Homo sapiens
Ontology highlight
ABSTRACT:
OTHER RELATED OMICS DATASETS IN: E-GEOD-12121
PROVIDER: PRJNA113779 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:Transcriptional profiling was utilized to define the biological pathways of gingival epithelial cells modulated by co-culture with the oral commensal S. gordonii and the opportunistic commensal F. nucleatum. We used microarrays to detail the global programme of gene expression underlying infection and identified distinct classes of up- and down-regulated genes during this process. Experiment Overall Design: Gingival epithelial HIGK cells were sham infected (CTRL) and infected with either the oral commensal S. gordonii (Sg) or the opportunistic commensal F. nucleatum (Fn). These samples were hybridized to Affymetrix microarrays. Understanding how host cells have adapted to commensals, and how barrier cells respond to limit their impact, provides a mechanistic biological basis of health in the mixed bacterial-human ecosystem of the oral cavity.
2009-04-28 | E-GEOD-6927 | biostudies-arrayexpress
Project description:Gingival Epithelial Cell Transcriptional Responses to Commensal and Opportunistic Oral Microbial Species.
| PRJNA99353 | ENA
Project description:Transcriptional profiling was utilized to define the biological pathways of gingival epithelial cells modulated by mono- and complex co-culture with oral commensal S. gordonii and pathogenic P. gingivalis. We used microarrays to detail the global programme of gene expression underlying infection and identified distinct classes of up- and down-regulated genes during this process. Experiment Overall Design: Gingival epithelial HIGK cells were sham infected (CTRL) and infected with either the oral commensal S. gordonii (Sg) or the pathogenic P. gingivalis (Pg) as well as co-cultured in mixed cultures of Sg and Pg (Sg+Pg). These samples were hybridized to Affymetrix microarrays. Understanding how host cells have adapted to commensals, and how barrier cells respond to limit their impact, provides a mechanistic biological basis of health in the mixed bacterial-human ecosystem of the oral cavity and provides insight on how the degree of complexity of a microbiome influences this balance.
2009-07-18 | E-GEOD-12121 | biostudies-arrayexpress
Project description:Transcriptional profiling was utilized to define the biological pathways of gingival epithelial cells modulated by co-culture with the oral commensal S. gordonii and the opportunistic commensal F. nucleatum. We used microarrays to detail the global programme of gene expression underlying infection and identified distinct classes of up- and down-regulated genes during this process. Keywords: infection state
2007-06-21 | GSE6927 | GEO
Project description:Transcriptional profiling was utilized to define the biological pathways of gingival epithelial cells modulated by mono- and complex co-culture with oral commensal S. gordonii and pathogenic P. gingivalis. We used microarrays to detail the global programme of gene expression underlying infection and identified distinct classes of up- and down-regulated genes during this process. Keywords: infection state
2009-07-14 | GSE12121 | GEO
Project description:Gingival Epithelial Cell Transcriptional Responses to Pathogenic Oral Microbial Species.
| PRJNA103635 | ENA
Project description:Transcription profiling by array of human gingival epithelial cell responses to a complex microbiome
2014-07-03 | E-GEOD-12121 | ExpressionAtlas
Project description:The opportunistic pathogen A. actinomycetemcomitans (Aa) expereinces fluctuating oxygen levels in its natural habitat, the gingival crevice of the human oral cavity. Since oxygen influences metabolic interactions between Aa and other oral microbes, we sought to characterize oxygen-dependent Aa gene expression.
2014-02-01 | E-MTAB-2213 | biostudies-arrayexpress
Project description:Leber2015 - Mucosal immunity and gut
microbiome interaction during C. difficile infection
This model is described in the article:
Systems Modeling of
Interactions between Mucosal Immunity and the Gut Microbiome
during Clostridium difficile Infection.
Leber A, Viladomiu M, Hontecillas R,
Abedi V, Philipson C, Hoops S, Howard B, Bassaganya-Riera
J.
PLoS ONE 2015; 10(7): e0134849
Abstract:
Clostridium difficile infections are associated with the use
of broad-spectrum antibiotics and result in an exuberant
inflammatory response, leading to nosocomial diarrhea, colitis
and even death. To better understand the dynamics of mucosal
immunity during C. difficile infection from initiation through
expansion to resolution, we built a computational model of the
mucosal immune response to the bacterium. The model was
calibrated using data from a mouse model of C. difficile
infection. The model demonstrates a crucial role of T helper 17
(Th17) effector responses in the colonic lamina propria and
luminal commensal bacteria populations in the clearance of C.
difficile and colonic pathology, whereas regulatory T (Treg)
cells responses are associated with the recovery phase. In
addition, the production of anti-microbial peptides by inflamed
epithelial cells and activated neutrophils in response to C.
difficile infection inhibit the re-growth of beneficial
commensal bacterial species. Computational simulations suggest
that the removal of neutrophil and epithelial cell derived
anti-microbial inhibitions, separately and together, on
commensal bacterial regrowth promote recovery and minimize
colonic inflammatory pathology. Simulation results predict a
decrease in colonic inflammatory markers, such as neutrophilic
influx and Th17 cells in the colonic lamina propria, and length
of infection with accelerated commensal bacteria re-growth
through altered anti-microbial inhibition. Computational
modeling provides novel insights on the therapeutic value of
repopulating the colonic microbiome and inducing regulatory
mucosal immune responses during C. difficile infection. Thus,
modeling mucosal immunity-gut microbiota interactions has the
potential to guide the development of targeted fecal
transplantation therapies in the context of precision medicine
interventions.
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2014-04-08 | BIOMD0000000583 | BioModels
Project description:In this paper, we first report that EC smoking significantly increases the odds of gingival inflammation. Then, we seek to identify and explain the mechanism that underlies the relationship between EC smoking and gingival inflammation via the oral microbiome. We performed mediation analyses to assess if EC smoking affects the oral microbiome, which in turn affects gingival inflammation. For this, we collected saliva and subgingival samples from EC users and non-users and profiled their microbial compositions via 16S rRNA amplicon sequencing. We then performed α-diversity, β-diversity, and taxonomic differential analyses to survey the disparity in microbial composition between EC users and non-users. We found significant increases in α-diversity in EC users and disparities in β-diversity between EC users and non-users.
2022-12-09 | GSE201949 | GEO