Antibiotic Selection Pressure Determination through Sequence-Based Metagenomics

Area of Science:

• Microbiology
• Genetics
• Pharmacology

Background:

• The human gut harbors a dynamic reservoir of antibiotic resistance genes (ARGs).
• Antimicrobial treatments significantly impact the gut resistome, promoting resistance gene transfer and selection.
• Understanding these impacts is crucial for managing antibiotic resistance.

Purpose of the Study:

• To monitor the development of intestinal ARGs during a 6-day ciprofloxacin treatment course in healthy individuals.
• To quantify the selection pressure exerted by ciprofloxacin on the intestinal resistome.
• To introduce a novel algorithm for analyzing antibiotic selection pressure in clinical settings.

Main Methods:

• Sequenced-based metagenomics and ARG quantification methods were employed.
• Fixed- and random-effect models were used to determine ARG abundance changes per defined daily dose of ciprofloxacin.
• Analysis focused on shifts in ARG composition and abundance.

Main Results:

• Ciprofloxacin treatment caused significant shifts in the intestinal resistome composition.
• Strong positive selection for class D beta-lactamases was observed in one individual, partly on mobile genetic elements.
• A trend towards negative selection for class A beta-lactamases was noted. ARG composition partially returned to baseline within 4 weeks post-treatment.

Conclusions:

• Antibiotic treatment profoundly affects the gut resistome, with varying selection pressures on different ARGs.
• A novel analysis algorithm can quantify antibiotic selection pressure, aiding in the choice of antimicrobial agents with lower selective impact.
• Minimizing selective pressure from antibiotics can reduce the spread of resistance and hospital-acquired infections.