The Search for 'Evolution-Proof' Antibiotics. Issue 6 (June 2018)

• Record Type: Journal Article
• Authors: Bell, Graham; MacLean, Craig
• Is Part Of: Trends in microbiology. Volume 26:Issue 6(2018)
• Page Start: 471
• Page End: 483
• Publication Date: 2018-06
• Subjects: Microbiology -- Periodicals; Infection -- Periodicals; Virulence (Microbiology) -- Periodicals; Infection -- Periodicals; Microbiology -- Periodicals; Virulence -- Periodicals; Microbiologie -- Périodiques; Infection -- Périodiques; Virulence (Microbiologie) -- Périodiques; Infection; Microbiology; Virulence (Microbiology); 579
• DOI: 10.1016/j.tim.2017.11.005
• Languages: English
• ISSNs: 0966-842X

Abstract

Abstract : The effectiveness of antibiotics has been widely compromised by the evolution of resistance among pathogenic bacteria. It would be restored by the development of antibiotics to which bacteria cannot evolve resistance. We first discuss two kinds of 'evolution-proof' antibiotic. The first comprises literally evolution-proof antibiotics to which bacteria cannot become resistant by mutation or horizontal gene transfer. The second category comprises agents to which resistance may arise, but so rarely that it does not become epidemic. The likelihood that resistance to a novel agent will spread is evaluated here by a simple model that includes biological and therapeutic parameters governing the evolution of resistance within hosts and the transmission of resistant strains between hosts. This model leads to the conclusion that epidemic spread is unlikely if the frequency of mutations that confer resistance falls below a defined minimum value, and it identifies potential targets for intervention to prevent the evolution of resistance. Whether or not evolution-proof antibiotics are ever found, searching for them is likely to improve the deployment of new and existing agents by advancing our understanding of how resistance evolves. Trends: The efficacy of existing antibiotics has been compromised by the widespread evolution of resistance in pathogenic bacteria. We require new approaches to predict and prevent the evolution of new antibiotics that are being developed. Fluctuation tests that saturate the genome with mutations can be used to measure the potential for pathogens to evolve resistance by spontaneous mutation. Functional metagenomics and amplifying bioreactors can be used to identify environmental reservoirs of resistance genes. The epidemic spread of resistance can be stopped by preventing resistance evolution within hosts or transmission between hosts.