Iterative Multi Level Calibration of Metabolic Networks

Title:Iterative Multi Level Calibration of Metabolic Networks

Volume: 11 Issue: 1

Author(s): Max Conway, Claudio Angione and Pietro Liò

Affiliation:

Keywords: Meta-analysis, gene expression engineering, multi-scale model, metabolic network exploration.

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.

Cite this article as:

Conway Max, Angione Claudio and Liò Pietro, Iterative Multi Level Calibration of Metabolic Networks, Current Bioinformatics 2016; 11 (1) . https://dx.doi.org/10.2174/1574893611666151203222505