Modeling of Conjugative- and Phage-Mediated CRISPR-Based System Against Antimicrobial Resistant Bacteria

Area of Science:

• Synthetic biology applications in medicine
• Microbial genetics and evolution
• Systems biology modeling

Background:

• Antimicrobial resistance (AMR) is a growing global health crisis, reducing antibiotic efficacy.
• Novel therapeutic strategies are urgently needed to overcome drug-resistant pathogens.
• Synthetic biology offers innovative approaches to combat AMR.

Purpose of the Study:

• To assess a synthetic biology strategy using engineered bacteria and phages against AMR.
• To evaluate targeted gene silencing via CRISPR interference as an alternative to direct bacterial killing.
• To explore the implications of mutations on therapeutic system robustness.

Main Methods:

• Developed a comprehensive mathematical model for engineered delivery systems (probiotic bacteria, phages) and antimicrobial actuators (CRISPR systems).
• Modeled the dynamics of antibiotic-resistant bacteria competing with probiotics in a host environment.
• Incorporated parameters for mutations affecting actuator functionality and simulated their impact on therapeutic performance.

Main Results:

• Simulations demonstrated how actuator efficiency and pathogen mutations influence long-term resistance gene suppression.
• Model insights guided optimal therapeutic design choices by revealing system robustness.
• Identified engineered phages and CRISPR interference as highly promising interventions.

Conclusions:

• The modeling framework accurately predicts and optimizes engineered therapies against resistant pathogens.
• Established a quantitative basis for designing and optimizing engineered phage- and bacterial-based therapies.
• Advanced the application of synthetic biology for combating antimicrobial resistance.