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Utilizing evolutionary interactions to limit multidrug resistance

Periodic Reporting for period 3 - LimitMDR (Utilizing evolutionary interactions to limit multidrug resistance)

Reporting period: 2018-05-01 to 2019-10-31

Antibiotic resistance is an increasing global public health concern that is limiting our ability to treat bacterial infections. Current problems of antibiotic resistance result from a reduced development of truly novel antibiotics over that past several decades. Yet, during this time bacteria have continued to evolve resistance in response to treatment. A long term solution to the antibiotic resistance problem must involve both improved prudence in antibiotic consumption as well as development of novel types of antibiotics. Yet, such efforts will take political will and time to develop. In the meantime, we must use the antibiotics we have at our disposal in the most efficient way possible. Recently, it has been discovered that evolution of antibiotic resistance in bacteria can be associated with increased sensitivity towards other antibiotics. This is referred to as collateral sensitivity. The current project is focused on elucidating the collateral sensitivities of antibiotic resistant bacteria belonging to the important human pathogens E.coli and P.aeruginosa. Through a thorough characterisation of the molecular mechanisms and evolutionary trajectories that lead to collateral sensitivity and antibiotic resistance we shall develop strategies to rationally treat these infections. These results will serve to improve the use of the current arsenal of drugs for the benefit of patients suffering from multidrug resistant infections.
So far the project has focused on the evolution of antibiotic resistance and collateral sensitivity in E.coli and P.aeruginosa from a phenotypic perspective. An initial project characterized key biomarkers of collateral sensivitiy in P.aeruginosa and linked these to clinical isolates. This work was recently published in Cell (Imamovic et al. 2018). Additional work has elucidated the dynamics of mutation accumulation in evolving populations of E.coli (Hickman et. al. 2017) and has also assessed different strategies for effective laboratory adaptive evolution (Jahn et al. 2017).
The project has already advanced substantially beyond state of the art by demonstrating clear links between collateral sensitivity interactions identified in laboratory evolution and in a chronically infection patients suffering from cystic fibrosis. It is the ambition to build further on this data to create a framework for rational treatment strategies of such chronic infections. Furthermore, it is expected that the project shall elucidate molecular mechanisms of collateral sensitivity.