Dissecting Mast Cells In Periodontitis At Single-Cell/Bulk Resolution

To explore the heterogeneity of mast cells (MCs) in gingival tissues and uncover the molecular mechanisms by which MCs regulate neutrophil extracellular traps (NETs) through intracellular trapping (MIT), while also elucidating the role of cell interactions within the immune microenvironment in driving disease progression. We harmonized four independent single-cell transcriptomic datasets comprising 40 gingival tissue samples from healthy controls and periodontitis patients, and MCs were annotated based on classic marker genes. Functional subgroups MIT-MCs were identified through subpopulation classification and MIT gene module analysis. Interactions between MIT-MCs and neutrophils were analyzed using cell communication analysis, with co-localization validated by spatial transcriptomics. Confocal microscopy was employed to confirm the MIT-MCs in gingival tissue sections. Additionally, we established a periodontitis prediction model based on MIT-MCs-related genes by machine learning methods. Six MCs subpopulations were identified, with the MIT-MCs subset markedly enriched in periodontitis. This subpopulation exhibited suppressed lipid metabolism and hyperactivated pro-inflammatory pathways, notably type I interferon signaling. Cell-cell communication analysis revealed the interactions between MIT-MCs and neutrophils, corroborated by spatial transcriptomics showing their anatomical co-localization. Confocal microscopy further demonstrated intracellular neutrophil trapping within MIT-MCs, directly visualizing MIT-driven neutrophil engagement. Machine learning identified three MIT-MCs-associated biomarkers, which were validated as robust predictors of periodontitis. The identification of the MIT-MCs subgroup and the confirmation that MCs cooperates with NETs to drive the progression of periodontitis provide new strategies for targeting MCs-mediated immune pathology.