Determining How a Dynamic Microbiome Contributes to Cystic Fibrosis Lung Disease

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Project Summary Pulmonary exacerbations are a pervasive complication of chronic lung infection. These events cause an increase in symptom severity, loss of lung function and require aggressive antibiotic treatment. While the bacterial communities in chronically infected lungs are believed to be involved in exacerbations, there is a poor understanding of how or why this happens. Our preliminary evidence indicates there is a dysbiotic shift that occurs during CF pulmonary exacerbation (CFPE) to the dominance of anaerobic bacteria. This proposal attempts to further test this hypothesis and reveal mechanisms driving microbiome dynamics during CFPEs. Cystic Fibrosis (CF) is a chronic lung disease that is caused by mutations in the Cystic Fibrosis Transmembrane Conductance Regulator gene (CFTR). These mutations cause a buildup of mucus in the lungs due to disrupted epithelial ion transport. This abundant mucus plugs the conducting airways, and due to the presence of bacteria, creates anaerobic environments. Although poorly characterized as CF pathogens, anaerobic bacteria are ubiquitous in CF lungs and believed to play a role in the disease. Our preliminary data indicates that there is a dysbiotic shift from pathogen dominance to anaerobes during CFPE development. Antibiotic treatment kills these anaerobes allowing the classic pathogens of CF, such as Pseudomonas aeruginosa, to again take over the lung. We are able to reproduce these dynamics in the laboratory allowing us to directly study their cause. This project will investigate CFPE microbial dynamics using clinical samples from patients, laboratory experiments and mathematical modeling. We will collect longitudinal sputum samples from patients through exacerbation events and analyze the microbial taxonomic composition, host response and metabolite production. In addition, we will use a novel culture model that mimics the CF lung environment (called the WinCF model) to test our hypothesis in vivo. WinCF can be manipulated to test the effect of chemical and biological perturbations on the CF microbial community structure, metabolism and virulence. We will test multiple variables on the structure and function of the CF microbial community in an attempt to understand the drivers of dynamics observed during exacerbations. Results from these studies will be mathematically modeled using a recently developed model of the CF microbiome growing in mucus- plugged bronchioles. The entire project will utilize cutting edge multi-omics methods including microbiome sequencing, metabolomics and novel bioinformatics data analysis platforms. Our scientific rationale is that a better understanding of what causes microbial changes during CFPEs will lead to more efficacious and targeted therapy against pathogens.