Abstract
Peri-implantitis is an inflammatory disease affecting tissues surrounding dental implants, with microbial biofilms recognized as the primary etiological factor. However, most previous studies analyzed samples from peri-implant pockets, and research on biofilms directly attached to explanted implant surfaces remains limited. This study compared the microbial composition and functional characteristics of biofilms from explanted implant surfaces in peri-implantitis cases with subgingival plaque from healthy controls. A total of 41 samples (peri-implantitis n=19, healthy controls n=22) were obtained from the Apple Tree Oral Biobank. The V3-V4 region of 16S rRNA gene was sequenced using Illumina MiSeq, ASVs were generated using DADA2, and taxonomic assignment was performed using SILVA database (v138.1). Alpha and beta diversity analyses were conducted, and functional potential was predicted using PICRUSt2. The peri-implantitis group showed significantly higher Simpson index (p=0.0086) and phylogenetic diversity (p<0.0001), with distinct clustering separation between groups. Beyond well-known periodontal pathogens (Porphyromonas gingivalis, Tannerella forsythia, Treponema denticola, Filifactor alocis), the peri-implantitis group exhibited significant increases in sulfate-reducing bacteria (Desulfobulbus, Desulfovibrio) and emerging pathogens ([Eubacterium] nodatum group, [Eubacterium] saphenum group, Phocaeicola abscessus, Pseudoramibacter alactolyticus, Pyramidobacter). Health-associated bacteria (Corynebacterium, Neisseria, Capnocytophaga, Lautropia) were decreased. Functional analysis revealed enrichment in LPS biosynthesis, sulfur metabolism, iron acquisition, and amino acid degradation pathways, while carbohydrate metabolism was decreased. This study demonstrates that diverse emerging pathogens, including sulfate-reducing bacteria, are associated with peri-implantitis biofilms in explanted implant surface biofilms, contributing to expanded understanding of peri-implantitis etiology and development of candidate biomarkers.