Periodontal inflammation: Integrating genes and dysbiosis

Shaoping Zhang, Ning Yu, Roger M. Arce

Research output: Contribution to journalReview article

1 Citation (Scopus)

Abstract

Biofilm bacteria co-evolve and reach a symbiosis with the host on the gingival surface. The disruption of the homeostatic relationship between plaque bacteria and the host can initiate and promote periodontal disease progression. Recent advances in sequencing technologies allow researchers to profile disease-associated microbial communities and quantify microbial metabolic activities and host transcriptional responses. In addition to confirming the findings from previous studies, new putative pathogens and novel genes that have not previously been associated with periodontitis, emerge. For example, multiple studies have reported that Synergistetes bacteria are associated with periodontitis. Genes involved in epithelial barrier defense were downregulated in periodontitis, while excessive expression of interleukin-17 was associated with a hyperinflammatory response in periodontitis and with a unique microbial community. Bioinformatics-enabled gene ontology pathway analyses provide a panoramic view of the bacterial and host activities as they shift from periodontal health to disease. Additionally, host innate factors, such as genetic variants identified by either a candidate-gene approach or genome-wide association analyses, have an impact on subgingival bacterial colonization. Transgenic mice carrying candidate genetic variants, or with the deletion of candidate genes mimicking the deleterious loss-of-function variant effect, provide experimental evidence validating the biologic relevance of the novel markers associated with the microbial phenotype identified through a statistical approach. Further refinement in bioinformatics, data management approaches, or statistical tools, are required to gain insight into host-microbe interactions by harmonizing the multidimensional “big” data at the genomic, transcriptional, and proteomic levels.

Original languageEnglish (US)
Pages (from-to)129-142
Number of pages14
JournalPeriodontology 2000
Volume82
Issue number1
DOIs
StatePublished - Feb 1 2020

Fingerprint

Dysbiosis
Periodontitis
Inflammation
Computational Biology
Bacteria
Genes
Gene Ontology
Symbiosis
Interleukin-17
Genome-Wide Association Study
Gene Deletion
Periodontal Diseases
Biofilms
Proteomics
Transgenic Mice
Disease Progression
Down-Regulation
Research Personnel
Technology
Phenotype

Keywords

  • genome-wide association study (GWAS)
  • inflammation
  • microbiome
  • periodontitis
  • transcriptome

ASJC Scopus subject areas

  • Periodontics

Cite this

Periodontal inflammation : Integrating genes and dysbiosis. / Zhang, Shaoping; Yu, Ning; Arce, Roger M.

In: Periodontology 2000, Vol. 82, No. 1, 01.02.2020, p. 129-142.

Research output: Contribution to journalReview article

Zhang, Shaoping ; Yu, Ning ; Arce, Roger M. / Periodontal inflammation : Integrating genes and dysbiosis. In: Periodontology 2000. 2020 ; Vol. 82, No. 1. pp. 129-142.
@article{974033814c284f408b56c1537bd81e1d,
title = "Periodontal inflammation: Integrating genes and dysbiosis",
abstract = "Biofilm bacteria co-evolve and reach a symbiosis with the host on the gingival surface. The disruption of the homeostatic relationship between plaque bacteria and the host can initiate and promote periodontal disease progression. Recent advances in sequencing technologies allow researchers to profile disease-associated microbial communities and quantify microbial metabolic activities and host transcriptional responses. In addition to confirming the findings from previous studies, new putative pathogens and novel genes that have not previously been associated with periodontitis, emerge. For example, multiple studies have reported that Synergistetes bacteria are associated with periodontitis. Genes involved in epithelial barrier defense were downregulated in periodontitis, while excessive expression of interleukin-17 was associated with a hyperinflammatory response in periodontitis and with a unique microbial community. Bioinformatics-enabled gene ontology pathway analyses provide a panoramic view of the bacterial and host activities as they shift from periodontal health to disease. Additionally, host innate factors, such as genetic variants identified by either a candidate-gene approach or genome-wide association analyses, have an impact on subgingival bacterial colonization. Transgenic mice carrying candidate genetic variants, or with the deletion of candidate genes mimicking the deleterious loss-of-function variant effect, provide experimental evidence validating the biologic relevance of the novel markers associated with the microbial phenotype identified through a statistical approach. Further refinement in bioinformatics, data management approaches, or statistical tools, are required to gain insight into host-microbe interactions by harmonizing the multidimensional “big” data at the genomic, transcriptional, and proteomic levels.",
keywords = "genome-wide association study (GWAS), inflammation, microbiome, periodontitis, transcriptome",
author = "Shaoping Zhang and Ning Yu and Arce, {Roger M.}",
year = "2020",
month = "2",
day = "1",
doi = "10.1111/prd.12267",
language = "English (US)",
volume = "82",
pages = "129--142",
journal = "Periodontology 2000",
issn = "0906-6713",
publisher = "Blackwell Munksgaard",
number = "1",

}

TY - JOUR

T1 - Periodontal inflammation

T2 - Integrating genes and dysbiosis

AU - Zhang, Shaoping

AU - Yu, Ning

AU - Arce, Roger M.

PY - 2020/2/1

Y1 - 2020/2/1

N2 - Biofilm bacteria co-evolve and reach a symbiosis with the host on the gingival surface. The disruption of the homeostatic relationship between plaque bacteria and the host can initiate and promote periodontal disease progression. Recent advances in sequencing technologies allow researchers to profile disease-associated microbial communities and quantify microbial metabolic activities and host transcriptional responses. In addition to confirming the findings from previous studies, new putative pathogens and novel genes that have not previously been associated with periodontitis, emerge. For example, multiple studies have reported that Synergistetes bacteria are associated with periodontitis. Genes involved in epithelial barrier defense were downregulated in periodontitis, while excessive expression of interleukin-17 was associated with a hyperinflammatory response in periodontitis and with a unique microbial community. Bioinformatics-enabled gene ontology pathway analyses provide a panoramic view of the bacterial and host activities as they shift from periodontal health to disease. Additionally, host innate factors, such as genetic variants identified by either a candidate-gene approach or genome-wide association analyses, have an impact on subgingival bacterial colonization. Transgenic mice carrying candidate genetic variants, or with the deletion of candidate genes mimicking the deleterious loss-of-function variant effect, provide experimental evidence validating the biologic relevance of the novel markers associated with the microbial phenotype identified through a statistical approach. Further refinement in bioinformatics, data management approaches, or statistical tools, are required to gain insight into host-microbe interactions by harmonizing the multidimensional “big” data at the genomic, transcriptional, and proteomic levels.

AB - Biofilm bacteria co-evolve and reach a symbiosis with the host on the gingival surface. The disruption of the homeostatic relationship between plaque bacteria and the host can initiate and promote periodontal disease progression. Recent advances in sequencing technologies allow researchers to profile disease-associated microbial communities and quantify microbial metabolic activities and host transcriptional responses. In addition to confirming the findings from previous studies, new putative pathogens and novel genes that have not previously been associated with periodontitis, emerge. For example, multiple studies have reported that Synergistetes bacteria are associated with periodontitis. Genes involved in epithelial barrier defense were downregulated in periodontitis, while excessive expression of interleukin-17 was associated with a hyperinflammatory response in periodontitis and with a unique microbial community. Bioinformatics-enabled gene ontology pathway analyses provide a panoramic view of the bacterial and host activities as they shift from periodontal health to disease. Additionally, host innate factors, such as genetic variants identified by either a candidate-gene approach or genome-wide association analyses, have an impact on subgingival bacterial colonization. Transgenic mice carrying candidate genetic variants, or with the deletion of candidate genes mimicking the deleterious loss-of-function variant effect, provide experimental evidence validating the biologic relevance of the novel markers associated with the microbial phenotype identified through a statistical approach. Further refinement in bioinformatics, data management approaches, or statistical tools, are required to gain insight into host-microbe interactions by harmonizing the multidimensional “big” data at the genomic, transcriptional, and proteomic levels.

KW - genome-wide association study (GWAS)

KW - inflammation

KW - microbiome

KW - periodontitis

KW - transcriptome

UR - http://www.scopus.com/inward/record.url?scp=85076595866&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85076595866&partnerID=8YFLogxK

U2 - 10.1111/prd.12267

DO - 10.1111/prd.12267

M3 - Review article

C2 - 31850627

AN - SCOPUS:85076595866

VL - 82

SP - 129

EP - 142

JO - Periodontology 2000

JF - Periodontology 2000

SN - 0906-6713

IS - 1

ER -