Effects of topical fluoride application on oral microbiota in young children with severe dental caries

Frontiers in Cellular and Infection Microbiology

Cellular and Infection Microbiology

Dan Jiang¹  Zhi Zhou²  Jun Luo²  Ting Cai²  Yueheng Li³  Zhengyan Yang³ 

[1]Chongqing Key Laboratory of Oral Biomedical Engineering of Higher Education, Department of Preventive Dentistry, Chongqing, China

[2]Department of Preventive Dentistry, Stomatological Hospital of Chongqing Medical University, Chongqing, China

[3]Chongqing Key Laboratory of Oral Biomedical Engineering of Higher Education, Department of Preventive Dentistry, Chongqing, China

[4]Department of Preventive Dentistry, Stomatological Hospital of Chongqing Medical University, Chongqing, China

[5]Chongqing Key Laboratory of Oral Biomedical Engineering of Higher Education, Department of Preventive Dentistry, Chongqing, China

[6]Chongqing Key Laboratory of Oral Diseases and Biomedical Sciences, Chongqing, China

关键词: microbial community;    fluoride;    dental caries;    high-throughput sequencing;    saliva;   

DOI  :  10.3389/fcimb.2023.1104343

 received in 2022-11-21, accepted in 2023-02-17,  发布年份 2023

来源: Frontiers

【 摘 要 】

While the effect of fluoride on severe early childhood caries (S-ECC) is clear, knowledge of how it influences the oral microbiota and the consequential effects on oral health is limited. In this cohort study, we investigated the changes introduced in the oral ecosystem before and after using fluoride varnish in 54- to 66-month-old individuals (n=90: 18 children were sampled at 5 different time points). 16S rDNA was amplified from bacterial samples using polymerase chain reaction, and high-throughput sequencing was performed using Illumina MiSeq platforms. Many pronounced microbial changes were related to the effects of fluoride varnishing. The health-associated Bacteroides and Uncultured_bacterium_f_Enterobacteriaceae were enriched in the saliva microbiome following treatment with fluoride varnishing. Co-occurrence network analysis of the dominant genera showed that different groups clearly showed different bacterial correlations. The PICRUSt algorithm was used to predict the function of the microbial communities from saliva samples. The results showed that starch and sucrose metabolism was greater after fluoride use. BugBase was used to determine phenotypes present in microbial community samples. The results showed that Haemophilus and Neisseria (phylum Proteobacteria) was greater before fluoride use. We conclude that the changes in oral microbiology play a role in fluoride prevention of S-ECC.

【 授权许可】

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Copyright © 2023 Yang, Cai, Li, Jiang, Luo and Zhou