Figure 1

A schematic view of the framework to simulate an inhibitor's effect on bacterial growth. Given the inhibitor concentration [I], the Inhibition Model describes how the inhibitor affects the reaction flux of the reaction being inhibited (i.e., the target reaction). These effects are modeled via explicit constraints on the target reaction flux. Using these constraints and the constraints on substrate uptake rate , we analyzed the Metabolic Network to infer the biomass growth rate μ and substrate uptake rate v _C . Using the Population Growth Model, we related biomass growth rate μ and substrate uptake rate v _C to cell concentration [X]. We dynamically coupled the biomass growth rate and the diminished substrate concentration to develop a time-dependent model that dynamically infers cell concentration after the introduction of an inhibitor. Once these model components were specified, together with the initial substrate [C₀] and cell [X₀] concentrations in the growth medium, the calculations performed within this framework only required input in the form of a specific inhibitor concentration [I] to predict cellular growth.