The lung microbiome impacts 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 LRT microbiome were explored for a cohort of active (AS), former (FS), and never (NS) smokers. Bronchoalveolar lavages (BAL) were collected from 55 volunteer subjects (nine NS, 24 FS, and 22 AS). The LRT microbiome composition was assessed using 16S rRNA amplicon sequencing. Identification of differentially abundant taxa, co-occurrence patterns, discriminant analysis, and biomarker inferences were performed. The data show that smoking results in a loss in the diversity of the lower respiratory tract (LRT) microbiome, change in the co-occurrence patterns, and a weakening of the tight community structure present in healthy microbiomes. The increased abundance of Ralstonia taxa 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, suggesting that cessation of smoking may not be sufficient for the lung microbiota to return to a composition similar to that of never smokers. The 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.

This study was supported by the:
  • Florida Department of State (Award 09KW-10)
    • Principle Award Recipient: Giri Narasimhan
  • This is an open-access article distributed under the terms of the Creative Commons Attribution License.

Article metrics loading...

Loading full text...

Full text loading...

This is a required field
Please enter a valid email address
Approval was a Success
Invalid data
An Error Occurred
Approval was partially successful, following selected items could not be processed due to error