The Fitness of Beta-Lactamase Mutants Depends Nonlinearly on Resistance Level at Sublethal Antibiotic Concentrations.

Adaptive evolutionary processes are constrained by the availability of mutations which cause a fitness benefit and together make up the fitness landscape, which maps genotype space onto fitness under specified conditions. Experimentally derived fitness landscapes have demonstrated a predictability to evolution by identifying limited "mutational routes" that evolution by natural selection may take between low and high-fitness genotypes. However, such studies often utilize indirect measures to determine fitness. We estimated the competitive fitness of mutants relative to all single-mutation neighbors to describe the fitness landscape of three mutations in a ß-lactamase enzyme. Fitness assays were performed at sublethal concentrations of the antibiotic cefotaxime in a structured and unstructured environment. In the unstructured environment, the antibiotic selected for higher-resistance types-but with an equivalent fitness for a subset of mutants, despite substantial variation in resistance-resulting in a stratified fitness landscape. In contrast, in a structured environment with a low antibiotic concentration, antibiotic-susceptible genotypes had a relative fitness advantage, which was associated with antibiotic-induced filamentation. These results cast doubt that highly resistant genotypes have a unique selective advantage in environments with subinhibitory concentrations of antibiotics and demonstrate that direct fitness measures are required for meaningful predictions of the accessibility of evolutionary routes. IMPORTANCE The evolution of antibiotic-resistant bacterial populations underpins the ongoing antibiotic resistance crisis. We aim to understand how antibiotic-degrading enzymes can evolve to cause increased resistance, how this process is constrained, and whether it can be predictable. To this end, competition experiments were performed with a combinatorially complete set of mutants of a ß-lactamase gene subject to subinhibitory concentrations of the antibiotic cefotaxime. While some mutations confer on their hosts high resistance to cefotaxime, in competition these mutations do not always confer a selective advantage. Specifically, high-resistance mutants had equivalent fitnesses despite different resistance levels and even had selective disadvantages under conditions involving spatial structure. Together, our findings suggest that the relationship between resistance level and fitness at subinhibitory concentrations is complex; predicting the evolution of antibiotic resistance requires knowledge of the conditions that select for resistant genotypes and the selective advantage evolved types have over their predecessors.

Minimal Surviving Inoculum in Collective Antibiotic Resistance.

A common strategy used by bacteria to resist antibiotics is enzymatic degradation or modification. This reduces the antibiotic threat in the environment and is therefore potentially a collective mechanism that also enhances the survival of nearby cells. Collective resistance is of clinical significance, yet a quantitative understanding at the population level is still incomplete. Here, we develop a general theoretical framework of collective resistance by antibiotic degradation. Our modeling study reveals that population survival crucially depends on the ratio of timescales of two processes: the rates of population death and antibiotic removal. However, it is insensitive to molecular, biological, and kinetic details of the underlying processes that give rise to these timescales. Another important aspect of antibiotic degradation is the degree of cooperativity, related to the permeability of the cell wall to antibiotics and enzymes. These observations motivate a coarse-grained, phenomenological model, with two compound parameters representing the population's race to survival and single-cell effective resistance. We propose a simple experimental assay to measure the dose-dependent minimal surviving inoculum and apply it to Escherichia coli expressing several types of ß-lactamase. Experimental data analyzed within the theoretical framework corroborate it with good agreement. Our simple model may serve as a reference for more complex situations, such as heterogeneous bacterial communities. IMPORTANCE Collective resistance occurs when bacteria work together to decrease the concentration of antibiotics in their environment, for example, by actively breaking down or modifying them. This can help bacteria survive by reducing the effective antibiotic concentration below their threshold for growth. In this study, we used mathematical modeling to examine the factors that influence collective resistance and to develop a framework to understand the minimum population size needed to survive a given initial antibiotic concentration. Our work helps to identify generic mechanism-independent parameters that can be derived from population data and identifies combinations of parameters that play a role in collective resistance. Specifically, it highlights the relative timescales involved in the survival of populations that inactivate antibiotics, as well as the levels of cooperation versus privatization. The results of this study contribute to our understanding of population-level effects on antibiotic resistance and may inform the design of antibiotic therapies.

Interaction between mutation type and gene pleiotropy drives parallel evolution in the laboratory.

What causes evolution to be repeatable is a fundamental question in evolutionary biology. Pleiotropy, i.e. the effect of an allele on multiple traits, is thought to enhance repeatability by constraining the number of available beneficial mutations. Additionally, pleiotropy may promote repeatability by allowing large fitness benefits of single mutations via adaptive combinations of phenotypic effects. Yet, this latter evolutionary potential may be reaped solely by specific types of mutations able to realize optimal combinations of phenotypic effects while avoiding the costs of pleiotropy. Here, we address the interaction of gene pleiotropy and mutation type on evolutionary repeatability in a meta-analysis of experimental evolution studies with Escherichia coli. We hypothesize that single nucleotide polymorphisms (SNPs) are principally able to yield large fitness benefits by targeting highly pleiotropic genes, whereas indels and structural variants (SVs) provide smaller benefits and are restricted to genes with lower pleiotropy. By using gene connectivity as proxy for pleiotropy, we show that non-disruptive SNPs in highly pleiotropic genes yield the largest fitness benefits, since they contribute more to parallel evolution, especially in large populations, than inactivating SNPs, indels and SVs. Our findings underscore the importance of considering genetic architecture together with mutation type for understanding evolutionary repeatability. This article is part of the theme issue 'Interdisciplinary approaches to predicting evolutionary biology'.

Towards evolutionary predictions: Current promises and challenges.

Evolution has traditionally been a historical and descriptive science, and predicting future evolutionary processes has long been considered impossible. However, evolutionary predictions are increasingly being developed and used in medicine, agriculture, biotechnology and conservation biology. Evolutionary predictions may be used for different purposes, such as to prepare for the future, to try and change the course of evolution or to determine how well we understand evolutionary processes. Similarly, the exact aspect of the evolved population that we want to predict may also differ. For example, we could try to predict which genotype will dominate, the fitness of the population or the extinction probability of a population. In addition, there are many uses of evolutionary predictions that may not always be recognized as such. The main goal of this review is to increase awareness of methods and data in different research fields by showing the breadth of situations in which evolutionary predictions are made. We describe how diverse evolutionary predictions share a common structure described by the predictive scope, time scale and precision. Then, by using examples ranging from SARS-CoV2 and influenza to CRISPR-based gene drives and sustainable product formation in biotechnology, we discuss the methods for predicting evolution, the factors that affect predictability and how predictions can be used to prevent evolution in undesirable directions or to promote beneficial evolution (i.e. evolutionary control). We hope that this review will stimulate collaboration between fields by establishing a common language for evolutionary predictions.

Population dynamics of cross-protection against ß-lactam antibiotics in droplet microreactors.

Introduction: Bacterial strains that are resistant to antibiotics may protect not only themselves, but also sensitive bacteria nearby if resistance involves antibiotic degradation. Such cross-protection poses a challenge to effective antibiotic therapy by enhancing the long-term survival of bacterial infections, however, the current understanding is limited. Methods: In this study, we utilize an automated nanoliter droplet analyzer to study the interactions between Escherichia coli strains expressing a ß-lactamase (resistant) and those not expressing it (sensitive) when exposed to the ß-lactam antibiotic cefotaxime (CTX), with the aim to define criteria contributing to cross-protection. Results: We observed a cross-protection window of CTX concentrations for the sensitive strain, extending up to approximately 100 times its minimal inhibitory concentration (MIC). Through both microscopy and enzyme activity analyses, we demonstrate that bacterial filaments, triggered by antibiotic stress, contribute to cross-protection. Discussion: The antibiotic concentration window for cross-protection depends on the difference in ß-lactamase activity between co-cultured strains: larger differences shift the 'cross-protection window' toward higher CTX concentrations. Our findings highlight the dependence of opportunities for cross-protection on the relative resistance levels of the strains involved and suggest a possible specific role for filamentation.

Succession in the caecal microbiota of developing broilers colonised by extended-spectrum ß-lactamase-producing Escherichia coli.

BACKGROUND: Broilers are among the most common and dense poultry production systems, where antimicrobials have been used extensively to promote animal health and performance. The continuous usage of antimicrobials has contributed to the appearance of resistant bacteria, such as extended-spectrum ß-lactamase-producing Escherichia coli (ESBL-Ec). Here, we studied the ESBL-Ec prevalence and successional dynamics of the caecal microbiota of developing broilers in a commercial flock during their production life cycle (0-35 days). Broilers were categorised as ESBL-Ec colonised (ESBL-Ec+) or ESBL-Ec non-colonised (ESBL-Ec-) by selective culturing. Using 16S rRNA gene sequencing, we i. compared the richness, evenness and composition of the caecal microbiota of both broilers' groups and ii. assessed the combined role of age and ESBL-Ec status on the broilers' caecal microbiota. RESULTS: From day two, we observed an increasing linear trend in the proportions of ESBL-Ec throughout the broilers' production life cycle, X2 (1, N = 12) = 28.4, p < 0.001. Over time, the caecal microbiota richness was consistently higher in ESBL-Ec- broilers, but significant differences between both broilers' groups were found exclusively on day three (Wilcoxon rank-sum test, p = 0.016). Bray-Curtis distance-based RDA (BC-dbRDA) showed no explanatory power of ESBL-Ec status, while age explained 14% of the compositional variation of the caecal microbiota, F (2, 66) = 6.47, p = 0.001. CONCLUSIONS: This study assessed the role of ESBL-Ec in the successional dynamics of the caecal microbiota in developing broilers and showed that the presence of ESBL-Ec is associated with mild but consistent reductions in alpha diversity and with transient bacterial compositional differences. We also reported the clonal spread of ESBL-Ec and pointed to the farm environment as a likely source for ESBLs.

Stochastic establishment of ß-lactam-resistant Escherichia coli mutants reveals conditions for collective resistance.

For antibiotic resistance to arise, new resistant mutants must establish in a bacterial population before they can spread via natural selection. Comprehending the stochastic factors that influence mutant establishment is crucial for a quantitative understanding of antibiotic resistance emergence. Here, we quantify the single-cell establishment probability of four Escherichia coli strains expressing ß-lactamase alleles with different activity against the antibiotic cefotaxime, as a function of antibiotic concentration in both unstructured (liquid) and structured (agar) environments. We show that concentrations well below the minimum inhibitory concentration (MIC) can substantially hamper establishment, particularly for highly resistant mutants. While the pattern of establishment suppression is comparable in both tested environments, we find greater variability in establishment probability on agar. Using a simple branching model, we investigate possible sources of this stochasticity, including environment-dependent lineage variability, but cannot reject other possible causes. Lastly, we use the single-cell establishment probability to predict each strain's MIC in the absence of social interactions. We observe substantially higher measured than predicted MIC values, particularly for highly resistant strains, which indicates cooperative effects among resistant cells at large cell numbers, such as in standard MIC assays.

Estimating plasmid conjugation rates: A new computational tool and a critical comparison of methods.

Plasmids are important vectors for the spread of genes among diverse populations of bacteria. However, there is no standard method to determine the rate at which they spread horizontally via conjugation. Here, we compare commonly used methods on simulated and experimental data, and show that the resulting conjugation rate estimates often depend strongly on the time of measurement, the initial population densities, or the initial ratio of donor to recipient populations. Differences in growth rate, e.g. induced by sub-lethal antibiotic concentrations or temperature, can also significantly bias conjugation rate estimates. We derive a new 'end-point' measure to estimate conjugation rates, which extends the well-known Simonsen method to include the effects of differences in population growth and conjugation rates from donors and transconjugants. We further derive analytical expressions for the parameter range in which these approximations remain valid. We present an easy to use R package and web interface which implement both new and previously existing methods to estimate conjugation rates. The result is a set of tools and guidelines for accurate and comparable measurement of plasmid conjugation rates.

Population size mediates the contribution of high-rate and large-benefit mutations to parallel evolution.

Mutations with large fitness benefits and mutations occurring at high rates may both cause parallel evolution, but their contribution is predicted to depend on population size. Moreover, high-rate and large-benefit mutations may have different long-term adaptive consequences. We show that small and 100-fold larger bacterial populations evolve resistance to a ß-lactam antibiotic by using similar numbers, but different types of mutations. Small populations frequently substitute similar high-rate structural variants and loss-of-function point mutations, including the deletion of a low-activity ß-lactamase, and evolve modest resistance levels. Large populations more often use low-rate, large-benefit point mutations affecting the same targets, including mutations activating the ß-lactamase and other gain-of-function mutations, leading to much higher resistance levels. Our results demonstrate the separation by clonal interference of mutation classes with divergent adaptive consequences, causing a shift from high-rate to large-benefit mutations with increases in population size.

Second compartment widens plasmid invasion conditions: Two-compartment pair-formation model of conjugation in the gut.

Understanding under which conditions conjugative plasmids encoding antibiotic resistance can invade bacterial communities in the gut is of particular interest to combat the spread of antibiotic resistance within and between animals and humans. We extended a one-compartment model of conjugation to a two-compartment model, to analyse how differences in plasmid dynamics in the gut lumen and at the gut wall affect the invasion of plasmids. We compared scenarios with one and two compartments, different migration rates between the lumen and wall compartments, and different population dynamics. We focused on the effect of attachment and detachment rates on plasmid dynamics, explicitly describing pair formation followed by plasmid transfer in the pairs. The parameter space allowing plasmid invasion in the one-compartment model is affected by plasmid costs and intrinsic conjugation rates of the transconjugant, but not by these characteristics of the donor. The parameter space allowing plasmid invasion in the two-compartment model is affected by attachment and detachment rates in the lumen and wall compartment, and by the bacterial density at the wall. The one- and two-compartment models predict the same parameter space for plasmid invasion if the conditions in both compartments are equal to the conditions in the one-compartment model. In contrast, the addition of the wall compartment widens the parameter space allowing invasion compared with the one-compartment model, if the density at the wall is higher than in the lumen, or if the attachment rate at the wall is high and the detachment rate at the wall is low. We also compared the pair-formation models with bulk-conjugation models that describe conjugation by instantaneous transfer of the plasmid at contact between cells, without explicitly describing pair formation. Our results show that pair-formation and bulk-conjugation models predict the same parameter space for plasmid invasion. From our simulations, we conclude that conditions at the gut wall should be taken into account to describe plasmid dynamics in the gut and that transconjugant characteristics rather than donor characteristics should be used to parameterize the models.

Chicken gut microbiome members limit the spread of an antimicrobial resistance plasmid in Escherichia coli.

Plasmid-mediated antimicrobial resistance is a major contributor to the spread of resistance genes within bacterial communities. Successful plasmid spread depends upon a balance between plasmid fitness effects on the host and rates of horizontal transmission. While these key parameters are readily quantified in vitro, the influence of interactions with other microbiome members is largely unknown. Here, we investigated the influence of three genera of lactic acid bacteria (LAB) derived from the chicken gastrointestinal microbiome on the spread of an epidemic narrow-range ESBL resistance plasmid, IncI1 carrying blaCTX-M-1, in mixed cultures of isogenic Escherichia coli strains. Secreted products of LAB decreased E. coli growth rates in a genus-specific manner but did not affect plasmid transfer rates. Importantly, we quantified plasmid transfer rates by controlling for density-dependent mating opportunities. Parametrization of a mathematical model with our in vitro estimates illustrated that small fitness costs of plasmid carriage may tip the balance towards plasmid loss under growth conditions in the gastrointestinal tract. This work shows that microbial interactions can influence plasmid success and provides an experimental-theoretical framework for further study of plasmid transfer in a microbiome context.

Antibiotic Breakdown by Susceptible Bacteria Enhances the Establishment of ß-Lactam Resistant Mutants.

For a better understanding of the evolution of antibiotic resistance, it is imperative to study the factors that determine the initial establishment of mutant resistance alleles. In addition to the antibiotic concentration, the establishment of resistance alleles may be affected by interactions with the surrounding susceptible cells from which they derive, for instance via the release of nutrients or removal of the antibiotic. Here, we investigate the effects of social interactions with surrounding susceptible cells on the establishment of Escherichia coli mutants with increasing ß-lactamase activity (i.e., the capacity to hydrolyze ß-lactam antibiotics) from single cells under the exposure of the antibiotic cefotaxime (CTX) on agar plates. We find that relatively susceptible cells, expressing a ß-lactamase with very low antibiotic-hydrolyzing activity, increase the probability of mutant cells to survive and outgrow into colonies due to the active breakdown of the antibiotic. However, the rate of breakdown by the susceptible strain is much higher than expected based on its low enzymatic activity. A detailed theoretical model suggests that this observation may be explained by cell filamentation causing delayed lysis. While susceptible cells may hamper the spread of higher-resistant ß-lactamase mutants at relatively high frequencies, our findings show that they promote their initial establishment.

Choice of ß-Lactam Resistance Pathway Depends Critically on Initial Antibiotic Concentration.

Antibiotic resistance trajectories with different final resistance may critically depend on the first mutation, due to epistatic interactions. Here, we study the effect of mutation bias and the concentration-dependent effects on fitness of two clinically important mutations in TEM-1 ß-lactamase in initiating alternative trajectories to cefotaxime resistance. We show that at low cefotaxime concentrations, the R164S mutation (a mutation of arginine to serine at position 164), which confers relatively low resistance, is competitively superior to the G238S mutation, conferring higher resistance, thus highlighting a critical influence of antibiotic concentration on long-term resistance evolution.

Coexistence of fluorescent Escherichia coli strains in millifluidic droplet reactors.

Understanding competition and cooperation within microbiota is of high fundamental and clinical importance, helping to comprehend species' evolution and biodiversity. We co-encapsulated and cultured two isogenic Escherichia coli strains expressing blue (BFP) and yellow (YFP) fluorescent proteins into numerous emulsion droplets and quantified their growth by employing fluorescence measurements. To characterize and compare the bacterial growth kinetics and behavior in mono and co-culture, we compared the experimental observations with predictions from a simple growth model. Varying the initial ratio (R0) of both cell types injected, we observed a broad landscape from competition to cooperation between both strains in their confined microenvironments depending on start frequency: from a nearly symmetric situation at R0 = 1, up to the domination of one subpopulation when R0 ≫ 1 (or R0 ≪ 1). Due to competition between the strains, their doubling times and final biomass ratios (R1) continuously deviate from the monoculture behavior. The correlation map of the two strains' doubling times reveals that the R0 is one of the critical parameters affecting the competitive interaction between isogenic bacterial strains. Thanks to this strategy, different species of bacteria can be monitored simultaneously in real-time. Further advantages include high statistical output, unaffected bacteria growth, and long-time measurements in a well-mixed environment. We expect that the millifluidic droplet-based reactor can be utilized for practical clinical applications, such as bacterial antibiotic resistance and enzyme reaction kinetics studies.

Clonal Interference and Mutation Bias in Small Bacterial Populations in Droplets.

Experimental evolution studies have provided key insights into the fundamental mechanisms of evolution. One striking observation is that parallel and convergent evolution during laboratory evolution can be surprisingly common. However, these experiments are typically performed with well-mixed cultures and large effective population sizes, while pathogenic microbes typically experience strong bottlenecks during infection or drug treatment. Yet, our knowledge about adaptation in very small populations, where selection strength and mutation supplies are limited, is scant. In this study, wild-type and mutator strains of the bacterium Escherichia coli were evolved for about 100 generations towards increased resistance to the ß-lactam antibiotic cefotaxime in millifluidic droplets of 0.5 µL and effective population size of approximately 27,000 cells. The small effective population size limited the adaptive potential of wild-type populations, where adaptation was limited to inactivating mutations, which caused the increased production of outer-membrane vesicles, leading to modest fitness increases. In contrast, mutator clones with an average of ~30-fold higher mutation rate adapted much faster by acquiring both inactivating mutations of an outer-membrane porin and particularly inactivating and gain-of-function mutations, causing the upregulation or activation of a common efflux pump, respectively. Our results demonstrate how in very small populations, clonal interference and mutation bias together affect the choice of adaptive trajectories by mediating the balance between high-rate and large-benefit mutations.

Effect of donor-recipient relatedness on the plasmid conjugation frequency: a meta-analysis.

BACKGROUND: Conjugation plays a major role in the transmission of plasmids encoding antibiotic resistance genes in both clinical and general settings. The conjugation efficiency is influenced by many biotic and abiotic factors, one of which is the taxonomic relatedness between donor and recipient bacteria. A comprehensive overview of the influence of donor-recipient relatedness on conjugation is still lacking, but such an overview is important to quantitatively assess the risk of plasmid transfer and the effect of interventions which limit the spread of antibiotic resistance, and to obtain parameter values for conjugation in mathematical models. Therefore, we performed a meta-analysis on reported conjugation frequencies from Escherichia coli donors to various recipient species. RESULTS: Thirty-two studies reporting 313 conjugation frequencies for liquid broth matings and 270 conjugation frequencies for filter matings were included in our meta-analysis. The reported conjugation frequencies varied over 11 orders of magnitude. Decreasing taxonomic relatedness between donor and recipient bacteria, when adjusted for confounding factors, was associated with a lower conjugation frequency in liquid matings. The mean conjugation frequency for bacteria of the same order, the same class, and other classes was 10, 20, and 789 times lower than the mean conjugation frequency within the same species, respectively. This association between relatedness and conjugation frequency was not found for filter matings. The conjugation frequency was furthermore found to be influenced by temperature in both types of mating experiments, and in addition by plasmid incompatibility group in liquid matings, and by recipient origin and mating time in filter matings. CONCLUSIONS: In our meta-analysis, taxonomic relatedness is limiting conjugation in liquid matings, but not in filter matings, suggesting that taxonomic relatedness is not a limiting factor for conjugation in environments where bacteria are fixed in space.

Unraveling the causes of adaptive benefits of synonymous mutations in TEM-1 ß-lactamase.

While synonymous mutations were long thought to be without phenotypic consequences, there is growing evidence they can affect gene expression, protein folding, and ultimately the fitness of an organism. In only a few cases have the mechanisms by which synonymous mutations affect the phenotype been elucidated. We previously identified 48 mutations in TEM-1 ß-lactamase that increased resistance of Escherichia coli to cefotaxime, 10 of which were synonymous. To better understand the molecular mechanisms underlying the beneficial effect of these synonymous mutations, we made a series of measurements for a panel containing the 10 synonymous together with 10 non-synonymous mutations as a reference. Whereas messenger levels were unaffected, we found that total and functional TEM protein levels were higher for 5 out of 10 synonymous mutations. These observations suggest that some of these mutations act on translation or a downstream process. Similar effects were observed for some small-benefit non-synonymous mutations, suggesting a similar causal mechanism. For the synonymous mutations, we found that the cost of resistance scales with TEM protein levels. A resistance landscape for four synonymous mutations revealed strong epistasis: none of the combinations of mutations exceeded the resistance of the largest-effect mutation and there were synthetically neutral combinations. By considering combined effects of these mutations, we could infer that functional TEM protein level is a multi-dimensional phenotype. These results suggest that synonymous mutations may have beneficial effects by increasing the expression of an enzyme with low substrate activity, which may be realized via multiple, yet unknown, post-transcriptional mechanisms.

[Polymicrobial infections: ecosystems with special properties]. / Polymicrobiële infecties: ecosystemen met bijzondere eigenschappen.

Bacteria often live together in complex communities. Insight into these microbial ecosystems is essential to make it possible to intervene when these ecosystems lead to disease. Bacteria do not only respond to their host, but they also affect each other, which may have far-reaching consequences for the course of the disease. In this article we describe that clinical isolates in a polymicrobial infection can be seen as ecosystems. These ecosystems often have properties that separate isolates do not have; they may, for example, be more virulent or more resistant to antibiotics. We therefore emphasise that the whole is greater than the sum of its parts, even for infections.