ArticleMicrobiome2017
The metabolic footprint of the airway bacterial community in cystic fibrosis.
Article in Microbiome, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 2 of them syntheses that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
4 citing papers in PubMed, 2 syntheses or guidelines pooled it, 16 citations in OpenAlex.
- Bacteria of the lung microbiome and health biomarkers in chronic airway disease: a systematic review and meta-analysis.NPJ biofilms and microbiomes · 2026Pooled it
- The respiratory microbiota alpha-diversity in chronic lung diseases: first systematic review and meta-analysis.Respiratory research · 2022Pooled it
- A Different Microbiome Gene Repertoire in the Airways of Cystic Fibrosis Patients with Severe Lung Disease.International journal of molecular sciences · 2017Trial
- Airway Microbiome in Children with Cystic Fibrosis: A Review of Microbial Shifts and Therapeutic Impacts.Medicina (Kaunas, Lithuania) · 2025Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors at 2 institutions in 1 country.
Funding
Abstract
backgroundProgressive, chronic bacterial infection of the airways is a leading cause of death in cystic fibrosis (CF). Culture-independent methods based on sequencing of the bacterial 16S rRNA gene describe a distinct microbial community that decreases in richness and diversity with disease progression. Understanding the functional characteristics of the microbial community may aid in identifying potential therapies and may assist in management, but current methods are cumbersome. Here, we demonstrate the use of an oxidative metabolic assay as a complement to sequencing methods to describe the microbiome in the airways of patients with CF.
methodsExpectorated sputum was collected from 16 CF subjects and 8 control subjects. The Biolog Gen III Microplate was used in a community-level physiological profiling (CLPP)-based assay to examine oxidative metabolic activity. 16S rRNA V4 amplicon sequencing was used to characterize the taxonomy and diversity of the samples. Correlations were then identified among the oxidative activity and taxonomy data. In an additional paired analysis, sputum from seven CF subjects were collected at two separate clinic visits and compared for oxidative activity, taxonomy, and diversity.
resultsSignificant differences in oxidative metabolic activity, microbial taxonomy, and diversity were found between the CF and control sputum samples. Oxidative activity correlated positively with total genera but not with other measures of diversity or taxonomy, demonstrating that the metabolic assay complements the structural aspects of the microbiome. As expected, Pseudomonas was significantly enriched in CF samples, while Streptococcus and Prevotella were similarly abundant in both CF and control samples. Paired analysis of CF samples at separate clinic visits revealed comparable oxidative activity that correlated with similar stability in taxonomy and diversity.
conclusionsThe CLPP assay used in this study complements existing sequencing methods to delineate the oxidative metabolic footprint of the CF airway bacterial community. This method may be useful to study the CF microbial community over time and with changes in disease state.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.