A Robust Ex-vivo Culture System for Gingival Tissues

Objectives: Current skin and gingival tissue models available for the assessment of drug toxicity and cosmetic testing, including mouthwashes and tooth whitening products, are reconstructed 3D tissue constructs that are fragile and do not fully represent the architecture of the epithelium. Objectives: To develop an ex-vivo gingival model that recapitulates tissues in vivo and is capable of producing quantitative data to monitor cellular responses.
Methods: Mandibles were dissected from male Wistar rats and cut vertically preserving the interaction of the gingival tissues with the underlying periodontium. Samples were exposed to either H₂O₂ gel (6%, 9.5%, 25%), 456nm LED light (25mW, 50mW, 100mW, 200mW) or both for 30 mins. Total RNA from the treated and untreated tissues was extracted using RNeasy Mini Kit and QIAshredder (Qiagen). RNA quantity and purity was determined by 260/280nm absorbance. The relative expression of inflammatory markers (TNFα, IL-1, IL-6, COX-2) and apoptotic markers (BAX, p53) was assessed by qPCR and compared with untreated tissue.
Results: Each experimental group produced a range of total mRNA between 200-600 ng/ul, with nucleic acid purity ~2.0, using 260/280 absorbance. Low intensity LED (25mW, 50mW) did not induce any inflammation response compared to high intensity LED (100mW, 200mW), which triggered an inflammatory response within the gingival tissue due to increased gene expression of TNFα, IL-1, IL-6 and COX-2. H₂O₂ gel application on gingival tissue showed similar increases of inflammatory markers, similar to that shown with high intensity LED. When 100mW light and 25% H₂O₂ gel were combined, expression of IL-6 increased by 10 fold compared to 100mW LED or 25% H₂O₂ gel alone.
Conclusions: We show that our ex vivo gingival culture system can provide reliable and accurate quantitative data, and can be used as a robust alternative to current commercial testing models for epithelial and gingival tissue, routinely utilised for pre-clinical assessment.