Enrichment of the lung microbiome with oral taxa is associated with lung inflammation of a Th17 phenotype

Abstract

Microaspiration is a common phenomenon in healthy subjects, but its frequency is increased in chronic inflammatory airway diseases, and its role in inflammatory and immune phenotypes is unclear. We have previously demonstrated that acellular bronchoalveolar lavage samples from half of the healthy people examined are enriched with oral taxa (here called pneumotypeSPT) and this finding is associated with increased numbers of lymphocytes and neutrophils in bronchoalveolar lavage. Here, we have characterized the inflammatory phenotype using a multi-omic approach. By evaluating both upper airway and acellular bronchoalveolar lavage samples from 49 subjects from three cohorts without known pulmonary disease, we observed that pneumotypeSPT was associated with a distinct metabolic profile, enhanced expression of inflammatory cytokines, a pro-inflammatory phenotype characterized by elevated Th-17 lymphocytes and, conversely, a blunted alveolar macrophage TLR4 response. The cellular immune responses observed in the lower airways of humans with pneumotypeSPT indicate a role for the aspiration-derived microbiota in regulating the basal inflammatory status at the pulmonary mucosal surface.

Figures

Figure 1. Major differences in microbial composition of the lower airways are driven by enrichment with either supraglottic taxa or background taxa

a, Unsupervised hierarchical clustering of most abundant taxa (relative abundance ≥3% in any sample) for BAL samples, upper airway and background samples. Upper airway samples were obtained by oral wash or by separate bronchoscopy. BAL samples were obtained after passing the upper airways without suctioning and wedging in a subsegment of the lower airways. The dendrogram indicates two well-separated clusters, one dominated by background samples and 27 of the 49 BAL samples, and a second dominated by upper airway samples plus 22 of the 49 BAL samples. The heat map shows that the first cluster is enriched with Acidocella, Pseudomonas and Sphingomonas and the second cluster is enriched with taxa most commonly found in the upper airways such as Prevotella, Rothia and Veillonella. b, Principal coordinates analysis (PCoA) based on weighted UniFrac distances demonstrate that pneumotypeSPT BAL samples clustered separately from pneumotypeBPT BAL samples. Samples from all three cohorts can be found in both pneumotype clusters. c, Comparison of UniFrac distance between paired acellular BAL samples from New York University (NYU) (n = 31), the Lung HIV Microbiome Project (LHMP) (n = 14) and Ohio State University (OSU) (n = 4) show that there is greater UniFrac distance between pneumotypeSPT and pneumotypeBPT than between different institutions (represented as median (IQR), statistical significance of sample groupings based on Adonis). d, Cladogram representing results from calculated LDA LEfSe comparing taxonomic composition of BAL samples from pneumotypeSPT and pneumotypeBPT. Multiple significant taxonomic differences were observed at different phylogenetic levels, with labels in the cladogram written for differences at the phylum level and indicated by letters for differences at the class level.

Figure 2. Comparison of inferred metagenomes of pneumotypeSPT and pneumotypeBPT

a, PCoA based on Jensen–Shannon divergence shows that the metagenome of pneumotypeSPT is significantly different from the metagenome of pneumotypeBPT. b, LEfSe analysis was performed using the summarized functional annotation for the KOs annotated to metabolism inferred for each BAL sample. This analysis showed multiple functional differences in the genomic composition of pneumotypeSPT as compared with pneumotypeBPT. c, STAMP was used to determine metabolic pathways differentially enriched (P < 0.05) and their effect size (η2). The 15 top metabolic pathways for each pneumotype are represented with effect size and relative abundance.

Figure 3. Correlation between the lower airway microbiome and metabolome

a,b, Average UniFrac distances between pairs of BAL samples and upper airways was positively (a) or negatively (b) correlated with levels of metabolites in BAL fluid. Red symbols represent BAL samples identified as pneumotypeSPT and green symbols represent BAL samples identified as pneumotypeBPT (lines represent medians and standard error, SE, P values are based on Spearman’s ρ). c, A co-occurrence network for genus-level summarized taxa was built using SparCC as described in the Methods. Genera (circles) were then correlated with levels of metabolites, and significantly correlated metabolites (grey octagons) are represented in the network. Genera identified as markers for pneumotypeBPT are in light green and genera identified as markers for pneumotypeSPT are in light red. Cytoscape 3.2.1 was used to visualize the network with a prefuse force-directed layout, with the length of edges being 1 – ρ for positive correlations and absolute (ρ) for negative correlations. Nodes in close proximity are therefore highly positively correlated, and nodes further apart are highly negatively correlated.

Figure 4. Similarity of the lower airway microbiome with the upper airway microbiome is associated with the percentage of lymphocytes in BAL

a,b, Average UniFrac distances between pairs of BAL samples and upper airways were negatively correlated with the percentage of CD4+ IL17+ cells (a) and the percentage of lymphocytes (b) in BAL. c, Similarity of the lower airway microbiome with the upper airway microbiome is associated with increased expression of STAT3 mRNA in bronchial epithelial cells. d, Negative significant correlations were found between average UniFrac distances of BAL to the upper airway and fractalkine and IL-1α. Red symbols represent BAL samples identified as pneumotypeSPT and green symbols represent BAL samples identified as pneumotypeBPT (lines represent median and SE, P value based on Spearman’s ρ). e, Network analysis built around co-occurrent taxa as defined previously (see Fig. 3). Taxa (circles) remaining in the model were then correlated with levels of cells and cytokines in BAL (grey triangles). Genera identified as markers for pneumotypeBPT are shown in light green and genera identified as markers for pneumotypeSPT are shown in light red. Significant correlations are shown in the network. The network was visualized with Cytoscape with the same parameters as previously defined. GM-CSF, granulocyte-macrophage colony-stimulating factor; G-CSF, granulocyte colony-stimulating factor; GRO, growth-related oncogene-α.

Figure 5. PneumotypeSPT is associated with a blunted TLR4 response of alveolar macrophages

Alveolar macrophages of subjects with pneumotypeSPT or pneumotypeBPT were cultured for 24 h and exposed to 10 ng LPS or media alone. Cytokine production was compared for LPS/MA to calculate fold induction. Average UniFrac distances between pairs of BAL samples and upper airways correlated to fold induction of MDC, IL-6 and GM-CSF. Red symbols represent BAL samples identified as pneumotypeSPT and green symbols represent BAL samples identified as pneumotypeBPT (lines represent median and SE, P value based on Spearman’s ρ).