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Results for “Eco-evolutionary feedbacks”

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PubMed2026

Mutations in filamentous bacteriophages spark eco-evolutionary feedbacks in Pseudomonas aeruginosa.

Microbial populations strongly shape their environment, which can re-route adaptation toward organism-generated fitness optima. However, the conditions that promote these eco-evolutionary feedbacks are unclear. Here, we used experimental evolution to test whether high population density, by strengthening niche construction, drives eco-evolutionary feedbacks in the bacterial pathogen Pseudomonas aeruginosa (Pa) MPAO1. We tested for adaptation to organism-modified environments by measuring the relative performance of ancestral and endpoint populations in filtrate generated by each evolutionary line sampled across generations. Contrary to expectations, we found that endpoint populations had higher performance than the ancestral strain in filtrate across nearly all evolutionary lines regardless of population density. This was caused by the emergence of hyperactive filamentous bacterio(phage) mutants during experimental passaging that inhibited the ancestral strain but not endpoint populations in modified media. Hyperactive phages emerged from one of two avirulent prophages in MPAO1's genome (Pf4 or Pf6). Hyperactive phages drove the evolution of phage resistance in bacterial populations via mutations in the type IV pilus (TIVP), the phage's binding receptor. In a follow-up experiment, we showed that these TIVP mutations pleiotropically reduced motility and conferred resistance to a TIVP-targeting virulent phage, both of which are important traits for Pa infection and treatment. Overall, this work suggests that filamentous phage evolution can drive eco-evolutionary feedbacks in bacterial populations, causing phenotypic and genetic changes that would not be anticipated from adaptation to the extrinsic environment alone.

Pseudomonas aeruginosa↗
PubMed2025

Intracellular interactions shape antiviral resistance outcomes in poliovirus via eco-evolutionary feedback.

Antiviral resistance evolution poses a major obstacle for controlling viral infections. A promising strategy is to target shared viral proteins that allow drug susceptible viruses to sensitize resistant ones during cellular coinfection, muting selection for resistance. Pocapavir, a poliovirus capsid inhibitor, employs this sociovirological strategy. While susceptible viruses significantly suppressed resistance in the presence of pocapavir in cell culture, a pocapavir clinical trial observed widespread resistance evolution and limited improvements to clearance times. To reconcile these findings, we present an intra-host eco-evolutionary model of poliovirus in the presence of pocapavir, which reproduces both the potent interference observed in vitro and the resistance emergence seen in patients. In the short term, our model predicts that a high density of susceptible viruses sensitizes resistant ones to pocapavir, mirroring cell culture results. However, over multiple replication cycles, pocapavir's high potency collapses viral density, which reduces coinfection and allows resistance to evolve as observed in the clinical trial. Since coinfection is essential to suppress resistance, enabling greater survival of susceptible viruses could offer therapeutic advantages. Counterintuitively, we demonstrate that this can be achieved by lessening antiviral potency, which can limit resistance evolution while also maintaining a low viral load. These findings suggest that antivirals that rely on viral intracellular interaction must balance immediate neutralization with the preservation of future coinfection, yielding more sustained inhibition. Explicitly considering the eco-evolutionary feedback encompassing viral density, shared phenotypes and absolute fitness not only provides new insights into designing effective therapies but also illuminates viral evolutionary dynamics more broadly.

Journal Article↗
PubMed2025

Pervasive fitness trade-offs revealed by rapid adaptation to shifting population densities in large experimental populations of Drosophila melanogaster.

Trade-offs are an inherent feature of organismal biology that are expected play a fundamental role in the evolution of natural populations. Efforts to quantify trade-offs are largely confined to phenotypic measurements and the identification of negative genetic-correlations among fitness-relevant traits. Here, we use time-series genomic data collected during experimental evolution in large, genetically diverse populations of Drosophila melanogaster to directly measure the manifestation of trade-offs in response to fluctuating selection on ecological timescales. Specifically, we first conducted a lab-based selection experiment to quantify a genome-wide signal of antagonistic pleiotropy elicited in response to shifting population densities and associated with reproduction and stress tolerance selection. In doing so, we identified a putative role of two cosmopolitan inversions in these trade-offs. We then conducted an independent experiment to show that a simple manipulation of increasing population density under controlled lab-based conditions identified loci that are relevant to selection during population expansion and collapse in a complex, semi-natural setting. In concert, our results reveal how adaptation in complex, natural environments can be coarse-grained in such a manner to drive repeatable and predictable patterns of genomic variation, and further add credence to models positing a role of generic fitness trade-offs in the maintenance of variation in natural populations.

Drosophila melanogaster↗
PubMed2026

Disentangling host genetic variation for avoidance and resistance to pathogens.

BACKGROUND: Hosts can use avoidance (e.g., behavior) to reduce their contact rates with pathogens; after contact, they can use resistance (e.g., immunity) to reduce the establishment and proliferation of an infection. Because both defenses preserve host fitness and reduce pathogen fitness, we expect that their epidemiological and evolutionary effects will be interdependent. This study used a two-locus model to understand the evolution of allelic associations (i.e., linkage disequilibrium or LD) between genes determining levels of avoidance and resistance in the presence of an infectious disease or a parasite. RESULTS: We found that polymorphism in both avoidance and resistance was possible, but only for a limited range of parameter values. At equilibrium within these polymorphic populations, avoidance and resistance alleles were negatively associated (i.e., in negative LD). However, most commonly, polymorphism was only stably maintained at one defense locus, and the other locus became fixed for one allele. CONCLUSIONS: The model shows that avoidance and resistance are likely to influence each other's evolution because of their joint effects on infection and their costs; however, predictions about their relationship are not necessarily straightforward or intuitive. For example, avoidance and resistance may be more likely to covary across than within populations.

Animals↗