Concentration-dependent selection of small phenotypic differences in TEM beta-lactamase-mediated antibiotic resistance

Selection versus transmission: Quantitative and organismic biology in antibiotic resistance

We aimed to determine the importance of selection (mostly dependent on the anthropogenic use of antimicrobials) and transmission (mostly dependent on hygiene and sanitation) as drivers of the spread of antibiotic-resistant bacterial populations. The first obstacle to estimating the relative weight of both independent variables is the lack of detailed quantitative data concerning the number of bacterial cells, potentially either pathogenic or harmless, and bacterial species exposed to antimicrobial action in the microbiotas of specific environments. The second obstacle is the difficulty of considering the relative importance of the transmission and selection exerting their combined effects on antibiotic resistance across eco-biological levels. As a consequence, advances are urgently required in quantitative biology and organismic biology of antimicrobial resistance. The absolute number of humans exposed to antibiotics and the absolute number of potentially pathogenic and commensal bacteria in their microbiomes should influence both the selection and transmission of resistant bacterial populations. The "whole Earth" microbiome, with astonishingly high numbers of bacterial cells and species, which are also exposed to anthropogenic antimicrobials in various biogeographical spaces, shapes the antibiotic resistance landscape. These biogeographical spaces influence various intensities of selection and transmission of potentially pathogenic bacteria. While waiting for more precise data, biostatistics analysis and mathematical or computational modeling can provide proxies to compare the influence of selection and transmission in resistant bacteria. In European countries with lower sanitation levels, antibiotic consumption plays a major role in increasing antibiotic resistance; however, this is not the case in countries with high sanitation levels. Although both independent variables are linked, their relative influence on the level of antibiotic resistance varies according to the particular location. Therefore, interventions directed to decrease antibiotic resistance should be designed "a la carte" for specific locations with particular ecological conditions, including sanitation facilities.

A study of antibiotic resistance pattern of clinical bacterial pathogens isolated from patients in a tertiary care hospital

We investigated antibiotic resistance pattern in clinical bacterial pathogens isolated from in-patients and out-patients, and compared it with non-clinical bacterial isolates. 475 bacterial strains isolated from patients were examined for antibiotic resistance. Staphylococcus spp. (148; 31.1%) were found to be the most prevalent, followed by Klebsiella pneumoniae (135; 28.4%), Escherichia coli (74; 15.5%), Pseudomonas aeruginosa (65; 13.6%), Enterobacter spp. (28; 5.8%), and Acinetobacter spp. (25; 5.2%). Drug-resistant bacteria isolated were extended spectrum-β-lactamase K. pneumoniae (8.8%), E. coli (20%), metallo-β-lactamase P. aeruginosa (14; 2.9%), erythromycin-inducing clindamycin resistant (7.4%), and methicillin-resistant Staphylococcus species (21.6%). Pathogens belonging to the Enterobacteriaceae family were observed to undergo directional selection developing resistance against antibiotics ciprofloxacin, piperacillin-tazobactam, cefepime, and cefuroxime. Pathogens in the surgical ward exhibited higher levels of antibiotic resistance, while non-clinical P. aeruginosa and K. pneumoniae strains were more antibiotic-susceptible. Our research assisted in identifying the drugs that can be used to control infections caused by antimicrobial resistant bacteria in the population and in monitoring the prevalence of drug-resistant bacterial pathogens.

Need for standardization in sub-lethal antibiotics research

While monitoring and managing resistant and persistent microbes is of utmost importance and should not be glossed over, one must also focus on mitigating the microbe's ability to cause harm. Exploring the concept of lowering or even suppressing the microbe's virulence with sub-Minimum Inhibitory Concentration (MIC) antibiotics holds promise and warrants further investigation. At present, such antibiotic concentrations have mostly been studied to cover the side-effects of gradient exposure, overlooking the possibility of utilizing them to influence not only bacterial virulence, but also colonization, fitness and collateral sensitivities. This review focuses on conflicting findings of studies demonstrating both increased and decreased virulence in microbes under sub-MIC antibiotic exposure. It identifies lack of standardization in this field of research as one of the main culprits for discordant results across numerous studies on virulence. It critically discusses important terminology related to bacterial traits and existing methods to determine MIC and sub-MIC ranges. Lastly, possible directions toward standardized sub-MIC profiling and thereby tailored treatment options in the future are explored.

Addition of aminoglycosides reduces recurrence of infections with multidrug-resistant Gram-negative bacilli in patients with sepsis and septic shock

OBJECTIVES

Aminoglycosides and β-lactams have been recommended for treatment of sepsis/septic shock despite a lack of mortality benefit. Previous studies have examined resistance emergence for the same bacterial isolate using old dosing regimens and during a narrow follow-up window. We hypothesised that combination regimens employing aminoglycosides will decrease the cumulative incidence of infections due to multidrug-resistant (MDR) Gram-negative bacilli (GNB) compared with β-lactams alone.

METHODS

All adult patients admitted to Barnes Jewish Hospital between 2010 and 2017 with a diagnosis of sepsis/septic shock were included in this retrospective cohort study. Patients were divided into two treatment groups, with and without aminoglycosides. Patient demographics, severity of presentation, administered antibiotics, follow-up cultures with susceptibility results for a period of 4-60 days, and mortality were extracted. After propensity score matching, a Fine-Gray subdistribution proportional hazards model summarised the estimated incidence of subsequent infections with MDR-GNB in the presence of all-cause death as a competing risk.

RESULTS

A total of 10 212 septic patients were included, with 1996 (19.5%) treated with at least two antimicrobials including one aminoglycoside. After propensity score matching, the cumulative incidence of MDR-GNB infections between 4-60 days was lower in the combination group (incidence at 60 days 0.073, 95% CI 0.062-0.085) versus patients not receiving aminoglycosides (0.116, 95% CI 0.102-0.130). Patients aged ≤65 years and with haematological malignancies had a larger treatment effect in subgroup analyses.

CONCLUSION

Addition of aminoglycosides to β-lactams may protect against subsequent infections due to MDR-GNB in patients with sepsis/septic shock.

Alternate Antimicrobial Therapies and Their Companion Tests

New antimicrobial approaches are essential to counter antimicrobial resistance. The drug development pipeline is exhausted with the emergence of resistance, resulting in unsuccessful trials. The lack of an effective drug developed from the conventional drug portfolio has mandated the introspection into the list of potentially effective unconventional alternate antimicrobial molecules. Alternate therapies with clinically explicable forms include monoclonal antibodies, antimicrobial peptides, aptamers, and phages. Clinical diagnostics optimize the drug delivery. In the era of diagnostic-based applications, it is logical to draw diagnostic-based treatment for infectious diseases. Selection criteria of alternate therapeutics in infectious diseases include detection, monitoring of response, and resistance mechanism identification. Integrating these diagnostic applications is disruptive to the traditional therapeutic development. The challenges and mitigation methods need to be noted. Applying the goals of clinical pharmacokinetics that include enhancing efficacy and decreasing toxicity of drug therapy, this review analyses the strong correlation of alternate antimicrobial therapeutics in infectious diseases. The relationship between drug concentration and the resulting effect defined by the pharmacodynamic parameters are also analyzed. This review analyzes the perspectives of aligning diagnostic initiatives with the use of alternate therapeutics, with a particular focus on companion diagnostic applications in infectious diseases.

Chemical characterization of riverine sediments affected by wastewater treatment plant effluent discharge

This study was aimed at assessing the contribution of wastewater treatment effluents to the contamination profile of the sediments of receiving waterways. Three wastewater treatment plants (WWTP) were addressed, encompassing different population equivalent sizes, urbanization degrees and treatment methods translating differences in expected contamination patterns. Within each WWTP system, the assessment targeted the effluent and sediment samples collected upstream and downstream the effluent discharge point; contaminants belonging to several concerning chemical classes (metals and metalloids; pesticides; pharmaceuticals and personal care products, PPCPs; and polycyclic aromatic hydrocarbons, PAHs) were quantified both in effluent and sediment samples. Clear associations between contaminants present in the effluent and corresponding sediment samples were not always verified. In fact, a noticeable difference between the number or abundance of contaminants detected in effluents and in sediments, suggesting that effluents are not always the most likely source (e.g. PAHs). However, sediment contaminants that were likely sourced by the effluents were also identified (e.g. PPCPs). Sediment analysis offers an important historical view of contamination, especially in flowing recipient ecosystems where any characterization over the water matrix is ephemeral and linking exclusively to the moment of sampling. Hence, sediments should be considered for the establishment of WWTP operational benchmarks regulating the emission of contaminants, which is currently focused mostly on effluent composition thus potentially over/underestimating the longer-term impact of effluent discharge in the recipient waterways.

Mycobacterium smegmatis strains genetically resistant to moxifloxacin emerge de novo from the moxifloxacin-surviving population containing high levels of superoxide, H2O2, hydroxyl radical, and Fe (II)

Background

The antibiotic-exposed bacteria often contain the reactive oxygen species (ROS), hydroxyl radical, which inflicts genome-wide mutations, causing the de novo formation of antibiotic-resistant strains. Hydroxyl radical is generated by Fenton reaction of Fe (II) with the ROS, H₂O₂, which, in turn, is formed by the dismutation of the ROS, superoxide. Therefore, for the emergence of bacterial strains genetically resistant to antibiotics, increased levels of superoxide, H₂O₂, hydroxyl radical, and Fe (II) should be present in the antibiotic-exposed bacteria. Here, we verified this premise by finding out whether the in vitro cultures of M. smegmatis, exposed to MBC of moxifloxacin for a prolonged duration, contain significantly high levels of superoxide, H₂O₂, hydroxyl radical, and Fe (II).

Methods

Biological triplicate cultures of M. smegmatis, were exposed to MBC of moxifloxacin for 84 h. The colony-forming units (CFUs) of the cultures were determined on moxifloxacin-free and moxifloxacin-containing plates for the entire 84 h at a regular interval of 6 h. The cultures were analyzed at specific time points of killing phase (KP), antibiotic-surviving phase (ASP), and regrowth phase (RGP) for the presence of superoxide, H₂O₂, hydroxyl radical, and Fe (II) using the ROS- and Fe (II)-detecting fluorescence probes. The experimental cultures were grown in the presence of ROS and Fe (II) quenchers also and determined the levels of fluorescence corresponding to the ROS- and Fe (II)-specific probes. This was performed to establish the specificity of detection of ROS and Fe (II). Biological triplicate cultures, unexposed to moxifloxacin but cultured for 84 h, were used as the control for the measurement of ROS and Fe (II) levels. The CFUs of the cultures were determined on moxifloxacin-free and moxifloxacin-containing plates for the entire 84 h at regular intervals of 6 h. Flow cytometry analyses were performed for the detection and quantitation of the levels of fluorescence of the ROS-and Fe (II)-specific probes. The experimental cultures were grown in the presence of thiourea and bipyridyl as the ROS and Fe (II) quenchers, respectively, for the determination of the levels of fluorescence corresponding to the ROS- and Fe (II)-specific probes. Paired t-test was used to calculate statistical significance (n = 3).

Results

The moxifloxacin-exposed cultures, but not the cultures unexposed to moxifloxacin, showed a triphasic response with a KP, ASP, and RGP. The cells in the late KP and ASP contained significantly elevated levels of superoxide, H₂O₂, hydroxyl radical, and Fe (II). Thus, high levels of the ROS and Fe (II) were found in the small population (in the ASP) of M. smegmatis cells that survived the moxifloxacin-mediated killing. From this moxifloxacin-surviving population (in the ASP), moxifloxacin-resistant genetic resisters emerged de novo at high frequency, regrew, divided, and populated the cultures. The levels of these ROS, Fe (II), and the high moxifloxacin resister generation frequency were quenched in the cultures grown in the presence of the respective ROS and Fe (II) quenchers. The cultures unexposed to moxifloxacin did not show any of these responses, indicating that the whole response was specific to antibiotic exposure.

Conclusions

Significantly high levels of superoxide, H₂O₂, hydroxyl radical, and Fe (II) were generated in the M. smegmatis cultures exposed to moxifloxacin for a prolonged duration. It promoted the de novo emergence of genetic resisters to moxifloxacin at high frequency.

Evolutionary Pathways and Trajectories in Antibiotic Resistance

Evolution is the hallmark of life. Descriptions of the evolution of microorganisms have provided a wealth of information, but knowledge regarding "what happened" has precluded a deeper understanding of "how" evolution has proceeded, as in the case of antimicrobial resistance. The difficulty in answering the "how" question lies in the multihierarchical dimensions of evolutionary processes, nested in complex networks, encompassing all units of selection, from genes to communities and ecosystems. At the simplest ontological level (as resistance genes), evolution proceeds by random (mutation and drift) and directional (natural selection) processes; however, sequential pathways of adaptive variation can occasionally be observed, and under fixed circumstances (particular fitness landscapes), evolution is predictable. At the highest level (such as that of plasmids, clones, species, microbiotas), the systems' degrees of freedom increase dramatically, related to the variable dispersal, fragmentation, relatedness, or coalescence of bacterial populations, depending on heterogeneous and changing niches and selective gradients in complex environments. Evolutionary trajectories of antibiotic resistance find their way in these changing landscapes subjected to random variations, becoming highly entropic and therefore unpredictable. However, experimental, phylogenetic, and ecogenetic analyses reveal preferential frequented paths (highways) where antibiotic resistance flows and propagates, allowing some understanding of evolutionary dynamics, modeling and designing interventions. Studies on antibiotic resistance have an applied aspect in improving individual health, One Health, and Global Health, as well as an academic value for understanding evolution. Most importantly, they have a heuristic significance as a model to reduce the negative influence of anthropogenic effects on the environment.

Genotoxic Agents Produce Stressor-Specific Spectra of Spectinomycin Resistance Mutations Based on Mechanism of Action and Selection in Bacillus subtilis

Mutagenesis is integral for bacterial evolution and the development of antibiotic resistance. Environmental toxins and stressors are known to elevate the rate of mutagenesis through direct DNA toxicity, known as stress-associated mutagenesis, or via a more general stress-induced process that relies on intrinsic bacterial pathways. Here, we characterize the spectra of mutations induced by an array of different stressors using high-throughput sequencing to profile thousands of spectinomycin-resistant colonies of Bacillus subtilis. We found 69 unique mutations in the rpsE and rpsB genes, and that each stressor leads to a unique and specific spectrum of antibiotic-resistance mutations. While some mutations clearly reflected the DNA damage mechanism of the stress, others were likely the result of a more general stress-induced mechanism. To determine the relative fitness of these mutants under a range of antibiotic selection pressures, we used multistrain competitive fitness experiments and found an additional landscape of fitness and resistance. The data presented here support the idea that the environment in which the selection is applied (mutagenic stressors that are present), as well as changes in local drug concentration, can significantly alter the path to spectinomycin resistance in B. subtilis.

Concordance Between Antibiotic Resistance Genes and Susceptibility in Symptomatic Urinary Tract Infections

PURPOSE

Studies have shown that multiple genes influence antibiotic susceptibility, but the relationship between genotypic and phenotypic antibiotic susceptibility is unclear. We sought to analyze the concordance between the presence of antibiotic resistance (ABR) genes and antibiotic susceptibility results in urine samples collected from patients with symptomatic urinary tract infection (UTI).

PATIENTS AND METHODS

Urine samples were collected from patients presenting to 37 geographically disparate urology clinics across the United States from July 2018 to February 2019. Multiplex polymerase chain reaction was used to detect 27 ABR genes. In samples containing at least one culturable organism at a concentration of ≥ 104 cells per mL, pooled antibiotic susceptibility testing (P-AST), which involves simultaneous growing all detected bacteria together in the presence of antibiotic and then measure susceptibility, was performed against 14 antibiotics. The concordance rate between the ABR genes and the P-AST results was generated for the overall group. The concordance rates for each antibiotic between monomicrobial and polymicrobial infection were compared using chi-square test.

RESULTS

Results from ABR gene detection and P-AST of urine samples from 1155 patients were included in the concordance analysis. Overall, there was a 60% concordance between the presence or absence of ABR genes and corresponding antimicrobial susceptibility with a range of 49-78% across antibiotic classes. Vancomycin, meropenem, and piperacillin/tazobactam showed significantly lower concordance rates in polymicrobial infections than in monomicrobial infections.

CONCLUSION

Given the 40% discordance rate, the detection of ABR genes alone may not provide reliable data to make informed clinical decisions in UTI management. However, when used in conjunction with susceptibility testing, ABR gene data can offer valuable clinical information for antibiotic stewardship.

Modeling the effect of vaccination on selection for antibiotic resistance in Streptococcus pneumonia e

Vaccines against bacterial pathogens can protect recipients from becoming infected with potentially antibiotic-resistant pathogens. However, by altering the selective balance between antibiotic-sensitive and antibiotic-resistant bacterial strains, vaccines may also suppress-or spread-antibiotic resistance among unvaccinated individuals. Predicting the outcome of vaccination requires knowing what drives selection for drug-resistant bacterial pathogens and what maintains the circulation of both antibiotic-sensitive and antibiotic-resistant strains of bacteria. To address this question, we used mathematical modeling and data from 2007 on penicillin consumption and penicillin nonsusceptibility in Streptococcus pneumoniae (pneumococcus) invasive isolates from 27 European countries. We show that the frequency of penicillin resistance in S. pneumoniae can be explained by between-host diversity in antibiotic use, heritable diversity in pneumococcal carriage duration, or frequency-dependent selection brought about by within-host competition between antibiotic-resistant and antibiotic-sensitive S. pneumoniae strains. We used our calibrated models to predict the impact of non-serotype-specific pneumococcal vaccination upon the prevalence of S. pneumoniae carriage, incidence of disease, and frequency of S. pneumoniae antibiotic resistance. We found that the relative strength and directionality of competition between drug-resistant and drug-sensitive pneumococcal strains was the most important determinant of whether vaccination would promote, inhibit, or have little effect upon the evolution of antibiotic resistance. Last, we show that country-specific differences in pathogen transmission substantially altered the predicted impact of vaccination, highlighting that policies for managing antibiotic resistance with vaccines must be tailored to a specific pathogen and setting.

Role of Synonymous Mutations in the Evolution of TEM β-Lactamase Genes

Nonsynonymous mutations are well documented in TEM β-lactamases. The resulting amino acid changes often alter the conferred phenotype from broad spectrum (2b) conferred by TEM-1 to extended spectrum (2be), inhibitor resistant (2br), or both extended spectrum and inhibitor resistant (2ber). The encoding bla _TEM genes also deviate in numerous synonymous mutations, which are not well understood. bla _TEM-3 (2be), bla _TEM-33 (2br), and bla _TEM-109 (2ber) were studied in comparison to bla _TEM-1 bla _TEM-33 was chosen for more detailed studies because it deviates from bla _TEM-1 by a single nonsynonymous mutation and three additional synonymous mutations. Genes encoding the enzymes with only nonsynonymous or all (including synonymous) mutations plus all permutations between bla _TEM-1 and bla _TEM-33 were expressed in Escherichia coli cells. In disc diffusion assays, genes encoding TEM-3, TEM-33, and TEM-109 with all synonymous mutations resulted in higher resistance levels than genes without synonymous mutations. Disc diffusion assays with the 16 genes carrying all possible nucleotide change combinations between bla _TEM-1 and bla _TEM-33 indicated different susceptibilities for different variants. Nucleotide BLAST searches did not identify genes without synonymous mutations but did identify some without nonsynonymous mutations. Energies of possible secondary mRNA structures calculated with mfold are generally higher with synonymous mutations, suggesting that their role could be to destabilize the mRNA and facilitate its unfolding for efficient translation. In summary, our data indicate that transition from bla _TEM-1 to other variant genes by simply acquiring the nonsynonymous mutations is not favored. Instead, synonymous mutations seem to support the transition to other variant genes with nonsynonymous mutations leading to different phenotypes.

Cryptic β-Lactamase Evolution Is Driven by Low β-Lactam Concentrations

Very low antibiotic concentrations have been shown to drive the evolution of antimicrobial resistance. While substantial progress has been made to understand the driving role of low concentrations during resistance development for different antimicrobial classes, the importance of β-lactams, the most commonly used antibiotics, is still poorly studied.

Our current understanding of how low antibiotic concentrations shape the evolution of contemporary β-lactamases is limited. Using the widespread carbapenemase OXA-48, we tested the long-standing hypothesis that selective compartments with low antibiotic concentrations cause standing genetic diversity that could act as a gateway to developing clinical resistance. Here, we subjected Escherichia coli expressing bla_OXA-48, on a clinical plasmid, to experimental evolution at sub-MICs of ceftazidime. We identified and characterized seven single variants of OXA-48. Susceptibility profiles and dose-response curves showed that they increased resistance only marginally. However, in competition experiments at sub-MICs of ceftazidime, they demonstrated strong selectable fitness benefits. Increased resistance was also reflected in elevated catalytic efficiencies toward ceftazidime. These changes are likely caused by enhanced flexibility of the Ω- and β5-β6 loops and fine-tuning of preexisting active site residues. In conclusion, low-level concentrations of β-lactams can drive the evolution of β-lactamases through cryptic phenotypes which may act as stepping-stones toward clinical resistance.

IMPORTANCE Very low antibiotic concentrations have been shown to drive the evolution of antimicrobial resistance. While substantial progress has been made to understand the driving role of low concentrations during resistance development for different antimicrobial classes, the importance of β-lactams, the most commonly used antibiotics, is still poorly studied. Here, we shed light on the evolutionary impact of low β-lactam concentrations on the widespread β-lactamase OXA-48. Our data indicate that the exposure to β-lactams at very low concentrations enhances β-lactamase diversity and drives the evolution of β-lactamases by significantly influencing their substrate specificity. Thus, in contrast to high concentrations, low levels of these drugs may substantially contribute to the diversification and divergent evolution of these enzymes, providing a standing genetic diversity that can be selected and mobilized when antibiotic pressure increases.

The Origin of Niches and Species in the Bacterial World

Niches are spaces for the biological units of selection, from cells to complex communities. In a broad sense, "species" are biological units of individuation. Niches do not exist without individual organisms, and every organism has a niche. We use "niche" in the Hutchinsonian sense as an abstraction of a multidimensional environmental space characterized by a variety of conditions, both biotic and abiotic, whose quantitative ranges determine the positive or negative growth rates of the microbial individual, typically a species, but also parts of the communities of species contained in this space. Microbial organisms ("species") constantly diversify, and such diversification (radiation) depends on the possibility of opening up unexploited or insufficiently exploited niches. Niche exploitation frequently implies "niche construction," as the colonized niche evolves with time, giving rise to new potential subniches, thereby influencing the selection of a series of new variants in the progeny. The evolution of niches and organisms is the result of reciprocal interacting processes that form a single unified process. Centrifugal microbial diversification expands the limits of the species' niches while a centripetal or cohesive process occurs simultaneously, mediated by horizontal gene transfers and recombinatorial events, condensing all of the information recovered during the diversifying specialization into "novel organisms" (possible future species), thereby creating a more complex niche, where the selfishness of the new organism(s) establishes a "homeostatic power" limiting the niche's variation. Once the niche's full carrying capacity has been reached, reproductive isolation occurs, as no foreign organisms can outcompete the established population/community, thereby facilitating speciation. In the case of individualization-speciation of the microbiota, its contribution to the animal' gut structure is a type of "niche construction," the result of crosstalk between the niche (host) and microorganism(s). Lastly, there is a parallelism between the hierarchy of niches and that of microbial individuals. The increasing anthropogenic effects on the biosphere (such as globalization) might reduce the diversity of niches and bacterial individuals, with the potential emergence of highly transmissible multispecialists (which are eventually deleterious) resulting from the homogenization of the microbiosphere, a possibility that should be explored and prevented.

Stochastic bacterial population dynamics restrict the establishment of antibiotic resistance from single cells

The emergence of antibiotic resistance poses a critical threat to the efficacy of antibiotic treatments. A resistant bacterial population must originally arise from a single cell that mutates or acquires a resistance gene. This single cell may, by chance, fail to successfully reproduce before it dies, leading to loss of the nascent resistant lineage. Here, we show that antibiotic concentrations that selectively favor resistance are nonetheless sufficient to reduce the chance of outgrowth from a single cell to a very low probability. Our findings suggest that lower antibiotic concentrations than those required to clear a large resistant population may be sufficient to prevent, with high probability, outgrowth of initially rare resistant mutants.

A better understanding of how antibiotic exposure impacts the evolution of resistance in bacterial populations is crucial for designing more sustainable treatment strategies. The conventional approach to this question is to measure the range of concentrations over which resistant strain(s) are selectively favored over a sensitive strain. Here, we instead investigate how antibiotic concentration impacts the initial establishment of resistance from single cells, mimicking the clonal expansion of a resistant lineage following mutation or horizontal gene transfer. Using two Pseudomonas aeruginosa strains carrying resistance plasmids, we show that single resistant cells have <5% probability of detectable outgrowth at antibiotic concentrations as low as one-eighth of the resistant strain’s minimum inhibitory concentration (MIC). This low probability of establishment is due to detrimental effects of antibiotics on resistant cells, coupled with the inherently stochastic nature of cell division and death on the single-cell level, which leads to loss of many nascent resistant lineages. Our findings suggest that moderate doses of antibiotics, well below the MIC of resistant strains, may effectively restrict de novo emergence of resistance even though they cannot clear already-large resistant populations.

Aryl Hydrocarbon Receptor Modulation by Tuberculosis Drugs Impairs Host Defense and Treatment Outcomes

Antimicrobial resistance in tuberculosis (TB) is a public health threat of global dimension, worsened by increasing drug resistance. Host-directed therapy (HDT) is an emerging concept currently explored as an adjunct therapeutic strategy for TB. One potential host target is the ligand-activated transcription factor aryl hydrocarbon receptor (AhR), which binds TB virulence factors and controls antibacterial responses. Here, we demonstrate that in the context of therapy, the AhR binds several TB drugs, including front line drugs rifampicin (RIF) and rifabutin (RFB), resulting in altered host defense and drug metabolism. AhR sensing of TB drugs modulates host defense mechanisms, notably impairs phagocytosis, and increases TB drug metabolism. Targeting AhR in vivo with a small-molecule inhibitor increases RFB-treatment efficacy. Thus, the AhR markedly impacts TB outcome by affecting both host defense and drug metabolism. As a corollary, we propose the AhR as a potential target for HDT in TB in adjunct to canonical chemotherapy.

Mathematical modelling for antibiotic resistance control policy: do we know enough?

BACKGROUND

Antibiotics remain the cornerstone of modern medicine. Yet there exists an inherent dilemma in their use: we are able to prevent harm by administering antibiotic treatment as necessary to both humans and animals, but we must be mindful of limiting the spread of resistance and safeguarding the efficacy of antibiotics for current and future generations. Policies that strike the right balance must be informed by a transparent rationale that relies on a robust evidence base.

MAIN TEXT

One way to generate the evidence base needed to inform policies for managing antibiotic resistance is by using mathematical models. These models can distil the key drivers of the dynamics of resistance transmission from complex infection and evolutionary processes, as well as predict likely responses to policy change in silico. Here, we ask whether we know enough about antibiotic resistance for mathematical modelling to robustly and effectively inform policy. We consider in turn the challenges associated with capturing antibiotic resistance evolution using mathematical models, and with translating mathematical modelling evidence into policy.

CONCLUSIONS

We suggest that in spite of promising advances, we lack a complete understanding of key principles. From this we advocate for priority areas of future empirical and theoretical research.

Aggressive or moderate drug therapy for infectious diseases? Trade-offs between different treatment goals at the individual and population levels

Antimicrobial resistance is one of the major public health threats of the 21st century. There is a pressing need to adopt more efficient treatment strategies in order to prevent the emergence and spread of resistant strains. The common approach is to treat patients with high drug doses, both to clear the infection quickly and to reduce the risk of de novo resistance. Recently, several studies have argued that, at least in some cases, low-dose treatments could be more suitable to reduce the within-host emergence of antimicrobial resistance. However, the choice of a drug dose may have consequences at the population level, which has received little attention so far. Here, we study the influence of the drug dose on resistance and disease management at the host and population levels. We develop a nested two-strain model and unravel trade-offs in treatment benefits between an individual and the community. We use several measures to evaluate the benefits of any dose choice. Two measures focus on the emergence of resistance, at the host level and at the population level. The other two focus on the overall treatment success: the outbreak probability and the disease burden. We find that different measures can suggest different dosing strategies. In particular, we identify situations where low doses minimize the risk of emergence of resistance at the individual level, while high or intermediate doses prove most beneficial to improve the treatment efficiency or even to reduce the risk of resistance in the population.

Concentration-dependent enrichment of resistant Enterococcus faecium exposed to linezolid in an in vitro dynamic model

To explore the relationship between pharmacokinetic variables and enterococcal resistance to linezolid, a vancomycin-resistant strain whose mutant prevention concentration (MPC) exceeded the MIC by two fold was selected among six clinical isolates of Enterococcus faecium. The selected strain was exposed to simulated pharmacokinetics of twice-daily linezolid for five days. Mutants resistant to 2 × MIC of the antibiotic were enriched at ratios of the 24-h area under the concentration-time curve (AUC₂₄) to the MIC of 15 and 30 h but not at 60 and 120 h. These observations could be explained by the different times when antibiotic concentrations exceed the MPC (T_>MPC): 0 to 14, 63 and 100% of the dosing interval. Using the area under the bacterial mutant concentration-time curve (AUBC_M) determined in this study and in previous work with other E. faecium strains (MPC/MIC 4), a strain-independent T_>MPC relationship with mutant enrichment was established.

Within-host dynamics shape antibiotic resistance in commensal bacteria

The spread of antibiotic resistance, a major threat to human health, is poorly understood. Simple population-level models of disease transmission predict that above a certain rate of antibiotic consumption in a population, resistant bacteria should completely eliminate non-resistant strains, while below this threshold they should be unable to persist at all. This prediction stands at odds with empirical evidence showing that resistant and non-resistant strains coexist stably over a wide range of antibiotic consumption rates. Not knowing what drives this long-term coexistence is a barrier to developing evidence-based strategies for managing the spread of resistance. Here, we argue that competition between resistant and sensitive pathogens within individual hosts gives resistant pathogens a relative fitness benefit when they are rare, promoting coexistence between strains at the population level. To test this hypothesis, we embed mechanistically-explicit within-host dynamics in a structurally-neutral disease transmission model. Doing so allows us to reproduce patterns of resistance observed in the opportunistic pathogens Escherichia coli and Streptococcus pneumoniae across European countries, and to identify factors that may shape resistance evolution in bacteria by modulating the intensity and outcomes of within-host competition.

An ecosystem framework for understanding and treating disease

Pathogens and cancers are pervasive health risks in the human population. I argue that if we are to better understand disease and its treatment, then we need to take an ecological perspective of disease itself. I generalize and extend an emerging framework that views disease as an ecosystem and many of its components as interacting in a community. I develop the framework for biological etiological agents (BEAs) that multiply within humans—focusing on bacterial pathogens and cancers—but the framework could be extended to include other host and parasite species. I begin by describing why we need an ecosystem framework to understand disease, and the main components and interactions in bacterial and cancer disease ecosystems. Focus is then given to the BEA and how it may proceed through characteristic states, including emergence, growth, spread and regression. The framework is then applied to therapeutic interventions. Central to success is preventing BEA evasion, the best known being antibiotic resistance and chemotherapeutic resistance in cancers. With risks of evasion in mind, I propose six measures that either introduce new components into the disease ecosystem or manipulate existing ones. An ecosystem framework promises to enhance our understanding of disease, BEA and host (co)evolution, and how we can improve therapeutic outcomes.

Novel Insights into Selection for Antibiotic Resistance in Complex Microbial Communities

Recent research has demonstrated that selection for antibiotic resistance occurs at very low antibiotic concentrations in single-species experiments, but the relevance of these findings when species are embedded in complex microbial communities is unclear. We show that the strength of selection for naturally occurring resistance alleles in a complex community remains constant from low subinhibitory to above clinically relevant concentrations. Selection increases with antibiotic concentration before reaching a plateau where selection remains constant over a 2-order-magnitude concentration range. This is likely to be due to cross protection of the susceptible bacteria in the community following rapid extracellular antibiotic degradation by the resistant population, shown experimentally through a combination of chemical quantification and bacterial growth experiments. Metagenome and 16S rRNA analyses of sewage-derived bacterial communities evolved under cefotaxime exposure show preferential enrichment for bla_CTX-M genes over all other beta-lactamase genes, as well as positive selection and co-selection for antibiotic resistant, opportunistic pathogens. These findings have far-reaching implications for our understanding of the evolution of antibiotic resistance, by challenging the long-standing assumption that selection occurs in a dose-dependent manner.

Antibiotic resistance is one of the greatest global issues facing society. Still, comparatively little is known about selection for resistance at very low antibiotic concentrations. We show that the strength of selection for clinically important resistance genes within a complex bacterial community can remain constant across a large antibiotic concentration range (wide selective space). Therefore, largely understudied ecological compartments could be just as important as clinical environments for selection of antibiotic resistance.

Transmission in the Origins of Bacterial Diversity, From Ecotypes to Phyla

Any two lineages, no matter how distant they are now, began their divergence as one population splitting into two lineages that could coexist indefinitely. The rate of origin of higher-level taxa is therefore the product of the rate of speciation times the probability that two new species coexist long enough to reach a particular level of divergence. Here I have explored these two parameters of disparification in bacteria. Owing to low recombination rates, sexual isolation is not a necessary milestone of bacterial speciation. Rather, irreversible and indefinite divergence begins with ecological diversification, that is, transmission of a bacterial lineage to a new ecological niche, possibly to a new microhabitat but at least to new resources. Several algorithms use sequence data from a taxon of focus to identify phylogenetic groups likely to bear the dynamic properties of species. Identifying these newly divergent lineages allows us to characterize the genetic bases of speciation, as well as the ecological dimensions upon which new species diverge. Speciation appears to be least frequent when a given lineage has few new resources it can adopt, as exemplified by photoautotrophs, C1 heterotrophs, and obligately intracellular pathogens; speciation is likely most rapid for generalist heterotrophs. The genetic basis of ecological divergence may determine whether ecological divergence is irreversible and whether lineages will diverge indefinitely into the future. Long-term coexistence is most likely when newly divergent lineages utilize at least some resources not shared with the other and when the resources themselves will coexist into the remote future.

Environmental and genetic modulation of the phenotypic expression of antibiotic resistance

Antibiotic resistance can be acquired by mutation or horizontal transfer of a resistance gene, and generally an acquired mechanism results in a predictable increase in phenotypic resistance. However, recent findings suggest that the environment and/or the genetic context can modify the phenotypic expression of specific resistance genes/mutations. An important implication from these findings is that a given genotype does not always result in the expected phenotype. This dissociation of genotype and phenotype has important consequences for clinical bacteriology and for our ability to predict resistance phenotypes from genetics and DNA sequences. A related problem concerns the degree to which the genes/mutations currently identified in vitro can fully explain the in vivo resistance phenotype, or whether there is a significant additional amount of presently unknown mutations/genes (genetic ‘dark matter’) that could contribute to resistance in clinical isolates. Finally, a very important question is whether/how we can identify the genetic features that contribute to making a successful pathogen, and predict why some resistant clones are very successful and spread globally? In this review, we describe different environmental and genetic factors that influence phenotypic expression of antibiotic resistance genes/mutations and how this information is needed to understand why particular resistant clones spread worldwide and to what extent we can use DNA sequences to predict evolutionary success.

Genetic adaptation of microbial populations present in high-intensity catfish production systems with therapeutic oxytetracycline treatment

Microbial communities that are present in aquaculture production systems play significant roles in degrading organic matter, controlling diseases, and formation of antibiotic resistance. It is important to understand the diversity and abundance of microbial communities and their genetic adaptations associated with environmental physical and chemical changes. Here we collected water and sediment samples from a high-intensity catfish production system and its original water reservoir. The metagenomic analysis showed that Proteobacteria, Actinobacteria, Bacteroidetes, Cyanobacteria, and Firmicutes were the top five phyla identified from all samples. The aquaculture production system significantly changed the structure of aquatic microbial populations. Substantial changes were also observed in SNP patterns among four sample types. The gene-specific sweep was found to be more common than genome-wide sweep. The selective sweep analysis revealed that 21 antibiotic resistant (AR) genes were under selection, with most belonging to antibiotic efflux pathways. Over 200 AR gene gains and losses were determined by changes in gene frequencies. Most of the AR genes were characterized as ABC efflux pumps, RND efflux pumps, and tetracycline MFS efflux pumps. Results of this study suggested that aquaculture waste, especially waste containing therapeutic antibiotics, has a significant impact on microbial population structures and their genetic structures.

Integrating human and environmental health in antibiotic risk assessment: A critical analysis of protection goals, species sensitivity and antimicrobial resistance

Antibiotics are vital in the treatment of bacterial infectious diseases but when released into the environment they may impact non-target organisms that perform vital ecosystem services and enhance antimicrobial resistance development with significant consequences for human health. We evaluate whether the current environmental risk assessment regulatory guidance is protective of antibiotic impacts on the environment, protective of antimicrobial resistance, and propose science-based protection goals for antibiotic manufacturing discharges. A review and meta-analysis was conducted of aquatic ecotoxicity data for antibiotics and for minimum selective concentration data derived from clinically relevant bacteria. Relative species sensitivity was investigated applying general linear models, and predicted no effect concentrations were generated for toxicity to aquatic organisms and compared with predicted no effect concentrations for resistance development. Prokaryotes were most sensitive to antibiotics but the range of sensitivities spanned up to several orders of magnitude. We show reliance on one species of (cyano)bacteria and the 'activated sludge respiration inhibition test' is not sufficient to set protection levels for the environment. Individually, neither traditional aquatic predicted no effect concentrations nor predicted no effect concentrations suggested to safeguard for antimicrobial resistance, protect against environmental or human health effects (via antimicrobial resistance development). Including data from clinically relevant bacteria and also more species of environmentally relevant bacteria in the regulatory framework would help in defining safe discharge concentrations for antibiotics for patient use and manufacturing that would protect environmental and human health. It would also support ending unnecessary testing on metazoan species.

The Acinetobacter Outer Membrane Contains Multiple Specific Channels for Carbapenem β-Lactams as Revealed by Kinetic Characterization Analyses of Imipenem Permeation into Acinetobacter baylyi Cells

The number and type of outer membrane (OM) channels responsible for carbapenem uptake in Acinetobacter are still not well defined. Here, we addressed these questions by using Acinetobacter baylyi as a model species and a combination of methodologies aimed to characterize OM channels in their original membrane environment. Kinetic and competition analyses of imipenem (IPM) uptake by A. baylyi whole cells allowed us to identify different carbapenem-specific OM uptake sites. Comparative analyses of IPM uptake by A. baylyi wild-type (WT) cells and ΔcarO mutants lacking CarO indicated that this OM protein provided a carbapenem uptake site displaying saturable kinetics and common binding sites for basic amino acids compatible with a specific channel. The kinetic analysis uncovered another carbapenem-specific channel displaying a somewhat lower affinity for IPM than that of CarO and, in addition, common binding sites for basic amino acids as determined by competition studies. The use of A. baylyi gene deletion mutants lacking OM proteins proposed to function in carbapenem uptake in Acinetobacter baumannii indicated that CarO and OprD/OccAB1 mutants displayed low but consistent reductions in susceptibility to different carbapenems, including IPM, meropenem, and ertapenem. These two mutants also showed impaired growth on l-Arg but not on other carbon sources, further supporting a role of CarO and OprD/OccAB1 in basic amino acid and carbapenem uptake. A multiple-carbapenem-channel scenario may provide clues to our understanding of the contribution of OM channel loss or mutation to the carbapenem-resistant phenotype evolved by pathogenic members of the Acinetobacter genus.

The evolution of no-cost resistance at sub-MIC concentrations of streptomycin in Streptomyces coelicolor

At the high concentrations used in medicine, antibiotics exert strong selection on bacterial populations for the evolution of resistance. However, these lethal concentrations may not be representative of the concentrations bacteria face in soil, a recognition that has led to questions of the role of antibiotics in soil environments as well as the dynamics of resistance evolution during sublethal challenge. Here we examine the evolution of resistance to sub-minimal inhibitory concentrations (sub-MIC) of streptomycin in the filamentous soil bacterium Streptomyces coelicolor. First, we show that spontaneous resistance to streptomycin causes an average fitness deficit of ~21% in the absence of drugs; however, these costs are eliminated at concentrations as low as 1/10 the MIC of susceptible strains. Using experimental evolution, we next show that resistance to >MIC levels of streptomycin readily evolves when bacteria are exposed to sub-MIC doses for 500 generations. Furthermore, the resistant clones that evolved at sub-MIC streptomycin concentrations carry no fitness cost. Whole-genome analyses reveal that evolved resistant clones fixed some of the same mutations as those isolated at high drug concentrations; however, all evolved clones carry additional mutations and some fixed mutations that either compensate for costly resistance or have no associated fitness costs. Our results broaden the conditions under which resistance can evolve in nature and suggest that rather than low-concentration antibiotics acting as signals, resistance evolves in response to antibiotics used as weapons.

Governing factors affecting the impacts of silver nanoparticles on wastewater treatment

Silver nanoparticles (nanosilver or AgNPs) enter municipal wastewater from various sources, raising concerns about their potential adverse effects on wastewater treatment processes. We argue that the biological effects of silver nanoparticles at environmentally realistic concentrations (μgL^-1 or lower) on the performance of a full-scale municipal water resource recovery facility (WRRF) are minimal. Reactor configuration is a critical factor that reduces or even mutes the toxicity of silver nanoparticles towards wastewater microbes in a full-scale WRRF. Municipal sewage collection networks transform silver nanoparticles into silver(I)-complexes/precipitates with low ecotoxicity, and preliminary/primary treatment processes in front of biological treatment utilities partially remove silver nanoparticles to sludge. Microbial functional redundancy and microbial adaptability to silver nanoparticles also greatly alleviate the adverse effects of silver nanoparticles on the performance of a full-scale WRRF. Silver nanoparticles in a lab-scale bioreactor without a sewage collection system and/or a preliminary/primary treatment process, in contrast to being in a full scale system, may deteriorate the reactor performance at relatively high concentrations (e.g., mgL^-1 levels or higher). However, in many cases, silver nanoparticles have minimal impacts on lab-scale bioreactors, such as sequencing batch bioreactors (SBRs), especially when at relatively low concentrations (e.g., less than 1mgL^-1). The susceptibility of wastewater microbes to silver nanoparticles is species-specific. In general, silver nanoparticles have higher toxicity towards nitrifying bacteria than heterotrophic bacteria.

In vivo pharmacodynamics of piperacillin/tazobactam: implications for antimicrobial efficacy and resistance suppression with innovator and generic products

Recent studies have shown that the pharmacodynamic (PD) index driving the efficacy of β-lactam/β-lactamase inhibitor combinations such as ceftazidime/avibactam and ceftolozane/tazobactam is the percentage of time the free inhibitor concentration is above a threshold (fT_>threshold). However, data with piperacillin/tazobactam (TZP) are scarce. Here we aimed to assess the relationship between fT_>threshold and TZP antibacterial efficacy by a population pharmacokinetic study in mice and dose-effect experiments in a neutropenic murine thigh infection model with two isogenic strains of Escherichia coli differentially expressing TEM-1 β-lactamase. We also explored the dynamics of resistance selection with the innovator and a non-equivalent generic, extrapolated the results to the clinic by Monte Carlo simulation of standard TZP doses, and estimated the economic impact of generic-selected resistance. The fT_>threshold index described well the efficacy of TZP versus E. coli, with threshold values from 0.5 mg/L to 2 mg/L and mean exposures of 42% for stasis and 56% for 1 log₁₀ kill. The non-equivalent generic required a longer exposure (fT_>threshold 33%) to suppress resistance compared with the innovator (fT_>threshold 22%), leading to a higher frequency of resistance selection in the clinical simulation (16% of patients with the generic vs. 1% with the innovator). Finally, we estimated that use of TZP generics in a scenario of 25% therapeutic non-equivalence would result in extra expenses approaching US$1 billion per year in the USA owing to selection of resistant micro-organisms, greatly offsetting the savings gained from generic substitution and further emphasising the need for demonstrated and not assumed therapeutic equivalence.

Multicopy plasmids potentiate the evolution of antibiotic resistance in bacteria

Plasmids are thought to play a key role in bacterial evolution by acting as vehicles for horizontal gene transfer, but the role of plasmids as catalysts of gene evolution remains unexplored. We challenged populations of Escherichia coli carrying the bla_TEM-1 β-lactamase gene on either the chromosome or a multicopy plasmid (19 copies per cell) with increasing concentrations of ceftazidime. The plasmid accelerated resistance evolution by increasing the rate of appearance of novel TEM-1 mutations, thereby conferring resistance to ceftazidime, and then by amplifying the effect of TEM-1 mutations due to the increased gene dosage. Crucially, this dual effect was necessary and sufficient for the evolution of clinically relevant levels of resistance. Subsequent evolution occurred by mutations in a regulatory RNA that increased the plasmid copy number, resulting in marginal gains in ceftazidime resistance. These results uncover a role for multicopy plasmids as catalysts for the evolution of antibiotic resistance in bacteria.

Low-Concentration Ciprofloxacin Selects Plasmid-Mediated Quinolone Resistance Encoding Genes and Affects Bacterial Taxa in Soil Containing Manure

The spread of antimicrobial resistance in environment is promoted at least in part by the inappropriate use of antibiotics in animals and humans. The present study was designed to investigate the impact of different concentrations of ciprofloxacin in soil containing manure on the development of plasmid-mediated quinolone resistance (PMQR) – encoding genes and the abundance of soil bacterial communities. For these studies, high-throughput next-generation sequencing of 16S rRNA, real-time polymerase chain reaction and standard microbiologic culture methods were utilized. We demonstrated that the dissipate rate of relative abundances of some of PMQR-encoding genes, such as qnrS, oqxA and aac(6^′)-Ib-cr, were significantly lower with ciprofloxacin 0.04 and 0.4 mg/kg exposure as compared to no-ciprofloxacin control and ciprofloxacin 4 mg/kg exposure during 2 month. Also, the number of ciprofloxacin resistant bacteria was significantly greater in ciprofloxacin 0.04 and 0.4 mg/kg exposure as compared with no-ciprofloxacin control and the ciprofloxacin 4 mg/kg exposure. In addition, lower ciprofloxacin concentration provided a selective advantage for the populations of Xanthomonadales and Bacillales in orders while Agrobacterium, Bacillus, Enterococcus, and Burkholderia in genera. These findings suggest that lower concentration of ciprofloxacin resulted in a slower rate of PMQR-encoding genes dissipation and selected development of ciprofloxacin-resistant bacteria in soil amended with manure.

Impact on Bacterial Resistance of Therapeutically Nonequivalent Generics: The Case of Piperacillin-Tazobactam

Previous studies have demonstrated that pharmaceutical equivalence and pharmacokinetic equivalence of generic antibiotics are necessary but not sufficient conditions to guarantee therapeutic equivalence (better called pharmacodynamic equivalence). In addition, there is scientific evidence suggesting a direct link between pharmacodynamic nonequivalence of generic vancomycin and promotion of resistance in Staphylococcus aureus. To find out if even subtle deviations from the expected pharmacodynamic behavior with respect to the innovator could favor resistance, we studied a generic product of piperacillin-tazobactam characterized by pharmaceutical and pharmacokinetic equivalence but a faulty fit of Hill's Emax sigmoid model that could be interpreted as pharmacodynamic nonequivalence. We determined the impact in vivo of this generic product on the resistance of a mixed Escherichia coli population composed of ∼99% susceptible cells (ATCC 35218 strain) and a ∼1% isogenic resistant subpopulation that overproduces TEM-1 β-lactamase. After only 24 hours of treatment in the neutropenic murine thigh infection model, the generic amplified the resistant subpopulation up to 20-times compared with the innovator, following an inverted-U dose-response relationship. These findings highlight the critical role of therapeutic nonequivalence of generic antibiotics as a key factor contributing to the global problem of bacterial resistance.

Does High-Dose Antimicrobial Chemotherapy Prevent the Evolution of Resistance?

High-dose chemotherapy has long been advocated as a means of controlling drug resistance in infectious diseases but recent empirical studies have begun to challenge this view. We develop a very general framework for modeling and understanding resistance emergence based on principles from evolutionary biology. We use this framework to show how high-dose chemotherapy engenders opposing evolutionary processes involving the mutational input of resistant strains and their release from ecological competition. Whether such therapy provides the best approach for controlling resistance therefore depends on the relative strengths of these processes. These opposing processes typically lead to a unimodal relationship between drug pressure and resistance emergence. As a result, the optimal drug dose lies at either end of the therapeutic window of clinically acceptable concentrations. We illustrate our findings with a simple model that shows how a seemingly minor change in parameter values can alter the outcome from one where high-dose chemotherapy is optimal to one where using the smallest clinically effective dose is best. A review of the available empirical evidence provides broad support for these general conclusions. Our analysis opens up treatment options not currently considered as resistance management strategies, and it also simplifies the experiments required to determine the drug doses which best retard resistance emergence in patients.

The evolution of antimicrobial resistant pathogens threatens much of modern medicine. For over one hundred years, the advice has been to ‘hit hard’, in the belief that high doses of antimicrobials best contain resistance evolution. We argue that nothing in evolutionary theory supports this as a good rule of thumb in the situations that challenge medicine. We show instead that the only generality is to either use the highest tolerable drug dose or the lowest clinically effective dose; that is, one of the two edges of the therapeutic window. This approach suggests treatment options not currently considered, and simplifies the experiments required to identify the dose that best retards resistance evolution.

Pervasive selection for and against antibiotic resistance in inhomogeneous multistress environments

Antibiotic-sensitive and -resistant bacteria coexist in natural environments with low, if detectable, antibiotic concentrations. Except possibly around localized antibiotic sources, where resistance can provide a strong advantage, bacterial fitness is dominated by stresses unaffected by resistance to the antibiotic. How do such mixed and heterogeneous conditions influence the selective advantage or disadvantage of antibiotic resistance? Here we find that sub-inhibitory levels of tetracyclines potentiate selection for or against tetracycline resistance around localized sources of almost any toxin or stress. Furthermore, certain stresses generate alternating rings of selection for and against resistance around a localized source of the antibiotic. In these conditions, localized antibiotic sources, even at high strengths, can actually produce a net selection against resistance to the antibiotic. Our results show that interactions between the effects of an antibiotic and other stresses in inhomogeneous environments can generate pervasive, complex patterns of selection both for and against antibiotic resistance.

Antibiotic concentrations are low in most natural environments, except around localized antibiotic sources. Here, Chait et al. show that sub-inhibitory antibiotic levels can interact with many other stresses to generate complex patterns of selection for and against resistance to the antibiotic.

Ecotoxicology, Environmental Risk Assessment and Potential Impact on Human Health

This chapter examines potential risks posed by active pharmaceutical ingredients (APIs) present in the aquatic environment to humans and aquatic life. We begin by describing the mechanisms by which pharmaceuticals enter the vertebrate body, produce effects and leave the body. Then we describe theoretical and practical issues limiting the certainty which can be expected from risk estimates. This is followed by a description of particular considerations applicable to evaluation of human risks, along with a summary of methods and conclusions from some important studies examining those risks. A similar discussion of theoretical issues and selected data relevant for estimating risks to aquatic life is then presented. We finish by discussing potential contributions of antibiotics present in the environment to the development and spread of antibiotic resistance. We conclude that there are too few data to definitively address every concern, particularly risks to aquatic life and contributions to development of antibiotic resistance. On the other hand, available data suggest risks to humans are very low for all active pharmaceutical ingredients (APIs) and risks to aquatic life are very low for most APIs. Although aquatic risks cannot be as confidently ruled out for a few APIs, potential risks are probably limited to particularly contaminated regions in close vicinity to concentrated pollution sources, such as wastewater treatment plant outfalls.

Isolated cell behavior drives the evolution of antibiotic resistance

Bacterial antibiotic resistance is typically quantified by the minimum inhibitory concentration (MIC), which is defined as the minimal concentration of antibiotic that inhibits bacterial growth starting from a standard cell density. However, when antibiotic resistance is mediated by degradation, the collective inactivation of antibiotic by the bacterial population can cause the measured MIC to depend strongly on the initial cell density. In cases where this inoculum effect is strong, the relationship between MIC and bacterial fitness in the antibiotic is not well defined. Here, we demonstrate that the resistance of a single, isolated cell—which we call the single-cell MIC (scMIC)—provides a superior metric for quantifying antibiotic resistance. Unlike the MIC, we find that the scMIC predicts the direction of selection and also specifies the antibiotic concentration at which selection begins to favor new mutants. Understanding the cooperative nature of bacterial growth in antibiotics is therefore essential in predicting the evolution of antibiotic resistance.

The path of least resistance: aggressive or moderate treatment?

The evolution of resistance to antimicrobial chemotherapy is a major and growing cause of human mortality and morbidity. Comparatively little attention has been paid to how different patient treatment strategies shape the evolution of resistance. In particular, it is not clear whether treating individual patients aggressively with high drug dosages and long treatment durations, or moderately with low dosages and short durations can better prevent the evolution and spread of drug resistance. Here, we summarize the very limited available empirical evidence across different pathogens and provide a conceptual framework describing the information required to effectively manage drug pressure to minimize resistance evolution.

Tackling antibiotic resistance: the environmental framework

Antibiotic resistance is a threat to human and animal health worldwide, and key measures are required to reduce the risks posed by antibiotic resistance genes that occur in the environment. These measures include the identification of critical points of control, the development of reliable surveillance and risk assessment procedures, and the implementation of technological solutions that can prevent environmental contamination with antibiotic resistant bacteria and genes. In this Opinion article, we discuss the main knowledge gaps, the future research needs and the policy and management options that should be prioritized to tackle antibiotic resistance in the environment.

Is selection relevant in the evolutionary emergence of drug resistance?

The emergence of drug-resistant pathogens is often considered a canonical case of evolution by natural selection. Here we argue that the strength of selection can be a poor predictor of the rate of resistance emergence. It is possible for a resistant strain to be under negative selection and still emerge in an infection or spread in a population. Measuring the right parameters is a necessary first step toward the development of evidence-based resistance-management strategies. We argue that it is the absolute fitness of the resistant strains that matters most and that a primary determinant of the absolute fitness of a resistant strain is the ecological context in which it finds itself.

Public health evolutionary biology of antimicrobial resistance: priorities for intervention

The three main processes shaping the evolutionary ecology of antibiotic resistance (AbR) involve the emergence, invasion and occupation by antibiotic-resistant genes of significant environments for human health. The process of emergence in complex bacterial populations is a high-frequency, continuous swarming of ephemeral combinatory genetic and epigenetic explorations inside cells and among cells, populations and communities, expanding in different environments (migration), creating the stochastic variation required for evolutionary progress. Invasion refers to the process by which AbR significantly increases in frequency in a given (invaded) environment, led by external invaders local multiplication and spread, or by endogenous conversion. Conversion occurs because of the spread of AbR genes from an exogenous resistant clone into an established (endogenous) bacterial clone(s) colonizing the environment; and/or because of dissemination of particular resistant genetic variants that emerged within an endogenous clonal population. Occupation of a given environment by a resistant variant means a permanent establishment of this organism in this environment, even in the absence of antibiotic selection. Specific interventions on emergence influence invasion, those acting on invasion also influence occupation and interventions on occupation determine emergence. Such interventions should be simultaneously applied, as they are not simple solutions to the complex problem of AbR.

Widening the spaces of selection: evolution along sublethal antimicrobial gradients

The work of Gullberg et al. (E. Gullberg, L. M. Albrecht, C. Karlsson, L. Sandegren, D. I. Andersson, mBio 5:e01918-14, 2014) indicates that extremely low concentrations of antibiotics and heavy metals are able to compensate for the cost of harboring a plasmid encoding resistances to these inhibitors. Therefore, the “spaces of selection” for plasmids encoding antibiotic or metal resistance along gradients of antimicrobial agents might be huge, and in wide spaces a high number of bacterial cells are exposed to the selective effects. These spaces are even broader if several inhibitors are simultaneously present. Probably very small inhibitor concentrations in the environment, including in sewage and other water bodies, are sufficient to ensure the maintenance and spread of this kind of multiresistance plasmid.

Clonal expansion during Staphylococcus aureus infection dynamics reveals the effect of antibiotic intervention

To slow the inexorable rise of antibiotic resistance we must understand how drugs impact on pathogenesis and influence the selection of resistant clones. Staphylococcus aureus is an important human pathogen with populations of antibiotic-resistant bacteria in hospitals and the community. Host phagocytes play a crucial role in controlling S. aureus infection, which can lead to a population "bottleneck" whereby clonal expansion of a small fraction of the initial inoculum founds a systemic infection. Such population dynamics may have important consequences on the effect of antibiotic intervention. Low doses of antibiotics have been shown to affect in vitro growth and the generation of resistant mutants over the long term, however whether this has any in vivo relevance is unknown. In this work, the population dynamics of S. aureus pathogenesis were studied in vivo using antibiotic-resistant strains constructed in an isogenic background, coupled with systemic models of infection in both the mouse and zebrafish embryo. Murine experiments revealed unexpected and complex bacterial population kinetics arising from clonal expansion during infection in particular organs. We subsequently elucidated the effect of antibiotic intervention within the host using mixed inocula of resistant and sensitive bacteria. Sub-curative tetracycline doses support the preferential expansion of resistant microorganisms, importantly unrelated to effects on growth rate or de novo resistance acquisition. This novel phenomenon is generic, occurring with methicillin-resistant S. aureus (MRSA) in the presence of β-lactams and with the unrelated human pathogen Pseudomonas aeruginosa. The selection of resistant clones at low antibiotic levels can result in a rapid increase in their prevalence under conditions that would previously not be thought to favor them. Our results have key implications for the design of effective treatment regimes to limit the spread of antimicrobial resistance, where inappropriate usage leading to resistance may reduce the efficacy of life-saving drugs.

Experimental evolution as an efficient tool to dissect adaptive paths to antibiotic resistance

Antibiotic treatments increasingly fail due to rapid dissemination of drug resistance. Comparative genomics of clinical isolates highlights the role of de novo adaptive mutations and horizontal gene transfer (HGT) in the acquisition of resistance. Yet it cannot fully describe the selective pressures and evolutionary trajectories that yielded today's problematic strains. Experimental evolution offers a compelling addition to such studies because the combination of replicated experiments under tightly controlled conditions with genomics of intermediate time points allows real-time reconstruction of evolutionary trajectories. Recent studies thus established causal links between antibiotic deployment therapies and the course and timing of mutations, the cost of resistance and the likelihood of compensating mutations. They particularly underscored the importance of long-term effects. Similar investigations incorporating horizontal gene transfer (HGT) are wanting, likely because of difficulties associated with its integration into experiments. In this review, we describe current advances in experimental evolution of antibiotic resistance and reflect on ways to incorporate horizontal gene transfer into the approach. We contend it provides a powerful tool for systematic and highly controlled dissection of evolutionary paths to antibiotic resistance that needs to be taken into account for the development of sustainable anti-bacterial treatment strategies.

Optimization of antibiotic dosing schedules in the light of increasing antibiotic resistance

The development of antibiotic-resistant bacteria is an increasing problem throughout the world and is, without doubt, due to the increasing use of antibiotics themselves. As organisms become more resistant, treatment options become more limited and treatment failures increasingly likely. The need to reverse, or at least minimize this pattern of increasing resistance is therefore essential. Numerous strategies to achieve this have been postulated and there is no doubt that a combination of these will ultimately prove to be most effective. Among them, using antibiotic dosing regimens that may be less likely to promote resistance is one measure which could be beneficial, and this will be the focus of this review. Individual antibiotics will be discussed under the headings of the patterns of killing activity that they produce. Namely whether they exhibit concentration-dependent killing with prolonged persistent effects, time-dependent killing with minimal or no persistent effects, or time-dependent killing with prolonged persistent effects. The available evidence for optimal dosing regimens, as far as minimizing antibiotic resistance is concerned, will be reviewed. Where possible, recommendations relating to clinical practice will be made, or failing that, an indication of where further research would be of benefit.

Antibiotic resistance shaping multi-level population biology of bacteria

Antibiotics have natural functions, mostly involving cell-to-cell signaling networks. The anthropogenic production of antibiotics, and its release in the microbiosphere results in a disturbance of these networks, antibiotic resistance tending to preserve its integrity. The cost of such adaptation is the emergence and dissemination of antibiotic resistance genes, and of all genetic and cellular vehicles in which these genes are located. Selection of the combinations of the different evolutionary units (genes, integrons, transposons, plasmids, cells, communities and microbiomes, hosts) is highly asymmetrical. Each unit of selection is a self-interested entity, exploiting the higher hierarchical unit for its own benefit, but in doing so the higher hierarchical unit might acquire critical traits for its spread because of the exploitation of the lower hierarchical unit. This interactive trade-off shapes the population biology of antibiotic resistance, a composed-complex array of the independent "population biologies." Antibiotics modify the abundance and the interactive field of each of these units. Antibiotics increase the number and evolvability of "clinical" antibiotic resistance genes, but probably also many other genes with different primary functions but with a resistance phenotype present in the environmental resistome. Antibiotics influence the abundance, modularity, and spread of integrons, transposons, and plasmids, mostly acting on structures present before the antibiotic era. Antibiotics enrich particular bacterial lineages and clones and contribute to local clonalization processes. Antibiotics amplify particular genetic exchange communities sharing antibiotic resistance genes and platforms within microbiomes. In particular human or animal hosts, the microbiomic composition might facilitate the interactions between evolutionary units involved in antibiotic resistance. The understanding of antibiotic resistance implies expanding our knowledge on multi-level population biology of bacteria.

The Inactivation of intrinsic antibiotic resistance determinants widens the mutant selection window for quinolones in Stenotrophomonas maltophilia

We have determined that the mutational inactivation of the SmeDEF efflux pump and the SmQnr quinolone resistance protein widens the mutant selection windows for ofloxacin and ciprofloxacin of Stenotrophomonas maltophilia by reducing their MICs. Resistant mutants arising from a strain lacking SmeDEF and SmQnr presented levels of susceptibility similar to those of the wild-type strain. This indicates that inactivation of intrinsic resistance determinants might increase the chances for selecting resistant mutants at low antibiotic concentrations.

Quantifying the adaptive potential of an antibiotic resistance enzyme

For a quantitative understanding of the process of adaptation, we need to understand its "raw material," that is, the frequency and fitness effects of beneficial mutations. At present, most empirical evidence suggests an exponential distribution of fitness effects of beneficial mutations, as predicted for Gumbel-domain distributions by extreme value theory. Here, we study the distribution of mutation effects on cefotaxime (Ctx) resistance and fitness of 48 unique beneficial mutations in the bacterial enzyme TEM-1 β-lactamase, which were obtained by screening the products of random mutagenesis for increased Ctx resistance. Our contributions are threefold. First, based on the frequency of unique mutations among more than 300 sequenced isolates and correcting for mutation bias, we conservatively estimate that the total number of first-step mutations that increase Ctx resistance in this enzyme is 87 [95% CI 75-189], or 3.4% of all 2,583 possible base-pair substitutions. Of the 48 mutations, 10 are synonymous and the majority of the 38 non-synonymous mutations occur in the pocket surrounding the catalytic site. Second, we estimate the effects of the mutations on Ctx resistance by determining survival at various Ctx concentrations, and we derive their fitness effects by modeling reproduction and survival as a branching process. Third, we find that the distribution of both measures follows a Fréchet-type distribution characterized by a broad tail of a few exceptionally fit mutants. Such distributions have fundamental evolutionary implications, including an increased predictability of evolution, and may provide a partial explanation for recent observations of striking parallel evolution of antibiotic resistance.