Chemical Communication of Antibiotic Resistance by a Highly Resistant Subpopulation of Bacterial Cells

The overall antibiotic resistance of a bacterial population results from the combination of a wide range of susceptibilities displayed by subsets of bacterial cells. Bacterial heteroresistance to antibiotics has been documented for several opportunistic Gram-negative bacteria, but the mechanism of heteroresistance is unclear. We use Burkholderia cenocepacia as a model opportunistic bacterium to investigate the implications of heterogeneity in the response to the antimicrobial peptide polymyxin B (PmB) and also other bactericidal antibiotics. Here, we report that B. cenocepacia is heteroresistant to PmB. Population analysis profiling also identified B. cenocepacia subpopulations arising from a seemingly homogenous culture that are resistant to higher levels of polymyxin B than the rest of the cells in the culture, and can protect the more sensitive cells from killing, as well as sensitive bacteria from other species, such as Pseudomonas aeruginosa and Escherichia coli. Communication of resistance depended on upregulation of putrescine synthesis and YceI, a widely conserved low-molecular weight secreted protein. Deletion of genes for the synthesis of putrescine and YceI abrogate protection, while pharmacologic inhibition of putrescine synthesis reduced resistance to polymyxin B. Polyamines and YceI were also required for heteroresistance of B. cenocepacia to various bactericidal antibiotics. We propose that putrescine and YceI resemble "danger" infochemicals whose increased production by a bacterial subpopulation, becoming more resistant to bactericidal antibiotics, communicates higher level of resistance to more sensitive members of the population of the same or different species.     

铜绿假单胞菌异质性耐药的研究进展

异质性耐药是指细菌中的同源亚群对某种抗生素表现出不同的敏感性,被认为是细菌由敏感进化成完全耐药的中间阶段.常规的临床检验无法有效检测出异质性耐药,这对临床治疗用药造成了巨大的威胁,引起患者的反复感染和用药失败.铜绿假单胞菌作为医院内感染的主要条件致病菌之一,其耐药机制已被广泛研究,而异质性耐药研究则相对较少.本文主要就...     

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.     

Combating bacteria and drug resistance by inhibiting mechanisms of persistence and adaptation

Antibiotics have revolutionized the treatment of infectious disease but have also rapidly selected for the emergence of resistant pathogens. Traditional methods of antibiotic discovery have failed to keep pace with the evolution of this resistance, which suggests that new strategies to combat bacterial infections may be required. An improved understanding of bacterial stress responses and evolution suggests that in some circumstances, the ability of bacteria to survive antibiotic therapy either by transiently tolerating antibiotics or by evolving resistance requires specific biochemical processes that may themselves be subject to intervention. Inhibiting these processes may prolong the efficacy of current antibiotics and provide an alternative to escalating the current arms race between antibiotics and bacterial resistance. Though these approaches are not clinically validated and will certainly face their own set of challenges, their potential to protect our ever-shrinking arsenal of antibiotics merits their investigation. This Review summarizes the early efforts toward this goal.     

Individual bacteria in structured environments rely on phenotypic resistance to phage

Bacteriophages represent an avenue to overcome the current antibiotic resistance crisis, but evolution of genetic resistance to phages remains a concern. In vitro, bacteria evolve genetic resistance, preventing phage adsorption or degrading phage DNA. In natural environments, evolved resistance is lower possibly because the spatial heterogeneity within biofilms, microcolonies, or wall populations favours phenotypic survival to lytic phages. However, it is also possible that the persistence of genetically sensitive bacteria is due to less efficient phage amplification in natural environments, the existence of refuges where bacteria can hide, and a reduced spread of resistant genotypes. Here, we monitor the interactions between individual planktonic bacteria in isolation in ephemeral refuges and bacteriophage by tracking the survival of individual cells. We find that in these transient spatial refuges, phenotypic resistance due to reduced expression of the phage receptor is a key determinant of bacterial survival. This survival strategy is in contrast with the emergence of genetic resistance in the absence of ephemeral refuges in well-mixed environments. Predictions generated via a mathematical modelling framework to track bacterial response to phages reveal that the presence of spatial refuges leads to fundamentally different population dynamics that should be considered in order to predict and manipulate the evolutionary and ecological dynamics of bacteria–phage interactions in naturally structured environments.

Bacteriophages represent a promising avenue to overcome the current antibiotic resistance crisis, but evolution of phage resistance remains a concern. This study shows that in the presence of spatial refuges, genetic resistance to phage is less of a problem than commonly assumed, but the persistence of genetically susceptible bacteria suggests that eradicating bacterial pathogens from structured environments may require combined phage-antibiotic therapies.     

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.     

Metabolic constraints on the evolution of antibiotic resistance

Despite our continuous improvement in understanding antibiotic resistance, the interplay between natural selection of resistance mutations and the environment remains unclear. To investigate the role of bacterial metabolism in constraining the evolution of antibiotic resistance, we evolved Escherichia coli growing on glycolytic or gluconeogenic carbon sources to the selective pressure of three different antibiotics. Profiling more than 500 intracellular and extracellular putative metabolites in 190 evolved populations revealed that carbon and energy metabolism strongly constrained the evolutionary trajectories, both in terms of speed and mode of resistance acquisition. To interpret and explore the space of metabolome changes, we developed a novel constraint‐based modeling approach using the concept of shadow prices. This analysis, together with genome resequencing of resistant populations, identified condition‐dependent compensatory mechanisms of antibiotic resistance, such as the shift from respiratory to fermentative metabolism of glucose upon overexpression of efflux pumps. Moreover, metabolome‐based predictions revealed emerging weaknesses in resistant strains, such as the hypersensitivity to fosfomycin of ampicillin‐resistant strains. Overall, resolving metabolic adaptation throughout antibiotic‐driven evolutionary trajectories opens new perspectives in the fight against emerging antibiotic resistance.     

Genotype‐by‐environment interactions due to antibiotic resistance and adaptation in Escherichia coli

Mutations that are beneficial in one environment can have different fitness effects in other environments. In the context of antibiotic resistance, the resulting genotype‐by‐environment interactions potentially make selection on resistance unpredictable in heterogeneous environments. Furthermore, resistant bacteria frequently fix additional mutations during evolution in the absence of antibiotics. How do these two types of mutations interact to determine the bacterial phenotype across different environments? To address this, I used Escherichia coli as a model system, measuring the effects of nine different rifampicin resistance mutations on bacterial growth in 31 antibiotic‐free environments. I did this both before and after approximately 200 generations of experimental evolution in antibiotic‐free conditions (LB medium), and did the same for the antibiotic‐sensitive wild type after adaptation to the same environment. The following results were observed: (i) bacteria with and without costly resistance mutations adapted to experimental conditions and reached similar levels of competitive fitness; (ii) rifampicin resistance mutations and adaptation to LB both indirectly altered growth in other environments; and (iii) resistant‐evolved genotypes were more phenotypically different from the ancestor and from each other than resistant‐nonevolved and sensitive‐evolved genotypes. This suggests genotype‐by‐environment interactions generated by antibiotic resistance mutations, observed previously in short‐term experiments, are more pronounced after adaptation to other types of environmental variation, making it difficult to predict long‐term selection on resistance mutations from fitness effects in a single environment.     

Effects of antibiotic resistance alleles on bacterial evolutionary responses to viral parasites

Antibiotic resistance has wide-ranging effects on bacterial phenotypes and evolution. However, the influence of antibiotic resistance on bacterial responses to parasitic viruses remains unclear, despite the ubiquity of such viruses in nature and current interest in therapeutic applications. We experimentally investigated this by exposing various Escherichia coli genotypes, including eight antibiotic-resistant genotypes and a mutator, to different viruses (lytic bacteriophages). Across 960 populations, we measured changes in population density and sensitivity to viruses, and tested whether variation among bacterial genotypes was explained by their relative growth in the absence of parasites, or mutation rate towards phage resistance measured by fluctuation tests for each phage. We found that antibiotic resistance had relatively weak effects on adaptation to phages, although some antibiotic-resistance alleles impeded the evolution of resistance to phages via growth costs. By contrast, a mutator allele, often found in antibiotic-resistant lineages in pathogenic populations, had a relatively large positive effect on phage-resistance evolution and population density under parasitism. This suggests costs of antibiotic resistance may modify the outcome of phage therapy against pathogenic populations previously exposed to antibiotics, but the effects of any co-occurring mutator alleles are likely to be stronger.     

Adaptive Resistance Mutations at Suprainhibitory Concentrations Independent of SOS Mutagenesis

Emergence of resistant bacteria during antimicrobial treatment is one of the most critical and universal health threats. It is known that several stress-induced mutagenesis and heteroresistance mechanisms can enhance microbial adaptation to antibiotics. Here, we demonstrate that the pathogen Bartonella can undergo stress-induced mutagenesis despite the fact it lacks error-prone polymerases, the rpoS gene and functional UV-induced mutagenesis. We demonstrate that Bartonella acquire de novo single mutations during rifampicin exposure at suprainhibitory concentrations at a much higher rate than expected from spontaneous fluctuations. This is while exhibiting a minimal heteroresistance capacity. The emerged resistant mutants acquired a single rpoB mutation, whereas no other mutations were found in their whole genome. Interestingly, the emergence of resistance in Bartonella occurred only during gradual exposure to the antibiotic, indicating that Bartonella sense and react to the changing environment. Using a mathematical model, we demonstrated that, to reproduce the experimental results, mutation rates should be transiently increased over 1,000-folds, and a larger population size or greater heteroresistance capacity is required. RNA expression analysis suggests that the increased mutation rate is due to downregulation of key DNA repair genes (mutS, mutY, and recA), associated with DNA breaks caused by massive prophage inductions. These results provide new evidence of the hazard of antibiotic overuse in medicine and agriculture.     

Dynamics of antibiotic resistant Mycobacterium tuberculosis during long-term infection and antibiotic treatment

For an infecting bacterium the human body provides several potential ecological niches with both internally (e.g. host immunity) and externally (e.g. antibiotic use) imposed growth restrictions that are expected to drive adaptive evolution in the bacterium, including the development of antibiotic resistance. To determine the extent and pattern of heterogeneity generated in a bacterial population during long-term antibiotic treatment, we examined in a monoclonal Mycobacterium tuberculosis infection antibiotic resistant mutants isolated from one patient during a 9-years period. There was a progressive accumulation of resistance mutations in the infecting clone. Furthermore, apparent clonal sweeps as well as co-existence of different resistant mutants were observed during this time, demonstrating that during treatment there is a high degree of dynamics in the bacterial population. These findings have important implications for diagnostics and treatment of drug resistant tuberculosis infections.     

Fast drug rotation reduces bacterial resistance evolution in a microcosm experiment

Drug rotation (cycling), in which multiple drugs are administrated alternatively, has the potential for limiting resistance evolution in pathogens. The frequency of drug alternation could be a major factor to determine the effectiveness of drug rotation. Drug rotation practices often have low frequency of drug alternation, with an expectation of resistance reversion. Here we, based on evolutionary rescue and compensatory evolution theories, suggest that fast drug rotation can limit resistance evolution in the first place. This is because fast drug rotation would give little time for the evolutionarily rescued populations to recover in population size and genetic diversity, and thus decrease the chance of future evolutionary rescue under alternate environmental stresses. We experimentally tested this hypothesis using the bacterium Pseudomonas fluorescens and two antibiotics (chloramphenicol and rifampin). Increasing drug rotation frequency reduced the chance of evolutionary rescue, and most of the finally surviving bacterial populations were resistant to both drugs. Drug resistance incurred significant fitness costs, which did not differ among the drug treatment histories. A link between population sizes during the early stages of drug treatment and the end-point fates of populations (extinction vs survival) suggested that population size recovery and compensatory evolution before drug shift increase the chance of population survival. Our results therefore advocate fast drug rotation as a promising approach to reduce bacterial resistance evolution, which in particular could be a substitute for drug combination when the latter has safety risks.     

Loss of a pyoverdine secondary receptor in Pseudomonas aeruginosa results in a fitter strain suitable for population invasion

The rapid emergence of antibiotic resistant bacterial pathogens constitutes a critical problem in healthcare and requires the development of novel treatments. Potential strategies include the exploitation of microbial social interactions based on public goods, which are produced at a fitness cost by cooperative microorganisms, but can be exploited by cheaters that do not produce these goods. Cheater invasion has been proposed as a ‘Trojan horse’ approach to infiltrate pathogen populations with strains deploying built-in weaknesses (e.g., sensitiveness to antibiotics). However, previous attempts have been often unsuccessful because population invasion by cheaters was prevented by various mechanisms including the presence of spatial structure (e.g., growth in biofilms), which limits the diffusion and exploitation of public goods. Here we followed an alternative approach and examined whether the manipulation of public good uptake and not its production could result in potential ‘Trojan horses’ suitable for population invasion. We focused on the siderophore pyoverdine produced by the human pathogen Pseudomonas aeruginosa MPAO1 and manipulated its uptake by deleting and/or overexpressing the pyoverdine primary (FpvA) and secondary (FpvB) receptors. We found that receptor synthesis feeds back on pyoverdine production and uptake rates, which led to strains with altered pyoverdine-associated costs and benefits. Moreover, we found that the receptor FpvB was advantageous under iron-limited conditions but revealed hidden costs in the presence of an antibiotic stressor (gentamicin). As a consequence, FpvB mutants became the fittest strain under gentamicin exposure, displacing the wildtype in liquid cultures, and in biofilms and during infections of the wax moth larvae Galleria mellonella, which both represent structured environments. Our findings reveal that an evolutionary trade-off associated with the costs and benefits of a versatile pyoverdine uptake strategy can be harnessed for devising a Trojan-horse candidate for medical interventions.Subject terms: Molecular evolution, Bacterial genetics, Clinical microbiology     

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.     

茄子种质资源抗青枯病的鉴定与评价

对304份茄子种质资源进行抗青枯病苗期人工接种鉴定,筛选出免疫材料10份,高抗材料51份,抗病材料35份,中抗材料32份,感病或高感材料176份,分别占鉴定材料的3.3%、16.8%、11.5%、10.5%和57.9%.茄子野生近缘种Solanum sisymbriifolium和S.torvum对青枯病有较强的抗病性,可作为茄子青枯病的抗源材料.获得4份抗青枯病的种间体细胞杂种.茄子对青枯病的抗性遗传较为复杂,主要由多基因控制.     

Biological cost and compensatory evolution in fusidic acid-resistant Staphylococcus aureus

Fusidic acid resistance resulting from mutations in elongation factor G (EF-G) of Staphylococcus aureus is associated with fitness costs during growth in vivo and in vitro. In both environments, these costs can be partly or fully compensated by the acquisition of secondary intragenic mutations. Among clinical isolates of S. aureus, fusidic acid-resistant strains have been identified that carry multiple mutations in EF-G at positions similar to those shown experimentally to cause resistance and fitness compensation. This observation suggests that fitness-compensatory mutations may be an important aspect of the evolution of antibiotic resistance in the clinical environment, and may contribute to a stabilization of the resistant bacteria present in a bacterial population.     

Accurate assessment of antibiotic susceptibility and screening resistant strains of a bacterial population by linear gradient plate

The dynamics of a bacterial population exposed to the minimum inhibitory concentration (MIC) of an antibiotic is an important issue in pharmacological research. Therefore, a novel antibiotic susceptibility test is urgently needed that can both precisely determine the MIC and accurately select antibiotic-resistant strains from clinical bacterial populations. For this purpose, we developed a method based on Fick's laws of diffusion using agar plates containing a linear gradient of antibiotic. The gradient plate contained two layers. The bottom layer consisted of 15 mL agar containing the appropriate concentration of enrofloxacin and allowed to harden in the form of a wedge with the plate slanted such that the entire bottom was just covered. The upper layer consisted of 15 mL plain nutrient agar added with the plate held in the horizontal position. After allowing vertical diffusion of the drug from the bottom agar layer for 12 h, the enrofloxacin concentration was diluted in proportion to the ratio of the agar layer thicknesses. The uniform linear concentration gradient was verified by measuring the enrofloxacin concentration on the agar surface. When heavy bacterial suspensions were spread on the agar surface and incubated for more than 12 h, only resistant cells were able to form colonies beyond the boundary of confluent growth of susceptible cells. In this way, the true MIC of enrofloxacin was determined. The MICs obtained using this linear gradient plate were consistent with those obtained using conventional antibiotic susceptibility tests. Discrete colonies were then spread onto a gradient plate with higher antibiotic concentrations; the boundary line increased significantly, and gene mutations conferring resistance were identified. This new method enables the rapid identification of resistant strains in the bacterial population. Use of the linear gradient plate can easily identify the precise MIC and reveal the dynamic differentiation of bacteria near the MIC. This method allows the study of genetic and physiological characteristics of individual strains, and may be useful for early warning of antibiotic resistance that may occur after use of certain antimicrobial agents, and guide clinical treatment.     

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.     

Digital PCR to Detect and Quantify Heteroresistance in Drug Resistant Mycobacterium tuberculosis

Drug resistance in Mycobacterium tuberculosis presents an enormous public health threat. It is typically defined as >1% of drug resistant colonies using the agar proportion method. Detecting small numbers of drug resistant Tb in a population, also known as heteroresistance, is challenging with current methodologies. Here we have utilized digital PCR to detect heteroresistance within M. tuberculosis populations with excellent accuracy versus the agar proportion method. We designed dual TaqMan-MGB probes to detect wild-type and mutant sequences of katG (315), rpoB (531), gyrA (94,95) and rrs (1401), genes that associate with resistance to isoniazid, rifampin, fluoroquinolone, and aminoglycoside respectively. We generated heteroresistant mixtures of susceptible and extensively drug resistant Tb, followed by DNA extraction and digital PCR. Digital PCR yielded a close approximation to agar proportion''s percentages of resistant colonies, and yielded 100% concordance with agar proportion''s susceptible/resistant results. Indeed, the digital PCR method was able to identify mutant sequence in mixtures containing as little as 1000∶1 susceptible:resistant Tb. By contrast, real-time PCR or PCR followed by Sanger sequencing were less sensitive and had little resolution to detect heteroresistance, requiring fully 1∶1 or 10∶1 susceptible:resistant ratios in order to detect resistance. Our assay can also work in sputum so long as sufficient quantities of Tb are present (>1000 cfu/ml). This work demonstrates the utility of digital PCR to detect and quantify heteroresistance in drug resistant Tb, which may be useful to inform treatment decisions faster than agar proportion.     

Branched chain fatty acid synthesis drives tissue-specific innate immune response and infection dynamics of Staphylococcus aureus

Fatty acid-derived acyl chains of phospholipids and lipoproteins are central to bacterial membrane fluidity and lipoprotein function. Though it can incorporate exogenous unsaturated fatty acids (UFA), Staphylococcus aureus synthesizes branched chain fatty acids (BCFA), not UFA, to modulate or increase membrane fluidity. However, both endogenous BCFA and exogenous UFA can be attached to bacterial lipoproteins. Furthermore, S. aureus membrane lipid content varies based upon the amount of exogenous lipid in the environment. Thus far, the relevance of acyl chain diversity within the S. aureus cell envelope is limited to the observation that attachment of UFA to lipoproteins enhances cytokine secretion by cell lines in a TLR2-dependent manner. Here, we leveraged a BCFA auxotroph of S. aureus and determined that driving UFA incorporation disrupted infection dynamics and increased cytokine production in the liver during systemic infection of mice. In contrast, infection of TLR2-deficient mice restored inflammatory cytokines and bacterial burden to wildtype levels, linking the shift in acyl chain composition toward UFA to detrimental immune activation in vivo. In in vitro studies, bacterial lipoproteins isolated from UFA-supplemented cultures were resistant to lipase-mediated ester hydrolysis and exhibited heightened TLR2-dependent innate cell activation, whereas lipoproteins with BCFA esters were completely inactivated after lipase treatment. These results suggest that de novo synthesis of BCFA reduces lipoprotein-mediated TLR2 activation and improves lipase-mediated hydrolysis making it an important determinant of innate immunity. Overall, this study highlights the potential relevance of cell envelope acyl chain repertoire in infection dynamics of bacterial pathogens.