Abstract

Escherichia coli genome-scale metabolic models (GEMs) have been published with ability to predict metabolic engineering capabilities that could be consistent with experimental measurements. However, the GEMs have limited scope, and the models are of two types, metabolism models (M-model), and metabolism and gene expression (ME-model) that could guide the constructions of proof-of-principle strains of particularly E. coli bacterium that may find applications in metabolic engineering strategies, synthetic biology [1], and beyond. GEMs have been clearly established to be capable of predicting metabolic engineering capabilities and could sometime lead to biological discoveries for missing reactions and/or missing gene functions [2-4]. In addition, systems metabolic engineering has proof useful with the use of GEMs where time consuming experimental trial and error was shortened by predicting engineering strategies using GEMs. Although sometimes prediction could fail to agree with experimental data, but in that circumstances missing knowledge can be uncovered and gaps in the reconstruction can therefore be bridged leading to novel biological discoveries [3,4].