Dataset Information

Comparison of microbiomes from different niches of upper and lower airways in children and adolescents with cystic fibrosis.

ABSTRACT: Changes in the airway microbiome may be important in the pathophysiology of chronic lung disease in patients with cystic fibrosis. However, little is known about the microbiome in early cystic fibrosis lung disease and the relationship between the microbiomes from different niches in the upper and lower airways. Therefore, in this cross-sectional study, we examined the relationship between the microbiome in the upper (nose and throat) and lower (sputum) airways from children with cystic fibrosis using next generation sequencing. Our results demonstrate a significant difference in both ? and ?-diversity between the nose and the two other sampling sites. The nasal microbiome was characterized by a polymicrobial community while the throat and sputum communities were less diverse and dominated by a few operational taxonomic units. Moreover, sputum and throat microbiomes were closely related especially in patients with clinically stable lung disease. There was a high inter-individual variability in sputum samples primarily due to a decrease in evenness linked to increased abundance of potential respiratory pathogens such as Pseudomonas aeruginosa. Patients with chronic Pseudomonas aeruginosa infection exhibited a less diverse sputum microbiome. A high concordance was found between pediatric and adult sputum microbiomes except that Burkholderia was only observed in the adult cohort. These results indicate that an adult-like lower airways microbiome is established early in life and that throat swabs may be a good surrogate in clinically stable children with cystic fibrosis without chronic Pseudomonas aeruginosa infection in whom sputum sampling is often not feasible.

SUBMITTER: Boutin S

PROVIDER: S-EPMC4309611 | biostudies-literature | 2015

REPOSITORIES: biostudies-literature

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Comparison of microbiomes from different niches of upper and lower airways in children and adolescents with cystic fibrosis.

Boutin Sébastien S Graeber Simon Y SY Weitnauer Michael M Panitz Jessica J Stahl Mirjam M Clausznitzer Diana D Kaderali Lars L Einarsson Gisli G Tunney Michael M MM Elborn J Stuart JS Mall Marcus A MA Dalpke Alexander H AH

PloS one 20150128 1

Changes in the airway microbiome may be important in the pathophysiology of chronic lung disease in patients with cystic fibrosis. However, little is known about the microbiome in early cystic fibrosis lung disease and the relationship between the microbiomes from different niches in the upper and lower airways. Therefore, in this cross-sectional study, we examined the relationship between the microbiome in the upper (nose and throat) and lower (sputum) airways from children with cystic fibrosis ...[more]

PMID: 25629612

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Project description:The microbial metagenome in cystic fibrosis (CF) airways was investigated by whole-genome shotgun sequencing of total DNA isolated from nasal lavage samples, oropharyngeal swabs, and induced sputum samples collected from 65 individuals with CF aged 7 to 50 years. Each patient harbored a personalized microbial metagenome unique in microbial load and composition, the exception being monocultures of the most common CF pathogens Staphylococcus aureus and Pseudomonas aeruginosa from patients with advanced lung disease. The sampling of the upper airways by nasal lavage uncovered the fungus Malassezia restricta and the bacterium Staphylococcus epidermidis as prominent species. Healthy and CF donors harbored qualitatively and quantitatively different spectra of commensal bacteria in their sputa, even in the absence of any typical CF pathogen. If P. aeruginosa, S. aureus, or Stenotrophomonas maltophilia belonged to the trio of the most abundant species in the CF sputum metagenome, common inhabitants of the respiratory tract of healthy subjects, i.e., Eubacterium sulci, Fusobacterium periodonticum, and Neisseria subflava, were present only in low numbers or not detectable. Random forest analysis identified the numerical ecological parameters of the bacterial community, such as Shannon and Simpson diversity, as the key parameters that globally distinguish sputum samples from CF and healthy donors. IMPORTANCE Cystic fibrosis (CF) is the most common life-limiting monogenetic disease in European populations and is caused by mutations in the CFTR gene. Chronic airway infections with opportunistic pathogens are the major morbidity that determines prognosis and quality of life in most people with CF. We examined the composition of the microbial communities of the oral cavity and upper and lower airways in CF patients across all age groups. From early on, the spectrum of commensals is different in health and CF. Later on, when the common CF pathogens take up residence in the lungs, we observed differential modes of depletion of the commensal microbiota in the presence of S. aureus, P. aeruginosa, S. maltophilia, or combinations thereof. It remains to be seen whether the implementation of lifelong CFTR (cystic fibrosis transmembrane conductance regulator) modulation will change the temporal evolution of the CF airway metagenome.

Project description:The leading cause of morbidity and mortality in cystic fibrosis (CF) is progressive lung disease secondary to chronic airway infection and inflammation; however, what drives CF airway infection and inflammation is not well understood. By providing a physiological snapshot of the airway, metabolomics can provide insight into these processes. Linking metabolomic data with microbiome data and phenotypic measures can reveal complex relationships between metabolites, lower airway bacterial communities, and disease outcomes. In this study, we characterize the airway metabolome in bronchoalveolar lavage fluid (BALF) samples from persons with CF (PWCF) and disease control (DC) subjects and use multi-omic network analysis to identify correlations with the airway microbiome. The Biocrates targeted liquid chromatography mass spectrometry (LC-MS) platform was used to measure 409 metabolomic features in BALF obtained during clinically indicated bronchoscopy. Total bacterial load (TBL) was measured using quantitative polymerase chain reaction (qPCR). The Qiagen EZ1 Advanced automated extraction platform was used to extract DNA, and bacterial profiling was performed using 16S sequencing. Differences in metabolomic features across disease groups were assessed univariately using Wilcoxon rank sum tests, and Random forest (RF) was used to identify features that discriminated across the groups. Features were compared to TBL and markers of inflammation, including white blood cell count (WBC) and percent neutrophils. Sparse supervised canonical correlation network analysis (SsCCNet) was used to assess multi-omic correlations. The CF metabolome was characterized by increased amino acids and decreased acylcarnitines. Amino acids and acylcarnitines were also among the features most strongly correlated with inflammation and bacterial burden. RF identified strong metabolomic predictors of CF status, including L-methionine-S-oxide. SsCCNet identified correlations between the metabolome and the microbiome, including correlations between a traditional CF pathogen, Staphylococcus, a group of nontraditional taxa, including Prevotella, and a subnetwork of specific metabolomic markers. In conclusion, our work identified metabolomic characteristics unique to the CF airway and uncovered multi-omic correlations that merit additional study.

Dataset Information

Comparison of microbiomes from different niches of upper and lower airways in children and adolescents with cystic fibrosis.

Publications

Comparison of microbiomes from different niches of upper and lower airways in children and adolescents with cystic fibrosis.

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