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The fitness costs of antibiotic resistance mutations.

Melnyk AH, Wong A, Kassen R - Evol Appl (2014)

Bottom Line: In this review, we performed a meta-analysis to investigate the fitness costs associated with single mutational events that confer resistance.Generally, these mutations were costly, although several drug classes and species of bacteria on average did not show a cost.Further investigations into the rate and fitness values of compensatory mutations that alleviate the costs of resistance will help us to better understand both the emergence and management of antibiotic resistance in clinical settings.

View Article: PubMed Central - PubMed

Affiliation: Centre for Advanced Research in Environmental Genomics, Department of Biology, University of Ottawa Ottawa, ON, Canada.

ABSTRACT
Antibiotic resistance is increasing in pathogenic microbial populations and is thus a major threat to public health. The fate of a resistance mutation in pathogen populations is determined in part by its fitness. Mutations that suffer little or no fitness cost are more likely to persist in the absence of antibiotic treatment. In this review, we performed a meta-analysis to investigate the fitness costs associated with single mutational events that confer resistance. Generally, these mutations were costly, although several drug classes and species of bacteria on average did not show a cost. Further investigations into the rate and fitness values of compensatory mutations that alleviate the costs of resistance will help us to better understand both the emergence and management of antibiotic resistance in clinical settings.

No MeSH data available.


Related in: MedlinePlus

The level of resistance conferred by a mutation is negatively correlated with its’ fitness in the absence of the antibiotic (r2 = 0.228). Different symbols are associated with different classes of antibiotic.
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fig05: The level of resistance conferred by a mutation is negatively correlated with its’ fitness in the absence of the antibiotic (r2 = 0.228). Different symbols are associated with different classes of antibiotic.

Mentions: We regressed MIC against relative fitness to test the prediction that high levels of resistance impose greater fitness costs than lower levels of resistance (Fig.5). The relative fitness of a resistance mutation is negatively correlated with the fold-increase in MIC conferred by the mutation (Fig.5, t126 = −6.21, P < 0.0001), with fold-increase in MIC accounting for 22.8% of the variation in fitness (F1,126 = 38.6, P < 0.0001). A subset of data was used for this analysis because seven studies did not measure MIC (Schrag and Perott 1996; Criswell et al. 2006; Gagneux et al. 2006; Balsalobre and de la Campa 2008; Hao et al. 2009; Trindade et al. 2009; Borrell et al. 2013). Although it would be of interest to perform separate regressions for each class of antibiotic to see if the correlation holds across different mechanisms of action, for many of the drug classes, sample sizes are too small to permit reliable regression coefficients to be estimated.


The fitness costs of antibiotic resistance mutations.

Melnyk AH, Wong A, Kassen R - Evol Appl (2014)

The level of resistance conferred by a mutation is negatively correlated with its’ fitness in the absence of the antibiotic (r2 = 0.228). Different symbols are associated with different classes of antibiotic.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4380921&req=5

fig05: The level of resistance conferred by a mutation is negatively correlated with its’ fitness in the absence of the antibiotic (r2 = 0.228). Different symbols are associated with different classes of antibiotic.
Mentions: We regressed MIC against relative fitness to test the prediction that high levels of resistance impose greater fitness costs than lower levels of resistance (Fig.5). The relative fitness of a resistance mutation is negatively correlated with the fold-increase in MIC conferred by the mutation (Fig.5, t126 = −6.21, P < 0.0001), with fold-increase in MIC accounting for 22.8% of the variation in fitness (F1,126 = 38.6, P < 0.0001). A subset of data was used for this analysis because seven studies did not measure MIC (Schrag and Perott 1996; Criswell et al. 2006; Gagneux et al. 2006; Balsalobre and de la Campa 2008; Hao et al. 2009; Trindade et al. 2009; Borrell et al. 2013). Although it would be of interest to perform separate regressions for each class of antibiotic to see if the correlation holds across different mechanisms of action, for many of the drug classes, sample sizes are too small to permit reliable regression coefficients to be estimated.

Bottom Line: In this review, we performed a meta-analysis to investigate the fitness costs associated with single mutational events that confer resistance.Generally, these mutations were costly, although several drug classes and species of bacteria on average did not show a cost.Further investigations into the rate and fitness values of compensatory mutations that alleviate the costs of resistance will help us to better understand both the emergence and management of antibiotic resistance in clinical settings.

View Article: PubMed Central - PubMed

Affiliation: Centre for Advanced Research in Environmental Genomics, Department of Biology, University of Ottawa Ottawa, ON, Canada.

ABSTRACT
Antibiotic resistance is increasing in pathogenic microbial populations and is thus a major threat to public health. The fate of a resistance mutation in pathogen populations is determined in part by its fitness. Mutations that suffer little or no fitness cost are more likely to persist in the absence of antibiotic treatment. In this review, we performed a meta-analysis to investigate the fitness costs associated with single mutational events that confer resistance. Generally, these mutations were costly, although several drug classes and species of bacteria on average did not show a cost. Further investigations into the rate and fitness values of compensatory mutations that alleviate the costs of resistance will help us to better understand both the emergence and management of antibiotic resistance in clinical settings.

No MeSH data available.


Related in: MedlinePlus