Substantial Differences in the Subgingival Microbiome Measured by 16S Metagenomics According to Periodontitis Status in Older Women

• Published in: Dentistry journal 2018-10, Vol.6 (4), p.58
• Main Authors: LaMonte, Michael J, Genco, Robert J, Zheng, Wei, McSkimming, Daniel I, Andrews, Christopher A, Hovey, Kathleen M, Li, Lu, Sun, Yijun, Buck, Michael J, Millen, Amy E, Falkner, Karen L, Wactawski-Wende, Jean
• Format: Article
• Language: English
• Subjects: Abundance; Aging; Bacteria; Biofilms; Decomposition; Discriminant analysis; Endotoxins; Gene expression; Genes; Gingiva; Gluconeogenesis; Glycolysis; Gum disease; Immunosenescence; Kinases; Krebs cycle; Measurement techniques; menopause; Metagenomics; microbiome; Microbiomes; Microbiota; Microorganisms; Older people; Pathogens; periodontal disease; Periodontitis; Periodontium; Post-menopause; Protein kinase; Proteolysis; rRNA 16S; Target recognition; Tricarboxylic acid cycle; women; Womens health
• ISSN: 2304-6767; 2304-6767
• DOI: 10.3390/dj6040058

Aging invokes physiological changes, such as immunosenescence and inflammation, that could increase host susceptibility to oral microbiome shifts that enable periodontitis progression in later life. At present, there is a dearth of studies specifically evaluating the oral microbiome and periodontitis in older adults. We used high-throughput untargeted sequencing methods and functional metagenomic analyses to assess and compare the subgingival biofilm of postmenopausal women (mean age 71 years) according to periodontitis status. Subgingival plaque samples were obtained from 15 postmenopausal women with no periodontitis, and from 15 women with severe periodontitis, determined by probing measures. The 16S rRNA gene (V1⁻V3 region) was sequenced on the 454 FLX platform. The PICRUSt technique was used to provide information on what the potential functional characteristics of microbiota might be in healthy, compared with diseased, periodontium. The subgingival microbiome associated with periodontitis showed clear differences to that associated with health. Of the 464 species identified, 22.8% had elevated abundance in disease, while only 6.3% had elevated abundance in health. Among the 12 most prevalent organisms in periodontitis, one-half have previously been recognized as periodontal pathogens by other investigators. The subgingival microbiome in periodontitis contained genes that could code for specific activities, including microbial mobility, synthesis of endotoxin, and proteolytic degradation. The healthy microbiome included genes that could code for sustaining microbial life, including encoding for transporters, glycolysis, gluconeogenesis, the Krebs cycle, and protein kinases. In the present study on postmenopausal women, aged 60 and older, the subgingival microbiome differed in composition and potential function between those with and without periodontitis. Studies of functional gene expression, such as transcriptomics, are needed to definitively identify the molecules carrying out functions associated with pathogenic subgingival complexes. This, in turn, could lead to identification of targets for enhanced management of periodontitis and, possibly, other diseases, in later life.