Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/160494
Title: Integrative microbiomics in bronchiectasis exacerbations
Authors: Mac Aogáin, Micheál
Narayana, Jayanth Kumar
Tiew, Pei Yee
Nur A'tikah Mohamed Ali
Yong, Valerie Fei Lee
Jaggi, Tavleen K.
Lim, Albert Yick Hou
Keir, Holly R.
Dicker, Alison J.
Thng, Kai Xian
Tsang, Akina
Ivan, Fransiskus Xaverius
Poh, Mau Ern
Oriano, Martina
Aliberti, Stefano
Blasi, Francesco
Low, Teck Boon
Ong, Thun How
Oliver, Brian
Giam, Yan Hui
Tee, Augustine
Koh, Mariko Siyue
Abisheganaden, John Arputhan
Tsaneva-Atanasova, Krasimira
Chalmers, James D.
Chotirmall, Sanjay Haresh
Keywords: Science::Medicine
Issue Date: 2021
Source: Mac Aogáin, M., Narayana, J. K., Tiew, P. Y., Nur A'tikah Mohamed Ali, Yong, V. F. L., Jaggi, T. K., Lim, A. Y. H., Keir, H. R., Dicker, A. J., Thng, K. X., Tsang, A., Ivan, F. X., Poh, M. E., Oriano, M., Aliberti, S., Blasi, F., Low, T. B., Ong, T. H., Oliver, B., ...Chotirmall, S. H. (2021). Integrative microbiomics in bronchiectasis exacerbations. Nature Medicine, 27(4), 688-699. https://dx.doi.org/10.1038/s41591-021-01289-7
Project: NMRC/TA/0048/2016
MOH-000141
NIM/03/2018
Journal: Nature Medicine
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.
URI: https://hdl.handle.net/10356/160494
ISSN: 1078-8956
DOI: 10.1038/s41591-021-01289-7
Rights: © 2021 The Author(s), under exclusive licence to Springer Nature America, Inc. All rights reserved.
Fulltext Permission: none
Fulltext Availability: No Fulltext
Appears in Collections:LKCMedicine Journal Articles

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