Ecosystem

Internal medicine

Microbiome

Bronchiectasis

Bioinformatics

Biology

Gene

Metagenomics

Ecology

Immunology

Exacerbation

Lung

Interactome

Genetics

Medicine

Biome

Nature Medicine

Bronchiectasis, a progressive chronic airway disease, is characterized by microbial colonization and infection. We present an approach to the multi-biome that integrates bacterial, viral and fungal communities in bronchiectasis through weighted similarity network fusion (                https://integrative-microbiomics.ntu.edu.sg                              ). Patients at greatest risk of exacerbation have less complex microbial co-occurrence networks, reduced diversity and a higher degree of antagonistic interactions in their airway microbiome. Furthermore, longitudinal interactome dynamics reveals microbial antagonism during exacerbation, which resolves following treatment in an otherwise stable multi-biome. Assessment of the Pseudomonas interactome shows that interaction networks, rather than abundance alone, are associated with exacerbation risk, and that incorporation of microbial interaction data improves clinical prediction models. Shotgun metagenomic sequencing of an independent cohort validated the multi-biome interactions detected in targeted analysis and confirmed the association with exacerbation. Integrative microbiomics captures microbial interactions to determine exacerbation risk, which cannot be appreciated by the study of a single microbial group. Antibiotic strategies probably target the interaction networks rather than individual microbes, providing a fresh approach to the understanding of respiratory infection. Integrated analysis of bacterial, fungal and microbial communities in the airways of patients with bronchiectasis demonstrates that interaction networks, rather than the relative abundance of any single microbial species, are associated with exacerbation risk.

Integrative microbiomics in bronchiectasis exacerbations