Microbiological effects of sublethal levels of antibiotics

Transcription

1 Nature Reviews Microbiology AOP, published online 27 May 2014; doi: /nrmicro3270 REVIEWS Microbiological effects of sublethal levels of antibiotics Dan I. Andersson and Diarmaid Hughes Abstract The widespread use of antibiotics results in the generation of antibiotic concentration gradients in humans, livestock and the environment. Thus, bacteria are frequently exposed to non-lethal (that is, subinhibitory) concentrations of drugs, and recent evidence suggests that this is likely to have an important role in the evolution of antibiotic resistance. In this Review, we discuss the ecology of antibiotics and the ability of subinhibitory concentrations to select for bacterial resistance. We also consider the effects of low-level drug exposure on bacterial physiology, including the generation of genetic and phenotypic variability, as well as the ability of antibiotics to function as signalling molecules. Together, these effects accelerate the emergence and spread of antibiotic-resistant bacteria among humans and animals. Minimal inhibitory concentration (MIC). The lowest concentration of an antibiotic that, under a defined set of experimental conditions, inhibits visible growth of a bacterial culture. Department of Medical Biochemistry and Microbiology, BOX 582, Biomedical Center, Uppsala University, SE Uppsala, Sweden. Correspondence to D.I.A. e mail: Dan.Andersson@imbim.uu.se doi: /nrmicro3270 Published online 27 May 2014 Antibiotics are arguably the most powerful drugs in medicine, but their very success also threatens to be their downfall. The widespread, and often inappropriate, use of antibiotics worldwide in recent years 1 3 has resulted in a situation in which multidrug-resistant (MDR) bacterial pathogens, such as extended-spectrum β-lactamase (ESBL) Gram-negative bacteria and extensively drugresistant tuberculosis (XDR TB), are now a serious threat to the continued effectiveness of these drugs 3,4. We are entering an uncertain age in which the future of infection control is in the balance and the outcome will be determined by our success in developing novel antibiotics (or other methods of infection control) and our willingness to learn from the mistakes that were made during the antibiotic era so that history is not repeated. When antibiotics were first introduced into medicine about 70 years ago, the rationale of dosing was relatively simple: to achieve a therapeutic dose at the infected site that was high enough to clear the bacterial infection without having a severe toxic effect in the patient. Initial research on bacterial susceptibility and antibiotic dosing introduced one of the central concepts of the field: the minimal inhibitory concentration (MIC), which is defined as the lowest concentration of drug that, under established in vitro conditions, inhibits visible growth of a target bacterial population 5. The basic rationale of antibiotic dosing to maintain an antibiotic concentration that is higher than the MIC in the relevant body compartment for long enough to clear the infection was then adapted to suit the characteristics of different drug classes 6. Although mutants that were resistant to high antibiotic concentrations could be easily selected in vitro, the low probability of encountering resistant infections in clinical situations, combined with the availability of alternative effective antibiotics, meant that therapeutic success could be achieved in most clinical situations until the past few decades. When the increasing frequency of clinical resistance became a recognized problem, the selection of, and mechanisms underlying, high-level resistance phenotypes were understandably the primary focus of attention 7,8. Owing to this initial focus on high-level antibiotic resistance and the widely held assumption that most, if not all, clinically relevant resistance emerges as a result of bacterial exposure to antibiotic concentrations that are higher than the MIC (that is, lethal doses), the potential for sublethal antibiotic concentrations to select for resistant mutants was mostly ignored. In this Review, we discuss the effects of exposing bacteria to antibiotic concentrations that are below the MIC (referred to hereafter as sub-mic concentrations; also referred to as subinhibitory in the literature). By definition, sub-mic antibiotic concentrations allow susceptible strains to continue to grow, which sometimes results in a reduced growth rate compared with the growth rate that is observed in the absence of the drug. Continued growth in the presence of sub-mic antibiotic levels is a crucial aspect of the current antibiotic resistance crisis, as these drug concentrations are found in many natural environments (such as sewage water and sludge, rivers, lakes and even drinking water 9 12 ), and they also occur NATURE REVIEWS MICROBIOLOGY ADVANCE ONLINE PUBLICATION 1

2 Human medicine Animal husbandry Plant production Aquaculture Therapeutic use Resistant bacteria Therapeutic and preventive use or growth promotion (Direct contact) Food Hospital Community Antibiotics (Urine and faeces) Resistant bacteria Antibiotics (Urine and faeces) Resistant bacteria (Direct spread or run-off) Environment Lakes, rivers and soils Antibiotics Pharmaceutical industry Accidental and intentional release of antibiotics from production plants Figure 1 Ecology of antibiotics and antibiotic resistance. An overview of the ecology of antibiotics, showing how these drugs are cycled between different environments, such as the medical environment, agricultural settings, the aquacultural environment, the pharmaceutical industry and the wider environment. A large percentage of the antibiotics that are used globally (20 80%, depending on the antibiotic class) are released into the environment in an active form, via the excretion of drugs in urine and faeces and the intentional or accidental release of drugs. Thus, antibiotics will exert selective pressure on bacteria in humans, animals and plants, owing to intentional use, and in the wider environment, owing to unintentional spill-over. This imposes a widespread selective pressure on bacteria, leading to the selection of resistant strains, which are also capable of transmitting between different environments, thereby creating the potential for the global movement of antibiotic resistance genes and determinants. Antibiotic gradients The gradual increases or decreases in antibiotic concentration that are observed between two spatially segregated sites (for example, two tissues in the body). Aquaculture The farming of aquatic organisms such as fish, mollusks and aquatic plants. in patients and livestock during antibiotic therapy More importantly, recent studies have shown that these low antibiotic concentrations exert their effects on at least three different levels: as selectors of resistance (by enriching for pre-existing resistant bacteria and by selecting for de novo resistance); as generators of genetic and phenotypic variability (by increasing the rate of adaptive evolution, including resistance development); and as signalling molecules (influencing various physiological activities, including virulence, biofilm formation and gene expression). The idea that sub-mic antibiotic concentrations can have a broad range of physiological and morphological effects on bacteria has been discussed since the very early days of clinical antibiotic use and is reviewed in a classic article by Lorian 16. In this Review, we discuss the ecology of antibiotics in the environment and describe recent studies that show that exposure to sub-mic antibiotic concentrations leads to the selection of bacterial drug resistance. We also consider the consequences of exposure to sublethal drug doses on bacterial physiology, including mutagenesis, virulence and biofilm formation. Sub-MIC environments Antibiotics have been naturally produced by bacteria and fungi for millions of years 17. Furthermore, during the last 70 years or so, humans have produced and used large amounts of antimicrobial drugs for both medicinal and agricultural purposes. Thus, human use, as well as natural antibiotic biosynthesis and release, generates antibiotic gradients in the body and in the wider environment, which results in bacterial exposure to concentrations that are both higher and lower than the MIC. These two antibiotic reservoirs (treated humans, livestock, crops or aquaculture, and the wider environment) are intimately connected, which leads to the cycling of antibiotics and bacteria (including antibiotic-resistant bacteria) between the in vivo and ex vivo environments (FIG. 1). Treated humans and livestock. When antibiotics are used clinically, the primary goal is to achieve the highest possible non-toxic concentration to obtain the highest cure rates and prevent the development of de novo resistance in the host. However, many human and animal treatment regimens fall short of achieving this goal, 2 ADVANCE ONLINE PUBLICATION

3 Box 1 The public health impact of antibiotic use in agriculture Whether the use of antibiotics in livestock is fuelling the spread of antibiotic-resistant bacteria among humans is currently a hotly debated question. Considering the general principles of evolution and the relative ease by which bacteria can spread between animals and humans (in both directions) (FIG. 1), agricultural use is expected to be an important contributor to the emergence of resistant bacteria in humans. However, the extent to which the crossover of resistant bacteria occurs and the conditions that facilitate such transmission events have been more difficult to determine, mostly owing to the lack of robust epidemiological data. Some recent studies strongly suggest that methicillin-resistant Staphylococcus aureus (MRSA) can be transmitted from infected animals to humans (in this case, livestock workers and veterinary practitioners) 122,123. In another study, it was shown that a livestock-associated MRSA strain had emerged from an antibiotic-susceptible human-associated strain after it crossed from humans to livestock 124. Together, these studies suggest that resistant pathogens not only emerge in agricultural settings but also subsequently transmit to humans, thus establishing an ecological link between MRSA in livestock and clinical cases of MRSA. However, this widely accepted view that human and animal epidemics of resistant bacteria are synonymous has been challenged by a recent study of the epidemiology of multidrugresistant Salmonella enterica subsp. enterica serovar Typhimurium DT104, using well-characterized isolates that were collected in Scotland over a 22 year period 125. Using whole-genome sequencing, the study dissected the phylogenetic associations of the bacterium and its resistance genes with co located human and animal populations to determine the origins and dissemination of resistance genes and the bacterium. The data suggested that only a small proportion of the infections were transmitted between humans and local animals, and the authors suggested that other sources, such as imported food, foreign travel and environmental reservoirs, were more important sources of S. Typhimurium infection and drug resistance in humans 125. The contrasting conclusions of these different studies might reflect differences between organisms and environments, but they also clearly highlight the need for greater availability, quality and consistency in international surveillance data in order to gain a full understanding of the ecology of bacterial zoonoses and the associated antimicrobial drug resistance genes. Minimal selective concentration (MSC). The lowest concentration of an antibiotic that results in the selection of a resistant mutant in a population over an isogenic susceptible strain. as antibiotic concentrations are often below the MIC in body compartments and tissues, such that target bacteria are only weakly inhibited 15. The reasons for these failures are manifold, including suboptimal dosing regimens, poor drug pharmacokinetics (that is, poor drug distribution and penetration into certain tissues), the use of low-activity drugs and poor patient compliance Moreover, in addition to the target bacteria, antibiotics often have a collateral effect on the microbiota and alter its composition, particularly when the treatment is of long-term duration 22,23. Such alterations are the result of lethal and non-lethal antibiotic concentrations in the intestine, on the skin and on epithelial surfaces In fact, for certain agricultural applications of antibiotics, the goal is to maintain long-term exposure to sub-mic antibiotic levels; for example, when antibiotics are used as feed additives to promote growth in animal production, the administered doses are typically subtherapeutic and often result in concentrations below the MIC 26,27. As a result, both the microbiota and pathogens that are present in these animals will experience longterm exposure to sub-lethal levels of antibiotics 27,28 that generally last for the whole production period, which ranges from months to years, depending on the species. The environment. In the ex vivo environment, bacteria are exposed to low levels of antibiotics owing to the natural production of antibiotics by bacteria and fungi, the excretion of antibiotics from treated subjects, the use of antibiotics in farming (BOX 1) and aquaculture and industrial pollution from antibiotic-production plants 11. Depending on the antibiotic class, 20 80% of an administered antibiotic is excreted by humans and animals (mainly via urine, but also via faeces) in an unchanged chemical form to waste water, sludge and manure 29. Thus, a substantial fraction of antibiotics (in their chemically stable form) that are used in animal husbandry, plant production, aquaculture and human therapy will ultimately end up in various external environments (such as rivers, lakes and soils ) and food products (such as milk and meat ), where they can potentially continue to exert their effects. For example, the consumption of meat or milk that has been contaminated with antibiotics in quantities that are below the detection limit, could result in antibiotic concentrations in the body that are above the minimal selective concentration (MSC; discussed below), which could lead to the enrichment of resistant bacteria. Another source of antibiotic contamination is effluent from pharmaceutical plants 42,43. Thus, antibiotics (and consequently antibiotic-resistant bacteria) can spread between environments and ecosystems (FIG. 1), and sublethal concentrations can potentially select for resistance, generate genotypic and phenotypic variability and function in bacterial signalling. Selection dynamics at sub-mic concentrations The MIC, which is the lowest concentration of antibiotic that is required to prevent bacterial growth, is a deceptively simple concept. It is measured under standardized in vitro conditions (that is, a defined growth medium, inoculum size, incubation temperature and duration) using twofold drug-dilution steps and subsequent visual evaluation of bacterial growth or non growth as the outcome. Some obvious caveats to the usefulness of the MIC include the fact that the determined values are relatively imprecise (as MIC is measured in a stepwise manner) and they may not easily translate into an effective concentration in vivo (as MIC is measured under very specific in vitro conditions). A more serious caveat is that the the MIC only measures the drug concentration that causes complete inhibition of visible bacterial growth and provides no information on the range of drug concentrations that, to varying degrees, reduce the bacterial growth rate and change the selection dynamics within a population. It has traditionally been assumed that the selection of resistant bacteria only occurs at antibiotic concentrations between the MIC of the susceptible wild-type population (MIC susc ) and the MIC of the resistant population (MIC res ). This suggests that concentrations that are lower than the MIC susc do not inhibit the growth of susceptible bacteria and are therefore not selective. This hypothesis, which is known as the mutant selective window hypothesis 44,45 has dominated the field, although the potential influence of sub-mic antibiotic concentrations on selection has also been discussed 14,15. However, theoretical discussions alone cannot provide a definitive answer, as experimental data is needed to determine the quantitative relationship between antibiotic concentration and NATURE REVIEWS MICROBIOLOGY ADVANCE ONLINE PUBLICATION 3

4 Mutational space All possible mutations that can confer a specific phenotype. This can vary from one to several mutations, depending on the system that is studied. selective force. In other words, how rapidly and to what extent do resistant bacteria outcompete their susceptible counterparts as a function of antibiotic levels? To address this cental question, two recent studies 46,47 designed and executed a rigorous set of experiments to test and measure the selective potential of sub-mic antibiotic concentrations (BOX 2). Enrichment of pre-existing resistant mutants. In the first study, susceptible wild-type and isogenic resistant strains of Escherichia coli and Salmonella enterica subsp. enterica serovar Typhimurium were competed at a range of antibiotic concentrations, which enabled the MSC of each antibiotic to be calculated 46 (BOX 2). Interestingly, the MSC values that were obtained were strongly dependent on the particular resistance mutation that was present. Several of the resistant mutants had MSC values that were tenfold lower than the MIC; the strain carrying the transposon Tn10 (which encodes tetracycline resistance) had an MSC value that was 100 fold lower than the MIC, and the Escherichia coli strain that had the most common mutation associated with fluoroquinolone resistance (S83L in gyra) had an MSC for ciprofloxacin that was 230 fold lower than the MIC 46. For all combinations of antibiotic, bacteria and resistance mutation that were tested (in addition to several other unpublished observations; D.I.A., D. H. and co workers), the MSC of the resistant strain was considerably lower than the MIC of the isogenic susceptible wild-type strain. Using an elegant colour-based assay (BOX 2), the second study obtained similar results 47, which together provided compelling evidence that sub-mic concentrations of antibiotics are generally selective for pre-existing resistant mutants in mixed bacterial populations. Using systemic infection models, a recent study has shown that bacterial exposure to low antibiotic concentrations in vivo leads to the preferential expansion of resistant subpopulations of Staphylococcus aureus and Pseudomonas aeruginosa 48. The authors found that exposure of mixtures of isogenic resistant and susceptible strains to subcurative tetracycline or oxacillin doses (defined as an antibiotic dose that produced no significant response in an in vivo model) resulted in a significant skewing of the strain ratios in favour of the resistant subpopulation. The mechanism of selection remains to be fully elucidated, but it seems to be strongly influenced by phagocyte activity and population bottlenecks during infection 48. Nevertheless, this study provides strong evidence for the ability of low antibiotic concentrations to select for resistant bacteria in vivo. De novo selection of resistance. In addition to the selection of pre-existing mutants, one study 46 also evolved multiple independent lineages of wild-type E. col i and S. Typhimurium strains under constant exposure to sub-mic (0.1 x MIC) levels of ciprofloxacin and streptomycin, respectively, to assess the emergence of de novo resistance. In all of the evolved lineages, the number of resistant subpopulations progressively increased throughout the course of the experiments (over a period of generations). After 600 generations, almost all lineages contained subpopulations of bacteria (of cells) that were resistant to concentrations of the drug that were several times higher than the MIC of the wild-type strain. These data show that the selective effect of sub-mic antibiotic concentrations is not limited to the enrichment of pre-existing mutants but that low antibiotic concentrations can also effectively select for de novo resistance in wild-type susceptible populations 46. Consequences of selection at sub-mic antibiotic concentrations. The experiments that are described above clearly show that extremely low antibiotic concentrations (in the ng per ml range) can select for bacterial resistance. Antibiotic concentrations in the ng per ml to µg per ml range are widespread in natural environments and are often associated with human sewage, run-off from farming activities and effluent from industrial plants 30,34,49. Accordingly, in addition to the selection of resistant strains during clinical therapy, it is likely that the selection of antibiotic resistance in ex vivo environments is an overlooked contributor to the widespread emergence of bacterial resistance on a global scale. Importantly, the selection of antibiotic resistance at sub-mic concentrations differs in several important respects from the selection of resistance at lethal drug concentrations. First, the mutational space is much greater at sub-mic concentrations than at lethal concentrations 50. When a wild-type susceptible population is exposed to a high (that is, lethal) concentration of antibiotic, the only mutants that survive are rare pre-existing mutants that have high-level resistance, whereas the remaining susceptible population is killed. Traditionally, these types of resistant mutants (those with large-effect phenotypes, such as high-level rifampicin resistance as a result of a single mutation in the rpob gene) are more amenable to study in vitro, and this has strongly influenced our understanding of the genetic basis of resistance and resistance mechanisms 8,51. By contrast, bacteria that are exposed to sub-mic antibiotic concentrations are inhibited in terms of growth but are not usually killed. Thus, as most of the population survives, non-lethal selection results in the emergence of a broader range of mutant variants particularly variants that carry high-frequency mutations, most of which will individually have small phenotypic effects 50. Examples of such small-effect mutations include partial chromosomal duplications 52,53. Duplications are frequent in bacterial populations (they occur at a frequency of per cell per gene) and are a major contributor to the development of resistance: first, by increasing the copy number of certain genes that confer low-level resistance, they can amplify a pre-existing weak resistance phenotype, and second, as such amplifications increase the probability of bacterial survival and growth in the presence of an antibiotic, this creates an opportunity for other, higher-level resistance mutations to emerge. Related to the point above, selection under sub-mic conditions also tends to be progressive (that is, it involves multiple mutations that accumulate successively) and is strongly associated with mutations that have a low 4 ADVANCE ONLINE PUBLICATION

5 Box 2 Selection of resistant mutants at sub-mic antibiotic concentrations One experimental set up that was used to measure and quantify the overnight growth, as the vast majority of cells were the tolc mutants effects of sub-minimal inhibitory concentration (sub-mic) antibiotic that expressed the purple chromogenic protein. However, if the strains concentrations involved constructing isogenic wild-type and resistant were inoculated at this 20/1 ratio in broth containing an antibiotic at a bacterial strains of Escherichia coli and Salmonella enterica subsp. enterica concentration that inhibited the growth rate of the hypersensitive tolc serovar Typhimurium 46. Each resistant strain differed from the wild type by mutant strain relative to that of the wild type, the wild type could then a single clinically relevant resistance mutation or resistance gene, which outgrow the mutant strain sufficiently to turn the culture bright yellow in conferred reduced susceptibility to fluoroquinolones, aminoglycosides or colour. Thus, yellow colour after overnight growth of a mixed culture was tetracycline. In addition, all strains carried a gene expressing either cyan diagnostic of the presence of a biologically relevant level of antibiotic. fluorescent protein (CFP) or yellow fluorescent protein (YFP) (which had a Both experimental systems can detect the presence of biologically negligible effect on fitness) to facilitate discrimination between the relevant antibiotic concentrations and each can be used to quantify the resistant and sensitive strains by FACS (fluorescence-activated cell MSC. They differ in their approach, in that one approach works by sorting) analysis. Strains were competed pairwise (wild type versus each enriching for mutants with reduced susceptibility 46, whereas the other mutant) in batch cultures at a range of antibiotic concentrations and approach works by inhibiting the growth of a hypersensitive strain relative were serially passaged at regular intervals for up to 80 generations. This to a wild-type strain 47. Figure adapted from REF. 46. experimental set up enabled the detection of growth-rate differences a as low as 0.3% per generation 46,126, which approaches the empirically 100 determined practical limit that is set by periodic selection events 127,128 (that is, the selection pressure that results in the selection of unrelated adaptive mutations). In the experiment shown in part a of the figure, the growth competitions at each tetracycline concentration were started with an 10 initial mutant/wild type ratio of 1/1. In the absence of antibiotic, the wild-type strain typically had a competitive advantage (which is indicated by the negative slope in part a of the figure), reflecting the relative fitness 1 cost of each particular resistance determinant. However, as the antibiotic concentration increased, there was a progressive shift in selection towards the isogenic resistant mutant strain (indicated by the positive slopes in part a of the figure). The slope of each competition (that is, the Generations of growth competition change in the ratio of the mutant/wild-type strains as a function of time) is used to calculate the selection coefficient. In these experiments, a positive 75 ng per ml tetracycline 25 ng per ml tetracycline selection coefficient means that the fraction of resistant mutants in 50 ng per ml tetracycline No antibiotic the population increases relative to the fraction of the susceptible wild-type population in the presence of a particular concentration of b 0.10 drug. By plotting the change in selection coefficient as a function of antibiotic concentration (see the figure, part b), it is possible to calculate 0.08 the lowest antibiotic concentration that is required to select for growth of the resistant mutant over the wild type (which is given by the intercept on 0.06 the x axis in part b of the figure); in other words, this is the lowest 0.04 antibiotic concentration that is needed to neutralize the fitness cost of each resistance determinant. This concentration is the minimal selective MSC 0.02 concentration (MSC) of antibiotic 46, and drug concentrations that exceed the MSC enrich for the resistant mutant strain (see the figure, part c). Note 0 that the MSC for tetracycline in this experiment (15 ng per ml; see the figure, part b) is 100 fold lower than the MIC of the susceptible wild-type strain (which is 1,500 ng per ml). These data show that, contrary to the classical view, in which selection is thought to operate only at drug Tetracycline concentration (ng per ml) concentrations between the MIC of the susceptible strain (MIC susc ) and the MIC of the resistant strain (MIC res ) which is known as the traditional c Sub-MIC Traditional selective window selection for resistant mutants also occurs at drug selective window selective window concentrations between the MSC and the MIC of the susceptible strain (which is known as the sub-mic selective window) 46 (see the figure, part c). A second experimental system 47 used wild-type E. col i and a drughypersensitive strain with a mutation in tolc. This mutant is hypersensitive to several antibiotics as the mutation in tolc eliminates the activity of the AcrAB TolC multidrug efflux pump. The wild-type strain was engineered to express YFP, whereas the mutant strain expressed a purple chromogenic protein. If the two strains were inoculated at an appropriate ratio (a mutant/wild type ratio of 20/1 a ratio that was empirically determined MSC MIC susc MIC res by the authors) in broth without drug, the culture colour was purple after Tetracycline concentration Selection coefficient Mutant/wild-type ratio Growth rate Antibiotic concentration fitness cost 33. The progressive nature of evolution under sub-mic selection arises as such low-cost mutations (for example, duplications and amplifications) typically occur at a high frequency 50,54. The strong association of low-fitness-cost mutations with sub-mic selection is a predictable consequence of the nature of selection and evolution under a weak selective pressure. This is because the antibiotic disturbs competition dynamics NATURE REVIEWS MICROBIOLOGY ADVANCE ONLINE PUBLICATION 5

6 FACS (Fluorescence-activated cell sorting). A laser-based technology that is used for cell sorting and cell counting, in which fluorescently tagged suspended cells pass through an electronic detection apparatus. Periodic selection A type of natural selection in which diversity within a bacterial population is recurrently purged owing to the emergence of adaptive mutants that outcompete other bacteria in the population. Selection coefficient A measure of the relative fitness of a strain or phenotype (it can also be used to refer to selective differences between genotypes). Fitness cost In the context of this review, the reduction in growth and reproductive potential that accompanies a resistance mutation or other genetic change. Mutator bacteria Bacteria with increased mutation rates; they are typically the result of inactivating mutations in DNA repair systems (such as the mismatch-repair system). SOS response A global response to DNA damage in which cell growth is arrested and DNA repair and mutagenesis are induced. The key proteins that are involved are RecA and LexA. Integrative conjugative elements (ICEs). Mobile genetic elements in bacterial chromosomes; they have the ability to be transferred between cells by conjugation. They encode the integrative ability of bacteriophages and transposons and the transfer mechanism of conjugative plasmids. RecBCD pathway A pathway of homologous recombination that utilizes the enzyme complex RecBCD and targets DNA with double-strand breaks. It requires RecA for strand invasion. in a mixed population by reducing the growth rate of the susceptible wild-type strain relative to that of the resistant mutant. In order to outcompete the wild-type strain, a resistant mutant that carries a high-cost mutation requires a higher concentration of antibiotic to sufficiently suppress wild-type growth, relative to the concentration that is required by a low-fitness-cost mutant. Thus, the MSC is a function of fitness cost, and low-cost resistance mutations should be preferentially selected for under sub-mic conditions as they have a low MSC. This association between low fitness cost and sub-mic selection has an important implication: it means that the restricted use of antibiotics as a means to counter-select resistant populations is unlikely to be effective in situations in which resistance has emerged under sub-mic selection. For those scenarios in which a reduction in the level of antibiotic use has failed to result in a decline in resistance (or has resulted in only a moderate decline), it is possible that low-fitness-cost mutants have been a contributing factor 55,56. Third, as sub-mic selection favours the accumulation of multiple small-step mutations, it enriches for mutator bacteria. Bacteria that have high mutation rates are enriched, as they accumulate mutations at an increased rate and thus experience more rapid adaptation to the growth-inhibitory environment. This is functionally analogous to the well-known correlation between selection in changing environments (for example, successive exposure to different antibiotics) and the enrichment of mutators 57. Last, the selective agent that is, sub-mic antibiotic concentrations can also modulate the rate at which resistant mutants occur by affecting the rates of horizontal gene transfer (HGT), recombination, and mutagenesis (discussed below). Such modulatory effects are less important at lethal drug concentrations, as the susceptible cells are typically killed before any associated phenotype is expressed. Increased genotypic and phenotypic variability In the previous sections, we argue that antibiotics at sub-mic levels are widely distributed in the in vivo and ex vivo environments and are capable of both enriching for resistant bacteria and selecting for de novo resistance. However, the mechanisms by which sub-mic antibiotic levels influence the selection of resistant bacteria might involve more than simply favouring the growth of resistant strains over their susceptible counterparts. In the 1960s, it was found that sub-mic concentrations of the aminoglycoside streptomycin cause misreading errors during translation, which result in phenotypic changes, such as reduced growth rate 58. It was also proposed that errors in protein synthesis might be propagated to the genome, owing to the production of defective DNA polymerases by error-prone translation 59. Although the idea that antibiotic-associated translational errors might be a cause of mutations generated a lot of interest and debate 60, few studies tested the hypothesis 61,62. However, a growing body of evidence suggests that several antibiotics at sub- MIC concentrations and not just those that induce translational errors can increase the rate of resistance development. This involves an increase in the rates and frequency of various genetic processes, including HGT 63 65, recombination and mutagenesis (FIG. 2). Increased HGT and recombination. HGT can be stimulated by antibiotics and is often mediated by the induction of the SOS response (BOX 3); for example, treatment of E. col i O157:H7 with fluoroquinolones activates the SOS response, resulting in the induction of a prophage that encodes the shiga toxin gene. Increased expression of the toxin (which exacerbates the disease symptoms) and amplification of the phage population promotes transfer of the toxin gene to susceptible bacteria 77. Similarly, fluoroquinolones also activate the SOS response in S. aureus, which induces staphylococcal prophages and co resident staphylococcal pathogenicity islands to excise and replicate 64. These pathogenicity islands can then be transferred to susceptible strains by the induced phage. Antibiotic-stimulated SOS induction can also promote the transmission of antibiotic resistance genes, as exemplified by the spread of integrative conjugative elements (ICEs) throughout populations of Vibrio cholerae 65. SXT is a 100 kb V. cholerae ICE that encodes genes conferring resistance to chlor amphenicol, sulphamethoxazole, trimethoprim, streptomycin and heavy metals 78. Before 1993, SXT-related elements were not detected in V. cholera e, but they are now present in almost all Asian and African isolates 78,79. The ability of SXT to transfer is regulated by a repressor protein, SetR, but this repression is relieved by the induction of the SOS response. Two antibiotic classes the fluoroquinolones and trimethoprim have been shown to induce SXT by stimulating the transcription of conjugative, transfer and integrase genes, which suggests that the use of antibiotics might promote the spread of SXT-like ICE elements in V. cholerae 65. Antibiotic exposure can also affect recombination independently of HGT. Sublethal fluoroquinolone concentrations were shown to stimulate intrachromosomal recombination between identical and near-identical sequences in E. coli (via either the RecBCD pathway or the RecFOR pathway) and to stimulate conjugational (that is, interchromosomal) recombination, both of which were independent of induction of the SOS response 66. The same study also showed that fluoroquinolones stimulate recombination in mismatch-repair system-deficient mutator strains, which already have a high rate of recombination in the absence of antibiotics 66. This stimulation of homologous recombination seems to be specific for fluoro quinolones, as it was not observed following exposure to ten other antibiotics that were of different chemical classes and had different molecular targets 67. Recombination involving class I integrons is also stimulated by antibiotic exposure. These genetic elements, which are frequently found in Gram-negative pathogens, often encode arrays of antibiotic resistance gene cassettes under the control of a single promoter 80 and can accumulate new gene cassettes in a recombination process that is mediated by a site-specific integrase enzyme. The system is organized such that the cassettes that are closest to the promoter are expressed at the 6 ADVANCE ONLINE PUBLICATION

7 Sub-MIC antibiotic concentrations (fluoroquinolones, β-lactams and aminoglycosides) SOS response RpoS induction Prophage induction ICE induction Integron recombination Transposition Error-prone DNA polymerase G T T srna Replicative DNA polymerase A T T Inhibition of mismatch repair HGT and recombination Mutagenesis Figure 2 Influence of sub-mic levels of antibiotics on HGT, recombination and mutagenesis. Several classes of antibiotics at sub-minimal inhibitory concentration (sub-mic) levels (such as fluoroquinolones, β lactams and aminoglycosides) have been shown to induce the SOS response and the RpoS regulon. The downstream consequences of induction can lead to genetic alterations that are associated with the movement of mobile elements (such as the induction of prophages, integrative conjugative elements (ICEs) and transposons all of which can carry resistance and/ or virulence determinants), activation of recombinases (such as integrases and transposases) and an increase in the rate of mutagenesis during chromosome replication (by the induction of error-prone DNA polymerases and the suppression of mismatch repair). Note that these processes are not completely distinct in their consequences: recombination (including transposition and integron rearrangements) is a form of genetic mutation, transposition is often closely associated with horizontal gene transfer (HGT), if the transposon recombines into a mobile element, and mutagenesis caused by DNA polymerases can increase rates of intrachromosomal recombination and transposition as well as causing point mutations. RecFOR pathway A pathway of homologous recombination that involves the enzymes RecJ and RecFOR. It primarily functions on DNA with single-strand breaks and requires RecA for strand invasion. Mismatch-repair system A strand-specific DNA-repair system that is present in most organisms; it recognizes and repairs erroneous DNA replication and recombination and DNA damage. Sigma factors Transcription factors that target RNA polymerase to specific gene promoters during the initiation of transcription. highest levels. Accordingly, changes in the relative expression of individual gene cassettes can be modulated by rearranging the order of cassettes by site-specific recombination 80. Importantly, this type of integron rearrangement event probably led to the emergence of a cephalosporin-resistant P. aeruginosa strain in a hospital patient who was undergoing antibiotic therapy 68. The rearrangement that caused cephalosporin resistance involved the deletion of a gene that was originally located upstream of the ESBL gene on the integron, which resulted in increased transcription, translation and secretion of the β lactamase gene in vitro, as it was positioned closer to the promoter. The patient had been treated with a cephalosporin (to treat P. aeruginos a) and metronidazole (to treat an anaerobic infection). It was shown that metronidazole could trigger the SOS response in P. aeruginosa, thus activating the expression of integrase and thereby inducing cassette rearrangements. This mechanism provides a plausible scenario for the selection of a cephalosporin-resistant strain in this patient during therapy and implicates antibioticmediated genetic rearrangements in the emergence of clinical resistance 68. Increased mutagenesis. Sub-MIC antibiotic concentrations have been shown to increase mutagenesis, which is also associated with the induction of the SOS response 67,71, Inactivation of reca 74 or the presence of a non-cleavable LexA repressor 75 both of which inhibit activation of the SOS response abolishes this mutagenic effect. In S. aureu s, induction of the SOS response by sublethal antibiotic concentrations was also shown to increase the rate of IS256 transposition by a mechanism that was dependent on the downstream effects of SOS induction on the regulation of transposition by sigma factors 75. An important recent study elucidated the mechanism by which sub-mic concentrations of the β lactam antibiotic ampicillin increase mutagenesis in E. coli 76. This study found that sub-mic concentrations of bacteriocidal antibiotics (for example, the fluoroquinolones, aminoglycosides and β lactams) induce expression of the stress-response sigma factor RpoS. Using ampicillin as a model bacteriocidal drug, it was shown that the increase in RpoS expression is regulated at the levels of translation and protein stability. RpoS positively regulates the small RNA (srna) SdsR and, at elevated RpoS concentrations, this srna is induced and was shown to bind to and repress the muts mrna. As a consequence, cells become depleted for the MutS protein (which has a central role in the repair of replication errors), thereby leading to an increase in mutation rate. Further investigation revealed that the mutagenesis that is induced by sub-mic levels of ampicillin was caused by the combined activities of both the normal replicative DNA polymerase (in the absence of adequate mismatch repair, owing to MutS depletion) and of the error-prone DNA polymerase IV, which is part of the RpoS regulon (FIG. 2). Combined with the large body of evidence from different bacterial species, which shows that low levels NATURE REVIEWS MICROBIOLOGY ADVANCE ONLINE PUBLICATION 7

8 Box 3 The SOS response The term SOS response refers to a set of co regulated genes that are induced in response to DNA damage 129,130. The system is widespread in bacteria and promotes cell survival by repairing damaged genomes. In Escherichia coli, the SOS system consists of more than 40 genes and is regulated by the LexA repressor protein (see the figure). Following a single-stranded DNA (ssdna) or double-stranded DNA (dsdna) break, activated RecA protomers assemble into filaments on chromosomal sites that have persistent single-stranded DNA as they are not repaired. Interactions between activated RecA protomers and the LexA repressor induce the autocleavage of LexA, which causes it to dissociate from the DNA, thereby relieving repression of the SOS regulon. The genes that are regulated by LexA include lexa itself, which generates a negative-feedback loop to re establish repression after the damage is repaired. Other genes within the SOS system include uvrabc (which is involved in nucleotide-excision repair), reca (which is required for homologous recombination) and genes that encode several translesion DNA polymerases: dina (which encodes pol II), dinb (which encodes pol IV) and umudc (which encodes pol V). The activity of the translesion polymerases is a double-edged sword : they maintain chromosome integrity by enabling the replication machinery to bypass lesions that otherwise block the passage of the replicative DNA polymerase, but they also contribute to mutagenesis by introducing base substitutions at a high frequency. As the LexA-binding sequences that are upstream of its regulated genes vary around a consensus sequence, there are differences in the binding affinity of LexA for different genes in the SOS system, and consequently, genes that have low affinities, including lexa, are upregulated early. Secondary metabolites Organic compounds that are not directly involved in the normal growth, development and reproduction of an organism. Activated RecA protomers ssdna or dsdna break LexA RecA filament Autocleavage of LexA LexA-regulated gene Transcription Transcription of different classes of antibiotics induce mutagenesis, this study supports the hypothesis that sub-mic drug concentrations are likely to have an important role in the generation and evolution of resistance 76. Phenotypic variability. The effects of sub-mic antibiotic concentrations are not only limited to genetic alterations but also affect bacterial phenotypes. This is clearly evident from several studies that show that sublethal anti biotic levels increase the frequency of persisters. Persisters are slowly growing or non-growing phenotypic variants that stochastically emerge in susceptible bacterial populations and are refractory to multiple antibiotics. The slowly growing or non-growing state of bacterial persisters, which is the result of a general arrest in metabolic activity, is thought to be responsible for their ability to survive exposure to antibiotics 81. Two major differences distinguish persistence from resistance: first, antibiotic tolerance is not heritable as it is not caused by genetic mutation and, second, persistence is a transient state that is reversed following the removal of the antibiotic. Persistence is suggested to have important clinical implications as it is thought to reduce the rate of clearance of bacterial infections 82 and to potentially promote the emergence of genetically resistant mutants. Thus, it is important to understand how persisters are generated and the factors that determine their emergence in populations. The question of the origin of persisters in otherwise susceptible populations has been controversial, but two studies have shown that exposure to sublethal antibiotic concentrations might have a role. These two studies showed that pretreatment of susceptible populations of E. coli and S. aureus with sub-mic concentrations of antibiotics resulted in a considerable increase in the frequency of persister cells following subsequent exposure to bacteriocidal concentrations of the same antibiotics 83,84. The mechanism of ciprofloxacin-induced persister formation was dependent on the induction of the SOS response, which suggests that the refractory state was the result of DNA damage 83. Persisters that were generated by exposure to sub-mic concentrations of one antibiotic (such as ciprofloxacin, gentamicin, vancomycin or oxacillin) were also found to be refractory to various other classes of antibiotics to which they had not been pre-exposed 84, which is consistent with the multidrug-tolerant phenotype of persister cells. The conclusion that antibiotics at sub-mic concentrations are responsible for inducing the formation of persisters is also supported by the high degree of variation in the frequency of persisters in independent populations after drug exposure 84. Low antibiotic levels as intercellular signals Microorganisms synthesize a large number of nonpolymeric small molecules that often have unclear metabolic and physiological roles in the producer organism Some of these molecules have antibacterial activity, as defined by their ability to inhibit bacterial growth Antibiotic production in nature clearly must provide a substantial benefit to the producers, considering that these complex and energy-requiring biosynthetic pathways have evolved and are maintained. The most common explanation for the role of antibiotics in nature is that they function as ecological weapons, such that, in a complex multispecies community, the producer species can inhibit the growth of competitors 90 ; however, other potential roles have also been proposed. One hypothesis suggests that antibiotic production (and the synthesis of so called secondary metabolites in general) fulfils a metabolic role by enabling bacteria to eliminate excess reducing power by the excretion of antibiotics 91,92. A particularly interesting case is the role of endogenous phenazine antibiotics in promoting the anaerobic survival of P. aeruginosa by facilitating extracellular electron transfer 92. Another interesting idea is that antibiotics at low, non-inhibitory concentrations can function as signalling molecules between cells of the same species or between cells of different species 93. Such signalling has a range of functional consequences, including the induction of conjugative transfer, gene expression, quorum sensing, biofilm formation and bacterial virulence 87,88,92,94 97 (TABLE 1). Quorum sensing. Evidence for the potential involvement of antibiotics in quorum sensing comes from two types of evidence: first, specific types of antibiotics are 8 ADVANCE ONLINE PUBLICATION

9 Table 1 Sub-MIC antibiotic concentrations alter a diverse range of processes in bacteria Process altered Target* Antibiotic involved Bacterial species Gene expression DNA CIP; FUR; NOR; OFL; SXT; TRM E. coli 139,140,141 ; L. monocytogenes 109 ; P. aeruginosa 142 ; S. aureus 104 RNA RIF E. coli 139 ; L. monocytogenes 109 ; S. enterica 135,136,143 Protein Cell wall AZI; CHL; CLI; DAP; ERY; FLO; GEN; KAN; LIN; PUR; TET AMP; AMX; BAC; CAZ; CEC; CXM; PEN; POL; TEC; VAN Membrane CER S. aureus 151 SOS induction DNA CIP; FUR; LEV; NOR; OFL; TRM E. coli 66,141,152 ; S. aureus 64,153 Cell wall β lactams E. coli 154 Virulence DNA CIP; TRM S. aureus 113 Protein AZI; CLI; LIN P. aeruginosa 98 ; S. aureus 107 B. subtilis 144 ; E. coli 139 ; L. monocytogenes 109 ; P. aeruginosa 98 ; S. aureus 107,106,103,145 ; S. enterica 135,146 ; S. pneumoniae 147 ; S. pyogenes 110 E. coli 139,148,149 ; L. monocytogenes 109,150 ; P. aeruginosa 142 ; S. enterica 111 Biofilm formation Protein AZI; CIP; TGC; TOB E. faecalis 155 ; P. aeruginosa 98,99,105 ; S. aureus 104 Quorum sensing Protein AZI; AI peptides P. aeruginosa 98,99,101 ; S. aureus 100 ; S. pneumoniae 102 Conjugation Protein TET Bacteroides ; B. subtilis 159 ; L. monocytogenes 160 Cell wall β lactams S. aureus 161 Flagella formation Protein MUP P. aeruginosa 108 ; P. mirabilis 108 Haemolysis Cell wall CEF S. aureus 112 AI, autoinducer; AMP, ampicillin; AMX, amoxicillin; AZI, azithromycin; BAC, bacitracin; B. subtilis, Bacillus subtilis; CAZ, ceftazidime; CEC, cecropin A; CEF, cefoxitin; CER, cerulenin; CHL, chloramphenicol; CIP, ciprofloxacin; CLI, clindamycin; CXM, cefuroxime; DAP, daptomycin; E. coli, Escherichia coli; E. faecalis, Enterococcus faecalis; ERY, erythromycin; FLO, florfenicol; FUR, furazolidine; GEN, gentamycin; KAN, kanamycin; LEV, levofloxacin; LIN, linezolid; L. monocytogenes, Listeria monocytogenes; MIC, minimal inhibitory concentration; MUP, mupirocin; NOR, norfloxacin; OFL, ofloxacin; P. aeruginosa, Pseudomonas aeruginosa; PEN, penicillin; P. mirabilis, Proteus mirabilis; POL, polymyxin; PUR, puromycin; RIF, rifampicin; S. aureus, Staphylococcus aureus; S. enterica, Salmonella enterica; S. pneumoniae, Streptococcus pneumoniae; S. pyogenes, Streptococcus pyogenes; SXT, cotrimexazole; TEC, teichoplanin; TET, tetracycline; TGC, tigecycline; TOB, tobramycin; TRM, trimethoprim; VAN, vancomycin. *Target: DNA refers to replication, supercoiling or nucleotide precursor synthesis; RNA refers to RNA polymerase; protein refers to the protein synthesis machinery, mainly the ribosome; cell wall refers to peptidoglycan synthesis; and membrane refers to the cell membrane. Competence A transient physiological state in which bacteria are proficient in the uptake of extracellular DNA. Natural competence is usually regulated in response to environmental signals. directly involved in quorum sensing (such as lantibiotics) or interfere with quorum sensing, and second, certain quorum-sensing autoinducers have antimicrobial activity. As quorum-sensing systems often regulate virulence gene expression and biofilm formation, the observed downstream effects of interfering with quorum sensing are often related to alterations in virulence-associated properties (see below). For example, the macrolide azithromycin strongly antagonizes quorum sensing in P. aeruginosa, which results in the reduced production of virulence factors and impaired biofilm formation 98. This inhibition seems to result from azithromycinmediated inhibition of gene expression, specifically of the genes encoding enzymes that are involved in the synthesis of the autoinducer N acyl homoserine lactone 99. Examples of autoinducers that have antimicrobial activity include S. aureu s peptides that seem to function as both autologous inducers (of related strains) and growth inhibitors (of strains from other groups) 100. Similarly, the autoinducer Ahl1, which is produced by the Gram-negative species P. aeruginosa, inhibits the growth of Gram-positive bacteria 101. Another interesting case is the autoinducer competence-stimulating peptide (CSP), which is produced by Streptococcus pneumoniae for the control of competence; this peptide causes a temporary growth arrest that blocks systemic infection in mice 102. Biofilm formation and adherence. Exposure of S. aureus to sub-mic levels of florfenicol (an analogue of chloramphenicol that is used in veterinary medicine) causes a substantial increase in bacterial adherence to eukaryotic host cells, owing to the induction of a global gene activator, sae (which encodes a regulator of a two-component system), and the stabilization of mrnas that encode adherence-associated proteins 103. In another example, sub-mic levels of ciprofloxacin were shown to upregulate the expression of fibronectin-binding proteins in S. aureu s, which increases bacterial adherence to host tissue. This increased expression of fibronectin-binding proteins seems to involve two pathways: upregulation of the stress-response sigma factor SigB and induction of the SOS response (which is RecA and LexA dependent). The combined activity of both pathways promotes bacterial adhesion 104. Interestingly, in P. aeruginosa and E. coli, aminoglycoside antibiotics (such as tobramycin) have been found to induce biofilm formation. In P. aeruginos a, this response requires a functional arr gene, which encodes an inner membrane phosphodiesterase, the substrate of which is cyclic di guanosine monophosphate (c di GMP), which is a second messenger molecule that has a well-established role in biofilm formation, as it inhibits bacterial motility and promotes cell surface adhesion 105. Virulence. Expression of virulence factors in bacteria is regulated by a network of regulatory factors and signal transduction pathways that respond to specific environmental cues, such as ph, ions, nutrient status, temperature and oxygen radicals, among others. As virulence factor expression is responsive to these complex pathways, NATURE REVIEWS MICROBIOLOGY ADVANCE ONLINE PUBLICATION 9