16S rRNA sequencing reveals relationships among enrichment of oral microbiota in the lower respiratory tract and pulmonary nodules malignant progression

Abstract

Micro-aspiration of oral microorganisms results in considerable enrichment within the lower respiratory tract (LRT), constituting an early event in lung cancer pathogenesis. To explore the correlation between malignant risk of pulmonary nodules (PNs) and oral commensals enrichment in LRT, oral saliva and bronchial alveolar lavage fluid samples from 22 low-risk PN patients, 17 intermediate-risk PN patients, and 11 high-risk PN patients were analyzed using 16S rRNA gene sequencing. Alpha and beta diversity analyses reveal minimal variation in oral microbial diversity and abundance among patients with different risks of PN. In contrast, a significant reduction in the diversity of LRT microbiota is observed in patients at high risk of PN. Based on multigroup comparative analysis of species differences and the linear discriminant analysis effect size method, Synergistes and Tannerella were identified as the dominant bacterial genera in the oral and LRT of high-risk PN patients, respectively. The study found that the LRT microbiota of PN patients seemed to originate from the oral, and the high enrichment of oral microbiota in the lower respiratory tract was most common in high-risk PN patients. The predominant bacterial genera present in the oral cavity and LRT of patients with PN were identified through abundance variance analysis. Eight key microbial genera were found in both the oral cavity and LRT: Streptococcus, Granulicatella, Porphyromonas, Bacillus, Neisseria, Alloprevotella, Prevotella, and Leptotrichia. Notably, receiver operating characteristic analysis identified Streptococcus, Granulicatella, and Leptotrichia as reliable biomarkers to differentiate high-risk PN. Spearman correlation analysis confirmed that the accumulation of oral microorganisms in the LRT played an important role in the process of PN cancerization. The co-occurrence network showed that the coexistence of Veillonella and Streptococcus in the oral and LRT may be involved in the occurrence of PN, while the LRT cluster of Rothia occurred in high-risk PN patients. Correlation analysis among species identified microbial communities predominantly composed of Veillonella, which may facilitate pulmonary carcinogenesis.

Importance: This study is the first to elucidate the composition and interrelationships of oral and lower respiratory tract (LRT) microbiota in patients with pulmonary nodule (PN) across varying malignancy risk levels. We conducted an analysis to investigate the correlation between the malignant potential of PNs and the enrichment of oral microbiota within the LRT. Additionally, we explored the feasibility of utilizing oral-lower respiratory commensal microbiota as biomarkers to assess the benign and malignant nature of pulmonary nodules. This study aims to provide evidence supporting early diagnosis and intervention strategies for lung cancer.

Keywords: biomarkers; lower respiratory microbiome; malignant risk; oral microbiome; pulmonary nodules.

Fig 1

Structural characteristics and comparative analysis of oral microbiota in low-, medium-, and high-risk PN. (A) Proportions of bacterial phylum levels. (B) Proportions of bacterial genera levels. (C) Beta diversity differences estimated by principal coordinate analysis (PCoA). Top, weighted PCoA plots; bottom, unweighted PCoA plots. OSL group (blue dots); OSM group (red dots); OSH group (green dots); each dot represents a single sample.

Fig 2

Comparative analysis of oral microbiota in low-, medium-, and high-risk PN. (A) Comparative analysis of species differences in three groups. (B) Differential oral bacteria genus.

Fig 3

Structural characteristics and comparative analysis of LRT microbiota in low-, medium-, and high-risk PN. (A) Proportions of bacterial phylum levels. (B) Proportions of bacterial genera levels. (C) Differences in alpha diversity for chao1, Sobs index. (D) Beta diversity differences estimated by PCoA. Top, weighted PCoA plots; bottom, unweighted PCoA plots. BALFL group (blue dots); BALFM group (red dots); BALFH group (green dots); each dot represents a single sample. (E) Linear discriminant analysis (LDA＞3). (F) Comparative analysis of species differences in three groups. (G) Differential oral bacteria genus.

Fig 4

Comparative analysis of oral microbiota and LRT microbiota. (A) ASV Venn plot. Different colored graphics represent different groups, and the overlapping numbers between different colored graphics represent the number of ASVs shared between two groups. (B) Differences in alpha diversity for Shannon index. Top, low-risk group; middle, medium-risk group; bottom, high-risk group. (C) Beta diversity differences estimated by PCoA. Right, weighted PCoA plots; left, unweighted PCoA plots. BALF group (blue dots); OS group (red dots); top, low-risk group; middle, medium-risk group; bottom, high-risk group; each dot represents a single sample.

Fig 5

ROC analysis of eight potential microbiota biomarkers and combinations of the three microorganisms. Association: ROC analysis of Streptococcus, Granulicatella, and Leptotrichia.

Fig 6

Co-occurrence network of low-, medium-, and high-risk PN. (A) Co-occurrence network of LRT microbiome. BALFH group (blue dots); BALFL group (red dots); BALFM group (green dots). (B) Co-occurrence network of oral microbiome. OSH group (blue dots); OSL group (red dots); OSM group (green dots). Each node represented an ASV, and the circles indicate the shared dense clusters in both groups.

Fig 7

The analysis of the correlation between 13 differential genera and top 30 most abundant bacterial genera in OS and BALF. (A) Low-risk group. (B) Medium-risk group. (C) High-risk group (*P < 0.05, **P < 0.01, and ***P < 0.001).