Related Experiment Video
Updated: Feb 12, 2026
Tick Microbiome Characterization by Next-Generation 16S rRNA Amplicon Sequencing
Published on: August 25, 2018
Comparison of microbiome profiles across sample types in patients with peri-implantitis using 16S rRNA sequencing
Da-Mi Kim1, Inpyo Hong1, Joo-Yeon Lee1
1Department of Periodontology, Research Institute for Periodontal Regeneration, Yonsei University College of Dentistry, Seoul, Korea.
Purpose:
Numerous studies have applied microbial analyses to peri-implantitis, including analyses of samples collected from various sites. While characteristics of the peri-implantitis microbiome have been identified, differences in sampling methods between studies have not been considered. The present study aimed to (1) characterize microbial similarities among saliva, gingival crevicular fluid (GCF), subgingival plaque (SGP) and inflammatory connective tissue (ICT) within the same participant with peri-implantitis; and (2) determine the microbial profiles of peri-implantitis sites.
Methods:
Saliva, GCF, and SGP samples were collected from 18 patients undergoing peri-implantitis surgery, and ICT samples were obtained after flap elevation. The collected samples were analyzed using 16S rRNA sequencing.
Results:
The sampling sites showed a mean bone loss of 6.9 mm and a maximum probing depth (PD) of 8.3 mm. Alpha diversity did not differ significantly among ICT, GCF, and SGP, whereas saliva exhibited a distinct diversity profile. Additionally, beta diversity analyses indicated that the microbial community structure differed significantly between saliva and the other samples. In taxonomic analyses, the microbial profiles of ICT, GCF, and SGP were clearly distinguishable from those of saliva. Saliva had lower proportions of Bacteroidetes and higher proportions of Proteobacteria and Actinobacteria species, especially at sites with deep PD. Pearson correlation analyses revealed strong correlations between ICT and both GCF and SGP, but not between ICT and saliva. Pathogenic species such as Porphyromonas gingivalis, Tannerella forsythia, Treponema denticola, Campylobacter rectus, Filifactor alocis, and Porphyromonas endodontalis were more abundant in ICT than in saliva.
Conclusions:
ICT, GCF, and SGP shared similar microbial profiles, whereas saliva exhibited a significantly different profile. ICT, GCF, and SGP had higher abundances of peri-implant pathogenic species, whereas saliva tended to have lower abundances; this difference was especially pronounced in deep pockets.
Related Concept Videos
01:14Drug Dissolution: Requirements and Profile Comparison
01:18Sampling Methods: Sample Types
Solid samples include a variety of substances, such as sediments from water bodies, soil, metals, and biological tissues. Two standard methods for extracting sediments from water bodies are grab sampling and piston coring. Grab sampling involves using a device to collect a discrete sediment sample from the bottom of a water body with minimal disturbance. Grab samples do not always represent the entire area due to...
01:23Types of RNA
Three main types of RNA are involved in protein synthesis: messenger RNA (mRNA), transfer RNA (tRNA), and ribosomal RNA (rRNA). These RNAs perform diverse functions and can be broadly classified as protein-coding or non-coding RNA. Non-coding RNAs play important roles in the regulation of gene expression in response to developmental and environmental changes. Non-coding RNAs in prokaryotes can be manipulated to develop more effective antibacterial drugs for human or animal use.
RNA...
02:57The Sense of Self: Reflected Self-Appraisal and Social Comparison
01:13Multiple Comparison Tests
It would be easy to compare two samples using a significance alpha level of 0.05. In other words, there is only one sample pair to be compared. However, it would be difficult to identify a significantly different sample if the number...
02:02Cis-regulatory Sequences