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Updated: Feb 4, 2026
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Design and Use of a Low Cost, Automated Morbidostat for Adaptive Evolution of Bacteria Under Antibiotic Drug Selection
Published on: September 27, 2016
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Evolution of bacteria specialization along an antibiotic dose gradient
Noémie Harmand1, Romain Gallet2, Guillaume Martin3
1CEFE, CNRS, Univ Montpellier Univ Paul Valéry Montpellier 3, EPHE, IRD Montpellier France.
Evolution Letters
|October 5, 2018
Summary
Antibiotic resistance evolves rapidly, with pathogens specializing to specific drug doses. Fitness costs vary with dose, increasing at higher concentrations and decreasing at lower ones.
Area of Science:
- Evolutionary Biology
- Microbial Ecology
- Antimicrobial Resistance
Background:
- Pathogen resistance to antibiotics and pesticides is a critical global challenge.
- Current models often simplify resistance evolution to treated vs. untreated environments, ignoring crucial dose gradients.
- The impact of varying antibiotic concentrations on resistance evolution and associated fitness trade-offs remains poorly understood.
Purpose of the Study:
- To investigate fitness trade-offs during experimental evolution of antibiotic resistance across a dose gradient.
- To determine if adaptation to low versus high antibiotic doses involves different phenotypic traits.
- To analyze the evolution of resistance costs over time at different antibiotic concentrations.
Main Methods:
- Experimental evolution of *Escherichia coli* resistant lines at various antibiotic concentrations for approximately 400 generations.
- Analysis of phenotypic traits and fitness costs associated with resistance at different antibiotic doses.
- Application of evolutionary ecology models to interpret observed adaptation patterns.
Main Results:
- Rapid evolution of dose-specific specialization occurred after initial resistance mutations.
- Pervasive fitness trade-offs were observed among different antibiotic evolution doses.
- Fitness costs of resistance were compensated over time at low doses but increased at high doses, following a linear trend with log-dose.
Conclusions:
- Adaptation to antibiotic resistance exhibits dose-specialization, consistent with adaptation across environmental gradients.
- Fitness costs of resistance evolve predictably along antibiotic dose gradients, explaining variability in cost evolution.
- Resistance management strategies require more realistic models that incorporate dose-dependent specialization.
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