Mutator genomes decay, despite sustained fitness gains, in a long-term experiment with bacteria.

Understanding the extreme variation among bacterial genomes remains an unsolved challenge in evolutionary biology, despite long-standing debate about the relative importance of natural selection, mutation, and random drift. A potentially important confounding factor is the variation in mutation rates between lineages and over evolutionary history, which has been documented in several species. Mutation accumulation experiments have shown that hypermutability can erode genomes over short timescales. These results, however, were obtained under conditions of extremely weak selection, casting doubt on their general relevance. Here, we circumvent this limitation by analyzing genomes from mutator populations that arose during a long-term experiment with Escherichia coli, in which populations have been adaptively evolving for >50,000 generations. We develop an analytical framework to quantify the relative contributions of mutation and selection in shaping genomic characteristics, and we validate it using genomes evolved under regimes of high mutation rates with weak selection (mutation accumulation experiments) and low mutation rates with strong selection (natural isolates). Our results show that, despite sustained adaptive evolution in the long-term experiment, the signature of selection is much weaker than that of mutational biases in mutator genomes. This finding suggests that relatively brief periods of hypermutability can play an outsized role in shaping extant bacterial genomes. Overall, these results highlight the importance of genomic draft, in which strong linkage limits the ability of selection to purge deleterious mutations. These insights are also relevant to other biological systems evolving under strong linkage and high mutation rates, including viruses and cancer cells.

Mutational spectrum drives the rise of mutator bacteria.

Understanding how mutator strains emerge in bacterial populations is relevant both to evolutionary theory and to reduce the threat they pose in clinical settings. The rise of mutator alleles is understood as a result of their hitchhiking with linked beneficial mutations, although the factors that govern this process remain unclear. A prominent but underappreciated fact is that each mutator allele increases only a specific spectrum of mutational changes. This spectrum has been speculated to alter the distribution of fitness effects of beneficial mutations, potentially affecting hitchhiking. To study this possibility, we analyzed the fitness distribution of beneficial mutations generated from different mutator and wild-type Escherichia coli strains. Using antibiotic resistance as a model system, we show that mutational spectra can alter these distributions substantially, ultimately determining the competitive ability of each strain across environments. Computer simulation showed that the effect of mutational spectrum on hitchhiking dynamics follows a non-linear function, implying that even slight spectrum-dependent fitness differences are sufficient to alter mutator success frequency by several orders of magnitude. These results indicate an unanticipated central role for the mutational spectrum in the evolution of bacterial mutation rates. At a practical level, this study indicates that knowledge of the molecular details of resistance determinants is crucial for minimizing mutator evolution during antibiotic therapy.

Bypass of genetic constraints during mutator evolution to antibiotic resistance.

Genetic constraints can block many mutational pathways to optimal genotypes in real fitness landscapes, yet the extent to which this can limit evolution remains to be determined. Interestingly, mutator bacteria elevate only specific types of mutations, and therefore could be very sensitive to genetic constraints. Testing this possibility is not only clinically relevant, but can also inform about the general impact of genetic constraints in adaptation. Here, we evolved 576 populations of two mutator and one wild-type Escherichia coli to doubling concentrations of the antibiotic cefotaxime. All strains carried TEM-1, a ß-lactamase enzyme well known by its low availability of mutational pathways. Crucially, one of the mutators does not elevate any of the relevant first-step mutations known to improve cefatoximase activity. Despite this, both mutators displayed a similar ability to evolve more than 1000-fold resistance. Initial adaptation proceeded in parallel through general multi-drug resistance mechanisms. High-level resistance, in contrast, was achieved through divergent paths; with the a priori inferior mutator exploiting alternative mutational pathways in PBP3, the target of the antibiotic. These results have implications for mutator management in clinical infections and, more generally, illustrate that limits to natural selection in real organisms are alleviated by the existence of multiple loci contributing to fitness.

Changing fitness effects of mutations through long-term bacterial evolution.

The distribution of fitness effects of new mutations shapes evolution, but it is challenging to observe how it changes as organisms adapt. Using Escherichia coli lineages spanning 50,000 generations of evolution, we quantify the fitness effects of insertion mutations in every gene. Macroscopically, the fraction of deleterious mutations changed little over time whereas the beneficial tail declined sharply, approaching an exponential distribution. Microscopically, changes in individual gene essentiality and deleterious effects often occurred in parallel; altered essentiality is only partly explained by structural variation. The identity and effect sizes of beneficial mutations changed rapidly over time, but many targets of selection remained predictable because of the importance of loss-of-function mutations. Taken together, these results reveal the dynamic-but statistically predictable-nature of mutational fitness effects.

Antibiotics and antibiotic resistance: a bitter fight against evolution.

One of the most terrible consequences of Darwinian evolution is arguably the emergence and spread of antibiotic resistance, which is becoming a serious menace to modern societies. While spontaneous mutation, recombination and horizontal gene transfer are recognized as the main causes of this notorious phenomenon; recent research has raised awareness that sub-lethal concentrations of antibiotics can also foster resistance as an undesirable side-effect. They can produce genetic changes by different ways, including a raise of free radicals within the cell, induction of error-prone DNA-polymerases mediated by SOS response, imbalanced nucleotide metabolism or affect directly DNA. In addition to certain environmental conditions, subinhibitory concentrations of antimicrobials may increase, even more, the mutagenic effect of antibiotics. Here, we review the state of knowledge on antibiotics as promoters of antibiotic resistance.

Genomewide overexpression screen for fosfomycin resistance in Escherichia coli: MurA confers clinical resistance at low fitness cost.

To determine whether the overexpression of chromosomal genes can confer fosfomycin resistance, genomewide screening of a complete set of 5,272 plasmid-expressed open reading frames of Escherichia coli (ASKA collection) was performed. Major results are that (i) no clinical level of resistance is achieved by overexpressing chromosomal genes, except murA; (ii) this level is reached at a low fitness cost; and (iii) this cost is much lower than that imposed by other mutations conferring fosfomycin resistance.

Effect of recA inactivation on mutagenesis of Escherichia coli exposed to sublethal concentrations of antimicrobials.

OBJECTIVES: Low concentrations of some antibiotics have been reported to stimulate mutagenesis and recombination, which may facilitate bacterial adaptation to different types of stress, including antibiotic pressure. However, the mutagenic effect of most of the currently used antibiotics remains untested. Furthermore, it is known that in many bacteria, including Escherichia coli, stimulation of mutagenesis is mediated by the SOS response. Thus, blockage or attenuation of this response through the inhibition of RecA has been proposed as a possible therapeutic adjuvant in combined therapy to reduce the ability to generate antibiotic-resistant mutants. The aim of this work was to study the capacity of sublethal concentrations of antimicrobials of different families with different molecular targets to increase the mutant frequency of E. coli, and the effect that inactivation of recA would have on antibiotic-mediated mutagenesis. METHODS: We tested the mutagenicity of the following antimicrobials: ampicillin; ceftazidime; imipenem; fosfomycin; ciprofloxacin; trimethoprim; sulfamethoxazole; trimethoprim/sulfamethoxazole; colistin; tetracycline; gentamicin; rifampicin; and chloramphenicol. RESULTS: Eight out of the 13 antimicrobials tested stimulate E. coli mutagenesis (slightly in most cases), with trimethoprim, alone or in combination with sulfamethoxazole, producing the highest effect. Inactivation of recA abolishes the mutagenic effect and also produces increased susceptibility to some of the tested antimicrobials. CONCLUSIONS: The fact that inactivation of recA reduces mutagenicity and/or increases the activity of a large number of antimicrobials supports the hypothesis that RecA inhibition might have favourable effects on antibiotic therapy.

Estimating mutation rates in low-replication experiments.

Since mutation rate is a key biological parameter, its proper estimation has received great attention for decades. However, instead of the mutation rate, many authors opt for reporting the average mutant frequency, a less meaningful quantity. This is because the standard methods to estimate the mutation rate, derived from the Luria and Delbrück's fluctuation analysis, ideally require high-replication experiments to be applied; a requirement often unattainable due to constraints of time, budget or sample availability. But the main problem with mutant frequency, apart from being less informative, is its poor reproducibility; an especially marked defect when the chosen average is the arithmetic mean. Several authors tried to avoid this by employing other averages (such as the median or the geometric mean) or discarding outliers, though as far as we know nobody has evaluated which method performs best under low-replication settings. Here we use computer simulations to compare the performance of different methods used in low-replication experiments (≤4 cultures). Besides the customary averages of mutant frequency, we also tested two well-known fluctuation methods. Contrary to common practice, our results support that fluctuation methods should be applied in such circumstances, as they perform as well as or better than any average of mutant frequency. In particular, experimentalists will benefit from using MSS maximum likelihood in low-replication experiments because it: (i) provides more reproducible results, (ii) allows for direct estimation of mutation rate and (iii) allows for the application of conventional statistics.

Flux, toxicity, and expression costs generate complex genetic interactions in a metabolic pathway.

Our ability to predict the impact of mutations on traits relevant for disease and evolution remains severely limited by the dependence of their effects on the genetic background and environment. Even when molecular interactions between genes are known, it is unclear how these translate to organism-level interactions between alleles. We therefore characterized the interplay of genetic and environmental dependencies in determining fitness by quantifying ~4000 fitness interactions between expression variants of two metabolic genes, starting from various environmentally modulated expression levels. We detect a remarkable variety of interactions dependent on initial expression levels and demonstrate that they can be quantitatively explained by a mechanistic model accounting for catabolic flux, metabolite toxicity, and expression costs. Complex fitness interactions between mutations can therefore be predicted simply from their simultaneous impact on a few connected molecular phenotypes.

Mutation bias and GC content shape antimutator invasions.

Mutators represent a successful strategy in rapidly adapting asexual populations, but theory predicts their eventual extinction due to their unsustainably large deleterious load. While antimutator invasions have been documented experimentally, important discrepancies among studies remain currently unexplained. Here we show that a largely neglected factor, the mutational idiosyncrasy displayed by different mutators, can play a major role in this process. Analysing phylogenetically diverse bacteria, we find marked and systematic differences in the protein-disruptive effects of mutations caused by different mutators in species with different GC compositions. Computer simulations show that these differences can account for order-of-magnitude changes in antimutator fitness for a realistic range of parameters. Overall, our results suggest that antimutator dynamics may be highly dependent on the specific genetic, ecological and evolutionary history of a given population. This context-dependency further complicates our understanding of mutators in clinical settings, as well as their role in shaping bacterial genome size and composition.

Parallel Evolution of High-Level Aminoglycoside Resistance in Escherichia coli Under Low and High Mutation Supply Rates.

Antibiotic resistance is a major concern in public health worldwide, thus there is much interest in characterizing the mutational pathways through which susceptible bacteria evolve resistance. Here we use experimental evolution to explore the mutational pathways toward aminoglycoside resistance, using gentamicin as a model, under low and high mutation supply rates. Our results show that both normo and hypermutable strains of Escherichia coli are able to develop resistance to drug dosages > 1,000-fold higher than the minimal inhibitory concentration for their ancestors. Interestingly, such level of resistance was often associated with changes in susceptibility to other antibiotics, most prominently with increased resistance to fosfomycin. Whole-genome sequencing revealed that all resistant derivatives presented diverse mutations in five common genetic elements: fhuA, fusA and the atpIBEFHAGDC, cyoABCDE, and potABCD operons. Despite the large number of mutations acquired, hypermutable strains did not pay, apparently, fitness cost. In contrast to recent studies, we found that the mutation supply rate mainly affected the speed (tempo) but not the pattern (mode) of evolution: both backgrounds acquired the mutations in the same order, although the hypermutator strain did it faster. This observation is compatible with the adaptive landscape for high-level gentamicin resistance being relatively smooth, with few local maxima; which might be a common feature among antibiotics for which resistance involves multiple loci.

Determinants of Genetic Diversity of Spontaneous Drug Resistance in Bacteria.

Any pathogen population sufficiently large is expected to harbor spontaneous drug-resistant mutants, often responsible for disease relapse after antibiotic therapy. It is seldom appreciated, however, that while larger populations harbor more mutants, the abundance distribution of these mutants is expected to be markedly uneven. This is because a larger population size allows early mutants to expand for longer, exacerbating their predominance in the final mutant subpopulation. Here, we investigate the extent to which this reduction in evenness can constrain the genetic diversity of spontaneous drug resistance in bacteria. Combining theory and experiments, we show that even small variations in growth rate between resistant mutants and the wild type result in orders-of-magnitude differences in genetic diversity. Indeed, only a slight fitness advantage for the mutant is enough to keep diversity low and independent of population size. These results have important clinical implications. Genetic diversity at antibiotic resistance loci can determine a population's capacity to cope with future challenges (i.e., second-line therapy). We thus revealed an unanticipated way in which the fitness effects of antibiotic resistance can affect the evolvability of pathogens surviving a drug-induced bottleneck. This insight will assist in the fight against multidrug-resistant microbes, as well as contribute to theories aimed at predicting cancer evolution.

The rule of declining adaptability in microbial evolution experiments.

One of the most recurrent observations after two decades of microbial evolution experiments regards the dynamics of fitness change. In a given environment, low-fitness genotypes are recurrently observed to adapt faster than their more fit counterparts. Since adaptation is the main macroscopic outcome of Darwinian evolution, studying its patterns of change could potentially provide insight into key issues of evolutionary theory, from fixation dynamics to the genetic architecture of organisms. Here, we re-analyze several published datasets from experimental evolution with microbes and show that, despite large differences in the origin of the data, a pattern of inverse dependence of adaptability with fitness clearly emerges. In quantitative terms, it is remarkable to observe little if any degree of idiosyncrasy across systems as diverse as virus, bacteria and yeast. The universality of this phenomenon suggests that its emergence might be understood from general principles, giving rise to the exciting prospect that evolution might be statistically predictable at the macroscopic level. We discuss these possibilities in the light of the various theories of adaptation that have been proposed and delineate future directions of research.

Antimicrobials as promoters of genetic variation.

The main causes of antibiotic resistance are the selection of naturally occurring resistant variants and horizontal gene transfer processes. In recent years, the implications of antibiotic contact or treatment in drug resistance acquisition by bacteria have been gradually more evident. The ultimate source of bacterial genetic alterations to face antibiotic toxicity is mutation. All evidence points to antibiotics, especially when present at sublethal concentrations, as responsible for increasing genetic variation and therefore participating in the emergence of antibiotic resistance. Antibiotics may cause genetic changes by means of different pathways involving an increase of free radicals inside the cell or oxidative stress, by inducing error-prone polymerases mediated by SOS response, misbalancing nucleotide metabolism or acting directly on DNA. In addition, the concerted action of certain environmental conditions with subinhibitory concentrations of antimicrobials may contribute to increasing the mutagenic effect of antibiotics even more. Here we review and discuss in detail the recent advances concerning these issues and their relevance in the field of antibiotic resistance.

The Escherichia coli SOS gene dinF protects against oxidative stress and bile salts.

DNA is constantly damaged by physical and chemical factors, including reactive oxygen species (ROS), such as superoxide radical (O(2)(-)), hydrogen peroxide (H(2)O(2)) and hydroxyl radical (•OH). Specific mechanisms to protect and repair DNA lesions produced by ROS have been developed in living beings. In Escherichia coli the SOS system, an inducible response activated to rescue cells from severe DNA damage, is a network that regulates the expression of more than 40 genes in response to this damage, many of them playing important roles in DNA damage tolerance mechanisms. Although the function of most of these genes has been elucidated, the activity of some others, such as dinF, remains unknown. The DinF deduced polypeptide sequence shows a high homology with membrane proteins of the multidrug and toxic compound extrusion (MATE) family. We describe here that expression of dinF protects against bile salts, probably by decreasing the effects of ROS, which is consistent with the observed decrease in H(2)O(2)-killing and protein carbonylation. These results, together with its ability to decrease the level of intracellular ROS, suggests that DinF can detoxify, either direct or indirectly, oxidizing molecules that can damage DNA and proteins from both the bacterial metabolism and the environment. Although the exact mechanism of DinF activity remains to be identified, we describe for the first time a role for dinF.

Assessing the emergence of resistance: the absence of biological cost in vivo may compromise fosfomycin treatments for P. aeruginosa infections.

BACKGROUND: Fosfomycin is a cell wall inhibitor used efficiently to treat uncomplicated urinary tract and gastrointestinal infections. A very convenient feature of fosfomycin, among others, is that although the expected frequency of resistant mutants is high, the biological cost associated with mutation impedes an effective growth rate, and bacteria cannot offset the obstacles posed by host defenses or compete with sensitive bacteria. Due to the current scarcity of new antibiotics, fosfomycin has been proposed as an alternative treatment for other infections caused by a wide variety of bacteria, particularly Pseudomonas aeruginosa. However, whether fosfomycin resistance in P. aeruginosa provides a fitness cost still remains unknown. PRINCIPAL FINDINGS: We herein present experimental evidence to show that fosfomycin resistance cannot only emerge easily during treatment, but that it is also cost-free for P. aeruginosa. We also tested if, as has been reported for other species such as Escherichia coli, Klebsiella pneumoniae and Proteus mirabilis, fosfomycin resistant strains are somewhat compromised in their virulence. As concerns colonization, persistence, lung damage, and lethality, we found no differences between the fosfomycin resistant mutant and its sensitive parental strain. The probability of acquisition in vitro of resistance to the combination of fosfomycin with other antibiotics (tobramycin and imipenem) has also been studied. While the combination of fosfomycin with tobramycin makes improbable the emergence of resistance to both antibiotics when administered together, the combination of fosfomycin plus imipenem does not avoid the appearance of mutants resistant to both antibiotics. CONCLUSIONS: We have reached the conclusion that the use of fosfomycin for P. aeruginosa infections, even in combined therapy, might not be as promising as expected. This study should encourage the scientific community to assess the in vivo cost of resistance for specific antibiotic-bacterial species combinations, and therefore avoid reaching universal conclusions from single model organisms.

Side effects of antibiotics on genetic variability.

In recent years, there has been accumulating evidence that antibiotics, besides their antimicrobial action, potentially have a number of undesired side effects that can, at least in some cases, promote genetic variability of bacteria. In addition to resistant variants, antibiotics have also been shown to select mutator clones, thus stimulating evolution towards further resistance. Furthermore, mutations, recombination and horizontal gene transfer have been reported to be somehow affected when bacteria are exposed to subinhibitory concentrations of certain antibiotics. These findings may have implications for the use of antibiotics, because they may have undesired side effects, such as enhancing antibiotic resistance evolution. Here we present data supporting (or not) this fearsome possibility and discuss whether this potential threat should be taken into consideration.