Dataset Information

Neutrophilic proteolysis in the cystic fibrosis lung correlates with a pathogenic microbiome.

ABSTRACT:

Background

Studies 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.

Methods

Here 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.

Results

The 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.

Conclusions

In 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.

SUBMITTER: Quinn RA

PROVIDER: S-EPMC6375204 | biostudies-literature | 2019 Feb

REPOSITORIES: biostudies-literature

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Publications

Neutrophilic proteolysis in the cystic fibrosis lung correlates with a pathogenic microbiome.

Quinn Robert A RA Adem Sandeep S Mills Robert H RH Comstock William W DeRight Goldasich Lindsay L Humphrey Gregory G Aksenov Alexander A AA Melnik Alexei V AV da Silva Ricardo R Ackermann Gail G Bandeira Nuno N Gonzalez David J DJ Conrad Doug D O'Donoghue Anthony J AJ Knight Rob R Dorrestein Pieter C PC

Microbiome 20190213 1

<h4>Background</h4>Studies 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.<h4>Methods</h4>Here we investigated the microbial and molecular composition of CF sputum samples using 16S rRNA gene amplicon sequencing and untarge ...[more]

PMID: 30760325

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Project description:In cystic fibrosis, dynamic and complex communities of microbial pathogens and commensals can colonize the lung. Cultured isolates from lung sputum reveal high inter- and intraindividual variability in pathogen strains, sequence variants, and phenotypes; disease progression likely depends on the precise combination of infecting lineages. Routine clinical protocols, however, provide a limited overview of the colonizer populations. Therefore, a more comprehensive and precise identification and characterization of infecting lineages could assist in making corresponding decisions on treatment. Here, we describe longitudinal tracking for four cystic fibrosis patients who exhibited extreme clinical phenotypes and, thus, were selected from a pilot cohort of 11 patients with repeated sampling for more than a year. Following metagenomics sequencing of lung sputum, we find that the taxonomic identity of individual colonizer lineages can be easily established. Crucially, even superficially clonal pathogens can be subdivided into multiple sublineages at the sequence level. By tracking individual allelic differences over time, an assembly-free clustering approach allows us to reconstruct multiple lineage-specific genomes with clear structural differences. Our study showcases a culture-independent shotgun metagenomics approach for longitudinal tracking of sublineage pathogen dynamics, opening up the possibility of using such methods to assist in monitoring disease progression through providing high-resolution routine characterization of the cystic fibrosis lung microbiome.IMPORTANCE Cystic fibrosis patients frequently suffer from recurring respiratory infections caused by colonizing pathogenic and commensal bacteria. Although modern therapies can sometimes alleviate respiratory symptoms by ameliorating residual function of the protein responsible for the disorder, management of chronic respiratory infections remains an issue. Here, we propose a minimally invasive and culture-independent method to monitor microbial lung content in patients with cystic fibrosis at minimal additional effort on the patient's part. Through repeated sampling and metagenomics sequencing of our selected cystic fibrosis patients, we successfully classify infecting bacterial lineages and deconvolute multiple lineage variants of the same species within a given patient. This study explores the application of modern computational methods for deconvoluting lineages in the cystic fibrosis lung microbiome, an environment known to be inhabited by a heterogeneous pathogen population that complicates management of the disorder.

Dataset Information

Neutrophilic proteolysis in the cystic fibrosis lung correlates with a pathogenic microbiome.

Background

Methods

Results

Conclusions

Publications

Neutrophilic proteolysis in the cystic fibrosis lung correlates with a pathogenic microbiome.

Similar Datasets

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