Skip to content
2000
Volume 11, Issue 1
  • ISSN: 1574-8936
  • E-ISSN: 2212-392X

Abstract

Frameworks for metabolic engineering have been successfully applied in combination with pre- and post-processing algorithms on genome-wide metabolic models. However, genetic engineering methods with a particular focus on understanding results from multiple perspectives and combining automated and human design are still lacking. To this end, we adopt a multi-objective genetic design technique to find the optimal gene expression levels in genome-scale metabolic reconstructions. Then, we analyse the optimized network by introducing a new multi-omic, multi-level post-processing and visualization procedure, Metabex, which uses Cytoscape for network visualization. These two components are connected together to form a feedback loop that establishes a continual process of machine optimization and human analysis and guidance. To benchmark our framework, we optimize two species of Geobacter for electricity production and biomass synthesis; we achieve increases in electricity production for only a slight decrease in biomass. Many regulatory strategies contributed to this value, locally and globally. For instance, a direct, local strategy was a down-regulation of Cytochrome C Oxidase, while there was simultaneously a global reduction in cofactor and prosthetic group biosynthesis. Finally, we discuss multiple applications of our tool, including model exploration, model engineering, comparative modelling, meta-analysis and model refinement.

Loading

Article metrics loading...

/content/journals/cbio/10.2174/1574893611666151203222505
2016-02-01
2025-06-14
Loading full text...

Full text loading...

/content/journals/cbio/10.2174/1574893611666151203222505
Loading
This is a required field
Please enter a valid email address
Approval was a Success
Invalid data
An Error Occurred
Approval was partially successful, following selected items could not be processed due to error
Please enter a valid_number test