Mining Microbial Transcriptomes to Engineer Cell-Based Bacterial Biosensors in Gut-Resident Bacteroidaceae

Abstract

The gastrointestinal tract is rich in metabolic, immune, and microbiome-derived signals that can inform the design of live biotherapeutics and diagnosis of intestinal disorders. Engineered cell-based biosensors can tap into this molecular information and report on their environment, yet their development in gut-resident symbionts has been limited by a lack of validated sensor systems. Here, we present a generalizable pipeline that leverages bacterial transcriptional profiling to identify environment-responsive systems for biosensor engineering. Candidate Sensors Systems (CSSs) mined from healthy, disease, and in vitro transcriptomes were assembled into a barcoded library in Bacteroidaceae chassis and screened in high-throughput in vivo to identify responsive promoters. A unique Bacteroidales ECF-type sigma factor operon with ties to sphingolipid metabolism and flux was highly responsive in chemically-induced colitis models. The biosensor responded robustly to disease and returned to baseline upon recovery, establishing an in vivo-driven strategy for discovering functional biosensors in non-model gut-resident bacteria.