Temporal variation in antibiotic environments slows down resistance evolution in pathogenic Pseudomonas aeruginosa

Area of Science:

• Microbiology
• Evolutionary Biology
• Public Health

Background:

• Antibiotic resistance poses a significant global public health threat.
• Developing novel treatment strategies is crucial to mitigate the rise of antibiotic resistance.
• Understanding resistance evolution dynamics is key to designing effective therapies.

Purpose of the Study:

• To evaluate the efficacy of sequential antibiotic treatment in decelerating resistance evolution.
• To investigate the impact of antibiotic order in sequential protocols on treatment outcomes.
• To identify evolutionary mechanisms underlying the observed treatment effects.

Main Methods:

• Conducted two independent laboratory-controlled evolution experiments using Pseudomonas aeruginosa PA14.
• Applied sequential treatment protocols with two pairs of clinically relevant antibiotics: doripenem/ciprofloxacin and cefsulodin/gentamicin.
• Utilized sublethal antibiotic dosages to observe resistance evolution over time.

Main Results:

• Sequential antibiotic application significantly decelerated resistance evolution compared to monotherapy.
• Sequential treatments led to enhanced bacterial population extinction, even at sublethal doses.
• An order effect was observed, with significant variation in long-term efficacy depending on the sequence of antibiotics administered.
• Asymmetric evolutionary constraints, where adaptation to one antibiotic hindered adaptation to another, were identified as a likely cause for the order effect.

Conclusions:

• Sequential antibiotic treatment is a promising strategy to slow down the evolution of antibiotic resistance.
• The order of antibiotic administration in sequential therapy critically influences treatment efficacy.
• Understanding asymmetric evolutionary constraints can inform the development of more robust and evolution-proof antimicrobial treatments.