Integrative microbiomics in bronchiectasis exacerbations

Micheál Mac Aogáin, Jayanth Kumar Narayana, Pei Yee Tiew, Nur A’tikah Binte Mohamed Ali, Valerie Fei Lee Yong, Tavleen Kaur Jaggi, Albert Yick Hou Lim, Holly R. Keir, Alison J. Dicker, Kai Xian Thng, Akina Tsang, Fransiskus Xaverius Ivan, Mau Ern Poh, Martina Oriano, Stefano Aliberti, Francesco Blasi, Teck Boon Low, Thun How Ong, Brian Oliver, Yan Hui GiamAugustine Tee, Mariko Siyue Koh, John Arputhan Abisheganaden, Krasimira Tsaneva-Atanasova, James D. Chalmers, Sanjay H. Chotirmall

Research output: Contribution to journalArticlepeer-review

Abstract

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.

Original languageEnglish
Pages (from-to)688-699
Number of pages12
JournalNature Medicine
Volume27
Early online date5 Apr 2021
DOIs
Publication statusPublished - Apr 2021

Keywords

  • Respiratory tract diseases
  • Translational research

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