Large-Scale Screening of E. coli Promoters for Small Molecule Biosensor Development

The field of synthetic biology makes significant contributions to healthcare, environmental engineering, and technology through the manipulation of cellular macromolecules and whole organisms. Oftentimes, these advancements are dependent upon biosensors to report on an activity of interest within a cell or to detect extracellular cues and report on them in a measurable way. This project undertaken as part of iGEM 2024 (Internationally Genetic Engineered Machines Competition 2024) centered around the choice of 10 small molecules related to environmental and human health with the goal of developing transcriptional biosensors to report on their concentrations. Each molecule was screened against a library of over 2000 promoter-GFP constructs in search of promoters responsive to each molecule. Further, a Deep Learning model was used to predict active promoter-molecule pairs and in silico putative hits from the screen were analyzed with molecular docking. While no robust biosensor hits were found for the molecules of interest, our work demonstrates a useful pipeline for further small molecule biosensor development.