Fig. 8: The genetic optimizer can be deployed to maximize cellular growth rate.
From: A blueprint for a synthetic genetic feedback optimizer
Detailed mathematical model and additional data are provided in Supplementary Section 3, together with simulation parameters in Supplementary Section 5. Blue curves indicate performance when SpoTH is exogenously optimized by adjusting the inducer concentration. Green and purple curves denote trajectories with zero and maximal induction of SpoTH. Closed loop performance is evaluated in the presence of stochastic noise impacting the kinetics of all species. Cellular stress is modulated via βp63. a Growth rate is negatively impacted by rising levels of the alarmone (p)ppGpp (p) as it downregulates the production of ribosomes (z). Cellular stress results in elevated RelA (r) expression, which upregulates the synthesis of (p)ppGpp via the increased production rate constant βp. Conversely, (p)ppGpp concentration can be decreased via SpoTH (s) by activating its expression either exogenously63 or by placing its promoter under the control of the regulator x. The dashed red flat headed arrows from SpoTH represent the load that SpoTH expression places on ribosomes as its mRNA is translated. b Expression of SpoTH results in sequestration of shared cellular resources, thus the metabolic burden due to SpoTH overexpression can counteract the positive impact of (p)ppGpp removal on growth rate, resulting in a non-monotonic relationship. c Closed loop performance is evaluated based on 100 independent simulations with random initial conditions during the second half of each simulation by considering the average of y and its standard deviation. Red curve and red shaded region denote the mean of these averages and standard deviations, respectively. d The optimizer successfully tracks the time-varying optimum in response to both abrupt and gradual changes in βp representing cellular stress. Red curves and shaded regions correspond to the mean and standard deviation of trajectories considering 100 independent simulations with random initial conditions. For individual trajectories, see Supplementary Fig. 17.
