Death and population dynamics affect mutation rate estimates and evolvability under stress in bacteria

Maggot therapy for resistant infections: the disconnect between scientific evidence, clinical acceptance and practice

OBJECTIVE

Practitioners and scientists are re-examining marginalised wound care therapies to find strategies that combat the growing problem of antimicrobial resistance (AMR) without compromising patient outcomes. Maggot therapy (MT) makes up just an estimated 0.02% of UK's National Health Service spending on wound care. This study aims to uncover why MT is not used more often, despite its affordability and high level of efficacy for both debridement and disinfection, particularly in the context of AMR infections, and to determine what can be done to ensure MT is more effectively used in the future to improve patient outcomes and manage the growing problem of AMR.

METHOD

For this investigation, a qualitative review of case studies using MT against AMR infections and a quantitative analysis of randomised control trials (RCTs) were performed using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses framework.

RESULTS

Analysis showed that MT is highly effective against a range of infections and wound types, and compares well against conventional therapies. The low use of MT may be due in part to the documented 'yuck factor', often associated with maggots as well as misconceptions around the cost, efficacy and accessibility of MT. To overcome these factors, more RCTs on the spectrum and efficacy of MT across various clinical manifestations are needed, as well as professional and public engagement campaigns.

CONCLUSION

MT is an underused therapy, particularly regarding AMR infections, and expanding its use in these circumstances appears warranted. MT could play a vital role in conserving the efficacy of the existing pool of antimicrobials available and should be considered in the development of antimicrobial stewardship programmes.

DECLARATION OF INTEREST

This work was supported by the Swansea Employability Academy, Swansea University (internal funding). The authors have no conflicts of interest to declare.

Estimating mutation rates under heterogeneous stress responses

Exposure to environmental stressors, including certain antibiotics, induces stress responses in bacteria. Some of these responses increase mutagenesis and thus potentially accelerate resistance evolution. Many studies report increased mutation rates under stress, often using the standard experimental approach of fluctuation assays. However, single-cell studies have revealed that many stress responses are heterogeneously expressed in bacterial populations, which existing estimation methods have not yet addressed. We develop a population dynamic model that considers heterogeneous stress responses (subpopulations of cells with the response off or on) that impact both mutation rate and cell division rate, inspired by the DNA-damage response in Escherichia coli (SOS response). We derive the mutant count distribution arising in fluctuation assays under this model and then implement maximum likelihood estimation of the mutation-rate increase specifically associated with the expression of the stress response. Using simulated mutant count data, we show that our inference method allows for accurate and precise estimation of the mutation-rate increase, provided that this increase is sufficiently large and the induction of the response also reduces the division rate. Moreover, we find that in many cases, either heterogeneity in stress responses or mutant fitness costs could explain similar patterns in fluctuation assay data, suggesting that separate experiments would be required to identify the true underlying process. In cases where stress responses and mutation rates are heterogeneous, current methods still correctly infer the effective increase in population mean mutation rate, but we provide a novel method to infer distinct stress-induced mutation rates, which could be important for parameterising evolutionary models.

Different Scenarios for the Origin and the Subsequent Succession of a Hypothetical Microbial Community in the Cloud Layer of Venus

The possible existence of a microbial community in the venusian clouds is one of the most intriguing hypotheses in modern astrobiology. Such a community must be characterized by a high survivability potential under severe environmental conditions, the most extreme of which are very low pH levels and water activity. Considering different scenarios for the origin of life and geological history of our planet, a few of these scenarios are discussed in the context of the origin of hypothetical microbial life within the venusian cloud layer. The existence of liquid water on the surface of ancient Venus is one of the key outstanding questions influencing this possibility. We link the inherent attributes of microbial life as we know it that favor the persistence of life in such an environment and review the possible scenarios of life's origin and its evolution under a strong greenhouse effect and loss of water on Venus. We also propose a roadmap and describe a novel methodological approach for astrobiological research in the framework of future missions to Venus with the intent to reveal whether life exists today on the planet.

Phenotypic shifts induced by environmental pre-stressors modify antibiotic resistance in Staphylococcus aureus

Introduction

Escalating prevalence of antibiotic resistance in Staphylococcus aureus has necessitated urgent exploration into the fundamental mechanisms underlying antibiotic resistance emergence, particularly in relation to its interaction with environmental stressors. This study aimed to investigate the effects of environmental stressors prior to antibiotic exposure on the antibiotic resistance of S. aureus.

Methods

We used Raman spectroscopy and flow cytometry to measure prior stress-induced phenotypic alterations of S. aureus, and identified the association between phenotypic shifts and the antibiotic resistance.

Results

The results revealed a multifaceted relationship between stressors and the development of antibiotic resistance. The stressors effectuate distinct phenotypic diversifications and subsequently amplify these phenotypic alterations following antibiotic treatments, contingent upon the specific mode of action; these phenotypic shifts in turn promote the development of antibiotic resistance in S. aureus. This study's findings demonstrated that the presence of pre-stress conditions triggered an augmentation of resistance to vancomycin (VAN), while concurrently attenuating resistance to norfloxacin. Marked shifts in Raman peaks associated with lipids and nucleic acids demonstrated correlations with elevated survival rates following VAN treatment.

Conclusion

Consequently, these observations indicate that pre-stress conditions "prime" bacterial cells for differential responses to antibiotics and bear significant implications for formulating clinical therapeutic strategies.

Fitness Costs of Antibiotic Resistance Impede the Evolution of Resistance to Other Antibiotics

Antibiotic resistance is a major threat to global health, claiming the lives of millions every year. With a nearly dry antibiotic development pipeline, novel strategies are urgently needed to combat resistant pathogens. One emerging strategy is the use of sequential antibiotic therapy, postulated to reduce the rate at which antibiotic resistance evolves. Here, we use the soft agar gradient evolution (SAGE) system to carry out high-throughput in vitro bacterial evolution against antibiotic pressure. We find that evolution of resistance to the antibiotic chloramphenicol (CHL) severely affects bacterial fitness, slowing the rate at which resistance to the antibiotics nitrofurantoin and streptomycin emerges. In vitro acquisition of compensatory mutations in the CHL-resistant cells markedly improves fitness and nitrofurantoin adaptation rates but fails to restore rates to wild-type levels against streptomycin. Genome sequencing reveals distinct evolutionary paths to resistance in fitness-impaired populations, suggesting resistance trade-offs in favor of mitigation of fitness costs. We show that the speed of bacterial fronts in SAGE plates is a reliable indicator of adaptation rates and evolutionary trajectories to resistance. Identification of antibiotics whose mutational resistance mechanisms confer stable impairments may help clinicians prescribe sequential antibiotic therapies that are less prone to resistance evolution.

Developmental Selection and the Perception of Mutation Bias

The notion that mutations are random relative to their fitness effects is central to the Neo-Darwinian view of evolution. However, a recent interpretation of the patterns of mutation accumulation in the genome of Arabidopsis thaliana has challenged this notion, arguing for the presence of a targeted DNA repair mechanism that causes a nonrandom association of mutation rates and fitness effects. Specifically, this mechanism was suggested to cause a reduction in the rates of mutations on essential genes, thus lowering the rates of deleterious mutations. Central to this argument were attempts to rule out selection at the population level. Here, we offer an alternative and parsimonious interpretation of the patterns of mutation accumulation previously attributed to mutation bias, showing how they can instead or additionally be caused by developmental selection, that is selection occurring at the cellular level during the development of a multicellular organism. Thus, the depletion of deleterious mutations in A. thaliana may indeed be the result of a selective process, rather than a bias in mutation. More broadly, our work highlights the importance of considering development in the interpretation of population-genetic analyses of multicellular organisms, and it emphasizes that efforts to identify mechanisms involved in mutational biases should explicitly account for developmental selection.

Mutators can drive the evolution of multi-resistance to antibiotics

Antibiotic combination therapies are an approach used to counter the evolution of resistance; their purported benefit is they can stop the successive emergence of independent resistance mutations in the same genome. Here, we show that bacterial populations with 'mutators', organisms with defects in DNA repair, readily evolve resistance to combination antibiotic treatment when there is a delay in reaching inhibitory concentrations of antibiotic-under conditions where purely wild-type populations cannot. In populations of Escherichia coli subjected to combination treatment, we detected a diverse array of acquired mutations, including multiple alleles in the canonical targets of resistance for the two drugs, as well as mutations in multi-drug efflux pumps and genes involved in DNA replication and repair. Unexpectedly, mutators not only allowed multi-resistance to evolve under combination treatment where it was favoured, but also under single-drug treatments. Using simulations, we show that the increase in mutation rate of the two canonical resistance targets is sufficient to permit multi-resistance evolution in both single-drug and combination treatments. Under both conditions, the mutator allele swept to fixation through hitch-hiking with single-drug resistance, enabling subsequent resistance mutations to emerge. Ultimately, our results suggest that mutators may hinder the utility of combination therapy when mutators are present. Additionally, by raising the rates of genetic mutation, selection for multi-resistance may have the unwanted side-effect of increasing the potential to evolve resistance to future antibiotic treatments.

Efficient, robust, and versatile fluctuation data analysis using MLE MUtation Rate calculator (mlemur)

The fluctuation assay remains an important tool for analyzing the levels of mutagenesis in microbial populations. The mutant counts originating from some average number of mutations are usually assumed to obey the Luria-Delbrück distribution. While several tools for estimating mutation rates are available, they sometimes lack accuracy or versatility under non-standard conditions. In this work, extensions to the Luria-Delbrück protocol to account for phenotypic lag and cellular death with either perfect or partial plating were developed. Hence, the novel MLE MUtation Rate calculator, or mlemur, is the first tool that provides a user-friendly graphical interface allowing the researchers to model their data with consideration for partial plating, differential growth of mutants and non-mutants, phenotypic lag, cellular death, variability of the final number of cells, post-exponential-phase mutations, and the size of the inoculum. Additionally, mlemur allows the users to incorporate most of these special conditions at the same time to obtain highly accurate estimates of mutation rates and P values, confidence intervals for an arbitrary function of data (such as fold), and perform power analysis and sample size determination for the likelihood ratio test. The accuracy of point and interval estimates produced by mlemur against historical and simulated fluctuation experiments are assessed. Both mlemur and the analyses in this work might be of great help when evaluating fluctuation experiments and increase the awareness of the limitations of the widely-used Lea-Coulson formulation of the Luria-Delbrück distribution in the more realistic biological contexts.

Estimating mutation rates in a Markov branching process using approximate Bayesian computation

Estimating microbial mutation rates is an essential task in evolutionary biology, with wide range applications in related fields such as virology, epidemiology, clinic and public health, and antibiotic research. Significant progress has been made on this research since 1943 when Luria-Delbrück fluctuation analysis was first introduced. However, existing estimators of mutation rates are heavily reliant on model assumptions in fluctuation analysis, and become less applicable to real microbial experiments which deviate from the model assumptions. To overcome this difficulty, we propose to model fluctuation experimental data by a two-type Markov branching process (MBP) and use approximate Bayesian computation (ABC) to estimate the mutation probability parameters. Such an ABC-based mutation rate estimator is based on intensive simulations from the mutation process, thereby taking advantage of modern computing power. Most importantly, its likelihood-free feature allows more complex and realistic setups of the mutation process, especially when the distribution of the number of mutants cannot be easily derived. To further improve computation efficiency, we use a Gaussian process surrogate to substitute the simulator in the ABC algorithm, and call the resulting estimator GPS-ABC. Simulation studies show that, when used to estimate constant mutation rate in MBP, ABC-based estimators generally outperform traditional moment or likelihood-based estimators. When mutations occur in two stages, i.e., in MBP with a piece-wise constant mutation rate function, traditional mutation rate estimators become not applicable, yet GPS-ABC still achieves reasonable estimates. Finally, the proposed GPS-ABC estimator is used to analyze real fluctuation experimental datasets for studying drug resistance.

Inferring density-dependent population dynamics mechanisms through rate disambiguation for logistic birth-death processes

Density dependence is important in the ecology and evolution of microbial and cancer cells. Typically, we can only measure net growth rates, but the underlying density-dependent mechanisms that give rise to the observed dynamics can manifest in birth processes, death processes, or both. Therefore, we utilize the mean and variance of cell number fluctuations to separately identify birth and death rates from time series that follow stochastic birth-death processes with logistic growth. Our nonparametric method provides a novel perspective on stochastic parameter identifiability, which we validate by analyzing the accuracy in terms of the discretization bin size. We apply our method to the scenario where a homogeneous cell population goes through three stages: (1) grows naturally to its carrying capacity, (2) is treated with a drug that reduces its carrying capacity, and (3) overcomes the drug effect to restore its original carrying capacity. In each stage, we disambiguate whether the dynamics occur through the birth process, death process, or some combination of the two, which contributes to understanding drug resistance mechanisms. In the case of limited sample sizes, we provide an alternative method based on maximum likelihood and solve a constrained nonlinear optimization problem to identify the most likely density dependence parameter for a given cell number time series. Our methods can be applied to other biological systems at different scales to disambiguate density-dependent mechanisms underlying the same net growth rate.

Estimation of Rates of Non-neutral Mutations When Bacteria are Exposed to Subinhibitory Levels of Antibiotics

The increasingly widespread use of antibiotics has raised an urgent public health question: how does nonlethal exposure of antibiotics increase rates of bacterial mutations that confer antibiotic resistance? Quantitative studies of this sort are rare, and interested investigators tend to neglect scenarios where the mutation inducer and the selective agent are the same. One possible reason for this puzzling neglect is that such an investigation may lead to results that are prone to a Lamarckian interpretation, but a more tangible reason is that successful estimation of mutation rates in such scenarios requires new computational methods. This study presents computational methods tailored for a mutation model in which some wide-type cells may be killed by nonlethal exposure to an antibiotic, but in which mutants proliferate unimpeded. Methods for computing maximum likelihood estimates of mutation rates and their corresponding confidence intervals are devised and evaluated by simulations.

Global coordination of the mutation and growth rates across the genetic and nutritional variety in Escherichia coli

Fitness and mutability are the primary traits of living organisms for adaptation and evolution. However, their quantitative linkage remained largely deficient. Whether there is any general relationship between the two features and how genetic and environmental variables influence them remained unclear and were addressed here. The mutation and growth rates of an assortment of Escherichia coli strain collections, including the wild-type strains and the genetically disturbed strains of either reduced genomes or deletion of the genes involved in the DNA replication fidelity, were evaluated in various media. The contribution of media to the mutation and growth rates was differentiated depending on the types of genetic disturbance. Nevertheless, the negative correlation between the mutation and growth rates was observed across the genotypes and was common in all media. It indicated the comprehensive association of the correlated mutation and growth rates with the genetic and medium variation. Multiple linear regression and support vector machine successfully predicted the mutation and growth rates and the categories of genotypes and media, respectively. Taken together, the study provided a quantitative dataset linking the mutation and growth rates, genotype, and medium and presented a simple and successful example of predicting bacterial growth and mutability by data-driven approaches.

Biocides used as material preservatives modify rates of de novo mutation and horizontal gene transfer in bacteria

Antimicrobial resistance (AMR) is a global health problem with the environment being an important compartment for the evolution and transmission of AMR. Previous studies showed that de-novo mutagenesis and horizontal gene transfer (HGT) by conjugation or transformation - important processes underlying resistance evolution and spread - are affected by antibiotics, metals and pesticides. However, natural microbial communities are also frequently exposed to biocides used as material preservatives, but it is unknown if these substances induce mutagenesis and HGT. Here, we show that active substances used in material preservatives can increase rates of mutation and conjugation in a species- and substance-dependent manner, while rates of transformation are not increased. The bisbiguanide chlorhexidine digluconate, the quaternary ammonium compound didecyldimethylammonium chloride, the metal copper, the pyrethroid-insecticide permethrin, and the azole-fungicide propiconazole increase mutation rates in Escherichia coli, whereas no increases were identified for Bacillus subtilis and Acinetobacter baylyi. Benzalkonium chloride, chlorhexidine and permethrin increased conjugation in E. coli. Moreover, our results show a connection between the RpoS-mediated general stress and the RecA-linked SOS response with increased rates of mutation and conjugation, but not for all biocides. Taken together, our data show the importance of assessing the contribution of material preservatives on AMR evolution and spread.

Ecological effects of stress drive bacterial evolvability under sub-inhibitory antibiotic treatments

Stress is thought to increase mutation rate and thus to accelerate evolution. In the context of antibiotic resistance, sub-inhibitory treatments could then lead to enhanced evolvability, thereby fuelling the adaptation of pathogens. Combining wet-lab experiments, stochastic simulations and a meta-analysis of the literature, we found that the increase in mutation rates triggered by antibiotic treatments is often cancelled out by reduced population size, resulting in no overall increase in genetic diversity. A careful analysis of the effect of ecological factors on genetic diversity showed that the potential for regrowth during recovery phase after treatment plays a crucial role in evolvability, being the main factor associated with increased genetic diversity in experimental data.

A genome-wide association study of the occurrence of genetic variations in Edwardsiella piscicida, Vibrio harveyi, and Streptococcus parauberis under stressed environments

Bacterial mutation and genetic diversity in aquaculture have led to increasing phenotypic variances, which can weaken or invalidate strategies for controlling diseases. However, few studies have monitored the degree of mutation in fish bacterial pathogens caused by environmental pressure within a short period. In this study, transcriptomic sequences from Edwardsiella piscicida, Vibrio harveyi and Streptococcus parauberis under stressed environments were used for investigating the emergence of variants. In detail, a sub-inhibitory concentration of formalin and phenol for E. piscicida, sea water at 30°C for V. harveyi and flounder serum for S. parauberis were used as stressed environments, and significant single-nucleotide polymorphisms (SNPs) and/or mutation sites were investigated after culture in the ordinary liquid media (control) and the stressed environment through a genome-wide association study. As results, several SNPs or mutations during incubation were observed under different environments in E. piscicida and/or V. harveyi in the genes relevant to flagella, fimbria type 3 secretion systems, and outer and inner membranes that have been directly exposed to external environments. In particular, given that flagella and fimbriae are considered important factors in differentiating the serotypes in some bacterial pathogens, it can be speculated that different environmental pressures are the source of phenotypic or serotypic differentiation from the same origin. On the other hands, S. parauberis did not exhibit notable changes for 4 h when inoculated in the serum from olive flounder. The results presented in this study provide examples of possible molecular evolution in pathogens relevant to the aquaculture industry as a response to different environmental pressure.

Mechanisms of antibiotic action shape the fitness landscapes of resistance mutations

Antibiotic-resistant pathogens are a major public health threat. A deeper understanding of how an antibiotic's mechanism of action influences the emergence of resistance would aid in the design of new drugs and help to preserve the effectiveness of existing ones. To this end, we developed a model that links bacterial population dynamics with antibiotic-target binding kinetics. Our approach allows us to derive mechanistic insights on drug activity from population-scale experimental data and to quantify the interplay between drug mechanism and resistance selection. We find that both bacteriostatic and bactericidal agents can be equally effective at suppressing the selection of resistant mutants, but that key determinants of resistance selection are the relationships between the number of drug-inactivated targets within a cell and the rates of cellular growth and death. We also show that heterogeneous drug-target binding within a population enables resistant bacteria to evolve fitness-improving secondary mutations even when drug doses remain above the resistant strain's minimum inhibitory concentration. Our work suggests that antibiotic doses beyond this "secondary mutation selection window" could safeguard against the emergence of high-fitness resistant strains during treatment.

The Effect of Heavy Metals on Conjugation Efficiency of an F-Plasmid in Escherichia coli

Conjugation, the process by which conjugative plasmids are transferred between bacteria, is regarded as a major contributor to the spread of antibiotic resistance, in both environmental and clinical settings. Heavy metals are known to co-select for antibiotic resistance, but the impact of the presence of these metals on conjugation itself is not clear. Here, we systematically investigate the impact that five heavy metals (arsenic, cadmium, copper, manganese, and zinc) have on the transfer of an IncF conjugative plasmid in Escherichia coli. Our results show that two of the metals, cadmium and manganese, have no significant impact, while arsenic and zinc both reduce conjugation efficiency by approximately 2-fold. Copper showed the largest impact, with an almost 100-fold decrease in conjugation efficiency. This was not mediated by any change in transcription from the major Py promoter responsible for transcription of the conjugation machinery genes. Further, we show that in order to have this severe impact on the transfer of the plasmid, copper sulfate needs to be present during the mating process, and we suggest explanations for this.

Stress-Induced Mutagenesis, Gambler Cells, and Stealth Targeting Antibiotic-Induced Evolution

Mechanisms of evolution and evolution of antibiotic resistance are both fundamental and world health problems. Stress-induced mutagenesis defines mechanisms of mutagenesis upregulated by stress responses, which drive adaptation when cells are maladapted to their environments—when stressed. Work in mutagenesis induced by antibiotics had produced tantalizing clues but not coherent mechanisms. We review recent advances in antibiotic-induced mutagenesis that integrate how reactive oxygen species (ROS), the SOS and general stress responses, and multichromosome cells orchestrate a stress response-induced switch from high-fidelity to mutagenic repair of DNA breaks. Moreover, while sibling cells stay stable, a mutable “gambler” cell subpopulation is induced by differentially generated ROS, which signal the general stress response. We discuss other evolvable subpopulations and consider diverse evolution-promoting molecules as potential targets for drugs to slow evolution of antibiotic resistance, cross-resistance, and immune evasion. An FDA-approved drug exemplifies “stealth” evolution-slowing drugs that avoid selecting resistance to themselves or antibiotics.

A Microfluidic Chip for Studies of the Dynamics of Antibiotic Resistance Selection in Bacterial Biofilms

Biofilms are arguably the most important mode of growth of bacteria, but how antibiotic resistance emerges and is selected in biofilms remains poorly understood. Several models to study evolution of antibiotic resistance have been developed, however, their usability varies depending on the nature of the biological question. Here, we developed and validated a microfluidic chip (Brimor) for studying the dynamics of enrichment of antibiotic-resistant bacteria in biofilms using real-time monitoring with confocal microscopy. In situ extracellular cellulose staining and physical disruption of the biomass confirmed Escherichia coli growth as biofilms in the chip. We showed that seven generations of growth occur in 16 h when biofilms were established in the growth chambers of Brimor, and that bacterial death and growth rates could be estimated under these conditions using a plasmid with a conditional replication origin. Additionally, competition experiments between antibiotic-susceptible and -resistant bacteria at sub-inhibitory concentrations demonstrated that the antibiotic ciprofloxacin selected for antibiotic resistance in bacterial biofilms at concentrations 17-fold below the minimal inhibitory concentration of susceptible planktonic bacteria. Overall, the microfluidic chip is easy to use and a relevant model for studying the dynamics of selection of antibiotic resistance in bacterial biofilms and we anticipate that the Brimor chip will facilitate basic research in this area.

Prochlorococcus have low global mutation rate and small effective population size

Prochlorococcus are the most abundant free-living photosynthetic carbon-fixing organisms in the ocean. Prochlorococcus show small genome sizes, low genomic G+C content, reduced DNA repair gene pool and fast evolutionary rates, which are typical features of endosymbiotic bacteria. Nevertheless, their evolutionary mechanisms are believed to be different. Evolution of endosymbiotic bacteria is dominated by genetic drift owing to repeated population bottlenecks, whereas Prochlorococcus are postulated to have extremely large effective population sizes (N_e) and thus drift has rarely been considered. However, accurately extrapolating N_e requires measuring an unbiased global mutation rate through mutation accumulation, which is challenging for Prochlorococcus. Here, we managed this experiment over 1,065 days using Prochlorococcus marinus AS9601, sequenced genomes of 141 mutant lines and determined its mutation rate to be 3.50 × 10^-10 per site per generation. Extrapolating N_e additionally requires identifying population boundaries, which we defined using PopCOGenT and over 400 genomes related to AS9601. Accordingly, we calculated its N_e to be 1.68 × 10⁷, which is only reasonably greater than that of endosymbiotic bacteria but surprisingly smaller than that of many free-living bacteria extrapolated using the same approach. Our results therefore suggest that genetic drift is a key driver of Prochlorococcus evolution.

The Infectious Dose Shapes Vibrio cholerae Within-Host Dynamics

During infection, the rates of pathogen replication, death, and migration affect disease progression, dissemination, transmission, and resistance evolution. Here, we follow the population dynamics of Vibrio cholerae in a mouse model by labeling individual bacteria with one of >500 unique, fitness-neutral genomic tags. Using the changes in tag frequencies and CFU numbers, we inform a mathematical model that describes the within-host spatiotemporal bacterial dynamics. This allows us to disentangle growth, death, forward, and retrograde migration rates continuously during infection. Our model has robust predictive power across various experimental setups. The population dynamics of V. cholerae shows substantial spatiotemporal heterogeneity in replication, death, and migration. Importantly, we find that the niche available to V. cholerae in the host increases with inoculum size, suggesting cooperative effects during infection. Therefore, it is not enough to consider just the likelihood of exposure (50% infectious dose) but rather the magnitude of exposure to predict outbreaks. IMPORTANCE Determining the rates of bacterial migration, replication, and death during infection is important for understanding how infections progress. Separately measuring these rates is often difficult in systems where multiple processes happen simultaneously. Here, we use next-generation sequencing to measure V. cholerae migration, replication, death, and niche size along the mouse gastrointestinal tract. We show that the small intestine of the mouse is a heterogeneous environment, and the population dynamic characteristics change substantially between adjacent gut sections. Our approach also allows us to characterize the effect of inoculum size on these processes. We find that the niche size in mice increases with the infectious dose, hinting at cooperative effects in larger inocula. The dose-response relationship between inoculum size and final pathogen burden is important for the infected individual and is thought to influence the progression of V. cholerae epidemics.

Cellular heterogeneity in DNA alkylation repair increases population genetic plasticity

DNA repair mechanisms fulfil a dual role, as they are essential for cell survival and genome maintenance. Here, we studied how cells regulate the interplay between DNA repair and mutation. We focused on the adaptive response that increases the resistance of Escherichia coli cells to DNA alkylation damage. Combination of single-molecule imaging and microfluidic-based single-cell microscopy showed that noise in the gene activation timing of the master regulator Ada is accurately propagated to generate a distinct subpopulation of cells in which all proteins of the adaptive response are essentially absent. Whereas genetic deletion of these proteins causes extreme sensitivity to alkylation stress, a temporary lack of expression is tolerated and increases genetic plasticity of the whole population. We demonstrated this by monitoring the dynamics of nascent DNA mismatches during alkylation stress as well as the frequency of fixed mutations that are generated by the distinct subpopulations of the adaptive response. We propose that stochastic modulation of DNA repair capacity by the adaptive response creates a viable hypermutable subpopulation of cells that acts as a source of genetic diversity in a clonal population.

Transcriptional Response of Mycobacterium tuberculosis to Cigarette Smoke Condensate

Smoking is known to be an added risk factor for tuberculosis (TB), with nearly a quarter of the TB cases attributed to cigarette smokers in the 22 countries with the highest TB burden. Many studies have indicated a link between risk of active TB and cigarette smoke. Smoking is also known to significantly decrease TB cure and treatment completion rate and increase mortality rates. Cigarette smoke contains thousands of volatile compounds including carcinogens, toxins, reactive solids, and oxidants in both particulate and gaseous phase. Yet, to date, limited studies have analyzed the impact of cigarette smoke components on Mycobacterium tuberculosis (Mtb), the causative agent of TB. Here we report the impact of cigarette smoke condensate (CSC) on survival, mutation frequency, and gene expression of Mtb in vitro. We show that exposure of virulent Mtb to cigarette smoke increases the mutation frequency of the pathogen and strongly induces the expression of the regulon controlled by SigH—a global transcriptional regulator of oxidative stress. SigH has previously been shown to be required for Mtb to respond to oxidative stress, survival, and granuloma formation in vivo. A high-SigH expression phenotype is known to be associated with greater virulence of Mtb. In patients with pulmonary TB who smoke, these changes may therefore play an important, yet unexplored, role in the treatment efficacy by potentially enhancing the virulence of tubercle bacilli.

Drug-induced resistance evolution necessitates less aggressive treatment

Increasing body of experimental evidence suggests that anticancer and antimicrobial therapies may themselves promote the acquisition of drug resistance by increasing mutability. The successful control of evolving populations requires that such biological costs of control are identified, quantified and included to the evolutionarily informed treatment protocol. Here we identify, characterise and exploit a trade-off between decreasing the target population size and generating a surplus of treatment-induced rescue mutations. We show that the probability of cure is maximized at an intermediate dosage, below the drug concentration yielding maximal population decay, suggesting that treatment outcomes may in some cases be substantially improved by less aggressive treatment strategies. We also provide a general analytical relationship that implicitly links growth rate, pharmacodynamics and dose-dependent mutation rate to an optimal control law. Our results highlight the important, but often neglected, role of fundamental eco-evolutionary costs of control. These costs can often lead to situations, where decreasing the cumulative drug dosage may be preferable even when the objective of the treatment is elimination, and not containment. Taken together, our results thus add to the ongoing criticism of the standard practice of administering aggressive, high-dose therapies and motivate further experimental and clinical investigation of the mutagenicity and other hidden collateral costs of therapies.

The within-host evolution of antimicrobial resistance in Mycobacterium tuberculosis

Tuberculosis (TB) has been responsible for the greatest number of human deaths due to an infectious disease in general, and due to antimicrobial resistance (AMR) in particular. The etiological agents of human TB are a closely-related group of human-adapted bacteria that belong to the Mycobacterium tuberculosis complex (MTBC). Understanding how MTBC populations evolve within-host may allow for improved TB treatment and control strategies. In this review, we highlight recent works that have shed light on how AMR evolves in MTBC populations within individual patients. We discuss the role of heteroresistance in AMR evolution, and review the bacterial, patient and environmental factors that likely modulate the magnitude of heteroresistance within-host. We further highlight recent works on the dynamics of MTBC genetic diversity within-host, and discuss how spatial substructures in patients' lungs, spatiotemporal heterogeneity in antimicrobial concentrations and phenotypic drug tolerance likely modulates the dynamics of MTBC genetic diversity in patients during treatment. We note the general characteristics that are shared between how the MTBC and other bacterial pathogens evolve in humans, and highlight the characteristics unique to the MTBC.

The AcrAB-TolC Efflux Pump Impacts Persistence and Resistance Development in Stationary-Phase Escherichia coli following Delafloxacin Treatment

Bacteria have a repertoire of strategies to overcome antibiotics in clinical use, complicating our ability to treat and cure infectious diseases. In addition to evolving resistance, bacteria within genetically clonal cultures can undergo transient phenotypic changes and tolerate high doses of antibiotics. These cells, termed persisters, exhibit heterogeneous phenotypes; the strategies that a bacterial population deploys to overcome one class of antibiotics can be distinct from those needed to survive treatment with drugs with another mode of action. It was previously reported that fluoroquinolones, which target DNA topoisomerases, retain the capacity to kill nongrowing bacteria that tolerate other classes of antibiotics. Here, we show that in Escherichia coli stationary-phase cultures and colony biofilms, persisters that survive treatment with the anionic fluoroquinolone delafloxacin depend on the AcrAB-TolC efflux pump. In contrast, we did not detect this dependence on AcrAB-TolC in E. coli persisters that survive treatment with three other fluoroquinolone compounds. We found that the loss of AcrAB-TolC activity via genetic mutations or chemical inhibition not only reduces delafloxacin persistence in nongrowing E. coli MG1655 or EDL933 (an E. coli O157:H7 strain), but it limits resistance development in progenies derived from delafloxacin persisters that were given the opportunity to recover in nutritive medium following antibiotic treatment. Our findings highlight the heterogeneity in defense mechanisms that persisters use to overcome different compounds within the same class of antibiotics. They further indicate that efflux pump inhibitors can potentiate the activity of delafloxacin against stationary-phase E. coli and block resistance development in delafloxacin persister progenies.

Microfluidic platform for monitoring Saccharomyces cerevisiae mutation accumulation

Mutations in DNA have large-ranging consequences, from evolution to disease. Many mechanisms contribute to mutational processes such as dysfunctions in DNA repair pathways and exogenous or endogenous mutagen exposures. Model organisms and mutation accumulation (MA) experiments are indispensable to study mutagenesis. Classical MA is, however, time consuming and laborious. To fill the need for more efficient approaches to characterize mutational profiles, we have developed an innovative microfluidic-based system that automatizes MA culturing over many generations in budding yeast. This unique experimental tool, coupled with high-throughput sequencing, reduces by one order of magnitude the time required for genome-wide measurements of mutational profiles, while also parallelizing and simplifying the cell culture. To validate our approach, we performed microfluidic MA experiments on two different genetic backgrounds, a wild-type strain and a base-excision DNA repair ung1 mutant characterized by a well-defined mutational profile. We show that the microfluidic device allows for mutation accumulation comparable to the traditional method on plate. Our approach thus paves the way to massively-parallel MA experiments with minimal human intervention that can be used to investigate mutational processes at the origin of human diseases and to identify mutagenic compounds relevant for medical and environmental research.

Inferring environmental transmission using phylodynamics: a case-study using simulated evolution of an enteric pathogen

Indirect (environmental) and direct (host-host) transmission pathways cannot easily be distinguished when they co-occur in epidemics, particularly when they occur on similar time scales. Phylodynamic reconstruction is a potential approach to this problem that combines epidemiological information (temporal, spatial information) with pathogen whole-genome sequencing data to infer transmission trees of epidemics. However, factors such as differences in mutation and transmission rates between host and non-host environments may obscure phylogenetic inference from these methods. In this study, we used a network-based transmission model that explicitly models pathogen evolution to simulate epidemics with both direct and indirect transmission. Epidemics were simulated according to factorial combinations of direct/indirect transmission proportions, host mutation rates and conditions of environmental pathogen growth. Transmission trees were then reconstructed using the phylodynamic approach SCOTTI (structured coalescent transmission tree inference) and evaluated. We found that although insufficient diversity sets a lower bound on when accurate phylodynamic inferences can be made, transmission routes and assumed pathogen lifestyle affected pathogen population structure and subsequently influenced both reconstruction success and the likelihood of direct versus indirect pathways being reconstructed. We conclude that prior knowledge of the likely ecology and population structure of pathogens in host and non-host environments is critical to fully using phylodynamic techniques.

Unexpectedly high mutation rate of a deep-sea hyperthermophilic anaerobic archaeon

Deep-sea hydrothermal vents resemble the early Earth, and thus the dominant Thermococcaceae inhabitants, which occupy an evolutionarily basal position of the archaeal tree and take an obligate anaerobic hyperthermophilic free-living lifestyle, are likely excellent models to study the evolution of early life. Here, we determined that unbiased mutation rate of a representative species, Thermococcus eurythermalis, exceeded that of all known free-living prokaryotes by 1-2 orders of magnitude, and thus rejected the long-standing hypothesis that low mutation rates were selectively favored in hyperthermophiles. We further sequenced multiple and diverse isolates of this species and calculated that T. eurythermalis has a lower effective population size than other free-living prokaryotes by 1-2 orders of magnitude. These data collectively indicate that the high mutation rate of this species is not selectively favored but instead driven by random genetic drift. The availability of these unusual data also helps explore mechanisms underlying microbial genome size evolution. We showed that genome size is negatively correlated with mutation rate and positively correlated with effective population size across 30 bacterial and archaeal lineages, suggesting that increased mutation rate and random genetic drift are likely two important mechanisms driving microbial genome reduction. Future determinations of the unbiased mutation rate of more representative lineages with highly reduced genomes such as Prochlorococcus and Pelagibacterales that dominate marine microbial communities are essential to test these hypotheses.

Microbial community composition interacts with local abiotic conditions to drive colonization resistance in human gut microbiome samples

Biological invasions can alter ecosystem stability and function, and predicting what happens when a new species or strain arrives remains a major challenge in ecology. In the mammalian gastrointestinal tract, susceptibility of the resident microbial community to invasion by pathogens has important implications for host health. However, at the community level, it is unclear whether susceptibility to invasion depends mostly on resident community composition (which microbes are present), or also on local abiotic conditions (such as nutrient status). Here, we used a gut microcosm system to disentangle some of the drivers of susceptibility to invasion in microbial communities sampled from humans. We found resident microbial communities inhibited an invading Escherichia coli strain, compared to community-free control treatments, sometimes excluding the invader completely (colonization resistance). These effects were stronger at later time points, when we also detected altered community composition and nutrient availability. By separating these two components (microbial community and abiotic environment), we found taxonomic composition played a crucial role in suppressing invasion, but this depended critically on local abiotic conditions (adapted communities were more suppressive in nutrient-depleted conditions). This helps predict when resident communities will be most susceptible to invasion, with implications for optimizing treatments based on microbiota management.

Bacterial defenses against a natural antibiotic promote collateral resilience to clinical antibiotics

Bacterial opportunistic human pathogens frequently exhibit intrinsic antibiotic tolerance and resistance, resulting in infections that can be nearly impossible to eradicate. We asked whether this recalcitrance could be driven by these organisms' evolutionary history as environmental microbes that engage in chemical warfare. Using Pseudomonas aeruginosa as a model, we demonstrate that the self-produced antibiotic pyocyanin (PYO) activates defenses that confer collateral tolerance specifically to structurally similar synthetic clinical antibiotics. Non-PYO-producing opportunistic pathogens, such as members of the Burkholderia cepacia complex, likewise display elevated antibiotic tolerance when cocultured with PYO-producing strains. Furthermore, by widening the population bottleneck that occurs during antibiotic selection and promoting the establishment of a more diverse range of mutant lineages, PYO increases apparent rates of mutation to antibiotic resistance to a degree that can rival clinically relevant hypermutator strains. Together, these results reveal an overlooked mechanism by which opportunistic pathogens that produce natural toxins can dramatically modulate the efficacy of clinical antibiotics and the evolution of antibiotic resistance, both for themselves and other members of clinically relevant polymicrobial communities.

Using rapid point-of-care tests to inform antibiotic choice to mitigate drug resistance in gonorrhoea

Background

The first cases of extensively drug resistant gonorrhoea were recorded in the United Kingdom in 2018. There is a public health need for strategies on how to deploy existing and novel antibiotics to minimise the risk of resistance development. As rapid point-of-care tests (POCTs) to predict susceptibility are coming to clinical use, coupling the introduction of an antibiotic with diagnostics that can slow resistance emergence may offer a novel paradigm for maximising antibiotic benefits. Gepotidacin is a novel antibiotic with known resistance and resistance-predisposing mutations. In particular, a mutation that confers resistance to ciprofloxacin acts as the ‘stepping-stone’ mutation to gepotidacin resistance.

Aim

To investigate how POCTs detecting Neisseria gonorrhoeae resistance mutations for ciprofloxacin and gepotidacin can be used to minimise the risk of resistance development to gepotidacin.

Methods

We use individual-based stochastic simulations to formally investigate the aim.

Results

The level of testing needed to reduce the risk of resistance development depends on the mutation rate under treatment and the prevalence of stepping-stone mutations. A POCT is most effective if the mutation rate under antibiotic treatment is no more than two orders of magnitude above the mutation rate without treatment and the prevalence of stepping-stone mutations is 1–13%.

Conclusion

Mutation frequencies and rates should be considered when estimating the POCT usage required to reduce the risk of resistance development in a given population. Molecular POCTs for resistance mutations and stepping-stone mutations to resistance are likely to become important tools in antibiotic stewardship.

Bacterial phenotypic heterogeneity in DNA repair and mutagenesis

Genetically identical cells frequently exhibit striking heterogeneity in various phenotypic traits such as their morphology, growth rate, or gene expression. Such non-genetic diversity can help clonal bacterial populations overcome transient environmental challenges without compromising genome stability, while genetic change is required for long-term heritable adaptation. At the heart of the balance between genome stability and plasticity are the DNA repair pathways that shield DNA from lesions and reverse errors arising from the imperfect DNA replication machinery. In principle, phenotypic heterogeneity in the expression and activity of DNA repair pathways can modulate mutation rates in single cells and thus be a source of heritable genetic diversity, effectively reversing the genotype-to-phenotype dogma. Long-standing evidence for mutation rate heterogeneity comes from genetics experiments on cell populations, which are now complemented by direct measurements on individual living cells. These measurements are increasingly performed using fluorescence microscopy with a temporal and spatial resolution that enables localising, tracking, and counting proteins with single-molecule sensitivity. In this review, we discuss which molecular processes lead to phenotypic heterogeneity in DNA repair and consider the potential consequences on genome stability and dynamics in bacteria. We further inspect these concepts in the context of DNA damage and mutation induced by antibiotics.

RESTAMP - Rate estimates by sequence-tag analysis of microbial populations

Microbial division rates determine the speed of mutation accumulation and thus the emergence of antimicrobial resistance. Microbial death rates are affected by antibiotic action and the immune system. Therefore, measuring these rates has advanced our understanding of host-pathogen interactions and antibiotic action. Several methods based on marker-loss or few inheritable neutral markers exist that allow estimating microbial division and death rates, each of which has advantages and limitations. Technical bottlenecks, i.e., experimental sampling events, during the experiment can distort the rate estimates and are typically unaccounted for or require additional calibration experiments. In this work, we introduce RESTAMP (Rate Estimates by Sequence Tag Analysis of Microbial Populations) as a method for determining bacterial division and death rates. This method uses hundreds of fitness neutral sequence barcodes to measure the rates and account for experimental bottlenecks at the same time. We experimentally validate RESTAMP and compare it to established plasmid loss methods. We find that RESTAMP has a number of advantages over plasmid loss or previous marker based techniques. (i) It enables to correct the distortion of rate estimates by technical bottlenecks. (ii) Rate estimates are independent of the sequence tag distribution in the starting culture allowing the use of an arbitrary number of tags. (iii) It introduces a bottleneck sensitivity measure that can be used to maximize the accuracy of the experiment. RESTAMP allows studying microbial population dynamics with great resolution over a wide dynamic range and can thus advance our understanding of host-pathogen interactions or the mechanisms of antibiotic action.

Antibiotic-Induced Mutagenesis: Under the Microscope

The development of antibiotic resistance poses an increasing threat to global health. Understanding how resistance develops in bacteria is critical for the advancement of new strategies to combat antibiotic resistance. In the 1980s, it was discovered that certain antibiotics induce elevated rates of mutation in bacteria. From this, an “increased evolvability” hypothesis was proposed: antibiotic-induced mutagenesis increases the genetic diversity of bacterial populations, thereby increasing the rate at which bacteria develop antibiotic resistance. However, antibiotic-induced mutagenesis is one of multiple competing factors that act on bacterial populations exposed to antibiotics. Its relative importance in shaping evolutionary outcomes, including the development of antibiotic resistance, is likely to depend strongly on the conditions. Presently, there is no quantitative model that describes the relative contribution of antibiotic-induced mutagenesis to bacterial evolution. A far more complete understanding could be reached if we had access to technology that enabled us to study antibiotic-induced mutagenesis at the molecular-, cellular-, and population-levels simultaneously. Direct observations would, in principle, allow us to directly link molecular-level events with outcomes in individual cells and cell populations. In this review, we highlight microscopy studies which have allowed various aspects of antibiotic-induced mutagenesis to be directly visualized in individual cells for the first time. These studies have revealed new links between error-prone DNA polymerases and recombinational DNA repair, evidence of spatial regulation occurring during the SOS response, and enabled real-time readouts of mismatch and mutation rates. Further, we summarize the recent discovery of stochastic population fluctuations in cultures exposed to sub-inhibitory concentrations of bactericidal antibiotics and discuss the implications of this finding for the study of antibiotic-induced mutagenesis. The studies featured here demonstrate the potential of microscopy to provide direct observation of phenomena relevant to evolution under antibiotic-induced mutagenesis.

N-acetylcysteine blocks SOS induction and mutagenesis produced by fluoroquinolones in Escherichia coli

BACKGROUND

Fluoroquinolones such as ciprofloxacin induce the mutagenic SOS response and increase the levels of intracellular reactive oxygen species (ROS). Both the SOS response and ROS increase bacterial mutagenesis, fuelling the emergence of resistant mutants during antibiotic treatment. Recently, there has been growing interest in developing new drugs able to diminish the mutagenic effect of antibiotics by modulating ROS production and the SOS response.

OBJECTIVES

To test whether physiological concentrations of N-acetylcysteine, a clinically safe antioxidant drug currently used in human therapy, is able to reduce ROS production, SOS induction and mutagenesis in ciprofloxacin-treated bacteria without affecting antibiotic activity.

METHODS

The Escherichia coli strain IBDS1 and its isogenic mutant deprived of SOS mutagenesis (TLS-) were treated with different concentrations of ciprofloxacin, N-acetylcysteine or both drugs in combination. Relevant parameters such as MICs, growth rates, ROS production, SOS induction, filamentation and antibiotic-induced mutation rates were evaluated.

RESULTS

Treatment with N-acetylcysteine reduced intracellular ROS levels (by ∼40%), as well as SOS induction (by up to 75%) and bacterial filamentation caused by subinhibitory concentrations of ciprofloxacin, without affecting ciprofloxacin antibacterial activity. Remarkably, N-acetylcysteine completely abolished SOS-mediated mutagenesis.

CONCLUSIONS

Collectively, our data strongly support the notion that ROS are a key factor in antibiotic-induced SOS mutagenesis and open the possibility of using N-acetylcysteine in combination with antibiotic therapy to hinder the development of antibiotic resistance.

Bacterial antibiotic resistance development and mutagenesis following exposure to subinhibitory concentrations of fluoroquinolones in vitro: a systematic review of the literature

BACKGROUND

Understanding social and scientific drivers of antibiotic resistance is critical to help preserve antibiotic efficacy. These drivers include exposure to subinhibitory antibiotic concentrations in the environment and clinic.

OBJECTIVES

To summarize and quantify the relationship between subinhibitory fluoroquinolone exposure and antibiotic resistance and mutagenesis to better understand resistance patterns and mechanisms.

METHODS

Following PRISMA guidelines, PubMed, Web of Science and Embase were searched for primary in vitro experimental studies on subinhibitory fluoroquinolone exposure and bacterial antibiotic resistance and mutagenesis, from earliest available dates through to 2018 without language limitation. A specifically developed non-weighted tool was used to assess risk of bias.

RESULTS

Evidence from 62 eligible studies showed that subinhibitory fluoroquinolone exposure results in increased resistance to the selecting fluoroquinolone. Most increases in MIC were low (median minimum of 3.7-fold and median maximum of 32-fold) and may not be considered clinically relevant. Mechanistically, resistance is partly explained by target mutations but also changes in drug efflux. Collaterally, resistance to other fluoroquinolones and unrelated antibiotic classes also develops. The mean ± SD quality score for all studies was 2.6 ± 1.8 with a range of 0 (highest score) to 7 (lowest score).

CONCLUSIONS

Low and moderate levels of resistance and efflux changes can create an opportunity for higher-level resistance or MDR. Future studies, to elucidate the genetic regulation of specific resistance mechanisms, and increased policies, including surveillance of low-level resistance changes or genomic surveillance of efflux pump genes and regulators, could serve as a predictor of MDR development.

Adverse effects of adaptive mutation to survive static culture conditions on successful fitness of the rice pathogen Burkholderia glumae in a host

Bacteria often possess relatively flexible genome structures and adaptive genetic variants that allow survival in unfavorable growth conditions. Bacterial survival tactics in disadvantageous microenvironments include mutations that are beneficial against threats in their niche. Here, we report that the aerobic rice bacterial pathogen Burkholderia glumae BGR1 changes a specific gene for improved survival in static culture conditions. Static culture triggered formation of colony variants with deletions or point mutations in the gene bspP (BGLU_RS28885), which putatively encodes a protein that contains PDC2, PAS-9, SpoIIE, and HATPase domains. The null mutant of bspP survived longer in static culture conditions and produced a higher level of bis-(3'-5')-cyclic dimeric guanosine monophosphate than the wild type. Expression of the bacterial cellulose synthase regulator (bcsB) gene was upregulated in the mutant, consistent with the observation that the mutant formed pellicles faster than the wild type. Mature pellicle formation was observed in the bspP mutant before pellicle formation in wild-type BGR1. However, the population density of the bspP null mutant decreased substantially when grown in Luria-Bertani medium with vigorous agitation due to failure of oxalate-mediated detoxification of the alkaline environment. The bspP null mutant was less virulent and exhibited less effective colonization of rice plants than the wild type. All phenotypes caused by mutations in bspP were recovered to those of the wild type by genetic complementation. Thus, although wild-type B. glumae BGR1 prolonged viability by spontaneous mutation under static culture conditions, such genetic changes negatively affected colonization in rice plants. These results suggest that adaptive gene sacrifice of B. glumae to survive unfavorable growth conditions is not always desirable as it can adversely affect adaptability in the host.

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

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.

Integrating mathematical models with experimental data to investigate the within-host dynamics of bacterial infections

Bacterial infections still constitute a major cause of mortality and morbidity worldwide. The unavailability of therapeutics, antimicrobial resistance and the chronicity of infections due to incomplete clearance contribute to this phenomenon. Despite the progress in antimicrobial and vaccine development, knowledge about the effect that therapeutics have on the host–bacteria interactions remains incomplete. Insights into the characteristics of bacterial colonization and migration between tissues and the relationship between replication and host- or therapeutically induced killing can enable efficient design of treatment approaches. Recently, innovative experimental techniques have generated data enabling the qualitative characterization of aspects of bacterial dynamics. Here, we argue that mathematical modeling as an adjunct to experimental data can enrich the biological insight that these data provide. However, due to limited interdisciplinary training, efforts to combine the two remain limited. To promote this dialogue, we provide a categorization of modeling approaches highlighting their relationship to data generated by a range of experimental techniques in the area of in vivo bacterial dynamics. We outline common biological themes explored using mathematical models with case studies across all pathogen classes. Finally, this review advocates multidisciplinary integration to improve our mechanistic understanding of bacterial infections and guide the use of existing or new therapies.

Genomic and phenotypic evolution of Escherichia coli in a novel citrate-only resource environment

Evolutionary innovations allow populations to colonize new ecological niches. We previously reported that aerobic growth on citrate (Cit⁺) evolved in an Escherichia coli population during adaptation to a minimal glucose medium containing citrate (DM25). Cit⁺ variants can also grow in citrate-only medium (DM0), a novel environment for E. coli. To study adaptation to this niche, we founded two sets of Cit⁺ populations and evolved them for 2500 generations in DM0 or DM25. The evolved lineages acquired numerous parallel mutations, many mediated by transposable elements. Several also evolved amplifications of regions containing the maeA gene. Unexpectedly, some evolved populations and clones show apparent declines in fitness. We also found evidence of substantial cell death in Cit⁺ clones. Our results thus demonstrate rapid trait refinement and adaptation to the new citrate niche, while also suggesting a recalcitrant mismatch between E. coli physiology and growth on citrate.

Resist or perish: Fate of a microbial population subjected to a periodic presence of antimicrobial

The evolution of antimicrobial resistance can be strongly affected by variations of antimicrobial concentration. Here, we study the impact of periodic alternations of absence and presence of antimicrobial on resistance evolution in a microbial population, using a stochastic model that includes variations of both population composition and size, and fully incorporates stochastic population extinctions. We show that fast alternations of presence and absence of antimicrobial are inefficient to eradicate the microbial population and strongly favor the establishment of resistance, unless the antimicrobial increases enough the death rate. We further demonstrate that if the period of alternations is longer than a threshold value, the microbial population goes extinct upon the first addition of antimicrobial, if it is not rescued by resistance. We express the probability that the population is eradicated upon the first addition of antimicrobial, assuming rare mutations. Rescue by resistance can happen either if resistant mutants preexist, or if they appear after antimicrobial is added to the environment. Importantly, the latter case is fully prevented by perfect biostatic antimicrobials that completely stop division of sensitive microorganisms. By contrast, we show that the parameter regime where treatment is efficient is larger for biocidal drugs than for biostatic drugs. This sheds light on the respective merits of different antimicrobial modes of action.

Selection or drift: The population biology underlying transposon insertion sequencing experiments

Transposon insertion sequencing methods such as Tn-seq revolutionized microbiology by allowing the identification of genomic loci that are critical for viability in a specific environment on a genome-wide scale. While powerful, transposon insertion sequencing suffers from limited reproducibility when different analysis methods are compared. From the perspective of population biology, this may be explained by changes in mutant frequency due to chance (drift) rather than differential fitness (selection). Here, we develop a mathematical model of the population biology of transposon insertion sequencing experiments, i.e. the changes in size and composition of the transposon-mutagenized population during the experiment. We use this model to investigate mutagenesis, the growth of the mutant library, and its passage through bottlenecks. Specifically, we study how these processes can lead to extinction of individual mutants depending on their fitness and the distribution of fitness effects (DFE) of the entire mutant population. We find that in typical in vitro experiments few mutants with high fitness go extinct. However, bottlenecks of a size that is common in animal infection models lead to so much random extinction that a large number of viable mutants would be misclassified. While mutants with low fitness are more likely to be lost during the experiment, mutants with intermediate fitness are expected to be much more abundant and can constitute a large proportion of detected hits, i.e. false positives. Thus, incorporating the DFEs of randomly generated mutations in the analysis may improve the reproducibility of transposon insertion experiments, especially when strong bottlenecks are encountered.

The Genetic Background Modulates the Evolution of Fluoroquinolone-Resistance in Mycobacterium tuberculosis

Fluoroquinolones (FQ) form the backbone in experimental treatment regimens against drug-susceptible tuberculosis. However, little is known on whether the genetic variation present in natural populations of Mycobacterium tuberculosis (Mtb) affects the evolution of FQ-resistance (FQ-R). To investigate this question, we used nine genetically distinct drug-susceptible clinical isolates of Mtb and measured their frequency of resistance to the FQ ofloxacin (OFX) in vitro. We found that the Mtb genetic background led to differences in the frequency of OFX-resistance (OFX-R) that spanned two orders of magnitude and substantially modulated the observed mutational profiles for OFX-R. Further, in vitro assays showed that the genetic background also influenced the minimum inhibitory concentration and the fitness effect conferred by a given OFX-R mutation. To test the clinical relevance of our in vitro work, we surveyed the mutational profile for FQ-R in publicly available genomic sequences from clinical Mtb isolates, and found substantial Mtb lineage-dependent variability. Comparison of the clinical and the in vitro mutational profiles for FQ-R showed that 51% and 39% of the variability in the clinical frequency of FQ-R gyrA mutation events in Lineage 2 and Lineage 4 strains, respectively, can be attributed to how Mtb evolves FQ-R in vitro. As the Mtb genetic background strongly influenced the evolution of FQ-R in vitro, we conclude that the genetic background of Mtb also impacts the evolution of FQ-R in the clinic.

Selective Inbreeding: Genetic Crosses Drive Apparent Adaptive Mutation in the Cairns-Foster System of Escherichia coli

The Escherichia coli system of Cairns and Foster employs a lac frameshift mutation that reverts rarely (10-9/cell/division) during unrestricted growth. However, when 108 cells are plated on lactose medium, the nongrowing lawn produces ∼50 Lac+ revertant colonies that accumulate linearly with time over 5 days. Revertants carry very few associated mutations. This behavior has been attributed to an evolved mechanism ("adaptive mutation" or "stress-induced mutagenesis") that responds to starvation by preferentially creating mutations that improve growth. We describe an alternative model, "selective inbreeding," in which natural selection acts during intercellular transfer of the plasmid that carries the mutant lac allele and the dinB gene for an error-prone polymerase. Revertant genome sequences show that the plasmid is more intensely mutagenized than the chromosome. Revertants vary widely in their number of plasmid and chromosomal mutations. Plasmid mutations are distributed evenly, but chromosomal mutations are focused near the replication origin. Rare, heavily mutagenized, revertants have acquired a plasmid tra mutation that eliminates conjugation ability. These findings support the new model, in which revertants are initiated by rare pre-existing cells (105) with many copies of the F'lac plasmid. These cells divide under selection, producing daughters that mate. Recombination between donor and recipient plasmids initiates rolling-circle plasmid over-replication, causing a mutagenic elevation of DinB level. A lac+ reversion event starts chromosome replication and mutagenesis by accumulated DinB. After reversion, plasmid transfer moves the revertant lac+ allele into an unmutagenized cell, and away from associated mutations. Thus, natural selection explains why mutagenesis appears stress-induced and directed.

Irregularities in genetic variation and mutation rates with environmental stresses

The appearance of new mutations is determined by the equilibrium between DNA error formation and repair. In bacteria like Escherichia coli, stresses are thought shift this balance towards increased mutagenesis. Recent findings, however, suggest a very uneven relationship between stress and mutations. Only a subset of stressful environments increase the net rate of mutation and different forms of nutritional stress (such as oxygen, carbon or phosphorus limitations) result in markedly different mutation rates after similar reductions in growth rate. Moreover, different stresses result in altered mutational spectra, with some increasing transposition and others increasing indel formation. Single-base substitution rates are lower with some stresses than in unstressed bacteria. Indeed, changes to the mix of mutations with stress are more widespread than a marked increase in net mutation rate. Much remains to be learned on how environments have unique mutational signatures and why some stresses are more mutagenic than others. Even beyond stress-induced genetic variation, the fundamental unresolved question in the stress-mutation relationship is the adaptive value of different types of mutations and mutation rates; is transposition, for example, more advantageous under anaerobic conditions? It remains to be investigated whether stress-specific genetic variation impacts on evolvability differentially in distinct environments.

Real-time visualization of mutations and their fitness effects in single bacteria

Mutations are the driving force of evolution and the source of important pathologies. The characterization of the dynamics and effects of mutations on fitness is therefore central to our understanding of evolution and to human health. This protocol describes how to implement two methods that we recently developed: mutation visualization (MV) and microfluidic mutation accumulation (µMA), which allow the occurrence of mutations created by DNA replication errors (MV) and the evolution of cell fitness during MA (µMA) to be followed directly in individual cells of Escherichia coli. MV provides a quantitative characterization of the dynamics of mutation occurrences, and µMA allows precise estimation of the distribution of fitness effects (DFEs) of mutations. Both methods use microfluidics and time-lapse microscopy, and a fluorescent mismatch repair (MMR) MutL protein is used as a marker for nascent mutations. Here, we present a single protocol describing how to implement the MV and µMA methods, including detailed procedures for microfluidic setup installation, data acquisition and data analysis and interpretation. Using this procedure, the microfluidic setup installation can be completed within 1 d, and automated data acquisition takes 2-4 d.

Antibiotic-Induced Genetic Variation: How It Arises and How It Can Be Prevented

By targeting essential cellular processes, antibiotics provoke metabolic perturbations and induce stress responses and genetic variation in bacteria. Here we review current knowledge of the mechanisms by which these molecules generate genetic instability. They include production of reactive oxygen species, as well as induction of the stress response regulons, which lead to enhancement of mutation and recombination rates and modulation of horizontal gene transfer. All these phenomena influence the evolution and spread of antibiotic resistance. The use of strategies to stop or decrease the generation of resistant variants is also discussed.

Gamblers: An Antibiotic-Induced Evolvable Cell Subpopulation Differentiated by Reactive-Oxygen-Induced General Stress Response

Antibiotics can induce mutations that cause antibiotic resistance. Yet, despite their importance, mechanisms of antibiotic-promoted mutagenesis remain elusive. We report that the fluoroquinolone antibiotic ciprofloxacin (cipro) induces mutations by triggering transient differentiation of a mutant-generating cell subpopulation, using reactive oxygen species (ROS). Cipro-induced DNA breaks activate the Escherichia coli SOS DNA-damage response and error-prone DNA polymerases in all cells. However, mutagenesis is limited to a cell subpopulation in which electron transfer together with SOS induce ROS, which activate the sigma-S (σS) general-stress response, which allows mutagenic DNA-break repair. When sorted, this small σS-response-"on" subpopulation produces most antibiotic cross-resistant mutants. A U.S. Food and Drug Administration (FDA)-approved drug prevents σS induction, specifically inhibiting antibiotic-promoted mutagenesis. Further, SOS-inhibited cell division, which causes multi-chromosome cells, promotes mutagenesis. The data support a model in which within-cell chromosome cooperation together with development of a "gambler" cell subpopulation promote resistance evolution without risking most cells.

Yeast Spontaneous Mutation Rate and Spectrum Vary with Environment

Mutation is the ultimate genetic source of evolution and biodiversity, but to what extent the environment impacts mutation rate and spectrum is poorly understood. Past studies discovered mutagenesis induced by antibiotic treatment or starvation, but its relevance and importance to long-term evolution is unclear because these severe stressors typically halt cell growth and/or cause substantial cell deaths. Here, we quantify the mutation rate and spectrum in Saccharomyces cerevisiae by whole-genome sequencing following mutation accumulation in each of seven environments with relatively rapid cell growths and minimal cell deaths. We find the point mutation rate per generation to differ by 3.6-fold among the seven environments, generally increasing in environments with slower cell growths. This trend renders the mutation rate per year more constant than that per generation across environments, which has implications for neutral evolution and the molecular clock. Additionally, we find substantial among-environment variations in mutation spectrum, such as the transition to transversion ratio and AT mutational bias. Other main mutation types, including small insertion or deletion, segmental duplication or deletion, and chromosome gain or loss also tend to occur more frequently in environments where yeast grows more slowly. In contrast to these findings from the nuclear genome, the yeast mitochondrial mutation rate rises with the growth rate, consistent with the metabolic rate hypothesis. Together, these observations indicate that environmental changes, which are ubiquitous in nature, influence not only natural selection, but also the amount and type of mutations available to selection, and suggest that ignoring the latter impact, as is currently practiced, may mislead evolutionary inferences.