McClean, D. | bioRxiv Science

bioRxiv2018

Focussing on resistance to front-line drugs is the most effective way to combat the antimicrobial resistance crisis

In medical, scientific and political arenas relating to antimicrobial resistance (AMR) there is currently an intense focus on multi-drug resistant pathogens that render last-line antimicrobial treatments ineffective. We question the current emphasis of attention on resistance to last-line antimicrobials, arguing that tackling resistance to front-line antimicrobials has a greater public health benefit. Using AMR monitoring data on 25 drug-pathogen combinations from across Europe, here we show that the presence of front-line pathogen resistance initiates a cascade of resistance selection that ultimately leads to pathogen resistance to last-line antimicrobials. We then interrogate, by modelling the dynamics of resistance evolution, whether 3 key interventions in the strategic response to AMR are more effectively targeted at front-line or last-line treatment. We show that interventions that make front-line therapy more effective by use of antimicrobial adjuvants or front-line resistance diagnostics or by introduction of a novel, front-line antimicrobial all lead to a larger reduction in mortality and morbidity than the same interventions implemented in last-line therapy. Mass use of a newly discovered antimicrobial in front-line infection management to maximise its public health benefit is contrary to current policy but may provide valuable incentives for drug developers. We demonstrate that funding, publications, and attention to those publications do not reflect the importance of front-line antimicrobials and are disproportionately devoted to last-line antimicrobials that account for less than 10% of antimicrobial prescriptions. While studying resistance to last-line drugs is undoubtedly important, our work relays a strong message to public health agencies, funding bodies, and researchers that allocating resources to front-line infections can be a more effective way to combat the antimicrobial resistance crisis.

evolutionary biology↗

bioRxiv2018

Coping with multiple enemies: pairwise interactions do not predict evolutionary change in complex multitrophic communities

Predicting the ecological and evolutionary trajectories of populations in multispecies communities is one of the fundamental challenges in ecology. Many of these predictions are made by scaling patterns observed from pairwise interactions. Here, we show that the coupling of ecological and evolutionary outcomes is likely to be weaker in increasingly complex communities due to greater chance of life-history trait correlations. Using model microbial communities comprising a focal bacterial species (Bacillus subtilis), a bacterial competitor, protist predator and phage parasite, we found that increasing the number of enemies in a community had an overall negative effect on B. subtilis population growth. However, only the competitor imposed direct selection for B. subtilis trait evolution in pairwise cultures and this effect was weakened in the presence of other antagonists that had a negative effect on the competitor. In contrast, adaptation to parasites was driven indirectly by correlated selection where competitors had a positive and predators a negative effect. For all measured traits, selection in pairwise communities was a poor predictor of B. subtilis evolution in more complex communities. Together, our results suggest that coupling of ecological and evolutionary outcomes is interaction-specific and generally less evident in more complex communities where the increasing number of trait correlations could mask weak ecological signals.

evolutionary biology↗