Multiobjective optimization has already been shown to be an appropriate tool to characterize and tune systems subject to multiple trade-offs among competing objectives. Here, we consider the dynamic regulation of a merging metabolic pathway motif. This motif appears in a wide range of metabolic engineering applications, including the production of phenylpropanoids highly appreciated by the pharma, nutraceutical and the cosmetic industries. We present an approach to use multiobjective optimization for the optimal tuning of the gene circuit parts composing the biomolecular controller and biosensor in the dynamic regulation of the metabolic pathway. We show how this approach can deal with the trade-offs between performance of the regulated pathway, robustness with respect to perturbations, and stability of the feedback loop. Our results suggest that the strategies for fine-tuning the tradeoffs among performance, robustness, and stability in dynamic pathway regulation are complex and it is not always possible to infer them by simple inspection. This renders the use of the multiobjective optimization methodology not only useful but necessary.
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