Project description:The oral mucosa is a frontline for microbial exposure and juxtaposes several unique tissues and mechanical structures. Based on parabiotic surgery of mice receiving systemic viral infections or co-housing with microbially diverse pet shop mice, we report that the oral mucosa harbors CD8+ CD103+ resident memory T cells (TRM), which locally survey tissues without recirculating. Oral antigen reencounter during the effector phase of immune responses potentiated TRM establishment within tongue, gums, palate, and cheek. Upon reactivation, oral TRM triggered changes in somatosensory and innate immune gene expression. We developed in vivo methods for depleting CD103+ TRM while sparing CD103neg TRM and recirculating cells. This revealed that CD103+ TRM were responsible for inducing local gene expression changes. Oral TRM putatively protected against local viral infection. This study provides methods for generating, assessing, and in vivo depleting oral TRM, documents their distribution throughout the oral mucosa, and provides evidence that TRM confer protection and trigger responses in oral physiology and innate immunity.
Project description:Identification of genes that are differentially regulated in fibroblasts derived from dysplastic oral mucosa and oral squamous cell carcinoma compared to fibroblasts derived from normal oral mucosa. Affymetrix microarrays were used to define differential gene expression.
Project description:Identification of genes that are differentially regulated in fibroblasts derived from dysplastic oral mucosa and oral squamous cell carcinoma compared to fibroblasts derived from normal oral mucosa. Affymetrix microarrays were used to define differential gene expression. Populations of fibroblasts were isolated from human normal oral mucosa, oral dysplasia and oral squamous cell carcinoma, maintained in 3D collagen I biomatrices, RNA extracted and processed for Affymetrix arrays. Fibroblasts maintained as monolayers were also included as comparators.
Project description:Injuries of the vocal folds frequently heal with scar formation, which can have lifelong detrimental impact on voice quality. Current treatments to prevent or resolve scars of the vocal fold mucosa are highly unsatisfactory. In contrast, the adjacent oral mucosa is mostly resistant to scarring. These differences in healing tendency might relate to distinct properties of the fibroblasts populating oral and vocal fold mucosae. We thus established the in vitro cultivation of paired, near-primary vocal fold fibroblasts (VFF) and oral mucosa fibroblasts (OMF) to perform a basic cellular characterization and comparative cellular proteomics. VFF were significantly larger than OMF, proliferated more slowly, and exhibited a sustained TGF-β1-induced elevation of pro-fibrotic interleukin 6. Cluster analysis of the proteomic data revealed distinct protein repertoires specific for VFF and OMF. Further, VFF displayed a broader protein spectrum, particularly a more sophisticated array of factors constituting and modifying the extracellular matrix. Conversely, subsets of OMF-enriched proteins were linked to cellular proliferation, nuclear events, and protection against oxidative stress. Altogether, this study supports the notion that fibroblasts sensitively adapt to the functional peculiarities of their respective anatomical location and presents several molecular targets for further investigation in the context of vocal fold wound healing.
Project description:The purpose of this study was to isolate NCSCs from oral mucosa using the neurosphere technique. Total RNA from human oral mucosa stromal cells and sphere-formig oral mucosa stromal cells was collected and compared at their gene expression level. Samples from 3 patients were analysed.
Project description:This dataset brief is about the descriptive proteomic comparison of human oral mucosa and vocal fold tissues by high-resolution mass spectrometry (CID-MS/MS). The vast majority of voice disorders is associated with changes of the unique but delicate tissue of the human vocal folds, wheras the ability to develop new effective treatment methods is significantly limited by the physical inaccessibility and the extremely rare occasion to gather healthy tissue biopsies. Therefore, oral mucosa reached specific interest for laryngological research, as the tissue harvesting process is less invasive and accompanied with faster healing and less scarring. Proteomic analysis of both tissues will provide a fundamental laryngological resource for the research community. Our study identifies a total of 1575 proteins detected within both tissues that are highly consistent in several crucial biological processes, cellular components, and molecular functions.
Project description:total RNAs were extracted from a canine oral malignant melanoma clinical sample (name as 3) and paired normal oral mucosa (name as 3prime) according to the phenol/guanidium thiocyanate method with DNase â treatment. these total RNA were submitted to Filgen, Inc. to perform microRNA microarray.
Project description:Thiele2013 - Oral mucosa squamous epithelial cells
The model of oral mucosa squamous epithelial cells metabolism is derived from the community-driven global reconstruction of human metabolism (version 2.02, MODEL1109130000
).
This model is described in the article:
A community-driven global reconstruction of human metabolism.
Thiele I, et al
.
Nature Biotechnology
Abstract:
Multiple models of human metabolism have been reconstructed, but each represents only a subset of our knowledge. Here we describe Recon 2, a community-driven,
consensus 'metabolic reconstruction', which is the most comprehensive representation of human metabolism that is applicable to computational modeling. Compared
with its predecessors, the reconstruction has improved topological and functional features, including ~2x more reactions and ~1.7x more unique metabolites. Using
Recon 2 we predicted changes in metabolite biomarkers for 49 inborn errors of metabolism with 77% accuracy when compared to experimental data. Mapping metabolomic
data and drug information onto Recon 2 demonstrates its potential for integrating and analyzing diverse data types. Using protein expression data, we automatically
generated a compendium of 65 cell type-specific models, providing a basis for manual curation or investigation of cell-specific metabolic properties. Recon 2 will
facilitate many future biomedical studies and is freely available at http://humanmetabolism.org/.
This model is hosted on BioModels Database
and identified by: MODEL1310110027
.
To cite BioModels Database, please use: BioModels Database: An enhanced,
curated and annotated resource for published quantitative kinetic models
.
To the extent possible under law, all copyright and related or neighbouring rights to this encoded model have been dedicated to the public domain worldwide. Please refer
to CC0 Public Domain Dedication
for more information.