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Periodontal microbial complexes associated with specific cell and tissue responses
Author(s) -
Kebschull Moritz,
Papapanou Panos N.
Publication year - 2011
Publication title -
journal of clinical periodontology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.456
H-Index - 151
eISSN - 1600-051X
pISSN - 0303-6979
DOI - 10.1111/j.1600-051x.2010.01668.x
Subject(s) - transcriptome , biology , phenotype , gene , gene expression , computational biology , regulation of gene expression , cell , gene expression profiling , genetics
Kebschull M, Papapanou PN. Periodontal microbial complexes associated with specific cell and tissue responses. J Clin Periodontol 2011; 38 (Suppl. 11): 17–27. doi: 10.1111/j.1600‐051X.2010.01668.x. Abstract Aims: In this review, we summarize data on the association between specific periodontal bacterial profiles and tissue gene/protein expression, generated from cell culture models and in vivo studies. Material and Methods: A PubMed search was conducted to identify publications related to the effects of periodontal microbiota on host cells/tissues. Results and Conclusions: The data indicate the presence of specific host tissue responses to particular microbial complexes, evident by differential regulation of gene or protein expression, ultimately resulting in distinct clinical phenotypes. Transcriptomic analyses showed that periodontal pathogens induce a small, “common core” of differentially regulated genes encoding for an inflammatory response, and a larger variable set of genes that may reflect pathogen‐specific cellular responses. Limitations of available studies include (i) the unclear role of hundreds of subgingival species not yet investigated, (ii) the fact that in vitro studies utilizing single populations of oral cells challenged with mono‐infections of planktonic bacteria may not adequately portray human periodontal diseases and (iii) the cross‐sectional nature of most human studies that makes them inherently incapable of allowing temporal or causal inferences. Longitudinal studies in humans hold the potential to be superior to any model, but need to be adequately powered and controlled.