 inhibitor plus chemotherapy exhibited an extended PFS (HR = 0.49, 95% CI, 0.27-0.88, p = 0.017). In multivariate PFS analyses, these M1c1 patients receiving first-line PD-1 inhibitor plus chemotherapy also demonstrated prolonged PFS (HR = 0.45, 95% CI, 0.22-0.92, p = 0.028). The serum metabolic profiles of M1c1 and M1c2 undergoing first-line PD-1 inhibitors plus chemotherapy displayed notable distinctions. In comparison to M1c1 patients, M1c2 patients exhibited alterations in various pathways pretreatment, including platelet activation, linoleic acid metabolism, and the VEGF signaling pathway. Diminished levels of lipid-associated metabolites (diacylglycerol, sphingomyelin) were correlated with adverse outcomes. NSCLC patients in M1c1, devoid of driver gene mutations, receiving first-line PD-1 inhibitors combined with chemotherapy, experienced superior outcomes compared to M1c2 patients. Moreover, metabolomic profiles strongly correlated with the prognosis of these patients, and M1c2 patients with unfavorable outcomes manifested distinct changes in metabolic pathways before treatment. These changes predominantly involved alterations in lipid metabolism, such as decreased diacylglycerol and sphingomyelin, which may impact tumor migration and invasion.

Metabolomics in Pakistan: A Comprehensive Analysis of Availability, Practices, and Challenges in Clinical Laboratories.

To comprehensively analyse the current state of metabolomics in clinical laboratories across Pakistan. Cross-sectional survey. Place and Duration of the Study: Section of Chemical Pathology, Department of Pathology and Laboratory Medicine, The Aga Khan University, Karachi, Pakistan, from June to November 2022. This survey assessed metabolomics availability, computational methods, and resources in Pakistani clinical laboratories. The survey questionnaire was distributed within the chemical pathology community via Google Forms, and responses were garnered from 44 chemical pathologists across 17 laboratories in 10 cities. Among respondents, 11 had formal metabolomics training, with three having less than 1 year, five more than 1 year, and 33 lacking any experience. Primary clinical applications included inherited metabolic disorders, bio-informatics, microbiology, therapeutic drug monitoring, toxicology, and nutritional and environmental science. Thirty-three labs reported no omics-related technology; LC-MS and GC-MS were present in eight labs and capillary spectroscopy, direct infusion mass spectroscopy, and Fourier transform infrared-spectroscopy were predominantly used for metabolite identification. Challenges identified in implementing metabolomics included lack of awareness, limited expertise, low volume, restricted applicability, high instrument costs, and insufficient funding. Metabolomics in Pakistan faces limitations, but the chemical pathology community expresses strong interest, emphasising the need for intensified efforts in education and training in this emerging field. Metabolomics, Chemical pathology, Pakistan, Clinical laboratories, Genetics, Survey.

Identification and characterization of transition metal-binding proteins and metabolites in the phloem sap of Brassica napus

Transition metal (TM) distribution through the phloem is an essential part of plant metabolism and is required for systemic signaling and balancing source-to-sink relationships. Due to their reactivity, TMs are expected to occur in complexes within the phloem sap; however, metal speciation in the phloem sap remains largely unexplored. Here, we isolated phloem sap from Brassica napus and analyzed it via size exclusion chromatography (SEC) coupled online to sector-field ICP-MS. Our data identified known TM binding proteins and molecules including metallothioneins (MT), glutathione, and nicotianamine. While the main peak of all metals was low MW (∼1.5 kD), additional peaks ∼10-15 kD containing Cu, Fe, S and Zn were also found. Further physicochemical analyses of MTs with and without affinity tags corroborated that MTs can form complexes of diverse molecular weights. We also identified and characterized potential artifacts in the TM-biding ability of B. napus MTs between tagged and non-tagged MTs. That is, the native BnMT2 binds Zn, Cu and Fe, while MT3a and MT3b only bind Cu and Zn. In contrast, his-tagged MTs bind less Cu and were found to bind Co and Mn and aggregated to oligomeric forms to a greater extent compared to the phloem sap. Our data indicates that TM chemistry in the phloem sap is more complex than previously anticipated and that more systematic analyses are needed to establish the precise speciation of TM and TM-ligand complexes within the phloem sap.

Application of a molecular networking approach using LC-HRMS combined with the MetWork webserver for clinical and forensic toxicology

Backgrounds and aimsIn toxicology, LC-HRMS for untargeted screening yields a great deal of high quality spectral data. However, there we lack tools to visualize/organize the MS data. We applied molecular networking (MN) to untargeted screening interpretation. Our aims were to compare theoretical MS libraries obtained in silico with our experimental dataset in patients to broaden its application, and to use the MetWork web application for metabolite identification. MethodsSamples were analyzed using an LC-HRMS system. For MN, data was generated using MZmine, and analyzed and visualized using MetGem. MetWork annotations were filtered and this file was used for annotation of the previously obtained MN. Results155 compounds including drugs found in patients were recorded. Using this dataset, we confirmed in 60 patients intake of tramadol, amitriptyline bromazepam, and cocaine. The results obtained by the reference methods were confirmed by MN approaches. Eighty percent of the compounds were common to both conventional and MN approaches. Using MetWork, metabolites and parent drugs such as amitriptyline, its metabolite nortriptyline and amitriptyline glucuronide phase 2 metabolites were anticipated and proposed as putative annotations. ConclusionThe workflow increases confidence in toxicological screening by highlighting putative structures in biological matrices in combination with CFM-ID (Competitive Fragmentation Modeling for Metabolite Identification) and MetWork to extend the annotation of potential drugs even without a reference standard.

Phytochemical Analysis and Evaluation of the Antioxidant, Anti-Inflammatory, Hemolytic, and Antibacterial Effects of Astragalus gombo (L.) Leaves.

The purpose of this study is to determine the phytochemical content and biological activities of the Astragalus gombo (endemic specie). While identification and quantification of individual secondary metabolites were performed by analysis HPLC. Antioxidant (DPPH and FRAP), anti-inflammatory, anti-hemolytic and antibacterial activities were evaluated. For analysis HPLC, we obtained 65 peaks and identified 6 major bioactive compounds. The total concentration in polyphenols, flavonoids and condensed tannins varied respectively from 66.306±0.88 mg GA eq/g, 34.312±1.4 mg Q eq/g and 5.343±2.74 mg Ca eq/g. In terms of antioxidant activity, we found that this extract had high inhibitory ratios equivalent to IC50=62.813±0.006 µg/mL for DPPH and IC50=19.375±0.041 µg/mL for FRAP. A high anti-inflammatory activity was estimated at 1615.81µg/mL, and a weak anti-hemolytic activity, the other hand the antibacterial activity is somewhat moderate against the five strains studied. This study demonstrated that the aqueous extract of A. gombo from El Oued region has tremendous antioxidant, anti-inflammatory and antibacterial abilities.

Identification of candidate exposure biomarkers for acetyl tributyl citrate and acetyl triethyl citrate using suspect screening in human liver microsomes

Acetyl tributyl citrate (ATBC) and acetyl triethyl citrate (ATEC) are increasingly used as alternatives to phthalates in various products, including food packaging, medical devices, and personal care items, raising concerns about their potential health impacts. This study aimed to investigate the in vitro human metabolism of ATBC and ATEC and identify potential exposure biomarkers applicable in human biomonitoring. Pooled human liver microsomes were utilized to conduct in vitro metabolism assays of deuterium labeled ATBC (ATBC-d3) and ATEC, and ultra performance liquid chromatography coupled to quadrupole-time-of-flight mass spectrometry (UPLC-qToF/MS) was employed for analysis. Suspect screening workflow and confidence level assignment were applied for metabolite identification. Time-course analysis revealed rapid metabolism of both compounds, with estimated apparent half-lives of approximately 5 min for ATBC-d3 and less than 15 min for ATEC. Eleven metabolites were identified for ATBC-d3 and six for ATEC. The predominant chemical reactions observed were carboxylic ester hydrolysis, deacetylation, and hydroxylation. Based on their abundance and specificity, MB1 (hydroxylated) and MB11 (hydrolyzed and hydroxylated) were proposed as candidate exposure biomarkers for ATBC, and ME1 (hydrolyzed and deacetylated) for ATEC. The identified metabolites and proposed sequences of kinetic process enhance our understanding of the fate of these compounds in the human body, potentially informing future toxicological assessments and guiding the development of more comprehensive human biomonitoring strategies.

Potential of high-resolution mass spectrometry for identification and structural elucidation of scopolamine metabolomic biomarkers in a confirmed case of Brugmansia intoxication. Specially application in drug-facilitated crimes

In forensic toxicology, scopolamine remains as one of the most challenging alkaloid in terms of analytical detection. Given its rapid elimination, the detection window in common matrices is short. Taking advantage of a real case of Brugmansia intoxication, a metabolic study was carried out. We report the real case of a 16-year-old boy admitted to an Emergency Unit after consumption at high school of a beverage made of Brugmansia dried flowers. The medical staff noticed agitation, mydriasis and tachycardia. Scopolamine and atropine were positively detected in biological fluids using liquid chromatography coupled with high-resolution mass spectrometry (UHPLC-HRMS/MS). To better characterize the intake and identify metabolic biomarkers, we developed a data mining workflow specific to tropane alkaloids and applied it to the urine sample. This metabolic profile may be useful in providing analytical methods with a wider detection window particularly in drug-facilitated crimes (DFC). Scopolamine and atropine metabolites were predicted in silico with GLORYx freeware to assist in metabolite identification. The previously published metabolic pathways for scopolamine and atropine in mammals were studied as well. A total of fifteen phase I and II metabolites were tentatively identified for scopolamine, while one metabolite was detected for atropine. In addition, we identified some tropane alkaloids from the plant that were also metabolized. These metabolites can be used as biomarkers of exposure to Solanaceae plants and may also be useful to distinguish between natural product use and clinical therapy.

Identification of serum metabolites associated with polybrominated diphenyl ethers (PBDEs) exposure in papillary thyroid carcinoma: a case–control study

As the most common endocrine cancer, thyroid cancer (TC) has sharply increased globally over the past three decades. The growing incidence of TC might be counted by genetics, radiation, iodine, autoimmune disease, and exposure to environmental endocrine–disrupting chemicals (EDCs). Polybrominated diphenyl ethers (PBDEs), being typical EDCs, have been widely utilized in plastics, electronics, furniture, and textiles as flame retardants since the 1980s, and research has indicated a significant correlation between their exposure and the risk of TC. Even so, PBDEs exposure impact on the metabolic signature for TC remains unexplored. In this study, eight congeners of PBDEs were determined in serum from 111 patents with papillary thyroid cancer (PTC) and 111 healthy participants based on case–control epidemiology using gas chromatography–atmospheric pressure chemical ionization–tandem mass spectrometry (GC-APCI–MS/MS). Based on the tertile distribution of total PBDEs concentrations in 59 participants, metabolomics analysis was further performed by ultra-high performance liquid chromatography coupled to hybrid quadrupole–Orbitrap MS. In the partial correlation analysis, the 29 identified metabolites were correlated with PBDEs exposure (P < 0.05). In addition, PBDEs disrupted the metabolism of glycerophospholipids, sphingolipids, taurine, and hypotaurine, indicating that neurotransmitters, oxidative stress, and inflammation are the vulnerable pathways affected in PTC. Furthermore, (±)-octopamine and 5-hydroxyindole, both of which modulate the actions of neurotransmitters, emerged as potential disturbed metabolite markers for TC following exposure to PBDEs. This study analyzed the impact of PBDEs on PTC in terms of the metabolic changes and further explored possible biomarkers, which helped us have a deep understanding of the possible mechanism of the effects of PBDEs on TC.

Advancing structural elucidation of conjugation drug metabolites in metabolite profiling with novel electron-activated dissociation.

This study focuses on the advantage of using the novel electron-activated dissociation (EAD) technology on the QTOF system for structural elucidation of conjugation metabolites. In drug metabolite identification, conceptual "boxes" are generally used to represent potential sites of modifications, which are proposed based on MS/MS data. Electron-activated dissociation (EAD) provides unique fragmentation patterns, potentially allowing for more precise localization of the metabolic modification sites compared to CID, particularly for conjugations. Known compounds were incubated with rat liver microsomes in the presence of nicotinamide adenine dinucleotide phosphate (NADPH), uridine dihosphate-glucuronic acid (UDPGA), and glutathione. Conjugation metabolites were analyzed using the QTOF system. High-resolution MS/MS spectra were collected using EAD and CID fragmentations along with TOF MS full scan for tested drugs and metabolites. Fragmentation patterns were compared to evaluate their efficiency in structural elucidation. Metabolite profiling identified conjugation metabolites (glucuronides and GSH adducts), using characteristic mass shifts. A comparison of EAD and CID fragmentation revealed EAD-specific fragments for most conjugates. EAD was able to break the relatively stable bonds on parent drug motifs while keeping relatively weak conjugation bonds intact, despite the generally low intensity of EAD. EAD effectively narrowed the conceptual "box" representing modification sites, providing more definitive information on conjugation sites and facilitating the structural elucidation of conjugated metabolites. EAD is a powerful tool for metabolite profiling in drug development, particularly for identifying conjugation sites. EAD-enabled MS/MS spectra offer a greater variety of signature fragments compared to CID, resulting in more comprehensive and unique structural information for metabolic modification analysis. Overall, EAD, complementary to CID, has the potential to narrow down potential modification sites, significantly enhancing the precision of conjugation metabolite structure elucidation.

The Potential of Deleterious rhizobacteria to Control Primary Weed &lt;i&gt;Echinochloa &lt;/i&gt;sp. on Rice

Deleterious rhizobacteria (DRB) is one of the rhizobacteria that can be used as a bioherbicide and can stimulate plant growth. The objectives that can be obtained from this study are to determine the potential of DRB on the growth of weeds Echinochloa crusgalli and Echinochloa colona on rice. Variables observed in this study were identification of secondary metabolites, measurement of weed sprouts, percentage effectiveness of bacterial isolates against weed seeds, normal sprouts, abnormal sprouts, fresh seeds that did not grow and dead seeds. The aim of this study is to explore biological agents that can be used to control the main weeds of rice crops. This candidate could be a recommendation for environmentally friendly controls. Exploration of the DRB group was obtained by collecting soil samples around the roots of rice crops. Then isolate it, identify as morphologically and physiologically, and test it in vitro studies. The results showed that DRB had the potential to control weed growth and could stimulate the growth of rice. The application of PFA and PFB isolates had a significant effect on inhibiting the length of weed roots and buds, the average percentage of control effectiveness &gt; 80-90%. Novelty in this study could be found as candidate groups of DRB bacteria with specific locations to control the weed Echinochloa sp. on rice crops. For society, this research could be an alternative to reduce dependence on synthetic herbicides . DRB has the potential to be formulated into a bioherbicide to control weeds.

Genome Mining and Genetic Manipulation Reveal New Isofuranonaphthoquinones in Nocardia Species.

The identification of specialized metabolites isolated from microorganisms is urgently needed to determine their roles in treating cancer and controlling multidrug-resistant pathogens. Naphthoquinones act as anticancer agents in various types of cancers, but some toxicity indicators have been limited in their appropriate application. In this context, new isofuranonaphthoquinones (ifnq) that are less toxic to humans could be promising lead compounds for developing anticancer drugs. The aim of this study is to identify and characterize novel furanonaphthoquinones (fnqs) from Nocardia sp. CS682 and to evaluate their potential therapeutic applications. Analysis of the genome of Nocardia sp. CS682 revealed the presence of a furanonaphthoquinone (fnq) gene cluster, which displays a similar genetic organization and high nucleotide sequence identity to the ifnq gene cluster from Streptomyces sp. RI-77, a producer of the naphthoquinones JBIR-76 and JBIR-77. In this study, the overexpression of the Streptomyces antibiotic regulatory protein (SARP) in Nocardia sp. CS682DR (nargenicin gene-deleted mutant) explicitly produced new fnqs, namely, NOC-IBR1 and NOC-IBR2. Subsequently, the role of the SARP regulator was confirmed by gene inactivation using CRISPR-Cas9 and complementation studies. Furthermore, antioxidant, antimicrobial, and cytotoxicity assays were performed for the isolated compounds, and it was found that NOC-IBR2 exhibited superior activities to NOC-IBR1. In addition, a flexible methyltransferase substrate, ThnM3, was found to be involved in terminal methylation of NOC-IBR1, which was confirmed by in vitro enzyme assays. Thus, this study supports the importance of genome mining and genome editing approaches for exploring new specialized metabolites in a rare actinomycete called Nocardia.

An isotopically-labelled temporal mass spectrometry imaging data analysis workflow to reveal glucose spatial metabolism patterns in bovine lens tissue

Application of stable isotopically labelled (SIL) molecules in Matrix-Assisted Laser Desorption/Ionization Mass Spectrometry Imaging (MALDI-MSI) over a series of time points allows the temporal and spatial dynamics of biochemical reactions to be tracked in a biological system. However, these large kinetic MSI datasets and the inherent variability of biological replicates presents significant challenges to the rapid analysis of the data. In addition, manual annotation of downstream SIL metabolites involves human input to carefully analyse the data based on prior knowledge and personal expertise. To overcome these challenges to the analysis of spatiotemporal MALDI-MSI data and improve the efficiency of SIL metabolite identification, a bioinformatics pipeline has been developed and demonstrated by analysing normal bovine lens glucose metabolism as a model system. The pipeline consists of spatial alignment to mitigate the impact of sample variability and ensure spatial comparability of the temporal data, dimensionality reduction to rapidly map regional metabolic distinctions within the tissue, and metabolite annotation coupled with pathway enrichment modules to summarise and display the metabolic pathways induced by the treatment. This pipeline will be valuable for the spatial metabolomics community to analyse kinetic MALDI-MSI datasets, enabling rapid characterisation of spatio-temporal metabolic patterns from tissues of interest.