Genome-scale in silico atpE gene knockout in Escherichia coli could drive novel biological discovery

One of the applications of E. coli genome-scale model is in the biological discovery of underground metabolic functions of partially characterized genes and/or enzymes. Here we report for the first time, a failed prediction of atpE gene knockout of no growth in the most recent E. coli reconstruction iJ01366 model, and a positive experimental growth on glucose, enabling a model-driven biological discovery of the underground metabolic function of this gene in E. coli metabolism. These findings unfolded what could be described as either scope gaps in the reconstruction or true biological gaps (knowledge gaps) on the missing atpE gene function in E. coli metabolism. This study informs other studies that the gaps could be pursued into the E. coli metabolism, leading to a modeldriven discovery in the future. This can be achieved by using gap filling algorithms (such as GrowMatch, SMILEY and OMNI) in combination with 13C labeling experiments and/or high throughput tools (such as phenotypic microarrays and robotic instruments) to update and uncover the missing atpE gene functions under different genetic and/or environmental conditions.