Network analysis of toxin production in Clostridioides difficile identifies key metabolic dependencies
Fig 4
Modified MTA identifies key reaction knockouts and pathways for transformation from a high to low toxin state.
The mMTA algorithm runs a reaction KO simulation to optimize changes in reaction flux that transform the model from the reference metabolic state (high toxin) to the target metabolic state (low toxin). The reaction knockouts with the highest transformation scores are shown on the y-axis. The reactions whose flux changed under these KO conditions are shown on the x-axis. Successfully changed reactions are defined as those whose flux changed from the reference in the desired direction by a minimum threshold of significance (successful: dark blue; unsuccessful: light grey). The metabolic pathways for these reactions are shown beneath the clustering dendrogram at the top.