Microbiota in Gingival Crevicular Fluid Before and After Mechanical Debridement With Antimicrobial Photodynamic Therapy in Peri-Implantitis

• DOI: 10.3389/fcimb.2021.777627
• Publication Date: 2022-01-07T09:23:54Z
• Authors: Haiyan Wang; Ye Liu; Wei Li; Wenyue Li; Hongtao Xu; Guangliang Niu; Zuomin Wang
• Keywords: mechanical debridement therapy; 16S ribosomal RNA gene sequencing; Microbiota; Gingival Crevicular Fluid; oral microbiota; Microbiology; Peri-Implantitis; QR1-502; Anti-Bacterial Agents; 3. Good health; 03 medical and health sciences; Cellular and Infection Microbiology; 0302 clinical medicine; photodynamic therapy; Debridement; Photochemotherapy; RNA, Ribosomal, 16S; Humans; peri-implantitis

ObjectivesThis study aims to compare the microbiota of gingival crevicular fluid (GCF) before and after mechanical debridement (MD) with antimicrobial photodynamic therapy (aPDT) and determine the core efficient microbiota in peri-implantitis after treatment.MethodsWe recruited 9 patients (14 implants) treated with MD+aPDT for peri-implantitis at our center from February 1, 2018, to February 1, 2019. GCF was collected using filter paper strip before and after the treatment. The bacterial 16S rRNA was amplified and sequenced using an Illumina MiSeq platform to characterize the GCF. Bioinformatics and statistical analyses were performed using QIIME2 and R.ResultsA total of 4,110,861 high-quality sequences were obtained from GCF samples. Based on the reference database, 1,120 amplicon sequence variants (ASVs) were finally harvested. Principal coordinates analysis indicated significant differences in the bacterial community structure between the 180 days after-treatment group and pre-treatment group. Difference analysis and least discriminant analysis showed that the differences were mainly reflected in non-dominant bacteria between these two groups. The non-dominant genera with significantly different distribution between the 180 days after-treatment group and the pre-treatment group included Lactobacillus, Pedobacter, Bulleidia, Centipeda, Desulfovibrio, Ochrobactrum, Staphylococcus, Microbacterium, Brevundimonas, Desulfobulbus, and Parvimonas. Moreover, a total of 29 predictive functional categories at KEGG level 2 were identified. The significant difference pathways at KEGG level 2 between after-treatment and pre-treatment were concentrated in infectious disease-related pathways.ConclusionsPatients with peri-implantitis have significant changes in the low-abundance bacteria of the GCF before and after MD+aPDT. MD+aPDT may change the composition of GCF microbiota by increasing the abundance of cluster 1 (beneficial) and decreasing that of cluster 4 (harmful), which may decrease metabolic response to infection and thus improve peri-implantitis.