The Effects of Electronic Cigarettes on Oral Microbiome and Metabolome in 3D Tissue-Engineered Models

Abstract

Background and aim: Recent studies have shown that electronic cigarettes (ECs) use disrupts the oral microbiome composition and diversity, impairing the metabolic pathways of the mucosal cells. However, to date, no reports have evaluated the role of EC exposure in the context of oral metabolome. Hence, the aim of this study was to investigate the role of EC aerosol exposure in the dysregulation of the oral microbiome and metabolome profile using in vitro 3D organotypic models of human oral mucosa.

Methods: 3D tissue-engineered human oral mucosa models were generated and infected with oral microbes obtained from saliva of a healthy donor. The epithelial surface of the oral mucosal models was exposed directly to the EC aerosol (flavoured; with and without nicotine) as it came out of a simulated activated device that mimicked the clinical situation. A comprehensive assessment of oral microbiome community composition by bacterial 16S rRNA gene sequencing was performed. A gas chromatography-based mass spectrometry analysis was also conducted to identify the effect of vaping on the oral metabolome profile.

Results: A higher alpha diversity in flavoured EC with nicotine groups was observed compared to controls, with notable differences in bacterial taxa abundance. Metabolomics analysis further demonstrated distinct clustering of control, EC with flavoured nicotine, and flavoured EC groups, confirming 13 metabolites that were statistically higher in levels in flavoured EC with nicotine group, indicating the adverse effects of nicotine on the oral mucosa model. Altered metabolites were mainly enriched in pathways associated with oral cancer progression.

Conclusion: This study underscores the significant impact of EC use on oral health, highlighting alterations in the oral microbiome, bacterial composition, and metabolite profiles via a clinically relevant in vitro 3D organotypic model of human oral mucosa.

Keywords: Electronic cigarette; metabolome profile; microbiome; oral mucosa; tissue engineering.

Fig. 1

A representation of alpha diversity upon electronic cigarette (EC) exposure. Alpha diversity is represented by (A) observed OTUs, (B) Chao index, (C) ACE index, (D) Shannon index, (E) Simpson index bar plots from control, EC-flavour and EC-flavour+ nicotine-exposed oral mucosa models groups. Alpha diversity indices are on the Y-axis and EC exposure status is represented on the X-axis. Significant difference (p < .05) determined by a one-way ANOVA with Tukey post-hoc test.

Fig. 2

Unique microbial species are present in OMMs exposed to electronic cigarettes (ECs) with flavour and nicotine. A, Operational taxonomic unit Venn map. B, Core-pan operational taxonomic unit plot depicting the number of common and unique species between control EC-flavour and EC-flavour+ nicotine groups. C, Principal component analysis (PCA) and partial least square discriminant analysis for the control EC-flavour and EC-flavour+ nicotine groups beta diversity of EC users and NSNV controls. Bar plots depicting beta-diversity based on (E) Bray Curtis and (F) weighted UniFrac indices. Significant difference (p < .05) determined by a one-way ANOVA with Tukey post-hoc test.

Fig. 3

Bacterial abundance upon electronic cigarette (EC) exposure. Differentially abundant bacterial taxa in the salivary microbiota in control and OMMs exposed to EC-flavour or EC-flavour+ nicotine, based on 16S rRNA sequencing. Data are represented as mean ±SD. (*p < .05, **p < .01, ***p < .001). Significant difference (p < .05) determined by a one-way ANOVA with Tukey post-hoc test.

Fig. 4

Total ion chromatogram of derivatised metabolites. Metabolites (A) separated using gas chromatography (GC) 1, GC2, and GC3 run protocols (B) extracted from three different sample volumes of the secretome and separated using GC3 protocol.

Fig. 5

Principal component analysis (PCA) and partial least square discriminant analysis (PLS-DA) plots of assessed models. Multivariate analysis showing (A) PCA and (B) PLS-DA scores plots. C, Permutation test statistics of the PLS-DA model.

Fig. 6

Dysregulated metabolites upon electronic cigarette exposure. A, Significantly dysregulated metabolites with p < .05 are represented in red circles. B, Bar plot (green: oral mucosa model [OMM] MO; blue: OMM MO Flv; red: OMM MO Flv+Nic) of the significantly dysregulated metabolites. Univariate statistical analysis using one-way ANOVA with post-hoc Tukey's analysis. Plots are represented as mean ±SEM. **p ≤ .01. ***p ≤ .001.

Fig. 7

Generated metabolomic set enrichment analysis plot. Metabolomic Set Enrichment Analysis (MSEA) showing the most significantly altered functional metabolic pathways in the infected oral mucosa model that was exposed to flavored ECs containing nicotine (OMM MO Flv+Nic (Micro-orgranisms exposed to Flavored E-cigarette containing Nicotine)) group. The graph was obtained using the online tool MSEA by plotting on the y-axis the—log of p values from pathway enrichment analysis.