Eco-evolutionary dynamics of experimental Pseudomonas aeruginosa populations under oxidative stress

Within-host environments are likely to present a challenging and stressful environment for opportunistic pathogenic bacteria colonizing from the external environment. How populations of pathogenic bacteria respond to such environmental challenges and how this varies between strains is not well understood. Oxidative stress is one of the defences adopted by the human immune system to confront invading bacteria. In this study, we show that strains of the opportunistic pathogenic bacterium Pseudomonas aeruginosa vary in their eco-evolutionary responses to hydrogen peroxide stress. By quantifying their 24 h growth kinetics across hydrogen peroxide gradients we show that a transmissible epidemic strain isolated from a chronic airway infection of a cystic fibrosis patient, LESB58, is much more susceptible to hydrogen peroxide than either of the reference strains, PA14 or PAO1, with PAO1 showing the lowest susceptibility. Using a 12 day serial passaging experiment combined with a mathematical model, we then show that short-term susceptibility controls the longer-term survival of populations exposed to subinhibitory levels of hydrogen peroxide, but that phenotypic evolutionary responses can delay population extinction. Our model further suggests that hydrogen peroxide driven extinctions are more likely with higher rates of population turnover. Together, these findings suggest that hydrogen peroxide is likely to be an effective defence in host niches where there is high population turnover, which may explain the counter-intuitively high susceptibility of a strain isolated from chronic lung infection, where such ecological dynamics may be slower

Mathematical modelling for antibiotic resistance control policy: do we know enough?

Background: Antibiotics remain the cornerstone of modern medicine. Yet there exists an inherent dilemma in their use: we are able to prevent harm by administering antibiotic treatment as necessary to both humans and animals, but we must be mindful of limiting the spread of resistance and safeguarding the efficacy of antibiotics for current and future generations. Policies that strike the right balance must be informed by a transparent rationale that relies on a robust evidence base. Main text: One way to generate the evidence base needed to inform policies for managing antibiotic resistance is by using mathematical models. These models can distil the key drivers of the dynamics of resistance transmission from complex infection and evolutionary processes, as well as predict likely responses to policy change in silico. Here, we ask whether we know enough about antibiotic resistance for mathematical modelling to robustly and effectively inform policy. We consider in turn the challenges associated with capturing antibiotic resistance evolution using mathematical models, and with translating mathematical modelling evidence into policy. Conclusions: We suggest that in spite of promising advances, we lack a complete understanding of key principles. From this we advocate for priority areas of future empirical and theoretical research

Opposing effects of final population density and stress on Escherichia coli mutation rate

Evolution depends on mutations. For an individual genotype, the rate at which mutations arise is known to increase with various stressors (stress-induced mutagenesis-SIM) and decrease at high final population density (density-associated mutation-rate plasticity-DAMP). We hypothesised that these two forms of mutation-rate plasticity would have opposing effects across a nutrient gradient. Here we test this hypothesis, culturing Escherichia coli in increasingly rich media. We distinguish an increase in mutation rate with added nutrients through SIM (dependent on error-prone polymerases Pol IV and Pol V) and an opposing effect of DAMP (dependent on MutT, which removes oxidised G nucleotides). The combination of DAMP and SIM results in a mutation rate minimum at intermediate nutrient levels (which can support 7 × 10  cells ml ). These findings demonstrate a strikingly close and nuanced relationship of ecological factors-stress and population density-with mutation, the fuel of all evolution

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

The Properties of Adaptive Walks in Evolving Populations of Fungus

A novel method to infer the number and fitness effect of beneficial mutations reveals that the bulk of adaptive evolution is attributable to a few mutations with variable effects on fitness

Population genetics of rifampicin-resistant pseudomonas aeruginosa

Antibiotic resistance is generally associated with a cost in terms of reduced competitive fitness in the absence of antibiotics. Despite this `cost of resistance', the cessation of antibiotic treatment does not result in significant reductions in the prevalence of resistance. The maintenance of resistance, in spite of the costs, has been attributed to the rarity of reversion mutations, relative to compensatory mutations at other loci in the genome. However, the large size of bacteria populations, and the potential for migration, suggest that reversion mutations should occasionally be introduced to resistant populations. In this thesis, I show that additional mechanisms can prevent fixation of reversion mutations even if they do occur. Using an experimental evolution approach, with rifampicin resistance in Pseudomonas aeruginosa as a model system, I measured the costs of resistance in several environments and followed the adaptive dynamics of resistant populations where a sensitive lineage had invaded by migration. The results suggest that several additional mechanisms contribute to the maintenance of antibiotic resistance. Most rifampicin resistance mutations are not unconditionally costly in all environments, suggesting that migration between environments could maintain a resistant reservoir population. In environments where resistance is initially costly, the fixation of a revertant is not guaranteed, even if introduced through migration. Revertant fixation was impeded or prevented by clonal interference from adaptation in the resistant strain. Revertants that did successfully replace the resistant strain were forced to adapt to do so. Contrary to assumptions in the existing literature, fitness in the resistant strains was not recovered by general compensatory mutations, but instead by adaptive mutations specific to the environment. The data challenge several assumptions about the maintenance of antibiotic resistance: that resistance mutations are always costly, that the rarity of back mutations prevents the reversion of resistance, and that resistant strains recover fitness by compensatory mutations.</p

Data from: Environmental pleiotropy and population demography 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

Population genetics of rifampicin-resistant pseudomonas aeruginosa

Antibiotic resistance is generally associated with a cost in terms of reduced competitive fitness in the absence of antibiotics. Despite this `cost of resistance', the cessation of antibiotic treatment does not result in significant reductions in the prevalence of resistance. The maintenance of resistance, in spite of the costs, has been attributed to the rarity of reversion mutations, relative to compensatory mutations at other loci in the genome. However, the large size of bacteria populations, and the potential for migration, suggest that reversion mutations should occasionally be introduced to resistant populations. In this thesis, I show that additional mechanisms can prevent fixation of reversion mutations even if they do occur. Using an experimental evolution approach, with rifampicin resistance in Pseudomonas aeruginosa as a model system, I measured the costs of resistance in several environments and followed the adaptive dynamics of resistant populations where a sensitive lineage had invaded by migration. The results suggest that several additional mechanisms contribute to the maintenance of antibiotic resistance. Most rifampicin resistance mutations are not unconditionally costly in all environments, suggesting that migration between environments could maintain a resistant reservoir population. In environments where resistance is initially costly, the fixation of a revertant is not guaranteed, even if introduced through migration. Revertant fixation was impeded or prevented by clonal interference from adaptation in the resistant strain. Revertants that did successfully replace the resistant strain were forced to adapt to do so. Contrary to assumptions in the existing literature, fitness in the resistant strains was not recovered by general compensatory mutations, but instead by adaptive mutations specific to the environment. The data challenge several assumptions about the maintenance of antibiotic resistance: that resistance mutations are always costly, that the rarity of back mutations prevents the reversion of resistance, and that resistant strains recover fitness by compensatory mutations