The Impact of Different Antibiotic Regimens on the Emergence of Antimicrobial-Resistant Bacteria

Backgroud

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.

Methods/Principal Findings

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.

Conclusions/Significance

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.     

Selection of resistant bacteria at very low antibiotic concentrations

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 and persistence—Implications for human health and treatment perspectives

Antimicrobial resistance (AMR) and persistence are associated with an elevated risk of treatment failure and relapsing infections. They are thus important drivers of increased morbidity and mortality rates resulting in growing healthcare costs. Antibiotic resistance is readily identifiable with standard microbiological assays, and the threat imposed by antibiotic resistance has been well recognized. Measures aiming to reduce resistance development and spreading of resistant bacteria are being enforced. However, the phenomenon of bacteria surviving antibiotic exposure despite being fully susceptible, so‐called antibiotic persistence, is still largely underestimated. In contrast to antibiotic resistance, antibiotic persistence is difficult to measure and therefore often missed, potentially leading to treatment failures. In this review, we focus on bacterial mechanisms allowing evasion of antibiotic killing and discuss their implications on human health. We describe the relationship between antibiotic persistence and bacterial heterogeneity and discuss recent studies that link bacterial persistence and tolerance with the evolution of antibiotic resistance. Finally, we review persister detection methods, novel strategies aiming at eradicating bacterial persisters and the latest advances in the development of new antibiotics.     

Resistance acquisition via the bacterial SOS response: the inducive role of antibiotics

After the euphoria of the antibiotic discovery and their tremendous action on bacterial infections outcomes, arrives a period of fear with the continuous emergence of bacteria that are resistant to almost all antibiotic treatments. It is becoming essential to better understand antibiotic resistance mechanisms to find new approaches to prevent the worldwide problem of multiresistance. The role of antibiotics on the direct induction of resistance acquisition is known. Recent studies have shown that some antibiotics, by inducing the bacterial SOS response, global repair response after DNA damages, are involved on a broader level in the induction, acquisition and dissemination of resistances in bacteria. We discuss here the role of antibiotics in resistance acquisition via the SOS response through several examples and the interest of identifying the SOS response regulators as the future targets of new families of antimicrobial molecules.     

Neuraminidase inhibitor resistance in influenza: assessing the danger of its generation and spread

Neuraminidase Inhibitors (NI) are currently the most effective drugs against influenza. Recent cases of NI resistance are a cause for concern. To assess the danger of NI resistance, a number of studies have reported the fraction of treated patients from which resistant strains could be isolated. Unfortunately, those results strongly depend on the details of the experimental protocol. Additionally, knowing the fraction of patients harboring resistance is not too useful by itself. Instead, we want to know how likely it is that an infected patient can generate a resistant infection in a secondary host, and how likely it is that the resistant strain subsequently spreads. While estimates for these parameters can often be obtained from epidemiological data, such data is lacking for NI resistance in influenza. Here, we use an approach that does not rely on epidemiological data. Instead, we combine data from influenza infections of human volunteers with a mathematical framework that allows estimation of the parameters that govern the initial generation and subsequent spread of resistance. We show how these parameters are influenced by changes in drug efficacy, timing of treatment, fitness of the resistant strain, and details of virus and immune system dynamics. Our study provides estimates for parameters that can be directly used in mathematical and computational models to study how NI usage might lead to the emergence and spread of resistance in the population. We find that the initial generation of resistant cases is most likely lower than the fraction of resistant cases reported. However, we also show that the results depend strongly on the details of the within-host dynamics of influenza infections, and most importantly, the role the immune system plays. Better knowledge of the quantitative dynamics of the immune response during influenza infections will be crucial to further improve the results.     

Targeting bioenergetics is key to counteracting the drug-tolerant state of biofilm-grown bacteria

Embedded in an extracellular matrix, biofilm-residing bacteria are protected from diverse physicochemical insults. In accordance, in the human host the general recalcitrance of biofilm-grown bacteria hinders successful eradication of chronic, biofilm-associated infections. In this study, we demonstrate that upon addition of promethazine, an FDA approved drug, antibiotic tolerance of in vitro biofilm-grown bacteria can be abolished. We show that following the addition of promethazine, diverse antibiotics are capable of efficiently killing biofilm-residing cells at minimal inhibitory concentrations. Synergistic effects could also be observed in a murine in vivo model system. PMZ was shown to increase membrane potential and interfere with bacterial respiration. Of note, antibiotic killing activity was elevated when PMZ was added to cells grown under environmental conditions that induce low intracellular proton levels. Our results imply that biofilm-grown bacteria avoid antibiotic killing and become tolerant by counteracting intracellular alkalization through the adaptation of metabolic and transport functions. Abrogation of antibiotic tolerance by interfering with the cell’s bioenergetics promises to pave the way for successful eradication of biofilm-associated infections. Repurposing promethazine as a biofilm-sensitizing drug has the potential to accelerate the introduction of new treatments for recalcitrant, biofilm-associated infections into the clinic.     

抗菌肽的抗生物膜机理研究进展

生物膜,也称为生物被膜,是指附着于有生命或无生命物体表面被细菌胞外大分子包裹的有组织的细菌群体。与浮游菌相比,生物膜内的细菌对抗生素的耐受性提高了10–1000倍,是造成目前细菌耐药的主要原因之一。作为一种新型抗菌制剂,抗菌肽的使用为生物膜感染的治疗提供了一种新的思路和手段。抗菌肽在抑制生物膜形成、杀灭生物膜内细菌以及消除成熟生物膜的过程中发挥了独特的优势。文中分析了近30年的数据,从细菌生物膜的结构入手,对抗菌肽可能的抗生物膜机理进行了综述,以期为抗菌肽临床治疗生物膜感染提供一定参考。     

细菌药物耐受

细菌药物耐受(Drug tolerance)是指在没有发生耐药突变的情况下细菌耐受抗生素杀菌的能力,表现为细菌群体难以或不能被杀菌型药物清除。细菌药物耐受的调控机制包括群体异质性和压力应答两种途径。药物耐受性的本质是细菌通过调控或遗传突变的方式改变生理代谢状态,从而抵制药物引起的细胞死亡途径。比如,处于缓慢生长或生长停滞生理状态的细菌往往能够抵抗药物的杀菌作用。临床研究发现细菌药物耐受是导致持续性感染疾病迁延难愈、复发率高的病原学机制之一。同时,研究证明耐受性的形成是细菌耐药性(Drug resistance)产生的进化途径之一。因此,揭示细菌药物耐受的机制将有助于人们深入了解抗生素的杀菌机理,以及细菌耐药性形成的适应性进化机制,并为新型杀菌药物以及药物增效剂靶标的发现和抗生素合理使用策略的开发奠定理论基础。     

Surface Acoustic Waves Enhance Neutrophil Killing of Bacteria

Biofilms are structured communities of bacteria that play a major role in the pathogenicity of bacteria and are the leading cause of antibiotic resistant bacterial infections on indwelling catheters and medical prosthetic devices. Failure to resolve these biofilm infections may necessitate the surgical removal of the prosthetic device which can be debilitating and costly. Recent studies have shown that application of surface acoustic waves to catheter surfaces can reduce the incidence of infections by a mechanism that has not yet been clarified. We report here the effects of surface acoustic waves (SAW) on the capacity of human neutrophils to eradicate S. epidermidis bacteria in a planktonic state and within biofilms. Utilizing a novel fibrin gel system that mimics a tissue-like environment, we show that SAW, at an intensity of 0.3 mW/cm², significantly enhances human neutrophil killing of S. epidermidis in a planktonic state and within biofilms by enhancing human neutrophil chemotaxis in response to chemoattractants. In addition, we show that the integrin CD18 plays a significant role in the killing enhancement observed in applying SAW. We propose from out data that this integrin may serve as mechanoreceptor for surface acoustic waves enhancing neutrophil chemotaxis and killing of bacteria.     

The Pharmaco –, Population and Evolutionary Dynamics of Multi-drug Therapy: Experiments with S. aureus and E. coli and Computer Simulations

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.     

Multicellular organization in bacteria as a target for drug therapy

Antibiotic treatments are now reaching the limit of their efficiency, especially in hospitals where certain bacteria are resistant to all available drugs. The development of new drugs against which resistance would be slower to evolve is an important challenge. Recent advances have shown that a potential strategy is to target global properties of infections instead of harming each individual bacterium. Consider an analogy with multicellular organisms. In order to kill an animal two strategies are possible. One can kill each of its cells individually. This is what antibiotics do to get rid of bacterial infections. An alternate way, for instance, is to disorganize the hormonal system of animal's body, leading eventually to its death. This second strategy could also be employed against infections, in place of antibiotics. Bacteria are indeed often involved into coordinated activities within a group, and certain drugs are able to disorganize these activities by blocking bacterial communication. In other words, these drugs are able to target infections as a whole, rather than individuals within infections. The present paper aims at analysing the consequence of this peculiarity on the evolution of bacterial resistance. We use a mathematical model, based on branching process, to calculate the fixation probability of a mutant resistant to this type of drug, and finally to predict the speed of resistance evolution. We show that this evolution is several orders of magnitude slower than in the case of antibiotic resistance. The explanation is as follows. By targeting treatments against adaptive properties of groups instead of individuals, we shift one level up the relevant unit of organization generating resistance. Instead of facing billions of bacteria with a very rapid evolutionary rate, these alternate treatments face a reduced number of larger organisms with lower evolutionary potential. In conclusion, this result leads us to emphasize the strong potential of anti‐bacterial treatments aiming at disorganizing social traits of microbes rather than at killing every individual.     

Targeted-antibacterial-plasmids (TAPs) combining conjugation and CRISPR/Cas systems achieve strain-specific antibacterial activity

The global emergence of drug-resistant bacteria leads to the loss of efficacy of our antibiotics arsenal and severely limits the success of currently available treatments. Here, we developed an innovative strategy based on targeted-antibacterial-plasmids (TAPs) that use bacterial conjugation to deliver CRISPR/Cas systems exerting a strain-specific antibacterial activity. TAPs are highly versatile as they can be directed against any specific genomic or plasmid DNA using the custom algorithm (CSTB) that identifies appropriate targeting spacer sequences. We demonstrate the ability of TAPs to induce strain-selective killing by introducing lethal double strand breaks (DSBs) into the targeted genomes. TAPs directed against a plasmid-born carbapenem resistance gene efficiently resensitise the strain to the drug. This work represents an essential step toward the development of an alternative to antibiotic treatments, which could be used for in situ microbiota modification to eradicate targeted resistant and/or pathogenic bacteria without affecting other non-targeted bacterial species.     

‘To be,or not to be’—The dilemma of ‘silent’ antimicrobial resistance genes in bacteria

Antimicrobial resistance is a serious threat to public health that dramatically undermines our ability to treat bacterial infections. Microorganisms exhibit resistance to different drug classes by acquiring resistance determinants through multiple mechanisms including horizontal gene transfer. The presence of drug resistance genotypes is mostly associated with corresponding phenotypic resistance against the particular antibiotic. However, bacterial communities harbouring silent antimicrobial resistance genes—genes whose presence is not associated with a corresponding resistant phenotype do exist. Under suitable conditions, the expression pattern of such genes often revert and regain resistance and could potentially lead to therapeutic failure. We often miss the presence of silent genes, since the current experimental paradigms are focused on resistant strains. Therefore, the knowledge on the prevalence, importance and mechanism of silent antibiotic resistance genes in bacterial pathogens are very limited. Silent genes, therefore, provide an additional level of complexity in the war against drug-resistant bacteria, reminding us that not only phenotypically resistant strains but also susceptible strains should be carefully investigated. In this review, we discuss the presence of silent antimicrobial resistance genes in bacteria, their relevance and their importance in public health.     

The activity of a small lytic peptide PTP-7 on <Emphasis Type="Italic">Staphylococcus aureus</Emphasis> biofilms

One of the most important features of bacterial biofilms is their resistance to antibiotics and to the host immune system. In this study, we have found that a small lytic peptide, PTP-7, is very potent to Gram-positive bacteria and is able to kill antibiotic sensitive and resistant Staphylococcus aureus indiscriminately. Further studies have revealed that despite being a cationic peptide, the antibacterial activity of PTP-7 was not affected by the negatively charged extracellular polymeric substance (EPS) of biofilms. PTP-7 could diffuse into the deep layer of S. aureus biofilms to kill bacteria inside biofilms efficiently and effectively. Neither the high concentrations of metal ions nor the acidic pH in biofilms affected the activity of peptide PTP-7. It seems that the unique sequence/structure together with the resistant bacteria killing ability of peptide PTP-7 confers its anti-biofilm activity. This study sheds new light on the treatment of bacterial biofilms, especially various biofilm related infections.     

Bacterial cheating drives the population dynamics of cooperative antibiotic resistance plasmids

Inactivation of β ‐lactam antibiotics by resistant bacteria is a ‘cooperative’ behavior that may allow sensitive bacteria to survive antibiotic treatment. However, the factors that determine the fraction of resistant cells in the bacterial population remain unclear, indicating a fundamental gap in our understanding of how antibiotic resistance evolves. Here, we experimentally track the spread of a plasmid that encodes a β ‐lactamase enzyme through the bacterial population. We find that independent of the initial fraction of resistant cells, the population settles to an equilibrium fraction proportional to the antibiotic concentration divided by the cell density. A simple model explains this behavior, successfully predicting a data collapse over two orders of magnitude in antibiotic concentration. This model also successfully predicts that adding a commonly used β ‐lactamase inhibitor will lead to the spread of resistance, highlighting the need to incorporate social dynamics into the study of antibiotic resistance.     

A New Approach for the Discovery of Antibiotics by Targeting Non-Multiplying Bacteria: A Novel Topical Antibiotic for Staphylococcal Infections

In a clinical infection, multiplying and non-multiplying bacteria co-exist. Antibiotics kill multiplying bacteria, but they are very inefficient at killing non-multipliers which leads to slow or partial death of the total target population of microbes in an infected tissue. This prolongs the duration of therapy, increases the emergence of resistance and so contributes to the short life span of antibiotics after they reach the market. Targeting non-multiplying bacteria from the onset of an antibiotic development program is a new concept. This paper describes the proof of principle for this concept, which has resulted in the development of the first antibiotic using this approach. The antibiotic, called HT61, is a small quinolone-derived compound with a molecular mass of about 400 Daltons, and is active against non-multiplying bacteria, including methicillin sensitive and resistant, as well as Panton-Valentine leukocidin-carrying Staphylococcus aureus. It also kills mupirocin resistant MRSA. The mechanism of action of the drug is depolarisation of the cell membrane and destruction of the cell wall. The speed of kill is within two hours. In comparison to the conventional antibiotics, HT61 kills non-multiplying cells more effectively, 6 logs versus less than one log for major marketed antibiotics. HT61 kills methicillin sensitive and resistant S. aureus in the murine skin bacterial colonization and infection models. No resistant phenotype was produced during 50 serial cultures over a one year period. The antibiotic caused no adverse affects after application to the skin of minipigs. Targeting non-multiplying bacteria using this method should be able to yield many new classes of antibiotic. These antibiotics may be able to reduce the rate of emergence of resistance, shorten the duration of therapy, and reduce relapse rates.     

In-silico investigation of a novel inhibitors against the antibiotic-resistant Neisseria gonorrhoeae bacteria

Antibiotics are drugs that are used to treat or prevent bacterial infections. They work by either killing or stopping bacteria from spreading. Nevertheless, it appeared in the last decade, Antibiotic-resistant bacteria are bacteria resistant to antibiotics and cannot be controlled or killed by them. In the presence of an antibiotic, they can live and even reproduce. The Neisseria gonorrhoeae bacteria is appearing to be a multidrug-resistant pathogen. Many factors contribute to antibiotic resistance, including unfettered access to antimicrobials, incorrect drug selection, misuse, and low-quality antibiotics. Here, we investigated in-silico docking screening and analysis for ten natural marine fungus extracted compounds. The resulted data were examined for the best binding affinity, toxicity, and chemical interactions. The most superior compound was elipyrone A with six hydrogen bonds, ?8.5 of binding affinity, and preferable results in the SWISS-ADME examination. It is well known that “Declining corporate investment and a lack of innovation in the development of new antibiotics are weakening efforts to battle drug-resistant illnesses,” according to the World Health Organization (WHO). So, we extended our effort to predict a new natural compound to overcome the resistance of this bacteria.     

Meta分析在细菌耐药性研究中的应用与展望

随着抗生素的大量不规范使用,细菌耐药性不断增强,导致耐药及多重耐药细菌的出现,严重威胁着人类健康。运用统计学方法对耐药性相关研究进行汇总与多元分析,有助于更好地了解全球细菌耐药性的流行与分布,明晰细菌耐药性形成规律与机制的共性问题。Meta分析是一种将多个同类型研究进行综合分析的统计学方法,已广泛应用于细菌耐药性的研究。本文简要描述了Meta分析的起源及基本流程,并采用文献计量的方法对2000-2020年关于Meta分析在细菌耐药性研究中的应用进行系统综述;进一步总结并阐述了Meta分析在细菌耐药性领域应用的成功案例和结论,而且对Meta分析方法在细菌耐药性领域中的进一步研究进行了展望,以期推动该方法在细菌耐药性研究中的应用,为耐药性问题的系统阐释和有效控制提供可靠的工具。     

Evaluating the efficacy of antimicrobial cycling programmes and patient isolation on dual resistance in hospitals

Antibiotic-resistant bacteria cause a number of infections in hospitals and are considered a threat to public health. A strategy suggested to curb the development of resistant hospital-acquired infections is antimicrobial cycling, in which antibiotic classes are alternated over time. This can be compared with a mixing programme in which, when given two drugs, half of the physicians prescribe one drug over the other. A mathematical model of antimicrobial cycling in a hospital population setting is developed to evaluate the efficacy of a cycling programme with an emphasis on reducing the emergence and significance of dual resistance. The model also considers the effects of physician compliance and isolating patients harbouring dual-resistant bacteria. Simulation results show that the optimal antimicrobial drug usage programme in hospital populations depends upon the type of resistance being targeted for treatment; a cycling programme is more effective against dual resistance compared with mixing. Patient isolation and high compliance to a cycling programme is also shown to dramatically decrease dual resistance in hospitalized populations. Ultimately, the exclusive use of antimicrobials in fighting nosocomial infection does not solve the problem but just slows down what appears to be a losing battle against drug resistance. We hope that this paper serves to instigate discussion on the many dimensions of the complex problem of drug resistance in hospital settings.     

Involvement of the efflux pumps in chloramphenicol selected strains of Burkholderia thailandensis: proteomic and mechanistic evidence

Burkholderia is a bacterial genus comprising several pathogenic species, including two species highly pathogenic for humans, B. pseudomallei and B. mallei. B. thailandensis is a weakly pathogenic species closely related to both B. pseudomallei and B. mallei. It is used as a study model. These bacteria are able to exhibit multiple resistance mechanisms towards various families of antibiotics. By sequentially plating B. thailandensis wild type strains on chloramphenicol we obtained several resistant variants. This chloramphenicol-induced resistance was associated with resistance against structurally unrelated antibiotics including quinolones and tetracyclines. We functionally and proteomically demonstrate that this multidrug resistance phenotype, identified in chloramphenicol-resistant variants, is associated with the overexpression of two different efflux pumps. These efflux pumps are able to expel antibiotics from several families, including chloramphenicol, quinolones, tetracyclines, trimethoprim and some β-lactams, and present a partial susceptibility to efflux pump inhibitors. It is thus possible that Burkholderia species can develop such adaptive resistance mechanisms in response to antibiotic pressure resulting in emergence of multidrug resistant strains. Antibiotics known to easily induce overexpression of these efflux pumps should be used with discernment in the treatment of Burkholderia infections.