Abstract
BackgroundStudies of the cystic fibrosis (CF) lung microbiome have consistently shown that lung function decline is associated with decreased microbial diversity due to the dominance of opportunistic pathogens. However, how this phenomenon is reflected in the metabolites and chemical environment of lung secretions remains poorly understood.MethodsHere we investigated the microbial and molecular composition of CF sputum samples using 16S rRNA gene amplicon sequencing and untargeted tandem mass spectrometry to determine their interrelationships and associations with clinical measures of disease severity.ResultsThe CF metabolome was found to exist in two states: one from patients with more severe disease that had higher molecular diversity and more Pseudomonas aeruginosa and the other from patients with better lung function having lower metabolite diversity and fewer pathogenic bacteria. The two molecular states were differentiated by the abundance and diversity of peptides and amino acids. Patients with severe disease and more pathogenic bacteria had higher levels of peptides. Analysis of the carboxyl terminal residues of these peptides indicated that neutrophil elastase and cathepsin G were responsible for their generation, and accordingly, these patients had higher levels of proteolytic activity from these enzymes in their sputum. The CF pathogen Pseudomonas aeruginosa was correlated with the abundance of amino acids and is known to primarily feed on them in the lung.ConclusionsIn cases of severe CF lung disease, proteolysis by host enzymes creates an amino acid-rich environment that P. aeruginosa comes to dominate, which may contribute to the pathogen’s persistence by providing its preferred carbon source.
Highlights
In the chronically infected cystic fibrosis (CF) lung, there is a severe microbial dysbiosis, where the organ becomes inundated with infectious agents, including bacteria, fungi, and viruses [1,2,3]
We combine microbiome sequencing, metabolomics and peptidomics on adult CF sputum to analyze the relationship between microbial/chemical composition and disease severity. We use these results to propose a model of how extensive neutrophilic proteolysis in the lung generates abundant peptides and amino acids that promote the growth and persistence of pathogens, leading to more severe lung disease
The microbiome profile of samples from meta-cluster 1 was enriched in anaerobic bacteria such as Streptoccoccus sp., Prevotella melaninogenica, and Veillonella dispar, whereas meta-cluster 2 was enriched in P. aeruginosa (Fig. 1)
Summary
In the chronically infected cystic fibrosis (CF) lung, there is a severe microbial dysbiosis, where the organ becomes inundated with infectious agents, including bacteria, fungi, and viruses [1,2,3] In response to this complex polymicrobial infection, the lung recruits high levels of neutrophils over decades, creating a highly inflammatory. High amounts of antibiotics from both acute and chronic therapies [11], and (2019) 7:23 microbial fermentation products including ethanol, acetate, 2-propanol, and 2,3-butanediol, are found in airway secretions [14, 15] Despite this well established knowledge of the CF microbial composition and growing understanding of the CF lung chemical environment, how the microbiome, metabolome and hyperinflammation collectively contribute to disease progression remains elusive. How this phenomenon is reflected in the metabolites and chemical environment of lung secretions remains poorly understood
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