Literature DB >> 12783489

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

Julio Vera1, Pedro de Atauri, Marta Cascante, Néstor V Torres.   

Abstract

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. Copyright 2003 Wiley Periodicals, Inc. Biotechnol Bioeng 83: 335-343, 2003.

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Year:  2003        PMID: 12783489     DOI: 10.1002/bit.10676

Source DB:  PubMed          Journal:  Biotechnol Bioeng        ISSN: 0006-3592            Impact factor:   4.530


  14 in total

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Journal:  Math Biosci       Date:  2016-08-30       Impact factor: 2.144

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

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Journal:  PLoS One       Date:  2012-09-20       Impact factor: 3.240

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

Authors:  Carlos Pozo; Alberto Marín-Sanguino; Rui Alves; Gonzalo Guillén-Gosálbez; Laureano Jiménez; Albert Sorribas
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7.  Multi-objective optimization of enzyme manipulations in metabolic networks considering resilience effects.

Authors:  Wu-Hsiung Wu; Feng-Sheng Wang; Maw-Shang Chang
Journal:  BMC Syst Biol       Date:  2011-09-19

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

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Journal:  BMC Bioinformatics       Date:  2009-11-24       Impact factor: 3.169

9.  Integrating systemic and molecular levels to infer key drivers sustaining metabolic adaptations.

Authors:  Pedro de Atauri; Míriam Tarrado-Castellarnau; Josep Tarragó-Celada; Carles Foguet; Effrosyni Karakitsou; Josep Joan Centelles; Marta Cascante
Journal:  PLoS Comput Biol       Date:  2021-07-23       Impact factor: 4.475

10.  Optimization of biotechnological systems through geometric programming.

Authors:  Alberto Marin-Sanguino; Eberhard O Voit; Carlos Gonzalez-Alcon; Nestor V Torres
Journal:  Theor Biol Med Model       Date:  2007-09-26       Impact factor: 2.432

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