Engineering Autoregulation in Enzymatic Degradation Based Systems for Robust Dynamics and Improved Host Capacity

Fast dynamics in synthetic genetic networks require fast enzymatic degradation which is not rate-limited by cell division. In bacteria, the SsrA tags are commonly used to target proteins to the native-to-E. coli ClpXP protease. However, expression of multiple SsrA-tagged proteins results in ‘enzymatic queuing’ due to their competition for a finite amount of protease. This leads to post-translational coupling of proteins or even worst to overloading of native proteases like ClpXP that lead to pathological phenotypes. To address the latter, we have designed, modelled and experimentally implemented a protease controller that a) sense the varying load imposed on proteases, such as the native ClpXP or heterologous mf-Lon, by varying amounts of tagged proteins and b) automatically adjust the total level of proteases to compensate and alleviate the effects of the post-translational coupling between the tagged proteins. The basic network comprises a self-regulated protease, realised by introducing a self-targeting tag on the protease. Our results suggest that when the levels of tagged proteins are varied, in the closed loop network, the protease levels auto-adjust to maintain a constant degradation rate. Therefore, the tagged proteins exhibit negligible sensitivities with respect to each other and result to a significantly more robust system to transient perturbations. Interestingly, in the conditions were the enzymatic degradation rate was maintained high, we have observed a significant benefit in host fitness, increased growth rates and protein production rate. We are currently investigating further whether this can be attributed to a recycling effect for shared cellular resources like amino acids.