Mining Microbial Transcriptomes to Engineer Novel Cell-Based Biosensors in Gut-Resident Bacteria

The gastrointestinal tract is an environment rich with information pertaining to metabolism, immunity, and the microbiome — information that could prove critical for the design of live biotherapeutics and the diagnosis and routine monitoring of intestinal disorders. Engineered cell-based biosensors represent a new class of diagnostics capable of tapping into this abundance of molecular information and reporting on their environment. However, the development of functional biosensors in gut-resident bacteria has been limited by a lack of validated sensor systems. Here, a generalizable pipeline is presented that leverages bacterial transcriptional profiling to identify environment-responsive systems suitable for cell-based biosensor engineering. In vivo and in vitro transcriptomes were first mined to validate a defined microbial community (DMC) approach to sensor discovery. This approach was then applied to a dextran sulfate sodium (DSS)–induced colitis model, identifying several inflammation-associated sensor systems. Candidate systems were assembled into a barcoded library in Bacteroidales chassis and screened at high-throughput in vivo to identify responsive promoters. A unique ECF-type sigma factor operon, present in both Bacteroides thetaiotaomicron and Phocaeicola vulgatus, was highly responsive across multiple DSS-induced colitis models, including a recovery model in which biosensor output dynamically tracked disease progression and returned to baseline upon host recovery. In vitro characterization of the sensor system revealed ties to sphingolipid metabolism and membrane stress, suggesting the biosensor may detect early host-derived signals of epithelial disruption rather than inflammation itself. Together, this work establishes an in vivo–driven strategy for discovering functional biosensors in non-model gut-resident bacteria and highlights the value of mining native transcriptional responses to environmental perturbations for developing live cell diagnostics and sense-and-respond biotherapeutics.