Dysbiosis of lower respiratory tract microbiome are associated with inflammation and microbial function variety

Kang-Jie Li, Zi-Long Chen, Yao Huang, Rui Zhang, Xiao-Qian Luan, Ting-Ting Lei, Ling Chen, Kang-Jie Li, Zi-Long Chen, Yao Huang, Rui Zhang, Xiao-Qian Luan, Ting-Ting Lei, Ling Chen

Abstract

Background: Lower respiratory tract (LRT) microbiome has been reported to associate with pulmonary diseases. Unregulated inflammation is an underlying cause of variable lung diseases. The lung microbiome may play an important role in the smoking-induced inflammatory lung diseases. What's more, the function of microbiome may be more important for understanding how microbes interact with host. Our study aims to explore the effects of smoking on the lower respiratory tract microbiome, the association between variation of lower respiratory tract microbiome and inflammation and whether smoking exposure changes the function of lower respiratory tract microbime.

Methods: Forty male mice were randomly divided into smoking group and non-smoking group, and the smoking group was exposed to cigarette smoke for 2 h per day for 90 days. After experiment, the blood samples were collected to measure the concentration of interleukin-6 (IL-6) and C reactive protein (CRP) by ELISA. Lung tissue samples were used to detect the community and diversity of lower respiratory tract microbiome through 16S rRNA gene quantification and sequencing technology. ANOSIM and STAMP were performed to analyze the differences of the microbial community structure between smoking group and non-smoking group. SPSS 24.0 software was used to analyze the correlations between microbiome and inflammation mediators through scatter plots and Spearman correlation coefficient. Microbial metabolic function was predicted by PICRUSt based on the 16 s rRNA gene quantification and sequencing results. PATRIC database was searched for the potential pathogenic bacteria in lower respiratory tract.

Results: Our results suggested that smoking had markedly effects on the microbiota structure of lower respiratory tract based on Bray-Curtis distance (R2 = 0.084, p = 0.005) and on unweighted uniFrac distance (R2 = 0.131, p = 0.002). Smoking mainly affected the abundance of microbiome which belong to Proteobacteria phyla and Firmicutes phyla. Moreover, our results also found that smoking increased the abundance of Acinetobacter, Bacillus and Staphylococcus, which were defined as pathogenic bacteria. Inflammatory mediators were observed to associate with certain microbiome at every level. Most of microbiome which were associated with inflammation belonged to Proteobacteria phyla or Firmicutes phyla. Moreover, we found that the decreased microbiome in smoking group, including Oceanospirillales, Desulfuromonadales, Nesterenkonia, and Lactobacillaceae, all were negatively correlated with IL-6 or CRP. Based on the level of inflammation, the abundance of microbiome differs. At genus level, Lactobacillus, Pelagibacterium, Geobacter and Zoogloea were significantly higher in smoking group with lower IL-6 concentration. The abundance of microbiome was not observed any statistical difference in subgroups with different weight. Three dominant genus, defined as pathogen, were found higher in the smoking group. The microbial functional prediction analysis revealed that ABC-type transport systems, transcription factors, amino acide transport and metabolism, arginine and proline metabolism et al. were distinctively decreased in smoking group, while the proportions of replication, recombination and repair, ribosome, DNA repair and recombination proteins were increased in smoking group (q < 0.05).

Conclusions: Members of Proteobacteria phyla and Firmicutes phyla played an important role in the microbial community composition and keeping a relatively balanced homeostasis. Microbiome dysbiosis might break the balance of immune system to drive lung inflammation. There might exist potential probiotics in lower respiratory tract, such as Lactobacillaceae. The altered function of Lower respiratory tract microbiome under smoking exposure may affect the physiological homeostasis of host.

Keywords: Function of microbiome; Inflammatory mediators; Lower respiratory tract; Microbiome; Smoking.

Conflict of interest statement

The authors declare that they have no competing interests.

Figures

Fig. 1
Fig. 1
Heat map of correlation coefficient value. Column A represents the correlation between IL-6 and microbiome in smoking group. Column B represents the correlation between CRP and microbiome in smoking group. Column C represents the correlation between IL-6 and microbiome in non-smoking group. Column D represents the correlation between CRP and microbiome in non-smoking group. Twenty microbiome which significantly associate with any inflammatory mediator in either smoking group or non-smoking group are stated
Fig. 2
Fig. 2
Relative abundance of function at KEGG Level1. Samples B2 to B20 belong to the smoking group and samples c3 to c16 belong to the non-smoking group
Fig. 3
Fig. 3
Difference of metabolism, genetic information processing and environmental information processing in two groups (level 1). Group B colored with blue represents the smoking group and group C colored with yellow represents the non-smoking group
Fig. 4
Fig. 4
41 level 2 KEGG Orthology groups in smoking and non-smoking groups. Samples A2 to B20 belong to the smoking group and samples C1 to C18 belong to the non-smoking group
Fig. 5
Fig. 5
Differences among the 41 KEGG2 pathway between two groups. Group B colored with blue represents the smoking group and group C colored with yellow represents the non-smoking group
Fig. 6
Fig. 6
The differences of metabolic pathways at KEGG level 3 between two groups. Group B colored with blue represents the smoking group and group C colored with yellow represents the non-smoking group
Fig. 7
Fig. 7
The category of General function prediction at COG level2. Samples A2 to B20 belong to the smoking group and samples C1 to C18 belong to the non-smoking group
Fig. 8
Fig. 8
The difference of specific functions between two groups at COG level2. Group B colored with blue represents the smoking group and group C colored with yellow represents the non-smoking group
Fig. 9
Fig. 9
Difference of the specific function of proteins in two groups. Group B colored with blue represents the smoking group and group C colored with yellow represents the non-smoking group

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