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Metabolic Reactions (metabolic + reaction)
Selected AbstractsNocturnal nutritional supplementation improves total body protein status of patients with liver cirrhosis: A randomized 12-month trial,HEPATOLOGY, Issue 2 2008Lindsay D. Plank Patients with liver cirrhosis exhibit early onset of gluconeogenesis after short-term fasting. This accelerated metabolic reaction to starvation may underlie their increased protein requirements and muscle depletion. A randomized controlled trial was conducted to test the hypothesis that provision of a late-evening nutritional supplement over a 12-month period would improve body protein stores in patients with cirrhosis. A total of 103 patients (68 male, 35 female; median age 51, range 28,74; Child-Pugh grading: 52A, 31B, 20C) were randomized to receive either daytime (between 0900 and 1900 hours) or nighttime (between 2100 and 0700 hours) supplementary nutrition (710 kcal/day). Primary etiology of liver disease was chronic viral hepatitis (67), alcohol (15), cholestatic (6), and other (15). Total body protein (TBP) was measured by neutron activation analysis at baseline, 3, 6, and 12 months. Total daily energy and protein intakes were assessed at baseline and at 3 months by comprehensive dietary recall. As a percentage of values predicted when well, TBP at baseline was similar for the daytime (85 ± 2[standard error of the mean]%) and nighttime (84 ± 2%) groups. For the nighttime group, significant increases in TBP were measured at 3 (0.38 ± 0.10 kg, P = 0.0004), 6 (0.48 ± 0.13 kg, P = 0.0007), and 12 months (0.53 ± 0.17 kg, P = 0.003) compared to baseline. For the daytime group, no significant changes in TBP were seen. Daily energy and protein intakes at 3 months were higher than at baseline in both groups (P < 0.0001), and these changes did not differ between the groups. Conclusion: Provision of a nighttime feed to patients with cirrhosis results in body protein accretion equivalent to about 2 kg of lean tissue sustained over 12 months. This improved nutritional status may have important implications for the clinical course of these patients. (HEPATOLOGY 2008.) [source] Energetics of overall metabolic reactions of thermophilic and hyperthermophilic Archaea and BacteriaFEMS MICROBIOLOGY REVIEWS, Issue 2 2001Jan P. Amend Abstract Thermophilic and hyperthermophilic Archaea and Bacteria have been isolated from marine hydrothermal systems, heated sediments, continental solfataras, hot springs, water heaters, and industrial waste. They catalyze a tremendous array of widely varying metabolic processes. As determined in the laboratory, electron donors in thermophilic and hyperthermophilic microbial redox reactions include H2, Fe2+, H2S, S, S2O32,, S4O62,, sulfide minerals, CH4, various mono-, di-, and hydroxy-carboxylic acids, alcohols, amino acids, and complex organic substrates; electron acceptors include O2, Fe3+, CO2, CO, NO3,, NO2,, NO, N2O, SO42,, SO32,, S2O32,, and S. Although many assimilatory and dissimilatory metabolic reactions have been identified for these groups of microorganisms, little attention has been paid to the energetics of these reactions. In this review, standard molal Gibbs free energies (,Gr°) as a function of temperature to 200°C are tabulated for 370 organic and inorganic redox, disproportionation, dissociation, hydrolysis, and solubility reactions directly or indirectly involved in microbial metabolism. To calculate values of ,Gr° for these and countless other reactions, the apparent standard molal Gibbs free energies of formation (,G°) at temperatures to 200°C are given for 307 solids, liquids, gases, and aqueous solutes. It is shown that values of ,Gr° for many microbially mediated reactions are highly temperature dependent, and that adopting values determined at 25°C for systems at elevated temperatures introduces significant and unnecessary errors. The metabolic processes considered here involve compounds that belong to the following chemical systems: H,O, H,O,N, H,O,S, H,O,N,S, H,O,Cinorganic, H,O,C, H,O,N,C, H,O,S,C, H,O,N,S,Camino acids, H,O,S,C,metals/minerals, and H,O,P. For four metabolic reactions of particular interest in thermophily and hyperthermophily (knallgas reaction, anaerobic sulfur and nitrate reduction, and autotrophic methanogenesis), values of the overall Gibbs free energy (,Gr) as a function of temperature are calculated for a wide range of chemical compositions likely to be present in near-surface and deep hydrothermal and geothermal systems. [source] Genome-scale modeling of Synechocystis sp.JOURNAL OF CHEMICAL TECHNOLOGY & BIOTECHNOLOGY, Issue 4 2009PCC 680, prediction of pathway insertion Abstract BACKGROUND: Cyanobacterium Synechocystis sp. PCC 6803 has been used widely as a model system for the study of photosynthetic organisms and higher plants. The aim of this work was to integrate the genomic information, biochemistry and physiological information available for Synechocystis sp. PCC 6803 to reconstruct a metabolic network for system biology investigations. RESULTS: A genome-scale Synechocystis sp. PCC 6803 metabolic network, including 633 genes, 704 metabolites and 831 metabolic reactions, was reconstructed for the study of optimal Synechocystis growth, network capacity and functions. Heterotrophic, photoautotrophic and mixotrophic growth conditions were simulated. The Synechocystis model was used for in silico predictions for the insertion of ethanol fermentation pathway, which is a novel approach for bioenergy and biofuels production developed in the authors' laboratory. Simulations of Synechocystis cell growth and ethanol production were compared with actual metabolic measurements which showed a satisfactory agreement. CONCLUSION: The Synechocystis metabolic network developed in this study is the first genome-scale mathematical model for photosynthetic organisms. The model may be used not only in global understanding of cellular metabolism and photosynthesis, but also in designing metabolic engineering strategies for desirable bio-products. Copyright © 2008 Society of Chemical Industry [source] Structure elucidation of aplidine metabolites formed in vitro by human liver microsomes using triple quadrupole mass spectrometryJOURNAL OF MASS SPECTROMETRY (INCORP BIOLOGICAL MASS SPECTROMETRY), Issue 6 2005Esther F. A. Brandon Abstract The cyclic depsipeptide aplidine is a new anti-cancer drug of marine origin. Four metabolites of this compound were found after incubation with pooled human microsomes using gradient high-performance liquid chromatography with ultraviolet detection. After chromatographic isolation, the metabolites have been identified using nano-electrospray triple quadrupole mass spectrometry. A highly specific sodium-ion interaction with the cyclic structure opens the depsipeptide ring, and cleavage of the amino acid residues gives sequence information when activated by collision-induced dissociation in the second quadrupole. The aplidine molecule could undergo the following metabolic reactions: hydroxylation at the isopropyl group (metabolites apli-h 1 and apli-h 2); C-dealkylation at the N(Me)-leucine group (metabolite apli-da); hydroxylation at the isopropyl group and C-dealkylation at the N(Me)-leucine group (metabolite apli-da/h), and C-demethylation at the threonine group (metabolite apli-dm). The identification of these metabolites formed in vitro may greatly aid the elucidation of the metabolic pathways of aplidine in humans. Copyright © 2005 John Wiley & Sons, Ltd. [source] Isolation and identification of metabolites from dihydromyricetinMAGNETIC RESONANCE IN CHEMISTRY, Issue 11 2007Yansong Zhang Abstract Dihydromyricetin (DHM) is the major bioactive constituent of Rattan Tea, which is the tender stems and leaves of Ampelopsis grossendentata. Seven metabolites (2,8) of DHM (1) were obtained by the chromatographic method. The metabolites 2,5 were obtained from the urine of rats administered orally with DHM; and metabolites 6,8 were detected in the fecal specimens of rats, which were also produced by human intestinal bacteria (HIB) in vitro, and were separated from the cultured media of HIB containing DHM. Their structures were elucidated as 5,7,3,,5,-tetrahydroxyflavanonol (2); 5,7,3,,5,-tetrahydroxy-4,-methoxyflavanonol (3); 5,7,4,,5,-tetrahydroxy-3,-methoxyflavanonol (4); and dihydromyricetin- O -5-,- D -glucuronide (5); (2R,3S)-5,7,3,,4,,5,-pentahydroxyflavanonol (6); 3,4,5,7,3,,4,,5,-hepthydroxyflavan (7) and 5,7,3,,4,,5,-pentahydroxyflavanone (8) on the basis of UV, NMR and LC-MS/MS data. These seven metabolites were formed through familiar metabolic reactions. Dihydromyricetin- O -5-,- D -glucuronide (5) is a new compound. The 13C-NMR data of (2) and (4) are reported for the first time. Copyright © 2007 John Wiley & Sons, Ltd. [source] Isobaric metabolite interferences and the requirement for close examination of raw data in addition to stringent chromatographic separations in liquid chromatography/tandem mass spectrometric analysis of drugs in biological matrixRAPID COMMUNICATIONS IN MASS SPECTROMETRY, Issue 13 2008Zhengyin Yan In addition to matrix effects, common interferences observed in liquid chromatography/tandem mass spectrometry (LC/MS/MS) analyses can be caused by the response of drug-related metabolites to the multiple reaction monitoring (MRM) channel of a given drug, as a result of in-source reactions or decomposition of either phase I or II metabolites. However, it has been largely ignored that, for some drugs, metabolism can lead to the formation of isobaric or isomeric metabolites that exhibit the same MRM transitions as parent drugs. The present study describes two examples demonstrating that interference caused by isobaric or isomeric metabolites is a practical issue in analyzing biological samples by LC/MS/MS. In the first case, two sequential metabolic reactions, demethylation followed by oxidation of a primary alcohol moiety to a carboxylic acid, produced an isobaric metabolite that exhibits a MRM transition identical to the parent drug. Because the drug compound was rapidly metabolized in rats and completely disappeared in plasma samples, the isobaric metabolite appeared as a single peak in the total ion current (TIC) trace and could easily be quantified as the drug since it was eluted at a retention time very close to that of the drug in a 12-min LC run. In the second example, metabolism via the ring-opening of a substituted isoxazole moiety led to the formation of an isomeric product that showed an almost identical collision-induced dissociation (CID) MS spectrum as the original drug. Because two components were co-eluted, the isomeric product could be mistakenly quantified and reported by data processing software as the parent drug if the TIC trace was not carefully inspected. Nowadays, all LC/MS data are processed by computer software in a highly automated fashion, and some analysts may spend much less time to visually examine raw TIC traces than they used to do. Two examples described in this article remind us that quality data require both adequate chromatographic separations and close examination of raw data in LC/MS/MS analyses of drugs in biological matrix. Copyright © 2008 John Wiley & Sons, Ltd. [source] Systematizing the generation of missing metabolic knowledgeBIOTECHNOLOGY & BIOENGINEERING, Issue 3 2010Jeffrey D. Orth Abstract Genome-scale metabolic network reconstructions are built from all of the known metabolic reactions and genes in a target organism. However, since our knowledge of any organism is incomplete, these network reconstructions contain gaps. Reactions may be missing, resulting in dead-ends in pathways, while unknown gene products may catalyze known reactions. New computational methods that analyze data, such as growth phenotypes or gene essentiality, in the context of genome-scale metabolic networks, have been developed to predict these missing reactions or genes likely to fill these knowledge gaps. A growing number of experimental studies are appearing that address these computational predictions, leading to discovery of new metabolic capabilities in the target organism. Gap-filling methods can thus be used to improve metabolic network models while simultaneously leading to discovery of new metabolic gene functions. Biotechnol. Bioeng. 2010;107: 403,412. © 2010 Wiley Periodicals, Inc. [source] Kinetic modeling of light limitation and sulfur deprivation effects in the induction of hydrogen production with Chlamydomonas reinhardtii: Part I. Model development and parameter identificationBIOTECHNOLOGY & BIOENGINEERING, Issue 1 2009Swanny Fouchard Abstract Chlamydomonas reinhardtii is a green microalga capable of turning its metabolism towards H2 production under specific conditions. However this H2 production, narrowly linked to the photosynthetic process, results from complex metabolic reactions highly dependent on the environmental conditions of the cells. A kinetic model has been developed to relate culture evolution from standard photosynthetic growth to H2 producing cells. It represents transition in sulfur-deprived conditions, known to lead to H2 production in Chlamydomonas reinhardtii, and the two main processes then induced which are an over-accumulation of intracellular starch and a progressive reduction of PSII activity for anoxia achievement. Because these phenomena are directly linked to the photosynthetic growth, two kinetic models were associated, the first (one) introducing light dependency (Haldane type model associated to a radiative light transfer model), the second (one) making growth a function of available sulfur amount under extracellular and intracellular forms (Droop formulation). The model parameters identification was realized from experimental data obtained with especially designed experiments and a sensitivity analysis of the model to its parameters was also conducted. Model behavior was finally studied showing interdependency between light transfer conditions, photosynthetic growth, sulfate uptake, photosynthetic activity and O2 release, during transition from oxygenic growth to anoxic H2 production conditions. Biotechnol. Bioeng. 2009;102: 232,245. © 2008 Wiley Periodicals, Inc. [source] Invariability of central metabolic flux distribution in Shewanella oneidensis MR-1 under environmental or genetic perturbationsBIOTECHNOLOGY PROGRESS, Issue 5 2009Yinjie J. Tang Abstract An environmentally important bacterium with versatile respiration, Shewanella oneidensis MR-1, displayed significantly different growth rates under three culture conditions: minimal medium (doubling time ,3 h), salt stressed minimal medium (doubling time ,6 h), and minimal medium with amino acid supplementation (doubling time ,1.5 h). 13C-based metabolic flux analysis indicated that fluxes of central metabolic reactions remained relatively constant under the three growth conditions, which is in stark contrast to the reported significant changes in the transcript and metabolite profiles under various growth conditions. Furthermore, 10 transposon mutants of S. oneidensis MR-1 were randomly chosen from a transposon library and their flux distributions through central metabolic pathways were revealed to be identical, even though such mutational processes altered the secondary metabolism, for example, glycine and C1 (5,10-Me-THF) metabolism. © 2009 American Institute of Chemical Engineers Biotechnol. Prog., 2009 [source] A hybrid model of anaerobic E. coli GJT001: Combination of elementary flux modes and cybernetic variablesBIOTECHNOLOGY PROGRESS, Issue 5 2008Jin Il Kim Flux balance analysis (FBA) in combination with the decomposition of metabolic networks into elementary modes has provided a route to modeling cellular metabolism. It is dependent, however, on the availability of external fluxes such as substrate uptake or growth rate before estimates can become available of intracellular fluxes. The framework classically does not allow modeling of metabolic regulation or the formulation of dynamic models except through dynamic measurement of external fluxes. The cybernetic modeling approach of Ramkrishna and coworkers provides a dynamic framework for modeling metabolic systems because of its focus on describing regulatory processes based on cybernetic arguments and hence has the capacity to describe both external and internal fluxes. In this article, we explore the alternative of developing hybrid models combining cybernetic models for the external fluxes with the flux balance approach for estimation of the internal fluxes. The approach has the merit of the simplicity of the early cybernetic models and hence computationally facile while also providing detailed information on intracellular fluxes. The hybrid model of this article is based on elementary mode decomposition of the metabolic network. The uptake rates for the various elementary modes are combined using global cybernetic variables based on maximizing substrate uptake rates. Estimation of intracellular metabolism is based on its stoichiometric coupling with the external fluxes under the assumption of (pseudo-) steady state conditions. The set of parameters of the hybrid model was estimated with the aid of nonlinear optimization routine, by fitting simulations with dynamic experimental data on concentrations of biomass, substrate, and fermentation products. The hybrid model estimations were tested with FBA (based on measured substrate uptake rate) for two different metabolic networks (one is a reduced network which fixes ATP contribution to the biomass and maintenance requirement of ATP, and the other network is a more complex network which has a separate reaction for maintenance.) for the same experiment involving anaerobic growth of E. coli GJT001. The hybrid model estimated glucose consumption and all fermentation byproducts to better than 10%. The FBA makes similar estimations of fermentation products, however, with the exception of succinate. The simulation results show that the global cybernetic variables alone can regulate the metabolic reactions obtaining a very satisfactory fit to the measured fermentation byproducts. In view of the hybrid model's ability to predict biomass growth and fermentation byproducts of anaerobic E. coli GJT001, this reduced order model offers a computationally efficient alternative to more detailed models of metabolism and hence useful for the simulation of bioreactors. [source] The Biochemistry of Drug Metabolism , An IntroductionCHEMISTRY & BIODIVERSITY, Issue 12 2008Part 6. Abstract This review is part of a series of review articles on the metabolism of drugs and other xenobiotics published in Chemistry & Biodiversity. After a thorough discussion of metabolic reactions and their enzymes, this article focuses on genetically determined differences in drug and xenobiotic metabolism. After a short introduction on the causes for genetic differences, the first focus is on species differences in drug and xenobiotic metabolism. A major chapter is then dedicated to clinically relevant genetic polymorphisms in human drug metabolism and resultant ethnic differences. The last two chapters deal with sex-dependent differences in drug metabolism and personalized pharmacotherapy related to inter-individual differences in drug metabolism. [source] Calculation of the Specific Rate of Catabolic Activity (Ac) from the Heat Flow Rate of Soil Microbial Reactions Measured by Calorimetry: Significance and ApplicationsCHEMISTRY & BIODIVERSITY, Issue 10 2004Nieves Barros The calculation of parameters involved in the kinetics of the microbial soil reactions linked to the carbon cycle is strongly limited by the methodologies employed. Hence, a mathematical model is proposed to quantify easily the specific rate of catabolic activity Ac by microcalorimetry based on Belaich's model. It permits to quantify Ac from the plots of the heat flow rate vs. time recorded from soil samples amended with glucose. It was applied for several soil samples collected in the Amazon. The results obtained were compared, and statistical and graphical analyses were used to provide the biophysical significance of Ac in soils. Results suggest that Ac could be used as an empirical measure of stress. It correlates positively with the heat yield, YQ/X, of the soil microbial growth reactions, indicating that higher specific rates of catabolic activity cause higher dissipation of energy per unit of cell, yielding less-efficient metabolic reactions, which could affect negatively the soil quality. It is strongly affected by the initial microbial population and by the percentage of nitrogen in the samples. The statistical analysis also demonstrated that Ac is more sensitive to changing environmental conditions than YQ/X, yielding more-accurate information about the soil metabolic processes. [source] SyGMa: Combining Expert Knowledge and Empirical Scoring in the Prediction of MetabolitesCHEMMEDCHEM, Issue 5 2008Lars Ridder Dr. Abstract Predictions of potential metabolites based on chemical structure are becoming increasingly important in drug discovery to guide medicinal chemistry efforts that address metabolic issues and to support experimental metabolite screening and identification. Herein we present a novel rule-based method, SyGMa (Systematic Generation of potential Metabolites), to predict the potential metabolites of a given parent structure. A set of reaction rules covering a broad range of phase,1 and phase,2 metabolism has been derived from metabolic reactions reported in the Metabolite Database to occur in humans. An empirical probability score is assigned to each rule representing the fraction of correctly predicted metabolites in the training database. This score is used to refine the rules and to rank predicted metabolites. The current rule set of SyGMa covers approximately 70,% of biotransformation reactions observed in humans. Evaluation of the rule-based predictions demonstrated a significant enrichment of true metabolites in the top of the ranking list: while in total, 68,% of all observed metabolites in an independent test set were reproduced by SyGMa, a large part, 30,% of the observed metabolites, were identified among the top three predictions. From a subset of cytochrome P450 specific metabolites, 84,% were reproduced overall, with 66,% in the top three predicted phase,1 metabolites. A similarity analysis of the reactions present in the database was performed to obtain an overview of the metabolic reactions predicted by SyGMa and to support ongoing efforts to extend the rules. Specific examples demonstrate the use of SyGMa in experimental metabolite identification and the application of SyGMa to suggest chemical modifications that improve the metabolic stability of compounds. [source] | |||||||||||||