Mac Aogain, Micheal and Narayana, Jayanth Kumar and Tiew, Pei Yee and Ali, Nur A'tikah Binte Mohamed and Yong, Valerie Fei Lee and Jaggi, Tavleen Kaur and Lim, Albert Yick Hou and Keir, Holly R. and Dicker, Alison J. and Thng, Kai Xian and Tsang, Akina and Ivan, Fransiskus Xaverius and Poh, Mau Ern and Oriano, Martina and Aliberti, Stefano and Blasi, Francesco and Low, Teck Boon and Ong, Thun How and Oliver, Brian and Giam, Yan Hui and Tee, Augustine and Koh, Mariko Siyue and Abisheganaden, John Arputhan and Tsaneva-Atanasova, Krasimira and Chalmers, James D. and Chotirmall, Sanjay H. (2021) Integrative microbiomics in bronchiectasis exacerbations. Nature Medicine, 27 (4). ISSN 1078-8956, DOI https://doi.org/10.1038/s41591-021-01289-7.
Full text not available from this repository.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.
| Item Type: | Article |
|---|---|
| Funders: | Ministry of Health-Singapore National Medical Research Council, Singapore [Grant No: NMRC/TA/0048/2016], Clinician-Scientist Individual Research Grant [Grant No: MOH-000141], NTU Integrated Medical, Biological and Environmental Life Sciences (NIMBELS) [Grant No: NIM/03/2018 ], British Lung Foundation through the GSK/British Lung Foundation Chair of Respiratory Research, Scottish Government Chief Scientist Office [Grant No: SCAF/17/03], UK Research & Innovation (UKRI) Engineering & Physical Sciences Research Council (EPSRC) [Grant No: EP/N014391/1] |
| Uncontrolled Keywords: | Bronchiectasis; Chronic airway disease; Respiratory infection |
| Subjects: | Q Science > QD Chemistry Q Science > QH Natural history > QH301 Biology |
| Divisions: | Faculty of Medicine |
| Depositing User: | Ms Zaharah Ramly |
| Date Deposited: | 27 May 2022 01:56 |
| Last Modified: | 27 May 2022 01:56 |
| URI: | http://eprints.um.edu.my/id/eprint/34639 |
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