Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, Singapore.
Department of Respiratory and Critical Care Medicine, Singapore General Hospital, Singapore, Singapore.
Nat Med. 2021 Apr;27(4):688-699. doi: 10.1038/s41591-021-01289-7. Epub 2021 Apr 5.
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.
支气管扩张症是一种渐进性的慢性气道疾病,其特征是微生物定植和感染。我们提出了一种多组学方法,通过加权相似网络融合(https://integrative-microbiomics.ntu.edu.sg)整合支气管扩张症中的细菌、病毒和真菌群落。处于加重风险最高的患者的微生物共现网络的复杂性较低,气道微生物组的多样性降低,拮抗相互作用的程度更高。此外,纵向相互作用组动力学揭示了加重期间的微生物拮抗作用,在多组学稳定的情况下,这种拮抗作用在治疗后得到解决。假单胞菌相互作用组的评估表明,相互作用网络而不仅仅是丰度与加重风险相关,并且纳入微生物相互作用数据可以改善临床预测模型。独立队列的鸟枪法宏基因组测序验证了靶向分析中检测到的多组学相互作用,并证实了与加重的关联。综合微生物组学可以捕捉微生物相互作用来确定加重风险,而这是单个微生物组研究无法理解的。抗生素策略可能针对相互作用网络而不是单个微生物,为理解呼吸道感染提供了一种新方法。