Abstract
Genetic algorithms, which have been used successfully in chemical engineering in recent years, enable us to probe deeper into the influences of alternate metabolic pathways on multi-product synthesis. In this chapter, optimization of enzyme activities in Escherichia coli for multiple objectives is proposed and explored using a detailed, non-linear dynamic model for central carbon metabolism in E. coli and a non-dominated sorting genetic algorithm for multi-objective optimization (MOO). A wide range of optimal enzyme activities regulating the amino acids synthesis is successfully obtained for selected, integrated pathway scenarios. The predicted potential improvements due to the optimized metabolic pathway recipe using the MOO strategy are highlighted and discussed in detail.
| Original language | English |
|---|---|
| Title of host publication | Multi-objective Optimization |
| Subtitle of host publication | Techniques And Applications In Chemical Engineering (With Cd-rom) |
| Publisher | World Scientific Publishing Co. |
| Pages | 401-427 |
| Number of pages | 27 |
| ISBN (Electronic) | 9789812836526 |
| DOIs | |
| State | Published - 1 Jan 2008 |
| Externally published | Yes |
Keywords
- Metabolic pathway recipe
- Mixed integer MOO (MIMOO)
- Multi-product microbial cell factory
- Pareto-optimal set