Sputum Bacterial Metacommunities in Distinguishing Heterogeneity in Respiratory Health and Disease

• Published in: Frontiers in microbiology Vol. 13; p. 719541
• Main Authors: Si, Jiyeon, Choi, Yongbin, Raes, Jeroen, Ko, Gwangpyo, You, Hyun Ju
• Format: Journal Article
• Language: English
• Published: Switzerland Frontiers Media S.A 31.03.2022
• Subjects: community typing; inflammation; metacommunity; Microbiology; network; Prevotella; sputum microbiome; inflammation; COPD metacommunity in sputum microbiome; Prevotella; sputum microbiome; community typing; metacommunity; network
• ISSN: 1664-302X; 1664-302X
• DOI: 10.3389/fmicb.2022.719541

Cluster-based analysis, or community typing, has been attempted as a method for studying the human microbiome in various body niches with the aim of reducing variations in the bacterial composition and linking the defined communities to host health and disease. In this study, we have presented the bacterial subcommunities in the healthy and the diseased population cohorts and have assessed whether these subcommunities can distinguish different host health conditions. We performed community typing analysis on the sputum microbiome dataset obtained from a healthy Korean twin-family cohort ( = 202) and an external chronic obstructive pulmonary disease (COPD) cohort ( = 324) and implemented a networks analysis to investigate the associations of bacterial metacommunities with host health parameters and microbial interactions in disease. The analysis of the sputum microbiome of a healthy Korean cohort revealed high levels of interindividual variation, which was driven by two dominant bacteria: and . Community typing of the cohort samples identified three metacommunities, namely, 1 (N1), 2 (N2), and (P), each of which showed different functional potential and links to host traits (e.g., triglyceride levels, waist circumference, and levels of high-sensitivity C-reactive protein). In particular, the -dominant metacommunity showed a low-community diversity, which implies an adverse health association. Network analysis of the healthy twin cohort illustrated co-occurrence of with pathogenic anaerobic bacteria; this bacterial cluster was negatively associated with high-density lipoproteins but positively correlated with waist circumference, blood pressure, and pack-years. Community typing of the external COPD cohort identified three sub-metacommunities: one exclusively comprising healthy subjects (HSs) and the other two (CS1 and CS2) comprising patients. The two COPD metacommunities, CS1 and CS2, showed different abundances of specific pathogens, such as and , as well as differing functional potential and community diversity. Network analysis of the COPD cohort showed enhanced bacterial coexclusions in the CS metacommunities when compared with HS metacommunity. Overall, our findings point to a potential association between pulmonary and host health and disease, making it possible to implement community typing for the diagnosis of heterogenic respiratory disease.