Background

Antibiotic resistance in bacterial infections is a growing threat to public health. Recent evidence shows that when exposed to stressful conditions, some bacteria perform higher rates of horizontal gene transfer and mutation, and thus acquire antibiotic resistance more rapidly.

Methods

We incorporate this new notion into a mathematical model for the emergence of antibiotic multi-resistance in a hospital setting.

Results

We show that when stress has a considerable effect on genetic variation, the emergence of antibiotic resistance is dramatically affected. A strategy in which patients receive a combination of antibiotics (combining) is expected to facilitate the emergence of multi-resistant bacteria when genetic variation is stress-induced. The preference between a strategy in which one of two effective drugs is assigned randomly to each patient (mixing), and a strategy where only one drug is administered for a specific period of time (cycling) is determined by the resistance acquisition mechanisms. We discuss several features of the mechanisms by which stress affects variation and predict the conditions for success of different antibiotic treatment strategies.

Conclusions

These findings should encourage research on the mechanisms of stress-induced genetic variation and establish the importance of incorporating data about these mechanisms when considering antibiotic treatment strategies.

Background

Homing endonucleases (HEases) are a large and diverse group of site-specific DNAases. They reside within self-splicing introns and inteins, and promote their horizontal dissemination. In recent years, HEases have been the focus of extensive research due to their promising potential use in gene targeting procedures for the treatment of genetic diseases and for the genetic engineering of crop, animal models and cell lines.

Results

Using mathematical analysis and computational modeling, we present here a novel account for the evolution and population dynamics of HEase genes (HEGs). We describe HEGs as paradoxical selfish elements whose long-term persistence in a single population relies on low transmission rates and a positive correlation between transmission efficiency and toxicity.

Conclusion

Plausible conditions allow HEGs to sustain at high frequency through long evolutionary periods, with the endonuclease frequency being either at equilibrium or periodically oscillating. The predictions of our model may prove important not only for evolutionary theory but also for gene therapy and bio-engineering applications of HEases.