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Iterative Multi Level Calibration of Metabolic Networks

[ Vol. 11 , Issue. 1 ]


Max Conway, Claudio Angione and Pietro Liò   Pages 93 - 105 ( 13 )


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.


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


University of Cambridge Computer Laboratory.

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