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New research in antibiotic resistance


Professor Peter Jeavons and recent DPhil graduate Daniel Nichol are co-authors of a Nature Communications paper which details a new approach for helping overcome antibiotic resistance. This approach combines mathematical modelling and biological experiments to determine the probability that second-line antibiotics will prove effective in treating an infection that has already gained resistance to an initial antibiotic treatment in a patient.

Antibiotic resistance represents a growing health crisis that necessitates the immediate discovery of novel treatment strategies. Developing entirely new drugs is difficult, time consuming and expensive, so it is important to try and identify ways in which existing drugs can be used more effectively. The identification of trade-offs in evolution forms the basis of an emerging strategy for combating drug resistance; prescribing sequences of drugs wherein the evolution of resistance to the first induces susceptibility to the next. Where this occurs, the first drug is said to induce collateral sensitivity in the second.

Experimental studies have attempted to identify drug pairs or sequences which exhibit this collateral sensitivity. However, drug pairs that are identified as collaterally sensitive will not necessarily induce collateral sensitivity each time they are prescribed, because evolution is driven by randomly arising mutations. Through mathematical modelling, the research team quantified the extent to which the existence of multiple evolutionary paths to resistance can lead to variable collateral sensitivities. These model predictions were verified using high-throughput experimental evolution of E. coli exposed to the widely-used antibiotic cefotaxime. By exposing 60 independently derived cefotaxime-resistant strains to a panel of follow-up drugs, the team found that the sensitivity profiles were indeed highly variable.

In the case of the antibiotic ticarcillin, another commonly prescribed antibiotic, the researchers found that the efficacy can increase by as much as three times when following cefotaxime. However, such collateral sensitivity was found to be rare and cross-resistance to be much more common, arising in 89% of the samples, and suggesting ticarcillin could prove a poor follow up drug. ‘These results clearly demonstrate the need to quantify the likelihoods of collateral sensitivity as a first step towards making informed decisions about antibiotic sequencing in the clinic’ said Daniel Nichol, the study’s lead author. ‘Unfortunately, the number of possible drug sequences is astronomical and direct testing of each sequence is likely intractable. We anticipate that improved theoretical models may be the only way to make the evolutionary predictions necessary to evaluate drug sequencing.’

The research team comprises Daniel Nichol, Peter Jeavons, Joseph Rutter, Christopher Bryant, Andrea M. Hujer, Sai Lek, Mark D. Adams, Alexander R. A. Anderson, Robert A. Bonomo and Jacob G. Scott

Read the paper here: