Articles producció científica> Enginyeria Química

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

  • Identification data

    Identifier: imarina:5122832
    Authors:
    Guillén-Gosálbez G, Sorribas A
    Abstract:
    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 charact
  • Others:

    Author, as appears in the article.: Guillén-Gosálbez G, Sorribas A
    Department: Enginyeria Química
    e-ISSN: 1471-2105
    URV's Author/s: Guillen Gosalbez, Gonzalo
    Keywords: Yeast Predictive reconstruction Outer-approximation Optimization Law Gene-expression Evolution Design principles Cluster assembly metabolism Biochemical systems
    Abstract: 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.
    Thematic Areas: Structural biology Saúde coletiva Química Molecular biology Medicina veterinaria Medicina ii Medicina i Mathematical & computational biology Matemática / probabilidade e estatística Interdisciplinar Farmacia Engenharias iv Engenharias iii Computer science applications Ciências sociais aplicadas i Ciências biológicas iii Ciências biológicas ii Ciências biológicas i Ciências agrárias i Ciência da computação Biotecnología Biotechnology & applied microbiology Biodiversidade Biochemistry Biochemical research methods Applied mathematics
    licence for use: https://creativecommons.org/licenses/by/3.0/es/
    Author's mail: gonzalo.guillen@urv.cat
    Author identifier: 0000-0003-2923-1518
    Record's date: 2023-02-22
    Journal volume: 10
    Papper version: info:eu-repo/semantics/publishedVersion
    Link to the original source: https://bmcbioinformatics.biomedcentral.com/articles/10.1186/1471-2105-10-386
    Papper original source: Bmc Bioinformatics. 10
    APA: Guillén-Gosálbez G, Sorribas A (2009). Identifying quantitative operation principles in metabolic pathways: a systematic method for searching feasible enzyme activity patterns leading to cellular adaptive responses. Bmc Bioinformatics, 10(), -. DOI: 10.1186/1471-2105-10-386
    Licence document URL: https://repositori.urv.cat/ca/proteccio-de-dades/
    Article's DOI: 10.1186/1471-2105-10-386
    Entity: Universitat Rovira i Virgili
    Journal publication year: 2009
    Publication Type: Journal Publications
  • Keywords:

    Applied Mathematics,Biochemical Research Methods,Biochemistry,Biotechnology & Applied Microbiology,Computer Science Applications,Mathematical & Computational Biology,Molecular Biology,Structural Biology
    Yeast
    Predictive reconstruction
    Outer-approximation
    Optimization
    Law
    Gene-expression
    Evolution
    Design principles
    Cluster assembly metabolism
    Biochemical systems
    Structural biology
    Saúde coletiva
    Química
    Molecular biology
    Medicina veterinaria
    Medicina ii
    Medicina i
    Mathematical & computational biology
    Matemática / probabilidade e estatística
    Interdisciplinar
    Farmacia
    Engenharias iv
    Engenharias iii
    Computer science applications
    Ciências sociais aplicadas i
    Ciências biológicas iii
    Ciências biológicas ii
    Ciências biológicas i
    Ciências agrárias i
    Ciência da computação
    Biotecnología
    Biotechnology & applied microbiology
    Biodiversidade
    Biochemistry
    Biochemical research methods
    Applied mathematics
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