DYNAMIC FLUX BALANCE ANALYSIS FOR PREDICTING GENE OVEREXPRESSION EFFECTS IN BATCH CULTURES
| Autor: | Jorge Mario Gómez Ramírez, Carol Milena Barreto-Rodriguez, Harold Molina-Bulla, Jessica Paola Ramirez-Angulo, Luke E. K. Achenie, Andrés Fernando González Barrios |
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| Rok vydání: | 2014 |
| Předmět: |
chemistry.chemical_classification
Ecology Applied Mathematics In silico Metabolic network General Medicine Biology medicine.disease_cause Agricultural and Biological Sciences (miscellaneous) Flux balance analysis chemistry.chemical_compound Enzyme chemistry Biochemistry medicine Glycerol Escherichia coli Gene Pyruvate kinase |
| Zdroj: | Journal of Biological Systems. 22:327-338 |
| ISSN: | 1793-6470 0218-3390 |
| DOI: | 10.1142/s0218339014500107 |
| Popis: | The advent of numerous technological platforms for genome sequencing has led to increasing understanding and construction of metabolic networks. A popular system engineering strategy is used to analyze microbial metabolic networks is flux balance analysis (FBA). In recent times, there has been a lot of interest in the study of the metabolic network dynamics when genes are overexpressed in the system. Herein, an optimization framework, which employs dynamic flux balance analysis (DFBA) is proposed for predicting ethanol concentration profiles in glycerol fermentations using Escherichia coli. In silico results were experimentally validated by overexpressing alcohol/acetaldehyde dehydrogenase adhE, pyruvate kinase pykF, pyruvate formate-lyase pflB and isoleucine-valine enzymes ilvC and llvL. |
| Databáze: | OpenAIRE |
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