Frontiers in Plant Science (Apr 2022)
Specific Bacterial Pathogen Phytosensing Is Enabled by a Synthetic Promoter-Transcription Factor System in Potato
Abstract
Phytosensors are genetically engineered plant-based sensors that feature synthetic promoters fused to reporter genes to sense and report the presence of specific biotic and abiotic stressors on plants. However, when induced reporter gene output is below detectable limits, owing to relatively weak promoters, the phytosensor may not function as intended. Here, we show modifications to the system to amplify reporter gene signal by using a synthetic transcription factor gene driven by a plant pathogen-inducible synthetic promoter. The output signal was unambiguous green fluorescence when plants were infected by pathogenic bacteria. We produced and characterized a phytosensor with improved sensing to specific bacterial pathogens with targeted detection using spectral wavelengths specific to a fluorescence reporter at 3 m standoff detection. Previous attempts to create phytosensors revealed limitations in using innate plant promoters with low-inducible activity since they are not sufficient to produce a strong detectable fluorescence signal for standoff detection. To address this, we designed a pathogen-specific phytosensor using a synthetic promoter-transcription factor system: the S-Box cis-regulatory element which has low-inducible activity as a synthetic 4xS-Box promoter, and the Q-system transcription factor as an amplifier of reporter gene expression. This promoter-transcription factor system resulted in 6-fold amplification of the fluorescence after infection with a potato pathogen, which was detectable as early as 24 h post-bacterial infection. This novel bacterial pathogen-specific phytosensor potato plant demonstrates that the Q-system may be leveraged as a powerful orthogonal tool to amplify a relatively weak synthetic inducible promoter, enabling standoff detection of a previously undetectable fluorescence signal. Pathogen-specific phytosensors would be an important asset for real-time early detection of plant pathogens prior to the display of disease symptoms on crop plants.
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