Toward a quantitative understanding of antibiotic resistance evolution

Companion Animal Owners' Knowledge, Attitudes and Perceptions Regarding Antibiotic Use in Portugal

While multiple studies have focused on the motivations surrounding antibiotic prescription among veterinarians, little is known about companion animal owners' knowledge, attitude and perception (KAP) regarding the topic. A nationwide survey directed toward Portuguese dog and cat owners was conducted online and at veterinary practices to characterize their KAP regarding antibiotics. After database curation, a total of 423 valid submissions were considered. Although 97.9% of respondents stated that they knew what an antibiotic was, 23.5% and 19.2% answered that they were used to treat viral and fungal infections, respectively. Antimicrobial effectiveness was favored over cost when 87.7% of owners agreed they would prefer to spend more money to identify the appropriate antibiotic. Around 87% of respondents recognized antibiotic resistance as a significant health problem and 74.6% strongly agreed/somewhat agreed that antibiotic use in pets may contribute to resistance development. However, only 25.3% recognized that this could promote resistance dissemination, showing little awareness of the interconnection between human and animal health. Moreover, 55.6% of respondents were neutral when asked whether antibiotics used in veterinary medicine were also important for humans. These findings suggest that communication between veterinarians and pet owners can still be improved to further clarify the impact that antibiotic use has in pets from a One-Health perspective, also enabling antimicrobial stewardship interventions.

Methyl halide transferase-based gas reporters for quantification of filamentous bacteria in microdroplet emulsions

The application of microfluidic techniques in experimental and environmental studies is a rapidly emerging field. Water-in-oil microdroplets can serve readily as controllable micro-vessels for studies that require spatial structure. In many applications, it is useful to monitor cell growth without breaking or disrupting the microdroplets. To this end, optical reporters based on color, fluorescence, or luminescence have been developed. However, optical reporters suffer from limitations when used in microdroplets such as inaccurate readings due to strong background interference or limited sensitivity during early growth stages. In addition, optical detection is typically not amenable to filamentous or biofilm-producing organisms that have significant nonlinear changes in opacity and light scattering during growth. To overcome such limitations, we show that volatile methyl halide gases produced by reporter cells expressing a methyl halide transferase (MHT) can serve as an alternative nonoptical detection approach suitable for microdroplets. In this study, an MHT-labeled Streptomyces venezuelae reporter strain was constructed and characterized. Protocols were established for the encapsulation and incubation of S. venezuelae in microdroplets. We observed the complete life cycle for S. venezuelae including the vegetative expansion of mycelia, mycelial fragmentation, and late-stage sporulation. Methyl bromide (MeBr) production was detected by gas chromatography-mass spectrometry (GC-MS) from S. venezuelae gas reporters incubated in either liquid suspension or microdroplets and used to quantitatively estimate bacterial density. Overall, using MeBr production as a means of quantifying bacterial growth provided a 100- to 1,000-fold increase in sensitivity over optical or fluorescence measurements of a comparable reporter strain expressing fluorescent proteins. IMPORTANCE Quantitative measurement of bacterial growth in microdroplets in situ is desirable but challenging. Current optical reporter systems suffer from limitations when applied to filamentous or biofilm-producing organisms. In this study, we demonstrate that volatile methyl halide gas production can serve as a quantitative nonoptical growth assay for filamentous bacteria encapsulated in microdroplets. We constructed an S. venezuelae gas reporter strain and observed a complete life cycle for encapsulated S. venezuelae in microdroplets, establishing microdroplets as an alternative growth environment for Streptomyces spp. that can provide spatial structure. We detected MeBr production from both liquid suspension and microdroplets with a 100- to 1,000-fold increase in signal-to-noise ratio compared to optical assays. Importantly, we could reliably detect bacteria with densities down to 106 CFU/mL. The combination of quantitative gas reporting and microdroplet systems provides a valuable approach to studying fastidious organisms that require spatial structure such as those found typically in soils.

Epistasis decreases with increasing antibiotic pressure but not temperature

Predicting mutational effects is essential for the control of antibiotic resistance (ABR). Predictions are difficult when there are strong genotype-by-environment (G × E), gene-by-gene (G × G or epistatic) or gene-by-gene-by-environment (G × G × E) interactions. We quantified G × G × E effects in Escherichia coli across environmental gradients. We created intergenic fitness landscapes using gene knock-outs and single-nucleotide ABR mutations previously identified to vary in the extent of G × E effects in our environments of interest. Then, we measured competitive fitness across a complete combinatorial set of temperature and antibiotic dosage gradients. In this way, we assessed the predictability of 15 fitness landscapes across 12 different but related environments. We found G × G interactions and rugged fitness landscapes in the absence of antibiotic, but as antibiotic concentration increased, the fitness effects of ABR genotypes quickly overshadowed those of gene knock-outs, and the landscapes became smoother. Our work reiterates that some single mutants, like those conferring resistance or susceptibility to antibiotics, have consistent effects across genetic backgrounds in stressful environments. Thus, although epistasis may reduce the predictability of evolution in benign environments, evolution may be more predictable in adverse environments. This article is part of the theme issue 'Interdisciplinary approaches to predicting evolutionary biology'.

Identification of Evolutionary Trajectories Associated with Antimicrobial Resistance Using Microfluidics

In vitro experimental evolution of pathogens to antibiotics is commonly used for the identification of clinical biomarkers associated with antibiotic resistance. Microdroplet emulsions allow exquisite control of spatial structure, species complexity, and selection microenvironments for such studies. We investigated the use of monodisperse microdroplets in experimental evolution. Using Escherichia coli adaptation to doxycycline, we examined how changes in environmental conditions such as droplet size, starting lambda value, selection strength, and incubation method affected evolutionary outcomes. We also examined the extent to which emulsions could reveal potentially new evolutionary trajectories and dynamics associated with antimicrobial resistance. Interestingly, we identified both expected and unexpected evolutionary trajectories including large-scale chromosomal rearrangements and amplification that were not observed in suspension culture methods. As microdroplet emulsions are well-suited for automation and provide exceptional control of conditions, they can provide a high-throughput approach for biomarker identification as well as preclinical evaluation of lead compounds.

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.

Forecasting of phenotypic and genetic outcomes of experimental evolution in Pseudomonas protegens

Experimental evolution with microbes is often highly repeatable under identical conditions, suggesting the possibility to predict short-term evolution. However, it is not clear to what degree evolutionary forecasts can be extended to related species in non-identical environments, which would allow testing of general predictive models and fundamental biological assumptions. To develop an extended model system for evolutionary forecasting, we used previous data and models of the genotype-to-phenotype map from the wrinkly spreader system in Pseudomonas fluorescens SBW25 to make predictions of evolutionary outcomes on different biological levels for Pseudomonas protegens Pf-5. In addition to sequence divergence (78% amino acid and 81% nucleotide identity) for the genes targeted by mutations, these species also differ in the inability of Pf-5 to make cellulose, which is the main structural basis for the adaptive phenotype in SBW25. The experimental conditions were changed compared to the SBW25 system to test if forecasts were extendable to a non-identical environment. Forty-three mutants with increased ability to colonize the air-liquid interface were isolated, and the majority had reduced motility and was partly dependent on the Pel exopolysaccharide as a structural component. Most (38/43) mutations are expected to disrupt negative regulation of the same three diguanylate cyclases as in SBW25, with a smaller number of mutations in promoter regions, including an uncharacterized polysaccharide synthase operon. A mathematical model developed for SBW25 predicted the order of the three main pathways and the genes targeted by mutations, but differences in fitness between mutants and mutational biases also appear to influence outcomes. Mutated regions in proteins could be predicted in most cases (16/22), but parallelism at the nucleotide level was low and mutational hot spot sites were not conserved. This study demonstrates the potential of short-term evolutionary forecasting in experimental populations and provides testable predictions for evolutionary outcomes in other Pseudomonas species.

Multi-scale Predictions of Drug Resistance Epidemiology Identify Design Principles for Rational Drug Design

Rationally designing drugs that last longer in the face of biological evolution is a critical objective of drug discovery. However, this goal is thwarted by the diversity and stochasticity of evolutionary trajectories that drive uncertainty in the clinic. Although biophysical models can qualitatively predict whether a mutation causes resistance, they cannot quantitatively predict the relative abundance of resistance mutations in patient populations. We present stochastic, first-principle models that are parameterized on a large in vitro dataset and that accurately predict the epidemiological abundance of resistance mutations across multiple leukemia clinical trials. The ability to forecast resistance variants requires an understanding of their underlying mutation biases. Beyond leukemia, a meta-analysis across prostate cancer, breast cancer, and gastrointestinal stromal tumors suggests that resistance evolution in the adjuvant setting is influenced by mutational bias. Our analysis establishes a principle for rational drug design: when evolution favors the most probable mutant, so should drug design.

Drug resistance is often addressed through next-generation drug design, but evolutionary diversity complicates these efforts. Here, Leighow et al. demonstrate that multi-scale models can quantitatively predict mutant frequency. We find that when heterogeneity is limited, analysis requires an understanding of substitution likelihood. We show that these models can inform evolutionarily optimized drug design.

Genome-Wide Analysis of Experimentally Evolved Candida auris Reveals Multiple Novel Mechanisms of Multidrug Resistance

Candida auris is globally recognized as an opportunistic fungal pathogen of high concern, due to its extensive multidrug resistance (MDR). Still, molecular mechanisms of MDR are largely unexplored. This is the first account of genome-wide evolution of MDR in C. auris obtained through serial in vitro exposure to azoles, polyenes, and echinocandins. We show the stepwise accumulation of copy number variations and novel mutations in genes both known and unknown in antifungal drug resistance. Echinocandin resistance was accompanied by a codon deletion in FKS1 hot spot 1 and a substitution in FKS1 "novel" hot spot 3. Mutations in ERG3 and CIS2 further increased the echinocandin MIC. Decreased azole susceptibility was linked to a mutation in transcription factor TAC1b and overexpression of the drug efflux pump Cdr1, a segmental duplication of chromosome 1 containing ERG11, and a whole chromosome 5 duplication, which contains TAC1b The latter was associated with increased expression of ERG11, TAC1b, and CDR2 but not CDR1 The simultaneous emergence of nonsense mutations in ERG3 and ERG11 was shown to decrease amphotericin B susceptibility, accompanied with fluconazole cross-resistance. A mutation in MEC3, a gene mainly known for its role in DNA damage homeostasis, further increased the polyene MIC. Overall, this study shows the alarming potential for and diversity of MDR development in C. auris, even in a clade until now not associated with MDR (clade II), stressing its clinical importance and the urge for future research.IMPORTANCECandida auris is a recently discovered human fungal pathogen and has shown an alarming potential for developing multi- and pan-resistance toward all classes of antifungals most commonly used in the clinic. Currently, C. auris has been globally recognized as a nosocomial pathogen of high concern due to this evolutionary potential. So far, this is the first study in which the stepwise progression of multidrug resistance (MDR) in C. auris is monitored in vitro Multiple novel mutations in known resistance genes and genes previously not or vaguely associated with drug resistance reveal rapid MDR evolution in a C. auris clade II isolate. Additionally, this study shows that in vitro experimental evolution can be a powerful tool to discover new drug resistance mechanisms, although it has its limitations.

Microscopic Analysis of Bacterial Inoculum Effect Using Micropatterned Biochip

Antimicrobial resistance has become a major problem in public health and clinical environments. Against this background, antibiotic susceptibility testing (AST) has become necessary to cure diseases in an appropriate and timely manner as it indicates the necessary concentration of antibiotics. Recently, microfluidic based rapid AST methods using microscopic analysis have been shown to reduce the time needed for the determination of the proper antibiotics. However, owing to the inoculum effect, the accurate measurement of the minimal inhibitory concentration (MIC) is difficult. We tested four standard bacteria: Staphylococcus aureus, Pseudomonas aeruginosa, Escherichia coli, and Enterococcus faecalis, against five different antibiotics: piperacillin, cefotaxime, amikacin, levofloxacin, and ampicillin. The results showed that overall, the microfluidic system has a similar inoculum effect compared to the conventional AST method. However, due to the different testing conditions and determination protocols of the growth of the microfluidic based rapid AST, a few results are not identical to the conventional methods using optical density. This result suggests that microfluidic based rapid AST methods require further research on the inoculum effect for practical use in hospitals and can then be used for effective antibiotic prescriptions.

Polyphenol Rich Sugar Cane Extract Inhibits Bacterial Growth

Plants that are primarily used as a food source commonly have undervalued biological properties beyond the basic supply of nutrients. One important example of this are the antimicrobial properties of plants. Inclusion of natural and food grade antimicrobial ingredients in recipes to prevent food spoilage and disease transmission, or in cosmetic products to prevent transient and pathogenic bacteria would have world-wide public health implications. A patented natural polyphenol rich sugar cane extract (PRSE), is marketed as a high anti-oxidant and polyphenol ingredient, but its anti-microbial activity has not been reported previously. We determined the anti-bacterial properties of PRSE on common human pathogens relating to a range of diseases including food poisoning, tooth decay, acne and severe skin infections using disc/well diffusion experiments. Our findings indicate that PRSE is an efficient antimicrobial, which could be included at differing dosages to target a range of food borne and environmental pathogens.

Mechanisms and phenotypic consequences of acquisition of tigecycline resistance by Stenotrophomonas maltophilia

OBJECTIVES

To elucidate the potential mutation-driven mechanisms involved in the acquisition of tigecycline resistance by the opportunistic pathogen Stenotrophomonas maltophilia. The mutational trajectories and their effects on bacterial fitness, as well as cross-resistance and/or collateral susceptibility to other antibiotics, were also addressed.

METHODS

S. maltophilia populations were submitted to experimental evolution in the presence of increasing concentrations of tigecycline for 30 days. The genetic mechanisms involved in the acquisition of tigecycline resistance were determined by WGS. Resistance was evaluated by performing MIC assays. Fitness of the evolved populations and individual clones was assessed by measurement of the maximum growth rates.

RESULTS

All the tigecycline-evolved populations attained high-level resistance to tigecycline following different mutational trajectories, yet with some common elements. Among the mechanisms involved in low susceptibility to tigecycline, mutations in the SmeDEF efflux pump negative regulator smeT, changes in proteins involved in the biogenesis of the ribosome and modifications in the LPS biosynthesis pathway seem to play a major role. Besides tigecycline resistance, the evolved populations presented cross-resistance to other antibiotics, such as aztreonam and quinolones, and they were hypersusceptible to fosfomycin, suggesting a possible combination treatment. Further, we found that the selected resistance mechanisms impose a relevant fitness cost when bacteria grow in the absence of antibiotic.

CONCLUSIONS

Mutational resistance to tigecycline was easily selected during exposure to this antibiotic. However, the fitness cost may compromise the maintenance of S. maltophilia tigecycline-resistant populations in the absence of antibiotic.

A Roadblock-and-Kill Mechanism of Action Model for the DNA-Targeting Antibiotic Ciprofloxacin

Fluoroquinolones, antibiotics that cause DNA damage by inhibiting DNA topoisomerases, are clinically important, but their mechanism of action is not yet fully understood. In particular, the dynamical response of bacterial cells to fluoroquinolone exposure has hardly been investigated, although the SOS response, triggered by DNA damage, is often thought to play a key role. Here, we investigated the growth inhibition of the bacterium Escherichia coli by the fluoroquinolone ciprofloxacin at low concentrations. We measured the long-term and short-term dynamical response of the growth rate and DNA production rate to ciprofloxacin at both the population and single-cell levels. We show that, despite the molecular complexity of DNA metabolism, a simple roadblock-and-kill model focusing on replication fork blockage and DNA damage by ciprofloxacin-poisoned DNA topoisomerase II (gyrase) quantitatively reproduces long-term growth rates in the presence of ciprofloxacin. The model also predicts dynamical changes in the DNA production rate in wild-type E. coli and in a recombination-deficient mutant following a step-up of ciprofloxacin. Our work highlights that bacterial cells show a delayed growth rate response following fluoroquinolone exposure. Most importantly, our model explains why the response is delayed: it takes many doubling times to fragment the DNA sufficiently to inhibit gene expression. We also show that the dynamical response is controlled by the timescale of DNA replication and gyrase binding/unbinding to the DNA rather than by the SOS response, challenging the accepted view. Our work highlights the importance of including detailed biophysical processes in biochemical-systems models to quantitatively predict the bacterial response to antibiotics.

Highly parallel lab evolution reveals that epistasis can curb the evolution of antibiotic resistance

Genetic perturbations that affect bacterial resistance to antibiotics have been characterized genome-wide, but how do such perturbations interact with subsequent evolutionary adaptation to the drug? Here, we show that strong epistasis between resistance mutations and systematically identified genes can be exploited to control spontaneous resistance evolution. We evolved hundreds of Escherichia coli K-12 mutant populations in parallel, using a robotic platform that tightly controls population size and selection pressure. We find a global diminishing-returns epistasis pattern: strains that are initially more sensitive generally undergo larger resistance gains. However, some gene deletion strains deviate from this general trend and curtail the evolvability of resistance, including deletions of genes for membrane transport, LPS biosynthesis, and chaperones. Deletions of efflux pump genes force evolution on inferior mutational paths, not explored in the wild type, and some of these essentially block resistance evolution. This effect is due to strong negative epistasis with resistance mutations. The identified genes and cellular functions provide potential targets for development of adjuvants that may block spontaneous resistance evolution when combined with antibiotics.

Phenotypic delay in the evolution of bacterial antibiotic resistance: Mechanistic models and their implications

Phenotypic delay-the time delay between genetic mutation and expression of the corresponding phenotype-is generally neglected in evolutionary models, yet recent work suggests that it may be more common than previously assumed. Here, we use computer simulations and theory to investigate the significance of phenotypic delay for the evolution of bacterial resistance to antibiotics. We consider three mechanisms which could potentially cause phenotypic delay: effective polyploidy, dilution of antibiotic-sensitive molecules and accumulation of resistance-enhancing molecules. We find that the accumulation of resistant molecules is relevant only within a narrow parameter range, but both the dilution of sensitive molecules and effective polyploidy can cause phenotypic delay over a wide range of parameters. We further investigate whether these mechanisms could affect population survival under drug treatment and thereby explain observed discrepancies in mutation rates estimated by Luria-Delbrück fluctuation tests. While the effective polyploidy mechanism does not affect population survival, the dilution of sensitive molecules leads both to decreased probability of survival under drug treatment and underestimation of mutation rates in fluctuation tests. The dilution mechanism also changes the shape of the Luria-Delbrück distribution of mutant numbers, and we show that this modified distribution provides an improved fit to previously published experimental data.

Resistance Evolution Against Antimicrobial Peptides in Staphylococcus aureus Alters Pharmacodynamics Beyond the MIC

Antimicrobial peptides (AMPs) have been proposed as a promising class of new antimicrobials partly because they are less susceptible to bacterial resistance evolution. This is possibly caused by their mode of action but also by their pharmacodynamic characteristics, which differ significantly from conventional antibiotics. Although pharmacodynamics of antibiotic resistant strains have been studied, such data are lacking for AMP resistant strains. Here, we investigated if the pharmacodynamics of the Gram-positive human pathogen Staphylococcous aureus evolve under antimicrobial peptide selection. Interestingly, the Hill coefficient (kappa κ) evolves together with the minimum inhibition concentration (MIC). Except for one genotype, strains harboring mutations in menF and atl, all mutants had higher kappa than the non-selected sensitive controls. Higher κ results in steeper pharmacodynamic curve and, importantly, in a narrower mutant selection window. S. aureus selected for resistance to melittin displayed cross resistant against pexiganan and had as steep pharmacodynamic curves (high κ) as pexiganan-selected lines. By contrast, the pexiganan-sensitive tenecin-selected lines displayed lower κ. Taken together, our data demonstrate that pharmacodynamic parameters are not fixed traits of particular drug/strain interactions but actually evolve under drug treatment. The contribution of factors such as κ and the maximum and minimum growth rates on the dynamics and probability of resistance evolution are open questions that require urgent attention.

The effect of spatiotemporal antibiotic inhomogeneities on the evolution of resistance

Combating the evolution of widespread antibiotic resistance is one of the most pressing challenges facing modern medicine. Recent research has demonstrated that the evolution of pathogens with high levels of resistance can be accelerated by spatial and temporal inhomogeneities in antibiotic concentration, which frequently arise in patients and the environment. Strategies to predict and counteract the effects of such inhomogeneities will be critical in the fight against resistance. In this paper we develop a mechanistic framework for modelling the adaptive evolution of resistance in the presence of spatiotemporal antibiotic concentrations, which treats the adaptive process as an interaction between two mutually orthogonal forces; the first returns cells to their wild-type state in the absence of antibiotic selection, and the second selects for increased coping ability in the presence of an antibiotic. We apply our model to investigate laboratory adaptation experiments, and then extend it to consider the case in which multiple strategies for resistance undergo competitive evolution.

Changes in the Carbon Metabolism of Escherichia coli During the Evolution of Doxycycline Resistance

Despite our continuous improvement in understanding the evolution of antibiotic resistance, the changes in the carbon metabolism during the evolution of antibiotic resistance remains unclear. To investigate the evolution of antibiotic resistance and the changes in carbon metabolism under antibiotic pressure, Escherichia coli K-12 was evolved for 38 passages under a concentration gradient of doxycycline (DOX). The 0th-passage sensitive strain W0, the 20th-passage moderately resistant strain M20, and the 38th-passage highly resistant strain E38 were selected for the determination of biofilm formation, colony area, and carbon metabolism levels, as well as genome and transcriptome sequencing. The MIC of DOX with E. coli significantly increased from 4 to 96 μg/ml, and the IC₅₀ increased from 2.18 ± 0.08 to 64.79 ± 0.75 μg/ml after 38 passages of domestication. Compared with the sensitive strain W0, the biofilm formation amount of the resistant strains M20 and E38 was significantly increased (p < 0.05). Single-nucleotide polymorphisms (SNPs) were distributed in antibiotic resistance-related genes such as ribosome targets, cell membranes, and multiple efflux pumps. In addition, there were no mutated genes related to carbon metabolism. However, the genes involved in the biosynthesis of secondary metabolites and carbon metabolism pathway were downregulated, showing a significant decrease in the metabolic intensity of 23 carbon sources (p < 0.05). The results presented here show that there may be a correlation between the evolution of E. coli DOX resistance and the decrease of carbon metabolism, and the mechanism was worthy of further research, providing a theoretical basis for the prevention and control of microbial resistance.

Engineered Graphene Oxide Nanocomposite Capable of Preventing the Evolution of Antimicrobial Resistance

Antimicrobial resistance (AMR) is spreading worldwide and keeps evolving to adapt to antibiotics, causing increasing threats in clinics, which necessitates the exploration of antimicrobial agents for not only killing of resistant cells but also prevention of AMR progression. However, so far, there has been no effective approach. Herein, we designed lanthanum hydroxide and graphene oxide nanocomposites (La@GO) to confer a synergistic bactericidal effect in all tested resistant strains. More importantly, long-term exposure of E. coli (AMR) to subminimum inhibitory concentrations of La@GO does not trigger detectable secondary resistance, while conventional antibiotics and silver nanoparticles lead to a 16- to 64-fold increase in tolerance. The inability of E. coli to evolve resistance to La@GO is likely due to a distinctive extracellular multitarget invasion killing mechanism involving lipid dephosphorylation, lipid peroxidation, and peptidoglycan disruption. Overall, our results highlight La@GO nanocomposites as a promising solution to combating resistant bacteria without inducing the evolution of AMR.

Learning the pattern of epistasis linking genotype and phenotype in a protein

Understanding the pattern of epistasis-the non-independence of mutations-is critical for relating genotype and phenotype. However, the combinatorial complexity of potential epistatic interactions has severely limited the analysis of this problem. Using new mutational approaches, we report a comprehensive experimental study of all 2¹³ mutants that link two phenotypically distinct variants of the Entacmaea quadricolor fluorescent protein-an opportunity to examine epistasis up to the 13^th order. The data show the existence of many high-order epistatic interactions between mutations, but also reveal extraordinary sparsity, enabling novel experimental and computational strategies for learning the relevant epistasis. We demonstrate that such information, in turn, can be used to accurately predict phenotypes in practical situations where the number of measurements is limited. Finally, we show how the observed epistasis shapes the solution space of single-mutation trajectories between the parental fluorescent proteins, informative about the protein's evolutionary potential. This work provides conceptual and experimental strategies to profoundly characterize epistasis in a protein, relevant to both natural and laboratory evolution.

Growth-dependent drug susceptibility can prevent or enhance spatial expansion of a bacterial population

As a population wave expands, organisms at the tip typically experience plentiful nutrients while those behind the front become nutrient-depleted. If the environment also contains a gradient of some inhibitor (e.g. a toxic drug), a tradeoff exists: the nutrient-rich tip is more exposed to the inhibitor, while the nutrient-starved region behind the front is less exposed. Here we show that this can lead to complex dynamics when the organism's response to the inhibitory substance is coupled to nutrient availability. We model a bacterial population which expands in a spatial gradient of antibiotic, under conditions where either fast-growing bacteria at the wave's tip, or slow-growing, resource-limited bacteria behind the front are more susceptible to the antibiotic. We find that growth-rate dependent susceptibility can have strong effects on the dynamics of the expanding population. If slow-growing bacteria are more susceptible, the population wave advances far into the inhibitory zone, leaving a trail of dead bacteria in its wake. In contrast, if fast-growing bacteria are more susceptible, the wave is blocked at a much lower concentration of antibiotic, but a large population of live bacteria remains behind the front. Our results may contribute to understanding the efficacy of different antimicrobials for spatially structured microbial populations such as biofilms, as well as the dynamics of ecological population expansions more generally.

Continuous culture of Escherichia coli, under selective pressure by a novel antimicrobial complex, does not result in development of resistance

We attempted to generate de novo resistance to a newly described biocidal complex, ITC (iodo-thiocyanate complex), and to levofloxacin (LVX) in Escherichia coli ATCC 25922, by means of selective chemostat culture. We measured resistance by determining the minimum inhibitory concentrations (MICs) for these agents. E. coli underwent 20-day parallel adaptive evolution routes under no antimicrobial selection, and gradually increasing ITC and LVX selection pressure. Long-term exposure of E. coli to ITC did not induce resistance to ITC, or cross-resistance to LVX. No distinct mutational pattern was evidenced from whole-genome sequence (WGS)-based comparisons of ITC-challenged and unchallenged bacterial populations. Moreover, the exposed E. coli population could not survive a 2 × MIC challenge of ITC. By contrast, resistance to LVX was rapidly induced (on day 1 the MIC had increased 16-fold), selected for (by day 14 the MIC had increased 64-fold) and enriched with a highly characteristic genome mutational pattern. WGS of this evolving population revealed that the majority of mutations appeared in the genes of LVX target proteins (GyrA, ParC, ParE) and drug influx (OmpF). This study suggests that the usage of ITC may not trigger the emergence of facile resistance or cross-resistance, in contrast to common antibiotics.

Multiscale Evolutionary Dynamics of Host-Associated Microbiomes

The composite members of the microbiota face a range of selective pressures and must adapt to persist in the host. We highlight recent work characterizing the evolution and transfer of genetic information across nested scales of host-associated microbiota, which enable resilience to biotic and abiotic perturbations. At the strain level, we consider the preservation and diversification of adaptive information in progeny lineages. At the community level, we consider genetic exchange between distinct microbes in the ecosystem. Finally, we frame microbiomes as open systems subject to acquisition of novel information from foreign ecosystems through invasion by outsider microbes.

Microfluidic screening of antibiotic susceptibility at a single-cell level shows the inoculum effect of cefotaxime on E. coli

Measurement of antibiotic susceptibility at the level of single cells is important as it reveals the concentration of an antibiotic that leads to drug resistance in bacterial strains. To date, no solution for large-scale studies of antibiotic susceptibility at the single-cell level has been shown. Here, we present a method for production and separation of emulsions consisting of subnanoliter droplets that allows us to identify each emulsion by their spatial position in the train of emulsions without chemical barcoding. The emulsions of droplets are separated by a third immiscible phase, thus forming large compartments-tankers-each filled with an emulsion of droplet reactors. Each tanker in a train can be set under different reaction conditions for hundreds or thousands of replications of the same reaction. The tankers allow for long term incubation - needed to check for growth of bacteria under a screen of conditions. We use microfluidic tankers to analyze susceptibility to cefotaxime in ca. 1900 replications for each concentration of the antibiotic in one experiment. We test cefotaxime susceptibility for different initial concentrations of bacteria, showing the inoculum effect down to the level of single cells for more than a hundred single-cell events per tanker. Lastly, we use tankers to observe the formation of aggregates of bacteria in the presence of cefotaxime in the increasing concentration of the antibiotic. The microfluidic tankers allow for facile studies of the inoculum effect and antibiotic susceptibility, and constitute an attractive, label-free screening method for a variety of other experiments in chemistry and biology.

Parallel Evolution of High-Level Aminoglycoside Resistance in Escherichia coli Under Low and High Mutation Supply Rates

Antibiotic resistance is a major concern in public health worldwide, thus there is much interest in characterizing the mutational pathways through which susceptible bacteria evolve resistance. Here we use experimental evolution to explore the mutational pathways toward aminoglycoside resistance, using gentamicin as a model, under low and high mutation supply rates. Our results show that both normo and hypermutable strains of Escherichia coli are able to develop resistance to drug dosages > 1,000-fold higher than the minimal inhibitory concentration for their ancestors. Interestingly, such level of resistance was often associated with changes in susceptibility to other antibiotics, most prominently with increased resistance to fosfomycin. Whole-genome sequencing revealed that all resistant derivatives presented diverse mutations in five common genetic elements: fhuA, fusA and the atpIBEFHAGDC, cyoABCDE, and potABCD operons. Despite the large number of mutations acquired, hypermutable strains did not pay, apparently, fitness cost. In contrast to recent studies, we found that the mutation supply rate mainly affected the speed (tempo) but not the pattern (mode) of evolution: both backgrounds acquired the mutations in the same order, although the hypermutator strain did it faster. This observation is compatible with the adaptive landscape for high-level gentamicin resistance being relatively smooth, with few local maxima; which might be a common feature among antibiotics for which resistance involves multiple loci.

Whole-genome sequencing reveals the mechanisms for evolution of streptomycin resistance in Lactobacillus plantarum

In this research, we investigated the evolution of streptomycin resistance in Lactobacillus plantarum ATCC14917, which was passaged in medium containing a gradually increasing concentration of streptomycin. After 25 d, the minimum inhibitory concentration (MIC) of L. plantarum ATCC14917 had reached 131,072 µg/mL, which was 8,192-fold higher than the MIC of the original parent isolate. The highly resistant L. plantarum ATCC14917 isolate was then passaged in antibiotic-free medium to determine the stability of resistance. The MIC value of the L. plantarum ATCC14917 isolate decreased to 2,048 µg/mL after 35 d but remained constant thereafter, indicating that resistance was irreversible even in the absence of selection pressure. Whole-genome sequencing of parent isolates, control isolates, and isolates following passage was used to study the resistance mechanism of L. plantarum ATCC14917 to streptomycin and adaptation in the presence and absence of selection pressure. Five mutated genes (single nucleotide polymorphisms and structural variants) were verified in highly resistant L. plantarum ATCC14917 isolates, which were related to ribosomal protein S12, LPXTG-motif cell wall anchor domain protein, LrgA family protein, Ser/Thr phosphatase family protein, and a hypothetical protein that may correlate with resistance to streptomycin. After passage in streptomycin-free medium, only the mutant gene encoding ribosomal protein S12 remained; the other 4 mutant genes had reverted to the wild type as found in the parent isolate. Although the MIC value of L. plantarum ATCC14917 was reduced in the absence of selection pressure, it remained 128-fold higher than the MIC value of the parent isolate, indicating that ribosomal protein S12 may play an important role in streptomycin resistance. Using the mobile elements database, we demonstrated that streptomycin resistance-related genes in L. plantarum ATCC14917 were not located on mobile elements. This research offers a way of combining laboratory evolution techniques and whole-genome sequencing for evaluating antibiotic resistance in probiotics.

Recombinant yeast and human cells as screening tools to search for antibacterial agents targeting the transcription termination factor Rho

The alarming issue of antibiotic resistance expansion requires a continuous search for new and efficient antibacterial agents. Here we describe the design of new tools to screen for target-specific inhibitors of the bacterial Rho factor directly inside eukaryotic cells. Rho factor is a global regulator of gene expression which is essential to most bacteria, especially Gram-negative. Since Rho has no functional or structural homolog in eukaryotes, it constitutes a valuable and well known bacterial target as evidenced by its inhibition by the natural antibiotic, Bicyclomycin. Our screening tools are based on perturbation of mRNA processing and packaging reactions in the nucleus of eukaryotic cells by the RNA-dependent helicase/translocase activity of bacterial Rho factor leading to a growth defect phenotype. In this approach, any compound that impedes Rho activity should restore growth to yeast or human cells expressing Rho protein, providing valuable means to screen for target-specific antibacterial agents within the environment of a eukaryotic cell. The yeast tool expressing E. coli Rho factor was validated using Bicyclomycin as the control antibacterial agent. The validation of the screening tool was further extended with a stable human cell line expressing Rho factor conditionally. Finally, we show that Rho factors from different bacterial pathogens can also be designed as yeast-based screening tools which can reveal subtle variations in the functional features of the proteins.

Chloramphenicol-borate/boronate complex for controlling infections by chloramphenicol-resistant bacteria

Increasing bacterial resistance to antibiotics is a pressing problem worldwide, with many health organisations prioritizing this issue. Whilst there is a desperate need for new effective antimicrobials, it is also important to understand the mechanisms and epidemiology of the resistant pathogens currently present in the community. Chloramphenicol is one such well known antibiotic which had lost its efficacy due to bacterial resistance. In this paper, we report the design, synthesis, and bio-studies of novel chloramphenicol-borate/boronate derivatives which showed the ability to control the infections caused by chloramphenicol-resistant bacteria. Activity profiling against P. aeruginosa strain EXR1 with catB gene indicated the inability of acetyl transferase to acetylate the chloramphenicol-borate/boronate complex, unlike chloramphenicol. Results obtained from the antimicrobial assays were further rationalized by molecular docking studies. The latter revealed that the probable reason for the enhanced antibacterial activity may be attributed to the change in the binding site of chloramphenicol-borate/boronate with chloramphenicol acetyl transferase (CAT) with respect to chloramphenicol itself. Hemolytic and genotoxic studies established the reduced toxicity of these synthetic derivatives with respect to chloramphenicol.

We report the design, synthesis, and bio-studies of novel chloramphenicol-borate/boronate derivatives which could control the infections caused by chloramphenicol-resistant bacteria.

Identification of antibiotics in wastewater: current state of extraction protocol and future perspectives

The release and occurrence of antibiotics in the aquatic environment has generated increased attention in the past few decades. The residual antibiotic in wastewater is important in the selection for antimicrobial resistance among microorganisms and the possibility of forming toxic derivatives. This review presents an assessment of the advancement in methods for extraction of antibiotics with solid phase extraction and liquid-liquid extraction methods applied in different aquatic environmental media. These advanced methods do enhance specificity, and also exhibit high accuracy and recovery. The aim of this review is to assess the pros and cons of the methods of extraction towards identification of quinolones and sulphonamides as examples of relevant antibiotics in wastewater. The challenges associated with the improvements are also examined with a view of providing potential perspectives for better extraction and identification protocols in the near future. From the context of this review, magnetic molecular imprinted polymer is superior over the remaining extraction methods (with the availability of commercial templates and monomers), is based on less cumbersome extraction procedures, uses less solvent and has the advantage of its reusable magnetic phase.