Over the past few decades, the emergence of multidrug resistance (MDR) to antibiotics in bacteria has led to major difficulties in the management of infected patients. At present, there is a serious lack of development of new antibacterial agents. Mathematical models are one approach to understand how antibiotic usage patterns may be optimized. However, the classical approach to modeling the emergence of MDR relies on the simplifying assumption that resistance is acquired at a constant rate. In their model, Obolski and Hadany introduce the notion of horizontal gene transfer and stress-induced mutation, with antibiotics constituting an environmental stressor of particular relevance. Finally, from this complex mathematical model, the authors propose predictions for minimizing MDR in bacteria depending on strategies of antibiotic treatment.
Please see related article: http://www.biomedcentral.com/1741-7015/10/89
antibiotic resistance; mathematical models; multidrug resistance
Antibiotic resistance arises through mechanisms such as selection of naturally occurring resistant mutants and horizontal gene transfer. Recently, oxidative stress has been implicated as one of the mechanisms whereby bactericidal antibiotics kill bacteria. Here we show that sub-lethal levels of bactericidal antibiotics induce mutagenesis, resulting in heterogeneous increases in the minimum inhibitory concentration for a range of antibiotics, irrespective of the drug target. This increase in mutagenesis correlates with an increase in ROS, and is prevented by the ROS scavenger thiourea and by anaerobic conditions, indicating that sub-lethal concentrations of antibiotics induce mutagenesis by stimulating the production of ROS. We demonstrate that these effects can lead to mutant strains that are sensitive to the applied antibiotic but resistant to other antibiotics. This work establishes a radical-based molecular mechanism whereby sub-lethal levels of antibiotics can lead to multidrug resistance, which has important implications for the widespread use and misuse of antibiotics.
Finding the most potent combinations of antibiotics in the lab can be a challenge if antibiotic interactions are not robust to evolutionary adaptation.
Conventional wisdom holds that the best way to treat infection with antibiotics is to ‘hit early and hit hard’. A favoured strategy is to deploy two antibiotics that produce a stronger effect in combination than if either drug were used alone. But are such synergistic combinations necessarily optimal? We combine mathematical modelling, evolution experiments, whole genome sequencing and genetic manipulation of a resistance mechanism to demonstrate that deploying synergistic antibiotics can, in practice, be the worst strategy if bacterial clearance is not achieved after the first treatment phase. As treatment proceeds, it is only to be expected that the strength of antibiotic synergy will diminish as the frequency of drug-resistant bacteria increases. Indeed, antibiotic efficacy decays exponentially in our five-day evolution experiments. However, as the theory of competitive release predicts, drug-resistant bacteria replicate fastest when their drug-susceptible competitors are eliminated by overly-aggressive treatment. Here, synergy exerts such strong selection for resistance that an antagonism consistently emerges by day 1 and the initially most aggressive treatment produces the greatest bacterial load, a fortiori greater than if just one drug were given. Whole genome sequencing reveals that such rapid evolution is the result of the amplification of a genomic region containing four drug-resistance mechanisms, including the acrAB efflux operon. When this operon is deleted in genetically manipulated mutants and the evolution experiment repeated, antagonism fails to emerge in five days and antibiotic synergy is maintained for longer. We therefore conclude that unless super-inhibitory doses are achieved and maintained until the pathogen is successfully cleared, synergistic antibiotics can have the opposite effect to that intended by helping to increase pathogen load where, and when, the drugs are found at sub-inhibitory concentrations.
We take an evolutionary approach to a problem from the medical sciences in seeking to understand how our knowledge of rapid bacterial evolution should shape the way we treat pathogens with antibiotic drugs. We pay particular attention to combinations of different drugs that are purposefully used to produce potent therapies. Textbook orthodoxy in medicine and pharmacology states one should hit the pathogen hard with the drug and then prolong the treatment to be certain of clearing it from the host; how effective this approach is remains the subject of discussion. If the textbooks are correct, a combination of two antibiotics that prevents bacterial growth more than if just one drug were used should provide a better treatment strategy. Testing alternatives like these, however, is difficult to do in vivo or in the clinic, so we examined these ideas in laboratory conditions where treatments can be carefully controlled and the optimal combination therapy easily determined by measuring bacterial densities at every moment for each treatment trialled. Studying drug concentrations where antibiotic synergy can be guaranteed, we found that treatment duration was crucial. The most potent combination therapy on day 1 turned out to be the worst of all the therapies we tested by the middle of day 2, and by day 5 it barely inhibited bacterial growth; by contrast, the drugs did continue to impair growth if administered individually.
The evolution of multi-antibiotic resistance in bacterial pathogens, often resulting from de novo mutations, is creating a public health crisis. Phages show promise for combating antibiotic-resistant bacteria, the efficacy of which, however, may also be limited by resistance evolution. Here, we suggest that phages may be used as supplements to antibiotics in treating initially sensitive bacteria to prevent resistance evolution, as phages are unaffected by most antibiotics and there should be little cross-resistance to antibiotics and phages. In vitro experiments using the bacterium Pseudomonas fluorescens, a lytic phage, and the antibiotic kanamycin supported this prediction: an antibiotic–phage combination dramatically decreased the chance of bacterial population survival that indicates resistance evolution, compared with antibiotic treatment alone, whereas the phage alone did not affect bacterial survival. This effect of the combined treatment in preventing resistance evolution was robust to immigration of bacteria from an untreated environment, but not to immigration from environment where the bacteria had coevolved with the phage. By contrast, an isogenic hypermutable strain constructed from the wild-type P. fluorescens evolved resistance to all treatments regardless of immigration, but typically suffered very large fitness costs. These results suggest that an antibiotic–phage combination may show promise as an antimicrobial strategy.
coevolution; fitness cost; immigration; mutator bacteria; phage therapy
The emergence and ongoing spread of antimicrobial-resistant bacteria is a major public health threat. Infections caused by antimicrobial-resistant bacteria are associated with substantially higher rates of morbidity and mortality compared to infections caused by antimicrobial-susceptible bacteria. The emergence and spread of these bacteria is complex and requires incorporating numerous interrelated factors which clinical studies cannot adequately address.
A model is created which incorporates several key factors contributing to the emergence and spread of resistant bacteria including the effects of the immune system, acquisition of resistance genes and antimicrobial exposure. The model identifies key strategies which would limit the emergence of antimicrobial-resistant bacterial strains. Specifically, the simulations show that early initiation of antimicrobial therapy and combination therapy with two antibiotics prevents the emergence of resistant bacteria, whereas shorter courses of therapy and sequential administration of antibiotics promote the emergence of resistant strains.
The principal findings suggest that (i) shorter lengths of antibiotic therapy and early interruption of antibiotic therapy provide an advantage for the resistant strains, (ii) combination therapy with two antibiotics prevents the emergence of resistance strains in contrast to sequential antibiotic therapy, and (iii) early initiation of antibiotics is among the most important factors preventing the emergence of resistant strains. These findings provide new insights into strategies aimed at optimizing the administration of antimicrobials for the treatment of infections and the prevention of the emergence of antimicrobial resistance.
The emergence of pathogenic bacteria resistant to multiple antibiotics is a serious worldwide public health concern. Whenever antibiotics are applied, the genes encoding for antibiotic resistance are selected for within bacterial populations. This has led to the prevalence of conjugative plasmids that carry resistance genes and can transfer themselves between diverse bacterial groups. In this study, we investigated whether it is feasible to attempt to prevent the spread of antibiotic resistances with a lytic bacteriophage, which can replicate in a wide range of gram-negative bacteria harbouring conjugative drug resistance–conferring plasmids. The counter-selection against the plasmid was shown to be effective, reducing the frequency of multidrug-resistant bacteria that formed via horizontal transfer by several orders of magnitude. This was true also in the presence of an antibiotic against which the plasmid provided resistance. Majority of the multiresistant bacteria subjected to phage selection also lost their conjugation capability. Overall this study suggests that, while we are obligated to maintain the selection for the spread of the drug resistances, the ‘fight evolution with evolution’ approach could help us even out the outcome to our favour.
evolution of antibiotic resistance; conjugation; conjugative plasmid-dependent phages; phage therapy
There is a dearth of treatment options for community-acquired and nosocomial Pseudomonas infections due to several rapidly emerging multidrug resistant phenotypes, which show resistance even to combination therapy. As an alternative, developing selective promiscuous hybrid compounds for simultaneous modulation of multiple targets is highly appreciated because it is difficult for the pathogen to develop resistance when an inhibitor has activity against multiple targets.
In line with our previous work on phytochemical–antibiotic combination assays and knowledge-based methods, using a fragment combination approach we here report a novel drug design strategy of conjugating synergistic phytochemical–antibiotic combinations into a single hybrid entity for multi-inhibition of P. aeruginosa DNA gyrase subunit B (GyrB)/topoisomerase IV subunit B (ParE) and dihydrofolate reductase (DHFR) enzymes. The designed conjugates were evaluated for their multitarget specificity using various computational methods including docking and dynamic simulations, drug-likeness using molecular properties calculations, and pharmacophoric features by stereoelectronic property predictions.
Evaluation of the designed hybrid compounds based on their physicochemical properties has indicated that they are promising drug candidates with drug-like pharmacotherapeutic profiles. In addition, the stereoelectronic properties such as HOMO (highest occupied molecular orbital), LUMO (lowest unoccupied molecular orbital), and MEP (molecular electrostatic potential) maps calculated by quantum chemical methods gave a good correlation with the common pharmacophoric features required for multitarget inhibition. Furthermore, docking and dynamics simulations revealed that the designed compounds have favorable binding affinity and stability in both the ATP-binding sites of GyrB/ParE and the folate-binding site of DHFR, by forming strong hydrogen bonds and hydrophobic interactions with key active site residues.
This new design concept of hybrid “phyto-drug” scaffolds, and their simultaneous perturbation of well-established antibacterial targets from two unrelated pathways, appears to be very promising and could serve as a prospective lead in multitarget drug discovery.
hybrid compounds; multi-target inhibition; drug resistance; dihydrofolate reductase; DNA gyrase subunit B; topoisomerase IV subunit B; rational drug design
The authors show that some mycobacteria carrying mutations conferring resistance to two antibiotics have a higher competitive fitness than corresponding strains carrying only one of these mutations. Moreover, the double-resistant strains exhibiting the highest competitive fitness in the laboratory are overrepresented in clinical settings with a high burden of extensively drug-resistant tuberculosis.
Background and objectives: Multidrug resistant (MDR) bacteria are a growing threat to global health. Studies focusing on single antibiotics have shown that drug resistance is often associated with a fitness cost in the absence of drug. However, little is known about the fitness cost associated with resistance to multiple antibiotics.
Methodology: We used Mycobacterium smegmatis as a model for human tuberculosis (TB) and an in vitro competitive fitness assay to explore the combined fitness effects and interaction between mutations conferring resistance to rifampicin (RIF) and ofloxacin (OFX); two of the most important first- and second-line anti-TB drugs, respectively.
Results: We found that 4 out of 17 M. smegmatis mutants (24%) resistant to RIF and OFX showed a statistically significantly higher or lower competitive fitness than expected when assuming a multiplicative model of fitness effects of each individual mutation. Moreover, 6 out of the 17 double drug-resistant mutants (35%) had a significantly higher fitness than at least one of the corresponding single drug-resistant mutants. The particular combinations of resistance mutations associated with no fitness deficit in M. smegmatis were the most frequent among 151 clinical isolates of MDR and extensively drug-resistant (XDR) Mycobacterium tuberculosis from South Africa.
Conclusions and implications: Our results suggest that epistasis between drug resistance mutations in mycobacteria can lead to MDR strains with no fitness deficit, and that these strains are positively selected in settings with a high burden of drug-resistant TB. Taken together, our findings support a role for epistasis in the evolution and epidemiology of MDR- and XDR-TB.
microbiology; antimicrobial; epidemiology; infection
When growing populations of bacteria are confronted with bactericidal antibiotics, the vast majority of cells are killed, but subpopulations of genetically susceptible but phenotypically resistant bacteria survive. In accord with the prevailing view, these “persisters” are non- or slowly dividing cells randomly generated from the dominant population. Antibiotics enrich populations for pre-existing persisters but play no role in their generation. The results of recent studies with Escherichia coli suggest that at least one antibiotic, ciprofloxacin, can contribute to the generation of persisters. To more generally elucidate the role of antibiotics in the generation of and selection for persisters and the nature of persistence in general, we use mathematical models and experiments with Staphylococcus aureus (Newman) and the antibiotics ciprofloxacin, gentamicin, vancomycin, and oxacillin. Our results indicate that the level of persistence varies among these drugs and their concentrations, and there is considerable variation in this level among independent cultures and mixtures of independent cultures. A model that assumes that the rate of production of persisters is low and persisters grow slowly in the presence of antibiotics can account for these observations. As predicted by this model, pre-treatment with sub-MIC concentrations of antibiotics substantially increases the level of persistence to drugs other than those with which the population is pre-treated. Collectively, the results of this jointly theoretical and experimental study along with other observations support the hypothesis that persistence is the product of many different kinds of errors in cell replication that result in transient periods of non-replication and/or slowed metabolism by individual cells in growing populations. This Persistence as Stuff Happens (PaSH) hypothesis can account for the ubiquity of this phenomenon. Like mutation, persistence is inevitable rather than an evolved character. What evolved and have been identified are genes and processes that affect the frequency of persisters.
Because of its importance to therapy, a great deal of effort has been devoted to understanding the mechanisms responsible for and the genetic basis of persistence in inherently susceptible but phenotypically antibiotic-resistant subpopulations of bacteria. Much of this research is based on the premise that persisters are produced at random from the susceptible population and the antibiotics used to detect them play no role in their generation. The results of this jointly theoretical and experimental study are inconsistent with this hypothesis. These results, along with observations reported by other investigators, including the failure to find bacteria that do not produce persisters but an abundance of genes modifying their frequency, support the hypothesis that there are many mechanisms responsible for persistence. Based on these collective theoretical and experimental results, along with evolutionary considerations, we postulate that persistence is analogous to mutation. It is an inevitable product of errors and glitches in cell replication and metabolism rather than an evolved character.
There are both pharmacodynamic and evolutionary reasons to use multiple rather than single antibiotics to treat bacterial infections; in combination antibiotics can be more effective in killing target bacteria as well as in preventing the emergence of resistance. Nevertheless, with few exceptions like tuberculosis, combination therapy is rarely used for bacterial infections. One reason for this is a relative dearth of the pharmaco-, population- and evolutionary dynamic information needed for the rational design of multi-drug treatment protocols. Here, we use in vitro pharmacodynamic experiments, mathematical models and computer simulations to explore the relative efficacies of different two-drug regimens in clearing bacterial infections and the conditions under which multi-drug therapy will prevent the ascent of resistance. We estimate the parameters and explore the fit of Hill functions to compare the pharmacodynamics of antibiotics of four different classes individually and in pairs during cidal experiments with pathogenic strains of Staphylococcus aureus and Escherichia coli. We also consider the relative efficacy of these antibiotics and antibiotic pairs in reducing the level of phenotypically resistant but genetically susceptible, persister, subpopulations. Our results provide compelling support for the proposition that the nature and form of the interactions between drugs of different classes, synergy, antagonism, suppression and additivity, has to be determined empirically and cannot be inferred from what is known about the pharmacodynamics or mode of action of these drugs individually. Monte Carlo simulations of within-host treatment incorporating these pharmacodynamic results and clinically relevant refuge subpopulations of bacteria indicate that: (i) the form of drug-drug interactions can profoundly affect the rate at which infections are cleared, (ii) two-drug therapy can prevent treatment failure even when bacteria resistant to single drugs are present at the onset of therapy, and (iii) this evolutionary virtue of two-drug therapy is manifest even when the antibiotics suppress each other's activity.
In this study, we combine pharmacodynamic experiments using pathogenic strains of E. coli and S. aureus with mathematical and computer simulation models to explore the relative efficacies of two-drug antibiotic combinations in clearing infections and preventing the emergence of resistance. We develop a pharmacodynamic method that provides a convenient way to determine whether drug combinations will interact synergistically, antagonistically, additively or suppressively. We find that it is not possible to predict the nature and form of drug interactions based on what is known about the mode of action of individual drugs, thus illustrating the necessity of assessing the efficacy of drug combinations empirically. Our simulations of the within-host population and evolutionary dynamics of bacteria undergoing multi-drug treatment indicate that the form of the interaction between drugs observed experimentally can substantially affect the rate of clearance of the infection. On the other hand, the form of these interactions plays a minimal role in the emergence of resistance. Even when antibiotics are suppressive, two-drug therapy can prevent the ascent of bacteria resistant to single drugs that are present at the start of therapy and/or generated during the course of the infection.
The evolution of drug resistance among pathogenic bacteria has led public health workers to rely increasingly on multidrug therapy to treat infections. Here, we compare the efficacy of combination therapy (i.e., using two antibiotics simultaneously) and sequential therapy (i.e., switching two antibiotics) in minimizing the evolution of multidrug resistance. Using in vitro experiments, we show that the sequential use of two antibiotics against Pseudomonas aeruginosa can slow down the evolution of multiple-drug resistance when the two antibiotics are used in a specific order. A simple population dynamics model reveals that using an antibiotic associated with high costs of resistance first minimizes the chance of multidrug resistance evolution during sequential therapy under limited mutation supply rate. As well as presenting a novel approach to multidrug therapy, this work shows that costs of resistance not only influences the persistence of antibiotic-resistant bacteria but also plays an important role in the emergence of resistance.
Infections caused by multi-resistant Gram positive bacteria represent a major health burden in the community as well as in hospitalized patients. Staphylococcus aureus, Enterococcus faecalis and Enterococcus faecium are well-known pathogens of hospitalized patients, frequently linked with resistance against multiple antibiotics, compromising effective therapy. Streptococcus pneumoniae and Streptococcus pyogenes are important pathogens in the community and S. aureus has recently emerged as an important community-acquired pathogen.
Population genetic studies reveal that recombination prevails as a driving force of genetic diversity in E. faecium, E. faecalis, S. pneumoniae, and S. pyogenes and thus, these species are weakly clonal. Although recombination has a relatively modest role driving the genetic variation of the core genome of S. aureus, the horizontal acquistion of resistance and virulence genes plays a key role in the emergence of new clinically relevant clones in this species. In this review we discuss the population genetics of E. faecium, E. faecalis, S. pneumoniae, S. pyogenes, and S. aureus. Knowledge of the population structure of these pathogens is not only highly relevant for (molecular) epidemiological research but also for identifying the genetic variation that underlies changes in clinical behaviour, to improve our understanding of the pathogenic behaviour of particular clones and to identify novel targets for vaccines or immunotherapy.
Enterococcus; Streptococcus; Staphylococcus; MLST; evolution; Molecular epidemiology
The emergence of drug-resistant bacteria poses a serious threat to human health. In the case of several antibiotics, including those of the quinolone and rifamycin classes, bacteria rapidly acquire resistance through mutation of chromosomal genes during therapy. In this work, we show that preventing induction of the SOS response by interfering with the activity of the protease LexA renders pathogenic Escherichia coli unable to evolve resistance in vivo to ciprofloxacin or rifampicin, important quinolone and rifamycin antibiotics. We show in vitro that LexA cleavage is induced during RecBC-mediated repair of ciprofloxacin-mediated DNA damage and that this results in the derepression of the SOS-regulated polymerases Pol II, Pol IV and Pol V, which collaborate to induce resistance-conferring mutations. Our findings indicate that the inhibition of mutation could serve as a novel therapeutic strategy to combat the evolution of antibiotic resistance.
The evolution of bacterial resistance to antibiotics presents a serious public-health threat, but may be inevitable because mutation is stimulated by exposure to some antibiotics. Inhibition of mutational mechanisms should slow resistance.
The rapid proliferation of antibiotic-resistant pathogens has spurred the use of drug combinations to maintain clinical efficacy and combat the evolution of resistance. Drug pairs can interact synergistically or antagonistically, yielding inhibitory effects larger or smaller than expected from the drugs' individual potencies. Clinical strategies often favor synergistic interactions because they maximize the rate at which the infection is cleared from an individual, but it is unclear how such interactions affect the evolution of multi-drug resistance. We used a mathematical model of in vivo infection dynamics to determine the optimal treatment strategy for preventing the evolution of multi-drug resistance. We found that synergy has two conflicting effects: it clears the infection faster and thereby decreases the time during which resistant mutants can arise, but increases the selective advantage of these mutants over wild-type cells. When competition for resources is weak, the former effect is dominant and greater synergy more effectively prevents multi-drug resistance. However, under conditions of strong resource competition, a tradeoff emerges in which greater synergy increases the rate of infection clearance, but also increases the risk of multi-drug resistance. This tradeoff breaks down at a critical level of drug interaction, above which greater synergy has no effect on infection clearance, but still increases the risk of multi-drug resistance. These results suggest that the optimal strategy for suppressing multi-drug resistance is not always to maximize synergy, and that in some cases drug antagonism, despite its weaker efficacy, may better suppress the evolution of multi-drug resistance.
The use of antibiotics against bacterial infections has led to the emergence of multi-drug resistant pathogens such as tuberculosis and MRSA. In order to control resistance, clinicians have increasingly turned to multi-antibiotic therapies. The common wisdom is to use combinations of drugs that act synergistically to kill the infection, but the impact of drug synergy on the evolution of resistance is unclear. Using mathematical simulations of an in vivo infection model, we asked what level of drug synergy would minimize the risk of multi-drug resistance while preserving the efficacy of treatment. We found that synergy may increase or decrease the risk of multi-drug resistance in a given treatment, depending on infection properties such as mutation rate and the availability of resources. Surprisingly, under conditions of strong competition for resources within the host, we found that maximal synergy—currently favored in clinical settings—can actually increase the risk of multi-drug resistance. Our results identify conditions under which drug synergy exacerbates the problem of multi-drug resistance, and offer guidelines for the selection of drug pairs that suppress it.
Streptococcus pneumoniae is a major pathogen in the community and presents high rates of resistance to the available antibiotics. To prevent antibiotic treatment failure caused by highly resistant bacteria, increasing the prescribed antibiotic dose has recently been suggested. The aim of the present study was to assess the influence of β-lactam prescribed doses on the emergence of resistance and selection in the community. A mathematical model was constructed by combining S. pneumoniae pharmacodynamic and population-dynamic approaches. The received-dose heterogeneity in the population was specifically modeled. Simulations over a 50-year period were run to test the effects of dose distribution and antibiotic exposure frequency changes on community resistance patterns, as well as the accuracy of the defined daily dose as a predictor of resistance. When the frequency of antibiotic exposure per year was kept constant, dose levels had a strong impact on the levels of resistance after a 50-year simulation. The lowest doses resulted in a high prevalence of nonsusceptible strains (≥70%) with MICs that were still low (1 mg/liter), whereas high doses resulted in a lower prevalence of nonsusceptible strains (<40%) and higher MICs (2 mg/liter). Furthermore, by keeping the volume of antibiotics constant in the population, different patterns of use (low antibiotic dose and high antibiotic exposure frequency versus high dose and low frequency) could lead to markedly different rates of resistance distribution and prevalence (from 10 to 100%). Our results suggest that pneumococcal resistance patterns in the community are strongly related to the individual β-lactam doses received: limiting β-lactam use while increasing the doses could help reduce the prevalence of resistance, although it should select for higher levels of resistance. Surveillance networks are therefore encouraged to collect both daily antibiotic exposure frequencies and individual prescribed doses.
The high mortality impact of infectious diseases will increase due to accelerated evolution of antibiotic resistance in important human pathogens. Development of antibiotic resistance is a evolutionary process inducing the erosion of the effectiveness of our arsenal of antibiotics. Resistance is not necessarily limited to a single class of antibacterial agents but may affect many unrelated compounds; this is termed ‘multidrug resistance’ (MDR). The major mechanism of MDR is the active expulsion of drugs by bacterial pumps; the treatment of Gram negative bacterial infections is compromised due to resistance mechanisms including the expression of efflux pumps that actively expel various usual antibiotics (ß-lactams, quinolones, …).
Enterobacter aerogenes has emerged among Enterobacteriaceae associated hospital infections during the last twenty years due to its faculty of adaptation to antibiotic stresses. Clinical isolates of E. aerogenes belonging to two strain collections isolated in 1995 and 2003 respectively, were screened to assess the involvement of efflux pumps in antibiotic resistance. Drug susceptibility assays were performed on all bacterial isolates and an efflux pump inhibitor (PAßN) previously characterized allowed to decipher the role of efflux in the resistance. Accumulation of labelled chloramphenicol was monitored in the presence of an energy poison to determine the involvement of active efflux on the antibiotic intracellular concentrations. The presence of the PAßN-susceptible efflux system was also identified in resistant E. aerogenes strains.
For the first time a noticeable increase in clinical isolates containing an efflux mechanism susceptible to pump inhibitor is report within an 8 year period. After the emergence of extended spectrum ß-lactamases in E. aerogenes and the recent characterisation of porin mutations in clinical isolates, this study describing an increase in inhibitor-susceptible efflux throws light on a new step in the evolution of mechanism in E. aerogenes.
Medical and pharmacological communities have long searched for antimicrobial drugs that increase their effect when used in combination, an interaction known as synergism. These drug combinations, however, impose selective pressures in favour of multi-drug resistance and as a result, the benefit of synergy may be lost after only a few bacterial generations. Furthermore, there is experimental evidence that antibiotic treatment can disrupt colonization resistance by shifting the balance between enteropathogenic and commensal bacteria in favour of the pathogens, with the potential to increase the risk of infections. So, we ask, what is the best way of using synergistic drugs? We pose an evolutionary model of commensal and pathogenic bacteria competing in a continuous culture device for a single limiting carbon source under the effect of two bacteriostatic and synergistic antibiotics. This model allows us to evaluate the efficacy of different drug deployment strategies and, using ideas from optimal control theory, to understand whether there are circumstances in which other types of therapy might be favoured over those based on fixed-dose multi-drug combinations. Our main result can be stated thus: the optimal deployment of synergistic antibiotics to remove a pathogen in the presence of commensal bacteria in our model system occurs not in combination, but by deploying them sequentially.
antimicrobial resistance; drug interactions; control theory
Antibiotic resistance mechanisms reported in Gram-negative bacteria are producing a worldwide health problem. The continuous dissemination of «multi-drug resistant» (MDR) bacteria drastically reduces the efficacy of our antibiotic “arsenal” and consequently increases the frequency of therapeutic failure. In MDR bacteria, the over-expression of efflux pumps that expel structurally-unrelated drugs contributes to the reduced susceptibility by decreasing the intracellular concentration of antibiotics. During the last decade, several clinical data indicate an increasing involvement of efflux pumps in the emergence and dissemination of resistant Gram-negative bacteria. It is necessary to clearly define the molecular, functional and genetic bases of the efflux pump in order to understand the translocation of antibiotic molecules through the efflux transporter. The recent investigation on the efflux pump AcrB at its structural and physiological level, including the identification of drug affinity sites and kinetic parameters for various antibiotics, may open the way to rationally develop an improved new generation of antibacterial agents as well as efflux inhibitors in order to efficiently combat efflux-based resistance mechanisms.
Antibiotic resistance; RND family drug transporters; bacterial efflux pump; MDR bacteria; outer membrane permeability; selectivity; structure-function relationship
Bacterial adaptation to external stresses and toxic compounds is a key step in the emergence of multidrug-resistant strains that are a serious threat to human health. Although some of the proteins and regulators involved in antibiotic resistance mechanisms have been described, no information is available to date concerning the early bacterial response to external stresses. Here we report that the expression of ompX, encoding an outer membrane protein, is increased during early exposure to drugs or environmental stresses. At the same time, the level of ompF porin expression is noticeably affected. Because of the role of these proteins in membrane permeability, these data suggest that OmpF and OmpX are involved in the control of the penetration of antibiotics such as β-lactams and fluoroquinolones through the enterobacterial outer membrane. Consequently, the early control of ompX and ompF induced by external stresses may represent a preliminary response to antibiotics, thus triggering the initial bacterial line of defense against antibiotherapy.
The widespread use of antibiotics is selecting for a variety of resistance mechanisms that seriously challenge our ability to treat bacterial infections. Resistant bacteria can be selected at the high concentrations of antibiotics used therapeutically, but what role the much lower antibiotic concentrations present in many environments plays in selection remains largely unclear. Here we show using highly sensitive competition experiments that selection of resistant bacteria occurs at extremely low antibiotic concentrations. Thus, for three clinically important antibiotics, drug concentrations up to several hundred-fold below the minimal inhibitory concentration of susceptible bacteria could enrich for resistant bacteria, even when present at a very low initial fraction. We also show that de novo mutants can be selected at sub-MIC concentrations of antibiotics, and we provide a mathematical model predicting how rapidly such mutants would take over in a susceptible population. These results add another dimension to the evolution of resistance and suggest that the low antibiotic concentrations found in many natural environments are important for enrichment and maintenance of resistance in bacterial populations.
Antibiotic resistance has emerged as a very significant health care problem due to the extensive use and misuse of antibiotics in human and veterinary medicine and in agriculture. It remains unclear where most of the resistant bacteria have been selected, and in particular if the low antibiotic concentrations that are present in natural environments or in human/animal body compartments during therapeutic or growth promotion use, are important for the selection and enrichment of resistant mutants. The presented data shows that for several clinically used antibiotics extremely low concentrations, similar to the concentrations found in natural environments, can select for resistant bacteria. These results suggest that antibiotic release into the environment might be a significant contributor to the emergence and maintenance of resistance and emphasize the importance of introducing measures to reduce antibiotic pollution.
It is known that bacteria showing a multi-drug resistance phenotype use several mechanisms to overcome the action of antibiotics. As a result, this phenotype can be a result of several mechanisms or a combination of thereof. The main mechanisms of antibiotic resistance are: mutations in target genes (such as DNA gyrase and topoisomerase IV); over-expression of efflux pumps; changes in the cell envelope; down regulation of membrane porins, and modified lipopolysaccharide component of the outer cell membrane (in the case of Gram-negative bacteria). In addition, adaptation to the environment, such as quorum sensing and biofilm formation can also contribute to bacterial persistence. Due to the rapid emergence and spread of bacterial isolates showing resistance to several classes of antibiotics, methods that can rapidly and efficiently identify isolates whose resistance is due to active efflux have been developed. However, there is still a need for faster and more accurate methodologies. Conventional methods that evaluate bacterial efflux pump activity in liquid systems are available. However, these methods usually use common efflux pump substrates, such as ethidium bromide or radioactive antibiotics and therefore, require specialized instrumentation, which is not available in all laboratories.
In this review, we will report the results obtained with the Ethidium Bromide-agar Cartwheel method. This is an easy, instrument-free, agar based method that has been modified to afford the simultaneous evaluation of as many as twelve bacterial strains. Due to its simplicity it can be applied to large collections of bacteria to rapidly screen for multi-drug resistant isolates that show an over-expression of their efflux systems. The principle of the method is simple and relies on the ability of the bacteria to expel a fluorescent molecule that is substrate for most efflux pumps, ethidium bromide. In this approach, the higher the concentration of ethidium bromide required to produce fluorescence of the bacterial mass, the greater the efflux capacity of the bacterial cells. We have tested and applied this method to a large number of Gram-positive and Gram-negative bacteria to detect efflux activity among these multi-drug resistant isolates. The presumptive efflux activity detected by the Ethidium Bromide-agar Cartwheel method was subsequently confirmed by the determination of the minimum inhibitory concentration for several antibiotics in the presence and absence of known efflux pump inhibitors.
Clinical isolates; Efflux activity; Efflux pumps; Ethidium bromide; Multi-drug resistance; Screening method.
Although optimization of fluoroquinolone dosage increases the efficacy of this class of drugs against bacterial infections, its impact on the emergence of resistance in commensal bacteria is unknown.
Six different dosing regimens of oral ciprofloxacin for 14 days were randomly assigned to 48 healthy volunteers. Individual pharmacokinetic and pharmacodynamic parameters combining antibiotic exposure in plasma, saliva and stool and MIC and MPC of ciprofloxacin against viridans group streptococci in the pharyngeal flora and Escherichia coli in the fecal flora were estimated. Their links with the emergence of resistance to nalidixic acid or ciprofloxacin in the fecal flora and to levofloxacin in the pharyngeal flora, at day 7, 14 or 42, were investigated.
Resistance emerged in 25% and 33% of the subjects in the fecal flora and the pharyngeal flora, respectively, mainly when local concentrations of ciprofloxacin were below the MIC. No variable integrating pharmacokinetic data and pharmacodynamic parameters were found to differ significantly between the subjects in whom resistance emerged or not. Probabilities of emergence of resistance were not significantly different whatever the antibiotic exposure.
Selection of resistant commensals during ciprofloxacin therapy is a frequent ecological side effect which is not preventable by optimizing dosing regimen.
Adult; Anti-Bacterial Agents; administration & dosage; pharmacokinetics; pharmacology; Ciprofloxacin; administration & dosage; pharmacokinetics; pharmacology; Drug Resistance, Bacterial; Escherichia coli; drug effects; Feces; microbiology; Female; Humans; Male; Microbial Sensitivity Tests; Pharynx; microbiology; Saliva; metabolism; Viridans Streptococci; drug effects; Young Adult
The persistence of antibiotic resistance depends on the fitness effects of resistance elements in the absence of antibiotics. Recent work shows that the fitness effect of a given resistance mutation is influenced by other resistance mutations on the same genome. However, resistant bacteria acquire additional beneficial mutations during evolution in the absence of antibiotics that do not alter resistance directly but may modify the fitness effects of new resistance mutations.
We experimentally evolved rifampicin-resistant and sensitive Escherichia coli in a drug-free environment, before measuring the effects of new resistance elements on fitness in antibiotic-free conditions. Streptomycin-resistance mutations had small fitness effects in rifampicin-resistant genotypes that had adapted to antibiotic-free growth medium, compared to the same genotypes without adaptation. We observed a similar effect when resistance was encoded by a different mechanism and carried on a plasmid. Antibiotic-sensitive bacteria that adapted to the same conditions showed the same pattern for some resistance elements but not others.
Epistatic variation of costs of resistance can result from evolution in the absence of antibiotics, as well as the presence of other resistance mutations.
Antibiotic resistance; Epistasis; Experimental evolution; Escherichia coli
Infection due to multidrug resistance pathogens is difficult to manage due to bacterial virulence factors and because of a relatively limited choice of antimicrobial agents. Thus, it is imperative to discover fresh antimicrobials or new practices that are effective for the treatment of infectious diseases caused by drug-resistant microorganisms. The objective of this experiment is to investigate for synergistic outcomes when crude methanolic extract of the stem bark of Afzelia africana and antibiotics were combined against a panel of antibiotic resistant bacterial strains that have been implicated in infections. Standard microbiological protocols were used to determine the minimum inhibitory concentrations (MICs) of the extract and antibiotics, as well as to investigate the effect of combinations of the methanolic extract of A. africana stem bark and selected antibiotics using the time-kill assay method. The extract of Afzelia africana exhibited antibacterial activities against both Gram-negative and Gram-positive bacteria made up of environmental and standard strains at a screening concentration of 5 mg/mL. The MICs of the crude extracts and the antibiotics varied between 1 μg/mL and 5.0 mg/mL. Overall, synergistic response constituted about 63.79% of all manner of combinations of extract and antibiotics against all test organisms; antagonism was not detected among the 176 tests carried out. The extract from A. africana stem bark showed potentials of synergy in combination with antibiotics against strains of pathogenic bacteria. The detection of synergy between the extract and antibiotics demonstrates the potential of this plant as a source of antibiotic resistance modulating compounds.
Afzelia Africana; synergy; antibiotics; extract; drug-resistant; microorganisms
Small colony variants (SCVs) are slow-growing bacteria, which often show increased resistance to antibiotics and cause latent or recurrent infections. It is therefore important to understand the mechanisms at the basis of this phenotypic switch.
One SCV (termed PAO-SCV) was isolated, showing high resistance to gentamicin and to the cephalosporine cefotaxime. PAO-SCV was prone to reversion as evidenced by emergence of large colonies with a frequency of 10−5 on media without antibiotics while it was stably maintained in presence of gentamicin. PAO-SCV showed a delayed growth, defective motility, and strongly reduced levels of the quorum sensing Pseudomonas quinolone signal (PQS). Whole genome expression analysis further suggested a multi-layered antibiotic resistance mechanism, including simultaneous over-expression of two drug efflux pumps (MexAB-OprM, MexXY-OprM), the LPS modification operon arnBCADTEF, and the PhoP-PhoQ two-component system. Conversely, the genes for the synthesis of PQS were strongly down-regulated in PAO-SCV. Finally, genomic analysis revealed the presence of mutations in phoP and phoQ genes as well as in the mexZ gene encoding a repressor of the mexXY and mexAB-oprM genes. Only one mutation occurred only in REV, at nucleotide 1020 of the tufA gene, a paralog of tufB, both encoding the elongation factor Tu, causing a change of the rarely used aspartic acid codon GAU to the more common GAC, possibly causing an increase of tufA mRNA translation. High expression of phoP and phoQ was confirmed for the SCV variant while the revertant showed expression levels reduced to wild-type levels.
By combining data coming from phenotypic, gene expression and proteome analysis, we could demonstrate that resistance to aminoglycosides in one SCV mutant is multifactorial including overexpression of efflux mechanisms, LPS modification and is accompanied by a drastic down-regulation of the Pseudomonas quinolone signal quorum sensing system.