There is accumulating evidence in the biomedical literature suggesting the role of smoking in increasing the risk of oral diseases including some oral cancers. Smoking alters microbial attributes of the oral cavity by decreasing the commensal microbial population and increasing the pathogenic microbes. This study aims to investigate the shift in the salivary microbiota between smokers and non-smokers in Jordan. Our methods relied on high-throughput next-generation sequencing (NGS) experiments for V3-V4 hypervariable regions of the 16S rRNA gene, followed by comprehensive bioinformatics analysis including advanced multidimensional data visualization methods and statistical analysis approaches. Six genera-Streptococcus, Prevotella, Vellionella, Rothia, Neisseria, and Haemophilus-predominated the salivary microbiota of all samples with different percentages suggesting the possibility for the salivary microbiome to restored after quitting smoking. Three genera-Streptococcus, Prevotella, and Veillonella-showed significantly elevated levels among smokers at the expense of Neisseria in non-smokers. In conclusion, smoking has a definite impact on shifting the salivary microbiota in smokers. We can suggest that there is microbial signature at the genera level that can be used to classify smokers and non-smokers by Linear Discriminant Analysis Effect Size (LEfSe) based on the salivary abundance of genera. Proteomics and metabolomics studies are highly recommended to fully understand the effect of bacterial endotoxin release and xenobiotic metabolism on the bacterial interrelationships in the salivary microbiome and how they affect the growth of each other in the saliva of smokers.
Keywords: 16S rRNA; Jordan; bioinformatics; microbiome; microbiota; next-generation sequencing; operational taxonomic unit (OTU); saliva; smoking.