Faculty Bibliography

Micro-aspiration commonly occurs in health and its prevalence is increased in many lung diseases. A dysbiotic signature identified by enrichment with oral microbes is associated with increased inflammation and distinct metabolic profile in the lung microenvironment. 16S rRNA gene sequencing is commonly used for taxonomic annotation and inferred functional capacity. However, it is desirable to actually measure the function of these bacteria. We therefore took an approach that combines marker gene amplification, whole genome shotgun sequencing (WGS), RNA sequencing (RNA) and measured metabolites. Upper (UA), lower airway (BAL), and background (BKG) samples were obtained via bronchoscopy from 19 healthy subjects. 16S rRNA gene sequencing was used to assess the microbiota and identify dysbiosis among lower airway samples. In parallel, functional microbial signatures were identified via WGS metagenome and RNA metatrascriptome sequencing. Dirichlet Multinomial Modelling identified two clusters from the 16S data where: 12 BAL samples clustered with BKG samples and were characterized as BAL. BPT (enriched with background characteristic taxa such as Acinetobacter, Pseudomonadales) and 7 clustered with most UA samples and were characterized as BAL. SPT (enriched with oral commensals such as Veillonella and Streptococcus). Using Gene-Set-Enrichment Analysis (GSEA), there is very little overlap between the three sequencing methods for taxonomic annotation (Figure 1A-F). For functional annotation, in samples clustered to BAL. SPT, withWGS, most upregulated pathways are associated with Ribosome while with RNA a number of pathways are upregulated including lipid metabolism and fatty acid metabolism. Comparing the differentially expressed pathways for BAL. SPT samples, between the three sequencing methods, some pathways share directionality and significance (Figure 1H,J,L). For example, fatty acid biosynthesis is significantly upregulated in all three sequencing methods. Short chain fatty acids (SCFAs) were therefore measured. UA and BAL samples had significantly higher levels of acetate and propionate when compared to BKG samples. However, only with RNA, KOs associated to these SCFAs are significantly elevated in both UA and BAL samples (Figure 1K), similar to measuring these SCFAs by mass spectrometry. In addition, taxa associated with these KOs in RNA are known upper airway commensals (Figure 1M). 16S rRNA gene sequencing does not provide accurate functional information in the lower airway microbiome. The addition of RNA metatranscriptomic characterization of the lower airway microbiota is feasible and provides functional insights that are consistent with metabolomic signatures identified in a dysbiotic signature. The addition of this technology to standard microbiome investigations may provide important insight into the interaction between microbiome and host

The use of next-generation sequencing and multiomic analysis reveals new insights on the identity of microbes in the lower airways blurring the lines between commensals and pathogens. Microbes are not found in isolation; rather they form complex metacommunities where microbe-host and microbe-microbe interactions play important roles on the host susceptibility to pathogens. In addition, the lower airway microbiota exert significant effects on host immune tone. Thus, this review highlights the roles that microbes in the respiratory tract play in the development of pneumonia.

BACKGROUND:In lung cancer, upregulation of the PI3K pathway is an early event that contributes to cell proliferation, survival, and tissue invasion. Upregulation of this pathway was recently described as associated with enrichment of the lower airways with bacteria identified as oral commensals. We hypothesize that host-microbe interactions in the lower airways of subjects with lung cancer affect known cancer pathways. METHODS:Airway brushes were collected prospectively from subjects with lung nodules at time of diagnostic bronchoscopy, including 39 subjects with final lung cancer diagnoses and 36 subjects with non-cancer diagnosis. Additionally, samples from 10 healthy control subjects were included. 16S rRNA gene amplicon sequencing and paired transcriptome sequencing (RNAseq) were performed on all airway samples. In addition, an in vitro model with airway epithelial cells exposed to bacteria/bacterial products was performed. RESULTS:The composition of the lower airway transcriptome in the cancer patients was significantly different from the controls, which included upregulation of ERK and PI3K signaling pathways. The lower airways of lung cancer patients were enriched for oral taxa (Streptococcus and Veillonella), which was associated with upregulation of the ERK and PI3K signaling pathways. In vitro exposure of airway epithelial cells to Veillonella, Prevotella, and Streptococcus led to upregulation of these same signaling pathways. CONCLUSIONS:The data presented here shows that several transcriptomic signatures previously identified as relevant to lung cancer pathogenesis are associated with enrichment of the lower airway microbiota with oral commensals.

Background: Aspiration is associated with non-tuberculous mycobacterial (NTM) pulmonary disease and airway dysbiosis is associated with increased inflammation. We examined whether NTM disease was associated with a distinct airway microbiota and immune profile.Methods: 297 oral wash and induced sputum samples were collected from 106 participants with respiratory symptoms and imaging abnormalities compatible with NTM. Lower airway samples were obtained in 20 participants undergoing bronchoscopy. 16S rRNA gene and a nested mycobacteriome sequencing approaches characterised microbiota composition. Inflammatory profiles of lower airway samples were also examined.Results: The prevalence of NTM+ cultures was 58%. Few changes were noted in microbiota characteristic or composition in oral wash and sputum samples among groups. Among NTM+ samples, 27% of the lower airway samples were enriched with Mycobacterium A mycobacteriome approach identified Mycobacterium in a greater percentage of samples, including some non-pathogenic strains. In NTM+ lower airway samples, taxa identified as oral commensals were associated with increased inflammatory biomarkers.Conclusions: The 16S rRNA gene sequencing approach is not sensitive in identifying NTM among airway samples which are culture positive. However, associations between lower airway inflammation and microbiota signatures suggest a potential role for these microbes in the inflammatory process in NTM disease.

In pediatric patients with chronic cough, respiratory culture techniques commonly yield negative results. Studies using culture-independent methods have found a high relative abundance of oral microbes in the lower airways, suggesting that the topographical continuity, and dynamics of the intraluminal contents of the aerodigestive system likely influence the lower airway microbiota. We hypothesize that in subjects with chronic cough, clinical diagnosis will correlate with distinct microbial signatures detected using culture-independent methods.