Does High-Dose Antimicrobial Chemotherapy Prevent the Evolution of Resistance?

Day, Troy; Read, Andrew F.

doi:10.1371/journal.pcbi.1004689

Cited by 129 publications

(198 citation statements)

References 62 publications

(83 reference statements)

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“…This could have implications for predicting the direct and knockon effects of antibiotic dosing on treatment outcomes (e.g., see discussion in ref. 67).…”

Section: Discussionmentioning

confidence: 99%

Antibiotic stress selects against cooperation in the pathogenic bacterium Pseudomonas aeruginosa

Vasse

Noble

Akhmetzhanov

et al. 2017

Proc. Natl. Acad. Sci. U.S.A.

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Cheats are a pervasive threat to public goods production in natural and human communities, as they benefit from the commons without contributing to it. Although ecological antagonisms such as predation, parasitism, competition, and abiotic environmental stress play key roles in shaping population biology, it is unknown how such stresses generally affect the ability of cheats to undermine cooperation. We used theory and experiments to address this question in the pathogenic bacterium, Pseudomonas aeruginosa. Although public goods producers were selected against in all populations, our competition experiments showed that antibiotics significantly increased the advantage of nonproducers. Moreover, the dominance of nonproducers in mixed cultures was associated with higher resistance to antibiotics than in either monoculture. Mathematical modeling indicates that accentuated costs to producer phenotypes underlie the observed patterns. Mathematical analysis further shows how these patterns should generalize to other taxa with public goods behaviors. Our findings suggest that explaining the maintenance of cooperative public goods behaviors in certain natural systems will be more challenging than previously thought. Our results also have specific implications for the control of pathogenic bacteria using antibiotics and for understanding natural bacterial ecosystems, where subinhibitory concentrations of antimicrobials frequently occur.evolution | cooperation | antibiotics | social behavior | resistance P ublic goods production is a characteristic of a diverse range of taxa, from microbes to humans (1-3). Explaining the persistence of this costly behavior is challenging, because cheats can exploit the commons without contributing. Kin selection theory has proven to be a successful framework for addressing this question, with the central prediction that cooperation is favored by sufficient benefits to, and positive assortment between, cooperators (4-8). For example, recent study in experimental bacterial populations has elucidated mechanisms such as assortment emerging from limited or budding dispersal (9, 10) and kin discrimination (11, 12) that are consistent with kin selection fostering cooperative behaviors (e.g., refs. 8 and 13). However, despite this accumulating consensus, little is known about how social populations respond to differences and variation in abiotic and biotic components of their environment. In particular, it is unclear how ecological antagonisms affect the ability of cheats to invade cooperator communities.Cooperation can be affected by stress directly through differential selection on cooperative phenotypes (14, 15), or by inducing specific plastic behaviors (16-22), especially when cooperation leads to increased stress resistance. However, in the absence of a direct benefit of the cooperative behavior against stress, the ecological and evolutionary outcomes of the interactions between nondefensive public goods and stress responses are less clear and are potentially complex. Cooperation may be infl...

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“…This could have implications for predicting the direct and knockon effects of antibiotic dosing on treatment outcomes (e.g., see discussion in ref. 67).…”

Section: Discussionmentioning

confidence: 99%

Antibiotic stress selects against cooperation in the pathogenic bacterium Pseudomonas aeruginosa

Vasse

Noble

Akhmetzhanov

et al. 2017

Proc. Natl. Acad. Sci. U.S.A.

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“…The time for start of the treatment can have a substantial influence on the underlying processes by which these factors are characterized. At the population level, the interplay between these factors manifests itself in the rise and fall of resistance (Lipsitch, 2001), making the identification of optimal treatment regimens extremely difficult to achieve in order to simultaneously minimize the incidence of disease and limit resistance emergence and spread (Colijn & Cohen, 2015; Day & Read, 2016). As has been demonstrated in recent studies, it is therefore important to develop multi-scale models that integrate both within-host infection dynamics and between-host disease transmission (Legros & Bonhoeffer, 2016).…”

Section: Discussionmentioning

confidence: 99%

Population dynamics of epidemic and endemic states of drug-resistance emergence in infectious diseases

Knipl

Röst

Moghadas

2017

PeerJ

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The emergence and spread of drug-resistance during treatment of many infectious diseases continue to degrade our ability to control and mitigate infection outcomes using therapeutic measures. While the coverage and efficacy of treatment remain key factors in the population dynamics of resistance, the timing for the start of the treatment in infectious individuals can significantly influence such dynamics. We developed a between-host disease transmission model to investigate the short-term (epidemic) and long-term (endemic) states of infections caused by two competing pathogen subtypes, namely the wild-type and resistant-type, when the probability of developing resistance is a function of delay in start of the treatment. We characterize the behaviour of disease equilibria and obtain a condition to minimize the fraction of population infectious at the endemic state in terms of probability of developing resistance and its transmission fitness. For the short-term epidemic dynamics, we illustrate that depending on the likelihood of resistance development at the time of treatment initiation, the same epidemic size may be achieved with different delays in start of the treatment, which may correspond to significantly different treatment coverages. Our results demonstrate that early initiation of treatment may not necessarily be the optimal strategy for curtailing the incidence of resistance or the overall disease burden. The risk of developing drug-resistance in-host remains an important factor in the management of resistance in the population.

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“…Following this is the effect of the Hill coefficient,β, on Tfix which, in line with [15], challenges the idea that increased clearance rates minimize the selection and fixation of resistant isolates. The increased selective pressure imposed by higher order bactericidal drugs leads to a more rapid fixation of resistance in the population.…”

Section: Discussionmentioning

confidence: 99%

Pharmacodynamic Considerations of Collateral Sensitivity in Design of Antibiotic Treatment Regimen

Udekwu

Weiss

2017

Preprint

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Antibiotics have greatly reduced the morbidity and mortality due to infectious diseases. Although antibiotic resistance is not a new problem, its breadth now constitutes a significant threat to human health. One strategy to help combat resistance is to find novel ways to use existing drugs, even those that display high rates of resistance. For the pathogens Escherichia coli and Pseudomonas aeruginosa, pairs of antibiotics have been identified for which evolution of resistance to drug A increases sensitivity to drug B and visa versa. These research groups have proposed cycling such pairs to treat infections, similar treatment strategies are being investigated for various cancer forms as well.While an exciting treatment prospect, no cycling experiments have yet been performed with consideration of pharmacokinetics (PK) and pharmacodynamics (PD). To test the plausibility of this scheme and search for ways to optimize it, we create a mathematical model with explicit PK-PD considerations. We study several possible treatment protocols using pairs of such antibiotics, and investigate the speed of ascent of multiply resistant mutants. Our analyses show that for low concentrations of antibiotics, treatment failure will always occur due to the rapid ascent and fixation of resistant mutants. However, at moderate to high concentrations of some types of bacteriostatic antibiotics with multiday cycling, resistance is prevented from developing and treatment succeeds. This calls for guarded optimism of such treatment protocols whose development can be directed by these types of models.

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Does High-Dose Antimicrobial Chemotherapy Prevent the Evolution of Resistance?

Cited by 129 publications

References 62 publications

Antibiotic stress selects against cooperation in the pathogenic bacterium Pseudomonas aeruginosa

Antibiotic stress selects against cooperation in the pathogenic bacterium Pseudomonas aeruginosa

Population dynamics of epidemic and endemic states of drug-resistance emergence in infectious diseases

Pharmacodynamic Considerations of Collateral Sensitivity in Design of Antibiotic Treatment Regimen

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