Sign in
Synthetic BiologyACS Synthetic Biology
Peer-reviewed journal article

Diagnostic and Therapeutic Microbial Circuit with Application to Intestinal Inflammation

Liana N. MerkiD, Andrey ShuriD, Smrutiti JenaiD, Javier Muñoz BrionesiD, Douglas K. BrubakeriD, Richard M. MurrayiD, Leopold N. GreeniD

Abstract

Bacteria genetically engineered to execute defined therapeutic and diagnostic functions in physiological settings can be applied to colonize the human microbiome, providing in situ surveillance and conditional disease modulation. However, many engineered microbes can only respond to single-input environmental factors, limiting their tunability, precision, and effectiveness as living diagnostic and therapeutic systems. For engineering microbes to improve complex chronic disorders such as inflammatory bowel disease, the bacteria must respond to combinations of stimuli in the proper context and time. This work implements a previously characterized split activator AND logic gate in the probiotic Escherichia coli strain Nissle 1917. Our system can respond to two input signals: the inflammatory biomarker tetrathionate and a second input signal, anhydrotetracycline (aTc), for manual control. We report 4-6 fold induction with a minimal leak when the two chemical signals are present. We model the AND gate dynamics using chemical reaction networks and tune parameters in silico to identify critical perturbations that affect our circuits selectivity. Finally, we engineer the optimized AND gate to secrete a therapeutic anti-inflammatory cytokine IL-22 using the hemolysin secretion pathway in the probiotic E. coli strain. We used a germ-free transwell model of the human gut epithelium to show that our engineering bacteria produce similar host cytokine responses compared to pure cytokine. Our study presents a scalable workflow to engineer cytokine-secreting microbes. It demonstrates the feasibility of IL-22 derived from probiotic E. coli Nissle with minimal off-target effects in a gut epithelial context.

PDFDOI

02 /Specification & Classification

Click any tag to browse matching papers

Reproducibility ledger

Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.

Sign in to file a reproducibility report.

Similarity Map
SelectedSame fieldCross-field
THISWeibel '24Riglar '16Yu '25Zhu '25Zou '25Praveschoti '18
73% semantic matchSynthetic Biology
Nathalie Weibel, Martina Curcio, Atilla Schreiber+17 more·ACS Synthetic Biology·Aug 8, 2024· 36 citations