Optimization of the bioconversion of glycerol to ethanol using Escherichia coli by implementing a bi-level programming framework for proposing gene transcription control strategies based on genetic algorithms

作     者：Carol Milena Barreto-Rodriguez Jessica Paola Ramirez-Angulo Jorge Mario Gomez-Ramirez Luke Achenie Andres Fernando Gonzalez-Barrios 

作者机构：Grupo de Diseno de Productos y Procesos(GDPP)Department of Chemical EngineeringUniversidad de los AndesBogotaColombia Multiscale and Multiphysics Modeling LabDepartment of Chemical EngineeringVirginia Polytechnic Institute and State UniversityBlacksburgVirginia 

出 版 物：《Advances in Bioscience and Biotechnology》 (生命科学与技术进展（英文）)

年 卷 期：2012年第3卷第4期

页      面：336-343页

学科分类：1002[医学-临床医学] 100214[医学-肿瘤学] 10[医学] 

基　　金：the support of the National BioResource Project(NIG,Japan):E.coli Strain for kindly providing us with the Keio Collection using for our experimental section Also this work is funded by Vicerrectoria de investigaciones at Universidad de los Andes 

主　　题：Bi-level Optimization Escherichia coli Metabolic Flux Analysis Genetic Algorithm 

摘      要：In silico approaches for metabolites optimization have been derived from the flood of sequenced and annotated genomes. However, there exist still numerous degrees of freedom in terms of optimization algorithm approaches that can be exploited in order to enhance yield of processes which are based on biological reactions. Here, we propose an evolutionary approach aiming to suggest different mutant for augmenting ethanol yield using glycerol as substrate in Escherichia coli. We found that this algorithm, even though is far from providing the global optimum, is able to uncover genes that a global optimizer would be incapable of. By over-expressing accB, eno, dapE, and accA mutants in ethanol production was augmented up to 2 fold compared to its counterpart E. coli BW25113.