Reinventing the AMR Wheel

Researchers from the University of Oxford have shown us, once again, that at the heart of scientific evolution lies the pursuit of challenge. Their aim? To redefine conventional understandings of antibiotic resistance in bacterial infections.

Antibiotic resistance poses an ever-increasing threat to global health, but scientists remain uncertain as to how within-host resistance develops. It is thought that pathogen populations are clonal within a host, and resistance arises due to de novo variant selection; however, the new study challenges this belief.

Analyzing samples collected from immunocompromised and critically ill patients before and after antibiotic treatment, the researchers tested whether resistance evolves more quickly in mixed-strain populations of Pseudomonas aeruginosa.  Contrary to popular belief, their findings suggest that patients commonly harbor multiple strains, with resistance emerging from pre-existing resistant strains, rather than new mutations.

“The key finding of this study is that resistance evolves rapidly in patients colonized by diverse Pseudomonas aeruginosa populations due to selection for pre-existing resistant strains,” said Craig MacLean, lead researcher and Professor from the University of Oxford’s Department of Biology. “The rate at which resistance evolves in patients varies widely across pathogens, and we speculate that high levels of within-host diversity may explain why some pathogens, such as Pseudomonas, rapidly adapt to antibiotic treatment.”

Yet, despite resistance emerging more quickly in mixed-strain infections, the results show it might  also lead to resistance becoming weaker if there’s a trade-off between resistance and growth rate. And that thought aligns with a growing body of literature showing that resistance genes carry fitness trade-offs that are stronger in mixed-strain populations than single-strain populations. The current research suggests that within-host diversity can drive the loss of resistance in the absence of antibiotic treatment.

The team suggests that studying within-host bacterial diversity may be important for predicting how likely a patient will respond to antibiotic treatment. MacLean concluded, “The diagnostic methods that we use to study antibiotic resistance in patient samples have changed very slowly over time, and our findings underscore the importance of developing new diagnostic methods that will make it easier to assess the diversity of pathogen populations in patient samples.”