Comparative phenotypic and genotypic analysis of distinct Pseudomonas aeruginosa T3SS effector genotypes

Background: ) play central roles in pathogenesis, yet their relationships with antimicrobial resistance, virulence profiles, serotypes, and clinical manifestations remain incompletely defined. Methods: Five hundred clinical specimens, sputum, urine, burn, wound, and eye exudates, 100 each, were collected from multiple hospitals for isolation of P. aeruginosa. Phenotypic and genotypic methods identified isolates and characterized T3SS effector genotypes, antimicrobial susceptibility, resistance genes, virulence genes, and serotypes. Clustering, strain typing, and correlation analyses assessed associations among resistance, virulence, epidemiology, and disease severity. Results: Among 125 isolates, exoS+ was the most prevalent T3SS effector, followed by exoU+, while exoT+ and exoY+ were less frequent. The exoU+ isolates were consistently associated with severe clinical manifestations across specimen types and were more often hospital acquired, with enrichment for serotypes O6 and O11. The exoS+ isolates showed broader serotype diversity with balanced hospital and community acquisition, whereas ExoT and ExoY were mainly associated with O6 and O11, with ExoY more common in community-acquired cases but less prevalent overall. Despite widespread antimicrobial resistance and broad distribution of resistance genes, polymyxin remained the most effective agent, with a low resistance rate of 15.2%. Multidrug resistance affected 81.6% of isolates and was observed across all T3SS effector genotypes, with frequent coexistence of resistance and virulence genes within individual isolates. Hierarchical clustering revealed marked intra-group and inter-group heterogeneity, with no evidence of dominant clonal expansion by effector genotype or specimen type, and correlation analysis showed weak associations among resistance, virulence, serotypes, and epidemiological features, except for a consistent link between exoU+ and markers of severe tissue injury. Conclusions: is driven by independently assorting resistance and virulence traits, not by fixed clonal backgrounds. These findings support integrating T3SS effector profiling into clinical risk assessment and surveillance.