摘要：AbstractExternal perturbations affecting gene regulatory networks, such as pathogen/virus attacks, can lead to adverse effects on the phenotype of the biological system. In this paper, we propose a systematic approach to mitigate the effect of such perturbations that can be implemented using the tools of synthetic biology. We use system identification techniques to build accurate models of an example gene regulatory network from time-series data, and proceed to identify the kernel architecture of the network, which is defined as the minimal set of interactions needed to reproduce the wild type temporal behaviour. The kernel architecture reveals four key pathways in the network which allow us to investigate a number of different mitigation strategies in the event of external perturbations. We show that while network reoptimisation can reduce the impact of perturbations, combining network rewiring with a synthetic feedback control loop allows the effect of the perturbation to be completely eliminated. The proposed approach highlights the potential of combining feedback control theory with synthetic biology for developing more resilient biological systems.
