mSystems. 2026 Jul 2:e0058026. doi: 10.1128/msystems.00580-26. Online ahead of print.
ABSTRACT
Mucins modulate microbial metabolism, which is crucial in many human infections. It is unknown whether the metabolic alterations induced by mucin are universal or unique across varied clinical isolates of bacterial pathogens. We experimentally profiled a representative set of seven clinical Pseudomonas aeruginosa isolates in a synthetic cystic fibrosis growth medium in the presence or absence of physiological mucin, using high-throughput transcriptomic analyses. We observed mucin-induced transcriptional changes across many central and peripheral metabolic pathways in all the clinical isolates. We utilized contextualized metabolic network models of P. aeruginosa clinical isolates to gain a deeper understanding of the relationship between mucin-driven metabolic modulations and the resulting shifts in metabolic dependencies. Our network model-driven analyses and subsequent growth experiments reveal differential effects of mucin on isolate metabolism and growth inhibition of key genes. Characterizing this rich set of P. aeruginosa isolates allows for a deeper understanding of the diversity of the pathogen and how mucins modulate isolate-specific pathways that may significantly impact treatment strategies.IMPORTANCEMucin, the principal component of mucus, is a key regulator of host-microbe interactions and substantially influences P. aeruginosa, a major antibiotic-resistant pathogen. While mucins are known to influence microbial physiology, most bacterial physiology studies rely on reference strains or mucus-free systems, failing to capture the complexity of host-associated environments and clinical isolate diversity. To address these shortcomings, we used purified mucin from porcine lung and a physiologically relevant medium to examine seven clinical isolates of P. aeruginosa. Transcriptomic profiling and genome-scale modeling revealed both universal and isolate-specific mucin-driven metabolic shifts, identifying pathways critical to adaptability and candidate drug targets. These findings highlight mucin as an active influencer of P. aeruginosa metabolism and underscore its potential implications for developing more effective, context-specific infection treatments.
PMID:42390224 | DOI:10.1128/msystems.00580-26