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The effect of surface material, roughness and wettability on the adhesion and proliferation of Streptococcus gordonii, Fusobacterium nucleatum and Porphyromonas gingivalis☆

Cited 4 time in Web of Science Cited 5 time in Scopus
Authors

Choi, Sunyoung; Jo, Ye-Hyeon; Luke Yeo, In-Sung; Yoon, Hyung-In; Lee, Jae-Hyun; Han, Jung-Suk

Issue Date
2023-04
Publisher
Association for Dental Sciences of the Republic of China
Citation
Journal of Dental Sciences, Vol.18 No.2, pp.517-525
Abstract
Background/purpose: Dental implants are inevitably exposed to bacteria in oral cavity. Understanding the colonization of bacteria on implant surface is necessary to prevent bacteria-related inflammation surrounding dental implants. The purpose of this study was to investigate the effect of surface properties on biofilm formation on the implant surface. Materials and methods: One early colonizer, Streptococcus gordonii (S. gordonii), and two late colonizers, Fusobacterium nucleatum (F. nucleatum) and Porphyromonas gingivalis (P. gingivalis), were grown on the titanium and zirconia surfaces with two types of surface roughness for 24 and 72 h. Each bacterial biofilm on specimens was quantified using crystal violet assay and observed by scanning electron microscopy. Results: S. gordonii formed more biofilm on the titanium surface than zirconia at the same roughness and more biofilm on the rough surface than smooth one of the same materials at 24 and 72 h of incubation. F. nucleatum adhered on all the surfaces at 24 h and proliferated actively on the surfaces except smooth zirconia at 72 h. P. gingivalis proliferated vigorously on the surfaces at 72 h while it scarcely adhered at 24 h. There was no consistent correlation between contact angle and biofilm formation of the three bacteria. Conclusion: The three bacteria proliferated most on the rough titanium surface and least on the smooth zirconia surface. In addition, the proliferation was affected by the bacterial species as well as the surface properties.
ISSN
1991-7902
URI
https://hdl.handle.net/10371/191754
DOI
https://doi.org/10.1016/j.jds.2022.09.010
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  • School of Dentistry
  • Department of Dentistry
Research Area Big Data Analysis, Dental Implant, Digital Dental Technology

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