Single cell analysis of oral mucosa basal layer cells
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA494028 | ENA |
REPOSITORIES: ENA
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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.
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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.
2005-01-01 | MODEL1310110027 | BioModels
Project description:The interplay among different cells in a tissue is essential for maintaining homeostasis. Although, disease states have been traditionally attributed to individual cell types, increasing evidence and new therapeutic options have demonstrated the primary role of multicellular functions to understand health and disease, opening new avenues to understand pathogenesis and develop new treatment strategies. We recently described the cellular composition and dynamics of the human oral mucosa; however, the spatial arrangement of cells is needed to better understand a morphologically complex tissue. Here, we link single-cell RNA sequencing, spatial transcriptomics, and high-resolution multiplex fluorescence in situ hybridisation to characterise human oral mucosa in health and oral chronic inflammatory disease. We define highly specialised epithelial and stromal compartments and describe location-specific immune programs. Furthermore, we discovered fine regional fibroblast states, and spatially mapped a rare pathogenic population localised in a highly immunogenic region, responsible for lymphocyte recruitment through CXCL8 and CXCL10 and with a possible role in pathological angiogenesis through ALOX5AP. Collectively, our study provides a comprehensive reference for the study of oral chronic disease pathogenesis.
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