Programmable Bacteria As Diagnostics of Gut Health

The mammalian gastrointestinal (GI) tract contains a dynamic community of symbiotic microbes that interact with the host to impact health, disease and metabolism. The gut microbiota are uniquely positioned to probe the GI environment, because they interact closely with the intestinal lumen as well as the host immune system. We constructed engineered bacteria to sense, remember, and report on the environmental conditions of the mammalian gut. Based on previous genetic memory systems, we constructed a modular, two-part system with a ‘trigger element’ that expresses the lambda cro gene in response to an environmental signal, and a ‘memory element’ derived from the cI/Cro transcriptional switch found in phage lambda. The memory element has an extremely stable cI state and a Cro state that is stable for many cell divisions. When engineered E. coli were administered to mice, and treated with anhydrotetracycline to trigger the memory element, all of the recovered E. coli switched from the cI state to the Cro state. However, those recovered from the untreated mice remained completely in the cI state. The trigger and memory elements were transferred from E. coli K12 to an uncharacterized E. coli strain isolated from the mouse. This newly engineered strain triggered in response to and maintained memory of stimulus exposure in vitro and within the mouse GI tract. Additionally, the engineered murine E. coli maintained a stable population within the mouse gut. Our engineered elements are very modular, therefore the probiotics can be easily modified to sense various diseases, such as Crohn's colorectal cancer, or the pathogens that cause C. diff infections as well as traveller's diarrhea. Therapeutic elements can also be added that would alleviate disease symptoms, or specifically kill pathogenic bacterial strains. This work demonstrates that E. coli can be engineered into living diagnostics capable of noninvasively probing the mammalian gut, and further lays a foundation for the use of synthetic genetic circuits as monitoring systems in complex, ill-defined environments.