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Content archived on 2024-06-18

Specificity of Antibiotic Resistance Evolution

Final Report Summary - SPECRESEVO (Specificity of Antibiotic Resistance Evolution)

This project investigated the specificity of genetic mechanisms associated with resistance evolution in experimental populations of bacteria exposed to antibiotics or viral parasites. The specific objectives and results were as follows:

1) Quantify the specificity of resistance mutations
Work performed: Antibiotic-resistant bacteria were isolated using conventional experimental protocols, before testing their effects on the bacterial phenotype across environments, represented by different types of laboratory growth medium, and across different genetic backgrounds, represented by bacteria with different evolutionary histories in terms of exposure to other antibiotics and growth in the laboratory.
Results: Resistance mutations can have very different effects on bacterial growth depending on environment ('genotype-by-environment interactions') and on genetic background ('epistasis').
Conclusions: predicting the spread or decline of antibiotic resistance in the absence of drugs requires that we understand variation of their phenotypic effects across genotypes and environments.

2) Identify genetic mechanisms of compensatory adaptation
Work performed: antibiotic-resistant and virus-resistant bacteria were experimentally evolved in the absence of antibiotics for hundreds of generations, before changes in their competitive ability relative to drug-sensitive bacteria and DNA sequence information were collected.
Results: Bacteria resistant to rifampicin can readily increase in fitness in the absence of antibiotics without reverting to drug sensitivity.
Conclusions: there are various mechanisms by which compensatory adaptation can proceed, and whole-genome sequencing will shed more light on the particular loci involved.

3) Quantify the specificity of compensatory mutations
Work performed: the phenotypic effects of costly alleles, including resistance mutations against other antibiotics, were quantified on different genetic backgrounds: antibiotic-resistant bacteria with and without mutations that increased their competitive fitness in the absence of antibiotics.
Results: Mutations that were beneficial on one antibiotic-resistant background could also reduce the cost of other mutations or even plasmids conferring resistance to other antibiotics, but this effect depended strongly on the particular mutations/plasmids involved.
Conclusions: Mutations that increase bacterial fitness in the laboratory have variable specificity across genetic backgrounds.

Potential impact of these results: this project has highlighted the role of experimental microbial evolution in research on antibiotic resistance, thereby connecting a key applied problem (drug resistance in pathogenic bacteria) with basic research.