Introduction: Chronic Pseudomonas aeruginosa infection remains a leading driver of morbidity in cystic fibrosis (CF) and is tightly linked to antimicrobial resistance (AMR). However, treatment failure often occurs even when routine susceptibility testing suggests activity. Emerging evidence indicates that CF airways can act as an evolutionary niche where P. aeruginosa diversifies into co-existing subpopulations with distinct resistance and tolerance profiles. This abstract proposes a framework describing how within-host diversity and heteroresistance contribute to persistent infection and recurrent antibiotic exposure.
Methods: We developed a conceptual framework by synthesizing established mechanisms in CF microbiology and AMR research and mapping them to clinical decision points. The model integrates (i) spatially structured biofilms and mucus-associated microenvironments, (ii) adaptive evolution under repeated antibiotic selection, and (iii) phenotypic heterogeneity (including heteroresistance and tolerant subpopulations) that may be under-detected by single-colony testing. We outline measurable indicators suitable for evaluation, including longitudinal culture patterns, multi-isolate susceptibility profiles, genomic diversity signals, and recurrence-related outcomes.
Results: The framework identifies three mechanisms that can sustain apparent “discordance” between lab susceptibility and clinical response: (1) coexistence of minority resistant subpopulations that expand during therapy, (2) biofilm-associated tolerance reducing effective antibiotic killing despite susceptibility in planktonic assays, and (3) rapid adaptive shifts during repeated treatment cycles. These processes may increase antibiotic burden, promote selection pressure, and accelerate progression to difficult-to-treat phenotypes in CF.
Conclusions: CF-associated P. aeruginosa AMR is not solely a single-strain resistance problem but a dynamic within-host ecosystem challenge. Incorporating within-host diversity into diagnostics and stewardship such as multi-isolate testing and longitudinal surveillanc may better align therapy with real-world AMR biology and reduce treatment failure.
