A longitudinal characterization of the Non-Cystic Fibrosis Bronchiectasis airway microbiome.
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ABSTRACT:
SUBMITTER: Woo TE
PROVIDER: S-EPMC6499777 | biostudies-literature | 2019 May
REPOSITORIES: biostudies-literature
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A longitudinal characterization of the Non-Cystic Fibrosis Bronchiectasis airway microbiome.
Woo T E TE Lim R R Heirali A A AA Acosta N N Rabin H R HR Mody C H CH Somayaji R R Surette M G MG Sibley C D CD Storey D G DG Parkins M D MD
Scientific reports 20190503 1
A diverse microbiota exists within the airways of individuals with non-cystic fibrosis bronchiectasis (nCFB). How the lung microbiome evolves over time, and whether changes within the microbiome correlate with future disease progression is not yet known. We assessed the microbial community structure of 133 serial sputa and subsequent disease course of 29 nCFB patients collected over a span of 4-16 years using 16S rRNA paired-end sequencing. Interestingly, no significant shifts in the microbial c ...[more]
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Project description:BackgroundThe prevalence of fungal disease in cystic fibrosis (CF) and non-CF bronchiectasis is increasing and the clinical spectrum is widening. Poor sensitivity and a lack of standard diagnostic criteria renders interpretation of culture results challenging. In order to develop effective management strategies, a more accurate and comprehensive understanding of the airways fungal microbiome is required. The study aimed to use DNA sequences from sputum to assess the load and diversity of fungi in adults with CF and non-CF bronchiectasis.MethodsNext generation sequencing of the ITS2 region was used to examine fungal community composition (n = 176) by disease and underlying clinical subgroups including allergic bronchopulmonary aspergillosis, chronic necrotizing pulmonary aspergillosis, non-tuberculous mycobacteria, and fungal bronchitis. Patients with no known active fungal disease were included as disease controls.ResultsITS2 sequencing greatly increased the detection of fungi from sputum. In patients with CF fungal diversity was lower, while burden was higher than those with non-CF bronchiectasis. The most common operational taxonomic unit (OTU) in patients with CF was Candida parapsilosis (20.4%), whereas in non-CF bronchiectasis sputum Candida albicans (21.8%) was most common. CF patients with overt fungal bronchitis were dominated by Aspergillus spp., Exophiala spp., Candida parapsilosis or Scedosporium spp.ConclusionThis study provides a framework to more accurately characterize the extended spectrum of fungal airways diseases in adult suppurative lung diseases.
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Project description:Bronchiectasis are often encountered in clinical practice, and are characterized by abnormal airway dilatation and distortion associated with impaired mucociliary clearance and mucous plugging, which are frequently associated with recurrent infections. Numerous etiologies can underlie the development of bronchiectasis, but the most important distinction in research and clinical practice is between bronchiectasis due to cystic fibrosis (CF) and bronchiectasis due to all other reasons (non-CF bronchiectasis). The causes of non-CF bronchiectasis are varied and often unclear. Patients disease severity and phenotypes of non-CF bronchiectasis also varied, which can influence disease trajectory, frequency of exacerbations and mortality. This article reviews the published evidence and suggests interventions to enhance airways clearance in patients with non-CF bronchiectasis, which are key components of an individualized therapeutic program in order to achieve symptomatic relief and prevention of exacerbations and functional decline.
| S-EPMC6830171 | biostudies-literature
Project description:Rationale: Non-cystic fibrosis bronchiectasis is characterized by airway mucus accumulation and sputum production, but the role of mucus concentration in the pathogenesis of these abnormalities has not been characterized.Objectives: This study was designed to: 1) measure mucus concentration and biophysical properties of bronchiectasis mucus; 2) identify the secreted mucins contained in bronchiectasis mucus; 3) relate mucus properties to airway epithelial mucin RNA/protein expression; and 4) explore relationships between mucus hyperconcentration and disease severity.Methods: Sputum samples were collected from subjects with bronchiectasis, with and without chronic erythromycin administration, and healthy control subjects. Sputum percent solid concentrations, total and individual mucin concentrations, osmotic pressures, rheological properties, and inflammatory mediators were measured. Intracellular mucins were measured in endobronchial biopsies by immunohistochemistry and gene expression. MUC5B (mucin 5B) polymorphisms were identified by quantitative PCR. In a replication bronchiectasis cohort, spontaneously expectorated and hypertonic saline-induced sputa were collected, and mucus/mucin concentrations were measured.Measurements and Main Results: Bronchiectasis sputum exhibited increased percent solids, total and individual (MUC5B and MUC5AC) mucin concentrations, osmotic pressure, and elastic and viscous moduli compared with healthy sputum. Within subjects with bronchiectasis, sputum percent solids correlated inversely with FEV1 and positively with bronchiectasis extent, as measured by high-resolution computed tomography, and inflammatory mediators. No difference was detected in MUC5B rs35705950 SNP allele frequency between bronchiectasis and healthy individuals. Hypertonic saline inhalation acutely reduced non-cystic fibrosis bronchiectasis mucus concentration by 5%.Conclusions: Hyperconcentrated airway mucus is characteristic of subjects with bronchiectasis, likely contributes to disease pathophysiology, and may be a target for pharmacotherapy.
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| S-EPMC4379018 | biostudies-literature
Project description:BackgroundEmerging experimental and epidemiological evidence highlights a crucial cross-talk between the intestinal flora and the lungs, termed the "gut-lung axis". However, the function of the gut microbiota in bronchiectasis remains undefined. In this study, we aimed to perform a multi-omics-based approach to identify the gut microbiome and metabolic profiles in patients with bronchiectasis.MethodsFecal samples collected from non-CF bronchiectasis patients (BE group, n = 61) and healthy volunteers (HC group, n = 37) were analyzed by 16 S ribosomal RNA (rRNA) sequencing. The BE group was divided into two groups based on their clinical status: acute exacerbation (AE group, n = 31) and stable phase (SP group, n = 30). Further, metabolome (lipid chromatography-mass spectrometry, LC-MS) analyses were conducted in randomly selected patients (n = 29) and healthy volunteers (n = 31).ResultsDecreased fecal microbial diversity and differential microbial and metabolic compositions were observed in bronchiectasis patients. Correlation analyses indicated associations between the differential genera and clinical parameters such as bronchiectasis severity index (BSI). Disease-associated gut microbiota was screened out, with eight genera exhibited high accuracy in distinguishing SP patients from HCs in the discovery cohort and validation cohort using a random forest model. Further correlation networks were applied to illustrate the relations connecting disease-associated genera and metabolites.ConclusionThe study uncovered the relationships among the decreased fecal microbial diversity, differential microbial and metabolic compositions in bronchiectasis patients by performing a multi-omics-based approach. It is the first study to characterize the gut microbiome and metabolome in bronchiectasis, and to uncover the gut microbiota's potentiality as biomarkers for bronchiectasis.Trial registration This study is registered with ClinicalTrials.gov, number NCT04490447.
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Project description:The identification of 16S rDNA biomarkers from respiratory samples to describe the continuum of clinical disease states within persons having cystic fibrosis (CF) has remained elusive. We sought to combine 16S, metagenomics, and metabolomics data to describe multiple transitions between clinical disease states in 14 samples collected over a 12-month period in a single person with CF. We hypothesized that each clinical disease state would have a unique combination of bacterial genera and volatile metabolites as a potential signature that could be utilized as a biomarker of clinical disease state. Taxonomy identified by 16S sequencing corroborated clinical culture results, with the majority of the 109 PCR amplicons belonging to the bacteria grown in clinical cultures (Escherichia coli and Staphylococcus aureus). While alpha diversity measures fluctuated across disease states, no significant trends were present. Principle coordinates analysis showed that treatment samples trended toward a different community composition than baseline and exacerbation samples. This was driven by the phylum Bacteroidetes (less abundant in treatment, log2 fold difference -3.29, p = 0.015) and the genus Stenotrophomonas (more abundant in treatment, log2 fold difference 6.26, p = 0.003). Across all sputum samples, 466 distinct volatile metabolites were identified with total intensity varying across clinical disease state. Baseline and exacerbation samples were rather uniform in chemical composition and similar to one another, while treatment samples were highly variable and differed from the other two disease states. When utilizing a combination of the microbiome and metabolome data, we observed associations between samples dominated Staphylococcus and Escherichia and higher relative abundances of alcohols, while samples dominated by Achromobacter correlated with a metabolomics shift toward more oxidized volatiles. However, the microbiome and metabolome data were not tightly correlated; examining both the metagenomics and metabolomics allows for more context to examine changes across clinical disease states. In our study, combining the sputum microbiome and metabolome data revealed stability in the sputum composition through the first exacerbation and treatment episode, and into the second exacerbation. However, the second treatment ushered in a prolonged period of instability, which after three additional exacerbations and treatments culminated in a new lung microbiome and metabolome.
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