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Mutation Rate Heterogeneity Increases Odds of Survival
in Unpredictable Environments
Ivan Matic
To cite this version:
Ivan Matic. Mutation Rate Heterogeneity Increases Odds of Survival in Unpredictable Environments. Molecular Cell, Elsevier, 2019, 75 (3), pp.421-425. �10.1016/j.molcel.2019.06.029�. �hal-02352068�
Mutation rates heterogeneity increases odds
of survival in unpredictable environments
Ivan Matic1, 2, 3, *1Institut Cochin, Inserm U1016, Paris, France 2 CNRS, UMR 8104, Paris, France
3 Université Paris Descartes, Paris, France
* Lead contact and corresponding author: Ivan Matic
Department of Infection, Immunity and Inflammation Institut Cochin
INSERM U1016 - CNRS UMR8104 - Université de Paris 24 rue du Faubourg Saint-Jacques, 6th floor
75014 Paris France E-mail: ivan.matic@inserm.fr Tel: +33 1 44 41 25 50 Fax : +33 1 44 41 25 59
Summary
Mutation rates affect both population’s present fitness and its capacity to adapt to future environmental changes. When available genetic variability limits adaptation to environmental change, natural selection favors high mutations rates. However, constitutively high mutation rates compromise population’s fitness in stable environments. This problem may be resolved if increase of mutation rates is limited to times of stress, is restricted to some genomic regions, and occurs only in a subpopulation of cells. Such within-population heterogeneity of mutation rates can result from the genetic, environmental and stochastic effects. Presence of subpopulations of transient mutator cells does not jeopardize the overall population fitness under stable environmental conditions. However, they can increase the odds of survival in changing environments because they represent reservoirs of increased genetic variability. Here we present evidence that such heterogeneity of mutation rates is more the norm than exception.
Mutations are continuously generated, permanent modifications of genetic material. They are the ultimate source of genetic variation, without which evolution would not exist. Therefore, understanding how mutations arise is fundamental to understanding the evolution of living systems. Newly arisen mutations can have markedly different impacts on the fitness of the organism, ranging from deleterious through neutral to beneficial. However, these mutations appear at very different rates. Because most of mutations with phenotypic effects are deleterious, natural selection drives mutation rates to the minimum possible level (Kimura, 1967; Sturtevant, 1937). In stable environment to which a given organism is adapted, very low mutation rates assure that populations remain adapted to existing conditions. However, in changing stressful environments, the available genetic variability can limit adaptation. In such cases, natural selection favors cells having mutator phenotype (Denamur and Matic, 2006). Mutator cells have indeed been observed at high frequency in natural populations of many bacterial species.
Mutator phenotypes result from alterations in genes coding for DNA repair enzymes and for proteins that assure accuracy of DNA replications. These mutated genes are called mutator alleles. The majority of strong mutators found in the laboratory and in nature have a defective mismatch-repair system due to the inactivation of mutS and mutL genes (Denamur and Matic, 2006). This repair system controls genome stability by eliminating DNA replication errors and by preventing recombination between non-identical DNA sequences. Mutator alleles are carried to high frequency through hitchhiking with the beneficial mutations they generate. The linkage between beneficial mutations and mutator alleles is particularly strong in bacteria because the rate of genetic exchange in these organisms is very low. Mutators are favored by very strong selective pressure and when several beneficial mutations are required for adaptation. The selection of mutator alleles depends also on many other parameters: the total population size; mutator strength, i.e., the increase of the mutator mutation rate relative to the non-mutator mutation rate; stability of the environment; environmental spatial heterogeneity and migration rates.
However, permanently genome-wide increased mutation rates compromise longer-term population fitness due to the continuous generation of deleterious mutations at high rates upon adaptation or due to antagonistic pleiotropy (Denamur and Matic, 2006). There are several possible solutions to this problem. Mutation rate of the adapted mutator cells may be reduced before the load of deleterious mutations becomes too high through the reversion of the mutator mutation or by the acquisition of the functional mismatch-repair genes from non-mutator bacteria via horizontal gene transfer (Denamur et al., 2000).
The trade-off between population adaptability: the ability to adapt, and adaptedness: the ability to remain adapted, can be broken by limiting the increase of mutation rates to restricted genomic regions, limited periods of time and by within-population heterogeneity of mutation rates. For example, some bacterial species, such as Haemophilus influenzae and Neisseria meningitidis (Moxon et al., 2006), possess mechanisms allowing them to permanently maintain high mutation rates at some
genomic loci while simultaneously avoiding fitness costs associated with high genome-wide mutation rates. The hypermutability of these loci results from the mutational properties of repetitive DNA sequences located within the gene or its transcription controlling elements. These genes code for evasins, lipopolysaccharide biosynthesis enzymes, adhesins and iron acquisition proteins. Repetitive DNA sequences experience high rates of insertion and deletion mutations through replication slippage, which results in alternating loss-of-function and reversions. Such mutagenesis can increase bacterial pathogen adaptability by enabling evasion of the host’s immune system. However, these localized mutation hot-spots allow adaptive response to déjà vu selective pressures, which limits their utility upon exposure to new environment stressors, like for example man-made antimicrobial drugs.
Another way to profit from an adaptive potential of increased mutation rate and to attenuate long-term impact of accumulation deleterious mutations would be to limit increase in the mutation rate only to stressful phases. Computer simulations have shown that this could be advantageous because it could facilitate adaptation to environmental challenges without compromising the overall population fitness in a stable environment (Bjedov et al., 2003; Ram and Hadany, 2014; Tenaillon et al., 2004). There is ample experimental evidence that different stresses can increase mutation rates via variety of different mechanisms: (i) Exogenous and endogenously generated chemical stressors can generate mutagenic miscoding DNA structures that cause DNA replication errors. For example, reactive oxygen species generate highly mutagenic 8-oxo-guanine. (ii) Some environmental stressors, like nitric oxide, can directly affect DNA but also inhibit anti-mutator DNA repair enzymes that contain metals, like zinc-containing formamidopyrimidine-DNA glycolyase that removes 8-oxo-guanine from DNA. (iii) Processing of DNA lesions can be mutagenic. Bypass of replication blocking lesions by the low-fidelity translesion-synthesis DNA polymerases that are induced by genotoxic stress is frequently mutagenic. Also, processing of lesions can result in DNA beaks, whose repair by homologous recombination results in genome rearrangements. For example, processing of nitric oxide-induced lesion by DNA glycosylases produces substrate for homologous recombination, which results in gene conversion events. (iv) Different stresses, such as starvation, high osmolarity, low temperature and low pH, antibiotics induce the sS
-regulated general stress response, which represses mismatch repair by increasing production of the small regulatory RNAs in Escherichia coli (Chen and Gottesman, 2017; Gutierrez et al., 2013). The absence of efficient mismatch-repair system genome stability surveillance leads to increased mutagenesis. (v) Different stresses induce the mobility of transposons and insertion sequences, which can lead to gene inactivation or activation. Therefore, stress-induced mutagenesis can be passive, unavoidable, consequence of the damages to cellular macromolecules but it can also be under be under active control of genetic factors. Nevertheless, regardless of the mechanisms involved in generation of stress-induced mutations, it is likely that the resulting increased genetic variability plays an important role in the adaptive evolution.
further decreased, while maintaining contribution of high mutation rates to the population adaptability, when only subpopulations of cells exhibit transiently high mutation rates. These mutator subpopulations would not affect mean whole population mutation rate but they could represent a reservoir of increased genetic variability. The presence of subpopulations of cells that generate mutants at a high rate could be particularly important when a combination of several mutations is required for adaptation to new complex environments (Alexander et al., 2017). Adaptive evolution is like hiking across a rugged and multiple-peaked fitness landscape. For a population that occupies a local low fitness peak, multiple mutations are required to reach a higher peak because it has to cross a valley of reduced fitness that separates peaks. Deleterious mutations trigger a descent to a fitness valley whereas an ascent to a higher fitness peak requires acquisition of compensatory mutations (Poon and Chao, 2005). Pairs of compensating deleterious mutations that are advantageous in combination frequently appear in evolutionary lineages. This phenomenon could be considerably facilitated by mutations that arise in bursts, as it is expected to occur in transiently hypermutable cells. In addition, multiple mutations are required to provide resistance to combination of drugs, which is frequently used for treatment of some major infectious diseases and cancer (Al-Lazikani et al., 2012; Goldberg et al., 2012).
The existence of the subpopulations of transient mutators in bacterial population has been theorized nearly 30 years ago (Ninio, 1991), but bulk population measurements that were used to study mutagenesis precluded until recently demonstration of their existence. By using mutation assay that allows visualization of emerging mutations in individual living E. coli cells coupled with the stress-response transcriptional and translation fidelity reporters, Woo et al (Woo et al., 2018) observed that mutations in proliferating cells arose more frequently in the subpopulations suffering endogenous stresses, such as problems with proteostasis, genome maintenance and reactive oxidative species production. Importantly, this observation shed a new light on an old question: do spontaneous mutations arise due to limits of the intrinsic fidelity of replicative DNA polymerase, or in a subpopulation of cells with special phenotypic properties?
Endogenous stresses may be induced by toxic metabolic byproducts, spontaneous chemical alteration of cellular components and stochastic fluctuations in the abundance of the low copy proteins, all of which can the fidelity of DNA replication and repair (Burcham, 1999; Choi et al., 2008; Linster et al., 2013). Most damages are eliminated by repair systems, but damages in some cells may escape repair and cause mutations. Hence, it was observed that overproduction of catalase, which eliminates H2O2, decreases spontaneous mutation rates in populations of
growing E. coli cells (Jee et al., 2016). This suggests that there is either high reactive oxidative species production and/or sub-optimal capacity to deal with such stress in some cells. The latter possibility is supported by the observation that fluctuations in O6-alkyl guanine transferase abundance among cells can compromise repair of
spontaneous mutagenic DNA alkylation damages in E. coli, and create a subpopulation of cells with increased mutation rates (Uphoff et al., 2016). Quantity of
proteins can vary not only due to the random distribution of the low abundance protein during cell division but also due to high translation errors, which may produce mutated and truncated proteins, which may have loss of function, partial function and dominant negative properties. Resulting sub-optimal quantity and/or quality of proteins implicated in DNA replication, DNA repair and other cellular functions, may impact spontaneous mutation rates. It was indeed found that there are significantly more DNA replication errors in subpopulations of cells having high translation errors (Woo et al., 2018). Therefore, even isogenic populations in stable and uniform environments contain subpopulations of cells with different propensity to generate mutations.
Cell-to-cell heterogeneity of mutation rates can also be induced upon exposure to exogenous stressors. Pribis et al. (Pribis et al., 2019) recently reported that sublethal treatment of E. coli populations with fluoroquinolone antibiotic, ciprofloxacin, triggers differentiation of subpopulations of transient mutator cells. They called these mutator cells: gamblers, because unlike most cells in the population they “take the risk” of producing mutations at high rate. They showed that the SOS, a genotoxic stress response regulon, induction is required for the ubiquinone-dependent production of reactive oxygen species. Reactive oxygen species activates the sS
general stress response regulon in a subpopulation of treated cells. The activation of the sS regulon allows for mutagenic repair of ciprofloxacin-induced double-strand
breaks. Most of the ciprofloxacin-induced mutations arise in the high reactive oxygen species and high sS cells, which become elongated due to SOS-induced inhibition of
cell division. Importantly, these filamentous cells contain multiple chromosomes, which may allow for increased efficiency of repair of double-strand breaks, for separation of beneficial and deleterious mutations, and for generation of new beneficial combination of mutations, through homologous recombination.
Reducing the capacity of bacterial pathogens to resist different stresses and to generate new resistances could be an important complement to existing antimicrobial strategies. Pribis et al., (Pribis et al., 2019) used the FDA-approved drug, edaravone that is indicated for treatment of acute-phase cerebral infarction and for amyotrophic lateral sclerosis. They showed that this anti-ROS drug, reduces the sS-induced
gambler population and inhibits ciprofloxacin-induced mutagenesis, but does not impair its antibiotic activity. It would be also interesting to test whether similar combination of drugs, analogous to edaravone action on antibiotic-treated E. coli, may be use for cancer therapy (Rosenberg and Queitsch, 2014) .
The identification of the molecular mechanisms governing appearance of the stress-induced hypermutable cell subpopulations, in particular of the sS regulon,
allowed confirming that observations made in laboratory are also valuable for natural environments. In E. coli, sS-dependent mutagenesis has a specific mutation signature
that is different from the spontaneous generation-dependent mutation spectra, and from signatures in mutation accumulation experiments, but closely matches mutation spectra found in existing genomes of different E. coli natural isolates (Maharjan and Ferenci, 2015). It is intriguing that induction of the sS stress response regulon, which
results in downregulation of genes required for rapid growth, and upregulation of genes involved in protection and maintenance of the cell, increases mutation rates due to dowregulation of the mismatch repair activity. The downregulation of DNA repair and fidelity genes like those coding for mismatch repair or for Mfd protein involved in transcription-coupled repair, and upregulation of SOS genes, dinB and umuCD, coding for low-fidelity translesion synthesis DNA polymerases was also observed in
E. coli natural isolates growing under stressful conditions (Feugeas et al., 2016). This
raises the question, why would cells downregulate genome maintenance and fidelity functions during stress?
One possibility is that the nature of DNA lesions might render high-fidelity repair too costly, or even dangerous for stressed cells because some DNA repair intermediates can be lethal for the cell. For example, during antibiotic treatment, DNA glycosylases generate abasic sites and strand breaks, which results in genome fragmentation and cell death (Giroux et al., 2017). Another, nonexclusive, hypothesis is that such regulation of genome fidelity factors during stress may increase probability of generation of adaptive variants. Support for the second hypothesis comes from the observation that there is the positive correlation between high gene expression under stressful conditions and increased gene variability (Feugeas et al., 2016). Mutagenesis of genes highly expressed during stress may result from the exposure of the single-strand DNA that is intrinsically mutable (Wright et al., 2013) and from formation of R-loops (Wimberly et al., 2013). Observed downregulation of transcription-coupled repair is expected to increase both events. Downregulation of mismatch repair activity assures that mutations will not be eliminated before fixation. Therefore, it seems that mutagenesis under stressful conditions preferentially target genes involved in stress response or environmental sensing and that downregulation of DNA repair functions may facilitate this process. Consequently, genes highly expressed during stress may evolve faster (Feugeas et al., 2016). This mechanism may also explain why horizontally acquired genes, which have a low level of expression under optimal growth conditions but are highly expressed under stressful conditions, have higher evolutionary rates (Davids and Zhang, 2008; Feugeas et al., 2016). These observations indicate that some mutations arise more frequently in restricted genomic regions and during limited period of time, i.e., during stress.
Importantly, because exogenous stressors are spatially and temporally unevenly distributed in natural habitats, they can induce different mutation rates and produce different types of mutation even within a single population. This is particularly pronounced in structured complex cell communities like bacterial colonies and human tumors (Klein and Glazer, 2010; Saint-Ruf et al., 2014). For example, heterogeneous oxygen availability within tumors results in downregulatation of a number of DNA repair pathways, including mismatch repair, thus leading to increased mutagenesis. In addition, spatially and temporally diverse microhabitats allow also for the coexistence of diverse mutants due to the attenuation of the exclusion dynamics between competing genotypes. Such reduced efficiency of natural selection in structured environments was proposed to explain high levels of genetic diversity in bacterial colonies and in human tumors (Ling et al., 2015; Saint-Ruf et al.,
2014). In such environments, even low-fitness mutants may persist long enough to acquire compensatory mutations. This is particularly relevant for the fate of drug-resistant mutations, which are typically associated with fitness defects. The presence of tumor cells carrying multiple mutations in the standing genetic variation before treatment is predicted to facilitate the emergence of drug resistance during treatment (Komarova and Wodarz, 2005).
In conclusion, the cell-to-cell heterogeneity of mutation rates is more the norm than exception. Such heterogeneity of mutation rates, which can result from genetic, environmental and stochastic effects, may increase the rate of complex adaptation without reducing the population mean fitness. Therefore, it is likely that within-population heterogeneity of mutation rates plays a major role in evolution of important biological phenomena, such as host–parasite coevolution, evolution of pathogen virulence, emergence of drug resistance in microbial populations and in cancer cells, which have a major impact on humans.
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Figure legend
Figure 1. Impact of the within-population heterogeneity of mutation rates on bacterial adaptive evolution.
First line: Low mutation rates assure that populations remain adapted to existing stable conditions, but it limits adaptation to changing stressful environments, like for example exposure to cytotoxic drugs.
Second line: Constitutively high mutation rates can increase probability of the emergence of adaptive variants, but they compromise population’s fitness in stable environments upon adaptation.
Third line: The presence of a subpopulation of cells with transiently high mutation rates does not compromise population’s fitness in stable environments. However, it can contribute to the population adaptability in fluctuating environments because it represents a reservoir of increased genetic variability.
