PubMed

Related Articles Transcriptomic and metabolomic analysis of ZmYUC1 mutant reveals the role of auxin during early endosperm formation in maize. Plant Sci. 2019 Apr;281:133-145 Authors: Bernardi J, Battaglia R, Bagnaresi P, Lucini L, Marocco A Abstract Kernel size in cereal is an important agronomic trait controlled by the interaction of genetic and environmental factors. The endosperm occupies most of the kernel area; for this reason, the endosperm cells dimension, number and metabolic content strongly influence kernel properties. This paper presents the transcriptomic and metabolomic analysis of the maize defective endosperm 18 (de18) mutant, where auxin accumulation in the endosperm is impaired. This mutation, involving the ZmYuc1 gene, leads to a reduced kernel size compared to the wild-type line B37. Our results mainly indicate that IAA concentration controls sugar and protein metabolism during kernel differentiation and it is necessary for BETL formation. Furthermore, a fine tuning of different auxin conjugates is reported as the main mechanism to counteract the auxin deficit. Some candidates as master regulators of endosperm transcriptional regulation mediated by auxin are found between MYB and MADS-box gene families. A link between auxin and storage protein accumulation is highlighted, suggesting that IAA directly or indirectly, through CK or ABA, regulates the transcription of zein coding genes. This study represents a move forward with respect to the current knowledge about the role of auxin during maize endosperm differentiation thus revealing the genes that are modulated by auxin and that control agronomic traits as kernel size and metabolic composition. PMID: 30824046 [PubMed - in process]

Related Articles Metabolomics analysis of a mouse model for chronic exposure to ambient PM2.5. Environ Pollut. 2019 Apr;247:953-963 Authors: Xu Y, Wang W, Zhou J, Chen M, Huang X, Zhu Y, Xie X, Li W, Zhang Y, Kan H, Ying Z Abstract Chronic ambient fine particulate matter (PM2.5) exposure correlates with various adverse health outcomes. Its impact on the circulating metabolome-a comprehensive functional readout of the interaction between an organism's genome and environment-has not however been fully understood. This study thus performed metabolomics analyses using a chronic PM2.5 exposure mouse model. C57Bl/6J mice (female) were subjected to inhalational concentrated ambient PM2.5 (CAP) or filtered air (FA) exposure for 10 months. Their sera were then analyzed by liquid chromatography-mass spectrometry (LC-MS) and gas chromatography-mass spectrometry (GC-MS). These analyses identified 2570 metabolites in total, and 148 of them were significantly different between FA- and CAP-exposed mice. The orthogonal partial least-squares discriminant analysis (OPLS-DA) and heatmap analyses displayed evident clustering of FA- and CAP-exposed samples. Pathway analyses identified 6 perturbed metabolic pathways related to amino acid metabolism. In contrast, biological characterization revealed that 71 differential metabolites were related to lipid metabolism. Furthermore, our results showed that CAP exposure increased stress hormone metabolites, 18-oxocortisol and 5a-tetrahydrocortisol, and altered the levels of circadian rhythm biomarkers including melatonin, retinal and 5-methoxytryptophol. PMID: 30823350 [PubMed - in process]

Adropin treatment restores cardiac glucose oxidation in pre-diabetic obese mice. J Mol Cell Cardiol. 2019 Feb 26;: Authors: Thapa D, Xie B, Zhang M, Stoner MW, Manning JR, Huckestein BR, Edmunds LR, Mullett SJ, McTiernan CF, Wendell SG, Jurczak MJ, Scott I Abstract Exposure to a high fat (HF) diet promotes increased fatty acid uptake, fatty acid oxidation and lipid accumulation in the heart. These maladaptive changes impact cellular energy metabolism and may promote the development of cardiac dysfunction. Attempts to increase cardiac glucose utilization have been proposed as a way to reverse cardiomyopathy in obese and diabetic individuals. Adropin is a nutrient-regulated metabolic hormone shown to promote glucose oxidation over fatty acid oxidation in skeletal muscle homogenates in vitro. The focus of the current study was to investigate whether adropin can regulate substrate metabolism in the heart following prolonged exposure to a HF diet in vivo. Mice on a long-term HF diet received serial intraperitoneal injections of vehicle or adropin over three days. Cardiac glucose oxidation was significantly reduced in HF animals, which was rescued by acute adropin treatment. Significant decreases in cardiac pyruvate dehydrogenase activity were observed in HF animals, which were also reversed by adropin treatment. In contrast to previous studies, this change was unrelated to Pdk4 expression, which remained elevated in both vehicle- and adropin-treated HF mice. Instead, we show that adropin modulated the expression of the mitochondrial acetyltransferase enzyme GCN5L1, which altered the acetylation status and activity of fuel metabolism enzymes to favor glucose utilization. Our findings indicate that adropin exposure leads to increased cardiac glucose oxidation under HF conditions, and may provide a future therapeutic avenue in the treatment of diabetic cardiomyopathy. PMID: 30822408 [PubMed - as supplied by publisher]

Assessment of NAD+metabolism in human cell cultures, erythrocytes, cerebrospinal fluid and primate skeletal muscle. Anal Biochem. 2019 Feb 26;: Authors: Demarest TG, Truong GTD, Lovett J, Mohanty JG, Mattison JA, Mattson MP, Ferrucci L, Bohr VA, Moaddel R Abstract The reduction-oxidation state of NAD+/NADH is critical for cellular health with NAD+ and its metabolites playing critical roles in aging and pathologies. Given the inherent autooxidation of reduced dinucleotides (i.e. NADH/NADPH), and the well-established differential stability, the accurate measurement of NAD+ and its metabolites is technically challenging. Moreover, sample processing, normalization and measurement strategies can profoundly alter results. Here we developed a rapid and sensitive liquid chromatography mass spectrometry-based method to quantify the NAD+ metabolome with careful consideration of these intrinsic chemical instabilities. Utilizing this method we assess NAD+ metabolite stabilities and determine the presence and concentrations of NAD+ metabolites in clinically relevant human samples including cerebrospinal fluid, erythrocytes, and primate skeletal muscle. PMID: 30822397 [PubMed - as supplied by publisher]

Serum metabolomics analysis of the effect of exercise on nonalcoholic fatty liver disease. Endocr Connect. 2019 Mar 01;: Authors: Li J, Zhao Y, Huang C, Chen Z, Shi X, Li L, Chen Z, Li X Abstract OBJECTIVE: Exercise benefits people with nonalcoholic fatty liver disease (NAFLD). The aim of this study was to identify a panel of biomarkers and to provide the possible mechanism for the effect of exercise on NAFLD patients via an untargeted mass spectrometry-based serum metabolomics study. METHODS: NAFLD patients were classified randomly into a control group (n=74) and a 6-month vigorous exercise (n=68) group. Differences in serum metabolic profiles were analyzed using untargeted ultra-performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry (UPLC-Q-TOF/MS) technology. Principal component analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS-DA) were used to validate differences between these two groups, and altered metabolites were obtained by ANOVA (fold change<2, P<0.05) and identified with the online database Metlin and an in-house database. RESULTS: Metabolic profiling and multiple statistical analyses of the serum samples indicated significant differences between the NAFLD patients in the control and the 6-month vigorous exercise groups. Finally, 36 metabolites were identified between the control vs exercise groups. These metabolites were mainly associated with glycerophospholipid- and sphingolipid-related pathways. CONCLUSION: Our study demonstrates that glycerophospholipid and sphingolipid alterations may contribute to the mechanism underlying the effect of exercise on NAFLD patients. A LC-MS-based metabolomics approach has potential value for screening exercise-induced biomarkers. PMID: 30822271 [PubMed - as supplied by publisher]

Related Articles Impact of primary carbon sources on microbiome shaping and biotransformation of pharmaceuticals and personal care products. Biodegradation. 2019 Feb 28;: Authors: Rossmassler K, Kim S, Broeckling CD, Galloway S, Prenni J, De Long SK Abstract Knowledge of the conditions that promote the growth and activity of pharmaceutical and personal care product (PPCP)-degrading microorganisms within mixed microbial systems are needed to shape microbiomes in biotreatment reactors and manage process performance. Available carbon sources influence microbial community structure, and specific carbon sources could potentially be added to end-of-treatment train biotreatment systems (e.g., soil aquifer treatment [SAT]) to select for the growth and activity of a range of microbial phylotypes that collectively degrade target PPCPs. Herein, the impacts of primary carbon sources on PPCP biodegradation and microbial community structure were explored to identify promising carbon sources for PPCP biotreatment application. Six types of primary carbon sources were investigated: casamino acids, two humic acid and peptone mixtures (high and low amounts of humic acid), molasses, an organic acids mixture, and phenol. Biodegradation was tracked for five PPCPs (diclofenac, 5-fluorouracil, gemfibrozil, ibuprofen, and triclosan). Primary carbon sources were found to differentially impact microbial community structures and rates and efficiencies of PPCP biotransformation. Of the primary carbon sources tested, casamino acids, organic acids, and phenol showed the fastest biotransformation; however, on a biomass-normalized basis, both humic acid-peptone mixtures showed comparable or superior biotransformation. By comparing microbial communities for the different primary carbon sources, abundances of unclassified Beijerinckiaceae, Beijerinckia, Sphingomonas, unclassified Sphingomonadaceae, Flavobacterium, unclassified Rhizobiales, and Nevskia were statistically linked with biotransformation of specific PPCPs. PMID: 30820709 [PubMed - as supplied by publisher]

Related Articles Identification of potential human urinary biomarkers for tomato juice intake by mass spectrometry-based metabolomics. Eur J Nutr. 2019 Feb 28;: Authors: Hövelmann Y, Jagels A, Schmid R, Hübner F, Humpf HU Abstract PURPOSE: Dietary biomarkers allow the accurate and objective determination of the dietary intake of humans and can thus be valuable for investigating the relation between consumption of foods and biochemical as well as physiological responses. The objective of this study was the identification of potential urinary biomarkers for consumption of tomato juice. METHODS: In the course of a dietary intervention study, the human urine metabolome of a study cohort was compared between a tomato-free diet and after intake of tomato juice by application of an LC-HRMS-based metabolomics approach. The data acquisition was achieved using an orbitrap mass spectrometer, followed by multistage data processing and univariate as well as multivariate statistical analysis to identify discriminating features. RESULTS: Statistical analysis revealed several unique features detectable after tomato juice intake. The most discriminating markers were putatively identified as hydroxylated and sulfonated metabolites of esculeogenin B, aglycone of the steroidal glycoalkaloid esculeoside B recently found in tomato juice. Furthermore, the β-carboline alkaloids tangutorid E and F and glucuronidated derivatives thereof were identified in urine. CONCLUSIONS: Steroidal glycoalkaloids in tomato juice are cleaved after ingestion, and hydroxylated and sulfonated metabolites of their aglycones might serve as urinary biomarkers for tomato juice intake. Similarly, β-carboline alkaloids and glucuronidated derivatives were identified as potential urinary biomarkers. Both the aglycones of the steroidal alkaloids and the β-carboline alkaloids might exhibit biological activities worth investigating. PMID: 30820652 [PubMed - as supplied by publisher]

Related Articles Metabolic characteristics revealing cell differentiation of nasopharyngeal carcinoma by combining NMR spectroscopy with Raman spectroscopy. Cancer Cell Int. 2019;19:37 Authors: Chen Y, Chen Z, Su Y, Lin D, Chen M, Feng S, Zou C Abstract Background: The staging system of nasopharyngeal carcinoma (NPC) has close relationship with the degree of cell differentiation, but most NPC patients remain undiagnosed until advanced phases. Novel metabolic markers need to be characterized to support diagnose at an early stage. Methods: Metabolic characteristics of nasopharyngeal normal cell NP69 and two types of NPC cells, including CNE1 and CNE2 associated with high and low differentiation degrees were studied by combining 1H NMR spectroscopy with Raman spectroscopy. Statistical methods were also utilized to determine potential characteristic metabolites for monitoring differentiation progression. Results: Metabolic profiles of NPC cells were significantly different according to differentiation degrees. Various characteristic metabolites responsible for different differentiated NPC cells were identified, and then disordered metabolic pathways were combed according to these metabolites. We found disordered pathways mainly included amino acids metabolisms like essential amino acids metabolisms, as well as altered lipid metabolism and TCA cycle, and abnormal energy metabolism. Thus our results provide evidence about close relationship between differentiation degrees of NPC cells and the levels of intracellular metabolites. Moreover, Raman spectrum analysis also provided complementary and confirmatory information about intracellular components in single living cells. Eight pathways were verified to that in NMR analysis, including amino acids metabolisms, inositol phosphate metabolism, and purine metabolism. Conclusions: Methodology of NMR-based metabolomics combining with Raman spectroscopy could be powerful and straightforward to reveal cell differentiation development and meanwhile lay the basis for experimental and clinical practice to monitor disease progression and therapeutic evaluation. PMID: 30820190 [PubMed]

Related Articles compMS2Miner: An Automatable Metabolite Identification, Visualization, and Data-Sharing R Package for High-Resolution LC-MS Data Sets. Anal Chem. 2017 04 04;89(7):3919-3928 Authors: Edmands WM, Petrick L, Barupal DK, Scalbert A, Wilson MJ, Wickliffe JK, Rappaport SM Abstract A long-standing challenge of untargeted metabolomic profiling by ultrahigh-performance liquid chromatography-high-resolution mass spectrometry (UHPLC-HRMS) is efficient transition from unknown mass spectral features to confident metabolite annotations. The compMS2Miner (Comprehensive MS2 Miner) package was developed in the R language to facilitate rapid, comprehensive feature annotation using a peak-picker-output and MS2 data files as inputs. The number of MS2 spectra that can be collected during a metabolomic profiling experiment far outweigh the amount of time required for pain-staking manual interpretation; therefore, a degree of software workflow autonomy is required for broad-scale metabolite annotation. CompMS2Miner integrates many useful tools in a single workflow for metabolite annotation and also provides a means to overview the MS2 data with a Web application GUI compMS2Explorer (Comprehensive MS2 Explorer) that also facilitates data-sharing and transparency. The automatable compMS2Miner workflow consists of the following steps: (i) matching unknown MS1 features to precursor MS2 scans, (ii) filtration of spectral noise (dynamic noise filter), (iii) generation of composite mass spectra by multiple similar spectrum signal summation and redundant/contaminant spectra removal, (iv) interpretation of possible fragment ion substructure using an internal database, (v) annotation of unknowns with chemical and spectral databases with prediction of mammalian biotransformation metabolites, wrapper functions for in silico fragmentation software, nearest neighbor chemical similarity scoring, random forest based retention time prediction, text-mining based false positive removal/true positive ranking, chemical taxonomic prediction and differential evolution based global annotation score optimization, and (vi) network graph visualizations, data curation, and sharing are made possible via the compMS2Explorer application. Metabolite identities and comments can also be recorded using an interactive table within compMS2Explorer. The utility of the package is illustrated with a data set of blood serum samples from 7 diet induced obese (DIO) and 7 nonobese (NO) C57BL/6J mice, which were also treated with an antibiotic (streptomycin) to knockdown the gut microbiota. The results of fully autonomous and objective usage of compMS2Miner are presented here. All automatically annotated spectra output by the workflow are provided in the Supporting Information and can alternatively be explored as publically available compMS2Explorer applications for both positive and negative modes ( https://wmbedmands.shinyapps.io/compMS2_mouseSera_POS and https://wmbedmands.shinyapps.io/compMS2_mouseSera_NEG ). The workflow provided rapid annotation of a diversity of endogenous and gut microbially derived metabolites affected by both diet and antibiotic treatment, which conformed to previously published reports. Composite spectra (n = 173) were autonomously matched to entries of the Massbank of North America (MoNA) spectral repository. These experimental and virtual (lipidBlast) spectra corresponded to 29 common endogenous compound classes (e.g., 51 lysophosphatidylcholines spectra) and were then used to calculate the ranking capability of 7 individual scoring metrics. It was found that an average of the 7 individual scoring metrics provided the most effective weighted average ranking ability of 3 for the MoNA matched spectra in spite of potential risk of false positive annotations emerging from automation. Minor structural differences such as relative carbon-carbon double bond positions were found in several cases to affect the correct rank of the MoNA annotated metabolite. The latest release and an example workflow is available in the package vignette ( https://github.com/WMBEdmands/compMS2Miner ) and a version of the published application is available on the shinyapps.io site ( https://wmbedmands.shinyapps.io/compMS2Example ). PMID: 28225587 [PubMed - indexed for MEDLINE]

22 new pubmed citations were retrieved for your search. Click on the search hyperlink below to display the complete search results: metabolomics These pubmed results were generated on 2019/03/01PubMed comprises more than millions of citations for biomedical literature from MEDLINE, life science journals, and online books. Citations may include links to full-text content from PubMed Central and publisher web sites.

22 new pubmed citations were retrieved for your search. Click on the search hyperlink below to display the complete search results: metabolomics These pubmed results were generated on 2019/03/01PubMed comprises more than millions of citations for biomedical literature from MEDLINE, life science journals, and online books. Citations may include links to full-text content from PubMed Central and publisher web sites.

18 new pubmed citations were retrieved for your search. Click on the search hyperlink below to display the complete search results: metabolomics These pubmed results were generated on 2019/02/28PubMed comprises more than millions of citations for biomedical literature from MEDLINE, life science journals, and online books. Citations may include links to full-text content from PubMed Central and publisher web sites.

18 new pubmed citations were retrieved for your search. Click on the search hyperlink below to display the complete search results: metabolomics These pubmed results were generated on 2019/02/28PubMed comprises more than millions of citations for biomedical literature from MEDLINE, life science journals, and online books. Citations may include links to full-text content from PubMed Central and publisher web sites.

Targeted metabolomics for the quantitative measurement of 9 gut microbiota-host co-metabolites in rat serum, urine and feces by liquid chromatography-tandem mass spectrometry. J Chromatogr B Analyt Technol Biomed Life Sci. 2019 Feb 19;1110-1111:133-143 Authors: Zeng Y, Lin Y, Li L, Li Y, Zhang X, Wang M, Chen Y, Luo L, Lu B, Xie Z, Liao Q Abstract Gut microbiota-host co-metabolites play an essential role in maintaining homeostasis, and their concentration changes are closely related to a variety of diseases. Developing a targeted metabolomics analytical platform for these co-metabolites will help to elucidate the relationship between intestinal flora and host. Here we present a simple and sensitive liquid chromatography-tandem mass spectrometry method for the analysis of nine gut microbiota-host co-metabolites in rat serum, urine and feces. The compounds were separated on a reversed-phase C18 column using gradient elution with a solvent system consisting of methanol and water (containing 0.05% formic acid) and a 7-min run time. All of the calibration curves exhibited good linear relationships (R2 ≥ 0.9984, Percent Residual Accuracy ≥93.27%). The intra- and interday precision, expressed as relative standard deviation (RSD), was ≤ 14.84%. The accuracy was within 100 ± 13.16% for all analytes. The recovery of the nine compounds in biological samples was ≥ 85.80% with an appropriate RSD (≤12.04%). The validated method was successfully applied to monitor the global changes of these metabolites in obesity. Taken together, these results demonstrate that the method can simultaneously determine the nine co-metabolites in multiple biological matrices and is an essential part of the targeted metabolomics analytical platform, which may become an approach to evaluate the occurrence, development and therapeutic effects of metabolic diseases. PMID: 30807966 [PubMed - as supplied by publisher]

A comparative study of UHPLC/Orbitrap MS metabolomics profiles and biological properties of Asphodeline taurica from Bulgaria and Turkey. J Pharm Biomed Anal. 2019 Feb 07;168:174-180 Authors: Lazarova I, Zengin G, Gevrenova R, Nedialkov P, Aneva I, Aumeeruddy MZ, Mahomoodally MF Abstract The present investigation attempts to compare the pharmacological properties and phytochemical profile of four extracts (ethyl acetate, dichloromethane, methanol, and water) of Asphodeline taurica (Pall.) Endl. roots from Bulgaria and Turkey. The Bulgarian ethyl acetate extract displayed the highest antioxidant activity in the DPPH, CUPRAC, and phosphomolybdenum assay, and strongest inhibition against α-amylase and α-glucosidase. The Turkish aqueous extract exhibited the strongest ABTS scavenging and ferric reducing power while its methanol extract was the most effective acetylcholinesterase (AChE) and butyrylcholinesterase (BChE) inhibitor. On the other hand, the Turkish dichloromethane extract showed the highest lipase inhibition. UHPLC/Orbitrap MS analysis showed a wide array of individual phenolics; six free anthraquinones, two bianthraquinones, three bianthracenes, three anthraquinone glycosides and one bianthracen glycoside were identified. The present data suggest that A. taurica roots can be considered as a valuable source of biologically active phytocompounds with functional properties for the cosmetic and pharmaceutical industries. PMID: 30807922 [PubMed - as supplied by publisher]

Metabolomic study reveals the acute hypotensive effect of S-1-propenylcysteine accompanied by alteration of the plasma histidine level in spontaneously hypertensive rats. J Pharm Biomed Anal. 2019 Feb 12;168:148-154 Authors: Matsutomo T, Ushijima M, Kunimura K, Ohtani M Abstract Our previous study has shown that a single dose of S-1-propenylcysteine (S1PC) exerted an antihypertensive effect in spontaneously hypertensive rats (SHR), while its mode of action remained to be further investigated. The aim of this study was to explore the potential mechanism of the antihypertensive effect of S1PC in SHR using a liquid chromatography-mass spectrometry (LC-MS)-based metabolomic approach. Blood samples were serially collected from SHR after a single oral administration of S1PC (6.5 mg/kg body weight). The metabolomics data acquired from the LC-MS analysis of plasma samples were processed using principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA). In addition, the SHR were treated with S1PC or histidine (10 mg/kg body weight) with and without intravenous preinjection of thioperamide, a histamine H3 receptor antagonist. The blood pressure of SHR was measured by the tail-cuff method at different times after administration. In the PLS-DA score plots, the clusters of the S1PC groups were clearly or partly separated from those of the control groups at 1.5 and 3 h after administration, indicating the metabolic profiles were substantially altered by the S1PC treatment at these time points. Comparative analysis based on variable importance in the projection (VIP) values obtained from PLS-DA led to the identification of 14 and 15 metabolites differing between the two groups at 1.5 and 3 h, respectively, which included various amino acids. Among the metabolites identified, the plasma histidine level in the S1PC group significantly increased at 1.5 and 3 h, and decreased to that in the control group at 6 h. Moreover, pretreatment with thioperamide inhibited the blood pressure lowering effect of S1PC as well as that of histidine. These results suggested that S1PC alters histidine metabolism and consequently exerts the antihypertensive effect via the central histamine H3 receptor. PMID: 30807919 [PubMed - as supplied by publisher]

1H NMR-based metabolomics profiling of citrus juices produced in Veracruz, México. Chem Biodivers. 2019 Feb 26;: Authors: Villa-Ruano N, Pérez-Hernández N, Zepeda-Vallejo LG, Quiroz-Acosta T, Mendieta-Moctezuma A, Montoya-García CO, García-Nava ML, Becerra Martínez E Abstract This study describes the 1H NMR-based metabolomics profiling of juices from citrus fruits harvested in the state of Veracruz, México. The hydrophilic profile of commercial lemons (Agrio and Persian), tangerines (Fremont and Mónica), oranges (Valencia and Washington Navel), and grapefruits (Red Ruby and Rio Red) was determined. According to our results, 35 metabolites were identified in the 1H NMR profiling. The statistical differences obtained by PCA and OPLS-DA revealed that specific amino acids, sugars, and organic acids were differential metabolites in the species and cultivars studied. High endogenous levels of sucrose (10-190 mM), α-glucose, β-glucose (α,β isomers, 40-205 mM), and fructose (36-170 mM) were detected in the juices of grapefruits, oranges, and tangerines, whereas citric acid (40-530 mM) was the principal organic acid in the juices of lemons. To calculate the specific amounts of metabolites from these species and their cultivars, the results were finely analyzed using the qNMR method. According to these calculations, Valencia oranges had the highest concentration of ascorbic acid (>2 mM). The described 1H NMR method is highly reproducible, inexpensive, and highly robust in comparison to other analytical methods used to determine the hydrophilic profile of citrus juices. PMID: 30807682 [PubMed - as supplied by publisher]

Metabolomics analysis in acute paraquat poisoning patients based on UPLC-Q-TOF-MS and machine learning approach. Chem Res Toxicol. 2019 Feb 26;: Authors: Wen C, Lin F, Huang B, Zhang Z, Wang X, Ma J, Lin G, Chen H, Hu L Abstract Most of paraquat (PQ) poisoned patients died for acute multiple organ failure (MOF) such as lung, kidney, and heart. However, the exact mechanism of intoxication is still unclear. In order to find out the initial toxic mechanism of PQ poisoning, a blood metabolomics study based on ultra-performance liquid chromatography coupled to quadrupole time-of-flight mass spectrometry (UPLC-Q-TOF-MS) and efficient machine learning approach was performed on 23 PQ poisoned patients and 29 healthy subjects. The initial PQ plasma concentrations of PQ poisoned patients were > 1000 ng/mL, and the blood samples were collected at before first hemoperfusion (HP), after first HP, and after last HP. The results showed that PQ poisoned patients all differed from healthy subjects, whatever they were before or after first HP or after last HP. The efficient machine learning approaches selected key metabolites from three UPLC/Q-TOF-MS datasets which had highest classification performance in terms of classification accuracy, Matthews Correlation Coefficients, sensitivity and specificity, respectively. The mass identification revealed that the most important metabolite was adenosine, which sustained in low level, regardless of whether PQ poisoned patients received HP treatment. In conclusion, decreased adenosine was the most important metabolite in PQ poisoned patients. The metabolic disturbance caused by PQ poisoning can't be improved by HP treatment even the PQ was cleared from the blood. PMID: 30807114 [PubMed - as supplied by publisher]

Related Articles Study of the metabolomic relationship between lung cancer and chronic obstructive pulmonary disease based on direct infusion mass spectrometry. Biochimie. 2019 Feb;157:111-122 Authors: Callejón-Leblic B, Pereira-Vega A, Vázquez-Gandullo E, Sánchez-Ramos JL, Gómez-Ariza JL, García-Barrera T Abstract The high prevalence of lung cancer (LC) has triggered the search of biomarkers for early diagnosis of this disease. For this purpose the study of metabolic changes related to the development of lung cancer could provide interesting information about its early diagnosis. In this sense, chronic obstructive pulmonary disease (COPD), a disease associated with tumor development, is a comorbidity that increases the risk of onset and progression of lung neoplasia and has also to be considered in the study of pathology related to lung cancer. This work develop a metabolomic approach based on direct infusion mass spectrometry using a hybrid triple quadrupole-time of flight mass spectrometer (DI-ESI-QqQ-TOF-MS) in order to identify altered metabolites from serum of LC and COPD patients and evaluate its relationship and implication in the progression of LC. This methodology has been applied to 30 serum samples from LC, 30 healthy patients used as controls (HC) and 30 serum samples from COPD to found altered metabolites from both LC and COPD diseases. In addition, some metabolic differences and similarities were found in Pulmonary Emphysema and Chronic Bronchitis patients. On the other hand, altered metabolites were studied in different stages of LC (II, III and IV) to evaluate the perturbation of them throughout the progression of disease. The sample treatment consisted of the extraction of polar and non-polar metabolites from serum that was later infused into the mass spectrometer using an electrospray ionization source in positive and negative mode. Partial least squares discriminant analysis (PLS-DA) allowed a classification between LC, HC and COPD groups in all acquisition modes. A total of 35 altered and common metabolites between LC and COPD, including amino acids, fatty acids, lysophospholipids, phospholipids and triacylglycerides were identified, being alanine, aspartate and glutamate metabolism the most altered. Finally, ROC curves were applied to the dataset and metabolites with AUC value higher than 0.70 were considered as relevant in the progression of LC. PMID: 30439409 [PubMed - indexed for MEDLINE]

Related Articles Rapid, field-deployable method for collecting and preserving plant metabolome for biochemical and functional characterization. PLoS One. 2018;13(9):e0203569 Authors: Skubel SA, Dushenkov V, Graf BL, Niu Q, Poulev A, Kalariya HM, Foxcroft LC, Raskin I Abstract Study of plant metabolome is a growing field of science that catalogs vast biochemical and functional diversity of phytochemicals. However, collecting and storing samples of plant metabolome, sharing these samples across the scientific community and making them compatible with bioactivity assays presents significant challenges to the advancement of metabolome research. We have developed a RApid Metabolome Extraction and Storage (RAMES) technology that allows efficient, highly compact, field-deployable collection and storage of libraries of plant metabolome. RAMES technology combines rapid extraction with immobilization of extracts on glass microfiber filter discs. Two grams of plant tissue extracted in ethanol, using a specially adapted Dremel® rotary tool, produces 25-35 replicas of 10 mm glass fiber discs impregnated with phytochemicals. These discs can be either eluted with solvents (such as 70% ethanol) to study the metabolomic profiles or used directly in a variety of functional assays. We have developed simple, non-sterile, anti-fungal, anti-bacterial, and anti-oxidant assays formatted for 24-multiwell plates directly compatible with RAMES discs placed inside the wells. Using these methods we confirmed activity in 30 out of 32 randomly selected anti-microbial medicinal plants and spices. Seven species scored the highest activity (total kill) in the anti-bacterial (bacteria from human saliva) and two anti-fungal screens (Fusarium spp. and Saccharomyces cerevisiae), providing functional validation of RAMES technology. RAMES libraries showed limited degradation of compounds after 12 months of storage at -20°C, while others remained stable. Fifty-eight percent of structures characterized in the extracts loaded onto RAMES discs could be eluted from the discs without significant losses. Miniaturized RAMES technology, as described and validated in this manuscript offers a labor, cost, and time-effective alternative to conventional collection of phytochemicals. RAMES technology enables creation of comprehensive metabolomic libraries from various ecosystems and geographical regions in a format compatible with further biochemical and functional studies. PMID: 30188945 [PubMed - indexed for MEDLINE]