Antimicrobial resistance (AMR) poses a critical threat to global health, rendering traditional antibiotics increasingly ineffective and amplifying the urgency for innovative solutions. Among promising alternatives, synthetic biology emerges as a powerful tool to combat AMR. This work proposes an innovative strategy based on engineering bacteriophages to deliver CRISPR interference (CRISPRi) systems into antibiotic-resistant pathogens to precisely silence target resistance genes. A comprehensive mathematical model is developed and simulated to capture the dynamics of phage-mediated CRISPRi delivery. By explicitly incorporating mutations that affect CRISPRi functionality, the study evaluates system performance and its potential for long-term therapeutic efficacy. This model serves as a critical framework for optimizing future CRISPRi-based interventions and advancing synthetic biology-driven approaches to tackle AMR.Clinical relevance - This paper provides a quantitative modeling framework to evaluate key parameters affecting engineered phage therapy efficiency, supporting rational design and phage posology optimization.

Modeling of Phage-Mediated CRISPRi System to Inhibit Antibiotic Resistances in Bacteria

Cimolato C.;Letrari S.;Del Favero S.;Schenato L.;Bellato M.
2025

Abstract

Antimicrobial resistance (AMR) poses a critical threat to global health, rendering traditional antibiotics increasingly ineffective and amplifying the urgency for innovative solutions. Among promising alternatives, synthetic biology emerges as a powerful tool to combat AMR. This work proposes an innovative strategy based on engineering bacteriophages to deliver CRISPR interference (CRISPRi) systems into antibiotic-resistant pathogens to precisely silence target resistance genes. A comprehensive mathematical model is developed and simulated to capture the dynamics of phage-mediated CRISPRi delivery. By explicitly incorporating mutations that affect CRISPRi functionality, the study evaluates system performance and its potential for long-term therapeutic efficacy. This model serves as a critical framework for optimizing future CRISPRi-based interventions and advancing synthetic biology-driven approaches to tackle AMR.Clinical relevance - This paper provides a quantitative modeling framework to evaluate key parameters affecting engineered phage therapy efficiency, supporting rational design and phage posology optimization.
2025
Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
47th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2025
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11577/3589915
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