Polygenic Adaptation and Clonal Interference Enable Sustained Diversity in Experimental Pseudomonas aeruginosa Populations

Enhanced surface colonisation and competition during bacterial adaptation to a fungus

Bacterial-fungal interactions influence microbial community performance of most ecosystems and elicit specific microbial behaviours, including stimulating specialised metabolite production. Here, we use a co-culture experimental evolution approach to investigate bacterial adaptation to the presence of a fungus, using a simple model of bacterial-fungal interactions encompassing the bacterium Bacillus subtilis and the fungus Aspergillus niger. We find in one evolving population that B. subtilis was selected for enhanced production of the lipopeptide surfactin and accelerated surface spreading ability, leading to inhibition of fungal expansion and acidification of the environment. These phenotypes were explained by specific mutations in the DegS-DegU two-component system. In the presence of surfactin, fungal hyphae exhibited bulging cells with delocalised secretory vesicles possibly provoking an RlmA-dependent cell wall stress. Thus, our results indicate that the presence of the fungus selects for increased surfactin production, which inhibits fungal growth and facilitates the competitive success of the bacterium.

Uncovering the GacS-mediated role in evolutionary progression through trajectory reconstruction in Pseudomonas aeruginosa

The genetic diversities of subpopulations drive the evolution of pathogens and affect their ability to infect hosts and cause diseases. However, most studies to date have focused on the identification and characterization of adaptive mutations in single colonies, which do not accurately reflect the phenotypes of an entire population. Here, to identify the composition of variant subpopulations within a pathogen population, we developed a streamlined approach that combines high-throughput sequencing of the entire population cells with genotyping of single colonies. Using this method, we reconstructed a detailed quorum-sensing (QS) evolutionary trajectory in Pseudomonas aeruginosa. Our results revealed a new adaptive mutation in the gacS gene, which codes for a histidine kinase sensor of a two-component system (TCS), during QS evolution. This mutation reduced QS activity, allowing the variant to sweep throughout the whole population, while still being vulnerable to invasion by the emerging QS master regulator LasR-null mutants. By tracking the evolutionary trajectory, we found that mutations in gacS facilitated QS-rewiring in the LasR-null mutant. This rapid QS revertant caused by inactive GacS was found to be associated with the promotion of ribosome biogenesis and accompanied by a trade-off of reduced bacterial virulence on host cells. In conclusion, our findings highlight the crucial role of the global regulator GacS in modulating the progression of QS evolution and the virulence of the pathogen population.

Correlated Allele Frequency Changes Reveal Clonal Structure and Selection in Temporal Genetic Data

In evolving populations where the rate of beneficial mutations is large, subpopulations of individuals with competing beneficial mutations can be maintained over long times. Evolution with this kind of clonal structure is commonly observed in a wide range of microbial and viral populations. However, it can be difficult to completely resolve clonal dynamics in data. This is due to limited read lengths in high-throughput sequencing methods, which are often insufficient to directly measure linkage disequilibrium or determine clonal structure. Here, we develop a method to infer clonal structure using correlated allele frequency changes in time-series sequence data. Simulations show that our method recovers true, underlying clonal structures when they are known and accurately estimate linkage disequilibrium. This information can then be combined with other inference methods to improve estimates of the fitness effects of individual mutations. Applications to data suggest novel clonal structures in an E. coli long-term evolution experiment, and yield improved predictions of the effects of mutations on bacterial fitness and antibiotic resistance. Moreover, our method is computationally efficient, requiring orders of magnitude less run time for large data sets than existing methods. Overall, our method provides a powerful tool to infer clonal structures from data sets where only allele frequencies are available, which can also improve downstream analyses.

Divergent molecular strategies drive evolutionary adaptation to competitive fitness in biofilm formation

Biofilm is a group of heterogeneously structured and densely packed bacteria with limited access to nutrients and oxygen. These intrinsic features can allow a mono-species biofilm to diversify into polymorphic subpopulations, determining the overall community's adaptive capability to changing ecological niches. However, the specific biological functions underlying biofilm diversification and fitness adaptation are poorly demonstrated. Here, we launched and monitored the experimental evolution of Pseudomonas aeruginosa biofilms, finding that two divergent molecular trajectories were adopted for adaptation to higher competitive fitness in biofilm formation: one involved hijacking bacteriophage superinfection to aggressively inhibit kin competitors, whereas the other induced a subtle change in cyclic dimeric guanosine monophosphate signaling to gain a positional advantage via enhanced early biofilm adhesion. Bioinformatics analyses implicated that similar evolutionary strategies were prevalent among clinical P. aeruginosa strains, indicative of parallelism between natural and experimental evolution. Divergence in the molecular bases illustrated the adaptive values of genomic plasticity for gaining competitive fitness in biofilm formation. Finally, we demonstrated that these fitness-adaptive mutations reduced bacterial virulence. Our findings revealed how the mutations intrinsically generated from the biofilm environment influence the evolution of P. aeruginosa.

Experimental evolution of Pseudomonas aeruginosa to colistin in spatially confined microdroplets identifies evolutionary trajectories consistent with adaptation in microaerobic lung environments

IMPORTANCE

Antibiotic resistance remains one of the great challenges confronting public health in the world today. Individuals with compromised immune systems or underlying health conditions are often at an increased for bacterial infections. Patients with cystic fibrosis (CF) produce thick mucus that clogs airways and provides a very favorable environment for infection by bacteria that further decrease lung function and, ultimately, mortality. CF patients are often infected by bacteria such as Pseudomonas aeruginosa early in life and experience a series of chronic infections that, over time, become increasingly difficult to treat due to increased antibiotic resistance. Colistin is a major antibiotic used to treat CF patients. Clinical and laboratory studies have identified PmrA/PmrB and PhoP/PhoQ as responsible for increased resistance to colistin. Both have been identified in CF patient lungs, but why, in some cases, is it one and not the other? In this study, we show that distinct evolutionary trajectories to colistin resistance may be favored by the microaerobic partitioning found within the damaged CF lung.

The Role of Hypermutation and Collateral Sensitivity in Antimicrobial Resistance Diversity of Pseudomonas aeruginosa Populations in Cystic Fibrosis Lung Infection

Pseudomonas aeruginosa is an opportunistic pathogen which causes chronic, drug-resistant lung infections in cystic fibrosis (CF) patients. In this study, we explore the role of genomic diversification and evolutionary trade-offs in antimicrobial resistance (AMR) diversity within P. aeruginosa populations sourced from CF lung infections. We analyzed 300 clinical isolates from four CF patients (75 per patient), and found that genomic diversity is not a consistent indicator of phenotypic AMR diversity. Remarkably, some genetically less diverse populations showed AMR diversity comparable to those with significantly more genetic variation. We also observed that hypermutator strains frequently exhibited increased sensitivity to antimicrobials, contradicting expectations from their treatment histories. Investigating potential evolutionary trade-offs, we found no substantial evidence of collateral sensitivity among aminoglycoside, beta-lactam, or fluoroquinolone antibiotics, nor did we observe trade-offs between AMR and growth in conditions mimicking CF sputum. Our findings suggest that (i) genomic diversity is not a prerequisite for phenotypic AMR diversity; (ii) hypermutator populations may develop increased antimicrobial sensitivity under selection pressure; (iii) collateral sensitivity is not a prominent feature in CF strains, and (iv) resistance to a single antibiotic does not necessarily lead to significant fitness costs. These insights challenge prevailing assumptions about AMR evolution in chronic infections, emphasizing the complexity of bacterial adaptation during infection.

Biofilm tolerance, resistance and infections increasing threat of public health

Microbial biofilms can cause chronic infection. In the clinical setting, the biofilm-related infections usually persist and reoccur; the main reason is the increased antibiotic resistance of biofilms. Traditional antibiotic therapy is not effective and might increase the threat of antibiotic resistance to public health. Therefore, it is urgent to study the tolerance and resistance mechanism of biofilms to antibiotics and find effective therapies for biofilm-related infections. The tolerance mechanism and host reaction of biofilm to antibiotics are reviewed, and bacterial biofilm related diseases formed by human pathogens are discussed thoroughly. The review also explored the role of biofilms in the development of bacterial resistance mechanisms and proposed therapeutic intervention strategies for biofilm related diseases.

Mutation bias and adaptation in bacteria

Genetic mutation, which provides the raw material for evolutionary adaptation, is largely a stochastic force. However, there is ample evidence showing that mutations can also exhibit strong biases, with some mutation types and certain genomic positions mutating more often than others. It is becoming increasingly clear that mutational bias can play a role in determining adaptive outcomes in bacteria in both the laboratory and the clinic. As such, understanding the causes and consequences of mutation bias can help microbiologists to anticipate and predict adaptive outcomes. In this review, we provide an overview of the mechanisms and features of the bacterial genome that cause mutational biases to occur. We then describe the environmental triggers that drive these mechanisms to be more potent and outline the adaptive scenarios where mutation bias can synergize with natural selection to define evolutionary outcomes. We conclude by describing how understanding mutagenic genomic features can help microbiologists predict areas sensitive to mutational bias, and finish by outlining future work that will help us achieve more accurate evolutionary forecasts.

Species and condition shape the mutational spectrum in experimentally evolved biofilms

IMPORTANCE

Biofilm formation is a vital factor for the survival and adaptation of bacteria in diverse environmental niches. Experimental evolution combined with the advancement of whole-population genome sequencing provides us a powerful tool to understand the genomic dynamic of evolutionary adaptation to different environments, such as during biofilm development. Previous studies described the genetic and phenotypic changes of selected clones from experimentally evolved Bacillus thuringiensis and Bacillus subtilis that were adapted under abiotic and biotic biofilm conditions. However, the full understanding of the dynamic evolutionary landscapes was lacking. Furthermore, the differences and similarities of adaptive mechanisms in B. thuringiensis and B. subtilis were not identified. To overcome these limitations, we performed longitudinal whole-population genome sequencing to study the underlying genetic dynamics at high resolution. Our study provides the first comprehensive mutational landscape of two bacterial species' biofilms that is adapted to an abiotic and biotic surface.

Parallel genetic adaptation of Bacillus subtilis to different plant species

Plant growth-promoting rhizobacteria benefit plants by stimulating their growth or protecting them against phytopathogens. Rhizobacteria must colonize and persist on plant roots to exert their benefits. However, little is known regarding the processes by which rhizobacteria adapt to different plant species, or behave under alternating host plant regimes. Here, we used experimental evolution and whole-population whole-genome sequencing to analyse how Bacillus subtilis evolves on Arabidopsis thaliana and tomato seedlings, and under an alternating host plant regime, in a static hydroponic setup. We observed parallel evolution across multiple levels of biological organization in all conditions, which was greatest for the two heterogeneous, multi-resource, spatially structured environments at the genetic level. Species-specific adaptation at the genetic level was also observed, possibly caused by the selection stress imposed by different host plants. Furthermore, a trade-off between motility and biofilm development was supported by mutational changes in motility- and biofilm-related genes. Finally, we identified several condition-specific and common targeted genes in different environments by comparing three different B. subtilis biofilm adaptation settings. The results demonstrate a common evolutionary pattern when B. subtilis is adapting to the plant rhizosphere in similar conditions, and reveal differences in genetic mechanisms between different host plants. These findings will likely support strain improvements for sustainable agriculture.

Identifying Targets of Selection in Laboratory Evolution Experiments

Adaptive evolution navigates a balance between chance and determinism. The stochastic processes of mutation and drift generate phenotypic variation; however, once mutations reach an appreciable frequency in the population, their fate is governed by the deterministic action of selection, enriching for favorable genotypes and purging the less-favorable ones. The net result is that replicate populations will traverse similar-but not identical-pathways to higher fitness. This parallelism in evolutionary outcomes can be leveraged to identify the genes and pathways under selection. However, distinguishing between beneficial and neutral mutations is challenging because many beneficial mutations will be lost due to drift and clonal interference, and many neutral (and even deleterious) mutations will fix by hitchhiking. Here, we review the best practices that our laboratory uses to identify genetic targets of selection from next-generation sequencing data of evolved yeast populations. The general principles for identifying the mutations driving adaptation will apply more broadly.

Biofilm antimicrobial susceptibility through an experimental evolutionary lens

Experimental evolution experiments in which bacterial populations are repeatedly exposed to an antimicrobial treatment, and examination of the genotype and phenotype of the resulting evolved bacteria, can help shed light on mechanisms behind reduced susceptibility. In this review we present an overview of why it is important to include biofilms in experimental evolution, which approaches are available to study experimental evolution in biofilms and what experimental evolution has taught us about tolerance and resistance in biofilms. Finally, we present an emerging consensus view on biofilm antimicrobial susceptibility supported by data obtained during experimental evolution studies.

Tolerance and resistance of microbial biofilms

Chronic infections caused by microbial biofilms represent an important clinical challenge. The recalcitrance of microbial biofilms to antimicrobials and to the immune system is a major cause of persistence and clinical recurrence of these infections. In this Review, we present the extent of the clinical problem, and the mechanisms underlying the tolerance of biofilms to antibiotics and to host responses. We also explore the role of biofilms in the development of antimicrobial resistance mechanisms.

Historical contingency drives compensatory evolution and rare reversal of phage resistance

Bacteria and lytic viruses (phages) engage in highly dynamic coevolutionary interactions over time, yet we have little idea of how transient selection by phages might shape the future evolutionary trajectories of their host populations. To explore this question, we generated genetically diverse phage-resistant mutants of the bacterium Pseudomonas syringae. We subjected the panel of mutants to prolonged experimental evolution in the absence of phages. Some populations re-evolved phage sensitivity, whereas others acquired compensatory mutations that reduced the costs of resistance without altering resistance levels. To ask whether these outcomes were driven by the initial genetic mechanisms of resistance, we next evolved independent replicates of each individual mutant in the absence of phages. We found a strong signature of historical contingency: some mutations were highly reversible across replicate populations, whereas others were highly entrenched. Through whole-genome sequencing of bacteria over time, we also found that populations with the same resistance gene acquired more parallel sets of mutations than populations with different resistance genes, suggesting that compensatory adaptation is also contingent on how resistance initially evolved. Our study identifies an evolutionary ratchet in bacteria–phage coevolution and may explain previous observations that resistance persists over time in some bacterial populations but is lost in others. We add to a growing body of work describing the key role of phages in the ecological and evolutionary dynamics of their host communities. Beyond this specific trait, our study provides a new insight into the genetic architecture of historical contingency, a crucial component of interpreting and predicting evolution.

Evolved resistance to a novel cationic peptide antibiotic requires high mutation supply

Background and Objectives

A key strategy for resolving the antibiotic resistance crisis is the development of new drugs with antimicrobial properties. The engineered cationic antimicrobial peptide WLBU2 (also known as PLG0206) is a promising broad-spectrum antimicrobial compound that has completed Phase I clinical studies. It has activity against Gram-negative and Gram-positive bacteria including infections associated with biofilm. No definitive mechanisms of resistance to WLBU2 have been identified.

Methodology

Here, we used experimental evolution under different levels of mutation supply and whole genome sequencing (WGS) to detect the genetic pathways and probable mechanisms of resistance to this peptide. We propagated populations of wild-type and hypermutator Pseudomonas aeruginosa in the presence of WLBU2 and performed WGS of evolved populations and clones.

Results

Populations that survived WLBU2 treatment acquired a minimum of two mutations, making the acquisition of resistance more difficult than for most antibiotics, which can be tolerated by mutation of a single target. Major targets of resistance to WLBU2 included the orfN and pmrB genes, previously described to confer resistance to other cationic peptides. More surprisingly, mutations that increase aggregation such as the wsp pathway were also selected despite the ability of WLBU2 to kill cells growing in a biofilm.

Conclusions and implications

The results show how experimental evolution and WGS can identify genetic targets and actions of new antimicrobial compounds and predict pathways to resistance of new antibiotics in clinical practice.

Molecular Basis of Wrinkled Variants Isolated From Pseudoalteromonas lipolytica Biofilms

Many Pseudoalteromonas species are dominant biofilm-forming Gammaproteobacteria in the ocean. The formation of Pseudoalteromonas biofilms is often accompanied by the occurrence of variants with different colony morphologies that may exhibit increased marine antifouling or anticorrosion activities. However, the genetic basis of the occurrence of these variants remains largely unexplored. In this study, we identified that wrinkled variants of P. lipolytica mainly arose due to mutations in the AT00_08765, a wspF-like gene, that are associated with decreased swimming motility and increased cellulose production. Moreover, we found that the spontaneous mutation in flhA, encoding a flagellar biosynthesis protein, also caused a wrinkled colony morphology that is associated with cellulose overproduction, indicating that flhA plays a dual role in controlling flagellar assembly and polysaccharide production in P. lipolytica. Investigation of wrinkled variants harboring spontaneous mutation in dgcB, encoding a GGDEF domain protein, also demonstrated dgcB plays an important role in regulating cellulose production and swimming motility. In addition, by screening the suppressor of the AT00_08765 variant strain, we also identified that the spontaneous mutation in cheR and bcsC directly abolished the wrinkled phenotype of the AT00_08765 variant strain, suggesting that the chemosensory signaling transduction and cellulose production are crucial for the determination of the wrinkled phenotype in P. lipolytica. Taken together, this study provides insights into the genetic variation within biofilms of P. lipolytica.

The nutritional environment is sufficient to select coexisting biofilm and quorum-sensing mutants of Pseudomonas aeruginosa

The evolution of bacterial populations during infections can be influenced by various factors including available nutrients, the immune system, and competing microbes, rendering it difficult to identify the specific forces that select on evolved traits. The genomes of Pseudomonas aeruginosa isolated from the airway of patients with cystic fibrosis (CF), for example, have revealed commonly mutated genes, but which phenotypes led to their prevalence is often uncertain. Here, we focus on effects of nutritional components of the CF airway on genetic adaptations by P. aeruginosa grown in either well-mixed (planktonic) or biofilm-associated conditions. After only 80 generations of experimental evolution in a simple medium with glucose, lactate, and amino acids, all planktonic populations diversified into lineages with mutated genes common to CF infections: morA, encoding a regulator of biofilm formation, or lasR, encoding a quorum sensing regulator that modulates the expression of virulence factors. Although mutated quorum sensing is often thought to be selected in vivo due to altered virulence phenotypes or social cheating, isolates with lasR mutations demonstrated increased fitness when grown alone and outcompeted the ancestral PA14 strain. Nonsynonymous SNPs in morA increased fitness in a nutrient concentration-dependent manner during planktonic growth and surprisingly also increased biofilm production. Populations propagated in biofilm conditions also acquired mutations in loci associated with chronic infections, including lasR and cyclic-di-GMP regulators roeA and wspF. These findings demonstrate that nutrient conditions and biofilm selection are sufficient to select mutants with problematic clinical phenotypes including increased biofilm and altered quorum sensing. Importance Pseudomonas aeruginosa produces dangerous chronic infections that are known for their rapid diversification and recalcitrance to treatment. We performed evolution experiments to identify adaptations selected by two specific aspects of the CF respiratory environment: nutrient levels and surface attachment. Propagation of P. aeruginosa in nutrients present within the CF airway was sufficient to drive diversification into subpopulations with identical mutations in regulators of biofilm and quorum sensing to those arising during infection. Thus, the adaptation of opportunistic pathogens to nutrients found in the host may select mutants with phenotypes that complicate treatment and clearance of infection.