GENETIC STRATEGIES FOR DEVELOPMENT OF EFFICIENT BACTERIAL WHOLE – CELL BIOSENSOR

Abstract

The burgeoning issue of antibiotic resistance is driving research towards finding new alternatives for antibiotics. Plant secondary metabolites are touted as attractive therapeutic alternatives in the development of an arsenal against bacterial pathogens. These metabolites have versatile activities as they are involved in the defense against bacteria, fungi, and insects; thus, leading to their exploration as antibacterial, antifungal, and insecticides. Synthetic biology approaches are becoming the method of choice for expressing plant secondary metabolites in microbial strains due to their rapid growth rate and large-scale production abilities. To follow the production of these metabolites in microbial cells, it is important to develop biosensing devices that are sensitive to the formation and accumulation of these compounds. Genetically encoded biosensors can be of immense use for real-time monitoring of the plant metabolites produced in microbial strains. Currently, few protein sensor-regulator pairs exist for plant metabolite detection. Hence there is a pressing need to develop sensors for the production, optimization, and sensing of plant secondary metabolites. In our first objective, we constructed a battery of biosensors containing fluorescent transcriptional bioreporters of stress-responsive genes to understand the response of bacteria against antibacterial plant secondary metabolites. Later, an expanded panel of E.coli knockout mutants was utilized to understand the genetic basis of bacterial killing and to enhance the biosensor sensitivity towards antibacterial metabolites as well. Our results suggest that transcriptional pattern-based response generated through GFP (green fluorescence protein), when screened across a battery of knockout mutants, has the potential to detect different classes of plant secondary metabolites showing antibacterial properties. Besides, we also report a novel biosensor based on yqhD – an oxidative stress-responsive genetic element for the specific detection of cinnamaldehyde in plant secondary metabolites with an impressive limit of detection (20ppm) and wide dynamic range (20ppm -160 ppm).