Transcriptional and metabolic flux profiling of triadimefon effects on cultured hepatocytes

Waterborne exposure to triadimefon causes thyroid endocrine disruption and developmental delay in Xenopus laevis tadpoles

Triadimefon (TDF) is a triazole-derivative fungicide that is detectable in the environment and target agricultural products, prompting concern over its risk to wildlife and human health. In our study, Nieuwkoop & Faber stage 51 Xenopus laevis tadpoles were exposed to different nominal concentrations TDF (0, 0.112, and 1.12mg/L) for 21 days while the tadpoles were undergoing pre-morphological development. Developmental condition, bioaccumulation and thyroid hormone levels, and mRNA expression of genes involved in the hypothalamic-pituitary-thyroid (HPT) axis were examined. Exposure to TDF caused a reduction in developmental rates on pre-metamorphosis of X. laevis. TDF exposure significantly decreased thyroid hormone (T4 and T3) concentrations, indicating thyroid endocrine disruption. The downregulation of thyroglobulin and upregulation of genes related to thyroid hormone metabolism (ugt1ab) might be responsible for the decreased thyroid hormone concentrations. Treatment with TDF also significantly increased mRNA expression of genes involved in thyroid-stimulating hormone as a compensatory mechanism response to decreased thyroid hormone concentrations. Gene expression and in silico ligand docking studies were combined to study the interaction between TDF and thyroid hormone receptor. Results showed that TDF could consequently affect the HPT axis signaling pathway. In addition, bioconcentration of TDF was observed in tadpoles, indicating the bioactivity of this compound. Taken together, the results suggest that TDF alters the HPT axis-related genes and changes thyroid hormone contents in X. laevis tadpoles, thus causing thyroid endocrine disruption and consequently delaying thyroid hormones-dependent metamorphic development.

PFA toolbox: a MATLAB tool for Metabolic Flux Analysis

BACKGROUND

Metabolic Flux Analysis (MFA) is a methodology that has been successfully applied to estimate metabolic fluxes in living cells. However, traditional frameworks based on this approach have some limitations, particularly when measurements are scarce and imprecise. This is very common in industrial environments. The PFA Toolbox can be used to face those scenarios.

RESULTS

Here we present the PFA (Possibilistic Flux Analysis) Toolbox for MATLAB, which simplifies the use of Interval and Possibilistic Metabolic Flux Analysis. The main features of the PFA Toolbox are the following: (a) It provides reliable MFA estimations in scenarios where only a few fluxes can be measured or those available are imprecise. (b) It provides tools to easily plot the results as interval estimates or flux distributions. (c) It is composed of simple functions that MATLAB users can apply in flexible ways. (d) It includes a Graphical User Interface (GUI), which provides a visual representation of the measurements and their uncertainty. (e) It can use stoichiometric models in COBRA format. In addition, the PFA Toolbox includes a User's Guide with a thorough description of its functions and several examples.

CONCLUSIONS

The PFA Toolbox for MATLAB is a freely available Toolbox that is able to perform Interval and Possibilistic MFA estimations.

Review: toxicometabolomics

Metabolomics use in toxicology is rapidly increasing, particularly owing to advances in mass spectroscopy, which is widely used in the life sciences for phenotyping disease states. Toxicology has the advantage of having the disease agent, the toxicant, available for experimental induction of metabolomics changes monitored over time and dose. This review summarizes the different technologies employed and gives examples of their use in various areas of toxicology. A prominent use of metabolomics is the identification of signatures of toxicity - patterns of metabolite changes predictive of a hazard manifestation. Increasingly, such signatures indicative of a certain hazard manifestation are identified, suggesting that certain modes of action result in specific derangements of the metabolism. This might enable the deduction of underlying pathways of toxicity, which, in their entirety, form the Human Toxome, a key concept for implementing the vision of Toxicity Testing for the 21st century. This review summarizes the current state of metabolomics technologies and principles, their uses in toxicology and gives a thorough overview on metabolomics bioinformatics, pathway identification and quality assurance. In addition, this review lays out the prospects for further metabolomics application also in a regulatory context.

Degradation of conazole fungicides in water by electrochemical oxidation

The electrochemical oxidation (EO) treatment in water of three conazole fungicides, myclobutanil, triadimefon and propiconazole, has been carried out at constant current using a BDD/SS system. First, solutions of each fungicide were electrolyzed to assess the effect of the experimental parameters such as current, pH and fungicide concentration on the decay of each compound and total organic carbon abatement. Then a careful analysis of the degradation by-products was made by high performance liquid chromatography, ion chromatography and gas chromatography coupled with mass spectrometry in order to provide a detailed discussion on the original reaction pathways. Thus, during the degradation of conazole fungicides by the electrochemical oxidation process, aromatic intermediates, aliphatic carboxylic acids and Cl(-) were detected prior to their complete mineralization to CO2 while NO3(-) anions remained in the treated solution. This is an essential preliminary step towards the applicability of the EO processes for the treatment of wastewater containing conazole fungicides.

Carbonyl reduction of triadimefon by human and rodent 11β-hydroxysteroid dehydrogenase 1

11β-Hydroxysteroid dehydrogenase 1 (11β-HSD1) catalyzes the conversion of inactive 11-oxo glucocorticoids (endogenous cortisone, 11-dehydrocorticosterone and synthetic prednisone) to their potent 11β-hydroxyl forms (cortisol, corticosterone and prednisolone). Besides, 11β-HSD1 accepts several other substrates. Using rodent liver microsomes and the unspecific inhibitor glycyrrhetinic acid, it has been proposed earlier that 11β-HSD1 catalyzes the reversible conversion of the fungicide triadimefon to triadimenol. In the present study, recombinant human, rat and mouse enzymes together with a highly selective 11β-HSD1 inhibitor were applied to assess the role of 11β-HSD1 in the reduction of triadimefon and to uncover species-specific differences. To further demonstrate the role of 11β-HSD1 in the carbonyl reduction of triadimefon, microsomes from liver-specific 11β-HSD1-deficient mice were employed. Molecular docking was applied to investigate substrate binding. The results revealed important species differences and demonstrated the irreversible 11β-HSD1-dependent reduction of triadimefon. Human liver microsomes showed 4 and 8 times higher activity than rat and mouse liver microsomes. The apparent Vmax/Km of recombinant human 11β-HSD1 was 5 and 15 times higher than that of mouse and rat 11β-HSD1, respectively, indicating isoform-specific differences and different expression levels for the three species. Experiments using inhibitors and microsomes from 11β-HSD1-deficient mice indicated that 11β-HSD1 is the major if not only enzyme responsible for triadimenol formation. The IC50 values of triadimefon and triadimenol for cortisone reduction suggested that exposure to these xenobiotica unlikely impairs the 11β-HSD1-dependent glucocorticoid activation. However, elevated glucocorticoids during stress or upon pharmacological administration likely inhibit 11β-HSD1-dependent metabolism of triadimefon in humans.

Advanced stoichiometric analysis of metabolic networks of mammalian systems

Metabolic engineering tools have been widely applied to living organisms to gain a comprehensive understanding about cellular networks and to improve cellular properties. Metabolic flux analysis (MFA), flux balance analysis (FBA), and metabolic pathway analysis (MPA) are among the most popular tools in stoichiometric network analysis. Although application of these tools into well-known microbial systems is extensive in the literature, various barriers prevent them from being utilized in mammalian cells. Limited experimental data, complex regulatory mechanisms, and the requirement of more complex nutrient media are some major obstacles in mammalian cell systems. However, mammalian cells have been used to produce therapeutic proteins, to characterize disease states or related abnormal metabolic conditions, and to analyze the toxicological effects of some medicinally important drugs. Therefore, there is a growing need for extending metabolic engineering principles to mammalian cells in order to understand their underlying metabolic functions. In this review article, advanced metabolic engineering tools developed for stoichiometric analysis including MFA, FBA, and MPA are described. Applications of these tools in mammalian cells are discussed in detail, and the challenges and opportunities are highlighted.

Stoichiometry based steady-state hepatic flux analysis: computational and experimental aspects

: The liver has many complex physiological functions, including lipid, protein and carbohydrate metabolism, as well as bile and urea production. It detoxifies toxic substances and medicinal products. It also plays a key role in the onset and maintenance of abnormal metabolic patterns associated with various disease states, such as burns, infections and major traumas. Liver cells have been commonly used in in vitro experiments to elucidate the toxic effects of drugs and metabolic changes caused by aberrant metabolic conditions, and to improve the functions of existing systems, such as bioartificial liver. More recently, isolated liver perfusion systems have been increasingly used to characterize intrinsic metabolic changes in the liver caused by various perturbations, including systemic injury, hepatotoxin exposure and warm ischemia. Metabolic engineering tools have been widely applied to these systems to identify metabolic flux distributions using metabolic flux analysis or flux balance analysis and to characterize the topology of the networks using metabolic pathway analysis. In this context, hepatic metabolic models, together with experimental methodologies where hepatocytes or perfused livers are mainly investigated, are described in detail in this review. The challenges and opportunities are also discussed extensively.

Metabolic network analysis of perfused livers under fed and fasted states: incorporating thermodynamic and futile-cycle-associated regulatory constraints

Isolated liver perfusion systems have been extensively used to characterize intrinsic metabolic changes in liver under various conditions, including systemic injury, hepatotoxin exposure, and warm ischemia. Most of these studies were performed utilizing fasted animals prior to perfusion so that a simplified metabolic network could be used in order to determine intracellular fluxes. However, fasting induced metabolic alterations might interfere with disease related changes. Therefore, there is a need to develop a "unified" metabolic flux analysis approach that could be similarly applied to both fed and fasted states. In this study we explored a methodology based on elementary mode analysis in order to determine intracellular fluxes and active pathways simultaneously. In order to decrease the solution space, thermodynamic constraints, and enzymatic regulatory properties for the formation of futile cycles were further considered in the model, resulting in a mixed integer quadratic programming problem. Given the published experimental observations describing the perfused livers under fed and fasted states, the proposed approach successfully determined that gluconeogenesis, glycogenolysis and fatty acid oxidation were active in both states. However, fasting increased the fluxes in gluconeogenic reactions whereas it decreased fluxes associated with glycogenolysis, TCA cycle, fatty acid oxidation and electron transport reactions. This analysis further identified that more pathways were found to be active in fed state while their weight values were relatively lower compared to fasted state. Glucose, lactate, glutamine, glutamate and ketone bodies were also found to be important external metabolites whose extracellular fluxes should be used in the hepatic metabolic network analysis. In conclusion, the mathematical formulation explored in this study is an attractive tool to analyze the metabolic network of perfused livers under various disease conditions. This approach could be simultaneously applied to both fasted and fed data sets.