Lower respiratory tract microbiome composition and community interactions in smokers

Study information

Reviewed Marked as Reviewed by Folakunmi on 2024-2-16

study design

prospective cohort

Citation

PMID PubMed identifier for scientific articles.

37091735

DOI Digital object identifier for electronic documents.

10.1099/acmi.0.000497.v3

URI

Authors

Campos M, Cickovski T, Fernandez M, Jaric M, Wanner A, Holt G, Donna E, Mendes E, Silva-Herzog E, Schneper L, Segal J, Amador DM, Riveros JD, Aguiar-Pulido V, Banerjee S, Salathe M, Mathee K, Narasimhan G

Journal

Access microbiology

Year

2023

Keywords:

clustering, co-occurrence networks, lower respiratory tract (LRT), microbiome, smoking

The lung microbiome impacts on lung function, making any smoking-induced changes in the lung microbiome potentially significant. The complex co-occurrence and co-avoidance patterns between the bacterial taxa in the lower respiratory tract (LRT) microbiome were explored for a cohort of active (AS), former (FS) and never (NS) smokers. Bronchoalveolar lavages (BALs) were collected from 55 volunteer subjects (9 NS, 24 FS and 22 AS). The LRT microbiome composition was assessed using 16S rRNA amplicon sequencing. Identification of differentially abundant taxa and co-occurrence patterns, discriminant analysis and biomarker inferences were performed. The data show that smoking results in a loss in the diversity of the LRT microbiome, change in the co-occurrence patterns and a weakening of the tight community structure present in healthy microbiomes. The increased abundance of the genus Ralstonia in the lung microbiomes of both former and active smokers is significant. Partial least square discriminant and DESeq2 analyses suggested a compositional difference between the cohorts in the LRT microbiome. The groups were sufficiently distinct from each other to suggest that cessation of smoking may not be sufficient for the lung microbiota to return to a similar composition to that of NS. The linear discriminant analysis effect size (LEfSe) analyses identified several bacterial taxa as potential biomarkers of smoking status. Network-based clustering analysis highlighted different co-occurring and co-avoiding microbial taxa in the three groups. The analysis found a cluster of bacterial taxa that co-occur in smokers and non-smokers alike. The clusters exhibited tighter and more significant associations in NS compared to FS and AS. Higher degree of rivalry between clusters was observed in the AS. The groups were sufficiently distinct from each other to suggest that cessation of smoking may not be sufficient for the lung microbiota to return to a similar composition to that of NS.