Mucus polymer concentration and in vivo adaptation converge to define the antibiotic response of Pseudomonas aeruginosa during chronic lung infection

• Published in: bioRxiv : the preprint server for biology
• Main Authors: Greenwald, Matthew A, Meinig, Suzanne L, Plott, Lucas M, Roca, Cristian, Higgs, Matthew G, Vitko, Nicholas P, Markovetz, Matthew R, Rouillard, Kaitlyn R, Carpenter, Jerome, Kesimer, Mehmet, Hill, David B, Schisler, Jonathan C, Wolfgang, Matthew C
• Format: Journal Article
• Language: English
• Published: United States 21.12.2023

The airway milieu of individuals with muco-obstructive airway diseases (MADs) is defined by the accumulation of dehydrated mucus due to hyperabsorption of airway surface liquid and defective mucociliary clearance. Pathological mucus becomes progressively more viscous with age and disease severity due to the concentration and overproduction of mucin and accumulation of host-derived extracellular DNA (eDNA). Respiratory mucus of MADs provides a niche for recurrent and persistent colonization by respiratory pathogens, including , which is responsible for the majority of morbidity and mortality in MADs. Despite high concentration inhaled antibiotic therapies and the absence of antibiotic resistance, antipseudomonal treatment failure in MADs remains a significant clinical challenge. Understanding the drivers of antibiotic recalcitrance is essential for developing more effective treatments that eradicate persistent infections. The complex and dynamic environment of diseased airways makes it difficult to model antibiotic efficacy . We aimed to understand how mucin and eDNA concentrations, the two dominant polymers in respiratory mucus, alter the antibiotic tolerance of . Our results demonstrate that polymer concentration and molecular weight affect survival post antibiotic challenge. Polymer-driven antibiotic tolerance was not explicitly associated with reduced antibiotic diffusion. Lastly, we established a robust and standardized model for recapitulating the antibiotic tolerance of observed in expectorated sputum across age, underlying MAD etiology, and disease severity, which revealed the inherent variability in intrinsic antibiotic tolerance of host-evolved populations. Antibiotic treatment failure in chronic lung infections is associated with increased morbidity and mortality, illustrating the clinical challenge of bacterial infection control. Understanding the underlying infection environment, as well as the host and bacterial factors driving antibiotic tolerance and the ability to accurately recapitulate these factors , is crucial for improving antibiotic treatment outcomes. Here, we demonstrate that increasing concentration and molecular weight of mucin and host eDNA drive increased antibiotic tolerance to tobramycin. Through systematic testing and modeling, we identified a biologically relevant condition that recapitulates antibiotic tolerance observed in treated sputum. Ultimately, this study revealed a dominant effect of evolved bacterial populations in defining inter-subject antibiotic tolerance and establishes a robust and translatable model for therapeutic development.