ArticleNPJ biofilms and microbiomes
Microbiome networks and change-point analysis reveal key community changes associated with cystic fibrosis pulmonary exacerbations.
Article in NPJ biofilms and microbiomes. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 44 papers, 1 of them a synthesis that pooled it.
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Who cites it
44 citing papers in PubMed, 1 synthesis or guideline pooled it, 88 citations in OpenAlex.
- Meta-Analysis of Altered Gut Microbiota Reveals Microbial and Metabolic Biomarkers for Colorectal Cancer.Microbiology spectrum · 2022Pooled it
- Dynamic balance of the lung microbiome in health and respiratory diseases.Chinese medical journal · 2026Review
- HS-AssociatedMicroorganisms · 2025Article
- Longitudinal gut microbiota dynamics in Antarctic research mission crews.Frontiers in microbiology · 2025Article
- Network analysis of gut microbial communities reveal key genera for a multiple sclerosis cohort with Mycobacterium avium subspecies paratuberculosis infection.Gut pathogens · 2024Article
- Infection and the microbiome in bronchiectasis.European respiratory review : an official journal of the European Respiratory Society · 2024Review
- Microbial community organization designates distinct pulmonary exacerbation types and predicts treatment outcome in cystic fibrosis.Nature communications · 2024Observational
- Microbial community organization designates distinct pulmonary exacerbation types and predicts treatment outcome in cystic fibrosis.Research square · 2024Article
- Longitudinal changes in the cystic fibrosis airway microbiota with time and treatment.Journal of cystic fibrosis : official journal of the European Cystic Fibrosis Society · 2024Article
- The presence of cystic fibrosis-related diabetes modifies the sputum microbiome in cystic fibrosis disease.American journal of physiology. Lung cellular and molecular physiology · 2024Article
- Specialty grand challenge: how can we use integrative approaches to understand microbial community dynamics?Frontiers in systems biology · 2024Article
- Lung microbiome: new insights into bronchiectasis' outcome.Frontiers in cellular and infection microbiology · 2024Review
- Microbial influencers and cotton leaf curl disease (CLCuD) susceptibility: a network perspective.Frontiers in microbiology · 2024Article
- Longitudinal development of the airway metagenome of preterm very low birth weight infants during the first two years of life.ISME communications · 2023Article
- Exploring Co-occurrence patterns and microbial diversity in the lung microbiome of patients with non-small cell lung cancer.BMC microbiology · 2023Article
- Delivery Mode and Perinatal Antibiotics Influence the Infant Gut Bacteriome and Mycobiome: A Network Analysis.Journal of fungi (Basel, Switzerland) · 2023Article
- Microbial Dysregulation of the Gut-Lung Axis in Bronchiectasis.American journal of respiratory and critical care medicine · 2023Article
- Gut microbiome signatures of Yorkshire Terrier enteropathy during disease and remission.Scientific reports · 2023Article
- Deficient butyrate-producing capacity in the gut microbiome is associated with bacterial network disturbances and fatigue symptoms in ME/CFS.Cell host & microbe · 2023Article
- Exploring the Cystic Fibrosis Lung Microbiome: Making the Most of a Sticky Situation.Journal of the Pediatric Infectious Diseases Society · 2022Review
Corrections and comments
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Authors and funding
13 authors at 3 institutions in 1 country.
Funding
Abstract
Over 90% of cystic fibrosis (CF) patients die due to chronic lung infections leading to respiratory failure. The decline in CF lung function is greatly accelerated by intermittent and progressively severe acute pulmonary exacerbations (PEs). Despite their clinical impact, surprisingly few microbiological signals associated with PEs have been identified. Here we introduce an unsupervised, systems-oriented approach to identify key members of the microbiota. We used two CF sputum microbiome data sets that were longitudinally collected through periods spanning baseline health and PEs. Key taxa were defined based on three strategies: overall relative abundance, prevalence, and co-occurrence network interconnectedness. We measured the association between changes in the abundance of the key taxa and changes in patient clinical status over time via change-point detection, and found that taxa with the highest level of network interconnectedness tracked changes in patient health significantly better than taxa with the highest abundance or prevalence. We also cross-sectionally stratified all samples into the clinical states and identified key taxa associated with each state. We found that network interconnectedness most strongly delineated the taxa among clinical states, and that anaerobic bacteria were over-represented during PEs. Many of these anaerobes are oropharyngeal bacteria that have been previously isolated from the respiratory tract, and/or have been studied for their role in CF. The observed shift in community structure, and the association of anaerobic taxa and PEs lends further support to the growing consensus that anoxic conditions and the subsequent growth of anaerobic microbes are important predictors of PEs.
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