Sequence-Based Network Completion Reveals the Integrality of Missing Reactions in Metabolic Networks [Metabolism]

June 3rd, 2015 by Krumholz, E. W., Libourel, I. G. L.

Genome-scale metabolic models are central in connecting genotypes to metabolic phenotypes. However, even for well-studied organisms such as Escherichia coli, draft networks do not contain a complete biochemical network. Missing reactions are referred to as gaps. These gaps need to be filled to enable functional analysis, and gap-filling choices influence model predictions. To investigate if functional networks existed where all gap-filling reactions were supported by sequence similarity to annotated enzymes, four draft networks were supplemented with all reactions from the Model SEED database for which minimal sequence similarity was found in their genomes.. Quadratic programming revealed that the number of reactions that could partake in a gap-filling solution was vast: 3270 in the case of E. coli, where 72% of the metabolites in the draft network could connect a gap-filling solution. Nonetheless, no network could be completed without the inclusion of orphaned enzymes, suggesting that parts of the biochemistry integral to biomass precursor formation are uncharacterized. But, many gap-filling reactions were well-determined, and the resulting networks showed improved prediction of gene essentiality compared to networks generated through canonical gap-filling. In addition, gene-essentiality predictions that were sensitive to poorly determined gap-filling reactions were of poor quality, suggesting that damage to the network structure resulting from the inclusion of erroneous gap-filling reactions may be predictable.