Project
Evolution of ecological interactions in Pseudomonas aeruginosa across different stress regimesMicrobial interactions fundamentally shape community structure and function, yet the environmental conditions that drive the evolution of cooperation versus competition remain poorly understood. This knowledge gap has important implications for both ecological theory and practical applications, including chronic infections like cystic fibrosis (CF), where Pseudomonas aeruginosa persists in a stressful, nutrient-heterogeneous environment. This project integrates two evolutionary frameworks: the Stress Gradient Hypothesis (SGH) and the Resource Level Hypothesis (RLH), to investigate how environmental stress and resource availability govern the evolution of microbial interactions. The SGH predicts that severe environmental stress promotes facilitative interactions, as stress-tolerant organisms modify harsh conditions to benefit others, while benign, resource-rich environments favor competition. To test this hypothesis, we will evolve 24 replicate populations of P. aeruginosa for approximately 1000 generations (~150 days) under crossed gradients of nutrient availability (SCFM nutrient-rich medium versus M9 minimal medium) and osmotic stress (elevated NaCl concentrations mimicking CF lung conditions). We expect that high-stress environments will select for mutations in osmo-protective and biofilm regulatory genes (e.g., algU, mucA) that facilitate neighboring cells, while also favoring cheater phenotypes with lasR mutations that exploit cooperative public goods production. The RLH, grounded in r/K selection theory, posits that resource abundance selects for rapid-growth strategies (r-strategists) that may generate metabolic overflow and cross-feeding opportunities, promoting facilitation. Conversely, resource scarcity selects for efficient resource use and stress tolerance (K-strategists), intensifying competition. We will test this by propagating 24 replicate lines of P. aeruginosa in SCFM for approximately 250 generations (~32 days), with transfers during exponential phase (high-resource, r-selection) or stationary phase (low-resource, K-selection). We predict that r-selected lines will accumulate mutations in growth-related genes (e.g., ribosomal proteins, aminoacyl-tRNA synthetases), while K-selected lines will show enrichment in stress-response pathways (e.g., gidA, dksA, recB). To quantify interaction dynamics, we will isolate evolved clones and measure pairwise interaction strengths using flow cytometry with a fluorescently marked ancestral strain. The Relative Intensity Index (RII) will be calculated to classify interactions as facilitative (RII > 0), competitive (RII < 0), or neutral (RII ≈ 0). Comprehensive phenotypic profiling will assess growth density, pyoverdine and pyocyanin production, biofilm formation, motility, and antibiotic resistance across treatments. Whole-genome sequencing of isolates exhibiting strong ecological interactions will identify mutations underlying interaction shifts, with temporal tracking of key mutations across evolutionary time points using PCR and Sanger sequencing. This work will provide critical insights into the ecological and evolutionary drivers of microbial cooperation and competition, bridging theoretical ecology with the practical challenge of understanding persistent infections. By revealing how environmental context shapes interaction evolution, this research may inform strategies for managing antibiotic-resistant pathogens in chronic infections and other microbiome-based applications where microbial interactions play central roles.
