A gene deletion experiment and its effect on cellular behavior can be simulated in a manner similar to the linear optimization of growth (or for any other objective function). The results can be used to guide the design of metabolic engineering strategies. Gene-reaction associations in the model describe the relationship between genes and their corresponding reactions; therefore, reactions can be removed from the model on the basis of individual gene deletions. The possible results from a simulation of a single gene deletion are unchanged maximal growth (nonessential), reduced maximal growth, or no growth (“sick” or lethal effect). The gene deletion analyses can be carried out genome-wide with the outcome tabulated to provide a comprehensive overview of gene essentiality for the system.

In certain cases, mutations in two genes produce a phenotype that is surprising in the light of each mutation’s individual effect. This phenomenon, which defines genetic interaction, can reveal functional relationships between genes and path­ways. For example, double mutants with surprisingly slow growth define syner­gistic interactions that can identify compensatory pathways or protein complexes (Harcombe et al. 2013). Like single gene deletions, double gene deletions can be simulated to encompass all possible double gene deletions in the network. This provides a powerful tool to simulate otherwise prohibitively difficult wet-bench genetic interaction experiments.