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Antibiotic interactions that select against resistance.

Remy Chait1, Allison Craney, Roy Kishony

  • 1Department of Systems Biology, Harvard Medical School, 200 Longwood Avenue, Boston, Massachusetts 02115, USA.

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|April 6, 2007
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Summary

Certain drug combinations can surprisingly select against antibiotic resistance, even at low doses. This discovery challenges our understanding of how resistance evolves and offers new strategies for antimicrobial drug development.

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Area of Science:

  • Microbiology
  • Evolutionary Biology
  • Pharmacology

Background:

  • Multidrug combinations are crucial for fighting antibiotic resistance and understanding microbial evolution.
  • While effects on bacterial growth are known, impact on selection between sensitive and resistant strains is less understood.
  • Typically, drugs favor resistant mutants over sensitive ones.

Purpose of the Study:

  • To investigate the impact of multidrug combinations on differential selection between sensitive and resistant bacterial populations.
  • To explore if drug combinations can invert the typical selection advantage for resistance.
  • To understand the implications for the evolution of antibiotic resistance.

Main Methods:

  • Direct competition assays were performed using doxycycline-resistant and doxycycline-sensitive Escherichia coli.
  • Hyper-antagonistic drug combinations were utilized.
  • Experiments were conducted at sublethal drug concentrations.

Main Results:

  • A class of hyper-antagonistic drug combinations was found to invert differential selection, favoring sensitive bacteria over resistant ones.
  • This inversion of selection occurred even against the drug's own resistance allele.
  • The effect was largely independent of the specific resistance mechanism and maintained wild-type inhibition.

Conclusions:

  • Drug interactions can create a previously unappreciated feature in the fitness landscape of resistance evolution.
  • A trade-off exists between drug interaction potency and selection pressure on resistant populations.
  • Findings suggest novel strategies for designing antimicrobial therapies that disfavor resistance.
  • Results provide insights into microbial ecology and evolution under drug pressure.