Profiling Gingival Inflammation in a 3D Oral Tissue Model Reveals Early Features of Disease Progression
Gingival health depends on a balanced interplay among the gingival epithelium, immune system, and oral microbiome. Disruption of this equilibrium through sustained biofilm accumulation and host inflammatory responses leads to gingivitis, a highly prevalent yet reversible condition which if left untreated could progress into more severe and irreversible condition called periodontitis. The early onset of gingivitis remains poorly defined due to subtle clinical presentation and pronounced interindividual variability. Current diagnostic approaches rely largely on clinical assessment and endpoint biomarkers, limiting insight into the early host-microbiome interactions that drive disease initiation. Here, we employ a previously validated, physiologically relevant oral tissue model (OTM) to longitudinally investigate epithelial-microbiome interactions following inoculation with patient-derived dysbiotic microbiomes from early-stage gingivitis. The OTM maintained host tissue integrity and microbial viability over a seven-day period, preserving epithelial barrier function, dynamic inflammatory responses, and disease-associated microbial signatures. Notably, we establish, for the first time in an in vitro platform, clinical calibration against gingival crevicular fluid (GCF), demonstrating that OTM responses recapitulate inoculum-dependent inflammatory signatures, increased microbial dissimilarity under dysbiotic conditions, and coordinated host-microbiome metabolic interactions. While pro-inflammatory responses were most pronounced at early time points, subsequent modulation toward anti-inflammatory states highlights the temporal complexity of host responses and suggests that longer culture durations may further resolve disease trajectories. Collectively, these findings validate the OTM as a robust, physiologically relevant platform that captures key features of periodontal health and inflammation. By integrating host viability, microbial ecology, and clinical benchmarking, this system enables mechanistic interrogation of early disease-driving processes and provides a translational framework for advancing predictive diagnostics and preventive therapeutic strategies in periodontal disease.