Figure 5. Numerical modeling and experimental validation of changes in tuning behavior as a function of 6AU concentration.

We simulated the gene expression dynamics of cells containing URA3 under the control of a non-native promoter, when exposed to uracil-depletion stress with varying concentrations of the URA3 inhibitor 6AU. The model employed is equivalent to that in Figure 2A, with k = 0.1, η = 0.1, and the target expression profile equal to that for the case shown in Figure 2B except for the case of the gene corresponding to URA3, whose optimal value was set to 80. (A) Typical trajectories of URA3 expression levels for a cell in the presence of low (blue) or high (red) 6AU concentrations, which alter the minimum URA3 expression level at which fitness-directed stochastic tuning can occur. We show results for a starting URA3 level [URA3]=25, with optimal fitness occurring at [URA3]=80. The initial and optimal URA3 levels are shown as gray lines. (B) Violin plots of the distributions of the minimum time required to reach a URA3+state (defined as [URA3]>75) in the presence of increasing concentrations of 6AU (implemented as higher thresholds of URA3 required for stochastic tuning to become active). In each case distributions reflect 50 independent trajectories simulated at each 6AU level. (C) Experimental validation of model predictions. Cells were grown in liquid ura-/6AU1 media (-URA) for 3–4 hr and then had the expression of fluorescent reporter proteins compared (using flow cytometry) with those of the equivalent cells grown in SC+glu (+URA) over the same time period. Values show log₂ fold changes from SC+glu to ura-/6AU1; error bars show bootstrap-based 95% confidence intervals. Biological replicates performed on different days are shown side by side; the order of replicates is matched for URA3-mRuby and DHFR-GFP.