The dysbiosis of oral microbiome (OM) precedes the clinical signs of periodontal disease. Its simple measure thus could indicate individuals at risk of periodontitis development; however, such a tool is still missing. Up to now, numerous microbial taxa were associated with periodontal health or periodontitis. The outputs of most studies could, nevertheless, be slightly biased from following two reasons: First, the healthy group is often characterized only by the absence of the disease, but the individuals could already suffer from dysbiosis without any visible signs. Second, the healthy/diseased OM characteristics are frequently determined based on average data obtained for whole groups of periodontally healthy persons versus patients. Especially in smaller sets of tested individuals the typical individual variability can thus complicate the unambiguous assignment of oral taxa to respective state of health. In this work the taxonomic composition of OM was evaluated for 20 periodontally healthy individuals and 15 patients with chronic periodontitis. The narrowed selection set of the most diseased patients (confirmed by clinical parameters) and the most distant group of healthy individuals with the lowest probability of dysbiosis was determined by clustering analysis and used for identification of marker taxa. Based on their representation in each individual oral cavity we proposed the numeric index of periodontal health called R/G value. Its diagnostic potential was further confirmed using independent set of 20 periodontally healthy individuals and 20 patients with periodontitis with 95 percent of samples assigned correctly. We also assessed the individual temporal OM dynamics in periodontal health and we compared it to periodontitis. We revealed that the taxonomic composition of the system changes dynamically but generally it ranges within values typical for periodontal health or transient state, but far from values typical for periodontitis. R/G value tool, formulated from individually evaluated data, allowed us to arrange individual OMs into a continuous series, instead of two distinct groups, thus mimicking the gradual transformation of a virtual person from periodontal health to disease. The application of R/G value index thus represents a very promising diagnostic tool for early prediction of persons at risk of developing periodontal disease.

Department of Genetics and Microbiology Faculty of Science Charles University Prague Czechia

Institute of Dental Medicine 1st Faculty of Medicine Charles University and General University Hospital Prague Prague Czechia

Institute of Microbiology v v i BIOCEV Czech Academy of Sciences Vestec Czechia

Institute of Microbiology v v i Czech Academy of Sciences Prague Czechia

Zobrazit více v PubMed

Abusleme L., Dupuy A. K., Dutzan N., Silva N., Burleson J. A., Strausbaugh L. D., et al. . (2013). The subgingival microbiome in health and periodontitis and its relationship with community biomass and inflammation. Isme. J. 7, 1016–1025.  10.1038/ismej.2012.174 PubMed DOI PMC

Baldrian P., Kolařík M., Štursová M., Kopecký J., Valášková V., Větrovský T., et al. . (2012). Active and total microbial communities in forest soil are largely different and highly stratified during decomposition. ISME J. 6, 248–258. 10.1038/ismej.2011.95 PubMed DOI PMC

Boutin S., Hagenfeld D., Zimmermann H., El Sayed N., Höpker T., Greiser H. K., et al. . (2017). Clustering of Subgingival Microbiota Reveals Microbial Disease Ecotypes Associated with Clinical Stages of Periodontitis in a Cross-Sectional Study. Front. Microbiol. 8, 340.  10.3389/fmicb.2017.00340 PubMed DOI PMC

Camelo-Castillo A. J., Mira A., Pico A., Nibali L., Henderson B., Donos N., et al. . (2015). Subgingival microbiota in health compared to periodontitis and the influence of smoking. Front. Microbiol. 6, 119. 10.3389/fmicb.2015.00119 PubMed DOI PMC

Curtis M. A., Diaz P. I., Van Dyke T. E. (2020). The role of the microbiota in periodontal disease. Periodontol. 2000 83, 14–25.  10.1111/prd.12296 PubMed DOI

Dowd S. E., Callaway T. R., Wolcott R. D., Sun Y., McKeehan T., Hagevoort R. G., et al. . (2008). Evaluation of the bacterial diversity in the feces of cattle using 16S rDNA bacterial tag-encoded FLX amplicon pyrosequencing (bTEFAP). BMC Microbiol. 8, 125.  10.1186/1471-2180-8-125 PubMed DOI PMC

Griffen A. L., Beall C. J., Campbell J. H., Firestone N. D., Kumar P. S., Yang Z. K., et al. . (2012). Distinct and complex bacterial profiles in human periodontitis and health revealed by 16S pyrosequencing. Isme. J. 6, 1176–1185.  10.1038/ismej.2011.191 PubMed DOI PMC

Hajishengallis G., Lamont R. J. (2012). Beyond the red complex and into more complexity: The polymicrobial synergy and dysbiosis (PSD) model of periodontal disease etiology. Mol. Oral. Microbiol. 27, 409–419.  10.1111/j.2041-1014.2012.00663.x PubMed DOI PMC

Hammer O., Harper D. A. T., Ryan P. D. (2001). PAST: paleontological statistics software package for education and data analysis. Palaeontol. Electron. 4 (1), 9.

Hong B. -Y., Araujo M. V. F., Strausbaugh L. D., Terzi E., Ioannidou E., Diaz P. I. (2015). Microbiome profiles in periodontitis in relation to host and disease characteristics. PLoS One 10(5), e0127077. PubMed PMC

Kirst M. E., Li E. C., Alfant B., Chi Y.-Y., Walker C., Magnusson I., et al. . (2015). Dysbiosis and alterations in predicted functions of the subgingival microbiome in chronic periodontitis. Appl. Environ. Microbiol. 81, 783–793. 10.1128/AEM.02712-14 PubMed DOI PMC

Kistler J. O., Booth V., Bradshaw D. J., Wade W. G. (2013). Bacterial Community Development in Experimental Gingivitis. PloS One 8 (8), e71227.  10.1371/journal.pone.0071227 PubMed DOI PMC

Klappenbach J. A., Saxman P. R., Cole J. R., Schmidt T. M. (2001). rrndb: the ribosomal RNA operon copy number database. Nucleic Acids Res. 29, 181–184. 10.1093/nar/29.1.181 PubMed DOI PMC

Lamont R., Koo H., Hajishengallis G. (2018). The oral microbiota: dynamic communities and host interactions. Nat. Rev. Microbiol. 16, 745–759.  10.1038/S41579-018-0089-X PubMed DOI PMC

Li Y., He J., He Z., Zhou Y., Yuan M., Xu X., et al. . (2014). Phylogenetic and functional gene structure shifts of the oral microbiomes in periodontitis patients. ISME J. 8 (9), 1879–1891. 10.1038/ismej.2014.28 PubMed DOI PMC

Meuric V., Le Gall-David S., Boyer E., Acuña-Amador L., Martin B., Fong S. B., et al. . (2017). Signature of microbial dysbiosis in periodontitis. Appl. Environ. Microbiol. 83 (14), e00462-17.  10.1128/AEM.00462-17 PubMed DOI PMC

Parameswaran P., Jalili R., Tao L., Shokralla S., Gharizadeh B., Ronaghi M., et al. . (2007). A pyrosequencing-tailored nucleotide barcode design unveils opportunities for large-scale sample multiplexing. Nucleic Acids Res. 35, 130.  10.1093/nar/gkm760 PubMed DOI PMC

Pérez-Chaparro P. J., Gonçalves C., Figueiredo L. C., Faveri M., Lobão E., Tamashiro N., et al. . (2014). Newly Identified Pathogens Associated with Periodontitis A Systematic Review. J. Dent. Res. 93, 846–858. 10.1177/0022034514542468 PubMed DOI PMC

Schloss P. D., Westcott S. L., Ryabin T., Hall J. R., Hartmann M., Hollister E. B., et al. . (2009). Introducing mothur: open-source, platform-independent, community-supported software for describing and comparing microbial communities. Appl. Env. Microbiol. 75, 7537–7541.  10.1128/AEM.01541-09 PubMed DOI PMC

Shi B., Chang M., Martin J., Mitreva M., Lux R., Klokkevold P., et al. . (2015). Dynamic changes in the subgingival microbiome and their potential for diagnosis and prognosis of periodontitis. MBio 6, e01926–e01914. 10.1128/mBio.01926-14 PubMed DOI PMC

Socransky S. S., Haffajee A. D. (2005). Periodontal microbial ecology. Periodontol. 2000 38, 135–187.  10.1111/j.1600-0757.2005.00107.x PubMed DOI

Socransky S. S., Haffajee A. D., Cugini M. A., Smith C., Kent R. L. (1998). Microbial complexes in subgingival plaque. J. Clin. Periodontol. 25, 134–144.  10.1111/j.1600-051X.1998.tb02419.x PubMed DOI

Stoddard S., Smith B., Hein R., Roller B. R. K., Schmidt T. M. (2015). rrnDB: improved tools for interpreting rRNA gene abundance in bacteria and archaea and a new foundation for future development. Nucleic Acids Res. 43 (Database issue), D593–D5938. 10.1093/nar/gku1201 PubMed DOI PMC

Szafranski S. P., Wos-Oxley M. L., Vilchez-Vargas R., Jáuregui R., Plumeier I., Klawonn F., et al. . (2015). High-resolution taxonomic profiling of the subgingival microbiome for biomarker discovery and periodontitis diagnosis. Appl. Environ. Microbiol. 81, 1047–1058.  10.1128/AEM.03534-14 PubMed DOI PMC

Tsai C.-Y., Tang Y., Tan T.-S., Chen K.-H., Liao K.-H., Liou M.-L. (2018). Subgingival microbiota in individuals with severe chronic periodontitis ScienceDirect. J. Microbiol. Immunol. Infect. 51, 226–234.  10.1016/j.jmii.2016.04.007 PubMed DOI

Větrovský T., Baldrian P., Morais D. (2018). SEED 2: A user-friendly platform for amplicon high-throughput sequencing data analyses. in. Bioinformatics 34 (13), 2292–2294.  10.1093/bioinformatics/bty071 PubMed DOI PMC

Větrovský T., Baldrian P. (2013). The variability of the 16S rRNA gene in bacterial genomes and its consequences for bacterial community analyses. PloS One 8, e57923. 10.1371/journal.pone.0057923 PubMed DOI PMC

Wang J., Qi J., Zhao H., He S., Zhang Y., Wei S., et al. . (2013). Metagenomic sequencing reveals microbiota and its functional potential associated with periodontal disease. Sci. Rep. 3 (1), 1843.  10.1038/srep01843 PubMed DOI PMC

Healthy microbiome - a mere idea or a sound concept?

The Oral Microbiome in Periodontal Health