A discovery platform to identify inducible synthetic circuitry from varied microbial sources

Gut microbes encode a variety of systems for molecular sensing and controlling conditional gene expression within the mammalian gut. Synthetic biology approaches such as whole-cell biosensing and sense-and-respond therapeutics aim to tap into this vast sensing repertoire to drive clinical and pre-clinical applications. An ongoing constraint is the limited number of well-characterized inducible circuit components to specifically sense in vivo conditions of interest, such as disease. Here, we extend the flexibility and power of a biosensor screening platform using bacterial memory circuits encoded in a gut commensal E. coli. We construct libraries driven by potential sensory components derived from a combination of E. coli promoters or bacterial two-component systems (TCSs) sourced from diverse gut bacteria. Each is tagged with unique DNA barcodes using a pooled construction method. Using our pipeline, we evaluate sensor activity and performance heterogeneity across in vitro and in vivo conditions including using a mouse inflammation model. We demonstrate the methods ability to identify biosensors of interest, including the identification of unannotated TCSs. Following the optimisation of library construction, analysis, and delivery to account for the challenges of working with engineered bacteria within a conventional mammalian gut microbiome, we identify and validate several further biosensors of interest responding to the murine gut environment, and specifically during inflammatory conditions. This approach can be applied to transcriptionally activated sensing elements of any type and will allow for rapid development of new biosensors that can advance synthetic biology approaches for complex environments.