Edelfosine-induced metabolic changes in cancer cells that precede the overproduction of reactive oxygen species and apoptosis

Background: Metabolic flux profiling based on the analysis of distribution of stable isotope tracer in metabolites is an important method widely used in cancer research to understand the regulation of cell metabolism and elaborate new therapeutic strategies. Recently, we developed software Isodyn, which extends the methodology of kinetic modeling to the analysis of isotopic isomer distribution for the evaluation of cellular metabolic flux profile under relevant conditions. This tool can be applied to reveal the metabolic effect of proapoptotic drug edelfosine in leukemia Jurkat cell line, uncovering the mechanisms of induction of apoptosis in cancer cells. Results: The study of 13C distribution of Jukat cells exposed to low edelfosine concentration, which induces apoptosis in ¿5% of cells, revealed metabolic changes previous to the development of apoptotic program. Specifically, it was found that low dose of edelfosine stimulates the TCA cycle. These metabolic perturbations were coupled with an increase of nucleic acid synthesis de novo, which indicates acceleration of biosynthetic and reparative processes. The further increase of the TCA cycle fluxes, when higher doses of drug applied, eventually enhance reactive oxygen species (ROS) production and trigger apoptotic program. Conclusion: The application of Isodyn to the analysis of mechanism of edelfosine-induced apoptosis revealed primary drug-induced metabolic changes, which are important for the subsequent initiation of apoptotic program. Initiation of such metabolic changes could be exploited in anticancer therapy.

Application of metabolic engineering to the production of scopolamine

Scopolamine is an alkaloid widely used in medicine for its anticholinergic activity. The aim of this review is to show that metabolic engineering techniques constitute a suitable tool to improve the production of tropane alkaloids, focusing in particular on scopolamine. We present an overview of results obtained by various research groups, including our own, who have studied the overexpression of genes involved in the biosynthesis of scopolamine in different plant species that produce tropane alkaloids. Experiments carried out to improve production in hairy root cultures will also be described, as well as those attempting to biotransform hyoscyamine into scopolamine in roots and transgenic tobacco cells.

Guidelines for specialized nutritional and metabolic support in the critically-ill patient. Update. Consensus SEMICYUC-SENPE: Oncohematological patient

Patients with cancer, irrespective of the stage of their disease, can require admission to the intensive care unit as a result of the complications of their underlying process or the surgical or pharmacological treatment provided. The cancer itself, as well as the critical status that can result from the complications of the disease, frequently lead to a high degree of hypermetabolism and inadequate energy intake, causing a high incidence of malnutrition in these patients. Moreover, cancer causes anomalous use of nutritional substrates and therefore the route of administration and proportion and intake of nutrients may differ in these patients from those in noncancer patients.

The metabolic syndrome, a multifaceted disease of affluence

Metabolic syndrome developed in consequence of an evolutionary inadequacy: the human body was unprepared for a dietary excess of nutrients, especially lipids (largely in detriment of carbohydrate). This excess awakens metabolic signals akin to those of starvation, in which the main energy staple is the body"s own lipid reserve. Lipid dietary abundance prevents the use of glucose, which in turn limits the oxidation of amino acids. To ward against a subsequent avalanche of substrates, the immune system and hypertrophied tissues (for example, adipose) elicit a series of defence responses. This response is probably the ultimate basis of a disease that is manifested as various pathologies, which were initially defined as distinct entities but which are slowly being seen as a single pathognomic unit in the literature. Based on their common origin of the ample availability of food in our modern society, the cluster of diseases comprising the metabolic syndrome is probably best described as a single multifaceted disease.

Metabolic alterations and increased liver mTOR expression precede the development of autoimmune disease in a murine model of lupus erythematosus

Although metabolic syndrome (MS) and systemic lupus erythematosus (SLE) are often associated, a common link has not been identified. Using the BWF1 mouse, which develops MS and SLE, we sought a molecular connection to explain the prevalence of these two diseases in the same individuals. We determined SLE- markers (plasma anti-ds-DNA antibodies, splenic regulatory T cells (Tregs) and cytokines, proteinuria and renal histology) and MS-markers (plasma glucose, non-esterified fatty acids, triglycerides, insulin and leptin, liver triglycerides, visceral adipose tissue, liver and adipose tissue expression of 86 insulin signaling-related genes) in 8-, 16-, 24-, and 36-week old BWF1 and control New-Zealand-White female mice. Up to week 16, BWF1 mice showed MS-markers (hyperleptinemia, hyperinsulinemia, fatty liver and visceral adipose tissue) that disappeared at week 36, when plasma anti-dsDNA antibodies, lupus nephritis and a pro-autoimmune cytokine profile were detected. BWF1 mice had hyperleptinemia and high splenic Tregs till week 16, thereby pointing to leptin resistance, as confirmed by the lack of increased liver P-Tyr-STAT-3. Hyperinsulinemia was associated with a down-regulation of insulin related-genes only in adipose tissue, whereas expression of liver mammalian target of rapamicyn (mTOR) was increased. Although leptin resistance presented early in BWF1 mice can slow-down the progression of autoimmunity, our results suggest that sustained insulin stimulation of organs, such as liver and probably kidneys, facilitates the over-expression and activity of mTOR and the development of SLE.

Distribution of events of positive selection and population differentiation in a metabolic pathway: the case of asparagine N-glycosylation

Asparagine N-Glycosylation is one of the most important forms of protein post-translational modification in eukaryotes. This metabolic pathway can be subdivided into two parts: an upstream sub-pathway required for achieving proper folding for most of the proteins synthesized in the secretory pathway, and a downstream sub-pathway required to give variability to trans-membrane proteins, and involved in adaptation to the environment and innate immunity. Here we analyze the nucleotide variability of the genes of this pathway in human populations, identifying which genes show greater population differentiation and which genes show signatures of recent positive selection. We also compare how these signals are distributed between the upstream and the downstream parts of the pathway, with the aim of exploring how forces of population differentiation and positive selection vary among genes involved in the same metabolic pathway but subject to different functional constraints. Our results show that genes in the downstream part of the pathway are more likely to show a signature of population differentiation, while events of positive selection are equally distributed among the two parts of the pathway. Moreover, events of positive selection are frequent on genes that are known to be at bifurcation points, and that are identified as being in key position by a network-level analysis such as MGAT3 and GCS1. These findings indicate that the upstream part of the Asparagine N-Glycosylation pathway has lower diversity among populations, while the downstream part is freer to tolerate diversity among populations. Moreover, the distribution of signatures of population differentiation and positive selection can change between parts of a pathway, especially between parts that are exposed to different functional constraints. Our results support the hypothesis that genes involved in constitutive processes can be expected to show lower population differentiation, while genes involved in traits related to the environment should show higher variability. Taken together, this work broadens our knowledge on how events of population differentiation and of positive selection are distributed among different parts of a metabolic pathway.

Diabetes mellitus, periapical inflammation and endodontic treatment outcome

The possible connection between chronic oral inflammatory processes, such as apical periodontitis and periodontal disease (PD), and systemic health is one of the most interesting aspects faced by the medical and dental scientific community. Chronic apical periodontitis shares important characteristics with PD: 1) both are chronic infections of the oral cavity, 2) the Gram-negative anaerobic microbiota found in both diseases is comparable, and 3) in both infectious processes increased local levels of inflammatory mediators may have an impact on systemic levels. One of the systemic disorders linked to PD is diabetes mellitus (DM); is therefore plausible to assume that chronic apical periodontitis and endodontic treatment are also associated with DM. The status of knowledge regarding the relationship between DM and endodontics is reviewed. Upon review, we conclude that there are data in the literature that associate DM with a higher prevalence of periapical lesions, greater size of the osteolityc lesions, greater likelihood of asymptomatic infections and worse prognosis for root filled teeth. The results of some studies suggest that periapical disease may contribute to diabetic metabolic dyscontrol

Identifying quantitative operation principles in metabolic pathways: a systematic method for searching feasible enzyme activity patterns leading to cellular adaptive responses

Background: Optimization methods allow designing changes in a system so that specific goals are attained. These techniques are fundamental for metabolic engineering. However, they are not directly applicable for investigating the evolution of metabolic adaptation to environmental changes. Although biological systems have evolved by natural selection and result in well-adapted systems, we can hardly expect that actual metabolic processes are at the theoretical optimum that could result from an optimization analysis. More likely, natural systems are to be found in a feasible region compatible with global physiological requirements. Results: We first present a new method for globally optimizing nonlinear models of metabolic pathways that are based on the Generalized Mass Action (GMA) representation. The optimization task is posed as a nonconvex nonlinear programming (NLP) problem that is solved by an outer- approximation algorithm. This method relies on solving iteratively reduced NLP slave subproblems and mixed-integer linear programming (MILP) master problems that provide valid upper and lower bounds, respectively, on the global solution to the original NLP. The capabilities of this method are illustrated through its application to the anaerobic fermentation pathway in Saccharomyces cerevisiae. We next introduce a method to identify the feasibility parametric regions that allow a system to meet a set of physiological constraints that can be represented in mathematical terms through algebraic equations. This technique is based on applying the outer-approximation based algorithm iteratively over a reduced search space in order to identify regions that contain feasible solutions to the problem and discard others in which no feasible solution exists. As an example, we characterize the feasible enzyme activity changes that are compatible with an appropriate adaptive response of yeast Saccharomyces cerevisiae to heat shock Conclusion: Our results show the utility of the suggested approach for investigating the evolution of adaptive responses to environmental changes. The proposed method can be used in other important applications such as the evaluation of parameter changes that are compatible with health and disease states.

Steady-state global optimization of metabolic non-linear dynamic models through recasting into power-law canonical models

Background: Design of newly engineered microbial strains for biotechnological purposes would greatly benefit from the development of realistic mathematical models for the processes to be optimized. Such models can then be analyzed and, with the development and application of appropriate optimization techniques, one could identify the modifications that need to be made to the organism in order to achieve the desired biotechnological goal. As appropriate models to perform such an analysis are necessarily non-linear and typically non-convex, finding their global optimum is a challenging task. Canonical modeling techniques, such as Generalized Mass Action (GMA) models based on the power-law formalism, offer a possible solution to this problem because they have a mathematical structure that enables the development of specific algorithms for global optimization. Results: Based on the GMA canonical representation, we have developed in previous works a highly efficient optimization algorithm and a set of related strategies for understanding the evolution of adaptive responses in cellular metabolism. Here, we explore the possibility of recasting kinetic non-linear models into an equivalent GMA model, so that global optimization on the recast GMA model can be performed. With this technique, optimization is greatly facilitated and the results are transposable to the original non-linear problem. This procedure is straightforward for a particular class of non-linear models known as Saturable and Cooperative (SC) models that extend the power-law formalism to deal with saturation and cooperativity. Conclusions: Our results show that recasting non-linear kinetic models into GMA models is indeed an appropriate strategy that helps overcoming some of the numerical difficulties that arise during the global optimization task.

Identifying the preferred subset of enzymatic profiles in nonlinear kinetic metabolic models via multiobjective global optimization and pareto filters

Optimization models in metabolic engineering and systems biology focus typically on optimizing a unique criterion, usually the synthesis rate of a metabolite of interest or the rate of growth. Connectivity and non-linear regulatory effects, however, make it necessary to consider multiple objectives in order to identify useful strategies that balance out different metabolic issues. This is a fundamental aspect, as optimization of maximum yield in a given condition may involve unrealistic values in other key processes. Due to the difficulties associated with detailed non-linear models, analysis using stoichiometric descriptions and linear optimization methods have become rather popular in systems biology. However, despite being useful, these approaches fail in capturing the intrinsic nonlinear nature of the underlying metabolic systems and the regulatory signals involved. Targeting more complex biological systems requires the application of global optimization methods to non-linear representations. In this work we address the multi-objective global optimization of metabolic networks that are described by a special class of models based on the power-law formalism: the generalized mass action (GMA) representation. Our goal is to develop global optimization methods capable of efficiently dealing with several biological criteria simultaneously. In order to overcome the numerical difficulties of dealing with multiple criteria in the optimization, we propose a heuristic approach based on the epsilon constraint method that reduces the computational burden of generating a set of Pareto optimal alternatives, each achieving a unique combination of objectives values. To facilitate the post-optimal analysis of these solutions and narrow down their number prior to being tested in the laboratory, we explore the use of Pareto filters that identify the preferred subset of enzymatic profiles. We demonstrate the usefulness of our approach by means of a case study that optimizes the ethanol production in the fermentation of Saccharomyces cerevisiae.

Effects of a post-weaning cafeteria diet in young rats: metabolic syndrome, reduced activity and low anxiety-like behaviour.

Among adolescents, overweight, obesity and metabolic syndrome are rapidly increasing in recent years as a consequence of unhealthy palatable diets. Animal models of diet-induced obesity have been developed, but little is known about the behavioural patterns produced by the consumption of such diets. The aim of the present study was to determine the behavioural and biochemical effects of a cafeteria diet fed to juvenile male and female rats, as well as to evaluate the possible recovery from these effects by administering standard feeding during the last week of the study. Two groups of male and female rats were fed with either a standard chow diet (ST) or a cafeteria (CAF) diet from weaning and for 8 weeks. A third group of males (CAF withdrawal) was fed with the CAF diet for 7 weeks and the ST in the 8th week. Both males and females developed metabolic syndrome as a consequence of the CAF feeding, showing overweight, higher adiposity and liver weight, increased plasma levels of glucose, insulin and triglycerides, as well as insulin resistance, in comparison with their respective controls. The CAF diet reduced motor activity in all behavioural tests, enhanced exploration, reduced anxiety-like behaviour and increased social interaction; this last effect was more pronounced in females than in males. When compared to animals only fed with a CAF diet, CAF withdrawal increased anxiety in the open field, slightly decreased body weight, and completely recovered the liver weight, insulin sensitivity and the standard levels of glucose, insulin and triglycerides in plasma. In conclusion, a CAF diet fed to young animals for 8 weeks induced obesity and metabolic syndrome, and produced robust behavioural changes in young adult rats, whereas CAF withdrawal in the last week modestly increased anxiety, reversed the metabolic alterations and partially reduced overweight.

Metabolic origin of δ15N values in nitrogenous compounds from Brassica napus L. leaves

Nitrogen isotope composition (δ15N) in plant organic matter is currently used as a natural tracer of nitrogen acquisition efficiency. However, the δ15N value of whole leaf material does not properly reflect the way in which N is assimilated because isotope fractionations along metabolic reactions may cause substantial differences among leaf compounds. In other words, any change in metabolic composition or allocation pattern may cause undesirable variability in leaf δ15N. Here, we investigated the δ15N in different leaf fractions and individual metabolites from rapeseed (Brassica napus) leaves. We show that there were substantial differences in δ15N between nitrogenous compounds (up to 30 ) and the content in (15N enriched) nitrate had a clear influence on leaf δ15N. Using a simple steady-state model of day metabolism, we suggest that the δ15N value in major amino acids was mostly explained by isotope fractionation associated with isotope effects on enzyme-catalysed reactions in primary nitrogen metabolism. δ15N values were further influenced by light versus dark conditions and the probable occurrence of alternative biosynthetic pathways. We conclude that both biochemical pathways (that fractionate between isotopes) and nitrogen sources (used for amino acid production) should be considered when interpreting the δ15N value of leaf nitrogenous compounds