Biomedical subjects

Néstor V Torres

Publications and source records attributed to Néstor V Torres.

5 recordsLinked to original sources

PubMed2004

Dynamics of sulfur amino acids in mammalian brain: assessment of the astrocytic-neuronal cysteine interaction by a mathematical hybrid model.

A mathematically hybrid model was used to analyze three mechanisms by which cysteine could be produced in the brain to be used as preferential substrate in the synthesis of neuronal glutathione. In that way, the fluxes of sulfur-compounds at the brain-blood barrier were integrated with their transport in astrocytes and neurons, and with their metabolism in astrocytes. We concluded that cysteine, in contrast with its precursor cystine, would not be taken up from the blood at the blood-brain barrier, but instead it must be lost continuously from astrocytes. Cysteine efflux is produced because the uptake of cystine in astrocytes is much greater than their cysteine demand to synthesize glutathione, hypotaurine and taurine. Once in the interstitial parenchyma, cysteine would be taken for the neurons, as backwardly by the endothelial cells. Remarkably, a close sulfur-macro balance can be maintained only if the surplus of the produced cysteine is transferred from the endothelial cells to the blood together with significant amounts of other sulfur-compounds, probably taurine and hypotaurine. In addition, the results obtained shown that alternative mechanisms of cysteine generation (i.e., nonenzymatic-thiol-disulfide exchange reaction, enzymatic cleavage of the glutathione effluxed from astrocytes) are not quantitatively significant under physiological conditions, in situ.

Animals↗

PubMed2003

Multicriteria optimization of biochemical systems by linear programming: application to production of ethanol by Saccharomyces cerevisiae.

In this study we present a method for simultaneous optimization of several metabolic responses of biochemical pathways. The method, based on the use of the power law formalism to obtain a linear system in logarithmic coordinates, is applied to ethanol production by Saccharomyces cerevisiae. Starting from an experimentally based kinetic model, we translated it to its power law equivalent. With this new model representation, we then applied the multiobjective optimization method. Our intent was to maximize ethanol production and minimize each of the internal metabolite concentrations. To ensure cell viability, all optimizations were carried out under imposed constraints. The different solutions obtained, which correspond to alternative patterns of enzyme overexpression, were implemented in the original model. We discovered few discrepancies between the S-system-optimized steady state and the corresponding optimized state in the original kinetic model, thus demonstrating the suitability of the S-system representation as the basis for the optimization procedure. In all optimized solutions, the ATP level reached its maximum and any increase in its activity positively affected the optimization process. This work illustrates that in any optimization study no single criteria is of general application being the multiobjective and constrained task the proper way to address it. It is concluded that the proposed multiobjective method can serve to carry out, in a single study, the general pattern of behavior of a given metabolic system with regard to its control and optimization.

Algorithms↗

PubMed2003

Optimization of biochemical systems by linear programming and general mass action model representations.

A new method is proposed for the optimization of biochemical systems. The method, based on the separation of the stoichiometric and kinetic aspects of the system, follows the general approach used in the previously presented indirect optimization method (IOM) developed within biochemical systems theory. It is called GMA-IOM because it makes use of the generalized mass action (GMA) as the model system representation form. The GMA representation avoids flux aggregation and thus prevents possible stoichiometric errors. The optimization of a system is used to illustrate and compare the features, advantages and shortcomings of both versions of the IOM method as a general strategy for designing improved microbial strains of biotechnological interest. Special attention has been paid to practical problems for the actual implementation of the new proposed strategy, such as the total protein content of the engineered strain or the deviation from the original steady state and its influence on cell viability.

Biochemical Phenomena↗

PubMed2002

Modeling, optimization and experimental assessment of continuous L-(-)-carnitine production by Escherichia coli cultures.

In a previous paper Cánovas et al. (Biotechnol Bioeng 2002;77:764-775) presented a model for L-(-)-carnitine production using Escherichia coli O44 K74, in a cell-recycle bioreactor for the biotransformation of crotonobetaine into L-carnitine. In this work we optimize this biotechnological setup and experimentally verify the predicted optimal parameter profiles. Provided with a reliable and robust S-system description of the cell-bioreactor combined system, we applied the Indirect Optimization Method described by Torres et al. (Biotechnol Bioeng 1997;55(5):758-772; Food Technol Biotechnol 1998;36(3):177-184). This optimization approach provides different parameter value profiles, all of which are compatible with the cell physiology and the bioreactor operating conditions, that yield increased rates of L-(-)-carnitine production. Three parameters were seen to be of critical importance for maximizing L-(-)-carnitine production: the dilution rate, the initial crotonobetaine concentration, and the carnitine dehydratase activity. When the first two were changed in the experimental setup, there was a 74% increase in the L-(-)-carnitine production rate, performance that was in close agreement with the predictions of the model. In accordance with the optimized solution, a further improvement (90% increase in the L-(-)-carnitine production rate) could be attained by over-expressing up to 5 times the carnitine dehydratase basal activity. Thus the optimization approach shown herein provides experimental evidence of a new strategy which demonstrates the possible variables that can be subjected to modifications compatible with the cell physiology and bioreactor operating conditions, and which are able to yield increased rates of L-(-)-carnitine production.

Alcohol Oxidoreductases↗

PubMed2002

Modelling, steady state analysis and optimization of the catalytic efficiency of the triosephosphate isomerase.

In the present work we have modelled and optimized the reaction mechanism of the triose phosphate isomerase (TIM) enzyme (E.C. 5.3.1.1). For this purpose we have used an approach that combines the S-system representation within the power law formalism and linear programming techniques. By this means we have explored those rate constants whose alterations are likely to improve the catalytic efficiency of the enzyme and investigated the available room for optimization in different metabolic conditions. The role and plausibility of the different types of mutations on the evolution of this enzyme have also been considered. Steady state sensitivity analysis was carried out and a new set of aggregated logarithmic gains was defined in order to quantify the responses of the system to changes in groups of rate constants that could be explained in terms of mutations affecting the catalytic properties of the enzyme. Evaluation of these logarithmic gains at different levels of saturation and disequilibrium ratios enabled us to reach conclusions about the meaning and role of the diffusion limitation terms. The catalytic efficiency of the monoenzymatic system was optimized through changes in the kinetic rate constants within different sets of restrictions ranging from thermodynamic or kinetic to evolutionary ones. Results showed that, at very different conditions, there is still room for improvement in the TIM enzyme. Thus, in a wide range of metabolically significant values of the disequilibrium ratio there is a minimal variation in the optimal profile that yields 2.1 times the velocity of the basal states. Though most of this increase is accounted for by the increase of the second order constants (that could have already reached a theoretical maximum) significant increases (20%) in catalytic efficiencies are obtained by changes of the internal steps only. Besides these new findings our optimization approach has been able to reproduce results obtained with other approaches.

Catalysis↗