Environmental pleiotropy and demographic history direct adaptation under antibiotic selection

Evolutionary rescue following environmental change requires mutations permitting population growth in the new environment. If change is severe enough to prevent most of the population reproducing, rescue becomes reliant on mutations already present. If change is sustained, the fitness effects in both environments, and how they are associated-termed 'environmental pleiotropy'-may determine which alleles are ultimately favoured. A population's demographic history-its size over time-influences the variation present. Although demographic history is known to affect the probability of evolutionary rescue, how it interacts with environmental pleiotropy during severe and sustained environmental change remains unexplored. Here, we demonstrate how these factors interact during antibiotic resistance evolution, a key example of evolutionary rescue fuelled by pre-existing mutations with pleiotropic fitness effects. We combine published data with novel simulations to characterise environmental pleiotropy and its effects on resistance evolution under different demographic histories. Comparisons among resistance alleles typically revealed no correlation for fitness-i.e., neutral pleiotropy-above and below the sensitive strain's minimum inhibitory concentration. Resistance allele frequency following experimental evolution showed opposing correlations with their fitness effects in the presence and absence of antibiotic. Simulations demonstrated that effects of environmental pleiotropy on allele frequencies depended on demographic history. At the population level, the major influence of environmental pleiotropy was on mean fitness, rather than the probability of evolutionary rescue or diversity. Our work suggests that determining both environmental pleiotropy and demographic history is critical for predicting resistance evolution, and we discuss the practicalities of this during in vivo evolution

Identifying and exploiting genes that potentiate the evolution of antibiotic resistance

There is an urgent need to develop novel approaches for predicting and preventing the evolution of antibiotic resistance. Here, we show that the ability to evolve de novo resistance to a clinically important β-lactam antibiotic, ceftazidime, varies drastically across the genus Pseudomonas. This variation arises because strains possessing the ampR global transcriptional regulator evolve resistance at a high rate. This does not arise because of mutations in ampR. Instead, this regulator potentiates evolution by allowing mutations in conserved peptidoglycan biosynthesis genes to induce high levels of β-lactamase expression. Crucially, blocking this evolutionary pathway by co-administering ceftazidime with the β-lactamase inhibitor avibactam can be used to eliminate pathogenic P. aeruginosa populations before they can evolve resistance. In summary, our study shows that identifying potentiator genes that act as evolutionary catalysts can be used to both predict and prevent the evolution of antibiotic resistance

The construction of small-scale, quasi-mechanistic spatial models of insect energetics in habitat restoration: A case study of beetles in Western Australia

Aim: The management and restoration of ecological processes mediated by biotic interactions is now broadly advocated and may be achieved by targeting restoration towards key agents. Although theoretically examined, a practical approach to incorporating the physiology and energetics of insects into restoration planning is poorly articulated. I aimed to provide a case study using the thermal biology and energetics of beetles to identify the distribution of habitat suitability in a large restoration landscape. Location: South-west Western Australia. Methods: I modelled the thermal performance of metabolic rates of thirteen Phyllococerus purpurascens, and twenty Colpochila “species 2,” measured repeatedly at seven temperatures between five and 40°C using flow-through respirometry. Thermal constraints were used to inform a species distribution model of each species at extremely high spatiotemporal resolution, projecting the physiological state of each species for every hour at 5″ resolution across a 152-km2 restoration landscape in south-western Australia to estimate the habitat suitability for beetles. Results: Both species’ metabolic rates increased exponentially to a critical point, followed by rapid decline, but the thermal tolerance thresholds were different for each species. Both had strikingly high-thermal tolerance relative to their nocturnal habits and local climatic conditions. The models of beetle prevalence estimated both species to be active and able to access the entire project area for all of the austral spring, summer and autumn. Main conclusions: The results reported here suggest ubiquitous habitat suitability for flower beetles in disturbed landscapes. Incorporation of similar mechanistic models for other species at high resolution offers potential insight into habitat suitability for a broad range of ectotherms

Prediction of antibiotic resistance : time for a new preclinical paradigm?

Predicting the future is difficult, especially for evolutionary processes that are influenced by numerous unknown factors. Still, this is what is required of drug developers when they assess the risk of resistance arising against a new antibiotic candidate during preclinical development. In this Opinion article, we argue that the traditional procedures that are used for the prediction of antibiotic resistance today could be markedly improved by including a broader analysis of bacterial fitness, infection dynamics, horizontal gene transfer and other factors. This will lead to more informed preclinical decisions for continuing or discontinuing the development of drug candidates