Abstract

Populations may genetically adapt to severe stress that would otherwise cause their extirpation. Recent theoretical work, combining stochastic demography with Fisher's geometric model of adaptation, has shown how evolutionary rescue becomes unlikely beyond some critical intensity of stress. Increasing mutation rates may however allow adaptation to more intense stress, raising concerns about the effectiveness of treatments against pathogens. This previous work assumes that populations are rescued by the rise of a single resistance mutation. However, even in asexual organisms, rescue can also stem from the accumulation of multiple mutations in a single genome. Here, we extend previous work to study the rescue process in an asexual population where the mutation rate is sufficiently high so that such events may be common. We predict both the ultimate extinction probability of the population and the distribution of extinction times. We compare the accuracy of different approximations covering a large range of mutation rates. Moderate increase in mutation rates favors evolutionary rescue. However, larger increase leads to extinction by the accumulation of a large mutation load, a process called lethal mutagenesis. We discuss how these results could help design "evolution-proof" antipathogen treatments that even highly mutable strains could not overcome.

Highlights

  • Evolutionary rescue (ER) happens when a population confronted with severe stress avoids extinction by genetic adaptation

  • Gomulkiewicz et al (2017) studied the distribution of extinction times for populations doomed to extinction, mostly in the absence of mutation. We extend this analysis to include frequent de novo mutation, rescue events involving several mutational steps, a particular form of epistasis and variable mutation effects depending on stress intensity, and an explicit description of the dynamics of mutation load

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Summary

Introduction

Evolutionary rescue (ER) happens when a population confronted with severe stress avoids extinction by genetic adaptation. Understanding and predicting when and how evolutionary rescue occurs is critical in fields as diverse as conservation biology, invasion biology, emergence of new diseases and the management of resistance to treatment in pests and pathogens (see reviews in Gonzalez et al 2013; Carlson et al.2014; Alexander et al 2014; Bell 2017). In all these situations, genetic variation, be it present before the onset of stress, or generated de novo after, is a key ingredient for evolutionary rescue, as expected theoretically Mutator alleles are often found in antibiotic resistant strains causing serious health issues (Eliopoulos and Blázquez 2003), raising concern about pathogens escaping our control by evolving higher mutation rates (for theoretical predictions see Taddei et al. 1997; Greenspoon and Mideo 2017)

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