Host-specific plasmid evolution explains the variable spread of clinical antibiotic-resistance plasmids.

Antibiotic resistance encoded on plasmids is a pressing global health problem. Predicting which plasmids spread in the long term remains very challenging, even though some key parameters influencing plasmid stability have been identified, such as plasmid growth costs and horizontal transfer rates. Here, we show these parameters evolve in a strain-specific way among clinical plasmids and bacteria, and this occurs rapidly enough to alter the relative likelihoods of different bacterium-plasmid combinations spreading. We used experiments with Escherichia coli and antibiotic-resistance plasmids isolated from patients, paired with a mathematical model, to track long-term plasmid stability (beyond antibiotic exposure). Explaining variable stability across six bacterium-plasmid combinations required accounting for evolutionary changes in plasmid stability traits, whereas initial variation of these parameters was a relatively poor predictor of long-term outcomes. Evolutionary trajectories were specific to particular bacterium-plasmid combinations, as evidenced by genome sequencing and genetic manipulation. This revealed epistatic (here, strain-dependent) effects of key genetic changes affecting horizontal plasmid transfer. Several genetic changes involved mobile elements and pathogenicity islands. Rapid strain-specific evolution can thus outweigh ancestral phenotypes as a predictor of plasmid stability. Accounting for strain-specific plasmid evolution in natural populations could improve our ability to anticipate and manage successful bacterium-plasmid combinations.

Community composition of bacteria isolated from Swiss banknotes varies depending on collection environment.

Humans interact constantly with surfaces and associated microbial communities in the environment. The factors shaping the composition of these communities are poorly understood: some proposed explanations emphasize the influence of local habitat conditions (niche-based explanations), while others point to geographic structure and the distance among sampled locations (dispersal-based explanations). However, the relative roles of these different drivers for microbial community assembly on human-associated surfaces are not clear. Here, we used a combination of sampling, sequencing (16S rRNA) and culturing to show that the composition of banknote-associated bacterial communities varies depending on the local collection environment. Using banknotes collected from various locations and types of shops across Switzerland, we found taxonomic diversity dominated by families such as Pseudomonadaceae and Staphylococcaceae, but with banknote samples from particular types of shops (especially butcher shops) having distinct community structure. By contrast, we found no evidence of geographic structure: similarity of community composition did not decrease with increasing distance among sampled locations. These results show that microbial communities associated with banknotes, one of the most commonly encountered and exchanged human-associated surfaces, can reflect the local environmental conditions (in this case, the type of shop), and the signal for this type of variation was stronger than that for geographic structure among the locations sampled here.

Clinical antibiotic-resistance plasmids have small effects on biofilm formation and population growth in Escherichia coli in vitro.

Antimicrobial resistance (AR) mechanisms encoded on plasmids can affect other phenotypic traits in bacteria, including biofilm formation. These effects may be important contributors to the spread of AR and the evolutionary success of plasmids, but it is not yet clear how common such effects are for clinical plasmids/bacteria, and how they vary among different plasmids and host strains. Here, we used a combinatorial approach to test the effects of clinical AR plasmids on biofilm formation and population growth in clinical and laboratory Escherichia coli strains. In most of the 25 plasmid-bacterium combinations tested, we observed no significant change in biofilm formation upon plasmid introduction, contrary to the notion that plasmids frequently alter biofilm formation. In a few cases we detected altered biofilm formation, and these effects were specific to particular plasmid-bacterium combinations. By contrast, we found a relatively strong effect of a chromosomal streptomycin-resistance mutation (in rpsL) on biofilm formation. Further supporting weak and host-strain-dependent effects of clinical plasmids on bacterial phenotypes in the combinations we tested, we found growth costs associated with plasmid carriage (measured in the absence of antibiotics) were moderate and varied among bacterial strains. These findings suggest some key clinical resistance plasmids cause only mild phenotypic disruption to their host bacteria, which may contribute to the persistence of plasmids in the absence of antibiotics.

Resident microbial communities inhibit growth and antibiotic-resistance evolution of Escherichia coli in human gut microbiome samples.

Countering the rise of antibiotic-resistant pathogens requires improved understanding of how resistance emerges and spreads in individual species, which are often embedded in complex microbial communities such as the human gut microbiome. Interactions with other microorganisms in such communities might suppress growth and resistance evolution of individual species (e.g., via resource competition) but could also potentially accelerate resistance evolution via horizontal transfer of resistance genes. It remains unclear how these different effects balance out, partly because it is difficult to observe them directly. Here, we used a gut microcosm approach to quantify the effect of three human gut microbiome communities on growth and resistance evolution of a focal strain of Escherichia coli. We found the resident microbial communities not only suppressed growth and colonisation by focal E. coli but also prevented it from evolving antibiotic resistance upon exposure to a beta-lactam antibiotic. With samples from all three human donors, our focal E. coli strain only evolved antibiotic resistance in the absence of the resident microbial community, even though we found resistance genes, including a highly effective resistance plasmid, in resident microbial communities. We identified physical constraints on plasmid transfer that can explain why our focal strain failed to acquire some of these beneficial resistance genes, and we found some chromosomal resistance mutations were only beneficial in the absence of the resident microbiota. This suggests, depending on in situ gene transfer dynamics, interactions with resident microbiota can inhibit antibiotic-resistance evolution of individual species.

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.

Transition bias influences the evolution of antibiotic resistance in Mycobacterium tuberculosis.

Transition bias, an overabundance of transitions relative to transversions, has been widely reported among studies of the rates and spectra of spontaneous mutations. However, demonstrating the role of transition bias in adaptive evolution remains challenging. In particular, it is unclear whether such biases direct the evolution of bacterial pathogens adapting to treatment. We addressed this challenge by analyzing adaptive antibiotic-resistance mutations in the major human pathogen Mycobacterium tuberculosis (MTB). We found strong evidence for transition bias in two independently curated data sets comprising 152 and 208 antibiotic-resistance mutations. This was true at the level of mutational paths (distinct adaptive DNA sequence changes) and events (individual instances of the adaptive DNA sequence changes) and across different genes and gene promoters conferring resistance to a diversity of antibiotics. It was also true for mutations that do not code for amino acid changes (in gene promoters and the 16S ribosomal RNA gene rrs) and for mutations that are synonymous to each other and are therefore likely to have similar fitness effects, suggesting that transition bias can be caused by a bias in mutation supply. These results point to a central role for transition bias in determining which mutations drive adaptive antibiotic resistance evolution in a key pathogen.

Rapid decline of adaptation of Pseudomonas fluorescens to soil biotic environment.

Interactions between microbes can both constrain and enhance their adaptation to the environment. However, most studies to date have employed simplified microbial communities and environmental conditions. We determined how the presence of a commercial potting compost microbial community affected adaptation of the soil bacterium Pseudomonas fluorescens SBW25 in potting compost. Pseudomonas fluorescens clones isolated from populations evolved in both the presence and absence of the community showed similar fitness increases when measured in the absence of the community. This suggests the presence of the community did not constrain adaptation. By contrast, fitness measured in the presence of the community increased for community-evolved populations, but decreased below the ancestral state for populations evolved in the absence of the community. This suggests some, but not all, mutations that were beneficial with respect to the abiotic environment were costly in the presence of the community, with the former selected against in the presence of the community. Whole-genome sequencing supports this interpretation: most mutations underpinning fitness changes were clone-specific, suggesting multiple genetic pathways to adaptation. Such extreme mutational effects have not been observed in comparable in vitro studies, suggesting that caution is needed when extrapolating results from simplified in vitro systems to natural contexts.

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.

Associations between sensitivity to antibiotics, disinfectants and heavy metals in natural, clinical and laboratory isolates of Escherichia coli.

Bacteria in nature often encounter non-antibiotic antibacterials (NAAs), such as disinfectants and heavy metals, and they can evolve resistance via mechanisms that are also involved in antibiotic resistance. Understanding whether susceptibility to different types of antibacterials is non-randomly associated across natural and clinical bacteria is therefore important for predicting the spread of resistance, yet there is no consensus about the extent of such associations or underlying mechanisms. We tested for associations between susceptibility phenotypes of 93 natural and clinical Escherichia coli isolates to various NAAs and antibiotics. Across all compound combinations, we detected a small number of non-random associations, including a trio of positive associations among chloramphenicol, triclosan and benzalkonium chloride. We investigated genetic mechanisms that can explain such associations using genomic information, genetic knockouts and experimental evolution. This revealed some mutations that are selected for by experimental exposure to one compound and confer cross-resistance to other compounds. Surprisingly, these interactions were asymmetric: selection for chloramphenicol resistance conferred cross-resistance to triclosan and benzalkonium chloride, but selection for triclosan resistance did not confer cross-resistance to other compounds. These results identify genetic changes involved in variable cross-resistance across antibiotics and NAAs, potentially contributing to associations in natural and clinical bacteria.

Resistance Gene Carriage Predicts Growth of Natural and Clinical Escherichia coli Isolates in the Absence of Antibiotics.

Bacterial pathogens that carry antibiotic resistance alleles sometimes pay a cost in the form of impaired growth in antibiotic-free conditions. This cost of resistance is expected to be a key parameter for understanding how resistance spreads and persists in pathogen populations. Analysis of individual resistance alleles from laboratory evolution and natural isolates has shown they are typically costly, but these costs are highly variable and influenced by genetic variation at other loci. It therefore remains unclear how strongly resistance is linked to impaired antibiotic-free growth in bacteria from natural and clinical scenarios, where resistance alleles are likely to coincide with other types of genetic variation. To investigate this, we measured the growth of 92 natural and clinical Escherichia coli isolates across three antibiotic-free environments. We then tested whether variation of antibiotic-free growth among isolates was predicted by their resistance to 10 antibiotics, while accounting for the phylogenetic structure of the data. We found that isolates with similar resistance profiles had similar antibiotic-free growth profiles, but it was not simply that higher average resistance was associated with impaired growth. Next, we used whole-genome sequences to identify antibiotic resistance genes and found that isolates carrying a greater number of resistance gene types grew relatively poorly in antibiotic-free conditions, even when the resistance genes they carried were different. This suggests that the resistance of bacterial pathogens is linked to growth costs in nature, but it is the total genetic burden and multivariate resistance phenotype that predict these costs, rather than individual alleles or mean resistance across antibiotics.IMPORTANCE Managing the spread of antibiotic resistance in bacterial pathogens is a major challenge for global public health. Central to this challenge is understanding whether resistance is linked to impaired bacterial growth in the absence of antibiotics, because this determines whether resistance declines when bacteria are no longer exposed to antibiotics. We studied 92 isolates of the key bacterial pathogen Escherichia coli; these isolates varied in both their antibiotic resistance genes and other parts of the genome. Taking this approach, rather than focusing on individual genetic changes associated with resistance as in much previous work, revealed that growth without antibiotics was linked to the number of specialized resistance genes carried and the combination of antibiotics to which isolates were resistant but was not linked to average antibiotic resistance. This approach provides new insights into the genetic factors driving the long-term persistence of antibiotic-resistant bacteria, which is important for future efforts to predict and manage resistance.

Adaptation to Parasites and Costs of Parasite Resistance in Mutator and Nonmutator Bacteria.

Parasitism creates selection for resistance mechanisms in host populations and is hypothesized to promote increased host evolvability. However, the influence of these traits on host evolution when parasites are no longer present is unclear. We used experimental evolution and whole-genome sequencing of Escherichia coli to determine the effects of past and present exposure to parasitic viruses (phages) on the spread of mutator alleles, resistance, and bacterial competitive fitness. We found that mutator alleles spread rapidly during adaptation to any of four different phage species, and this pattern was even more pronounced with multiple phages present simultaneously. However, hypermutability did not detectably accelerate adaptation in the absence of phages and recovery of fitness costs associated with resistance. Several lineages evolved phage resistance through elevated mucoidy, and during subsequent evolution in phage-free conditions they rapidly reverted to nonmucoid, phage-susceptible phenotypes. Genome sequencing revealed that this phenotypic reversion was achieved by additional genetic changes rather than by genotypic reversion of the initial resistance mutations. Insertion sequence (IS) elements played a key role in both the acquisition of resistance and adaptation in the absence of parasites; unlike single nucleotide polymorphisms, IS insertions were not more frequent in mutator lineages. Our results provide a genetic explanation for rapid reversion of mucoidy, a phenotype observed in other bacterial species including human pathogens. Moreover, this demonstrates that the types of genetic change underlying adaptation to fitness costs, and consequently the impact of evolvability mechanisms such as increased point-mutation rates, depend critically on the mechanism of resistance.

Reversing resistance: different routes and common themes across pathogens.

Resistance spreads rapidly in pathogen or pest populations exposed to biocides, such as fungicides and antibiotics, and in many cases new biocides are in short supply. How can resistance be reversed in order to prolong the effectiveness of available treatments? Some key parameters affecting reversion of resistance are well known, such as the fitness cost of resistance. However, the population biological processes that actually cause resistance to persist or decline remain poorly characterized, and consequently our ability to manage reversion of resistance is limited. Where do susceptible genotypes that replace resistant lineages come from? What is the epidemiological scale of reversion? What information do we need to predict the mechanisms or likelihood of reversion? Here, we define some of the population biological processes that can drive reversion, using examples from a wide range of taxa and biocides. These processes differ primarily in the origin of revertant genotypes, but also in their sensitivity to factors such as coselection and compensatory evolution that can alter the rate of reversion, and the likelihood that resistance will re-emerge upon re-exposure to biocides. We therefore argue that discriminating among different types of reversion allows for better prediction of where resistance is most likely to persist.

Parasite genetic distance and local adaptation in co-evolving bacteria-bacteriophage populations.

Antagonistic co-evolution between hosts and parasites can lead to local adaptation (LA) such that parasite fitness is greatest in sympatric hosts (or vice versa). The magnitude of LA typically increases with geographical distance, which is assumed to be because genetic (and hence phenotypic) distance increases with geographical distance. Here, we explicitly test the relationships between parasite genetic and phenotypic distance and LA using isolates of co-evolved viral parasites (lytic bacteriophage ϕ2) and the host bacterium Pseudomonas fluorescens SBW25. We find positive relationships between parasite genotype and infectivity phenotype, but the strength of the relationship was greater when infectivity was defined by the identity of hosts that could be infected rather than the actual number of hosts infected (host range), and when measurements were compared within rather than among populations. Crucially, we find a monotonic relationship between LA and genetic distance across phage isolates from different populations, although in contrast to many geographical studies, parasite LA decreased with genetic distance. These results can be explained by the fact that bacteria can rapidly adapt to phage infectivity mutations, but that evolved resistance has a degree of specificity to the local phage population. Our results show that antagonistic co-evolution alone can result in predictable links between genetic distance and host-parasite local adaptation.

Coevolution with bacteriophages drives genome-wide host evolution and constrains the acquisition of abiotic-beneficial mutations.

Studies of antagonistic coevolution between hosts and parasites typically focus on resistance and infectivity traits. However, coevolution could also have genome-wide effects on the hosts due to pleiotropy, epistasis, or selection for evolvability. Here, we investigate these effects in the bacterium Pseudomonas fluorescens SBW25 during approximately 400 generations of evolution in the presence or absence of bacteriophage (coevolution or evolution treatments, respectively). Coevolution resulted in variable phage resistance, lower competitive fitness in the absence of phages, and greater genome-wide divergence both from the ancestor and between replicates, in part due to the evolution of increased mutation rates. Hosts from coevolution and evolution treatments had different suites of mutations. A high proportion of mutations observed in coevolved hosts were associated with a known phage target binding site, the lipopolysaccharide (LPS), and correlated with altered LPS length and phage resistance. Mutations in evolved bacteria were correlated with higher fitness in the absence of phages. However, the benefits of these growth-promoting mutations were completely lost when these bacteria were subsequently coevolved with phages, indicating that they were not beneficial in the presence of resistance mutations (consistent with negative epistasis). Our results show that in addition to affecting genome-wide evolution in loci not obviously linked to parasite resistance, coevolution can also constrain the acquisition of mutations beneficial for growth in the abiotic environment.

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

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

The population genetics of antibiotic resistance: integrating molecular mechanisms and treatment contexts.

Despite efforts from a range of disciplines, our ability to predict and combat the evolution of antibiotic resistance in pathogenic bacteria is limited. This is because resistance evolution involves a complex interplay between the specific drug, bacterial genetics and both natural and treatment ecology. Incorporating details of the molecular mechanisms of drug resistance and ecology into evolutionary models has proved useful in predicting the dynamics of resistance evolution. However, putting these models to practical use will require extensive collaboration between mathematicians, molecular biologists, evolutionary ecologists and clinicians.

Higher resources decrease fluctuating selection during host-parasite coevolution.

We still know very little about how the environment influences coevolutionary dynamics. Here, we investigated both theoretically and empirically how nutrient availability affects the relative extent of escalation of resistance and infectivity (arms race dynamic; ARD) and fluctuating selection (fluctuating selection dynamic; FSD) in experimentally coevolving populations of bacteria and viruses. By comparing interactions between clones of bacteria and viruses both within- and between-time points, we show that increasing nutrient availability resulted in coevolution shifting from FSD, with fluctuations in average infectivity and resistance ranges over time, to ARD. Our model shows that range fluctuations with lower nutrient availability can be explained both by elevated costs of resistance (a direct effect of nutrient availability), and reduced benefits of resistance when population sizes of hosts and parasites are lower (an indirect effect). Nutrient availability can therefore predictably and generally affect qualitative coevolutionary dynamics by both direct and indirect (mediated through ecological feedbacks) effects on costs of resistance.

Type IV-A3 CRISPR-Cas systems drive inter-plasmid conflicts by acquiring spacers in trans.

Plasmid-encoded type IV-A CRISPR-Cas systems lack an acquisition module, feature a DinG helicase instead of a nuclease, and form ribonucleoprotein complexes of unknown biological functions. Type IV-A3 systems are carried by conjugative plasmids that often harbor antibiotic-resistance genes and their CRISPR array contents suggest a role in mediating inter-plasmid conflicts, but this function remains unexplored. Here, we demonstrate that a plasmid-encoded type IV-A3 system co-opts the type I-E adaptation machinery from its host, Klebsiella pneumoniae (K. pneumoniae), to update its CRISPR array. Furthermore, we reveal that robust interference of conjugative plasmids and phages is elicited through CRISPR RNA-dependent transcriptional repression. By silencing plasmid core functions, type IV-A3 impacts the horizontal transfer and stability of targeted plasmids, supporting its role in plasmid competition. Our findings shed light on the mechanisms and ecological function of type IV-A3 systems and demonstrate their practical efficacy for countering antibiotic resistance in clinically relevant strains.

The cost of antibiotic resistance depends on evolutionary history in Escherichia coli.

BACKGROUND: The persistence of antibiotic resistance depends on the fitness effects of resistance elements in the absence of antibiotics. Recent work shows that the fitness effect of a given resistance mutation is influenced by other resistance mutations on the same genome. However, resistant bacteria acquire additional beneficial mutations during evolution in the absence of antibiotics that do not alter resistance directly but may modify the fitness effects of new resistance mutations. RESULTS: We experimentally evolved rifampicin-resistant and sensitive Escherichia coli in a drug-free environment, before measuring the effects of new resistance elements on fitness in antibiotic-free conditions. Streptomycin-resistance mutations had small fitness effects in rifampicin-resistant genotypes that had adapted to antibiotic-free growth medium, compared to the same genotypes without adaptation. We observed a similar effect when resistance was encoded by a different mechanism and carried on a plasmid. Antibiotic-sensitive bacteria that adapted to the same conditions showed the same pattern for some resistance elements but not others. CONCLUSIONS: Epistatic variation of costs of resistance can result from evolution in the absence of antibiotics, as well as the presence of other resistance mutations.

The role of 'soaking' in spiteful toxin production in Pseudomonas aeruginosa.

The ubiquitous production of antibacterial toxins, such as bacteriocins, is an ecologically significant class of interbacterial interactions that have primarily evolved through their indirect fitness benefits to the producer. Bacteria release bacteriocins into the environment at a cost to individual cell, but individual bacteriocin-producing cells are unlikely to gain any direct benefit from their own toxin; indeed, cell lysis is required in many species. There is a growing body of research describing the ecological conditions that can favour the evolution of bacteriocin production. However, an important aspect of many bacteriocins has yet to be investigated: the ability of bacteriocin-producing cells to neutralize toxin ('soaking') produced by other clonemates. By competing Pseudomonas aeruginosa bacteriocin-producing wild-type and 'non-soaking' strains against a bacteriocin-susceptible strain, we find that soaking markedly reduces the fitness of a bacteriocin-producing strain at both high and low frequencies.