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Evaluating Evolutionary Models of Stress-Induced Mutagenesis in Bacteria

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Evaluating Evolutionary Models of Stress-Induced Mutagenesis in Bacteria PERSPECTIVES Experiments conducted using several dif- OPINION ferent bacteria, stress-response mechanisms and stressors have reported results that are Evaluating evolutionary models consistent with the existence of SIM (BOX 1). It is important to point out, however, that of stress-induced mutagenesis the existence of SIM is controversial, and it has been argued that mechanisms other than SIM could explain results such as those in bacteria presented in BOX 1 (for example, see REF. 14). Although we emphasize the importance R. Craig MacLean, Clara Torres-Barceló and Richard Moxon of using appropriate experimental designs and mutation rate estimation to test for SIM Abstract | Increased mutation rates under stress allow bacterial populations to (BOX 1), the premise of this article is that adapt rapidly to stressors, including antibiotics. Here we evaluate existing SIM occurs. models for the evolution of stress-induced mutagenesis and present a Mechanisms that couple stress to an new model arguing that it evolves as a result of a complex interplay between elevated mutation rate have been investi- direct selection for increased stress tolerance, second-order selection for gated in detail, but less attention has been given to understanding how natural selec- increased evolvability and genetic drift. Further progress in our understanding tion acts on genes involved in SIM, even of the evolutionary biology of stress and mutagenesis will require a more though SIM could have a crucial role in detailed understanding both of the patterns of stress encountered by bacteria accelerating adaptation by natural selection in nature and of the mutations that are produced under stress. to environmental stressors, including anti- biotics15–19. For example, the SOS pathway, which is associated with the expression It has been argued that exposure to stress is We refer to this phenomenon as stress- of error-prone polymerases19–22, increases associated with increased mutation rates in induced mutagenesis (SIM), because it the ability of both Escherichia coli and a wide variety of eukaryotes, bacteria and reflects mutagenesis that is induced, but not Mycobacterium tuberculosis to evolve resist- archaea1–7. In eukaryotes, the underlying directly caused, by stress. The term SIM has ance to antibiotics in mice23,24. Although it mechanistic causes of this phenomenon frequently been used in the literature but is intuitively reasonable that the proximate remain obscure. In microorganisms, posi- often without critical evaluation. Our use consequence of these increased mutation tive associations between stress and muta- of terminology emphasizes the distinction rates is an increase in evolvability under tion have been attributed to two distinct between mechanisms in which there is and stressful conditions, it does not follow that classes of mechanism. First, stress can lead in which there is not clear evidence that the ultimate evolutionary cause of SIM to a direct increase in the mutation rate: for stress, per se, results in altered mutation is selection for increased mutagenesis25. example, this can occur when toxic mol- rates. The juxtaposition of the terms is novel Because most new mutations are deleteri- ecules such as reactive oxygen and alkylat- in its emphasis and is key to our Perspective. ous, even under stressful conditions26,27, it ing agents directly damage DNA or inhibit is challenging to explain the evolution of enzymes that are involved in maintaining any mechanism that leads to an elevation a high fidelity of DNA replication and Mechanisms that couple of the mutation rate25,28. Two main expla- repair8. In this article, we refer to this first stress to an elevated mutation nations have been put forward to explain mechanism as stress-associated mutagenesis rate have been investigated SIM10,11,14,18,29. First, it has been argued that (SAM), because the relationship between an increase in the mutation rate is the una- stress and mutagenesis is purely coinciden- in detail, but less attention has voidable price that bacteria pay for mecha- tal: that is, there is no a priori reason why been given to understanding nisms that increase survival under stress. exposure to stress should lead to an elevated how natural selection acts on More controversially, it has been argued mutation rate. By contrast, stress could genes involved in SIM that SIM exists because selection favours indirectly increase mutation rates when the evolution of mechanisms that couple the exposure to stress results in changes in evolutionary demand for novelty imposed the expression of genes that elevate the We define a stressor as any environmen- by stress to the rate of production of novelty mutation rate by, for example, inducing tal variable that leads to a decrease of bacte- provided by mutation. We review and evalu- the expression of error-prone DNA rial growth rate or competitive ability, such ate experimental tests of these hypotheses in polymerases9–13 or by repressing the expression as elevated temperature, exposure to toxins a wide range of bacterial model systems and of genes involved in the repair of DNA9. or unfavourable pH. then introduce a novel hypothesis based on NATURE REVIEWS | GENETICS VOLUME 14 | MARCH 2013 | 221 © 2013 Macmillan Publishers Limited. All rights reserved PERSPECTIVES genetic drift to explain SIM, and we show are not mutually exclusive. Rather, we envis- The trade-off hypothesis that comparative evidence supports the age an interplay for which the complexity The simplest explanation for the origin of drift hypothesis. Although it is convenient is reflected in the variety and different time SIM is that natural selection favours genes to discuss each of the different proposed frames of the interactions between bacteria that increase fitness under stressful condi- mechanisms of SIM, we emphasize that they and environmental stressors. tions by, for example, increasing survival Box 1 | Measuring stress-induced mutagenesis In a seminal paper published in 1943, Luria and Delbrück66 described a 3.0 simple experimental method, known as a fluctuation test, for estimating bacterial mutation rates that is based on scoring the presence or absence of mutants with an easily selectable phenotype, such as antibiotic or phage 2.5 resistance, in bacterial populations. In a fluctuation test, a bacterial strain is used to set up numerous independent cultures that have a low enough population density that they do not initially contain any of the mutations 2.0 of interest. After some period of growth, the number of resistant mutants in a sample of N cells is then determined for each culture. Because the number of mutants per culture follows a Poisson distribution, Luria and 1.5 Delbrück66 argued that mutation rate (μ) per cell division can be estimated as μ = (−ln(p(0)) / N), where p(0) is the proportion of mutant free cultures, and N is the number of cells sampled from each culture. The downside of 1.0 this method is that large numbers of replicate cultures are required to estimate the mutation rate, especially if p(0) is close to 0 or 1. Maximum- in mutant log(increase Mutation rate: control) to unstressed relative frequency likelihood-based methods have been developed to use data on the 0.5 frequency distribution of mutants per culture, instead of just –2.0 –1.5 –1.0 –0.5 0.0 0.5 1.0 1.5 2.0 the proportion of mutant-free cultures, to estimate the mutation rate59,67,68. Severity of stress: log(relative antibiotic concentration) Unfortunately, many papers estimate changes in the mutation rate by simply estimating changes in the mean or median mutant frequency; this These studies show that the increase in mutationNature rate Reviews associated | Genetics with method provides a poor estimate of the mutation rate59,68. SIM can show profound variation. Although the causes of this variation are The ideal experiment to test for stress-induced mutagenesis using a not fully understood, one factor that is likely to have a key role in fluctuation test is as follows. First, it is necessary to measure the mutation determining the extent of SIM is the severity of stress, as demonstrated by rates in the presence and absence of a specific stressor to test the the fact that the increase in mutation rate associated with SIM on exposure hypothesis that stress increases the mutation rate. Second, it is necessary to antibiotics in Escherichia coli strongly correlates with antibiotic dose, as to measure the mutation rate of both a wild-type strain and a mutant shown in the figure. A study69 measured changes in the frequency of lacking a gene that is thought to be involved in stress-induced mutagenesis rifampicin-resistant mutants when populations of E. coli were exposed to (SIM); without this crucial control, it is not possible to distinguish ten different antibiotics (not including rifampicin) that were administered between SIM and stress-associated mutagenesis (SAM). It is also important at different relative doses. Across antibiotics, the increase in mutant to use a selectable marker phenotype that is selectively neutral in both the frequency strongly correlates with the strength of antibiotic-imposed 2 presence and the absence of the stressor being investigated. If the marker stress (correlation coefficient (r ) = 0.52; F1,8 = 8.7; P = 0.02). A recA mutant being used to estimate mutation rates is subject to selection, then changes did not show an increase in mutation frequency in response to any of these in marker frequency that are used to infer differences in the mutation rate treatments, demonstrating that stress-induced mutagenesis is driven by will be driven by both selection and mutation58. Examples of studies that the SOS pathway, which controls the expression of several error-prone have used this approach are given in the table. polymerases in E. coli. Data in the figure are from REF. 72. Bacterial species Increase in Stress factor Reporter system Tested SIM mechanism Refs mutation frequency associated with SIM Bacillus subtilis JJS149 5.4× UV irradiation (40 J m−2 or Rif resistance (10 μg mL−1) YqjW (Pol Y2 homologue) 70 60 J m−2) Caulobacter crescentus 3× UV irradiation (90 J m−2) Rif resistance (100 μg mL−1) ImuA and ImuB; DnaE2 71 NA1000 B.
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