The impact of phage and phage resistance on microbial community dynamics.

Where there are bacteria, there will be bacteriophages. These viruses are known to be important players in shaping the wider microbial community in which they are embedded, with potential implications for human health. On the other hand, bacteria possess a range of distinct immune mechanisms that provide protection against bacteriophages, including the mutation or complete loss of the phage receptor, and CRISPR-Cas adaptive immunity. While our previous work showed how a microbial community may impact phage resistance evolution, little is known about the inverse, namely how interactions between phages and these different phage resistance mechanisms affect the wider microbial community in which they are embedded. Here, we conducted a 10-day, fully factorial evolution experiment to examine how phage impact the structure and dynamics of an artificial four-species bacterial community that includes either Pseudomonas aeruginosa wild-type or an isogenic mutant unable to evolve phage resistance through CRISPR-Cas. Additionally, we used mathematical modelling to explore the ecological interactions underlying full community behaviour, as well as to identify general principles governing the impacts of phage on community dynamics. Our results show that the microbial community structure is drastically altered by the addition of phage, with Acinetobacter baumannii becoming the dominant species and P. aeruginosa being driven nearly extinct, whereas P. aeruginosa outcompetes the other species in the absence of phage. Moreover, we find that a P. aeruginosa strain with the ability to evolve CRISPR-based resistance generally does better when in the presence of A. baumannii, but that this benefit is largely lost over time as phage is driven extinct. Finally, we show that pairwise data alone is insufficient when modelling our microbial community, both with and without phage, highlighting the importance of higher order interactions in governing multispecies dynamics in complex communities. Combined, our data clearly illustrate how phage targeting a dominant species allows for the competitive release of the strongest competitor while also contributing to community diversity maintenance and potentially preventing the reinvasion of the target species, and underline the importance of mapping community composition before therapeutically applying phage.

Bacteria can be selected to help beneficial plasmids spread.

A recent commentary raised concerns about aspects of the model and assumptions used in a previous study which demonstrated that selection can favor chromosomal alleles that confer higher plasmid donation rates. Here, the authors of that previous study respond to the concerns raised.

Machine learning identification of Pseudomonas aeruginosa strains from colony image data.

When grown on agar surfaces, microbes can produce distinct multicellular spatial structures called colonies, which contain characteristic sizes, shapes, edges, textures, and degrees of opacity and color. For over one hundred years, researchers have used these morphology cues to classify bacteria and guide more targeted treatment of pathogens. Advances in genome sequencing technology have revolutionized our ability to classify bacterial isolates and while genomic methods are in the ascendancy, morphological characterization of bacterial species has made a resurgence due to increased computing capacities and widespread application of machine learning tools. In this paper, we revisit the topic of colony morphotype on the within-species scale and apply concepts from image processing, computer vision, and deep learning to a dataset of 69 environmental and clinical Pseudomonas aeruginosa strains. We find that colony morphology and complexity under common laboratory conditions is a robust, repeatable phenotype on the level of individual strains, and therefore forms a potential basis for strain classification. We then use a deep convolutional neural network approach with a combination of data augmentation and transfer learning to overcome the typical data starvation problem in biological applications of deep learning. Using a train/validation/test split, our results achieve an average validation accuracy of 92.9% and an average test accuracy of 90.7% for the classification of individual strains. These results indicate that bacterial strains have characteristic visual 'fingerprints' that can serve as the basis of classification on a sub-species level. Our work illustrates the potential of image-based classification of bacterial pathogens and highlights the potential to use similar approaches to predict medically relevant strain characteristics like antibiotic resistance and virulence from colony data.

The dynamic response of quorum sensing to density is robust to signal supplementation and individual signal synthase knockouts.

Quorum sensing (QS) is a widespread mechanism of environment sensing and behavioural coordination in bacteria. At its core, QS is based on the production, sensing and response to small signalling molecules. Previous work with Pseudomonas aeruginosa shows that QS can be used to achieve quantitative resolution and deliver a dosed response to the bacteria's density environment, implying a sophisticated mechanism of control. To shed light on how the mechanistic signal components contribute to graded responses to density, we assess the impact of genetic (AHL signal synthase deletion) and/or signal supplementation (exogenous AHL addition) perturbations on lasB reaction-norms to changes in density. Our approach condenses data from 2000 timeseries (over 74 000 individual observations) into a comprehensive view of QS-controlled gene expression across variation in genetic, environmental and signal determinants of lasB expression. We first confirm that deleting either (∆lasI, ∆rhlI) or both (∆lasIrhlI) AHL signal synthase gene attenuates QS response to density. In the ∆rhlI background we show persistent yet attenuated density-dependent lasB expression due to native 3-oxo-C12-HSL signalling. We then test if density-independent quantities of AHL signal (3-oxo-C12-HSL, C4-HSL) added to the WT either flatten or increase responsiveness to density and find that the WT response is robust to all tested concentrations of signal, alone or in combination. We then move to progressively supplementing the genetic knockouts and find that cognate signal supplementation of a single AHL signal (∆lasI +3-oxo-C12-HSL, ∆rhlI +C4HSL) is sufficient to restore the ability to respond in a density-dependent manner to increasing density. We also find that dual signal supplementation of the double AHL synthase knockout restores the ability to produce a graded response to increasing density, despite adding a density-independent amount of signal. Only the addition of high concentrations of both AHLs and PQS can force maximal lasB expression and ablate responsiveness to density. Our results show that density-dependent control of lasB expression is robust to multiple combinations of QS gene deletion and density-independent signal supplementation. Our work develops a modular approach to query the robustness and mechanistic bases of the central environmental sensing phenotype of quorum sensing.

The social lives of viruses and other mobile genetic elements: a commentary on Leeks et al. 2023.

Illustration of life-histories of phages and plasmids through horizontal and vertical transmission (see Figure 1 for more information).

A social life for discerning microbes.

Microbes are not only extremely social but also extremely discerning about whom they socialize with. Recent research has uncovered some of the evolutionary explanations behind these feats of social sophistication in bacteria (Ackermann et al., 2008; Diggle et al., 2007) and, most recently, has provided insights into the molecular mechanisms of discrimination in yeast (Smukalla et al., 2008).

Challenges and opportunities for cheat therapy in the control of bacterial infections.

Covering: 1999 to 2021Bacterial pathogens can be highly social, communicating and cooperating within multi-cellular groups to make us sick. The requirement for collective action in pathogens presents novel therapeutic avenues that seek to undermine cooperative behavior, what we call here 'cheat therapies'. We review two broad avenues of cheat therapy: first, the introduction of genetically engineered 'cheat' strains (bio-control cheats), and second the chemical induction of 'cheat' behavior in the infecting pathogens (chemical-control cheats). Both genetically engineered and chemically induced cheats can socially exploit the cooperative wildtype infection, reducing pathogen burden and the severity of disease. We review the costs and benefits of cheat therapies, highlighting advantages of evolutionary robustness and also the challenges of low to moderate efficacy, compared to conventional antibiotic treatments. We end with a summary of what we see as the most valuable next steps, focusing on adjuvant treatments and use as alternate therapies for mild, self-resolving infections - allowing the reservation of current and highly effective antibiotics for more critical patient needs.

Resistance diagnostics as a public health tool to combat antibiotic resistance: A model-based evaluation.

Rapid point-of-care resistance diagnostics (POC-RD) are a key tool in the fight against antibiotic resistance. By tailoring drug choice to infection genotype, doctors can improve treatment efficacy while limiting costs of inappropriate antibiotic prescription. Here, we combine epidemiological theory and data to assess the potential of resistance diagnostics (RD) innovations in a public health context, as a means to limit or even reverse selection for antibiotic resistance. POC-RD can be used to impose a nonbiological fitness cost on resistant strains by enabling diagnostic-informed treatment and targeted interventions that reduce resistant strains' opportunities for transmission. We assess this diagnostic-imposed fitness cost in the context of a spectrum of bacterial population biologies and find that POC-RD have a greater potential against obligate pathogens than opportunistic pathogens already subject to selection under "bystander" antibiotic exposure during asymptomatic carriage (e.g., the pneumococcus). We close by generalizing the notion of RD-informed strategies to incorporate carriage surveillance information and illustrate that coupling transmission-control interventions to the discovery of resistant strains in carriage can potentially select against resistance in a broad range of opportunistic pathogens.

Microbiome Data Enhances Predictive Models of Lung Function in People With Cystic Fibrosis.

BACKGROUND: Microbiome sequencing has brought increasing attention to the polymicrobial context of chronic infections. However, clinical microbiology continues to focus on canonical human pathogens, which may overlook informative, but nonpathogenic, biomarkers. We address this disconnect in lung infections in people with cystic fibrosis (CF). METHODS: We collected health information (lung function, age, and body mass index [BMI]) and sputum samples from a cohort of 77 children and adults with CF. Samples were collected during a period of clinical stability and 16S rDNA sequenced for airway microbiome compositions. We use ElasticNet regularization to train linear models predicting lung function and extract the most informative features. RESULTS: Models trained on whole-microbiome quantitation outperformed models trained on pathogen quantitation alone, with or without the inclusion of patient metadata. Our most accurate models retained key pathogens as negative predictors (Pseudomonas, Achromobacter) along with established correlates of CF disease state (age, BMI, CF-related diabetes). In addition, our models selected nonpathogen taxa (Fusobacterium, Rothia) as positive predictors of lung health. CONCLUSIONS: These results support a reconsideration of clinical microbiology pipelines to ensure the provision of informative data to guide clinical practice.

Community lifespan, niche expansion and the evolution of interspecific cooperation.

Microbes live in dense and diverse communities where they deploy many traits that promote the growth and survival of neighbouring species, all the while also competing for shared resources. Because microbial communities are highly dynamic, the costs and benefits of species interactions change over the growth cycle of a community. How mutualistic interactions evolve under such demographic and ecological conditions is still poorly understood. Here, we develop an eco-evolutionary model to explore how different forms of helping with distinct fitness effects (rate-enhancing and yield-enhancing) affect the multiple phases of community growth, and its consequences for the evolution of mutualisms. We specifically focus on a form of yield-enhancing trait in which cooperation augments the common pool of resources, termed niche expansion. We show that although mutualisms in which cooperation increases partners growth rate are generally favoured at early stages of community growth, niche expansion can evolve at later stages where densities are high. Further, we find that niche expansion can promote the evolution of reproductive restraint, in which a focal species adaptively reduces its own growth rate to increase the density of partner species. Our findings suggest that yield-enhancing mutualisms are more prevalent in stable habitats with a constant supply of resources, and where populations typically live at high densities. In general, our findings highlight the need to integrate different components of population growth in the analysis of mutualisms to understand the composition and function of microbial communities.

Combinatorial quorum sensing in Pseudomonas aeruginosa allows for novel cheating strategies.

In the opportunistic pathogen Pseudomonas aeruginosa, quorum sensing (QS) is a social trait that is exploitable by non-cooperating cheats. Previously it has been shown that by linking QS to the production of both public and private goods, cheats can be prevented from invading populations of cooperators and this was described by Dandekar et al. (Science 2012;338:264-266) as 'a metabolic incentive to cooperate'. We hypothesized that P. aeruginosa could evolve novel cheating strategies to circumvent private goods metabolism by rewiring its combinatorial response to two QS signals (3O-C12-HSL and C4-HSL). We performed a selection experiment that cycled P. aeruginosa between public and private goods growth media and evolved an isolate that rewired its control of cooperative protease expression from a synergistic (AND-gate) response to dual-signal input to a 3O-C12-HSL-only response. We show that this isolate circumvents metabolic incentives to cooperate and acts as a combinatorial signalling cheat, with higher fitness in competition with its ancestor. Our results show three important principles: first, combinatorial QS allows for diverse social strategies to emerge; second, restrictions levied by private goods are not sufficient to explain the maintenance of cooperation in natural populations; and third, modifying combinatorial QS responses could result in important physiological outcomes in bacterial populations.

Alternative therapeutics for self-limiting infections-An indirect approach to the antibiotic resistance challenge.

Alternative therapeutics for infectious diseases is a top priority, but what infections should be the primary targets? At present there is a focus on therapies for severe infections, for which effective treatment is most needed, but these infections are hard to manage, and progress has been limited. Here, we explore a different approach. Applying an evolutionary perspective to a review of antibiotic prescription studies, we identify infections that likely make a large contribution to resistance evolution across multiple taxa but are clinically mild and thus present easier targets for therapeutics development. Alternative therapeutics for these infections, we argue, would save lives indirectly by preserving the high efficacy of existing antibiotics for the patients who need them the most.

Haemolymph removal by Varroa mite destabilizes the dynamical interaction between immune effectors and virus in bees, as predicted by Volterra's model.

The association between the deformed wing virus and the parasitic mite Varroa destructor has been identified as a major cause of worldwide honeybee colony losses. The mite acts as a vector of the viral pathogen and can trigger its replication in infected bees. However, the mechanistic details underlying this tripartite interaction are still poorly defined, and, particularly, the causes of viral proliferation in mite-infested bees. Here, we develop and test a novel hypothesis that mite feeding destabilizes viral immune control through the removal of both virus and immune effectors, triggering uncontrolled viral replication. Our hypothesis is grounded on the predator-prey theory developed by Volterra, which predicts prey proliferation when both predators and preys are constantly removed from the system. Consistent with this hypothesis, we show that the experimental removal of increasing volumes of haemolymph from individual bees results in increasing viral densities. By contrast, we do not find consistent support for alternative proposed mechanisms of viral expansion via mite immune suppression or within-host viral evolution. Our results suggest that haemolymph removal plays an important role in the enhanced pathogen virulence observed in the presence of feeding Varroa mites. Overall, these results provide a new model for the mechanisms driving pathogen-parasite interactions in bees, which ultimately underpin honeybee health decline and colony losses.

Indirect Fitness Benefits Enable the Spread of Host Genes Promoting Costly Transfer of Beneficial Plasmids.

Bacterial genes that confer crucial phenotypes, such as antibiotic resistance, can spread horizontally by residing on mobile genetic elements (MGEs). Although many mobile genes provide strong benefits to their hosts, the fitness consequences of the process of transfer itself are less clear. In previous studies, transfer has been interpreted as a parasitic trait of the MGEs because of its costs to the host but also as a trait benefiting host populations through the sharing of a common gene pool. Here, we show that costly donation is an altruistic act when it spreads beneficial MGEs favoured when it increases the inclusive fitness of donor ability alleles. We show mathematically that donor ability can be selected when relatedness at the locus modulating transfer is sufficiently high between donor and recipients, ensuring high frequency of transfer between cells sharing donor alleles. We further experimentally demonstrate that either population structure or discrimination in transfer can increase relatedness to a level selecting for chromosomal transfer alleles. Both mechanisms are likely to occur in natural environments. The simple process of strong dilution can create sufficient population structure to select for donor ability. Another mechanism observed in natural isolates, discrimination in transfer, can emerge through coselection of transfer and discrimination alleles. Our work shows that horizontal gene transfer in bacteria can be promoted by bacterial hosts themselves and not only by MGEs. In the longer term, the success of cells bearing beneficial MGEs combined with biased transfer leads to an association between high donor ability, discrimination, and mobile beneficial genes. However, in conditions that do not select for altruism, host bacteria promoting transfer are outcompeted by hosts with lower transfer rate, an aspect that could be relevant in the fight against the spread of antibiotic resistance.

Community interactions and spatial structure shape selection on antibiotic resistant lineages.

Polymicrobial interactions play an important role in shaping the outcome of antibiotic treatment, yet how multispecies communities respond to antibiotic assault is still little understood. Here we use an individual-based simulation model of microbial biofilms to investigate how competitive and mutualistic interactions between an antibiotic-resistant and a susceptible strain (or species) influence the two-lineage community response to antibiotic exposure. Our model predicts that while increasing competition and antibiotics leads to increasing competitive release of the antibiotic-resistant strain, hitting a mutualistic community of cross-feeding species with antibiotics leads to a mutualistic suppression effect where both susceptible and resistant species are harmed. We next show that the impact of antibiotics is further governed by emergent spatial feedbacks within communities. Mutualistic cross-feeding communities can rescue susceptible members by subsidizing their growth inside the biofilm despite lack of access to the nutrient-rich and high-antibiotic growing front. Moreover, we show that antibiotic detoxification by resistant cells can protect nearby susceptible cells, but such cross-protection is more effective in mutualistic communities because mutualism drives mixing of resistant and susceptible cells. In contrast, competition leads to segregation, which ultimately prevents susceptible cells to profit from detoxification. Understanding how the interplay between microbial metabolic interactions and community spatial structuring shapes the outcome of antibiotic treatment can be key to effectively leverage the power of antibiotics and promote microbiome health.

An oscillating tragedy of the commons in replicator dynamics with game-environment feedback.

A tragedy of the commons occurs when individuals take actions to maximize their payoffs even as their combined payoff is less than the global maximum had the players coordinated. The originating example is that of overgrazing of common pasture lands. In game-theoretic treatments of this example, there is rarely consideration of how individual behavior subsequently modifies the commons and associated payoffs. Here, we generalize evolutionary game theory by proposing a class of replicator dynamics with feedback-evolving games in which environment-dependent payoffs and strategies coevolve. We initially apply our formulation to a system in which the payoffs favor unilateral defection and cooperation, given replete and depleted environments, respectively. Using this approach, we identify and characterize a class of dynamics: an oscillatory tragedy of the commons in which the system cycles between deplete and replete environmental states and cooperation and defection behavior states. We generalize the approach to consider outcomes given all possible rational choices of individual behavior in the depleted state when defection is favored in the replete state. In so doing, we find that incentivizing cooperation when others defect in the depleted state is necessary to avert the tragedy of the commons. In closing, we propose directions for the study of control and influence in games in which individual actions exert a substantive effect on the environmental state.

The State of the Union Is Strong: a Review of ASM's 6th Conference on Cell-Cell Communication in Bacteria.

The 6th American Society for Microbiology Conference on Cell-Cell Communication in Bacteria convened from 16 to 19 October 2017 in Athens, GA. In this minireview, we highlight some of the research presented at that meeting that addresses central questions emerging in the field, including the following questions. How are cell-cell communication circuits designed to generate responses? Where are bacteria communicating? Finally, why are bacteria engaging in such behaviors?

Within-host interference competition can prevent invasion of rare parasites.

Competition between parasite species or genotypes can play an important role in the establishment of parasites in new host populations. Here, we investigate a mechanism by which a rare parasite is unable to establish itself in a host population if a common resident parasite is already present (a 'priority effect'). We develop a simple epidemiological model and show that a rare parasite genotype is unable to invade if coinfecting parasite genotypes inhibit each other's transmission more than expected from simple resource partitioning. This is because a rare parasite is more likely to be in multiply-infected hosts than the common genotype, and hence more likely to pay the cost of reduced transmission. Experiments competing interfering clones of bacteriophage infecting a bacterium support the model prediction that the clones are unable to invade each other from rare. We briefly discuss the implications of these results for host-parasite ecology and (co)evolution.

The route of infection determines Wolbachia antibacterial protection in Drosophila.

Bacterial symbionts are widespread among metazoans and provide a range of beneficial functions. Wolbachia-mediated protection against viral infection has been extensively demonstrated in Drosophila. In mosquitoes that are artificially transinfected with Drosophila melanogaster Wolbachia (wMel), protection from both viral and bacterial infections has been demonstrated. However, no evidence for Wolbachia-mediated antibacterial protection has been demonstrated in Drosophila to date. Here, we show that the route of infection is key for Wolbachia-mediated antibacterial protection. Drosophila melanogaster carrying Wolbachia showed reduced mortality during enteric-but not systemic-infection with the opportunist pathogen Pseudomonas aeruginosaWolbachia-mediated protection was more pronounced in male flies and is associated with increased early expression of the antimicrobial peptide Attacin A, and also increased expression of a reactive oxygen species detoxification gene (Gst D8). These results highlight that the route of infection is important for symbiont-mediated protection from infection, that Wolbachia can protect hosts by eliciting a combination of resistance and disease tolerance mechanisms, and that these effects are sexually dimorphic. We discuss the importance of using ecologically relevant routes of infection to gain a better understanding of symbiont-mediated protection.