A Framework for Engineering Stress Resilient Plants Using Genetic Feedback Control and Regulatory Network Rewiring

Crop
disease leads to significant waste worldwide, both pre- and
postharvest, with subsequent economic and sustainability consequences.
Disease outcome is determined both by the plants’ response
to the pathogen and by the ability of the pathogen to suppress defense
responses and manipulate the plant to enhance colonization. The defense
response of a plant is characterized by significant transcriptional
reprogramming mediated by underlying gene regulatory networks, and
components of these networks are often targeted by attacking pathogens.
Here, using gene expression data from Botrytis cinerea-infected Arabidopsis plants, we develop a systematic
approach for mitigating the effects of pathogen-induced network perturbations,
using the tools of synthetic biology. We employ network inference
and system identification techniques to build an accurate model of
an Arabidopsis defense subnetwork that contains key
genes determining susceptibility of the plant to the pathogen attack.
Once validated against time-series data, we use this model to design
and test perturbation mitigation strategies based on the use of genetic
feedback control. We show how a synthetic feedback controller can
be designed to attenuate the effect of external perturbations on the
transcription factor CHE in our subnetwork. We investigate and compare
two approaches for implementing such a controller biologicallydirect
implementation of the genetic feedback controller, and rewiring the
regulatory regions of multiple genesto achieve the network
motif required to implement the controller. Our results highlight
the potential of combining feedback control theory with synthetic
biology for engineering plants with enhanced resilience to environmental
stress.