The impact of modulator therapy on the Pseudomonas aeruginosa cystic fibrosis lung transcriptome
Year: 2026
Type: article
Abstract: Chronic lung infection with Pseudomonas aeruginosa is a major complication of cystic fibrosis (CF), contributing to lung function decline and increased morbidity and mortality. Laboratory models are used to study CF infections, but their relevance depends on how accurately they reproduce microbial physiology during human infection. We previously developed a framework that uses bacterial gene expression in human infections to quantify model accuracy. Here, we applied this framework to determine how a major therapeutic intervention impacts P. aeruginosa physiology in the lungs of people with CF (pwCF) and to develop and evaluate refined preclinical models. We focused on elexacaftor/tezacaftor/ivacaftor (ETI), a highly effective CFTR modulator therapy that has improved outcomes for pwCF. However, evidence indicates that P. aeruginosa lung infections persist despite ETI therapy. Analysis of P. aeruginosa transcriptomes from human sputum collected before and after ETI initiation revealed minimal changes in gene expression, indicating that the CF airway continues to support a similar bacterial transcriptional state despite therapy. We then evaluated how strain selection, zinc limitation, and polymicrobial coculture influence the ability of laboratory models to recapitulate P. aeruginosa gene expression in human CF sputum. Growth of CF clinical isolates in zinc-limited synthetic CF sputum medium produced the most accurate model, whereas population-based cultures and coculture with Staphylococcus aureus had limited effects. These findings show that ETI therapy has little impact on the conserved P. aeruginosa transcriptional state in human CF sputum and that refined sputum-like models remain useful for studying persistent infection in the postmodulator era.
Language: English
Subfield: Pulmonary and Respiratory Medicine
Field: Medicine
Domain: Health Sciences
Open Access status: hybrid
Awards: G5335124949, G5351519675, G9001302692
OpenAlex ID: W7222270217
