Gut delivery of pentameric GLP-1 using genetically engineered Bacillus subtilis
Ningyuan Ye, Francesco Di PierroiD, Nicola ZerbinatiiD, Alexander BertuccioliiD, Chaorui DuaniD, Jingchen Xu, Ivan Paul Thaddeus AnterolaiD, Collins Chimezie, Jure Zupet, Jiahe LiiD
Abstract
Glucagon-like peptide-1 (GLP-1) receptor agonists and GLP-1 analogs are widely used for type 2 diabetes and weight management, but current approaches can be limited by manufacturing complexity, cost, formulation requirements, and the need for repeated administration. Living microbial delivery systems offer a potential strategy for sustained gastrointestinal production of therapeutic peptides, yet achieving stable expression, intestinal survival, and biologically relevant systemic exposure remains challenging. Here, we developed an engineered Bacillus subtilis (B. subtilis) spore-based platform for gastrointestinal delivery of pentameric GLP-1. By leveraging the stress resistance, storage stability, and genetic tractability of B. subtilis, we generated a chromosomally integrated strain that secretes a multimeric GLP-1 construct, which is processed in the intestine to release active GLP-1 monomers. Oral administration of engineered spores resulted in detectable serum GLP-1-related peptide signals in mice, accompanied by preliminary glucose-lowering activity in a fasting-refeeding test. In a longer-term study, engineered spore administration was associated with reduced body weight and adiposity in diet-induced obese mice, with semaglutide included as a positive pharmacologic benchmark. To improve translational suitability, we further generated a marker-free strain, which retained probiotic-relevant features of the parental strain, including gastrointestinal stress tolerance, epithelial cell adhesion, and antibiotic susceptibility. These findings establish proof-of-concept evidence that engineered spore-forming bacteria may serve as a scalable gastrointestinal peptide-delivery platform and support further evaluation of this approach in disease-relevant models of metabolic dysfunction.
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