Analysis of the Human Oral Microbiome of Smokers and Non-Smokers Using PCR-RFLP and Ribotyping

Abstract

Recent advances in the\rfield of microbial and medical ecology emphasize the critical role played by\roral bacteria in the delicate dynamic equilibrium of human health and disease,\rcreating the need to define the bacterial communities associated with healthy\rand non-healthy conditions and to capture shifts in community structure germane\rto diagnosis. Employing PCR-RFLP of the 16S rDNA gene from metagenomes and\rplate-wash (cultured) bacteria of oral wash from 10 volunteers, this study\revaluated the stability of oral bacteria in healthy subjects and documented\rcommunity shifts in smokers. Sequence analysis of selected 16S gene amplicons\rcloned with the Gene Hunter PCR-Trap vector and pCR 4-TOPO cloning kits was\rconducted to determine the bacteria identity and diversity indices of the two\rgroups. Ribopatterns generated by the restriction enzymes HaeIII and Sau3AI were\rsignificantly (p AluI using the GelCompare II software cluster analysis. A stable\rcore of bacteria DNA fingerprint was detected in all healthy subjects, and\rremained unchanged over the study period of 3 months. Signature bands (1500 bp\rwith HaeIII) in smokers and in\rnon-smokers (800 bp and 700 bp with Sau3A1) were evidently suggesting the\rpresence of potential biomarkers of healthy and non-healthy states. There was\rno significant difference in the DNA fingerprints of cultured and metagenomic\rextracts. The genera Xanthomonas, Streptococcus and phylum Candidatus\roccurred in large numbers in both groups, however, a major shift in composition\rwith the dominance of gram-negative bacteria in smokers compared to healthy\rsubjects was quite remarkable. Taxonomic diversity in smokers was quite high,\rincluding members of the genera Rothia, Synechococcus, Neisseria, Thiomargarita and\rPyrobaculum. These data highlight the presence of a stable core microbiome\ramidst a wide diversity, identify a distinct smokers’ cluster and open the way\rfor the search for potential biomarkers for specific diseases.