Dynamic collateral sensitivity profiles highlight opportunities and challenges for optimizing antibiotic treatments.

Area of Science:

• Microbiology
• Evolutionary Biology
• Pharmacology

Background:

• Rising antimicrobial resistance necessitates novel therapeutic strategies.
• Evolution-based therapies, including collateral sensitivity, are being explored to combat resistance.
• Understanding the temporal dynamics of collateral effects is crucial for effective treatment.

Purpose of the Study:

• To characterize collateral sensitivity profiles over evolutionary time in *Enterococcus faecalis*.
• To investigate how resistance evolution influences susceptibility to other antibiotics.
• To inform the development of dynamic antimicrobial dosing strategies.

Main Methods:

• Laboratory evolution experiments using *Enterococcus faecalis*.
• Phenotypic characterization of 400 strain-antibiotic combinations across four evolutionary time points.
• Development of a stochastic mathematical model (Markov decision process) to simulate dynamic collateral profiles.

Main Results:

• Globally, collateral resistance initially dominates, shifting to collateral sensitivity with prolonged antibiotic selection.
• Individual bacterial populations exhibit idiosyncratic collateral trends, with varying sensitivity changes over time.
• Dynamic collateral sensitivity relationships necessitate time-dependent drug switching for optimal efficacy.

Conclusions:

• Antimicrobial resistance evolution is complex and time-dependent.
• Collateral effects are not static and require temporal monitoring.
• Dynamic dosing strategies informed by evolutionary trajectories are essential for effective antimicrobial therapy and resistance containment.