850 resultados para Metabolic programing
Resumo:
Epidemiological studies demonstrate an association between insulin resistance, hypertension and cardiovascular morbidity. In addition to its metabolic effects, insulin also has important cardiovascular actions. The sympathetic nervous system and the nitric oxide-l-arginine pathway have emerged as central players in the mediation of these actions. Over the past decade, the underlying mechanisms and the factors that may govern the interaction between insulin and these two major cardiovascular regulatory systems have been studied extensively in healthy people and insulin-resistant individuals. Here we summarize the current understanding and gaps in knowledge on these interactions. We propose that a genetic and/or acquired defect of nitric oxide synthesis could represent a central defect triggering many of the metabolic, vascular and sympathetic abnormalities characteristic of insulin-resistant states, all of which may predispose to cardiovascular disease.
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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.
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PURPOSE: This study aimed to determine the neuro-mechanical and metabolic adjustments in the lower limbs induced by the running anaerobic sprint test (the so-called RAST). METHODS: Eight professional football players performed 6 × 35 m sprints interspersed with 10 s of active recovery on artificial turf with their football shoes. Sprinting mechanics (plantar pressure insoles), root mean square activity of the vastus lateralis (VL), rectus femoris (RF), and biceps femoris (BF) muscles (surface electromyography, EMG) and VL muscle oxygenation (near-infrared spectroscopy) were monitored continuously. RESULTS: Sprint time, contact time and total stride duration increased from the first to the last repetition (+17.4, +20.0 and +16.6 %; all P < 0.05), while flight time and stride length remained constant. Stride frequency (-13.9 %; P < 0.001) and vertical stiffness decreased (-27.2 %; P < 0.001) across trials. Root mean square EMG activities of RF and BF (-18.7 and -18.1 %; P < 0.01 and 0.001, respectively), but not VL (-1.2 %; P > 0.05), decreased over sprint repetitions and were correlated with the increase in running time (r = -0.82 and -0.90; both P < 0.05). Together with a better maintenance of RF and BF muscles activation levels over sprint repetitions, players with a better repeated-sprint performance (lower cumulated times) also displayed faster muscle de- (during sprints) and re-oxygenation (during recovery) rates (r = -0.74 and -0.84; P < 0.05 and 0.01, respectively). CONCLUSION: The repeated anaerobic sprint test leads to substantial alterations in stride mechanics and leg-spring behaviour. Our results also strengthen the link between repeated-sprint ability and the change in neuromuscular activation as well as in muscle de- and re-oxygenation rates.
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The guava (Psidium guajava L.) cv. Paluma has been cultivated in São Francisco Valley, Northeastern of Brazil, for in natura consumption and processing purposes. In spite of its importance, there are few scientific knowledge regarding guava physiology, nutrition, irrigation and fertigation. The objective of this work was to evaluate the effect of weather conditions and different concentrations of N and K applied by fertigation in foliar contents of reducing sugars, total soluble sugars, starch, sucrose, amino acids, and proteins. The field experiment was carried out at Bebedouro Experimental Field and the biochemical evaluations at the Laboratory of Seed and Plant Physiology, both located at Embrapa Semi-Árido, Petrolina-PE. The doses of 200 g N and 100 g K2O; 400 g N and 200 g K2O; 600 g N and 300 g K2O; and 800 g N and 400 g K2O per plant were applied in an experiment field. The experimental design was totally randomized blocks, with four treatments and five blocks. The weather conditions influenced the plant photosynthesis, which affects the plants metabolism. Guava presented specific responses to N and K fertigation for each parameter evaluated. The weather conditions during the evaluation period influenced guava responses to N and K fertigation.
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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.
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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.
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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.
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(13)C magnetic resonance spectroscopy (MRS) combined with the administration of (13)C labeled substrates uniquely allows to measure metabolic fluxes in vivo in the brain of humans and rats. The extension to mouse models may provide exclusive prospect for the investigation of models of human diseases. In the present study, the short-echo-time (TE) full-sensitivity (1)H-[(13)C] MRS sequence combined with high magnetic field (14.1 T) and infusion of [U-(13)C6] glucose was used to enhance the experimental sensitivity in vivo in the mouse brain and the (13)C turnover curves of glutamate C4, glutamine C4, glutamate+glutamine C3, aspartate C2, lactate C3, alanine C3, γ-aminobutyric acid C2, C3 and C4 were obtained. A one-compartment model was used to fit (13)C turnover curves and resulted in values of metabolic fluxes including the tricarboxylic acid (TCA) cycle flux VTCA (1.05 ± 0.04 μmol/g per minute), the exchange flux between 2-oxoglutarate and glutamate Vx (0.48 ± 0.02 μmol/g per minute), the glutamate-glutamine exchange rate V(gln) (0.20 ± 0.02 μmol/g per minute), the pyruvate dilution factor K(dil) (0.82 ± 0.01), and the ratio for the lactate conversion rate and the alanine conversion rate V(Lac)/V(Ala) (10 ± 2). This study opens the prospect of studying transgenic mouse models of brain pathologies.
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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
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In order to better understand the fate and activity of bacteria introduced into contaminated material for the purpose of enhancing biodegradation rates, we constructed Sphingomonas wittichii RW1 variants with gene reporters interrogating dibenzofuran metabolic activity. Three potential promoters from the dibenzofuran metabolic network were selected and fused to the gene for enhanced green fluorescent protein (EGFP). The stability of the resulting genetic constructions in RW1 was examined, with plasmids based on the broad-host range vector pME6012 being the most reliable. One of the selected promoters, upstream of the gene Swit_4925 for a putative 2-hydroxy-2,4-pentadienoate hydratase, was inducible by growth on dibenzofuran. Sphingomonas wittichii RW1 equipped with the Swit_4925 promoter egfp fusion grew in a variety of non-sterile sandy microcosms contaminated with dibenzofuran and material from a former gasification site. The strain also grew in microcosms without added dibenzofuran but to a very limited extent, and EGFP expression indicated the formation of consistent small subpopulations of cells with an active inferred dibenzofuran metabolic network. Evidence was obtained for competition for dibenzofuran metabolites scavenged by resident bacteria in the gasification site material, which resulted in a more rapid decline of the RW1 population. Our results show the importance of low inoculation densities in order to observe the population development of the introduced bacteria and further illustrate that the limited availability of unique carbon substrate may be the most important factor impinging growth.